Comparative mapping reveals quantitative trait loci that affect spawning time in coho salmon (Oncorhynchus kisutch

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Cristian Araneda

2012-01-01

Full Text Available Spawning time in salmonids is a sex-limited quantitative trait that can be modified by selection. In rainbow trout (Oncorhynchus mykiss, various quantitative trait loci (QTL that affect the expression of this trait have been discovered. In this study, we describe four microsatellite loci associated with two possible spawning time QTL regions in coho salmon (Oncorhynchus kisutch. The four loci were identified in females from two populations (early and late spawners produced by divergent selection from the same base population. Three of the loci (OmyFGT34TUF, One2ASC and One19ASC that were strongly associated with spawning time in coho salmon (p < 0.0002 were previously associated with QTL for the same trait in rainbow trout; a fourth loci (Oki10 with a suggestive association (p = 0.00035 mapped 10 cM from locus OmyFGT34TUF in rainbow trout. The changes in allelic frequency observed after three generations of selection were greater than expected because of genetic drift. This work shows that comparing information from closely-related species is a valid strategy for identifying QTLs for marker-assisted selection in species whose genomes are poorly characterized or lack a saturated genetic map.

Nonparametric functional mapping of quantitative trait loci.

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Yang, Jie; Wu, Rongling; Casella, George

2009-03-01

Functional mapping is a useful tool for mapping quantitative trait loci (QTL) that control dynamic traits. It incorporates mathematical aspects of biological processes into the mixture model-based likelihood setting for QTL mapping, thus increasing the power of QTL detection and the precision of parameter estimation. However, in many situations there is no obvious functional form and, in such cases, this strategy will not be optimal. Here we propose to use nonparametric function estimation, typically implemented with B-splines, to estimate the underlying functional form of phenotypic trajectories, and then construct a nonparametric test to find evidence of existing QTL. Using the representation of a nonparametric regression as a mixed model, the final test statistic is a likelihood ratio test. We consider two types of genetic maps: dense maps and general maps, and the power of nonparametric functional mapping is investigated through simulation studies and demonstrated by examples.

Quantitative trait loci associated with the tocochromanol (vitamin E) pathway in barley

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In this study, the Genome-Wide Association Studies approach was used to detect Quantitative Trait Loci associated with tocochromanol concentrations using a panel of 1,466 barley accessions. All major tocochromanol types- alpha-, beta-, delta-, gamma-tocopherol and tocotrienol- were assayed. We found...

Quantitative trait loci for yield and morphological traits in maize under drought stress

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Nikolić Ana

2011-01-01

Full Text Available Drought is one of the most important factors contributing to crop yield loss. In order to develop maize varieties with drought tolerance, it is necessary to explore the genetic basis. Mapping quantitative trait loci (QTL that control the yield and associate agronomic traits is one way of understanding drought genetics. QTLs associated with grain yield (GY, leaf width (LW3, LW4 plant height (PH, ear height (EH, leaf number (NL, tassel branch number (TBN and tassel length (TL were studied with composite interval mapping. A total of 43 QTLs were detected, distributed on all chromosomes, except chromosome 9. Phenotypic variability determined for the identified QTLs for all the traits was in the range from 20.99 to 87.24%. Mapping analysis identified genomic regions associated with two traits in a manner that was consistent with phenotypic correlation among traits, supporting either pleiotropy or tight linkage among QTLs.

High Resolution of Quantitative Traits Into Multiple Loci via Interval Mapping

OpenAIRE

Jansen, Ritsert C.; Stam, Piet

1994-01-01

A very general method is described for multiple linear regression of a quantitative phenotype on genotype [putative quantitative trait loci (QTLs) and markers] in segregating generations obtained from line crosses. The method exploits two features, (a) the use of additional parental and F1 data, which fixes the joint QTL effects and the environmental error, and (b) the use of markers as cofactors, which reduces the genetic background noise. As a result, a significant increase of QTL detection...

A Simple Linear Regression Method for Quantitative Trait Loci Linkage Analysis With Censored Observations

OpenAIRE

Anderson, Carl A.; McRae, Allan F.; Visscher, Peter M.

2006-01-01

Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using...

Estimation of genetic parameters and detection of quantitative trait loci for metabolites in Danish Holstein milk

DEFF Research Database (Denmark)

Buitenhuis, Albert Johannes; Sundekilde, Ulrik; Poulsen, Nina Aagaard

2013-01-01

Small components and metabolites in milk are significant for the utilization of milk, not only in dairy food production but also as disease predictors in dairy cattle. This study focused on estimation of genetic parameters and detection of quantitative trait loci for metabolites in bovine milk. F...... for lactic acid to >0.8 for orotic acid and β-hydroxybutyrate. A single SNP association analysis revealed 7 genome-wide significant quantitative trait loci [malonate: Bos taurus autosome (BTA)2 and BTA7; galactose-1-phosphate: BTA2; cis-aconitate: BTA11; urea: BTA12; carnitine: BTA25...

Quantitative trait loci (QTL mapping for growth traits on bovine chromosome 14

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Marcelo Miyata

2007-03-01

Full Text Available Quantitative trait loci (QTL mapping in livestock allows the identification of genes that determine the genetic variation affecting traits of economic interest. We analyzed the birth weight and weight at 60 days QTL segregating on bovine chromosome BTA14 in a F2 resource population using genotypes produced from seven microsatellite markers. Phenotypes were derived from 346 F2 progeny produced from crossing Bos indicus Gyr x Holstein Bos taurus F1 parents. Interval analysis to detect QTL for birth weight revealed the presence of a QTL (p < 0.05 at 1 centimorgan (cM from the centromere with an additive effect of 1.210 ± 0.438 kg. Interval analysis for weight at 60 days revealed the presence of a QTL (p < 0.05 at 0 cM from the centromere with an additive effect of 2.122 ± 0.735 kg. The region to which the QTL were assigned is described in the literature as responsible for some growth traits, milk yield, milk composition, fat deposition and has also been related to reproductive traits such as daughter pregnancy rate and ovulation rate. The effects of the QTL described on other traits were not investigated.

Genome Scan Detects Quantitative Trait Loci Affecting Female Fertility Traits in Danish and Swedish Holstein Cattle

DEFF Research Database (Denmark)

Höglund, Johanna Karolina; Guldbrandtsen, B; Su, G

2009-01-01

Data from the joint Nordic breeding value prediction for Danish and Swedish Holstein grandsire families were used to locate quantitative trait loci (QTL) for female fertility traits in Danish and Swedish Holstein cattle. Up to 36 Holstein grandsires with over 2,000 sons were genotyped for 416 mic...... for QTL segregating on Bos taurus chromosome (BTA)1, BTA7, BTA10, and BTA26. On each of these chromosomes, several QTL were detected affecting more than one of the fertility traits investigated in this study. Evidence for segregation of additional QTL on BTA2, BTA9, and BTA24 was found...

Joint analysis of quantitative trait loci and majoreffect causative mutations affecting meat quality and carcass composition traits in pigs

OpenAIRE

Cherel, Pierre; Pires, José; Glénisson, Jérôme; Milan, Denis; Iannuccelli, Nathalie; Herault, Frédéric; Damon, Marie; Le Roy, Pascale

2011-01-01

Abstract Background Detection of quantitative trait loci (QTLs) affecting meat quality traits in pigs is crucial for the design of efficient marker-assisted selection programs and to initiate efforts toward the identification of underlying polymorphisms. The RYR1 and PRKAG3 causative mutations, originally identified from major effects on meat characteristics, can be used both as controls for an overall QTL detection strategy for diversely affected traits and as a scale for detected QTL effect...

Quantitative trait loci for udder conformation and other udder traits in Finnish Ayrshire cattle

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N.F. SCHULMAN

2008-12-01

Full Text Available Udder traits are important due to their correlation with clinical mastitis which causes major economic losses to the dairy farms. Chromosomal areas associated with udder conformation traits, milking speed and leakage could be used in breeding programs to improve both udder traits and mastitis resistance. Quantitative trait loci (QTL mapping for udder traits was carried out on bovine chromosomes (BTA 9, 11, 14, 18, 20, 23, and 29, where earlier studies have indicated QTL for mastitis. A granddaughter design with 12 Ayrshire sire families and 360 sons was used. The sires and sons were typed for 35 markers. The traits analysed were udder depth, fore udder attachment, central ligament, distance from udder to floor, body stature, fore teat length, udder balance, rear udder height, milking speed, and leakage. Associations between markers and traits were analysed with multiple marker regression. Five genome-wise significant QTL were detected: stature on BTA14 and 23, udder balance on BTA23, rear udder height on BTA11, and central ligament on BTA23. On BTA11 and 14 the suggested QTL positions for udder traits are at the same position as previously detected QTL for mastitis and somatic cell count.;

CBCL Pediatric Bipolar Disorder Profile and ADHD: Comorbidity and Quantitative Trait Loci Analysis

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McGough, James J.; Loo, Sandra K.; McCracken, James T.; Dang, Jeffery; Clark, Shaunna; Nelson, Stanley F.; Smalley, Susan L.

2008-01-01

The pediatric bipolar disorder profile of the Child Behavior checklist is used to differentiate patterns of comorbidity and to search for quantitative trait loci in multiple affected ADHD sibling pairs. The CBCL-PBD profiling identified 8 percent of individuals with severe psychopathology and increased rates of oppositional defiant, conduct and…

Identification of quantitative trait loci influencing wood specific gravity in an outbred pedigree of loblolly pine

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A. Groover; M. Devey; T. Fiddler; J. Lee; R. Megraw; T. Mitchel-Olds; B. Sherman; S. Vujcic; C. Williams; D. Neale

1994-01-01

We report the identification of quantitative trait loci (QTL) influencing wood specific gravity (WSG) in an outbred pedigree of loblolly pine (Pinus taeda L.) . QTL mapping in an outcrossing species is complicated by the presence of multiple alleles (>2) at QTL and marker loci. Multiple alleles at QTL allow the examination of interaction among...

Quantitative Trait Loci Mapping Problem: An Extinction-Based Multi-Objective Evolutionary Algorithm Approach

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Nicholas S. Flann

2013-09-01

Full Text Available The Quantitative Trait Loci (QTL mapping problem aims to identify regions in the genome that are linked to phenotypic features of the developed organism that vary in degree. It is a principle step in determining targets for further genetic analysis and is key in decoding the role of specific genes that control quantitative traits within species. Applications include identifying genetic causes of disease, optimization of cross-breeding for desired traits and understanding trait diversity in populations. In this paper a new multi-objective evolutionary algorithm (MOEA method is introduced and is shown to increase the accuracy of QTL mapping identification for both independent and epistatic loci interactions. The MOEA method optimizes over the space of possible partial least squares (PLS regression QTL models and considers the conflicting objectives of model simplicity versus model accuracy. By optimizing for minimal model complexity, MOEA has the advantage of solving the over-fitting problem of conventional PLS models. The effectiveness of the method is confirmed by comparing the new method with Bayesian Interval Mapping approaches over a series of test cases where the optimal solutions are known. This approach can be applied to many problems that arise in analysis of genomic data sets where the number of features far exceeds the number of observations and where features can be highly correlated.

Fine mapping of quantitative trait loci for mastitis resistance on bovine chromosome 11

DEFF Research Database (Denmark)

Schulman, N F; Sahana, G; Iso-Touru, T

2009-01-01

Quantitative trait loci (QTL) affecting clinical mastitis (CM) and somatic cell score (SCS) were mapped on bovine chromosome 11. The mapping population consisted of 14 grandsire families belonging to three Nordic red cattle breeds: Finnish Ayrshire (FA), Swedish Red and White (SRB) and Danish Red......, each affecting one trait; or one QTL affecting a single trait. A QTL affecting CM was fine-mapped. In FA, a haplotype having a strong association with a high negative effect on mastitis resistance was identified. The mapping precision of an earlier detected SCS-QTL was not improved by the LDLA analysis...

Detection of Quantitative Trait Loci Affecting Fat Deposition Traits in Pigs

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B. H. Choi

2012-11-01

Full Text Available Quantitative trait loci (QTL associated with fat deposition traits in pigs are important gene positions in a chromosome that influence meat quality of pork. For QTL study, a three generation resource population was constructed from a cross between Korean native boars and Landrace sows. A total of 240 F2 animals from intercross of F1 were produced. 80 microsatellite markers covering chromosomes 1 to 10 were selected to genotype the resource population. Intervals between adjacent markers were approximately 19 cM. Linkage analysis was performed using CRIMAP software version 2.4 with a FIXED option to obtain the map distances. For QTL analysis, the public web-based software, QTL express (http://www.qtl.cap.ed.ac.uk was used. Two significant and two suggestive QTL were identified on SSC 6, 7, and 8 as affecting body fat and IMF traits. For QTL affecting IMF, the most significant association was detected between marker sw71 and sw1881 on SSC 6, and a suggestive QTL was identified between sw268 and sw205 on SSC8. These QTL accounted for 26.58% and 12.31% of the phenotypic variance, respectively. A significant QTL affecting IMF was detected at position 105 cM between markers sw71 and sw1881 on SSC 6.

Meta-Analysis of Results from Quantitative Trait Loci Mapping Studies on Pig Chromosome 4

NARCIS (Netherlands)

Moraes Silva, De K.M.; Bastiaansen, J.W.M.; Knol, E.F.; Merks, J.W.M.; Lopes, P.S.; Guimaraes, R.M.; Arendonk, van J.A.M.

2011-01-01

Meta-analysis of results from multiple studies could lead to more precise quantitative trait loci (QTL) position estimates compared to the individual experiments. As the raw data from many different studies are not readily available, the use of results from published articles may be helpful. In this

Genetic and Molecular Mechanisms of Quantitative Trait Loci Controlling Maize Inflorescence Architecture.

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Li, Manfei; Zhong, Wanshun; Yang, Fang; Zhang, Zuxin

2018-03-01

The establishment of inflorescence architecture is critical for the reproduction of flowering plant species. The maize plant generates two types of inflorescences, the tassel and the ear, and their architectures have a large effect on grain yield and yield-related traits that are genetically controlled by quantitative trait loci (QTLs). Since ear and tassel architecture are deeply affected by the activity of inflorescence meristems, key QTLs and genes regulating meristematic activity have important impacts on inflorescence development and show great potential for optimizing grain yield. Isolation of yield trait-related QTLs is challenging, but these QTLs have direct application in maize breeding. Additionally, characterization and functional dissection of QTLs can provide genetic and molecular knowledge of quantitative variation in inflorescence architecture. In this review, we summarize currently identified QTLs responsible for the establishment of ear and tassel architecture and discuss the potential genetic control of four ear-related and four tassel-related traits. In recent years, several inflorescence architecture-related QTLs have been characterized at the gene level. We review the mechanisms of these characterized QTLs.

Mapping quantitative trait loci in a selectively genotyped outbred population using a mixture model approach

NARCIS (Netherlands)

Johnson, David L.; Jansen, Ritsert C.; Arendonk, Johan A.M. van

1999-01-01

A mixture model approach is employed for the mapping of quantitative trait loci (QTL) for the situation where individuals, in an outbred population, are selectively genotyped. Maximum likelihood estimation of model parameters is obtained from an Expectation-Maximization (EM) algorithm facilitated by

Nonparametric modeling of longitudinal covariance structure in functional mapping of quantitative trait loci.

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Yap, John Stephen; Fan, Jianqing; Wu, Rongling

2009-12-01

Estimation of the covariance structure of longitudinal processes is a fundamental prerequisite for the practical deployment of functional mapping designed to study the genetic regulation and network of quantitative variation in dynamic complex traits. We present a nonparametric approach for estimating the covariance structure of a quantitative trait measured repeatedly at a series of time points. Specifically, we adopt Huang et al.'s (2006, Biometrika 93, 85-98) approach of invoking the modified Cholesky decomposition and converting the problem into modeling a sequence of regressions of responses. A regularized covariance estimator is obtained using a normal penalized likelihood with an L(2) penalty. This approach, embedded within a mixture likelihood framework, leads to enhanced accuracy, precision, and flexibility of functional mapping while preserving its biological relevance. Simulation studies are performed to reveal the statistical properties and advantages of the proposed method. A real example from a mouse genome project is analyzed to illustrate the utilization of the methodology. The new method will provide a useful tool for genome-wide scanning for the existence and distribution of quantitative trait loci underlying a dynamic trait important to agriculture, biology, and health sciences.

Quantitative Trait Loci Analysis of Allelopathy in Rice

DEFF Research Database (Denmark)

Jensen, L B; Courtois, B; Olofsdotter, M

2008-01-01

The allelopathic potential of rice (Oryza sativa L.) against Echinochloa crus-galli (L.) Beauv. was investigated under both laboratory and greenhouse conditions. A population of 150 recombinant inbred lines (RILs) was derived through single-seed descent from a cross between the indica cultivar AC...... the population phenotype was normally distributed. Two quantitative trait loci (QTLs) were located on chromosomes 4 and 7, explaining 20% of the phenotypic variation. A second relay seeding experiment was set up, this time including charcoal in the perlite. This screening showed that the allelopathic rice...... varieties did not have any effect on the weed species when grown with charcoal, the charcoal reversing the effect of any potential allelochemicals exuded from the rice roots. The second phenotypic experiment was conducted under greenhouse conditions in pots. Thirteen QTLs were detected for four different...

Quantile-based permutation thresholds for quantitative trait loci hotspots.

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Neto, Elias Chaibub; Keller, Mark P; Broman, Andrew F; Attie, Alan D; Jansen, Ritsert C; Broman, Karl W; Yandell, Brian S

2012-08-01

Quantitative trait loci (QTL) hotspots (genomic locations affecting many traits) are a common feature in genetical genomics studies and are biologically interesting since they may harbor critical regulators. Therefore, statistical procedures to assess the significance of hotspots are of key importance. One approach, randomly allocating observed QTL across the genomic locations separately by trait, implicitly assumes all traits are uncorrelated. Recently, an empirical test for QTL hotspots was proposed on the basis of the number of traits that exceed a predetermined LOD value, such as the standard permutation LOD threshold. The permutation null distribution of the maximum number of traits across all genomic locations preserves the correlation structure among the phenotypes, avoiding the detection of spurious hotspots due to nongenetic correlation induced by uncontrolled environmental factors and unmeasured variables. However, by considering only the number of traits above a threshold, without accounting for the magnitude of the LOD scores, relevant information is lost. In particular, biologically interesting hotspots composed of a moderate to small number of traits with strong LOD scores may be neglected as nonsignificant. In this article we propose a quantile-based permutation approach that simultaneously accounts for the number and the LOD scores of traits within the hotspots. By considering a sliding scale of mapping thresholds, our method can assess the statistical significance of both small and large hotspots. Although the proposed approach can be applied to any type of heritable high-volume "omic" data set, we restrict our attention to expression (e)QTL analysis. We assess and compare the performances of these three methods in simulations and we illustrate how our approach can effectively assess the significance of moderate and small hotspots with strong LOD scores in a yeast expression data set.

Detection of quantitative trait loci on chromosomes 1,2,3,12,14,15, X in pigs: performance characteristics

NARCIS (Netherlands)

Paixao, D.M.; Carneiro, P.L.S.; Paiva, S.R.; Sousa, K.R.S.; Verardo, L.L.; Braccini Neto, J.; Pinto, A.P.G.; Marubayashi Hidalgo, A.; Nascimento, C.; Périssé, I.V.; Lopes, P.S.; Guimaraes, S.E.F.

2013-01-01

The accomplishment of the present study had the objective of mapping Quantitative Trait Loci (QTL) related to performance traits in a F2 pig population developed by mating two Brazilian Piau breed sires with 18 dams from a commercial line (Landrace × Large White × Pietrain). The linkage map for this

Network-based group variable selection for detecting expression quantitative trait loci (eQTL

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Zhang Xuegong

2011-06-01

Full Text Available Abstract Background Analysis of expression quantitative trait loci (eQTL aims to identify the genetic loci associated with the expression level of genes. Penalized regression with a proper penalty is suitable for the high-dimensional biological data. Its performance should be enhanced when we incorporate biological knowledge of gene expression network and linkage disequilibrium (LD structure between loci in high-noise background. Results We propose a network-based group variable selection (NGVS method for QTL detection. Our method simultaneously maps highly correlated expression traits sharing the same biological function to marker sets formed by LD. By grouping markers, complex joint activity of multiple SNPs can be considered and the dimensionality of eQTL problem is reduced dramatically. In order to demonstrate the power and flexibility of our method, we used it to analyze two simulations and a mouse obesity and diabetes dataset. We considered the gene co-expression network, grouped markers into marker sets and treated the additive and dominant effect of each locus as a group: as a consequence, we were able to replicate results previously obtained on the mouse linkage dataset. Furthermore, we observed several possible sex-dependent loci and interactions of multiple SNPs. Conclusions The proposed NGVS method is appropriate for problems with high-dimensional data and high-noise background. On eQTL problem it outperforms the classical Lasso method, which does not consider biological knowledge. Introduction of proper gene expression and loci correlation information makes detecting causal markers more accurate. With reasonable model settings, NGVS can lead to novel biological findings.

Linkage of DNA Methylation Quantitative Trait Loci to Human Cancer Risk

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Holger Heyn

2014-04-01

Full Text Available Epigenetic regulation and, in particular, DNA methylation have been linked to the underlying genetic sequence. DNA methylation quantitative trait loci (meQTL have been identified through significant associations between the genetic and epigenetic codes in physiological and pathological contexts. We propose that interrogating the interplay between polymorphic alleles and DNA methylation is a powerful method for improving our interpretation of risk alleles identified in genome-wide association studies that otherwise lack mechanistic explanation. We integrated patient cancer risk genotype data and genome-scale DNA methylation profiles of 3,649 primary human tumors, representing 13 solid cancer types. We provide a comprehensive meQTL catalog containing DNA methylation associations for 21% of interrogated cancer risk polymorphisms. Differentially methylated loci harbor previously reported and as-yet-unidentified cancer genes. We suggest that such regulation at the DNA level can provide a considerable amount of new information about the biology of cancer-risk alleles.

Quantitative trait loci mapping of calving and conformation traits on Bos taurus autosome 18 in the German Holstein population.

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Brand, B; Baes, C; Mayer, M; Reinsch, N; Seidenspinner, T; Thaller, G; Kühn, Ch

2010-03-01

Linkage, linkage disequilibrium, and combined linkage and linkage disequilibrium analyses were performed to map quantitative trait loci (QTL) affecting calving and conformation traits on Bos taurus autosome 18 (BTA18) in the German Holstein population. Six paternal half-sib families consisting of a total of 1,054 animals were genotyped on 28 genetic markers in the telomeric region on BTA18 spanning approximately 30 Mb. Calving traits, body type traits, and udder type traits were investigated. Using univariately estimated breeding values, maternal and direct effects on calving ease and stillbirth were analyzed separately for first- and further-parity calvings. The QTL initially identified by separate linkage and linkage disequilibrium analyses could be confirmed by a combined linkage and linkage disequilibrium analysis for udder composite index, udder depth, fore udder attachment, front teat placement, body depth, rump angle, and direct effects on calving ease and stillbirth. Concurrence of QTL peaks and a similar shape of restricted log-likelihood ratio profiles were observed between udder type traits and for body depth and calving traits, respectively. Association analyses were performed for markers flanking the most likely QTL positions by applying a mixed model including a fixed allele effect of the maternally inherited allele and a random polygenic effect. Results indicated that microsatellite marker DIK4234 (located at 53.3 Mb) is associated with maternal effects on stillbirth, direct effects on calving ease, and body depth. A comparison of effects for maternally inherited DIK4234 alleles indicated a favorable, positive correlation of maternal and direct effects on calving. Additionally, the association of maternally inherited DIK4234 marker alleles with body depth implied that conformation traits might provide the functional background of the QTL for calving traits. For udder type traits, the strong coincidence of QTL peaks and the position of the QTL in a

Mapping of quantitative trait loci (QTL) for production, resistance and tolerance traits in Salix. Final Report

Energy Technology Data Exchange (ETDEWEB)

Roennberg-Waestljung, Ann Christin; Bertholdsson, Nils-Ove; Glynn, Carolyn; Weih, Martin; Aahman, Inger [SLU, Uppsala (Sweden). Dept. of Plant Biology and Forest Genetics

2004-05-01

Quantitative trait loci (QTL) for growth traits, water use efficiency and tolerance/resistance against metals and herbivores have been identified. A hybrid F2 population originating from a cross between a Salix dasyclados-clone (SW901290) and a S. viminalis-clone ('Jorunn') was used for the different studies in this project. The growth response was analyzed in a greenhouse experiment with two water treatments, normal and drought. In addition, three field experiments with contrasting soils and climates were established. QTL specific for each treatment or field environment but also QTL stable over the treatments or field environments were detected. Each QTL explained from 8 to 29 % of the phenotypic variation depending on trait, treatment or field environment. Clusters of QTL for different traits were mapped indicating a common genetic base or tightly-linked QTL. Stable QTL identified for dryweight can be useful tools for early selection in Salix. In a separate greenhouse experiment, with a subset of ten genotypes from the F2 population, we show that genotype is more important than irrigation treatment for production of phenolic substances as well as for resistance to herbivory by P vulgatissima.

Mapping quantitative trait loci (QTL in sheep. IV. Analysis of lactation persistency and extended lactation traits in sheep

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Lam Mary K

2011-06-01

Full Text Available Abstract Background In sheep dairy production, total lactation performance, and length of lactation of lactation are of economic significance. A more persistent lactation has been associated with improved udder health. An extended lactation is defined by a longer period of milkability. This study is the first investigation to examine the presence of quantitative trait loci (QTL for extended lactation and lactation persistency in sheep. Methods An (Awassi × Merino × Merino single-sire backcross family with 172 ewes was used to map QTL for lactation persistency and extended lactation traits on a framework map of 189 loci across all autosomes. The Wood model was fitted to data from multiple lactations to estimate parameters of ovine lactation curves, and these estimates were used to derive measures of lactation persistency and extended lactation traits of milk, protein, fat, lactose, useful yield, and somatic cell score. These derived traits were subjected to QTL analyses using maximum likelihood estimation and regression analysis. Results Overall, one highly significant (LOD > 3.0, four significant (2.0 Conclusion This study identified ten novel QTL for lactation persistency and extended lactation in sheep, but results suggest that lactation persistency and extended lactation do not have a major gene in common. These results provide a basis for further validation in extended families and other breeds as well as targeting regions for genome-wide association mapping using high-density SNP arrays.

Quantitative trait loci linked to PRNP gene controlling health and production traits in INRA 401 sheep

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Brunel Jean-Claude

2007-07-01

Full Text Available Abstract In this study, the potential association of PrP genotypes with health and productive traits was investigated. Data were recorded on animals of the INRA 401 breed from the Bourges-La Sapinière INRA experimental farm. The population consisted of 30 rams and 852 ewes, which produced 1310 lambs. The animals were categorized into three PrP genotype classes: ARR homozygous, ARR heterozygous, and animals without any ARR allele. Two analyses differing in the approach considered were carried out. Firstly, the potential association of the PrP genotype with disease (Salmonella resistance and production (wool and carcass traits was studied. The data used included 1042, 1043 and 1013 genotyped animals for the Salmonella resistance, wool and carcass traits, respectively. The different traits were analyzed using an animal model, where the PrP genotype effect was included as a fixed effect. Association analyses do not indicate any evidence of an effect of PrP genotypes on traits studied in this breed. Secondly, a quantitative trait loci (QTL detection approach using the PRNP gene as a marker was applied on ovine chromosome 13. Interval mapping was used. Evidence for one QTL affecting mean fiber diameter was found at 25 cM from the PRNP gene. However, a linkage between PRNP and this QTL does not imply unfavorable linkage disequilibrium for PRNP selection purposes.

Six quantitative trait loci influence task thresholds for hygienic behaviour in honeybees (Apis mellifera).

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Oxley, Peter R; Spivak, Marla; Oldroyd, Benjamin P

2010-04-01

Honeybee hygienic behaviour provides colonies with protection from many pathogens and is an important model system of the genetics of a complex behaviour. It is a textbook example of complex behaviour under simple genetic control: hygienic behaviour consists of two components--uncapping a diseased brood cell, followed by removal of the contents--each of which are thought to be modulated independently by a few loci of medium to large effect. A worker's genetic propensity to engage in hygienic tasks affects the intensity of the stimulus required before she initiates the behaviour. Genetic diversity within colonies leads to task specialization among workers, with a minority of workers performing the majority of nest-cleaning tasks. We identify three quantitative trait loci that influence the likelihood that workers will engage in hygienic behaviour and account for up to 30% of the phenotypic variability in hygienic behaviour in our population. Furthermore, we identify two loci that influence the likelihood that a worker will perform uncapping behaviour only, and one locus that influences removal behaviour. We report the first candidate genes associated with engaging in hygienic behaviour, including four genes involved in olfaction, learning and social behaviour, and one gene involved in circadian locomotion. These candidates will allow molecular characterization of this distinctive behavioural mode of disease resistance, as well as providing the opportunity for marker-assisted selection for this commercially significant trait.

Mapping of imprinted quantitative trait loci using immortalized F2 populations.

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Yongxian Wen

Full Text Available Mapping of imprinted quantitative trait loci (iQTLs is helpful for understanding the effects of genomic imprinting on complex traits in animals and plants. At present, the experimental designs and corresponding statistical methods having been proposed for iQTL mapping are all based on temporary populations including F2 and BC1, which can be used only once and suffer some other shortcomings respectively. In this paper, we propose a framework for iQTL mapping, including methods of interval mapping (IM and composite interval mapping (CIM based on conventional low-density genetic maps and point mapping (PM and composite point mapping (CPM based on ultrahigh-density genetic maps, using an immortalized F2 (imF2 population generated by random crosses between recombinant inbred lines or doubled haploid lines. We demonstrate by simulations that imF2 populations are very desirable and the proposed statistical methods (especially CIM and CPM are very powerful for iQTL mapping, with which the imprinting effects as well as the additive and dominance effects of iQTLs can be unbiasedly estimated.

Mapping of quantitative trait loci for resistance to fall armyworm and southwestern corn borer leaf-feeding damage in maize.

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Fall armyworm (FAW), Spodoptera frugiperda (J. E. Smith), and southwestern corn borer (SWCB), Diatraea grandiosella Dyar are damaging insect pests of maize resulting in significant yield and economic losses. A previous study identified quantitative trait loci (QTL) that contribute to reduced leaf-fe...

A simple linear regression method for quantitative trait loci linkage analysis with censored observations.

Science.gov (United States)

Anderson, Carl A; McRae, Allan F; Visscher, Peter M

2006-07-01

Standard quantitative trait loci (QTL) mapping techniques commonly assume that the trait is both fully observed and normally distributed. When considering survival or age-at-onset traits these assumptions are often incorrect. Methods have been developed to map QTL for survival traits; however, they are both computationally intensive and not available in standard genome analysis software packages. We propose a grouped linear regression method for the analysis of continuous survival data. Using simulation we compare this method to both the Cox and Weibull proportional hazards models and a standard linear regression method that ignores censoring. The grouped linear regression method is of equivalent power to both the Cox and Weibull proportional hazards methods and is significantly better than the standard linear regression method when censored observations are present. The method is also robust to the proportion of censored individuals and the underlying distribution of the trait. On the basis of linear regression methodology, the grouped linear regression model is computationally simple and fast and can be implemented readily in freely available statistical software.

Quantitative Trait Loci Analysis of Seed Quality Characteristics in Lentil using Single Nucleotide Polymorphism Markers

Directory of Open Access Journals (Sweden)

Michael J. Fedoruk

2013-11-01

Full Text Available Seed shape, color, and pattern of lentil ( Medik. subsp. are important quality traits as they determine market class and possible end uses. A recombinant inbred line population was phenotyped for seed dimensions over multiple site–years and classified according to cotyledon and seed coat color and pattern. The objectives were to determine the heritability of seed dimensions, identify genomic regions controlling these dimensions, and map seed coat and cotyledon color genes. A genetic linkage map consisting of 563 single nucleotide polymorphisms, 10 simple sequence repeats, and four seed color loci was developed for quantitative trait loci (QTL analysis. Loci for seed coat color and pattern mapped to linkage groups 2 (, 3 (, and 6 ( while the cotyledon color locus ( mapped to linkage group 1. The broad sense heritability estimates were high for seed diameter (broad-sense heritability [] = 0.92 and seed plumpness ( = 0.94 while seed thickness ( = 0.60 and days to flowering ( = 0.45 were more moderate. There were significant seed dimension QTL on six of the seven linkage groups. The most significant QTL for diameter and plumpness was found at the cotyledon color locus (. The markers identified in this study can be used to help enrich breeding populations for desired seed quality characteristics, thereby increasing efficiency in the lentil breeding program.

Mapping quantitative trait loci (QTL in sheep. II. Meta-assembly and identification of novel QTL for milk production traits in sheep

Directory of Open Access Journals (Sweden)

Lam Mary K

2009-10-01

Full Text Available Abstract An (Awassi × Merino × Merino backcross family of 172 ewes was used to map quantitative trait loci (QTL for different milk production traits on a framework map of 200 loci across all autosomes. From five previously proposed mathematical models describing lactation curves, the Wood model was considered the most appropriate due to its simplicity and its ability to determine ovine lactation curve characteristics. Derived milk traits for milk, fat, protein and lactose yield, as well as percentage composition and somatic cell score were used for single and two-QTL approaches using maximum likelihood estimation and regression analysis. A total of 15 significant (P P http://crcidp.vetsci.usyd.edu.au/cgi-bin/gbrowse/oaries_genome/. Many of the QTL for milk production traits have been reported on chromosomes 1, 3, 6, 16 and 20. Those on chromosomes 3 and 20 are in strong agreement with the results reported here. In addition, novel QTL were found on chromosomes 7, 8, 9, 14, 22 and 24. In a cross-species comparison, we extended the meta-assembly by comparing QTL regions of sheep and cattle, which provided strong evidence for synteny conservation of QTL regions for milk, fat, protein and somatic cell score data between cattle and sheep.

Targeted introgression of cotton fibre quality quantitative trait loci using molecular markers

International Nuclear Information System (INIS)

Lacape, J.M.; Trung-Bieu Nguyen; Hau, B.; Giband, M.

2007-01-01

Within the framework of a cotton breeding programme, molecular markers are used to improve the efficiency of the introgression of fibre quality traits of Gossypium barbadense into G. hirsutum. A saturated genetic map was developed based on genotyping data obtained from the BC 1 (75 plants) and BC 2 (200 plants) generations. Phenotypic measurements conducted over three generations (BC 1 , BC 2 and BC 2 S 1 ) allowed 80 quantitative trait loci (QTL) to be detected for fibre length, uniformity, strength, elongation, fineness and colour. Positive QTL, i.e. those for which favourable alleles came from the G. barbadense parent, were harboured by 19 QTL-rich regions on 15 'carrier' chromosomes. In subsequent generations (BC 3 and BC 4 ), markers framing the QTL-rich regions were used to select about 10 percent of over 400 plants analysed in each generation. Although BC plants selected through the marker-assisted selection (MAS) process show promising fibre quality, only their full field evaluation will allow validation of the procedure. (author)

Detection of novel quantitative trait loci for cutaneous melanoma by genome-wide scan in the MeLiM swine model

Czech Academy of Sciences Publication Activity Database

Du, Z. Q.; Vincent-Naulleau, S.; Gilbert, H.; Vignoles, F.; Créchet, F.; Shimogiri, T.; Yasue, H.; Leplat, J. J.; Bouet, S.; Gruand, J.; Horák, Vratislav; Milan, D.; Le Roy, P.; Geffrotin, C.

2006-01-01

Roč. 120, - (2006), s. 303-320 ISSN 0020-7136 Institutional research plan: CEZ:AV0Z50450515 Keywords : swine melanoma * quantitative trait loci * MC1R Subject RIV: FD - Oncology ; Hematology Impact factor: 4.693, year: 2006

SplicePlot: a utility for visualizing splicing quantitative trait loci.

Science.gov (United States)

Wu, Eric; Nance, Tracy; Montgomery, Stephen B

2014-04-01

RNA sequencing has provided unprecedented resolution of alternative splicing and splicing quantitative trait loci (sQTL). However, there are few tools available for visualizing the genotype-dependent effects of splicing at a population level. SplicePlot is a simple command line utility that produces intuitive visualization of sQTLs and their effects. SplicePlot takes mapped RNA sequencing reads in BAM format and genotype data in VCF format as input and outputs publication-quality Sashimi plots, hive plots and structure plots, enabling better investigation and understanding of the role of genetics on alternative splicing and transcript structure. Source code and detailed documentation are available at http://montgomerylab.stanford.edu/spliceplot/index.html under Resources and at Github. SplicePlot is implemented in Python and is supported on Linux and Mac OS. A VirtualBox virtual machine running Ubuntu with SplicePlot already installed is also available.

Genome-Wide Search for Quantitative Trait Loci Controlling Important Plant and Flower Traits in Petunia Using an Interspecific Recombinant Inbred Population of Petunia axillaris and Petunia exserta.

Science.gov (United States)

Cao, Zhe; Guo, Yufang; Yang, Qian; He, Yanhong; Fetouh, Mohammed; Warner, Ryan M; Deng, Zhanao

2018-05-15

A major bottleneck in plant breeding has been the much limited genetic base and much reduced genetic diversity in domesticated, cultivated germplasm. Identification and utilization of favorable gene loci or alleles from wild or progenitor species can serve as an effective approach to increasing genetic diversity and breaking this bottleneck in plant breeding. This study was conducted to identify quantitative trait loci (QTL) in wild or progenitor petunia species that can be used to improve important horticultural traits in garden petunia. An F 7 recombinant inbred population derived between Petunia axillaris and P. exserta was phenotyped for plant height, plant spread, plant size, flower counts, flower diameter, flower length, and days to anthesis, in Florida in two consecutive years. Transgressive segregation was observed for all seven traits in both years. The broad-sense heritability estimates for the traits ranged from 0.20 (days to anthesis) to 0.62 (flower length). A genome-wide genetic linkage map consisting 368 single nucleotide polymorphism bins and extending over 277 cM was searched to identify QTL for these traits. Nineteen QTL were identified and localized to five linkage groups. Eleven of the loci were identified consistently in both years; several loci explained up to 34.0% and 24.1% of the phenotypic variance for flower length and flower diameter, respectively. Multiple loci controlling different traits are co-localized in four intervals in four linkage groups. These intervals contain desirable alleles that can be introgressed into commercial petunia germplasm to expand the genetic base and improve plant performance and flower characteristics in petunia. Copyright © 2018, G3: Genes, Genomes, Genetics.

Quantitative trait loci mapping of heat tolerance in broccoli (Brassica oleracea var. italica) using genotyping-by-sequencing.

Science.gov (United States)

Branham, Sandra E; Stansell, Zachary J; Couillard, David M; Farnham, Mark W

2017-03-01

Five quantitative trait loci and one epistatic interaction were associated with heat tolerance in a doubled haploid population of broccoli evaluated in three summer field trials. Predicted rising global temperatures due to climate change have generated a demand for crops that are resistant to yield and quality losses from heat stress. Broccoli (Brassica oleracea var. italica) is a cool weather crop with high temperatures during production decreasing both head quality and yield. Breeding for heat tolerance in broccoli has potential to both expand viable production areas and extend the growing season but breeding efficiency is constrained by limited genetic information. A doubled haploid (DH) broccoli population segregating for heat tolerance was evaluated for head quality in three summer fields in Charleston, SC, USA. Multiple quantitative trait loci (QTL) mapping of 1,423 single nucleotide polymorphisms developed through genotyping-by-sequencing identified five QTL and one positive epistatic interaction that explained 62.1% of variation in heat tolerance. The QTL identified here can be used to develop markers for marker-assisted selection and to increase our understanding of the molecular mechanisms underlying plant response to heat stress.

Genome-wide haplotype analysis of cis expression quantitative trait loci in monocytes.

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Sophie Garnier

Full Text Available In order to assess whether gene expression variability could be influenced by several SNPs acting in cis, either through additive or more complex haplotype effects, a systematic genome-wide search for cis haplotype expression quantitative trait loci (eQTL was conducted in a sample of 758 individuals, part of the Cardiogenics Transcriptomic Study, for which genome-wide monocyte expression and GWAS data were available. 19,805 RNA probes were assessed for cis haplotypic regulation through investigation of ~2,1 × 10(9 haplotypic combinations. 2,650 probes demonstrated haplotypic p-values >10(4-fold smaller than the best single SNP p-value. Replication of significant haplotype effects were tested for 412 probes for which SNPs (or proxies that defined the detected haplotypes were available in the Gutenberg Health Study composed of 1,374 individuals. At the Bonferroni correction level of 1.2 × 10(-4 (~0.05/412, 193 haplotypic signals replicated. 1000 G imputation was then conducted, and 105 haplotypic signals still remained more informative than imputed SNPs. In-depth analysis of these 105 cis eQTL revealed that at 76 loci genetic associations were compatible with additive effects of several SNPs, while for the 29 remaining regions data could be compatible with a more complex haplotypic pattern. As 24 of the 105 cis eQTL have previously been reported to be disease-associated loci, this work highlights the need for conducting haplotype-based and 1000 G imputed cis eQTL analysis before commencing functional studies at disease-associated loci.

Genes and quantitative trait loci (QTL) controlling trace element concentrations in perennial grasses grown on phytotoxic soil contaminated with heavy metals

Science.gov (United States)

Perennial grasses cover diverse soils throughout the world, including sites contaminated with heavy metals, producing forages that must be safe for livestock and wildlife. Chromosome regions known as quantitative trait loci (QTLs) controlling forage mineral concentrations were mapped in a populatio...

Quantitative trait loci affecting phenotypic variation in the vacuolated lens mouse mutant, a multigenic mouse model of neural tube defects

NARCIS (Netherlands)

Korstanje, Ron; Desai, Jigar; Lazar, Gloria; King, Benjamin; Rollins, Jarod; Spurr, Melissa; Joseph, Jamie; Kadambi, Sindhuja; Li, Yang; Cherry, Allison; Matteson, Paul G.; Paigen, Beverly; Millonig, James H.

Korstanje R, Desai J, Lazar G, King B, Rollins J, Spurr M, Joseph J, Kadambi S, Li Y, Cherry A, Matteson PG, Paigen B, Millonig JH. Quantitative trait loci affecting phenotypic variation in the vacuolated lens mouse mutant, a multigenic mouse model of neural tube defects. Physiol Genomics 35:

Quantitative Trait Loci for Mercury Tolerance in Rice Seedlings

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Chong-qing WANG

2013-05-01

Full Text Available Mercury (Hg is one of the most toxic heavy metals to living organisms and its conspicuous effect is the inhibition of root growth. However, little is known about the molecular genetic basis for root growth under excess Hg2+ stress. To map quantitative trait loci (QTLs in rice for Hg2+ tolerance, a population of 120 recombinant inbred lines derived from a cross between two japonica cultivars Yuefu and IRAT109 was grown in 0.5 mmol/L CaCl2 solution. Relative root length (RRL, percentage of the seminal root length in +HgCl2 to –HgCl2, was used for assessing Hg2+ tolerance. In a dose-response experiment, Yuefu had a higher RRL than IRAT109 and showed the most significant difference at the Hg2+ concentration of 1.5 μmol/L. Three putative QTLs for RRL were detected on chromosomes 1, 2 and 5, and totally explained about 35.7% of the phenotypic variance in Hg2+ tolerance. The identified QTLs for RRL might be useful for improving Hg2+ tolerance of rice by molecular marker-assisted selection.

Quantitative trait loci markers derived from whole genome sequence data increases the reliability of genomic prediction

DEFF Research Database (Denmark)

Brøndum, Rasmus Froberg; Su, Guosheng; Janss, Luc

2015-01-01

This study investigated the effect on the reliability of genomic prediction when a small number of significant variants from single marker analysis based on whole genome sequence data were added to the regular 54k single nucleotide polymorphism (SNP) array data. The extra markers were selected...... with the aim of augmenting the custom low-density Illumina BovineLD SNP chip (San Diego, CA) used in the Nordic countries. The single-marker analysis was done breed-wise on all 16 index traits included in the breeding goals for Nordic Holstein, Danish Jersey, and Nordic Red cattle plus the total merit index...... itself. Depending on the trait’s economic weight, 15, 10, or 5 quantitative trait loci (QTL) were selected per trait per breed and 3 to 5 markers were selected to tag each QTL. After removing duplicate markers (same marker selected for more than one trait or breed) and filtering for high pairwise linkage...

Design database for quantitative trait loci (QTL) data warehouse, data mining, and meta-analysis.

Science.gov (United States)

Hu, Zhi-Liang; Reecy, James M; Wu, Xiao-Lin

2012-01-01

A database can be used to warehouse quantitative trait loci (QTL) data from multiple sources for comparison, genomic data mining, and meta-analysis. A robust database design involves sound data structure logistics, meaningful data transformations, normalization, and proper user interface designs. This chapter starts with a brief review of relational database basics and concentrates on issues associated with curation of QTL data into a relational database, with emphasis on the principles of data normalization and structure optimization. In addition, some simple examples of QTL data mining and meta-analysis are included. These examples are provided to help readers better understand the potential and importance of sound database design.

Quantitative Trait Loci Associated with Drought Tolerance in Brachypodium distachyon

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Yiwei Jiang

2017-05-01

Full Text Available The temperate wild grass Brachypodium distachyon (Brachypodium serves as model system for studying turf and forage grasses. Brachypodium collections show diverse responses to drought stress, but little is known about the genetic mechanisms of drought tolerance of this species. The objective of this study was to identify quantitative trait loci (QTLs associated with drought tolerance traits in Brachypodium. We assessed leaf fresh weight (LFW, leaf dry weight (LDW, leaf water content (LWC, leaf wilting (WT, and chlorophyll fluorescence (Fv/Fm under well-watered and drought conditions on a recombinant inbred line (RIL population from two parents (Bd3-1 and Bd1-1 known to differ in their drought adaptation. A linkage map of the RIL population was constructed using 467 single nucleotide polymorphism (SNP markers obtained from genotyping-by-sequencing. The Bd3-1/Bd1-1 map spanned 1,618 cM and had an average distance of 3.5 cM between adjacent single nucleotide polymorphisms (SNPs. Twenty-six QTLs were identified in chromosome 1, 2, and 3 in two experiments, with 14 of the QTLs under well-watered conditions and 12 QTLs under drought stress. In Experiment 1, a QTL located on chromosome 2 with a peak at 182 cM appeared to simultaneously control WT, LWC, and Fv/Fm under drought stress, accounting for 11–18.7% of the phenotypic variation. Allelic diversity of candidate genes DREB2B, MYB, and SPK, which reside in one multi-QTL region, may play a role in the natural variation in whole plant drought tolerance in Brachypodium. Co-localization of QTLs for multiple drought-related traits suggest that the gene(s involved are important regulators of drought tolerance in Brachypodium.

Quantitative trait loci for maysin synthesis in maize (Zea mays L.) lines selected for high silk maysin content.

Science.gov (United States)

Meyer, J D F; Snook, M E; Houchins, K E; Rector, B G; Widstrom, N W; McMullen, M D

2007-06-01

Maysin is a naturally occurring C-glycosyl flavone found in maize (Zea mays L.) silk tissue that confers resistance to corn earworm (Helicoverpa zea, Boddie). Recently, two new maize populations were derived for high silk maysin. The two populations were named the exotic populations of maize (EPM) and the southern inbreds of maize (SIM). Quantitative trait locus (QTL) analysis was employed to determine which loci were responsible for elevated maysin levels in inbred lines derived from the EPM and SIM populations. The candidate genes consistent with QTL position included the p (pericarp color), c2 (colorless2), whp1 (white pollen1) and in1 (intensifier1) loci. The role of these loci in controlling high maysin levels in silks was tested by expression analysis and use of the loci as genetic markers onto the QTL populations. These studies support p, c2 and whp1, but not in1, as loci controlling maysin. Through this study, we determined that the p locus regulates whp1 transcription and that increased maysin in these inbred lines was primarily due to alleles at both structural and regulatory loci promoting increased flux through the flavone pathway by increasing chalcone synthase activity.

Quantitative trait loci (QTL) mapping for inflorescence length traits in ...

African Journals Online (AJOL)

User

2011-05-02

May 2, 2011 ... character affected by ecological surroundings, growth ... developed from each F2 by bud self-pollination for QTL analysis. ... Quantitative traits measured for the each individual plant in F2 the population and F3 families ..... sex and parental interactions (Liu et al., 1996). ... evolution of solanaceous species.

Combining quantitative trait loci analysis with physiological models to predict genotype-specific transpiration rates.

Science.gov (United States)

Reuning, Gretchen A; Bauerle, William L; Mullen, Jack L; McKay, John K

2015-04-01

Transpiration is controlled by evaporative demand and stomatal conductance (gs ), and there can be substantial genetic variation in gs . A key parameter in empirical models of transpiration is minimum stomatal conductance (g0 ), a trait that can be measured and has a large effect on gs and transpiration. In Arabidopsis thaliana, g0 exhibits both environmental and genetic variation, and quantitative trait loci (QTL) have been mapped. We used this information to create a genetically parameterized empirical model to predict transpiration of genotypes. For the parental lines, this worked well. However, in a recombinant inbred population, the predictions proved less accurate. When based only upon their genotype at a single g0 QTL, genotypes were less distinct than our model predicted. Follow-up experiments indicated that both genotype by environment interaction and a polygenic inheritance complicate the application of genetic effects into physiological models. The use of ecophysiological or 'crop' models for predicting transpiration of novel genetic lines will benefit from incorporating further knowledge of the genetic control and degree of independence of core traits/parameters underlying gs variation. © 2014 John Wiley & Sons Ltd.

Quantitative trait loci for magnitude of the plasma cortisol response to confinement in rainbow trout.

Science.gov (United States)

Quillet, E; Krieg, F; Dechamp, N; Hervet, C; Bérard, A; Le Roy, P; Guyomard, R; Prunet, P; Pottinger, T G

2014-04-01

Better understanding of the mechanisms underlying interindividual variation in stress responses and their links with production traits is a key issue for sustainable animal breeding. In this study, we searched for quantitative trait loci (QTL) controlling the magnitude of the plasma cortisol stress response and compared them to body size traits in five F2 full-sib families issued from two rainbow trout lines divergently selected for high or low post-confinement plasma cortisol level. Approximately 1000 F2 individuals were individually tagged and exposed to two successive acute confinement challenges (1 month interval). Post-stress plasma cortisol concentrations were determined for each fish. A medium density genome scan was carried out (268 markers, overall marker spacing less than 10 cM). QTL detection was performed using qtlmap software, based on an interval mapping method (http://www.inra.fr/qtlmap). Overall, QTL of medium individual effects on cortisol responsiveness (confinement stressor are distinct traits sharing only part of their genetic control. Chromosomal location of the steroidogenic acute regulatory protein (STAR) makes it a good potential candidate gene for one of the QTL. Finally, comparison of body size traits QTL (weight, length and body conformation) with cortisol-associated QTL did not support evidence for negative genetic relationships between the two types of traits. © 2014 Stichting International Foundation for Animal Genetics.

Quantitative Trait Loci Mapping in Brassica rapa Revealed the Structural and Functional Conservation of Genetic Loci Governing Morphological and Yield Component Traits in the A, B, and C Subgenomes of Brassica Species

Science.gov (United States)

Li, Xiaonan; Ramchiary, Nirala; Dhandapani, Vignesh; Choi, Su Ryun; Hur, Yoonkang; Nou, Ill-Sup; Yoon, Moo Kyoung; Lim, Yong Pyo

2013-01-01

Brassica rapa is an important crop species that produces vegetables, oilseed, and fodder. Although many studies reported quantitative trait loci (QTL) mapping, the genes governing most of its economically important traits are still unknown. In this study, we report QTL mapping for morphological and yield component traits in B. rapa and comparative map alignment between B. rapa, B. napus, B. juncea, and Arabidopsis thaliana to identify candidate genes and conserved QTL blocks between them. A total of 95 QTL were identified in different crucifer blocks of the B. rapa genome. Through synteny analysis with A. thaliana, B. rapa candidate genes and intronic and exonic single nucleotide polymorphisms in the parental lines were detected from whole genome resequenced data, a few of which were validated by mapping them to the QTL regions. Semi-quantitative reverse transcriptase PCR analysis showed differences in the expression levels of a few genes in parental lines. Comparative mapping identified five key major evolutionarily conserved crucifer blocks (R, J, F, E, and W) harbouring QTL for morphological and yield components traits between the A, B, and C subgenomes of B. rapa, B. juncea, and B. napus. The information of the identified candidate genes could be used for breeding B. rapa and other related Brassica species. PMID:23223793

Systems genomics study reveals expression quantitative trait loci, regulator genes and pathways associated with boar taint in pigs

DEFF Research Database (Denmark)

Drag, Markus; Hansen, Mathias B.; Kadarmideen, Haja N.

2018-01-01

Boar taint is an offensive odour and/or taste from a proportion of non-castrated male pigs caused by skatole and androstenone accumulation during sexual maturity. Castration is widely used to avoid boar taint but is currently under debate because of animal welfare concerns. This study aimed...... to identify expression quantitative trait loci (eQTLs) with potential effects on boar taint compounds to improve breeding possibilities for reduced boar taint. Danish Landrace male boars with low, medium and high genetic merit for skatole and human nose score (HNS) were slaughtered at similar to 100 kg. Gene...... monitoring of other overlapping QTL traits should be performed to avoid any negative consequences of selection....

Discovery of quantitative trait loci for crossability from a synthetic wheat genotype

Institute of Scientific and Technical Information of China (English)

Li Zhang; Jin Wang; Ronghua Zhou; Jizeng Jia

2011-01-01

Crossability between wheat and rye is an important trait for wheat improvement.No quantitative trait loci (QTLs) were detected from wheat ancestors previously.The objectives of this study were to dissect the QTLs for crossability using 111 introgression lines (ILs) derived from synthetic hexaploid wheat.A total of 1275 SSR markers were screened for polymorphism between the two parents,and 552 markers of them displayed polymorphism,of which 64 were selected for genotyping the 111 BC5F6 ILs.Field trials were performed in a Latinized α-lattice design in Luoyang and Jiaozuo of Henan Province of China in 2007-2008 and 2008-2009 cropping seasons.One-way ANOVA and interval mapping (IM) analysis were used to detect QTL for crossability between wheat and rye.A total of 13 putative QTLs were detected.Five of them,QCa.caas.1A,QCa.caas.2D,QCa.caas.4B,QCa.caas.5B and QCa.caas.6A,were detected in both trials and three of them,QCa.caas.2D,QCa.caas.4B and QCa.caas.6A,were novel.The positive effect allele of the four QTLs came from the donor parent Am3 except QCa.caas.6A that came from the recurrent parent Laizhou953.ILs with both higher positive effect alleles and favorable agronomic traits developed in present study are elite germplasm for wide crossing in wheat.Results from the current study suggest that wheat ancestors can be rich in new sources of crossability genes.

Localization of quantitative trait loci associated with radiation induced pulmonary fibrosis in the mouse

International Nuclear Information System (INIS)

Oas, L.G.; Haston, C.K.; Travis, E.L.

1997-01-01

Purpose/Objective: Pulmonary fibrosis is often a limiting factor in the planning of radiotherapy for thoracic neoplasms. Differences in the propensity to develop radiation induced pulmonary fibrosis have been noted between C3Hf/Kam (resistant) and C57BL/6J (susceptible) mouse strains. Bleomycin and radiation induced pulmonary fibrosis have been shown to be heritable traits in mice with significant linkage to the major histocompatibility complex on chromosome 17. The heritability of radiation induced damage was estimated to be 38%±11% with 1-2 genetic factors influencing expression. Only 6.6% of the phenotypic variance could be attributed to chromosome 17. A search of the genome was undertaken to identify loci which may be responsible for the remaining phenotypic variance. Materials and Methods: C3Hf/Kam and C57BL/6J mice were crosbred to yield F1 and F2 (F1 intercross) generations. Two hundred sixty eight males and females of the F2 generation were treated with orthovoltage radiation, 14 or 16 Gy, to the whole thorax. The mice were sacrificed after development of respiratory distress or at 33 weeks. Histologic sections were assessed with quantified image analysis to determine the percentage of fibrosis in both lungs. Genotyping was done on the pooled DNA of the mice who developed respiratory distress with 44 32 P labeled microsatellite markers having an average spacing of 24.5 cM. Correlation of the quantitative trait loci (QTLs) with the highest quartile of fibrosis revealed 10 out of 44 regions showing possible linkage. Individual DNA from 54 mice with the least fibrosis and 40 with the most fibrosis were probed using these markers. PCR and gel electrophoresis were performed and the results analysed. Results: Of the 10 markers analysed, one locus on chromosome 1 meets the criterion of suggestion of linkage. Conclusion: These findings point to regions on the mouse genome for which further investigation of fibrosis associated loci may be warranted

Annotation of loci from genome-wide association studies using tissue-specific quantitative interaction proteomics

NARCIS (Netherlands)

Lundby, Alicia; Rossin, Elizabeth J.; Steffensen, Annette B.; Acha, Moshe Ray; Newton-Cheh, Christopher; Pfeufer, Arne; Lyneh, Stacey N.; Olesen, Soren-Peter; Brunak, Soren; Ellinor, Patrick T.; Jukema, J. Wouter; Trompet, Stella; Ford, Ian; Macfarlane, Peter W.; Krijthe, Bouwe P.; Hofman, Albert; Uitterlinden, Andre G.; Stricker, Bruno H.; Nathoe, Hendrik M.; Spiering, Wilko; Daly, Mark J.; Asselbergs, Ikea W.; van der Harst, Pim; Milan, David J.; de Bakker, Paul I. W.; Lage, Kasper; Olsen, Jesper V.

Genome-wide association studies (GWAS) have identified thousands of loci associated with complex traits, but it is challenging to pinpoint causal genes in these loci and to exploit subtle association signals. We used tissue-specific quantitative interaction proteomics to map a network of five genes

Mapping epistasis and environment × QTX interaction based on four -omics genotypes for the detected QTX loci controlling complex traits in tobacco

Directory of Open Access Journals (Sweden)

Liyuan Zhou

2013-12-01

Full Text Available Using newly developed methods and software, association mapping was conducted for chromium content and total sugar in tobacco leaf, based on four -omics datasets. Our objective was to collect data on genotype and phenotype for 60 leaf samples at four developmental stages, from three plant architectural positions and for three cultivars that were grown in two locations. Association mapping was conducted to detect genetic variants at quantitative trait SNP (QTS loci, quantitative trait transcript (QTT differences, quantitative trait protein (QTP variability, and quantitative trait metabolite (QTM changes, which can be summarized as QTX locus variation. The total heritabilities of the four -omics loci for both traits tested were 23.60% for epistasis and 15.26% for treatment interaction. Epistasis and environment × treatment interaction had important impacts on complex traits at all -omics levels. For decreasing chromium content and increasing total sugar in tobacco leaf, six methylated loci can be directly used for marker-assisted selection, and expression of ten QTTs, seven QTPs and six QTMs can be modified by selection or cultivation.

An international collaborative family-based whole genome quantitative trait linkage scan for myopic refractive error

DEFF Research Database (Denmark)

Abbott, Diana; Li, Yi-Ju; Guggenheim, Jeremy A

2012-01-01

To investigate quantitative trait loci linked to refractive error, we performed a genome-wide quantitative trait linkage analysis using single nucleotide polymorphism markers and family data from five international sites....

Detection of quantitative trait loci in Danish Holstein cattle affecting clinical mastitis, somatic cell score, udder conformation traits, and assessment of associated effects on milk yield

DEFF Research Database (Denmark)

Lund, M S; Guldbrandtsen, B; Buitenhuis, A J

2008-01-01

The aim of this study was to 1) detect QTL across the cattle genome that influence the incidence of clinical mastitis and somatic cell score (SCS) in Danish Holsteins, and 2) characterize these QTL for pleiotropy versus multiple linked quantitative trait loci (QTL) when chromosomal regions...... affecting clinical mastitis were also affecting other traits in the Danish udder health index or milk production traits. The chromosomes were scanned using a granddaughter design where markers were typed for 19 to 34 grandsire families and 1,373 to 2,042 sons. A total of 356 microsatellites covering all 29...... autosomes were used in the scan. Among the across-family regression analyses, 16 showed chromosome-wide significance for the primary traits incidence of clinical mastitis in first (CM1), second (CM2), and third (CM3) lactations, and SCS. Regions of chromosomes 5, 6, 9, 11, 15, and 26 were found to affect CM...

Mapping Quantitative Trait Loci (QTL in sheep. III. QTL for carcass composition traits derived from CT scans and aligned with a meta-assembly for sheep and cattle carcass QTL

Directory of Open Access Journals (Sweden)

Thomson Peter C

2010-09-01

Full Text Available Abstract An (Awassi × Merino × Merino single-sire backcross family with 165 male offspring was used to map quantitative trait loci (QTL for body composition traits on a framework map of 189 microsatellite loci across all autosomes. Two cohorts were created from the experimental progeny to represent alternative maturity classes for body composition assessment. Animals were raised under paddock conditions prior to entering the feedlot for a 90-day fattening phase. Body composition traits were derived in vivo at the end of the experiment prior to slaughter at 2 (cohort 1 and 3.5 (cohort 2 years of age, using computed tomography. Image analysis was used to gain accurate predictions for 13 traits describing major fat depots, lean muscle, bone, body proportions and body weight which were used for single- and two-QTL mapping analysis. Using a maximum-likelihood approach, three highly significant (LOD ≥ 3, 15 significant (LOD ≥ 2, and 11 suggestive QTL (1.7 ≤ LOD P P A meta-assembly of ovine QTL for carcass traits from this study and public domain sources was performed and compared with a corresponding bovine meta-assembly. The assembly demonstrated QTL with effects on carcass composition in homologous regions on OAR1, 2, 6 and 21.

Adrenal cortex expression quantitative trait loci in a German Holstein × Charolais cross.

Science.gov (United States)

Brand, Bodo; Scheinhardt, Markus O; Friedrich, Juliane; Zimmer, Daisy; Reinsch, Norbert; Ponsuksili, Siriluck; Schwerin, Manfred; Ziegler, Andreas

2016-10-06

The importance of the adrenal gland in regard to lactation and reproduction in cattle has been recognized early. Caused by interest in animal welfare and the impact of stress on economically important traits in farm animals the adrenal gland and its function within the stress response is of increasing interest. However, the molecular mechanisms and pathways involved in stress-related effects on economically important traits in farm animals are not fully understood. Gene expression is an important mechanism underlying complex traits, and genetic variants affecting the transcript abundance are thought to influence the manifestation of an expressed phenotype. We therefore investigated the genetic background of adrenocortical gene expression by applying an adaptive linear rank test to identify genome-wide expression quantitative trait loci (eQTL) for adrenal cortex transcripts in cattle. A total of 10,986 adrenal cortex transcripts and 37,204 single nucleotide polymorphisms (SNPs) were analysed in 145 F2 cows of a Charolais × German Holstein cross. We identified 505 SNPs that were associated with the abundance of 129 transcripts, comprising 482 cis effects and 17 trans effects. These SNPs were located on all chromosomes but X, 16, 24 and 28. Associated genes are mainly involved in molecular and cellular functions comprising free radical scavenging, cellular compromise, cell morphology and lipid metabolism, including genes such as CYP27A1 and LHCGR that have been shown to affect economically important traits in cattle. In this study we showed that adrenocortical eQTL affect the expression of genes known to contribute to the phenotypic manifestation in cattle. Furthermore, some of the identified genes and related molecular pathways were previously shown to contribute to the phenotypic variation of behaviour, temperament and growth at the onset of puberty in the same population investigated here. We conclude that eQTL analysis appears to be a useful approach providing

Exploring alternative models for sex-linked quantitative trait loci in outbred populations: application to an iberian x landrace pig intercross.

OpenAIRE

Pérez-Enciso, Miguel; Clop, Alex; Folch, Josep M; Sánchez, Armand; Oliver, Maria A; Ovilo, Cristina; Barragán, C; Varona, Luis; Noguera, José L

2002-01-01

We present a very flexible method that allows us to analyze X-linked quantitative trait loci (QTL) in crosses between outbred lines. The dosage compensation phenomenon is modeled explicitly in an identity-by-descent approach. A variety of models can be fitted, ranging from considering alternative fixed alleles within the founder breeds to a model where the only genetic variation is within breeds, as well as mixed models. Different genetic variances within each founder breed can be estimated. ...

Exercise and diet affect quantitative trait loci for body weight and composition traits in an advanced intercross population of mice

Science.gov (United States)

Kelly, Scott A.; Hua, Kunjie; Pomp, Daniel

2012-01-01

Driven by the recent obesity epidemic, interest in understanding the complex genetic and environmental basis of body weight and composition is great. We investigated this by searching for quantitative trait loci (QTLs) affecting a number of weight and adiposity traits in a G10 advanced intercross population produced from crosses of mice in inbred strain C57BL/6J with those in a strain selected for high voluntary wheel running. The mice in this population were fed either a high-fat or a control diet throughout the study and also measured for four exercise traits prior to death, allowing us to test for pre- and postexercise QTLs as well as QTL-by-diet and QTL-by-exercise interactions. Our genome scan uncovered a number of QTLs, of which 40% replicated QTLs previously found for similar traits in an earlier (G4) generation. For those replicated QTLs, the confidence intervals were reduced from an average of 19 Mb in the G4 to 8 Mb in the G10. Four QTLs on chromosomes 3, 8, 13, and 18 were especially prominent in affecting the percentage of fat in the mice. About of all QTLs showed interactions with diet, exercise, or both, their genotypic effects on the traits showing a variety of patterns depending on the diet or level of exercise. It was concluded that the indirect effects of these QTLs provide an underlying genetic basis for the considerable variability in weight or fat loss typically found among individuals on the same diet and/or exercise regimen. PMID:23048196

Identification of Quantitative Trait Loci for Resistance to RSIVD in Red Sea Bream (Pagrus major).

Science.gov (United States)

Sawayama, Eitaro; Tanizawa, Shiho; Kitamura, Shin-Ichi; Nakayama, Kei; Ohta, Kohei; Ozaki, Akiyuki; Takagi, Motohiro

2017-12-01

Red sea bream iridoviral disease (RSIVD) is a major viral disease in red sea bream farming in Japan. Previously, we identified one candidate male individual of red sea bream that was significantly associated with convalescent individuals after RSIVD. The purpose of this study is to identify the quantitative trait loci (QTL) linked to the RSIVD-resistant trait for future marker-assisted selection (MAS). Two test families were developed using the candidate male in 2014 (Fam-2014) and 2015 (Fam-2015). These test families were challenged with RSIV, and phenotypes were evaluated. Then, de novo genome sequences of red sea bream were obtained through next-generation sequencing, and microsatellite markers were searched and selected for linkage map construction. One immune-related gene, MHC class IIβ, was also used for linkage map construction. Of the microsatellite markers searched, 148 and 197 were mapped on 23 and 27 linkage groups in the female and male linkage maps, respectively, covering approximately 65% of genomes in both sexes. One QTL linked to an RSIVD-resistant trait was found in linkage group 2 of the candidate male in Fam-2014, and the phenotypic variance of the QTL was 31.1%. The QTL was closely linked to MHC class IIβ. Moreover, the QTL observed in Fam-2014 was also significantly linked to an RSIVD-resistant trait in the candidate male of Fam-2015. Our results suggest that the RSIVD-resistant trait in the candidate male was controlled by one major QTL closely linked to the MHC class IIβ gene and could be useful for MAS of red sea bream.

Prioritizing quantitative trait loci for root system architecture in tetraploid wheat.

Science.gov (United States)

Maccaferri, Marco; El-Feki, Walid; Nazemi, Ghasemali; Salvi, Silvio; Canè, Maria Angela; Colalongo, Maria Chiara; Stefanelli, Sandra; Tuberosa, Roberto

2016-02-01

Optimization of root system architecture (RSA) traits is an important objective for modern wheat breeding. Linkage and association mapping for RSA in two recombinant inbred line populations and one association mapping panel of 183 elite durum wheat (Triticum turgidum L. var. durum Desf.) accessions evaluated as seedlings grown on filter paper/polycarbonate screening plates revealed 20 clusters of quantitative trait loci (QTLs) for root length and number, as well as 30 QTLs for root growth angle (RGA). Divergent RGA phenotypes observed by seminal root screening were validated by root phenotyping of field-grown adult plants. QTLs were mapped on a high-density tetraploid consensus map based on transcript-associated Illumina 90K single nucleotide polymorphisms (SNPs) developed for bread and durum wheat, thus allowing for an accurate cross-referencing of RSA QTLs between durum and bread wheat. Among the main QTL clusters for root length and number highlighted in this study, 15 overlapped with QTLs for multiple RSA traits reported in bread wheat, while out of 30 QTLs for RGA, only six showed co-location with previously reported QTLs in wheat. Based on their relative additive effects/significance, allelic distribution in the association mapping panel, and co-location with QTLs for grain weight and grain yield, the RSA QTLs have been prioritized in terms of breeding value. Three major QTL clusters for root length and number (RSA_QTL_cluster_5#, RSA_QTL_cluster_6#, and RSA_QTL_cluster_12#) and nine RGA QTL clusters (QRGA.ubo-2A.1, QRGA.ubo-2A.3, QRGA.ubo-2B.2/2B.3, QRGA.ubo-4B.4, QRGA.ubo-6A.1, QRGA.ubo-6A.2, QRGA.ubo-7A.1, QRGA.ubo-7A.2, and QRGA.ubo-7B) appear particularly valuable for further characterization towards a possible implementation of breeding applications in marker-assisted selection and/or cloning of the causal genes underlying the QTLs. © The Author 2016. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Genomic value prediction for quantitative traits under the epistatic model

Directory of Open Access Journals (Sweden)

Xu Shizhong

2011-01-01

Full Text Available Abstract Background Most quantitative traits are controlled by multiple quantitative trait loci (QTL. The contribution of each locus may be negligible but the collective contribution of all loci is usually significant. Genome selection that uses markers of the entire genome to predict the genomic values of individual plants or animals can be more efficient than selection on phenotypic values and pedigree information alone for genetic improvement. When a quantitative trait is contributed by epistatic effects, using all markers (main effects and marker pairs (epistatic effects to predict the genomic values of plants can achieve the maximum efficiency for genetic improvement. Results In this study, we created 126 recombinant inbred lines of soybean and genotyped 80 makers across the genome. We applied the genome selection technique to predict the genomic value of somatic embryo number (a quantitative trait for each line. Cross validation analysis showed that the squared correlation coefficient between the observed and predicted embryo numbers was 0.33 when only main (additive effects were used for prediction. When the interaction (epistatic effects were also included in the model, the squared correlation coefficient reached 0.78. Conclusions This study provided an excellent example for the application of genome selection to plant breeding.

Systems genomics study reveals expression quantitative trait loci, regulator genes and pathways associated with boar taint in pigs

DEFF Research Database (Denmark)

Drag, Markus; Hansen, Mathias B.; Kadarmideen, Haja N.

2018-01-01

Boar taint is an offensive odour and/or taste from a proportion of non-castrated male pigs caused by skatole and androstenone accumulation during sexual maturity. Castration is widely used to avoid boar taint but is currently under debate because of animal welfare concerns. This study aimed...... to identify expression quantitative trait loci (eQTLs) with potential effects on boar taint compounds to improve breeding possibilities for reduced boar taint. Danish Landrace male boars with low, medium and high genetic merit for skatole and human nose score (HNS) were slaughtered at similar to 100 kg. Gene...... and SSC14. Functional characterisation of eQTLs revealed functions within regulation of androgen and the intracellular steroid hormone receptor signalling pathway and of xenobiotic metabolism by cytochrome P450 system and cellular response to oestradiol. A QTL enrichment test revealed 89 QTL traits...

A journey from a SSR-based low density map to a SNP-based high density map for identification of disease resistance quantitative trait loci in peanut

Science.gov (United States)

Mapping and identification of quantitative trait loci (QTLs) are important for efficient marker-assisted breeding. Diseases such as leaf spots and Tomato spotted wilt virus (TSWV) cause significant loses to peanut growers. The U.S. Peanut Genome Initiative (PGI) was launched in 2004, and expanded to...

Association Mapping of Malting Quality Quantitative Trait Loci in Winter Barley: Positive Signals from Small Germplasm Arrays

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Lucía Gutiérrez

2011-11-01

Full Text Available Malting quality comprises one of the most economically relevant set of traits in barley ( L.. It is a complex phenotype, expensive and difficult to measure, that would benefit from a marker-assisted selection strategy. Malting quality is a target of the U.S. Barley Coordinated Agricultural Project (CAP and development of winter habit malting barley varieties is a key objective of the U.S. barley research community. The objective of this work was to detect quantitative trait loci (QTL for malting quality traits in a winter breeding program that is a component of the U.S. Barley CAP. We studied the association between five malting quality traits and 3072 single nucleotide polymorphisms (SNPs from the barley oligonucleotide pool assay (BOPA 1 and 2, assayed in advanced inbred lines from the Oregon State University (OSU breeding program from three germplasm arrays (CAP I, CAP II, and CAP III. After comparing 16 models we selected a structured association model with posterior probabilities inferred from software STRUCTURE (QK approach to use on all germplasm arrays. Most of the marker-trait associations are germplasm- and environment-specific and close to previously mapped genes and QTL relevant for malt and beer quality. We found alleles fixed by random genetic drift, novel unmasked alleles, and genetic-background interaction. In a relatively small population size study we provide strong evidence for detecting true QTL.

Genes and quality trait loci (QTLs) associated with firmness in Malus x domestica

KAUST Repository

Marondedze, Claudius

2013-03-31

Fruit firmness, a quality quantitative trait, has long been established as a key textural property and one of the essential parameters for estimating ripening and shelf life of apples. Loss of firmness, also referred to as fruit softening, is undesirable in apples and represents a serious problem for growers in many countries. This results in the reduction of apple shelf life and in turn influences its commercialization. Low firmness impacts negatively on the sensory values of juiciness, crunchiness and crispness. Fruit firmness is affected by the inheritance of alleles at multiple loci and their possible interactions with the environment. Identification of these loci is key for the determination of genetic candidate markers that can be implemented in marker assisted selection and breeding for trees and/or cultivars that can yield firmer fruits with economic value. In turn, this technique can help reduce the time needed to evaluate plants and new cultivars could become available faster. This review provides an overview of quantitative trait loci (QTL), including additional putative QTLs that we have identified, and genes associated with firmness and their importance to biotechnology, the breeding industry and eventually the consumers.

Genome-wide quantitative trait loci mapping of the human cerebrospinal fluid proteome.

Science.gov (United States)

Sasayama, Daimei; Hattori, Kotaro; Ogawa, Shintaro; Yokota, Yuuki; Matsumura, Ryo; Teraishi, Toshiya; Hori, Hiroaki; Ota, Miho; Yoshida, Sumiko; Kunugi, Hiroshi

2017-01-01

Cerebrospinal fluid (CSF) is virtually the only one accessible source of proteins derived from the central nervous system (CNS) of living humans and possibly reflects the pathophysiology of a variety of neuropsychiatric diseases. However, little is known regarding the genetic basis of variation in protein levels of human CSF. We examined CSF levels of 1,126 proteins in 133 subjects and performed a genome-wide association analysis of 514,227 single nucleotide polymorphisms (SNPs) to detect protein quantitative trait loci (pQTLs). To be conservative, Spearman's correlation was used to identify an association between genotypes of SNPs and protein levels. A total of 421 cis and 25 trans SNP-protein pairs were significantly correlated at a false discovery rate (FDR) of less than 0.01 (nominal P genome-wide association studies. The present findings suggest that genetic variations play an important role in the regulation of protein expression in the CNS. The obtained database may serve as a valuable resource to understand the genetic bases for CNS protein expression pattern in humans. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Genetic and Physiological Characterization of Two Clusters of Quantitative Trait Loci Associated With Seed Dormancy and Plant Height in Rice

OpenAIRE

Ye, Heng; Beighley, Donn H.; Feng, Jiuhuan; Gu, Xing-You

2013-01-01

Seed dormancy and plant height have been well-studied in plant genetics, but their relatedness and shared regulatory mechanisms in natural variants remain unclear. The introgression of chromosomal segments from weedy into cultivated rice (Oryza sativa) prompted the detection of two clusters (qSD1-2/qPH1 and qSD7-2/qPH7) of quantitative trait loci both associated with seed dormancy and plant height. Together, these two clusters accounted for >96% of the variances for plant height and ~71% of t...

Association Mapping of Quantitative Trait Loci for Mineral Element Contents in Whole Grain Rice (Oryza sativa L.).

Science.gov (United States)

Huang, Yan; Sun, Chengxiao; Min, Jie; Chen, Yaling; Tong, Chuan; Bao, Jinsong

2015-12-23

Mineral elements in brown rice grain play an important role in human health. In this study, variations in the content of iron (Fe), zinc (Zn), selenium (Se), cadmium (Cd), and lead (Pb) in 378 accessions of brown rice were investigated, and association mapping was used to detect the quantitative trait loci (QTLs) responsible for the variation. Among seven subpopulations, the mean values of Zn and Cd in the japonica group were significantly higher than in the indica groups. The population structure accounted for from 5.7% (Se) to 22.1% (Pb) of the total variation. Correlation analyses showed that Pb was positively correlated with the other minerals (P rice grain by marker-assisted selection (MAS).

Genome-wide Association Study to Identify Quantitative Trait Loci for Meat and Carcass Quality Traits in Berkshire

Science.gov (United States)

Iqbal, Asif; Kim, You-Sam; Kang, Jun-Mo; Lee, Yun-Mi; Rai, Rajani; Jung, Jong-Hyun; Oh, Dong-Yup; Nam, Ki-Chang; Lee, Hak-Kyo; Kim, Jong-Joo

2015-01-01

Meat and carcass quality attributes are of crucial importance influencing consumer preference and profitability in the pork industry. A set of 400 Berkshire pigs were collected from Dasan breeding farm, Namwon, Chonbuk province, Korea that were born between 2012 and 2013. To perform genome wide association studies (GWAS), eleven meat and carcass quality traits were considered, including carcass weight, backfat thickness, pH value after 24 hours (pH24), Commission Internationale de l’Eclairage lightness in meat color (CIE L), redness in meat color (CIE a), yellowness in meat color (CIE b), filtering, drip loss, heat loss, shear force and marbling score. All of the 400 animals were genotyped with the Porcine 62K SNP BeadChips (Illumina Inc., USA). A SAS general linear model procedure (SAS version 9.2) was used to pre-adjust the animal phenotypes before GWAS with sire and sex effects as fixed effects and slaughter age as a covariate. After fitting the fixed and covariate factors in the model, the residuals of the phenotype regressed on additive effects of each single nucleotide polymorphism (SNP) under a linear regression model (PLINK version 1.07). The significant SNPs after permutation testing at a chromosome-wise level were subjected to stepwise regression analysis to determine the best set of SNP markers. A total of 55 significant (p<0.05) SNPs or quantitative trait loci (QTL) were detected on various chromosomes. The QTLs explained from 5.06% to 8.28% of the total phenotypic variation of the traits. Some QTLs with pleiotropic effect were also identified. A pair of significant QTL for pH24 was also found to affect both CIE L and drip loss percentage. The significant QTL after characterization of the functional candidate genes on the QTL or around the QTL region may be effectively and efficiently used in marker assisted selection to achieve enhanced genetic improvement of the trait considered. PMID:26580276

Genome-wide Association Study to Identify Quantitative Trait Loci for Meat and Carcass Quality Traits in Berkshire

Directory of Open Access Journals (Sweden)

Asif Iqbal

2015-11-01

Full Text Available Meat and carcass quality attributes are of crucial importance influencing consumer preference and profitability in the pork industry. A set of 400 Berkshire pigs were collected from Dasan breeding farm, Namwon, Chonbuk province, Korea that were born between 2012 and 2013. To perform genome wide association studies (GWAS, eleven meat and carcass quality traits were considered, including carcass weight, backfat thickness, pH value after 24 hours (pH24, Commission Internationale de l’Eclairage lightness in meat color (CIE L, redness in meat color (CIE a, yellowness in meat color (CIE b, filtering, drip loss, heat loss, shear force and marbling score. All of the 400 animals were genotyped with the Porcine 62K SNP BeadChips (Illumina Inc., USA. A SAS general linear model procedure (SAS version 9.2 was used to pre-adjust the animal phenotypes before GWAS with sire and sex effects as fixed effects and slaughter age as a covariate. After fitting the fixed and covariate factors in the model, the residuals of the phenotype regressed on additive effects of each single nucleotide polymorphism (SNP under a linear regression model (PLINK version 1.07. The significant SNPs after permutation testing at a chromosome-wise level were subjected to stepwise regression analysis to determine the best set of SNP markers. A total of 55 significant (p<0.05 SNPs or quantitative trait loci (QTL were detected on various chromosomes. The QTLs explained from 5.06% to 8.28% of the total phenotypic variation of the traits. Some QTLs with pleiotropic effect were also identified. A pair of significant QTL for pH24 was also found to affect both CIE L and drip loss percentage. The significant QTL after characterization of the functional candidate genes on the QTL or around the QTL region may be effectively and efficiently used in marker assisted selection to achieve enhanced genetic improvement of the trait considered.

Joint analysis of quantitative trait loci and major-effect causative mutations affecting meat quality and carcass composition traits in pigs.

Science.gov (United States)

Cherel, Pierre; Pires, José; Glénisson, Jérôme; Milan, Denis; Iannuccelli, Nathalie; Hérault, Frédéric; Damon, Marie; Le Roy, Pascale

2011-08-29

Detection of quantitative trait loci (QTLs) affecting meat quality traits in pigs is crucial for the design of efficient marker-assisted selection programs and to initiate efforts toward the identification of underlying polymorphisms. The RYR1 and PRKAG3 causative mutations, originally identified from major effects on meat characteristics, can be used both as controls for an overall QTL detection strategy for diversely affected traits and as a scale for detected QTL effects. We report on a microsatellite-based QTL detection scan including all autosomes for pig meat quality and carcass composition traits in an F2 population of 1,000 females and barrows resulting from an intercross between a Pietrain and a Large White-Hampshire-Duroc synthetic sire line. Our QTL detection design allowed side-by-side comparison of the RYR1 and PRKAG3 mutation effects seen as QTLs when segregating at low frequencies (0.03-0.08), with independent QTL effects detected from most of the same population, excluding any carrier of these mutations. Large QTL effects were detected in the absence of the RYR1 and PRKGA3 mutations, accounting for 12.7% of phenotypic variation in loin colour redness CIE-a* on SSC6 and 15% of phenotypic variation in glycolytic potential on SSC1. We detected 8 significant QTLs with effects on meat quality traits and 20 significant QTLs for carcass composition and growth traits under these conditions. In control analyses including mutation carriers, RYR1 and PRKAG3 mutations were detected as QTLs, from highly significant to suggestive, and explained 53% to 5% of the phenotypic variance according to the trait. Our results suggest that part of muscle development and backfat thickness effects commonly attributed to the RYR1 mutation may be a consequence of linkage with independent QTLs affecting those traits. The proportion of variation explained by the most significant QTLs detected in this work is close to the influence of major-effect mutations on the least affected

Joint analysis of quantitative trait loci and major-effect causative mutations affecting meat quality and carcass composition traits in pigs

Directory of Open Access Journals (Sweden)

Iannuccelli Nathalie

2011-08-01

Full Text Available Abstract Background Detection of quantitative trait loci (QTLs affecting meat quality traits in pigs is crucial for the design of efficient marker-assisted selection programs and to initiate efforts toward the identification of underlying polymorphisms. The RYR1 and PRKAG3 causative mutations, originally identified from major effects on meat characteristics, can be used both as controls for an overall QTL detection strategy for diversely affected traits and as a scale for detected QTL effects. We report on a microsatellite-based QTL detection scan including all autosomes for pig meat quality and carcass composition traits in an F2 population of 1,000 females and barrows resulting from an intercross between a Pietrain and a Large White-Hampshire-Duroc synthetic sire line. Our QTL detection design allowed side-by-side comparison of the RYR1 and PRKAG3 mutation effects seen as QTLs when segregating at low frequencies (0.03-0.08, with independent QTL effects detected from most of the same population, excluding any carrier of these mutations. Results Large QTL effects were detected in the absence of the RYR1 and PRKGA3 mutations, accounting for 12.7% of phenotypic variation in loin colour redness CIE-a* on SSC6 and 15% of phenotypic variation in glycolytic potential on SSC1. We detected 8 significant QTLs with effects on meat quality traits and 20 significant QTLs for carcass composition and growth traits under these conditions. In control analyses including mutation carriers, RYR1 and PRKAG3 mutations were detected as QTLs, from highly significant to suggestive, and explained 53% to 5% of the phenotypic variance according to the trait. Conclusions Our results suggest that part of muscle development and backfat thickness effects commonly attributed to the RYR1 mutation may be a consequence of linkage with independent QTLs affecting those traits. The proportion of variation explained by the most significant QTLs detected in this work is close to the

Detection and characterization of quantitative trait loci for meat quality traits in pigs

NARCIS (Netherlands)

Koning, de D.J.; Harlizius, B.; Rattink, A.P.; Groenen, M.A.M.; Brascamp, E.W.; Arendonk, van J.A.M.

2001-01-01

In an experimental cross between Meishan and Dutch Large White and Landrace lines, 785 F2 animals with carcass information and their parents were typed for molecular markers covering the entire porcine genome. Linkage was studied between these markers and eight meat quality traits. Quantitative

Quantitative trait loci for broomrape (Orobanche cumana Wallr.) resistance in sunflower.

Science.gov (United States)

Pérez-Vich, B; Akhtouch, B; Knapp, S J; Leon, A J; Velasco, L; Fernández-Martínez, J M; Berry, S T

2004-06-01

Broomrape (Orobanche cumana Wallr.) is a root parasite of sunflower that is regarded as one of the most important constraints of sunflower production in the Mediterranean region. Breeding for resistance is the most effective method of control. P-96 is a sunflower line which shows dominant resistance to broomrape race E and recessive resistance to the very new race F. The objective of this study was to map and characterize quantitative trait loci (QTL) for resistance to race E and to race F of broomrape in P-96. A population from a cross between P-96 and the susceptible line P-21 was phenotyped for broomrape resistance in four experiments, two for race E and two for race F, by measuring different resistance parameters (resistance or susceptibility, number of broomrape per plant, and proportion of resistant plants per F(3) family). This population was also genotyped with microsatellite and RFLP markers. A linkage map comprising 103 marker loci distributed on 17 linkage groups was developed, and composite interval mapping analyses were performed. In total, five QTL ( or1.1, or3.1, or7.1 or13.1 and or13.2) for resistance to race E and six QTL ( or1.1, or4.1, or5.1, or13.1, or13.2 and or16.1) for resistance to race F of broomrape were detected on 7 of the 17 linkage groups. Phenotypic variance for race E resistance was mainly explained by the major QTL or3.1 associated to the resistance or susceptibility character ( R(2)=59%), while race F resistance was explained by QTL with a small to moderate effect ( R(2) from 15.0% to 38.7%), mainly associated with the number of broomrape per plant. Or3.1 was race E-specific, while or1.1, or13.1 and or13.2 of were non-race specific. Or13.1, and or13.2 were stable across the four experiments. Or3.1, and or7.1 were stable over the two race E experiments and or1.1 and or5.1 over the two race F experiments. The results from this study suggest that resistance to broomrape in sunflower is controlled by a combination of qualitative, race

Analysis of heterosis and quantitative trait loci for kernel shape related traits using triple testcross population in maize.

Directory of Open Access Journals (Sweden)

Lu Jiang

Full Text Available Kernel shape related traits (KSRTs have been shown to have important influences on grain yield. The previous studies that emphasize kernel length (KL and kernel width (KW lack a comprehensive evaluation of characters affecting kernel shape. In this study, materials of the basic generations (B73, Mo17, and B73 × Mo17, 82 intermated B73 × Mo17 (IBM individuals, and the corresponding triple testcross (TTC populations were used to evaluate heterosis, investigate correlations, and characterize the quantitative trait loci (QTL for six KSRTs: KL, KW, length to width ratio (LWR, perimeter length (PL, kernel area (KA, and circularity (CS. The results showed that the mid-parent heterosis (MPH for most of the KSRTs was moderate. The performance of KL, KW, PL, and KA exhibited significant positive correlation with heterozygosity but their Pearson's R values were low. Among KSRTs, the strongest significant correlation was found between PL and KA with R values was up to 0.964. In addition, KW, PL, KA, and CS were shown to be significant positive correlation with 100-kernel weight (HKW. 28 QTLs were detected for KSRTs in which nine were augmented additive, 13 were augmented dominant, and six were dominance × additive epistatic. The contribution of a single QTL to total phenotypic variation ranged from 2.1% to 32.9%. Furthermore, 19 additive × additive digenic epistatic interactions were detected for all KSRTs with the highest total R2 for KW (78.8%, and nine dominance × dominance digenic epistatic interactions detected for KL, LWR, and CS with the highest total R2 (55.3%. Among significant digenic interactions, most occurred between genomic regions not mapped with main-effect QTLs. These findings display the complexity of the genetic basis for KSRTs and enhance our understanding on heterosis of KSRTs from the quantitative genetic perspective.

Bilaterally Asymmetric Effects of Quantitative Trait Loci (QTLs): QTLs That Affect Laxity in the Right Versus Left Coxofemoral (Hip) Joints of the Dog (Canis familiaris)

OpenAIRE

Chase, Kevin; Lawler, Dennis F.; Adler, Fred R.; Ostrander, Elaine A.; Lark, Karl G.

2004-01-01

In dogs hip joint laxity that can lead to degenerative joint disease (DJD) is frequent and heritable, providing a genetic model for some aspects of the human disease. We have used Portuguese water dogs (PWDs) to identify Quantitative trait loci (QTLs) that regulate laxity in the hip joint.A population of 286 PWDs, each characterized by ca. 500 molecular genetic markers, was analyzed for subluxation of the hip joint as measured by the Norberg angle, a quantitative radiographic measure of laxit...

Coincidence in map positions between pathogen-induced defense-responsive genes and quantitative resistance loci in rice

Institute of Scientific and Technical Information of China (English)

熊敏; 王石平; 张启发

2002-01-01

Quantitative disease resistance conferred by quantitative trait loci (QTLs) is presumably of wider spectrum and durable. Forty-four cDNA clones, representing 44 defense-responsive genes, were fine mapped to 56 loci distributed on 9 of the 12 rice chromosomes. The locations of 32 loci detected by 27 cDNA clones were associated with previously identified resistance QTLs for different rice diseases, including blast, bacterial blight, sheath blight and yellow mottle virus. The loci detected by the same multiple-copy cDNA clones were frequently located on similar locations of different chromosomes. Some of the multiple loci detected by the same clones were all associated with resistance QTLs. These results suggest that some of the genes may be important components in regulation of defense responses against pathogen invasion and they may be the candidates for studying the mechanism of quantitative disease resistance in rice.

Fine mapping quantitative trait loci under selective phenotyping strategies based on linkage and linkage disequilibrium criteria

DEFF Research Database (Denmark)

Ansari-Mahyari, S; Berg, P; Lund, M S

2009-01-01

disequilibrium-based sampling criteria (LDC) for selecting individuals to phenotype are compared to random phenotyping in a quantitative trait loci (QTL) verification experiment using stochastic simulation. Several strategies based on LAC and LDC for selecting the most informative 30%, 40% or 50% of individuals...... for phenotyping to extract maximum power and precision in a QTL fine mapping experiment were developed and assessed. Linkage analyses for the mapping was performed for individuals sampled on LAC within families and combined linkage disequilibrium and linkage analyses was performed for individuals sampled across...... the whole population based on LDC. The results showed that selecting individuals with similar haplotypes to the paternal haplotypes (minimum recombination criterion) using LAC compared to random phenotyping gave at least the same power to detect a QTL but decreased the accuracy of the QTL position. However...

A family-based joint test for mean and variance heterogeneity for quantitative traits.

Science.gov (United States)

Cao, Ying; Maxwell, Taylor J; Wei, Peng

2015-01-01

Traditional quantitative trait locus (QTL) analysis focuses on identifying loci associated with mean heterogeneity. Recent research has discovered loci associated with phenotype variance heterogeneity (vQTL), which is important in studying genetic association with complex traits, especially for identifying gene-gene and gene-environment interactions. While several tests have been proposed to detect vQTL for unrelated individuals, there are no tests for related individuals, commonly seen in family-based genetic studies. Here we introduce a likelihood ratio test (LRT) for identifying mean and variance heterogeneity simultaneously or for either effect alone, adjusting for covariates and family relatedness using a linear mixed effect model approach. The LRT test statistic for normally distributed quantitative traits approximately follows χ(2)-distributions. To correct for inflated Type I error for non-normally distributed quantitative traits, we propose a parametric bootstrap-based LRT that removes the best linear unbiased prediction (BLUP) of family random effect. Simulation studies show that our family-based test controls Type I error and has good power, while Type I error inflation is observed when family relatedness is ignored. We demonstrate the utility and efficiency gains of the proposed method using data from the Framingham Heart Study to detect loci associated with body mass index (BMI) variability. © 2014 John Wiley & Sons Ltd/University College London.

Mapping Quantitative Trait Loci (QTL) in sheep. III. QTL for carcass composition traits derived from CT scans and aligned with a meta-assembly for sheep and cattle carcass QTL.

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Cavanagh, Colin R; Jonas, Elisabeth; Hobbs, Matthew; Thomson, Peter C; Tammen, Imke; Raadsma, Herman W

2010-09-16

An (Awassi × Merino) × Merino single-sire backcross family with 165 male offspring was used to map quantitative trait loci (QTL) for body composition traits on a framework map of 189 microsatellite loci across all autosomes. Two cohorts were created from the experimental progeny to represent alternative maturity classes for body composition assessment. Animals were raised under paddock conditions prior to entering the feedlot for a 90-day fattening phase. Body composition traits were derived in vivo at the end of the experiment prior to slaughter at 2 (cohort 1) and 3.5 (cohort 2) years of age, using computed tomography. Image analysis was used to gain accurate predictions for 13 traits describing major fat depots, lean muscle, bone, body proportions and body weight which were used for single- and two-QTL mapping analysis. Using a maximum-likelihood approach, three highly significant (LOD ≥ 3), 15 significant (LOD ≥ 2), and 11 suggestive QTL (1.7 ≤ LOD < 2) were detected on eleven chromosomes. Regression analysis confirmed 28 of these QTL and an additional 17 suggestive (P < 0.1) and two significant (P < 0.05) QTL were identified using this method. QTL with pleiotropic effects for two or more tissues were identified on chromosomes 1, 6, 10, 14, 16 and 23. No tissue-specific QTL were identified.A meta-assembly of ovine QTL for carcass traits from this study and public domain sources was performed and compared with a corresponding bovine meta-assembly. The assembly demonstrated QTL with effects on carcass composition in homologous regions on OAR1, 2, 6 and 21.

Annotation of loci from genome-wide association studies using tissue-specific quantitative interaction proteomics

DEFF Research Database (Denmark)

Lundby, Alicia; Rossin, Elizabeth J.; Steffensen, Annette B.

2014-01-01

Genome-wide association studies (GWAS) have identified thousands of loci associated with complex traits, but it is challenging to pinpoint causal genes in these loci and to exploit subtle association signals. We used tissue-specific quantitative interaction proteomics to map a network of five genes...... involved in the Mendelian disorder long QT syndrome (LOTS). We integrated the LOTS network with GWAS loci from the corresponding common complex trait, QT-interval variation, to identify candidate genes that were subsequently confirmed in Xenopus laevis oocytes and zebrafish. We used the LOTS protein...... network to filter weak GWAS signals by identifying single-nucleotide polymorphisms (SNPs) in proximity to genes in the network supported by strong proteomic evidence. Three SNPs passing this filter reached genome-wide significance after replication genotyping. Overall, we present a general strategy...

The bovine QTL viewer: a web accessible database of bovine Quantitative Trait Loci

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Xavier Suresh R

2006-06-01

Full Text Available Abstract Background Many important agricultural traits such as weight gain, milk fat content and intramuscular fat (marbling in cattle are quantitative traits. Most of the information on these traits has not previously been integrated into a genomic context. Without such integration application of these data to agricultural enterprises will remain slow and inefficient. Our goal was to populate a genomic database with data mined from the bovine quantitative trait literature and to make these data available in a genomic context to researchers via a user friendly query interface. Description The QTL (Quantitative Trait Locus data and related information for bovine QTL are gathered from published work and from existing databases. An integrated database schema was designed and the database (MySQL populated with the gathered data. The bovine QTL Viewer was developed for the integration of QTL data available for cattle. The tool consists of an integrated database of bovine QTL and the QTL viewer to display QTL and their chromosomal position. Conclusion We present a web accessible, integrated database of bovine (dairy and beef cattle QTL for use by animal geneticists. The viewer and database are of general applicability to any livestock species for which there are public QTL data. The viewer can be accessed at http://bovineqtl.tamu.edu.

Detection of quantitative trait loci for carcass composition traits in pigs

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Renard Christine

2002-11-01

Full Text Available Abstract A quantitative trait locus (QTL analysis of carcass composition data from a three-generation experimental cross between Meishan (MS and Large White (LW pig breeds is presented. A total of 488 F2 males issued from six F1 boars and 23 F1 sows, the progeny of six LW boars and six MS sows, were slaughtered at approximately 80 kg live weight and were submitted to a standardised cutting of the carcass. Fifteen traits, i.e. dressing percentage, loin, ham, shoulder, belly, backfat, leaf fat, feet and head weights, two backfat thickness and one muscle depth measurements, ham + loin and back + leaf fat percentages and estimated carcass lean content were analysed. Animals were typed for a total of 137 markers covering the entire porcine genome. Analyses were performed using a line-cross (LC regression method where founder lines were assumed to be fixed for different QTL alleles and a half/full sib (HFS maximum likelihood method where allele substitution effects were estimated within each half-/full-sib family. Additional analyses were performed to search for multiple linked QTL and imprinting effects. Significant gene effects were evidenced for both leanness and fatness traits in the telomeric regions of SSC 1q and SSC 2p, on SSC 4, SSC 7 and SSC X. Additional significant QTL were identified for ham weight on SSC 5, for head weight on SSC 1 and SSC 7, for feet weight on SSC 7 and for dressing percentage on SSC X. LW alleles were associated with a higher lean content and a lower fat content of the carcass, except for the fatness trait on SSC 7. Suggestive evidence of linked QTL on SSC 7 and of imprinting effects on SSC 6, SSC 7, SSC 9 and SSC 17 were also obtained.

Chromosomal mapping of quantitative trait loci controlling elastin content in rat aorta.

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Gauguier, Dominique; Behmoaras, Jacques; Argoud, Karène; Wilder, Steven P; Pradines, Christelle; Bihoreau, Marie Thérèse; Osborne-Pellegrin, Mary; Jacob, Marie Paule

2005-03-01

Extracellular matrix molecules such as elastin and collagens provide mechanical support to the vessel wall. In addition to its structural role, elastin is a regulator that maintains homeostasis through biologic signaling. Genetically determined minor modifications in elastin and collagen in the aorta could influence the onset and evolution of arterial pathology, such as hypertension and its complications. We previously demonstrated that the inbred Brown Norway (BN) rat shows an aortic elastin deficit in both abdominal and thoracic segments, partly because of a decrease in tropoelastin synthesis when compared with the LOU rat, that elastin gene polymorphisms in these strains do not significantly account for. After a genome-wide search for quantitative trait loci (QTL) influencing the aortic elastin, collagen, and cell protein contents in an F2 population derived from BN and LOU rats, we identified on chromosomes 2 and 14, 3 QTL specifically controlling elastin levels, and a further highly significant QTL on chromosome 17 linked to the level of cell proteins. We also mapped 3 highly significant QTL linked to body weight (on chromosomes 1 and 3) and heart weight (on chromosome 1) in the cross. This study demonstrates the polygenic control of the content of key components of the arterial wall. Such information represents a first step in understanding possible mechanisms involved in dysregulation of these parameters in arterial pathology.

Metabolomic Quantitative Trait Loci (mQTL Mapping Implicates the Ubiquitin Proteasome System in Cardiovascular Disease Pathogenesis.

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William E Kraus

2015-11-01

Full Text Available Levels of certain circulating short-chain dicarboxylacylcarnitine (SCDA, long-chain dicarboxylacylcarnitine (LCDA and medium chain acylcarnitine (MCA metabolites are heritable and predict cardiovascular disease (CVD events. Little is known about the biological pathways that influence levels of most of these metabolites. Here, we analyzed genetics, epigenetics, and transcriptomics with metabolomics in samples from a large CVD cohort to identify novel genetic markers for CVD and to better understand the role of metabolites in CVD pathogenesis. Using genomewide association in the CATHGEN cohort (N = 1490, we observed associations of several metabolites with genetic loci. Our strongest findings were for SCDA metabolite levels with variants in genes that regulate components of endoplasmic reticulum (ER stress (USP3, HERC1, STIM1, SEL1L, FBXO25, SUGT1 These findings were validated in a second cohort of CATHGEN subjects (N = 2022, combined p = 8.4x10-6-2.3x10-10. Importantly, variants in these genes independently predicted CVD events. Association of genomewide methylation profiles with SCDA metabolites identified two ER stress genes as differentially methylated (BRSK2 and HOOK2. Expression quantitative trait loci (eQTL pathway analyses driven by gene variants and SCDA metabolites corroborated perturbations in ER stress and highlighted the ubiquitin proteasome system (UPS arm. Moreover, culture of human kidney cells in the presence of levels of fatty acids found in individuals with cardiometabolic disease, induced accumulation of SCDA metabolites in parallel with increases in the ER stress marker BiP. Thus, our integrative strategy implicates the UPS arm of the ER stress pathway in CVD pathogenesis, and identifies novel genetic loci associated with CVD event risk.

Complex pedigree analysis to detect quantitative trait loci in dairy cattle

NARCIS (Netherlands)

Bink, M.C.A.M.

1998-01-01

In dairy cattle, many quantitative traits of economic importance show phenotypic variation. For breeding purposes the analysis of this phenotypic variation and uncovering the contribution of genetic factors is very important. Usually, the individual gene effects contributing to the

Identification of genetic loci shared between schizophrenia and the Big Five personality traits.

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Smeland, Olav B; Wang, Yunpeng; Lo, Min-Tzu; Li, Wen; Frei, Oleksandr; Witoelar, Aree; Tesli, Martin; Hinds, David A; Tung, Joyce Y; Djurovic, Srdjan; Chen, Chi-Hua; Dale, Anders M; Andreassen, Ole A

2017-05-22

Schizophrenia is associated with differences in personality traits, and recent studies suggest that personality traits and schizophrenia share a genetic basis. Here we aimed to identify specific genetic loci shared between schizophrenia and the Big Five personality traits using a Bayesian statistical framework. Using summary statistics from genome-wide association studies (GWAS) on personality traits in the 23andMe cohort (n = 59,225) and schizophrenia in the Psychiatric Genomics Consortium cohort (n = 82,315), we evaluated overlap in common genetic variants. The Big Five personality traits neuroticism, extraversion, openness, agreeableness and conscientiousness were measured using a web implementation of the Big Five Inventory. Applying the conditional false discovery rate approach, we increased discovery of genetic loci and identified two loci shared between neuroticism and schizophrenia and six loci shared between openness and schizophrenia. The study provides new insights into the relationship between personality traits and schizophrenia by highlighting genetic loci involved in their common genetic etiology.

Quantitative trait loci for resistance to stripe rust of wheat revealed using global field nurseries and opportunities for stacking resistance genes.

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Bokore, Firdissa E; Cuthbert, Richard D; Knox, Ron E; Randhawa, Harpinder S; Hiebert, Colin W; DePauw, Ron M; Singh, Asheesh K; Singh, Arti; Sharpe, Andrew G; N'Diaye, Amidou; Pozniak, Curtis J; McCartney, Curt; Ruan, Yuefeng; Berraies, Samia; Meyer, Brad; Munro, Catherine; Hay, Andy; Ammar, Karim; Huerta-Espino, Julio; Bhavani, Sridhar

2017-12-01

Quantitative trait loci controlling stripe rust resistance were identified in adapted Canadian spring wheat cultivars providing opportunity for breeders to stack loci using marker-assisted breeding. Stripe rust or yellow rust, caused by Puccinia striiformis Westend. f. sp. tritici Erikss., is a devastating disease of common wheat (Triticum aestivum L.) in many regions of the world. The objectives of this research were to identify and map quantitative trait loci (QTL) associated with stripe rust resistance in adapted Canadian spring wheat cultivars that are effective globally, and investigate opportunities for stacking resistance. Doubled haploid (DH) populations from the crosses Vesper/Lillian, Vesper/Stettler, Carberry/Vesper, Stettler/Red Fife and Carberry/AC Cadillac were phenotyped for stripe rust severity and infection response in field nurseries in Canada (Lethbridge and Swift Current), New Zealand (Lincoln), Mexico (Toluca) and Kenya (Njoro), and genotyped with SNP markers. Six QTL for stripe rust resistance in the population of Vesper/Lillian, five in Vesper/Stettler, seven in Stettler/Red Fife, four in Carberry/Vesper and nine in Carberry/AC Cadillac were identified. Lillian contributed stripe rust resistance QTL on chromosomes 4B, 5A, 6B and 7D, AC Cadillac on 2A, 2B, 3B and 5B, Carberry on 1A, 1B, 4A, 4B, 7A and 7D, Stettler on 1A, 2A, 3D, 4A, 5B and 6A, Red Fife on 2D, 3B and 4B, and Vesper on 1B, 2B and 7A. QTL on 1A, 1B, 2A, 2B, 3B, 4A, 4B, 5B, 7A and 7D were observed in multiple parents. The populations are compelling sources of recombination of many stripe rust resistance QTL for stacking disease resistance. Gene pyramiding should be possible with little chance of linkage drag of detrimental genes as the source parents were mostly adapted cultivars widely grown in Canada.

Pathogen-specific effects of quantitative trait loci affecting clinical mastitis and somatic cell count in danish holstein cattle

DEFF Research Database (Denmark)

Sørensen, Lars Peter; Guldbrandtsen, Bernt; Thomasen, J.R.

2008-01-01

The aim of this study was to investigate whether quantitative trait loci (QTL) affecting the risk of clinical mastitis (CM) and QTL affecting somatic cell score (SCS) exhibit pathogen-specific effects on the incidence of mastitis. Bacteriological data on mastitis pathogens were used to investigate...... pathogen specificity of QTL affecting treatments of mastitis in first parity (CM1), second parity (CM2), and third parity (CM3), and QTL affecting SCS. The 5 most common mastitis pathogens in the Danish dairy population were analyzed: Streptococcus dysgalactiae, Escherichia coli, coagulase...... against coagulase-negative staphylococci and Strep. uberis. Our results show that particular mastitis QTL are highly likely to exhibit pathogen-specificity. However, the results should be interpreted carefully because the results are sensitive to the sampling method and method of analysis. Field data were...

Effects of normalization on quantitative traits in association test

Science.gov (United States)

2009-01-01

Background Quantitative trait loci analysis assumes that the trait is normally distributed. In reality, this is often not observed and one strategy is to transform the trait. However, it is not clear how much normality is required and which transformation works best in association studies. Results We performed simulations on four types of common quantitative traits to evaluate the effects of normalization using the logarithm, Box-Cox, and rank-based transformations. The impact of sample size and genetic effects on normalization is also investigated. Our results show that rank-based transformation gives generally the best and consistent performance in identifying the causal polymorphism and ranking it highly in association tests, with a slight increase in false positive rate. Conclusion For small sample size or genetic effects, the improvement in sensitivity for rank transformation outweighs the slight increase in false positive rate. However, for large sample size and genetic effects, normalization may not be necessary since the increase in sensitivity is relatively modest. PMID:20003414

Effects of normalization on quantitative traits in association test

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Yap Von Bing

2009-12-01

Full Text Available Abstract Background Quantitative trait loci analysis assumes that the trait is normally distributed. In reality, this is often not observed and one strategy is to transform the trait. However, it is not clear how much normality is required and which transformation works best in association studies. Results We performed simulations on four types of common quantitative traits to evaluate the effects of normalization using the logarithm, Box-Cox, and rank-based transformations. The impact of sample size and genetic effects on normalization is also investigated. Our results show that rank-based transformation gives generally the best and consistent performance in identifying the causal polymorphism and ranking it highly in association tests, with a slight increase in false positive rate. Conclusion For small sample size or genetic effects, the improvement in sensitivity for rank transformation outweighs the slight increase in false positive rate. However, for large sample size and genetic effects, normalization may not be necessary since the increase in sensitivity is relatively modest.

Genome-Wide Mapping of Growth-Related Quantitative Trait Loci in Orange-Spotted Grouper (Epinephelus coioides) Using Double Digest Restriction-Site Associated DNA Sequencing (ddRADseq).

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Yu, Hui; You, Xinxin; Li, Jia; Liu, Hankui; Meng, Zining; Xiao, Ling; Zhang, Haifa; Lin, Hao-Ran; Zhang, Yong; Shi, Qiong

2016-04-06

Mapping of quantitative trait loci (QTL) is essential for the discovery of genetic structures that related to complex quantitative traits. In this study, we identified 264,072 raw SNPs (single-nucleotide polymorphisms) by double digest restriction site associated DNA sequencing (ddRADseq), and utilized 3029 of these SNPs to construct a genetic linkage map in orange-spotted grouper (Epinephelus coioides) using a regression mapping algorithm. The genetic map contained 24 linkage groups (LGs) spanning a total genetic distance of 1231.98 cM. Twenty-seven significant growth-related QTLs were identified. Furthermore, we identified 17 genes (fez2, alg3, ece2, arvcf, sla27a4, sgk223, camk2, prrc2b, mchr1, sardh, pappa, syk, tert, wdrcp91, ftz-f1, mate1 and notch1) including three (tert, ftz-f1 and notch1) that have been reported to be involved in fish growth. To summarize, we mapped growth-related QTLs in the orange-spotted grouper. These QTLs will be useful in marker-assisted selection (MAS) efforts to improve growth-related traits in this economically important fish.

Linkage Map Construction and Quantitative Trait Locus Analysis of Agronomic and Fiber Quality Traits in Cotton

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Michael A. Gore

2014-03-01

Full Text Available The superior fiber properties of L. serve as a source of novel variation for improving fiber quality in Upland cotton ( L., but introgression from has been largely unsuccessful due to hybrid breakdown and a lack of genetic and genomic resources. In an effort to overcome these limitations, we constructed a linkage map and conducted a quantitative trait locus (QTL analysis of 10 agronomic and fiber quality traits in a recombinant inbred mapping population derived from a cross between TM-1, an Upland cotton line, and NM24016, an elite line with stabilized introgression from . The linkage map consisted of 429 simple-sequence repeat (SSR and 412 genotyping-by-sequencing (GBS-based single-nucleotide polymorphism (SNP marker loci that covered half of the tetraploid cotton genome. Notably, the 841 marker loci were unevenly distributed among the 26 chromosomes of tetraploid cotton. The 10 traits evaluated on the TM-1 × NM24016 population in a multienvironment trial were highly heritable, and most of the fiber traits showed considerable transgressive variation. Through the QTL analysis, we identified a total of 28 QTLs associated with the 10 traits. Our study provides a novel resource that can be used by breeders and geneticists for the genetic improvement of agronomic and fiber quality traits in Upland cotton.

Two-part zero-inflated negative binomial regression model for quantitative trait loci mapping with count trait.

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Moghimbeigi, Abbas

2015-05-07

Poisson regression models provide a standard framework for quantitative trait locus (QTL) mapping of count traits. In practice, however, count traits are often over-dispersed relative to the Poisson distribution. In these situations, the zero-inflated Poisson (ZIP), zero-inflated generalized Poisson (ZIGP) and zero-inflated negative binomial (ZINB) regression may be useful for QTL mapping of count traits. Added genetic variables to the negative binomial part equation, may also affect extra zero data. In this study, to overcome these challenges, I apply two-part ZINB model. The EM algorithm with Newton-Raphson method in the M-step uses for estimating parameters. An application of the two-part ZINB model for QTL mapping is considered to detect associations between the formation of gallstone and the genotype of markers. Copyright © 2015 Elsevier Ltd. All rights reserved.

Replicated analysis of the genetic architecture of quantitative traits in two wild great tit populations

NARCIS (Netherlands)

Santure, Anna W.; Poissant, Jocelyn; Cauwer, De Isabelle; Oers, Van Kees; Robinson, Matthew R.; Quinn, John L.; Groenen, M.A.M.; Visser, M.E.; Sheldon, Ben C.; Slate, Jon

2015-01-01

Currently, there is much debate on the genetic architecture of quantitative traits in wild populations. Is trait variation influenced by many genes of small effect or by a few genes of major effect? Where is additive genetic variation located in the genome? Do the same loci cause similar

Replicated analysis of the genetic architecture of quantitative traits in two wild great tit populations

NARCIS (Netherlands)

Santure, Anna W; Poissant, Jocelyn; De Cauwer, Isabelle; van Oers, Kees; Robinson, Matthew R; Quinn, John L; Groenen, Martien A M; Visser, Marcel E; Sheldon, Ben C; Slate, Jon

2015-01-01

Currently, there is much debate on the genetic architecture of quantitative traits in wild populations. Is trait variation influenced by many genes of small effect or by a few genes of major effect? Where is additive genetic variation located in the genome? Do the same loci cause similar phenotypic

Marker-assisted selection for improving quantitative traits of forage crops

International Nuclear Information System (INIS)

Dolstra, O.; Denneboom, C.; Vos, Ab L.F. de; Loo, E.N. van

2007-01-01

This chapter provides an example of using marker-assisted selection (MAS) for breeding perennial ryegrass (Lolium perenne), a pasture species. A mapping study had shown the presence of quantitative trait loci (QTL) for seven component traits of nitrogen use efficiency (NUE). The NUE-related QTL clustered in five chromosomal regions. These QTL were validated through divergent marker selection in an F 2 population. The criterion used for plant selection was a summation index based on the number of positive QTL alleles. The evaluation studies showed a strong indirect response of marker selection on NUE. Marker selection using a summation index such as applied here proved to be very effective for difficult and complex quantitative traits such as NUE. The strategy is easily applicable in outbreeding crops to raise the frequency of several desirable alleles simultaneously. (author)

Virulence attributes and hyphal growth of C. neoformans are quantitative traits and the MATalpha allele enhances filamentation.

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Xiaorong Lin

2006-11-01

Full Text Available Cryptococcus neoformans is a fungal human pathogen with a bipolar mating system. It undergoes a dimorphic transition from a unicellular yeast to hyphal filamentous growth during mating and monokaryotic fruiting. The traditional sexual cycle that leads to the production of infectious basidiospores involves cells of both alpha and a mating type. Monokaryotic fruiting is a modified form of sexual reproduction that involves cells of the same mating type, most commonly alpha, which is the predominant mating type in both the environment and clinical isolates. However, some a isolates can also undergo monokaryotic fruiting. To determine whether mating type and other genetic loci contribute to the differences in fruiting observed between alpha and a cells, we applied quantitative trait loci (QTL mapping to an inbred population of F2 progeny. We discovered that variation in hyphal length produced during fruiting is a quantitative trait resulting from the combined effects of multiple genetic loci, including the mating type (MAT locus. Importantly, the alpha allele of the MAT locus enhanced hyphal growth compared with the a allele. Other virulence traits, including melanization and growth at 39 degrees C, also are quantitative traits that share a common QTL with hyphal growth. The Mac1 transcription factor, encoded in this common QTL, regulates copper homeostasis. MAC1 allelic differences contribute to phenotypic variation, and mac1Delta mutants exhibit defects in filamentation, melanin production, and high temperature growth. Further characterization of these QTL regions will reveal additional quantitative trait genes controlling biological processes central to fungal development and pathogenicity.

An optimal strategy for functional mapping of dynamic trait loci.

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Jin, Tianbo; Li, Jiahan; Guo, Ying; Zhou, Xiaojing; Yang, Runqing; Wu, Rongling

2010-02-01

As an emerging powerful approach for mapping quantitative trait loci (QTLs) responsible for dynamic traits, functional mapping models the time-dependent mean vector with biologically meaningful equations and are likely to generate biologically relevant and interpretable results. Given the autocorrelation nature of a dynamic trait, functional mapping needs the implementation of the models for the structure of the covariance matrix. In this article, we have provided a comprehensive set of approaches for modelling the covariance structure and incorporated each of these approaches into the framework of functional mapping. The Bayesian information criterion (BIC) values are used as a model selection criterion to choose the optimal combination of the submodels for the mean vector and covariance structure. In an example for leaf age growth from a rice molecular genetic project, the best submodel combination was found between the Gaussian model for the correlation structure, power equation of order 1 for the variance and the power curve for the mean vector. Under this combination, several significant QTLs for leaf age growth trajectories were detected on different chromosomes. Our model can be well used to study the genetic architecture of dynamic traits of agricultural values.

Identification and Characterization of Quantitative Trait Loci for Shattering in Japonica Rice Landrace Jiucaiqing from Taihu Lake Valley, China

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Jinping Cheng

2016-11-01

Full Text Available Easy shattering reduces yield from grain loss during rice ( L. harvest. We characterized a nonshattering rice landrace Jiucaiqing from Taihu Lake valley in China. The breaking tensile strength (BTS; grams force, gf of the grain pedicel was measured using a digital force gauge to evaluate the degree of shattering at 0, 7, 14, 21, 28, and 35 d after heading (DAH. The BTS of Jiucaiqing did not significantly decrease with increasing DAH, maintaining a level of 152.2 to 195.9 gf, while that of IR26 decreased greatly during 0 to 14 DAH and finally stabilized at ∼100 gf. Then the chromosome segment substitution lines (CSSLs and near isogenic lines (NILs of Jiucaiqing in IR26 background were developed for quantitative trait loci (QTL mapping. Four putative QTL (, , , and for shattering were detected, and the was confirmed on chromosome 1. We further mapped to a 98.4-kb region, which contains 14 genes. Os01g62920 was considered to be a strong candidate for , which colocated with . Further quantitative real-time polymerase chain reaction (PCR analyses confirmed that the QTL can significantly decrease the expression of shattering related genes (, , , , and especially at the middle development stage at 10 and 15 cm panicle length, which causes rice shattering decrease. The elite allele and the NIL with desirable agronomic traits identified in this study could be useful for rice breeding.

The quantitative LOD score: test statistic and sample size for exclusion and linkage of quantitative traits in human sibships.

Science.gov (United States)

Page, G P; Amos, C I; Boerwinkle, E

1998-04-01

We present a test statistic, the quantitative LOD (QLOD) score, for the testing of both linkage and exclusion of quantitative-trait loci in randomly selected human sibships. As with the traditional LOD score, the boundary values of 3, for linkage, and -2, for exclusion, can be used for the QLOD score. We investigated the sample sizes required for inferring exclusion and linkage, for various combinations of linked genetic variance, total heritability, recombination distance, and sibship size, using fixed-size sampling. The sample sizes required for both linkage and exclusion were not qualitatively different and depended on the percentage of variance being linked or excluded and on the total genetic variance. Information regarding linkage and exclusion in sibships larger than size 2 increased as approximately all possible pairs n(n-1)/2 up to sibships of size 6. Increasing the recombination (theta) distance between the marker and the trait loci reduced empirically the power for both linkage and exclusion, as a function of approximately (1-2theta)4.

Identification of quantitative trait loci controlling root and shoot traits associated with drought tolerance in a lentil (Lens culinaris Medik. recombinant inbred line population

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Omar Idrissi

2016-08-01

Full Text Available Drought is one of the major abiotic stresses limiting lentil productivity in rainfed production systems. Specific rooting patterns can be associated with drought avoidance mechanisms that can be used in lentil breeding programs. In all, 252 co-dominant and dominant markers were used for Quantitative Trait Loci (QTL analysis on 132 lentil recombinant inbred lines based on greenhouse experiments for root and shoot traits during two seasons under progressive drought-stressed conditions. Eighteen QTLs controlling a total of 14 root and shoot traits were identified. A QTL-hotspot genomic region related to a number of root and shoot characteristics associated with drought tolerance such as dry root biomass, root surface area, lateral root number, dry shoot biomass and shoot length was identified. Interestingly, a QTL related to root-shoot ratio, an important trait for drought avoidance, explaining the highest phenotypic variance of 27.6 % and 28.9 % for the two consecutive seasons, respectively, was detected. This QTL was closed to the co-dominant SNP marker TP6337 and also flanked by the two SNP TP518 and TP1280. An important QTL related to lateral root number was found close to TP3371 and flanked by TP5093 and TP6072 SNP markers. Also, a QTL associated with specific root length was identified close to TP1873 and flanked by F7XEM6b SRAP marker and TP1035 SNP marker. These two QTLs were detected in both seasons. Our results could be used for marker-assisted selection in lentil breeding programs targeting root and shoot characteristics conferring drought avoidance as an efficient alternative to slow and labour-intensive conventional breeding methods.

Ascertainment correction for Markov chain Monte Carlo segregation and linkage analysis of a quantitative trait.

Science.gov (United States)

Ma, Jianzhong; Amos, Christopher I; Warwick Daw, E

2007-09-01

Although extended pedigrees are often sampled through probands with extreme levels of a quantitative trait, Markov chain Monte Carlo (MCMC) methods for segregation and linkage analysis have not been able to perform ascertainment corrections. Further, the extent to which ascertainment of pedigrees leads to biases in the estimation of segregation and linkage parameters has not been previously studied for MCMC procedures. In this paper, we studied these issues with a Bayesian MCMC approach for joint segregation and linkage analysis, as implemented in the package Loki. We first simulated pedigrees ascertained through individuals with extreme values of a quantitative trait in spirit of the sequential sampling theory of Cannings and Thompson [Cannings and Thompson [1977] Clin. Genet. 12:208-212]. Using our simulated data, we detected no bias in estimates of the trait locus location. However, in addition to allele frequencies, when the ascertainment threshold was higher than or close to the true value of the highest genotypic mean, bias was also found in the estimation of this parameter. When there were multiple trait loci, this bias destroyed the additivity of the effects of the trait loci, and caused biases in the estimation all genotypic means when a purely additive model was used for analyzing the data. To account for pedigree ascertainment with sequential sampling, we developed a Bayesian ascertainment approach and implemented Metropolis-Hastings updates in the MCMC samplers used in Loki. Ascertainment correction greatly reduced biases in parameter estimates. Our method is designed for multiple, but a fixed number of trait loci. Copyright (c) 2007 Wiley-Liss, Inc.

Quantitative trait loci (QTL) mapping of resistance to strongyles and coccidia in the free-living Soay sheep (Ovis aries).

Science.gov (United States)

Beraldi, Dario; McRae, Allan F; Gratten, Jacob; Pilkington, Jill G; Slate, Jon; Visscher, Peter M; Pemberton, Josephine M

2007-01-01

A genome-wide scan was performed to detect quantitative trait loci (QTL) for resistance to gastrointestinal parasites and ectoparasitic keds segregating in the free-living Soay sheep population on St. Kilda (UK). The mapping panel consisted of a single pedigree of 882 individuals of which 588 were genotyped. The Soay linkage map used for the scans comprised 251 markers covering the whole genome at average spacing of 15cM. The traits here investigated were the strongyle faecal egg count (FEC), the coccidia faecal oocyst count (FOC) and a count of keds (Melophagus ovinus). QTL mapping was performed by means of variance component analysis so that the genetic parameters of the study traits were also estimated and compared with previous studies in Soay and domestic sheep. Strongyle FEC and coccidia FOC showed moderate heritability (h(2)=0.26 and 0.22, respectively) in lambs but low heritability in adults (h(2)<0.10). Ked count appeared to have very low h(2) in both lambs and adults. Genome scans were performed for the traits with moderate heritability and two genomic regions reached the level of suggestive linkage for coccidia FOC in lambs (logarithm of the odds=2.68 and 2.21 on chromosomes 3 and X, respectively). We believe this is the first study to report a QTL search for parasite resistance in a free-living animal population and therefore may represent a useful reference for similar studies aimed at understanding the genetics of host-parasite co-evolution in the wild.

Analysis of genetic variants of coat colour loci and their influence on the coat colour phenotype and quantitative performance traits in the pig

OpenAIRE

Siebel, Krista

2010-01-01

The influence of four single coat colour loci (KIT, MC1R, TYR, ASP) on the coat colour phenotype and performance traits in the pig have been investigated in a resource population. The research revealed an unknown genotype for the white phenotype in the pig. The influence of the Agouti locus on the coat colour phenotype has been suggested. An influence of the coat colour loci KIT on growth performance traits and MC1R on body fatness could be demonstrated.

Quantitative trait loci associated with the immune response to a bovine respiratory syncytial virus vaccine.

Directory of Open Access Journals (Sweden)

Richard J Leach

Full Text Available Infectious disease is an important problem for animal breeders, farmers and governments worldwide. One approach to reducing disease is to breed for resistance. This linkage study used a Charolais-Holstein F2 cattle cross population (n = 501 which was genotyped for 165 microsatellite markers (covering all autosomes to search for associations with phenotypes for Bovine Respiratory Syncytial Virus (BRSV specific total-IgG, IgG1 and IgG2 concentrations at several time-points pre- and post-BRSV vaccination. Regions of the bovine genome which influenced the immune response induced by BRSV vaccination were identified, as well as regions associated with the clearance of maternally derived BRSV specific antibodies. Significant positive correlations were detected within traits across time, with negative correlations between the pre- and post-vaccination time points. The whole genome scan identified 27 Quantitative Trait Loci (QTL on 13 autosomes. Many QTL were associated with the Thymus Helper 1 linked IgG2 response, especially at week 2 following vaccination. However the most significant QTL, which reached 5% genome-wide significance, was on BTA 17 for IgG1, also 2 weeks following vaccination. All animals had declining maternally derived BRSV specific antibodies prior to vaccination and the levels of BRSV specific antibody prior to vaccination were found to be under polygenic control with several QTL detected.Heifers from the same population (n = 195 were subsequently immunised with a 40-mer Foot-and-Mouth Disease Virus peptide (FMDV in a previous publication. Several of these QTL associated with the FMDV traits had overlapping peak positions with QTL in the current study, including the QTL on BTA23 which included the bovine Major Histocompatibility Complex (BoLA, and QTL on BTA9 and BTA24, suggesting that the genes underlying these QTL may control responses to multiple antigens. These results lay the groundwork for future investigations to identify the

Relationship of the Interaction Between Two Quantitative Trait Loci with γ-Globin Expression in β-Thalassemia Intermedia Patients.

Science.gov (United States)

NickAria, Shiva; Haghpanah, Sezaneh; Ramzi, Mani; Karimi, Mehran

2018-05-10

Globin switching is a significant factor on blood hemoglobin (Hb) level but its molecular mechanisms have not yet been identified, however, several quantitative trait loci (QTL) and polymorphisms involved regions on chromosomes 2p, 6q, 8q and X account for variation in the γ-globin expression level. We studied the effect of interaction between a region on intron six of the TOX gene, chromosome 8q (chr8q) and XmnI locus on the γ-globin promoter, chr11p on γ-globin expression in 150 β-thalassemia intermedia (β-TI) patients, evaluated by statistical interaction analysis. Our results showed a significant interaction between one QTL on intron six of the TOX gene (rs9693712) and XmnI locus that effect γ-globin expression. Interchromosomal interaction mediates through transcriptional machanisms to preserve true genome architectural features, chromosomes localization and DNA bending. This interaction can be a part of the unknown molecular mechanism of globin switching and regulation of gene expression.

Modularization and epistatic hierarchy determine homeostatic actions of multiple blood pressure quantitative trait loci.

Science.gov (United States)

Chauvet, Cristina; Crespo, Kimberley; Ménard, Annie; Roy, Julie; Deng, Alan Y

2013-11-15

Hypertension, the most frequently diagnosed clinical condition world-wide, predisposes individuals to morbidity and mortality, yet its underlying pathological etiologies are poorly understood. So far, a large number of quantitative trait loci (QTLs) have been identified in both humans and animal models, but how they function together in determining overall blood pressure (BP) in physiological settings is unknown. Here, we systematically and comprehensively performed pair-wise comparisons of individual QTLs to create a global picture of their functionality in an inbred rat model. Rather than each of numerous QTLs contributing to infinitesimal BP increments, a modularized pattern arises: two epistatic 'blocks' constitute basic functional 'units' for nearly all QTLs, designated as epistatic module 1 (EM1) and EM2. This modularization dictates the magnitude and scope of BP effects. Any EM1 member can contribute to BP additively to that of EM2, but not to those of the same module. Members of each EM display epistatic hierarchy, which seems to reflect a related functional pathway. Rat homologues of 11 human BP QTLs belong to either EM1 or EM2. Unique insights emerge into the novel genetic mechanism and hierarchy determining BP in the Dahl salt-sensitive SS/Jr (DSS) rat model that implicate a portion of human QTLs. Elucidating the pathways underlying EM1 and EM2 may reveal the genetic regulation of BP.

Effects of Bos taurus autosome 9-located quantitative trait loci haplotypes on the disease phenotypes of dairy cows with experimentally induced Escherichia coli mastitis

DEFF Research Database (Denmark)

Khatun, Momena; Sørensen, Peter; Jørgensen, Hanne Birgitte Hede

2013-01-01

Several quantitative trait loci (QTL) affecting mastitis incidence and mastitis-related traits such as somatic cell score exist in dairy cows. Previously, QTL haplotypes associated with susceptibility to Escherichia coli mastitis in Nordic Holstein-Friesian (HF) cows were identified on Bos taurus...... autosome 9. In the present study, we induced experimental E. coli mastitis in Danish HF cows to investigate the effect of 2 E. coli mastitis-associated QTL haplotypes on the cows' disease phenotypes and recovery in early lactation. Thirty-two cows were divided in 2 groups bearing haplotypes with either low...... the HH group did. However, we also found interactions between the effects of haplotype and biopsy for body temperature, heart rate, and PMNL. In conclusion, when challenged with E. coli mastitis, HF cows with the specific Bos taurus autosome 9-located QTL haplotypes were associated with differences...

An integrated genetic map based on four mapping populations and quantitative trait loci associated with economically important traits in watermelon (Citrullus lanatus)

Science.gov (United States)

2014-01-01

Background Modern watermelon (Citrullus lanatus L.) cultivars share a narrow genetic base due to many years of selection for desirable horticultural qualities. Wild subspecies within C. lanatus are important potential sources of novel alleles for watermelon breeding, but successful trait introgression into elite cultivars has had limited success. The application of marker assisted selection (MAS) in watermelon is yet to be realized, mainly due to the past lack of high quality genetic maps. Recently, a number of useful maps have become available, however these maps have few common markers, and were constructed using different marker sets, thus, making integration and comparative analysis among maps difficult. The objective of this research was to use single-nucleotide polymorphism (SNP) anchor markers to construct an integrated genetic map for C. lanatus. Results Under the framework of the high density genetic map, an integrated genetic map was constructed by merging data from four independent mapping experiments using a genetically diverse array of parental lines, which included three subspecies of watermelon. The 698 simple sequence repeat (SSR), 219 insertion-deletion (InDel), 36 structure variation (SV) and 386 SNP markers from the four maps were used to construct an integrated map. This integrated map contained 1339 markers, spanning 798 cM with an average marker interval of 0.6 cM. Fifty-eight previously reported quantitative trait loci (QTL) for 12 traits in these populations were also integrated into the map. In addition, new QTL identified for brix, fructose, glucose and sucrose were added. Some QTL associated with economically important traits detected in different genetic backgrounds mapped to similar genomic regions of the integrated map, suggesting that such QTL are responsible for the phenotypic variability observed in a broad array of watermelon germplasm. Conclusions The integrated map described herein enhances the utility of genomic tools over

An integrated genetic map based on four mapping populations and quantitative trait loci associated with economically important traits in watermelon (Citrullus lanatus).

Science.gov (United States)

Ren, Yi; McGregor, Cecilia; Zhang, Yan; Gong, Guoyi; Zhang, Haiying; Guo, Shaogui; Sun, Honghe; Cai, Wantao; Zhang, Jie; Xu, Yong

2014-01-20

Modern watermelon (Citrullus lanatus L.) cultivars share a narrow genetic base due to many years of selection for desirable horticultural qualities. Wild subspecies within C. lanatus are important potential sources of novel alleles for watermelon breeding, but successful trait introgression into elite cultivars has had limited success. The application of marker assisted selection (MAS) in watermelon is yet to be realized, mainly due to the past lack of high quality genetic maps. Recently, a number of useful maps have become available, however these maps have few common markers, and were constructed using different marker sets, thus, making integration and comparative analysis among maps difficult. The objective of this research was to use single-nucleotide polymorphism (SNP) anchor markers to construct an integrated genetic map for C. lanatus. Under the framework of the high density genetic map, an integrated genetic map was constructed by merging data from four independent mapping experiments using a genetically diverse array of parental lines, which included three subspecies of watermelon. The 698 simple sequence repeat (SSR), 219 insertion-deletion (InDel), 36 structure variation (SV) and 386 SNP markers from the four maps were used to construct an integrated map. This integrated map contained 1339 markers, spanning 798 cM with an average marker interval of 0.6 cM. Fifty-eight previously reported quantitative trait loci (QTL) for 12 traits in these populations were also integrated into the map. In addition, new QTL identified for brix, fructose, glucose and sucrose were added. Some QTL associated with economically important traits detected in different genetic backgrounds mapped to similar genomic regions of the integrated map, suggesting that such QTL are responsible for the phenotypic variability observed in a broad array of watermelon germplasm. The integrated map described herein enhances the utility of genomic tools over previous watermelon genetic maps. A

Mapping quantitative trait loci affecting fatness and breast muscle weight in meat-type chicken lines divergently selected on abdominal fatness

Directory of Open Access Journals (Sweden)

Neau André

2006-01-01

Full Text Available Abstract Quantitative trait loci (QTL for abdominal fatness and breast muscle weight were investigated in a three-generation design performed by inter-crossing two experimental meat-type chicken lines that were divergently selected on abdominal fatness. A total of 585 F2 male offspring from 5 F1 sires and 38 F1 dams were recorded at 8 weeks of age for live body, abdominal fat and breast muscle weights. One hundred-twenty nine microsatellite markers, evenly located throughout the genome and heterozygous for most of the F1 sires, were used for genotyping the F2 birds. In each sire family, those offspring exhibiting the most extreme values for each trait were genotyped. Multipoint QTL analyses using maximum likelihood methods were performed for abdominal fat and breast muscle weights, which were corrected for the effects of 8-week body weight, dam and hatching group. Isolated markers were assessed by analyses of variance. Two significant QTL were identified on chromosomes 1 and 5 with effects of about one within-family residual standard deviation. One breast muscle QTL was identified on GGA1 with an effect of 2.0 within-family residual standard deviation.

Mapping and validation of major quantitative trait loci for kernel length in wild barley (Hordeum vulgare ssp. spontaneum).

Science.gov (United States)

Zhou, Hong; Liu, Shihang; Liu, Yujiao; Liu, Yaxi; You, Jing; Deng, Mei; Ma, Jian; Chen, Guangdeng; Wei, Yuming; Liu, Chunji; Zheng, Youliang

2016-09-13

Kernel length is an important target trait in barley (Hordeum vulgare L.) breeding programs. However, the number of known quantitative trait loci (QTLs) controlling kernel length is limited. In the present study, we aimed to identify major QTLs for kernel length, as well as putative candidate genes that might influence kernel length in wild barley. A recombinant inbred line (RIL) population derived from the barley cultivar Baudin (H. vulgare ssp. vulgare) and the long-kernel wild barley genotype Awcs276 (H.vulgare ssp. spontaneum) was evaluated at one location over three years. A high-density genetic linkage map was constructed using 1,832 genome-wide diversity array technology (DArT) markers, spanning a total of 927.07 cM with an average interval of approximately 0.49 cM. Two major QTLs for kernel length, LEN-3H and LEN-4H, were detected across environments and further validated in a second RIL population derived from Fleet (H. vulgare ssp. vulgare) and Awcs276. In addition, a systematic search of public databases identified four candidate genes and four categories of proteins related to LEN-3H and LEN-4H. This study establishes a fundamental research platform for genomic studies and marker-assisted selection, since LEN-3H and LEN-4H could be used for accelerating progress in barley breeding programs that aim to improve kernel length.

A consensus linkage map for molecular markers and Quantitative Trait Loci associated with economically important traits in melon (Cucumis melo L.)

Science.gov (United States)

2011-01-01

Background A number of molecular marker linkage maps have been developed for melon (Cucumis melo L.) over the last two decades. However, these maps were constructed using different marker sets, thus, making comparative analysis among maps difficult. In order to solve this problem, a consensus genetic map in melon was constructed using primarily highly transferable anchor markers that have broad potential use for mapping, synteny, and comparative quantitative trait loci (QTL) analysis, increasing breeding effectiveness and efficiency via marker-assisted selection (MAS). Results Under the framework of the International Cucurbit Genomics Initiative (ICuGI, http://www.icugi.org), an integrated genetic map has been constructed by merging data from eight independent mapping experiments using a genetically diverse array of parental lines. The consensus map spans 1150 cM across the 12 melon linkage groups and is composed of 1592 markers (640 SSRs, 330 SNPs, 252 AFLPs, 239 RFLPs, 89 RAPDs, 15 IMAs, 16 indels and 11 morphological traits) with a mean marker density of 0.72 cM/marker. One hundred and ninety-six of these markers (157 SSRs, 32 SNPs, 6 indels and 1 RAPD) were newly developed, mapped or provided by industry representatives as released markers, including 27 SNPs and 5 indels from genes involved in the organic acid metabolism and transport, and 58 EST-SSRs. Additionally, 85 of 822 SSR markers contributed by Syngenta Seeds were included in the integrated map. In addition, 370 QTL controlling 62 traits from 18 previously reported mapping experiments using genetically diverse parental genotypes were also integrated into the consensus map. Some QTL associated with economically important traits detected in separate studies mapped to similar genomic positions. For example, independently identified QTL controlling fruit shape were mapped on similar genomic positions, suggesting that such QTL are possibly responsible for the phenotypic variability observed for this trait in

A consensus linkage map for molecular markers and Quantitative Trait Loci associated with economically important traits in melon (Cucumis melo L.

Directory of Open Access Journals (Sweden)

Schaffer Arthur

2011-07-01

Full Text Available Abstract Background A number of molecular marker linkage maps have been developed for melon (Cucumis melo L. over the last two decades. However, these maps were constructed using different marker sets, thus, making comparative analysis among maps difficult. In order to solve this problem, a consensus genetic map in melon was constructed using primarily highly transferable anchor markers that have broad potential use for mapping, synteny, and comparative quantitative trait loci (QTL analysis, increasing breeding effectiveness and efficiency via marker-assisted selection (MAS. Results Under the framework of the International Cucurbit Genomics Initiative (ICuGI, http://www.icugi.org, an integrated genetic map has been constructed by merging data from eight independent mapping experiments using a genetically diverse array of parental lines. The consensus map spans 1150 cM across the 12 melon linkage groups and is composed of 1592 markers (640 SSRs, 330 SNPs, 252 AFLPs, 239 RFLPs, 89 RAPDs, 15 IMAs, 16 indels and 11 morphological traits with a mean marker density of 0.72 cM/marker. One hundred and ninety-six of these markers (157 SSRs, 32 SNPs, 6 indels and 1 RAPD were newly developed, mapped or provided by industry representatives as released markers, including 27 SNPs and 5 indels from genes involved in the organic acid metabolism and transport, and 58 EST-SSRs. Additionally, 85 of 822 SSR markers contributed by Syngenta Seeds were included in the integrated map. In addition, 370 QTL controlling 62 traits from 18 previously reported mapping experiments using genetically diverse parental genotypes were also integrated into the consensus map. Some QTL associated with economically important traits detected in separate studies mapped to similar genomic positions. For example, independently identified QTL controlling fruit shape were mapped on similar genomic positions, suggesting that such QTL are possibly responsible for the phenotypic variability

Inheritance analysis and mapping of quantitative trait loci (QTL controlling individual anthocyanin compounds in purple barley (Hordeum vulgare L. grains.

Directory of Open Access Journals (Sweden)

Xiao-Wei Zhang

Full Text Available Anthocyanin-rich barley can have great potential in promoting human health and in developing nutraceuticals and functional foods. As different anthocyanin compounds have different antioxidant activities, breeding cultivars with pre-designed anthocyanin compositions could be highly desirable. Working toward this possibility, we assessed and reported for the first time the genetic control of individual anthocyanin compounds in barley. Of the ten anthocyanins assessed, two, peonidin-3-glucoside (P3G and cyanidin-3-glucoside (C3G, were major components in the purple pericarp barley genotype RUSSIA68. Quantitative trait locus (QTL mapping showed that both anthocyanin compounds were the interactive products of two loci, one located on chromosome arm 2HL and the other on 7HS. However, the two different anthocyanin components seem to be controlled by different interactions between the two loci. The effects of the 7HS locus on P3G and C3G were difficult to detect without removing the effect of the 2HL locus. At least one copy of the 2HL alleles from the purple pericarp parent was required for the synthesis of P3G. This does not seem to be the case for the production of C3G which was produced in each of all the different allele combinations between the two loci. Typical maternal effect was also observed in the inheritance of purple pericarp grains in barley. The varied values of different compounds, coupled with their different genetic controls, highlight the need for targeting individual anthocyanins in crop breeding and food processing.

Quantitative trait loci controlling leaf appearance and curd initiation of cauliflower in relation to temperature.

Science.gov (United States)

Hasan, Yaser; Briggs, William; Matschegewski, Claudia; Ordon, Frank; Stützel, Hartmut; Zetzsche, Holger; Groen, Simon; Uptmoor, Ralf

2016-07-01

QTL regions on chromosomes C06 and C09 are involved in temperature dependent time to curd induction in cauliflower. Temperature is the main environmental factor influencing curding time of cauliflower (Brassica oleracea var. botrytis). Temperatures above 20-22 °C inhibit development towards curding even in many summer cultivars. To identify quantitative trait loci (QTL) controlling curding time and its related traits in a wide range of different temperature regimes from 12 to 27 °C, a doubled haploid (DH) mapping population segregating for curding time was developed and days to curd initiation (DCI), leaf appearance rate (LAR), and final leaf number (FLN) were measured. The population was genotyped with 176 single nucleotide polymorphism (SNP) markers. Composite interval mapping (CIM) revealed repeatedly detected QTL for DCI on C06 and C09. The estimated additive effect increased at high temperatures. Significant QTL × environment interactions (Q × E) for FLN and DCI on C06 and C09 suggest that these hotspot regions have major influences on temperature mediated curd induction. 25 % of the DH lines did not induce curds at temperatures higher than 22 °C. Applying a binary model revealed a QTL with LOD >15 on C06. Nearly all lines carrying the allele of the reliable early maturing parental line (PL) on that locus induced curds at high temperatures while only half of the DH lines carrying the allele of the unreliable PL reached the generative phase during the experiment. Large variation in LAR was observed. QTL for LAR were detected repeatedly in several environments on C01, C04 and C06. Negative correlations between LAR and DCI and QTL co-localizations on C04 and C06 suggest that LAR has also effects on development towards curd induction.

Estimating rice yield related traits and quantitative trait loci analysis under different nitrogen treatments using a simple tower-based field phenotyping system with modified single-lens reflex cameras

Science.gov (United States)

Naito, Hiroki; Ogawa, Satoshi; Valencia, Milton Orlando; Mohri, Hiroki; Urano, Yutaka; Hosoi, Fumiki; Shimizu, Yo; Chavez, Alba Lucia; Ishitani, Manabu; Selvaraj, Michael Gomez; Omasa, Kenji

2017-03-01

Application of field based high-throughput phenotyping (FB-HTP) methods for monitoring plant performance in real field conditions has a high potential to accelerate the breeding process. In this paper, we discuss the use of a simple tower based remote sensing platform using modified single-lens reflex cameras for phenotyping yield traits in rice under different nitrogen (N) treatments over three years. This tower based phenotyping platform has the advantages of simplicity, ease and stability in terms of introduction, maintenance and continual operation under field conditions. Out of six phenological stages of rice analyzed, the flowering stage was the most useful in the estimation of yield performance under field conditions. We found a high correlation between several vegetation indices (simple ratio (SR), normalized difference vegetation index (NDVI), transformed vegetation index (TVI), corrected transformed vegetation index (CTVI), soil-adjusted vegetation index (SAVI) and modified soil-adjusted vegetation index (MSAVI)) and multiple yield traits (panicle number, grain weight and shoot biomass) across a three trials. Among all of the indices studied, SR exhibited the best performance in regards to the estimation of grain weight (R2 = 0.80). Under our tower-based field phenotyping system (TBFPS), we identified quantitative trait loci (QTL) for yield related traits using a mapping population of chromosome segment substitution lines (CSSLs) and a single nucleotide polymorphism data set. Our findings suggest the TBFPS can be useful for the estimation of yield performance during early crop development. This can be a major opportunity for rice breeders whom desire high throughput phenotypic selection for yield performance traits.

Mapping Quantitative Trait Loci (QTL for Resistance to Late Blight in Tomato

Directory of Open Access Journals (Sweden)

Dilip R. Panthee

2017-07-01

Full Text Available Late blight caused by Phytophthora infestans (Montagne, Bary is a devastating disease of tomato worldwide. There are three known major genes, Ph-1, Ph-2, and Ph-3, conferring resistance to late blight. In addition to these three genes, it is also believed that there are additional factors or quantitative trait loci (QTL conferring resistance to late blight. Precise molecular mapping of all those major genes and potential QTL is important in the development of suitable molecular markers and hence, marker-assisted selection (MAS. The objective of the present study was to map the genes and QTL associated with late blight resistance in a tomato population derived from intra-specific crosses. To achieve this objective, a population, derived from the crossings of NC 1CELBR × Fla. 7775, consisting of 250 individuals at F2 and F2-derived families, were evaluated in replicated trials. These were conducted at Mountain Horticultural Crops Reseach & Extension Center (MHCREC at Mills River, NC, and Mountain Research Staion (MRS at Waynesville, NC in 2011, 2014, and 2015. There were two major QTL associated with late blight resistance located on chromosomes 9 and 10 with likelihood of odd (LOD scores of more than 42 and 6, explaining 67% and 14% of the total phenotypic variation, respectively. The major QTLs are probably caused by the Ph-2 and Ph-3 genes. Furthermore, there was a minor QTL on chromosomes 12, which has not been reported before. This minor QTL may be novel and may be worth investigating further. Source of resistance to Ph-2, Ph-3, and this minor QTL traces back to line L3707, or Richter’s Wild Tomato. The combination of major genes and minor QTL may provide a durable resistance to late blight in tomato.

Quantitative trait loci analysis of swine meat quality traits

DEFF Research Database (Denmark)

Li, H D; Lund, M S; Christensen, O F

2010-01-01

loss, and the Minolta color measurements L*, a*, and b* representing meat lightness, redness, and yellowness, respectively. The families consist of 3,883 progenies of 12 Duroc boars that were evaluated to identify the QTL. The linkage map consists of 462 SNP markers on 18 porcine autosomes...... were estimated from a posterior distribution of the QTL position. In total, 31 QTL for the 6 meat quality traits were found to be significant at the 5% chromosome-wide level, among which 11 QTL were significant at the 5% genome-wide level and 5 of these were significant at the 0.1% genome-wide level...... will be helpful for fine mapping and identifying genes affecting meat quality traits, and tightly linked markers may be incorporated into marker-assisted selection programs...

Genetic dissection of milk yield traits and mastitis resistance quantitative trait loci on chromosome 20 in dairy cattle.

Science.gov (United States)

Kadri, Naveen K; Guldbrandtsen, Bernt; Lund, Mogens S; Sahana, Goutam

2015-12-01

Intense selection to increase milk yield has had negative consequences for mastitis incidence in dairy cattle. Due to low heritability of mastitis resistance and an unfavorable genetic correlation with milk yield, a reduction in mastitis through traditional breeding has been difficult to achieve. Here, we examined quantitative trait loci (QTL) that segregate for clinical mastitis and milk yield on Bos taurus autosome 20 (BTA20) to determine whether both traits are affected by a single polymorphism (pleiotropy) or by multiple closely linked polymorphisms. In the latter but not the former situation, undesirable genetic correlation could potentially be broken by selecting animals that have favorable variants for both traits. First, we performed a within-breed association study using a haplotype-based method in Danish Holstein cattle (HOL). Next, we analyzed Nordic Red dairy cattle (RDC) and Danish Jersey cattle (JER) with the goal of determining whether these QTL identified in Holsteins were segregating across breeds. Genotypes for 12,566 animals (5,966 HOL, 5,458 RDC, and 1,142 JER) were determined by using the Illumina Bovine SNP50 BeadChip (50K; Illumina, San Diego, CA), which identifies 1,568 single nucleotide polymorphisms on BTA20. Data were combined, phased, and clustered into haplotype states, followed by within- and across-breed haplotype-based association analyses using a linear mixed model. Association signals for both clinical mastitis and milk yield peaked in the 26- to 40-Mb region on BTA20 in HOL. Single-variant association analyses were carried out in the QTL region using whole sequence level variants imputed from references of 2,036 HD genotypes (BovineHD BeadChip; Illumina) and 242 whole-genome sequences. The milk QTL were also segregating in RDC and JER on the BTA20-targeted region; however, an indication of differences in the causal factor(s) was observed across breeds. A previously reported F279Y mutation (rs385640152) within the growth hormone

Detection of expression quantitative trait Loci in complex mouse crosses: impact and alleviation of data quality and complex population substructure.

Science.gov (United States)

Iancu, Ovidiu D; Darakjian, Priscila; Kawane, Sunita; Bottomly, Daniel; Hitzemann, Robert; McWeeney, Shannon

2012-01-01

Complex Mus musculus crosses, e.g., heterogeneous stock (HS), provide increased resolution for quantitative trait loci detection. However, increased genetic complexity challenges detection methods, with discordant results due to low data quality or complex genetic architecture. We quantified the impact of theses factors across three mouse crosses and two different detection methods, identifying procedures that greatly improve detection quality. Importantly, HS populations have complex genetic architectures not fully captured by the whole genome kinship matrix, calling for incorporating chromosome specific relatedness information. We analyze three increasingly complex crosses, using gene expression levels as quantitative traits. The three crosses were an F(2) intercross, a HS formed by crossing four inbred strains (HS4), and a HS (HS-CC) derived from the eight lines found in the collaborative cross. Brain (striatum) gene expression and genotype data were obtained using the Illumina platform. We found large disparities between methods, with concordance varying as genetic complexity increased; this problem was more acute for probes with distant regulatory elements (trans). A suite of data filtering steps resulted in substantial increases in reproducibility. Genetic relatedness between samples generated overabundance of detected eQTLs; an adjustment procedure that includes the kinship matrix attenuates this problem. However, we find that relatedness between individuals is not evenly distributed across the genome; information from distinct chromosomes results in relatedness structure different from the whole genome kinship matrix. Shared polymorphisms from distinct chromosomes collectively affect expression levels, confounding eQTL detection. We suggest that considering chromosome specific relatedness can result in improved eQTL detection.

Quantitative trait loci for a neurocranium deformity, lack of operculum, in gilthead seabream (Sparus aurata L.).

Science.gov (United States)

Negrín-Báez, D; Navarro, A; Afonso, J M; Toro, M A; Zamorano, M J

2016-04-01

Lack of operculum, a neurocranial deformity, is the most common external abnormality to be found among industrially produced gilthead seabream (Sparus aurata L.), and this entails significant financial losses. This study conducts, for the first time in this species, a quantitative trait loci (QTL) analysis of the lack of operculum. A total of 142 individuals from a paternal half-sibling family (six full-sibling families) were selected for QTL mapping. They had previously shown a highly significant association with the prevalence of lack of operculum in a segregation analysis. All the fish were genotyped for 106 microsatellite markers using a set of multiplex PCRs (ReMsa1-ReMsa13). A linear regression methodology was used for the QTL analysis. Four QTL were detected for this deformity, two of which (QTLOP1 and QTLOP2) were significant. They were located at LG (linkage group) nine and LG10 respectively. Both QTL showed a large effect (about 27%), and furthermore, the association between lack of operculum and sire allelic segregation observed was statistically significant in the QTLOP1 analysis. These results represent a significant step towards including marker-assisted selection for this deformity in genetic breeding programmes to reduce the incidence of the deformity in the species. © 2016 Stichting International Foundation for Animal Genetics.

Two developmentally temporal quantitative trait loci underlie convergent evolution of increased branchial bone length in sticklebacks

Science.gov (United States)

Erickson, Priscilla A.; Glazer, Andrew M.; Cleves, Phillip A.; Smith, Alyson S.; Miller, Craig T.

2014-01-01

In convergent evolution, similar phenotypes evolve repeatedly in independent populations, often reflecting adaptation to similar environments. Understanding whether convergent evolution proceeds via similar or different genetic and developmental mechanisms offers insight towards the repeatability and predictability of evolution. Oceanic populations of threespine stickleback fish, Gasterosteus aculeatus, have repeatedly colonized countless freshwater lakes and streams, where new diets lead to morphological adaptations related to feeding. Here, we show that heritable increases in branchial bone length have convergently evolved in two independently derived freshwater stickleback populations. In both populations, an increased bone growth rate in juveniles underlies the convergent adult phenotype, and one population also has a longer cartilage template. Using F2 crosses from these two freshwater populations, we show that two quantitative trait loci (QTL) control branchial bone length at distinct points in development. In both populations, a QTL on chromosome 21 controls bone length throughout juvenile development, and a QTL on chromosome 4 controls bone length only in adults. In addition to these similar developmental profiles, these QTL show similar chromosomal locations in both populations. Our results suggest that sticklebacks have convergently evolved longer branchial bones using similar genetic and developmental programmes in two independently derived populations. PMID:24966315

Quantitative trait loci mapping for stomatal traits in interspecific ...

Indian Academy of Sciences (India)

Dr.YASODHA

seedling raising, field planting and maintenance of the mapping population. ... tereticornis and production of interspecific hybrids displaying hybrid vigour in terms of .... A total of 114, 115 and 129 SSR, ISSR and SRAP markers were generated .... stomatal traits with yield and adaptability would help to improve productivity of ...

Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

NARCIS (Netherlands)

S.I. Berndt (Sonja); S. Gustafsson (Stefan); R. Mägi (Reedik); A. Ganna (Andrea); E. Wheeler (Eleanor); M.F. Feitosa (Mary Furlan); A.E. Justice (Anne); K.L. Monda (Keri); D.C. Croteau-Chonka (Damien); F.R. Day (Felix); T. Esko (Tõnu); M. Fall (Magnus); T. Ferreira (Teresa); D. Gentilini (Davide); A.U. Jackson (Anne); J. Luan; J.C. Randall (Joshua); S. Vedantam (Sailaja); C.J. Willer (Cristen); T.W. Winkler (Thomas); A.R. Wood (Andrew); T. Workalemahu (Tsegaselassie); Y.-J. Hu (Yi-Juan); S.H. Lee (Sang Hong); L. Liang (Liming); D.Y. Lin (Dan); J. Min (Josine); B.M. Neale (Benjamin); G. Thorleifsson (Gudmar); J. Yang (Jian); E. Albrecht (Eva); N. Amin (Najaf); J.L. Bragg-Gresham (Jennifer L.); G. Cadby (Gemma); M. den Heijer (Martin); N. Eklund (Niina); K. Fischer (Krista); A. Goel (Anuj); J.J. Hottenga (Jouke Jan); J.E. Huffman (Jennifer); I. Jarick (Ivonne); A. Johansson (Åsa); T. Johnson (Toby); S. Kanoni (Stavroula); M.E. Kleber (Marcus); I.R. König (Inke); K. Kristiansson (Kati); Z. Kutalik (Zoltán); C. Lamina (Claudia); C. Lecoeur (Cécile); G. Li (Guo); M. Mangino (Massimo); W.L. McArdle (Wendy); M.C. Medina-Gomez (Carolina); M. Müller-Nurasyid (Martina); J.S. Ngwa; I.M. Nolte (Ilja); L. Paternoster (Lavinia); S. Pechlivanis (Sonali); M. Perola (Markus); M.J. Peters (Marjolein); M. Preuss (Michael); L.M. Rose (Lynda); J. Shi (Jianxin); D. Shungin (Dmitry); G.D. Smith; R.J. Strawbridge (Rona); I. Surakka (Ida); A. Teumer (Alexander); M.D. Trip (Mieke); J.P. Tyrer (Jonathan); J.V. van Vliet-Ostaptchouk (Jana); L. Vandenput (Liesbeth); L. Waite (Lindsay); J.H. Zhao (Jing Hua); D. Absher (Devin); F.W. Asselbergs (Folkert); M. Atalay (Mustafa); A.P. Attwood (Antony); A.J. Balmforth (Anthony); D.C.G. Basart (Dick); J.P. Beilby (John); L.L. Bonnycastle (Lori); P. Brambilla (Paolo); M. Bruinenberg (M.); H. Campbell (Harry); D.I. Chasman (Daniel); P.S. Chines (Peter); F.S. Collins (Francis); J. Connell (John); W. O Cookson (William); U. de Faire (Ulf); F. de Vegt (Femmie); M. Dei (Mariano); M. Dimitriou (Maria); T. Edkins (Ted); K. Estrada Gil (Karol); D.M. Evans (David); M. Farrall (Martin); F. Ferrario (Franco); J. Ferrières (Jean); L. Franke (Lude); F. Frau (Francesca); P.V. Gejman (Pablo); H. Grallert (Harald); H. Grönberg (Henrik); V. Gudnason (Vilmundur); A. Hall (Anne); A.S. Hall (Alistair); A.L. Hartikainen; C. Hayward (Caroline); N.L. Heard-Costa (Nancy); A.C. Heath (Andrew); J. Hebebrand (Johannes); G. Homuth (Georg); F.B. Hu (Frank); S.E. Hunt (Sarah); E. Hyppönen (Elina); C. Iribarren (Carlos); K.B. Jacobs (Kevin); J.-O. Jansson (John-Olov); A. Jula (Antti); M. Kähönen (Mika); S. Kathiresan (Sekar); F. Kee (F.); K-T. Khaw (Kay-Tee); M. Kivimaki (Mika); W. Koenig (Wolfgang); A. Kraja (Aldi); M. Kumari (Meena); K. Kuulasmaa (Kari); J. Kuusisto (Johanna); J. Laitinen (Jaana); T.A. Lakka (Timo); C. Langenberg (Claudia); L.J. Launer (Lenore); L. Lind (Lars); J. Lindstrom (Jaana); J. Liu (Jianjun); A. Liuzzi (Antonio); M.L. Lokki; M. Lorentzon (Mattias); P.A. Madden (Pamela); P.K. Magnusson (Patrik); P. Manunta (Paolo); D. Marek (Diana); W. März (Winfried); I.M. Leach (Irene Mateo); B. McKnight (Barbara); S.E. Medland (Sarah Elizabeth); E. Mihailov (Evelin); L. Milani (Lili); G.W. Montgomery (Grant); V. Mooser (Vincent); T.W. Mühleisen (Thomas); P. Munroe (Patricia); A.W. Musk (Arthur); N. Narisu (Narisu); G. Navis (Gerjan); G. Nicholson (Ggeorge); C. Nohr (Christian); K. Ong (Ken); B.A. Oostra (Ben); C.N.A. Palmer (Colin); A. Palotie (Aarno); J. Peden (John); N. Pedersen; A. Peters (Annette); O. Polasek (Ozren); A. Pouta (Anneli); P.P. Pramstaller (Peter Paul); I. Prokopenko (Inga); C. Pütter (Carolin); A. Radhakrishnan (Aparna); O. Raitakari (Olli); A. Rendon (Augusto); F. Rivadeneira Ramirez (Fernando); I. Rudan (Igor); T. Saaristo (Timo); J.G. Sambrook (Jennifer); A.R. Sanders (Alan); S. Sanna (Serena); J. Saramies (Jouko); S. Schipf (Sabine); S. Schreiber (Stefan); H. Schunkert (Heribert); S.-Y. Shin; S. Signorini (Stefano); J. Sinisalo (Juha); B. Skrobek (Boris); N. Soranzo (Nicole); A. Stancáková (Alena); K. Stark (Klaus); J. Stephens (Jonathan); K. Stirrups (Kathy); R.P. Stolk (Ronald); M. Stumvoll (Michael); A.J. Swift (Amy); E.V. Theodoraki (Eirini); B. Thorand (Barbara); D.-A. Tregouet (David-Alexandre); E. Tremoli (Elena); M.M. van der Klauw (Melanie); J.B.J. van Meurs (Joyce); S.H.H.M. Vermeulen (Sita); J. Viikari (Jorma); J. Virtamo (Jarmo); V. Vitart (Veronique); G. Waeber (Gérard); Z. Wang (Zhaoming); E. Widen (Elisabeth); S.H. Wild (Sarah); G.A.H.M. Willemsen (Gonneke); B. Winkelmann; J.C.M. Witteman (Jacqueline); B.H.R. Wolffenbuttel (Bruce); A. Wong (Andrew); A.F. Wright (Alan); M.C. Zillikens (Carola); P. Amouyel (Philippe); B.O. Boehm (Bernhard); E.A. Boerwinkle (Eric); D.I. Boomsma (Dorret); M. Caulfield (Mark); S.J. Chanock (Stephen); L.A. Cupples (Adrienne); D. Cusi (Daniele); G.V. Dedoussis (George); J. Erdmann (Jeanette); J.G. Eriksson (Johan); P.W. Franks (Paul); P. Froguel (Philippe); C. Gieger (Christian); U. Gyllensten (Ulf); A. Hamsten (Anders); T.B. Harris (Tamara); C. Hengstenberg (Christian); A.A. Hicks (Andrew); A. Hingorani (Aroon); A. Hinney (Anke); A. Hofman (Albert); G.K. Hovingh (Kees); K. Hveem (Kristian); T. Illig (Thomas); M.-R. Jarvelin (Marjo-Riitta); K.-H. Jöckel (Karl-Heinz); S. Keinanen-Kiukaanniemi (Sirkka); L.A.L.M. Kiemeney (Bart); D. Kuh (Diana); M. Laakso (Markku); T. Lehtimäki (Terho); D.F. Levinson (Douglas); N.G. Martin (Nicholas); A. Metspalu (Andres); A.D. Morris (Andrew); M.S. Nieminen (Markku); I. Njølstad (Inger); C. Ohlsson (Claes); A.J. Oldehinkel (Albertine); W.H. Ouwehand (Willem); C. Palmer (Cameron); B.W.J.H. Penninx (Brenda); C. Power (Christopher); M.A. Province (Mike); B.M. Psaty (Bruce); L. Qi (Lu); R. Rauramaa (Rainer); P.M. Ridker (Paul); S. Ripatti (Samuli); V. Salomaa (Veikko); N.J. Samani (Nilesh); H. Snieder (Harold); H.G. Sorensen; T.D. Spector (Timothy); J-A. Zwart (John-Anker); A. Tönjes (Anke); J. Tuomilehto (Jaakko); A.G. Uitterlinden (André); M. Uusitupa (Matti); P. van der Harst (Pim); P. Vollenweider (Peter); H. Wallaschofski (Henri); N.J. Wareham (Nick); H. Watkins (Hugh); H.E. Wichmann (Heinz Erich); J.F. Wilson (James F); G.R. Abecasis (Gonçalo); T.L. Assimes (Themistocles); I.E. Barroso (Inês); M. Boehnke (Michael); I.B. Borecki (Ingrid); P. Deloukas (Panagiotis); C. Fox (Craig); T.M. Frayling (Timothy); L. Groop (Leif); T. Haritunian (Talin); I.M. Heid (Iris); D. Hunter (David); R.C. Kaplan (Robert); F. Karpe (Fredrik); M.F. Moffatt (Miriam); K.L. Mohlke (Karen); J.R. O´Connell; Y. Pawitan (Yudi); E.E. Schadt (Eric); D. Schlessinger (David); V. Steinthorsdottir (Valgerdur); D.P. Strachan (David); U. Thorsteinsdottir (Unnur); C.M. van Duijn (Cornelia); P.M. Visscher (Peter); A.M. Di Blasio (Anna Maria); J.N. Hirschhorn (Joel); C.M. Lindgren (Cecilia); A.D. Morris (Andrew); D. Meyre (David); A. Scherag (Andre); M.I. McCarthy (Mark); E.K. Speliotes (Elizabeth); K.E. North (Kari); R.J.F. Loos (Ruth); E. Ingelsson (Erik)

2013-01-01

textabstractApproaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of

Systems genomics study reveals expression quantitative trait loci, regulator genes and pathways associated with boar taint in pigs.

Directory of Open Access Journals (Sweden)

Markus Drag

Full Text Available Boar taint is an offensive odour and/or taste from a proportion of non-castrated male pigs caused by skatole and androstenone accumulation during sexual maturity. Castration is widely used to avoid boar taint but is currently under debate because of animal welfare concerns. This study aimed to identify expression quantitative trait loci (eQTLs with potential effects on boar taint compounds to improve breeding possibilities for reduced boar taint. Danish Landrace male boars with low, medium and high genetic merit for skatole and human nose score (HNS were slaughtered at ~100 kg. Gene expression profiles were obtained by RNA-Seq, and genotype data were obtained by an Illumina 60K Porcine SNP chip. Following quality control and filtering, 10,545 and 12,731 genes from liver and testis were included in the eQTL analysis, together with 20,827 SNP variants. A total of 205 and 109 single-tissue eQTLs associated with 102 and 58 unique genes were identified in liver and testis, respectively. By employing a multivariate Bayesian hierarchical model, 26 eQTLs were identified as significant multi-tissue eQTLs. The highest densities of eQTLs were found on pig chromosomes SSC12, SSC1, SSC13, SSC9 and SSC14. Functional characterisation of eQTLs revealed functions within regulation of androgen and the intracellular steroid hormone receptor signalling pathway and of xenobiotic metabolism by cytochrome P450 system and cellular response to oestradiol. A QTL enrichment test revealed 89 QTL traits curated by the Animal Genome PigQTL database to be significantly overlapped by the genomic coordinates of cis-acting eQTLs. Finally, a subset of 35 cis-acting eQTLs overlapped with known boar taint QTL traits. These eQTLs could be useful in the development of a DNA test for boar taint but careful monitoring of other overlapping QTL traits should be performed to avoid any negative consequences of selection.

Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

NARCIS (Netherlands)

Berndt, Sonja I; Gustafsson, Stefan; Mägi, Reedik; Ganna, Andrea; Wheeler, Eleanor; Feitosa, Mary F; Justice, Anne E; Monda, Keri L; Croteau-Chonka, Damien C; Day, Felix R; Esko, Tõnu; Fall, Tove; Ferreira, Teresa; Gentilini, Davide; Jackson, Anne U; Luan, Jian'an; Randall, Joshua C; Vedantam, Sailaja; Willer, Cristen J; Winkler, Thomas W; Wood, Andrew R; Workalemahu, Tsegaselassie; Hu, Yi-Juan; Lee, Sang Hong; Liang, Liming; Lin, Dan-Yu; Min, Josine L; Neale, Benjamin M; Thorleifsson, Gudmar; Yang, Jian; Albrecht, Eva; Amin, Najaf; Bragg-Gresham, Jennifer L; Cadby, Gemma; den Heijer, Martin; Eklund, Niina; Fischer, Krista; Goel, Anuj; Hottenga, Jouke-Jan; Huffman, Jennifer E; Jarick, Ivonne; Johansson, Åsa; Johnson, Toby; Kanoni, Stavroula; Kleber, Marcus E; König, Inke R; Kristiansson, Kati; Kutalik, Zoltán; Lamina, Claudia; Lecoeur, Cecile; Li, Guo; Mangino, Massimo; McArdle, Wendy L; Medina-Gomez, Carolina; Müller-Nurasyid, Martina; Ngwa, Julius S; Nolte, Ilja M; Paternoster, Lavinia; Pechlivanis, Sonali; Perola, Markus; Peters, Marjolein J; Preuss, Michael; Rose, Lynda M; Shi, Jianxin; Shungin, Dmitry; Smith, Albert Vernon; Strawbridge, Rona J; Surakka, Ida; Teumer, Alexander; Trip, Mieke D; Tyrer, Jonathan; Van Vliet-Ostaptchouk, Jana V; Vandenput, Liesbeth; Waite, Lindsay L; Zhao, Jing Hua; Absher, Devin; Asselbergs, Folkert W; Atalay, Mustafa; Attwood, Antony P; Balmforth, Anthony J; Basart, Hanneke; Beilby, John; Bonnycastle, Lori L; Brambilla, Paolo; Bruinenberg, Marcel; Campbell, Harry; Chasman, Daniel I; Chines, Peter S; Collins, Francis S; Connell, John M; Cookson, William O; de Faire, Ulf; de Vegt, Femmie; Dei, Mariano; Dimitriou, Maria; Edkins, Sarah; Estrada, Karol; Evans, David M; Farrall, Martin; Ferrario, Marco M; Ferrières, Jean; Franke, Lude; Frau, Francesca; Gejman, Pablo V; Grallert, Harald; Grönberg, Henrik; Gudnason, Vilmundur; Hall, Alistair S; Hall, Per; Hartikainen, Anna-Liisa; Hayward, Caroline; Heard-Costa, Nancy L; Heath, Andrew C; Hebebrand, Johannes; Homuth, Georg; Hu, Frank B; Hunt, Sarah E; Hyppönen, Elina; Iribarren, Carlos; Jacobs, Kevin B; Jansson, John-Olov; Jula, Antti; Kähönen, Mika; Kathiresan, Sekar; Kee, Frank; Khaw, Kay-Tee; Kivimäki, Mika; Koenig, Wolfgang; Kraja, Aldi T; Kumari, Meena; Kuulasmaa, Kari; Kuusisto, Johanna; Laitinen, Jaana H; Lakka, Timo A; Langenberg, Claudia; Launer, Lenore J; Lind, Lars; Lindström, Jaana; Liu, Jianjun; Liuzzi, Antonio; Lokki, Marja-Liisa; Lorentzon, Mattias; Madden, Pamela A; Magnusson, Patrik K; Manunta, Paolo; Marek, Diana; März, Winfried; Mateo Leach, Irene; McKnight, Barbara; Medland, Sarah E; Mihailov, Evelin; Milani, Lili; Montgomery, Grant W; Mooser, Vincent; Mühleisen, Thomas W; Munroe, Patricia B; Musk, Arthur W; Narisu, Narisu; Navis, Gerjan; Nicholson, George; Nohr, Ellen A; Ong, Ken K; Oostra, Ben A; Palmer, Colin N A; Palotie, Aarno; Peden, John F; Pedersen, Nancy; Peters, Annette; Polasek, Ozren; Pouta, Anneli; Pramstaller, Peter P; Prokopenko, Inga; Pütter, Carolin; Radhakrishnan, Aparna; Raitakari, Olli; Rendon, Augusto; Rivadeneira, Fernando; Rudan, Igor; Saaristo, Timo E; Sambrook, Jennifer G; Sanders, Alan R; Sanna, Serena; Saramies, Jouko; Schipf, Sabine; Schreiber, Stefan; Schunkert, Heribert; Shin, So-Youn; Signorini, Stefano; Sinisalo, Juha; Skrobek, Boris; Soranzo, Nicole; Stančáková, Alena; Stark, Klaus; Stephens, Jonathan C; Stirrups, Kathleen; Stolk, Ronald P; Stumvoll, Michael; Swift, Amy J; Theodoraki, Eirini V; Thorand, Barbara; Tregouet, David-Alexandre; Tremoli, Elena; Van der Klauw, Melanie M; van Meurs, Joyce B J; Vermeulen, Sita H; Viikari, Jorma; Virtamo, Jarmo; Vitart, Veronique; Waeber, Gérard; Wang, Zhaoming; Widén, Elisabeth; Wild, Sarah H; Willemsen, Gonneke; Winkelmann, Bernhard R; Witteman, Jacqueline C M; Wolffenbuttel, Bruce H R; Wong, Andrew; Wright, Alan F; Zillikens, M Carola; Amouyel, Philippe; Boehm, Bernhard O; Boerwinkle, Eric; Boomsma, Dorret I; Caulfield, Mark J; Chanock, Stephen J; Cupples, L Adrienne; Cusi, Daniele; Dedoussis, George V; Erdmann, Jeanette; Eriksson, Johan G; Franks, Paul W; Froguel, Philippe; Gieger, Christian; Gyllensten, Ulf; Hamsten, Anders; Harris, Tamara B; Hengstenberg, Christian; Hicks, Andrew A; Hingorani, Aroon; Hinney, Anke; Hofman, Albert; Hovingh, Kees G; Hveem, Kristian; Illig, Thomas; Jarvelin, Marjo-Riitta; Jöckel, Karl-Heinz; Keinanen-Kiukaanniemi, Sirkka M; Kiemeney, Lambertus A; Kuh, Diana; Laakso, Markku; Lehtimäki, Terho; Levinson, Douglas F; Martin, Nicholas G; Metspalu, Andres; Morris, Andrew D; Nieminen, Markku S; Njølstad, Inger; Ohlsson, Claes; Oldehinkel, Albertine J; Ouwehand, Willem H; Palmer, Lyle J; Penninx, Brenda; Power, Chris; Province, Michael A; Psaty, Bruce M; Qi, Lu; Rauramaa, Rainer; Ridker, Paul M; Ripatti, Samuli; Salomaa, Veikko; Samani, Nilesh J; Snieder, Harold; Sørensen, Thorkild I A; Spector, Timothy D; Stefansson, Kari; Tönjes, Anke; Tuomilehto, Jaakko; Uitterlinden, André G; Uusitupa, Matti; van der Harst, Pim; Vollenweider, Peter; Wallaschofski, Henri; Wareham, Nicholas J; Watkins, Hugh; Wichmann, H-Erich; Wilson, James F; Abecasis, Goncalo R; Assimes, Themistocles L; Barroso, Inês; Boehnke, Michael; Borecki, Ingrid B; Deloukas, Panos; Fox, Caroline S; Frayling, Timothy; Groop, Leif C; Haritunian, Talin; Heid, Iris M; Hunter, David; Kaplan, Robert C; Karpe, Fredrik; Moffatt, Miriam F; Mohlke, Karen L; O'Connell, Jeffrey R; Pawitan, Yudi; Schadt, Eric E; Schlessinger, David; Steinthorsdottir, Valgerdur; Strachan, David P; Thorsteinsdottir, Unnur; van Duijn, Cornelia M; Visscher, Peter M; Di Blasio, Anna Maria; Hirschhorn, Joel N; Lindgren, Cecilia M; Morris, Andrew P; Meyre, David; Scherag, André; McCarthy, Mark I; Speliotes, Elizabeth K; North, Kari E; Loos, Ruth J F; Ingelsson, Erik

Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass

Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

NARCIS (Netherlands)

Berndt, Sonja I.; Gustafsson, Stefan; Mägi, Reedik; Ganna, Andrea; Wheeler, Eleanor; Feitosa, Mary F.; Justice, Anne E.; Monda, Keri L.; Croteau-Chonka, Damien C.; Day, Felix R.; Esko, Tõnu; Fall, Tove; Ferreira, Teresa; Gentilini, Davide; Jackson, Anne U.; Luan, Jian'an; Randall, Joshua C.; Vedantam, Sailaja; Willer, Cristen J.; Winkler, Thomas W.; Wood, Andrew R.; Workalemahu, Tsegaselassie; Hu, Yi-Juan; Lee, Sang Hong; Liang, Liming; Lin, Dan-Yu; Min, Josine L.; Neale, Benjamin M.; Thorleifsson, Gudmar; Yang, Jian; Albrecht, Eva; Amin, Najaf; Bragg-Gresham, Jennifer L.; Cadby, Gemma; den Heijer, Martin; Eklund, Niina; Fischer, Krista; Goel, Anuj; Hottenga, Jouke-Jan; Huffman, Jennifer E.; Jarick, Ivonne; Johansson, Asa; Johnson, Toby; Kanoni, Stavroula; Kleber, Marcus E.; König, Inke R.; Kristiansson, Kati; Kutalik, Zoltán; Lamina, Claudia; Lecoeur, Cecile; Li, Guo; Mangino, Massimo; McArdle, Wendy L.; Medina-Gomez, Carolina; Müller-Nurasyid, Martina; Ngwa, Julius S.; Nolte, Ilja M.; Paternoster, Lavinia; Pechlivanis, Sonali; Perola, Markus; Peters, Marjolein J.; Preuss, Michael; Rose, Lynda M.; Shi, Jianxin; Shungin, Dmitry; Smith, Albert Vernon; Strawbridge, Rona J.; Surakka, Ida; Teumer, Alexander; Trip, Mieke D.; Tyrer, Jonathan; van Vliet-Ostaptchouk, Jana V.; Vandenput, Liesbeth; Waite, Lindsay L.; Zhao, Jing Hua; Absher, Devin; Asselbergs, Folkert W.; Atalay, Mustafa; Attwood, Antony P.; Balmforth, Anthony J.; Basart, Hanneke; Beilby, John; Bonnycastle, Lori L.; Brambilla, Paolo; Bruinenberg, Marcel; Campbell, Harry; Chasman, Daniel I.; Chines, Peter S.; Collins, Francis S.; Connell, John M.; Cookson, William O.; de Faire, Ulf; de Vegt, Femmie; dei, Mariano; Dimitriou, Maria; Edkins, Sarah; Estrada, Karol; Evans, David M.; Farrall, Martin; Ferrario, Marco M.; Ferrières, Jean; Franke, Lude; Frau, Francesca; Gejman, Pablo V.; Grallert, Harald; Grönberg, Henrik; Gudnason, Vilmundur; Hall, Alistair S.; Hall, Per; Hartikainen, Anna-Liisa; Hayward, Caroline; Heard-Costa, Nancy L.; Heath, Andrew C.; Hebebrand, Johannes; Homuth, Georg; Hu, Frank B.; Hunt, Sarah E.; Hyppönen, Elina; Iribarren, Carlos; Jacobs, Kevin B.; Jansson, John-Olov; Jula, Antti; Kähönen, Mika; Kathiresan, Sekar; Kee, Frank; Khaw, Kay-Tee; Kivimäki, Mika; Koenig, Wolfgang; Kraja, Aldi T.; Kumari, Meena; Kuulasmaa, Kari; Kuusisto, Johanna; Laitinen, Jaana H.; Lakka, Timo A.; Langenberg, Claudia; Launer, Lenore J.; Lind, Lars; Lindström, Jaana; Liu, Jianjun; Liuzzi, Antonio; Lokki, Marja-Liisa; Lorentzon, Mattias; Madden, Pamela A.; Magnusson, Patrik K.; Manunta, Paolo; Marek, Diana; März, Winfried; Mateo Leach, Irene; McKnight, Barbara; Medland, Sarah E.; Mihailov, Evelin; Milani, Lili; Montgomery, Grant W.; Mooser, Vincent; Mühleisen, Thomas W.; Munroe, Patricia B.; Musk, Arthur W.; Narisu, Narisu; Navis, Gerjan; Nicholson, George; Nohr, Ellen A.; Ong, Ken K.; Oostra, Ben A.; Palmer, Colin N. A.; Palotie, Aarno; Peden, John F.; Pedersen, Nancy; Peters, Annette; Polasek, Ozren; Pouta, Anneli; Pramstaller, Peter P.; Prokopenko, Inga; Pütter, Carolin; Radhakrishnan, Aparna; Raitakari, Olli; Rendon, Augusto; Rivadeneira, Fernando; Rudan, Igor; Saaristo, Timo E.; Sambrook, Jennifer G.; Sanders, Alan R.; Sanna, Serena; Saramies, Jouko; Schipf, Sabine; Schreiber, Stefan; Schunkert, Heribert; Shin, So-Youn; Signorini, Stefano; Sinisalo, Juha; Skrobek, Boris; Soranzo, Nicole; Stančáková, Alena; Stark, Klaus; Stephens, Jonathan C.; Stirrups, Kathleen; Stolk, Ronald P.; Stumvoll, Michael; Swift, Amy J.; Theodoraki, Eirini V.; Thorand, Barbara; Tregouet, David-Alexandre; Tremoli, Elena; van der Klauw, Melanie M.; van Meurs, Joyce B. J.; Vermeulen, Sita H.; Viikari, Jorma; Virtamo, Jarmo; Vitart, Veronique; Waeber, Gérard; Wang, Zhaoming; Widén, Elisabeth; Wild, Sarah H.; Willemsen, Gonneke; Winkelmann, Bernhard R.; Witteman, Jacqueline C. M.; Wolffenbuttel, Bruce H. R.; Wong, Andrew; Wright, Alan F.; Zillikens, M. Carola; Amouyel, Philippe; Boehm, Bernhard O.; Boerwinkle, Eric; Boomsma, Dorret I.; Caulfield, Mark J.; Chanock, Stephen J.; Cupples, L. Adrienne; Cusi, Daniele; Dedoussis, George V.; Erdmann, Jeanette; Eriksson, Johan G.; Franks, Paul W.; Froguel, Philippe; Gieger, Christian; Gyllensten, Ulf; Hamsten, Anders; Harris, Tamara B.; Hengstenberg, Christian; Hicks, Andrew A.; Hingorani, Aroon; Hinney, Anke; Hofman, Albert; Hovingh, Kees G.; Hveem, Kristian; Illig, Thomas; Jarvelin, Marjo-Riitta; Jöckel, Karl-Heinz; Keinanen-Kiukaanniemi, Sirkka M.; Kiemeney, Lambertus A.; Kuh, Diana; Laakso, Markku; Lehtimäki, Terho; Levinson, Douglas F.; Martin, Nicholas G.; Metspalu, Andres; Morris, Andrew D.; Nieminen, Markku S.; Njølstad, Inger; Ohlsson, Claes; Oldehinkel, Albertine J.; Ouwehand, Willem H.; Palmer, Lyle J.; Penninx, Brenda; Power, Chris; Province, Michael A.; Psaty, Bruce M.; Qi, Lu; Rauramaa, Rainer; Ridker, Paul M.; Ripatti, Samuli; Salomaa, Veikko; Samani, Nilesh J.; Snieder, Harold; Sørensen, Thorkild I. A.; Spector, Timothy D.; Stefansson, Kari; Tönjes, Anke; Tuomilehto, Jaakko; Uitterlinden, André G.; Uusitupa, Matti; van der Harst, Pim; Vollenweider, Peter; Wallaschofski, Henri; Wareham, Nicholas J.; Watkins, Hugh; Wichmann, H.-Erich; Wilson, James F.; Abecasis, Goncalo R.; Assimes, Themistocles L.; Barroso, Inês; Boehnke, Michael; Borecki, Ingrid B.; Deloukas, Panos; Fox, Caroline S.; Frayling, Timothy; Groop, Leif C.; Haritunian, Talin; Heid, Iris M.; Hunter, David; Kaplan, Robert C.; Karpe, Fredrik; Moffatt, Miriam F.; Mohlke, Karen L.; O'Connell, Jeffrey R.; Pawitan, Yudi; Schadt, Eric E.; Schlessinger, David; Steinthorsdottir, Valgerdur; Strachan, David P.; Thorsteinsdottir, Unnur; van Duijn, Cornelia M.; Visscher, Peter M.; Di Blasio, Anna Maria; Hirschhorn, Joel N.; Lindgren, Cecilia M.; Morris, Andrew P.; Meyre, David; Scherag, André; McCarthy, Mark I.; Speliotes, Elizabeth K.; North, Kari E.; Loos, Ruth J. F.; Ingelsson, Erik

2013-01-01

Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass

Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

DEFF Research Database (Denmark)

Berndt, Sonja I; Gustafsson, Stefan; Mägi, Reedik

2013-01-01

Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass ...

Comparative Genomics Analyses Reveal Extensive Chromosome Colinearity and Novel Quantitative Trait Loci in Eucalyptus

Science.gov (United States)

Weng, Qijie; Li, Mei; Yu, Xiaoli; Guo, Yong; Wang, Yu; Zhang, Xiaohong; Gan, Siming

2015-01-01

Dense genetic maps, along with quantitative trait loci (QTLs) detected on such maps, are powerful tools for genomics and molecular breeding studies. In the important woody genus Eucalyptus, the recent release of E. grandis genome sequence allows for sequence-based genomic comparison and searching for positional candidate genes within QTL regions. Here, dense genetic maps were constructed for E. urophylla and E. tereticornis using genomic simple sequence repeats (SSR), expressed sequence tag (EST) derived SSR, EST-derived cleaved amplified polymorphic sequence (EST-CAPS), and diversity arrays technology (DArT) markers. The E. urophylla and E. tereticornis maps comprised 700 and 585 markers across 11 linkage groups, totaling at 1,208.2 and 1,241.4 cM in length, respectively. Extensive synteny and colinearity were observed as compared to three earlier DArT-based eucalypt maps (two maps with E. grandis × E. urophylla and one map of E. globulus) and with the E. grandis genome sequence. Fifty-three QTLs for growth (10–56 months of age) and wood density (56 months) were identified in 22 discrete regions on both maps, in which only one colocalizaiton was found between growth and wood density. Novel QTLs were revealed as compared with those previously detected on DArT-based maps for similar ages in Eucalyptus. Eleven to 585 positional candidate genes were obained for a 56-month-old QTL through aligning QTL confidence interval with the E. grandis genome. These results will assist in comparative genomics studies, targeted gene characterization, and marker-assisted selection in Eucalyptus and the related taxa. PMID:26695430

Comparative Genomics Analyses Reveal Extensive Chromosome Colinearity and Novel Quantitative Trait Loci in Eucalyptus.

Directory of Open Access Journals (Sweden)

Fagen Li

Full Text Available Dense genetic maps, along with quantitative trait loci (QTLs detected on such maps, are powerful tools for genomics and molecular breeding studies. In the important woody genus Eucalyptus, the recent release of E. grandis genome sequence allows for sequence-based genomic comparison and searching for positional candidate genes within QTL regions. Here, dense genetic maps were constructed for E. urophylla and E. tereticornis using genomic simple sequence repeats (SSR, expressed sequence tag (EST derived SSR, EST-derived cleaved amplified polymorphic sequence (EST-CAPS, and diversity arrays technology (DArT markers. The E. urophylla and E. tereticornis maps comprised 700 and 585 markers across 11 linkage groups, totaling at 1,208.2 and 1,241.4 cM in length, respectively. Extensive synteny and colinearity were observed as compared to three earlier DArT-based eucalypt maps (two maps with E. grandis × E. urophylla and one map of E. globulus and with the E. grandis genome sequence. Fifty-three QTLs for growth (10-56 months of age and wood density (56 months were identified in 22 discrete regions on both maps, in which only one colocalizaiton was found between growth and wood density. Novel QTLs were revealed as compared with those previously detected on DArT-based maps for similar ages in Eucalyptus. Eleven to 585 positional candidate genes were obained for a 56-month-old QTL through aligning QTL confidence interval with the E. grandis genome. These results will assist in comparative genomics studies, targeted gene characterization, and marker-assisted selection in Eucalyptus and the related taxa.

Multiple Linkage Disequilibrium Mapping Methods to Validate Additive Quantitative Trait Loci in Korean Native Cattle (Hanwoo

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Yi Li

2015-07-01

Full Text Available The efficiency of genome-wide association analysis (GWAS depends on power of detection for quantitative trait loci (QTL and precision for QTL mapping. In this study, three different strategies for GWAS were applied to detect QTL for carcass quality traits in the Korean cattle, Hanwoo; a linkage disequilibrium single locus regression method (LDRM, a combined linkage and linkage disequilibrium analysis (LDLA and a BayesCπ approach. The phenotypes of 486 steers were collected for weaning weight (WWT, yearling weight (YWT, carcass weight (CWT, backfat thickness (BFT, longissimus dorsi muscle area, and marbling score (Marb. Also the genotype data for the steers and their sires were scored with the Illumina bovine 50K single nucleotide polymorphism (SNP chips. For the two former GWAS methods, threshold values were set at false discovery rate <0.01 on a chromosome-wide level, while a cut-off threshold value was set in the latter model, such that the top five windows, each of which comprised 10 adjacent SNPs, were chosen with significant variation for the phenotype. Four major additive QTL from these three methods had high concordance found in 64.1 to 64.9Mb for Bos taurus autosome (BTA 7 for WWT, 24.3 to 25.4Mb for BTA14 for CWT, 0.5 to 1.5Mb for BTA6 for BFT and 26.3 to 33.4Mb for BTA29 for BFT. Several candidate genes (i.e. glutamate receptor, ionotropic, ampa 1 [GRIA1], family with sequence similarity 110, member B [FAM110B], and thymocyte selection-associated high mobility group box [TOX] may be identified close to these QTL. Our result suggests that the use of different linkage disequilibrium mapping approaches can provide more reliable chromosome regions to further pinpoint DNA makers or causative genes in these regions.

A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis

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Akira Ishikawa

2017-11-01

Full Text Available Large numbers of quantitative trait loci (QTL affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

A Strategy for Identifying Quantitative Trait Genes Using Gene Expression Analysis and Causal Analysis.

Science.gov (United States)

Ishikawa, Akira

2017-11-27

Large numbers of quantitative trait loci (QTL) affecting complex diseases and other quantitative traits have been reported in humans and model animals. However, the genetic architecture of these traits remains elusive due to the difficulty in identifying causal quantitative trait genes (QTGs) for common QTL with relatively small phenotypic effects. A traditional strategy based on techniques such as positional cloning does not always enable identification of a single candidate gene for a QTL of interest because it is difficult to narrow down a target genomic interval of the QTL to a very small interval harboring only one gene. A combination of gene expression analysis and statistical causal analysis can greatly reduce the number of candidate genes. This integrated approach provides causal evidence that one of the candidate genes is a putative QTG for the QTL. Using this approach, I have recently succeeded in identifying a single putative QTG for resistance to obesity in mice. Here, I outline the integration approach and discuss its usefulness using my studies as an example.

A computational approach for functional mapping of quantitative trait loci that regulate thermal performance curves.

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John Stephen Yap

2007-06-01

Full Text Available Whether and how thermal reaction norm is under genetic control is fundamental to understand the mechanistic basis of adaptation to novel thermal environments. However, the genetic study of thermal reaction norm is difficult because it is often expressed as a continuous function or curve. Here we derive a statistical model for dissecting thermal performance curves into individual quantitative trait loci (QTL with the aid of a genetic linkage map. The model is constructed within the maximum likelihood context and implemented with the EM algorithm. It integrates the biological principle of responses to temperature into a framework for genetic mapping through rigorous mathematical functions established to describe the pattern and shape of thermal reaction norms. The biological advantages of the model lie in the decomposition of the genetic causes for thermal reaction norm into its biologically interpretable modes, such as hotter-colder, faster-slower and generalist-specialist, as well as the formulation of a series of hypotheses at the interface between genetic actions/interactions and temperature-dependent sensitivity. The model is also meritorious in statistics because the precision of parameter estimation and power of QTLdetection can be increased by modeling the mean-covariance structure with a small set of parameters. The results from simulation studies suggest that the model displays favorable statistical properties and can be robust in practical genetic applications. The model provides a conceptual platform for testing many ecologically relevant hypotheses regarding organismic adaptation within the Eco-Devo paradigm.

Quantitative trait loci underlying resistance to sudden death syndrome (SDS) in MD96-5722 by 'Spencer' recombinant inbred line population of soybean.

Science.gov (United States)

Anderson, J; Akond, M; Kassem, M A; Meksem, K; Kantartzi, S K

2015-04-01

The best way to protect yield loss of soybean [Glycine max (L.) Merr.] due to sudden death syndrome (SDS), caused by Fusarium virguliforme (Aoki, O'Donnel, Homma & Lattanzi), is the development and use of resistant lines. Mapping quantitative trait loci (QTL) linked to SDS help developing resistant soybean germplasm through molecular marker-assisted selection strategy. QTL for SDS presented herein are from a high-density SNP-based genetic linkage map of MD 96-5722 (a.k.a 'Monocacy') by 'Spencer' recombinant inbred line using SoySNP6K Illumina Infinium BeadChip genotyping array. Ninety-four F 5:7 lines were evaluated for 2 years (2010 and 2011) at two locations (Carbondale and Valmeyer) in southern Illinois, USA to identify QTL controlling SDS resistance using disease index (DX). Composite interval mapping identified 19 SDS controlling QTL which were mapped on 11 separate linkage group (LG) or chromosomes (Chr) out of 20 LG or Chr of soybean genome. Many of these significant QTL identified in one environment/year were confirmed in another year or environment, which suggests a common genetic effects and modes of the pathogen. These new QTL are useful sources for SDS resistance studies in soybean breeding, complementing previously reported loci.

Expression quantitative trait loci and genetic regulatory network analysis reveals that Gabra2 is involved in stress responses in the mouse.

Science.gov (United States)

Dai, Jiajuan; Wang, Xusheng; Chen, Ying; Wang, Xiaodong; Zhu, Jun; Lu, Lu

2009-11-01

Previous studies have revealed that the subunit alpha 2 (Gabra2) of the gamma-aminobutyric acid receptor plays a critical role in the stress response. However, little is known about the gentetic regulatory network for Gabra2 and the stress response. We combined gene expression microarray analysis and quantitative trait loci (QTL) mapping to characterize the genetic regulatory network for Gabra2 expression in the hippocampus of BXD recombinant inbred (RI) mice. Our analysis found that the expression level of Gabra2 exhibited much variation in the hippocampus across the BXD RI strains and between the parental strains, C57BL/6J, and DBA/2J. Expression QTL (eQTL) mapping showed three microarray probe sets of Gabra2 to have highly significant linkage likelihood ratio statistic (LRS) scores. Gene co-regulatory network analysis showed that 10 genes, including Gria3, Chka, Drd3, Homer1, Grik2, Odz4, Prkag2, Grm5, Gabrb1, and Nlgn1 are directly or indirectly associated with stress responses. Eleven genes were implicated as Gabra2 downstream genes through mapping joint modulation. The genetical genomics approach demonstrates the importance and the potential power of the eQTL studies in identifying genetic regulatory networks that contribute to complex traits, such as stress responses.

Fine Mapping of QUICK ROOTING 1 and 2, Quantitative Trait Loci Increasing Root Length in Rice.

Science.gov (United States)

Kitomi, Yuka; Nakao, Emari; Kawai, Sawako; Kanno, Noriko; Ando, Tsuyu; Fukuoka, Shuichi; Irie, Kenji; Uga, Yusaku

2018-02-02

The volume that the root system can occupy is associated with the efficiency of water and nutrient uptake from soil. Genetic improvement of root length, which is a limiting factor for root distribution, is necessary for increasing crop production. In this report, we describe identification of two quantitative trait loci (QTLs) for maximal root length, QUICK ROOTING 1 ( QRO1 ) on chromosome 2 and QRO2 on chromosome 6, in cultivated rice ( Oryza sativa L.). We measured the maximal root length in 26 lines carrying chromosome segments from the long-rooted upland rice cultivar Kinandang Patong in the genetic background of the short-rooted lowland cultivar IR64. Five lines had longer roots than IR64. By rough mapping of the target regions in BC 4 F 2 populations, we detected putative QTLs for maximal root length on chromosomes 2, 6, and 8. To fine-map these QTLs, we used BC 4 F 3 recombinant homozygous lines. QRO1 was mapped between markers RM5651 and RM6107, which delimit a 1.7-Mb interval on chromosome 2, and QRO2 was mapped between markers RM20495 and RM3430-1, which delimit an 884-kb interval on chromosome 6. Both QTLs may be promising gene resources for improving root system architecture in rice. Copyright © 2018 Kitomi et al.

Fine Mapping of QUICK ROOTING 1 and 2, Quantitative Trait Loci Increasing Root Length in Rice

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Yuka Kitomi

2018-02-01

Full Text Available The volume that the root system can occupy is associated with the efficiency of water and nutrient uptake from soil. Genetic improvement of root length, which is a limiting factor for root distribution, is necessary for increasing crop production. In this report, we describe identification of two quantitative trait loci (QTLs for maximal root length, QUICK ROOTING 1 (QRO1 on chromosome 2 and QRO2 on chromosome 6, in cultivated rice (Oryza sativa L.. We measured the maximal root length in 26 lines carrying chromosome segments from the long-rooted upland rice cultivar Kinandang Patong in the genetic background of the short-rooted lowland cultivar IR64. Five lines had longer roots than IR64. By rough mapping of the target regions in BC4F2 populations, we detected putative QTLs for maximal root length on chromosomes 2, 6, and 8. To fine-map these QTLs, we used BC4F3 recombinant homozygous lines. QRO1 was mapped between markers RM5651 and RM6107, which delimit a 1.7-Mb interval on chromosome 2, and QRO2 was mapped between markers RM20495 and RM3430-1, which delimit an 884-kb interval on chromosome 6. Both QTLs may be promising gene resources for improving root system architecture in rice.

H2DB: a heritability database across multiple species by annotating trait-associated genomic loci.

Science.gov (United States)

Kaminuma, Eli; Fujisawa, Takatomo; Tanizawa, Yasuhiro; Sakamoto, Naoko; Kurata, Nori; Shimizu, Tokurou; Nakamura, Yasukazu

2013-01-01

H2DB (http://tga.nig.ac.jp/h2db/), an annotation database of genetic heritability estimates for humans and other species, has been developed as a knowledge database to connect trait-associated genomic loci. Heritability estimates have been investigated for individual species, particularly in human twin studies and plant/animal breeding studies. However, there appears to be no comprehensive heritability database for both humans and other species. Here, we introduce an annotation database for genetic heritabilities of various species that was annotated by manually curating online public resources in PUBMED abstracts and journal contents. The proposed heritability database contains attribute information for trait descriptions, experimental conditions, trait-associated genomic loci and broad- and narrow-sense heritability specifications. Annotated trait-associated genomic loci, for which most are single-nucleotide polymorphisms derived from genome-wide association studies, may be valuable resources for experimental scientists. In addition, we assigned phenotype ontologies to the annotated traits for the purposes of discussing heritability distributions based on phenotypic classifications.

Identification and validation of quantitative trait loci (QTL for canine hip dysplasia (CHD in German Shepherd Dogs.

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Lena Fels

Full Text Available Canine hip dysplasia (CHD is the most common hereditary skeletal disorder in dogs. To identify common alleles associated with CHD, we genotyped 96 German Shepherd Dogs affected by mild, moderate and severe CHD and 96 breed, sex, age and birth year matched controls using the Affymetrix canine high density SNP chip. A mixed linear model analysis identified five SNPs associated with CHD scores on dog chromosomes (CFA 19, 24, 26 and 34. These five SNPs were validated in a by sex, age, birth year and coancestry stratified sample of 843 German Shepherd Dogs including 277 unaffected dogs and 566 CHD-affected dogs. Mean coancestry coefficients among and within cases and controls were <0.1%. Genotype effects of these SNPs explained 20-32% of the phenotypic variance of CHD in German Shepherd Dogs employed for validation. Genome-wide significance in the validation data set could be shown for each one CHD-associated SNP on CFA24, 26 and 34. These SNPs are located within or in close proximity of genes involved in bone formation and related through a joint network. The present study validated positional candidate genes within two previously known quantitative trait loci (QTL and a novel QTL for CHD in German Shepherd Dogs.

Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations.

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Jingjing Liang

2017-05-01

Full Text Available Hypertension is a leading cause of global disease, mortality, and disability. While individuals of African descent suffer a disproportionate burden of hypertension and its complications, they have been underrepresented in genetic studies. To identify novel susceptibility loci for blood pressure and hypertension in people of African ancestry, we performed both single and multiple-trait genome-wide association analyses. We analyzed 21 genome-wide association studies comprised of 31,968 individuals of African ancestry, and validated our results with additional 54,395 individuals from multi-ethnic studies. These analyses identified nine loci with eleven independent variants which reached genome-wide significance (P < 1.25×10-8 for either systolic and diastolic blood pressure, hypertension, or for combined traits. Single-trait analyses identified two loci (TARID/TCF21 and LLPH/TMBIM4 and multiple-trait analyses identified one novel locus (FRMD3 for blood pressure. At these three loci, as well as at GRP20/CDH17, associated variants had alleles common only in African-ancestry populations. Functional annotation showed enrichment for genes expressed in immune and kidney cells, as well as in heart and vascular cells/tissues. Experiments driven by these findings and using angiotensin-II induced hypertension in mice showed altered kidney mRNA expression of six genes, suggesting their potential role in hypertension. Our study provides new evidence for genes related to hypertension susceptibility, and the need to study African-ancestry populations in order to identify biologic factors contributing to hypertension.

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

DEFF Research Database (Denmark)

Justice, Anne E; Winkler, Thomas W; Feitosa, Mary F

2017-01-01

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87......% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent...... direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting...

Quantitative trait loci controlling sulfur containing amino acids, methionine and cysteine, in soybean seeds.

Science.gov (United States)

Panthee, D R; Pantalone, V R; Sams, C E; Saxton, A M; West, D R; Orf, J H; Killam, A S

2006-02-01

Soybean [Glycine max (L.) Merr.] is the single largest source of protein in animal feed. However, a major limitation of soy proteins is their deficiency in sulfur-containing amino acids, methionine (Met) and cysteine (Cys). The objective of this study was to identify quantitative trait loci (QTL) associated with Met and Cys concentration in soybean seed. To achieve this objective, 101 F(6)-derived recombinant inbred lines (RIL) from a population developed from a cross of N87-984-16 x TN93-99 were used. Ground soybean seed samples were analyzed for Met and Cys concentration using a near infrared spectroscopy instrument. Data were analyzed using SAS software and QTL Cartographer. RIL differed (Pseed dry weight) for Cys and 4.4-8.8 (g kg(-1) seed dry weight) for Met. Heritability estimates on an entry mean basis were 0.14 and 0.57 for Cys and Met, respectively. A total of 94 polymorphic simple sequence repeat molecular genetic markers were screened in the RIL. Single factor ANOVA was used to identify candidate QTL, which were confirmed by composite interval mapping using QTL Cartographer. Four QTL linked to molecular markers Satt235, Satt252, Satt427 and Satt436 distributed on three molecular linkage groups (MLG) D1a, F and G were associated with Cys and three QTL linked to molecular markers Satt252, Satt564 and Satt590 distributed on MLG F, G and M were associated with Met concentration in soybean seed. QTL associated with Met and Cys in soybean seed will provide important information to breeders targeting improvements in the nutritional quality of soybean.

Identification of Major Quantitative Trait Loci for Seed Oil Content in Soybeans by Combining Linkage and Genome-Wide Association Mapping.

Science.gov (United States)

Cao, Yongce; Li, Shuguang; Wang, Zili; Chang, Fangguo; Kong, Jiejie; Gai, Junyi; Zhao, Tuanjie

2017-01-01

Soybean oil is the most widely produced vegetable oil in the world and its content in soybean seed is an important quality trait in breeding programs. More than 100 quantitative trait loci (QTLs) for soybean oil content have been identified. However, most of them are genotype specific and/or environment sensitive. Here, we used both a linkage and association mapping methodology to dissect the genetic basis of seed oil content of Chinese soybean cultivars in various environments in the Jiang-Huai River Valley. One recombinant inbred line (RIL) population (NJMN-RIL), with 104 lines developed from a cross between M8108 and NN1138-2 , was planted in five environments to investigate phenotypic data, and a new genetic map with 2,062 specific-locus amplified fragment markers was constructed to map oil content QTLs. A derived F 2 population between MN-5 (a line of NJMN-RIL) and NN1138-2 was also developed to confirm one major QTL. A soybean breeding germplasm population (279 lines) was established to perform a genome-wide association study (GWAS) using 59,845 high-quality single nucleotide polymorphism markers. In the NJMN-RIL population, 8 QTLs were found that explained a range of phenotypic variance from 6.3 to 26.3% in certain planting environments. Among them, qOil-5-1, qOil-10-1 , and qOil-14-1 were detected in different environments, and qOil-5-1 was further confirmed using the secondary F 2 population. Three loci located on chromosomes 5 and 20 were detected in a 2-year long GWAS, and one locus that overlapped with qOil-5-1 was found repeatedly and treated as the same locus. qOil-5-1 was further localized to a linkage disequilibrium block region of approximately 440 kb. These results will not only increase our understanding of the genetic control of seed oil content in soybean, but will also be helpful in marker-assisted selection for breeding high seed oil content soybean and gene cloning to elucidate the mechanisms of seed oil content.

Replication of linkage to quantitative trait loci: variation in location and magnitude of the lod score.

Science.gov (United States)

Hsueh, W C; Göring, H H; Blangero, J; Mitchell, B D

2001-01-01

Replication of linkage signals from independent samples is considered an important step toward verifying the significance of linkage signals in studies of complex traits. The purpose of this empirical investigation was to examine the variability in the precision of localizing a quantitative trait locus (QTL) by analyzing multiple replicates of a simulated data set with the use of variance components-based methods. Specifically, we evaluated across replicates the variation in both the magnitude and the location of the peak lod scores. We analyzed QTLs whose effects accounted for 10-37% of the phenotypic variance in the quantitative traits. Our analyses revealed that the precision of QTL localization was directly related to the magnitude of the QTL effect. For a QTL with effect accounting for > 20% of total phenotypic variation, > 90% of the linkage peaks fall within 10 cM from the true gene location. We found no evidence that, for a given magnitude of the lod score, the presence of interaction influenced the precision of QTL localization.

Identification of Genetic Loci Jointly Influencing Schizophrenia Risk and the Cognitive Traits of Verbal-Numerical Reasoning, Reaction Time, and General Cognitive Function.

Science.gov (United States)

Smeland, Olav B; Frei, Oleksandr; Kauppi, Karolina; Hill, W David; Li, Wen; Wang, Yunpeng; Krull, Florian; Bettella, Francesco; Eriksen, Jon A; Witoelar, Aree; Davies, Gail; Fan, Chun C; Thompson, Wesley K; Lam, Max; Lencz, Todd; Chen, Chi-Hua; Ueland, Torill; Jönsson, Erik G; Djurovic, Srdjan; Deary, Ian J; Dale, Anders M; Andreassen, Ole A

2017-10-01

Schizophrenia is associated with widespread cognitive impairments. Although cognitive deficits are one of the factors most strongly associated with functional outcome in schizophrenia, current treatment strategies largely fail to ameliorate these impairments. To develop more efficient treatment strategies in patients with schizophrenia, a better understanding of the pathogenesis of these cognitive deficits is needed. Accumulating evidence indicates that genetic risk of schizophrenia may contribute to cognitive dysfunction. To identify genomic regions jointly influencing schizophrenia and the cognitive domains of reaction time and verbal-numerical reasoning, as well as general cognitive function, a phenotype that captures the shared variation in performance across cognitive domains. Combining data from genome-wide association studies from multiple phenotypes using conditional false discovery rate analysis provides increased power to discover genetic variants and could elucidate shared molecular genetic mechanisms. Data from the following genome-wide association studies, published from July 24, 2014, to January 17, 2017, were combined: schizophrenia in the Psychiatric Genomics Consortium cohort (n = 79 757 [cases, 34 486; controls, 45 271]); verbal-numerical reasoning (n = 36 035) and reaction time (n = 111 483) in the UK Biobank cohort; and general cognitive function in CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) (n = 53 949) and COGENT (Cognitive Genomics Consortium) (n = 27 888). Genetic loci identified by conditional false discovery rate analysis. Brain messenger RNA expression and brain expression quantitative trait locus functionality were determined. Among the participants in the genome-wide association studies, 21 loci jointly influencing schizophrenia and cognitive traits were identified: 2 loci shared between schizophrenia and verbal-numerical reasoning, 6 loci shared between schizophrenia and

Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation.

Science.gov (United States)

Horikoshi, Momoko; Mӓgi, Reedik; van de Bunt, Martijn; Surakka, Ida; Sarin, Antti-Pekka; Mahajan, Anubha; Marullo, Letizia; Thorleifsson, Gudmar; Hӓgg, Sara; Hottenga, Jouke-Jan; Ladenvall, Claes; Ried, Janina S; Winkler, Thomas W; Willems, Sara M; Pervjakova, Natalia; Esko, Tõnu; Beekman, Marian; Nelson, Christopher P; Willenborg, Christina; Wiltshire, Steven; Ferreira, Teresa; Fernandez, Juan; Gaulton, Kyle J; Steinthorsdottir, Valgerdur; Hamsten, Anders; Magnusson, Patrik K E; Willemsen, Gonneke; Milaneschi, Yuri; Robertson, Neil R; Groves, Christopher J; Bennett, Amanda J; Lehtimӓki, Terho; Viikari, Jorma S; Rung, Johan; Lyssenko, Valeriya; Perola, Markus; Heid, Iris M; Herder, Christian; Grallert, Harald; Müller-Nurasyid, Martina; Roden, Michael; Hypponen, Elina; Isaacs, Aaron; van Leeuwen, Elisabeth M; Karssen, Lennart C; Mihailov, Evelin; Houwing-Duistermaat, Jeanine J; de Craen, Anton J M; Deelen, Joris; Havulinna, Aki S; Blades, Matthew; Hengstenberg, Christian; Erdmann, Jeanette; Schunkert, Heribert; Kaprio, Jaakko; Tobin, Martin D; Samani, Nilesh J; Lind, Lars; Salomaa, Veikko; Lindgren, Cecilia M; Slagboom, P Eline; Metspalu, Andres; van Duijn, Cornelia M; Eriksson, Johan G; Peters, Annette; Gieger, Christian; Jula, Antti; Groop, Leif; Raitakari, Olli T; Power, Chris; Penninx, Brenda W J H; de Geus, Eco; Smit, Johannes H; Boomsma, Dorret I; Pedersen, Nancy L; Ingelsson, Erik; Thorsteinsdottir, Unnur; Stefansson, Kari; Ripatti, Samuli; Prokopenko, Inga; McCarthy, Mark I; Morris, Andrew P

2015-07-01

Reference panels from the 1000 Genomes (1000G) Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE) Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS), supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI) at genome-wide significance, and two for fasting glucose (FG), none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3) and FG (GCK and G6PC2). The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.

Comparative mapping of quantitative trait loci for tassel-related traits ...

Indian Academy of Sciences (India)

QIANG YI

2018-03-15

Mar 15, 2018 ... in maize have evaluated flowering-related traits (Li et al. ... with Upadyayula et al. (2006). The measurements taken were TTL, the length (cm) of the tassel ...... M. Banziger, H. R. Mickelson and C. B. Penã–Valdivia), pp.

Quantitative trait loci identified for blood chemistry components of an advanced intercross line of chickens under heat stress.

Science.gov (United States)

Van Goor, Angelica; Ashwell, Christopher M; Persia, Michael E; Rothschild, Max F; Schmidt, Carl J; Lamont, Susan J

2016-04-14

Heat stress in poultry results in considerable economic losses and is a concern for both animal health and welfare. Physiological changes occur during periods of heat stress, including changes in blood chemistry components. A highly advanced intercross line, created from a broiler (heat susceptible) by Fayoumi (heat resistant) cross, was exposed to daily heat cycles for seven days starting at 22 days of age. Blood components measured pre-heat treatment and on the seventh day of heat treatment included pH, pCO2, pO2, base excess, HCO3, TCO2, K, Na, ionized Ca, hematocrit, hemoglobin, sO2, and glucose. A genome-wide association study (GWAS) for these traits and their calculated changes was conducted to identify quantitative trait loci (QTL) using a 600 K SNP panel. There were significant increases in pH, base excess, HCO3, TCO2, ionized Ca, hematocrit, hemoglobin, and sO2, and significant decreases in pCO2 and glucose after 7 days of heat treatment. Heritabilities ranged from 0.01-0.21 for pre-heat measurements, 0.01-0.23 for measurements taken during heat, and 0.00-0.10 for the calculated change due to heat treatment. All blood components were highly correlated within measurement days, but not correlated between measurement days. The GWAS revealed 61 QTL for all traits, located on GGA (Gallus gallus chromosome) 1, 3, 6, 9, 10, 12-14, 17, 18, 21-28, and Z. A functional analysis of the genes in these QTL regions identified the Angiopoietin pathway as significant. The QTL that co-localized for three or more traits were on GGA10, 22, 26, 28, and Z and revealed candidate genes for birds' response to heat stress. The results of this study contribute to our knowledge of levels and heritabilities of several blood components of chickens under thermoneutral and heat stress conditions. Most components responded to heat treatment. Mapped QTL may serve as markers for genomic selection to enhance heat tolerance in poultry. The Angiopoietin pathway is likely involved in the

Simulating the yield impacts of organ-level quantitative trait loci associated with drought response in maize: a "gene-to-phenotype" modeling approach.

Science.gov (United States)

Chenu, Karine; Chapman, Scott C; Tardieu, François; McLean, Greg; Welcker, Claude; Hammer, Graeme L

2009-12-01

Under drought, substantial genotype-environment (G x E) interactions impede breeding progress for yield. Identifying genetic controls associated with yield response is confounded by poor genetic correlations across testing environments. Part of this problem is related to our inability to account for the interplay of genetic controls, physiological traits, and environmental conditions throughout the crop cycle. We propose a modeling approach to bridge this "gene-to-phenotype" gap. For maize under drought, we simulated the impact of quantitative trait loci (QTL) controlling two key processes (leaf and silk elongation) that influence crop growth, water use, and grain yield. Substantial G x E interaction for yield was simulated for hypothetical recombinant inbred lines (RILs) across different seasonal patterns of drought. QTL that accelerated leaf elongation caused an increase in crop leaf area and yield in well-watered or preflowering water deficit conditions, but a reduction in yield under terminal stresses (as such "leafy" genotypes prematurely exhausted the water supply). The QTL impact on yield was substantially enhanced by including pleiotropic effects of these QTL on silk elongation and on consequent grain set. The simulations obtained illustrated the difficulty of interpreting the genetic control of yield for genotypes influenced only by the additive effects of QTL associated with leaf and silk growth. The results highlight the potential of integrative simulation modeling for gene-to-phenotype prediction and for exploiting G x E interactions for complex traits such as drought tolerance.

Statistical correction of the Winner's Curse explains replication variability in quantitative trait genome-wide association studies.

Directory of Open Access Journals (Sweden)

Cameron Palmer

2017-07-01

Full Text Available Genome-wide association studies (GWAS have identified hundreds of SNPs responsible for variation in human quantitative traits. However, genome-wide-significant associations often fail to replicate across independent cohorts, in apparent inconsistency with their apparent strong effects in discovery cohorts. This limited success of replication raises pervasive questions about the utility of the GWAS field. We identify all 332 studies of quantitative traits from the NHGRI-EBI GWAS Database with attempted replication. We find that the majority of studies provide insufficient data to evaluate replication rates. The remaining papers replicate significantly worse than expected (p < 10-14, even when adjusting for regression-to-the-mean of effect size between discovery- and replication-cohorts termed the Winner's Curse (p < 10-16. We show this is due in part to misreporting replication cohort-size as a maximum number, rather than per-locus one. In 39 studies accurately reporting per-locus cohort-size for attempted replication of 707 loci in samples with similar ancestry, replication rate matched expectation (predicted 458, observed 457, p = 0.94. In contrast, ancestry differences between replication and discovery (13 studies, 385 loci cause the most highly-powered decile of loci to replicate worse than expected, due to difference in linkage disequilibrium.

Using genetic markers to orient the edges in quantitative trait networks: the NEO software.

Science.gov (United States)

Aten, Jason E; Fuller, Tova F; Lusis, Aldons J; Horvath, Steve

2008-04-15

Systems genetic studies have been used to identify genetic loci that affect transcript abundances and clinical traits such as body weight. The pairwise correlations between gene expression traits and/or clinical traits can be used to define undirected trait networks. Several authors have argued that genetic markers (e.g expression quantitative trait loci, eQTLs) can serve as causal anchors for orienting the edges of a trait network. The availability of hundreds of thousands of genetic markers poses new challenges: how to relate (anchor) traits to multiple genetic markers, how to score the genetic evidence in favor of an edge orientation, and how to weigh the information from multiple markers. We develop and implement Network Edge Orienting (NEO) methods and software that address the challenges of inferring unconfounded and directed gene networks from microarray-derived gene expression data by integrating mRNA levels with genetic marker data and Structural Equation Model (SEM) comparisons. The NEO software implements several manual and automatic methods for incorporating genetic information to anchor traits. The networks are oriented by considering each edge separately, thus reducing error propagation. To summarize the genetic evidence in favor of a given edge orientation, we propose Local SEM-based Edge Orienting (LEO) scores that compare the fit of several competing causal graphs. SEM fitting indices allow the user to assess local and overall model fit. The NEO software allows the user to carry out a robustness analysis with regard to genetic marker selection. We demonstrate the utility of NEO by recovering known causal relationships in the sterol homeostasis pathway using liver gene expression data from an F2 mouse cross. Further, we use NEO to study the relationship between a disease gene and a biologically important gene co-expression module in liver tissue. The NEO software can be used to orient the edges of gene co-expression networks or quantitative trait

Identification of loci governing eight agronomic traits using a GBS-GWAS approach and validation by QTL mapping in soya bean.

Science.gov (United States)

Sonah, Humira; O'Donoughue, Louise; Cober, Elroy; Rajcan, Istvan; Belzile, François

2015-02-01

Soya bean is a major source of edible oil and protein for human consumption as well as animal feed. Understanding the genetic basis of different traits in soya bean will provide important insights for improving breeding strategies for this crop. A genome-wide association study (GWAS) was conducted to accelerate molecular breeding for the improvement of agronomic traits in soya bean. A genotyping-by-sequencing (GBS) approach was used to provide dense genome-wide marker coverage (>47,000 SNPs) for a panel of 304 short-season soya bean lines. A subset of 139 lines, representative of the diversity among these, was characterized phenotypically for eight traits under six environments (3 sites × 2 years). Marker coverage proved sufficient to ensure highly significant associations between the genes known to control simple traits (flower, hilum and pubescence colour) and flanking SNPs. Between one and eight genomic loci associated with more complex traits (maturity, plant height, seed weight, seed oil and protein) were also identified. Importantly, most of these GWAS loci were located within genomic regions identified by previously reported quantitative trait locus (QTL) for these traits. In some cases, the reported QTLs were also successfully validated by additional QTL mapping in a biparental population. This study demonstrates that integrating GBS and GWAS can be used as a powerful complementary approach to classical biparental mapping for dissecting complex traits in soya bean. © 2014 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

Science.gov (United States)

Berndt, Sonja I.; Gustafsson, Stefan; Mägi, Reedik; Ganna, Andrea; Wheeler, Eleanor; Feitosa, Mary F.; Justice, Anne E.; Monda, Keri L.; Croteau-Chonka, Damien C.; Day, Felix R.; Esko, Tõnu; Fall, Tove; Ferreira, Teresa; Gentilini, Davide; Jackson, Anne U.; Luan, Jian’an; Randall, Joshua C.; Vedantam, Sailaja; Willer, Cristen J.; Winkler, Thomas W.; Wood, Andrew R.; Workalemahu, Tsegaselassie; Hu, Yi-Juan; Lee, Sang Hong; Liang, Liming; Lin, Dan-Yu; Min, Josine L.; Neale, Benjamin M.; Thorleifsson, Gudmar; Yang, Jian; Albrecht, Eva; Amin, Najaf; Bragg-Gresham, Jennifer L.; Cadby, Gemma; den Heijer, Martin; Eklund, Niina; Fischer, Krista; Goel, Anuj; Hottenga, Jouke-Jan; Huffman, Jennifer E.; Jarick, Ivonne; Johansson, Åsa; Johnson, Toby; Kanoni, Stavroula; Kleber, Marcus E.; König, Inke R.; Kristiansson, Kati; Kutalik, Zoltán; Lamina, Claudia; Lecoeur, Cecile; Li, Guo; Mangino, Massimo; McArdle, Wendy L.; Medina-Gomez, Carolina; Müller-Nurasyid, Martina; Ngwa, Julius S.; Nolte, Ilja M.; Paternoster, Lavinia; Pechlivanis, Sonali; Perola, Markus; Peters, Marjolein J.; Preuss, Michael; Rose, Lynda M.; Shi, Jianxin; Shungin, Dmitry; Smith, Albert Vernon; Strawbridge, Rona J.; Surakka, Ida; Teumer, Alexander; Trip, Mieke D.; Tyrer, Jonathan; Van Vliet-Ostaptchouk, Jana V.; Vandenput, Liesbeth; Waite, Lindsay L.; Zhao, Jing Hua; Absher, Devin; Asselbergs, Folkert W.; Atalay, Mustafa; Attwood, Antony P.; Balmforth, Anthony J.; Basart, Hanneke; Beilby, John; Bonnycastle, Lori L.; Brambilla, Paolo; Bruinenberg, Marcel; Campbell, Harry; Chasman, Daniel I.; Chines, Peter S.; Collins, Francis S.; Connell, John M.; Cookson, William; de Faire, Ulf; de Vegt, Femmie; Dei, Mariano; Dimitriou, Maria; Edkins, Sarah; Estrada, Karol; Evans, David M.; Farrall, Martin; Ferrario, Marco M.; Ferrières, Jean; Franke, Lude; Frau, Francesca; Gejman, Pablo V.; Grallert, Harald; Grönberg, Henrik; Gudnason, Vilmundur; Hall, Alistair S.; Hall, Per; Hartikainen, Anna-Liisa; Hayward, Caroline; Heard-Costa, Nancy L.; Heath, Andrew C.; Hebebrand, Johannes; Homuth, Georg; Hu, Frank B.; Hunt, Sarah E.; Hyppönen, Elina; Iribarren, Carlos; Jacobs, Kevin B.; Jansson, John-Olov; Jula, Antti; Kähönen, Mika; Kathiresan, Sekar; Kee, Frank; Khaw, Kay-Tee; Kivimaki, Mika; Koenig, Wolfgang; Kraja, Aldi T.; Kumari, Meena; Kuulasmaa, Kari; Kuusisto, Johanna; Laitinen, Jaana H.; Lakka, Timo A.; Langenberg, Claudia; Launer, Lenore J.; Lind, Lars; Lindström, Jaana; Liu, Jianjun; Liuzzi, Antonio; Lokki, Marja-Liisa; Lorentzon, Mattias; Madden, Pamela A.; Magnusson, Patrik K.; Manunta, Paolo; Marek, Diana; März, Winfried; Mateo Leach, Irene; McKnight, Barbara; Medland, Sarah E.; Mihailov, Evelin; Milani, Lili; Montgomery, Grant W.; Mooser, Vincent; Mühleisen, Thomas W.; Munroe, Patricia B.; Musk, Arthur W.; Narisu, Narisu; Navis, Gerjan; Nicholson, George; Nohr, Ellen A.; Ong, Ken K.; Oostra, Ben A.; Palmer, Colin N.A.; Palotie, Aarno; Peden, John F.; Pedersen, Nancy; Peters, Annette; Polasek, Ozren; Pouta, Anneli; Pramstaller, Peter P.; Prokopenko, Inga; Pütter, Carolin; Radhakrishnan, Aparna; Raitakari, Olli; Rendon, Augusto; Rivadeneira, Fernando; Rudan, Igor; Saaristo, Timo E.; Sambrook, Jennifer G.; Sanders, Alan R.; Sanna, Serena; Saramies, Jouko; Schipf, Sabine; Schreiber, Stefan; Schunkert, Heribert; Shin, So-Youn; Signorini, Stefano; Sinisalo, Juha; Skrobek, Boris; Soranzo, Nicole; Stančáková, Alena; Stark, Klaus; Stephens, Jonathan C.; Stirrups, Kathleen; Stolk, Ronald P.; Stumvoll, Michael; Swift, Amy J.; Theodoraki, Eirini V.; Thorand, Barbara; Tregouet, David-Alexandre; Tremoli, Elena; Van der Klauw, Melanie M.; van Meurs, Joyce B.J.; Vermeulen, Sita H.; Viikari, Jorma; Virtamo, Jarmo; Vitart, Veronique; Waeber, Gérard; Wang, Zhaoming; Widén, Elisabeth; Wild, Sarah H.; Willemsen, Gonneke; Winkelmann, Bernhard R.; Witteman, Jacqueline C.M.; Wolffenbuttel, Bruce H.R.; Wong, Andrew; Wright, Alan F.; Zillikens, M. Carola; Amouyel, Philippe; Boehm, Bernhard O.; Boerwinkle, Eric; Boomsma, Dorret I.; Caulfield, Mark J.; Chanock, Stephen J.; Cupples, L. Adrienne; Cusi, Daniele; Dedoussis, George V.; Erdmann, Jeanette; Eriksson, Johan G.; Franks, Paul W.; Froguel, Philippe; Gieger, Christian; Gyllensten, Ulf; Hamsten, Anders; Harris, Tamara B.; Hengstenberg, Christian; Hicks, Andrew A.; Hingorani, Aroon; Hinney, Anke; Hofman, Albert; Hovingh, Kees G.; Hveem, Kristian; Illig, Thomas; Jarvelin, Marjo-Riitta; Jöckel, Karl-Heinz; Keinanen-Kiukaanniemi, Sirkka M.; Kiemeney, Lambertus A.; Kuh, Diana; Laakso, Markku; Lehtimäki, Terho; Levinson, Douglas F.; Martin, Nicholas G.; Metspalu, Andres; Morris, Andrew D.; Nieminen, Markku S.; Njølstad, Inger; Ohlsson, Claes; Oldehinkel, Albertine J.; Ouwehand, Willem H.; Palmer, Lyle J.; Penninx, Brenda; Power, Chris; Province, Michael A.; Psaty, Bruce M.; Qi, Lu; Rauramaa, Rainer; Ridker, Paul M.; Ripatti, Samuli; Salomaa, Veikko; Samani, Nilesh J.; Snieder, Harold; Sørensen, Thorkild I.A.; Spector, Timothy D.; Stefansson, Kari; Tönjes, Anke; Tuomilehto, Jaakko; Uitterlinden, André G.; Uusitupa, Matti; van der Harst, Pim; Vollenweider, Peter; Wallaschofski, Henri; Wareham, Nicholas J.; Watkins, Hugh; Wichmann, H.-Erich; Wilson, James F.; Abecasis, Goncalo R.; Assimes, Themistocles L.; Barroso, Inês; Boehnke, Michael; Borecki, Ingrid B.; Deloukas, Panos; Fox, Caroline S.; Frayling, Timothy; Groop, Leif C.; Haritunian, Talin; Heid, Iris M.; Hunter, David; Kaplan, Robert C.; Karpe, Fredrik; Moffatt, Miriam; Mohlke, Karen L.; O’Connell, Jeffrey R.; Pawitan, Yudi; Schadt, Eric E.; Schlessinger, David; Steinthorsdottir, Valgerdur; Strachan, David P.; Thorsteinsdottir, Unnur; van Duijn, Cornelia M.; Visscher, Peter M.; Di Blasio, Anna Maria; Hirschhorn, Joel N.; Lindgren, Cecilia M.; Morris, Andrew P.; Meyre, David; Scherag, André; McCarthy, Mark I.; Speliotes, Elizabeth K.; North, Kari E.; Loos, Ruth J.F.; Ingelsson, Erik

2014-01-01

Approaches exploiting extremes of the trait distribution may reveal novel loci for common traits, but it is unknown whether such loci are generalizable to the general population. In a genome-wide search for loci associated with upper vs. lower 5th percentiles of body mass index, height and waist-hip ratio, as well as clinical classes of obesity including up to 263,407 European individuals, we identified four new loci (IGFBP4, H6PD, RSRC1, PPP2R2A) influencing height detected in the tails and seven new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3, ZZZ3) for clinical classes of obesity. Further, we show that there is large overlap in terms of genetic structure and distribution of variants between traits based on extremes and the general population and little etiologic heterogeneity between obesity subgroups. PMID:23563607

Basal host resistance of barley to powdery mildew: connecting quantitative trait loci and candidate genes

NARCIS (Netherlands)

Aghnoum, R.; Marcel, T.C.; Johrde, A.; Pecchioni, N.; Schweizer, P.; Niks, R.E.

2010-01-01

The basal resistance of barley to powdery mildew (Blumeria graminis f. sp. hordei) is a quantitatively inherited trait that is based on nonhypersensitive mechanisms of defense. A functional genomic approach indicates that many plant candidate genes are involved in the defense against formation of

Expression quantitative trait loci for PAX8 contributes to the prognosis of hepatocellular carcinoma.

Directory of Open Access Journals (Sweden)

Shijie Ma

Full Text Available Paired-box family member PAX8 encodes a transcription factor that has a role in cell differentiation and cell growth and may participate in the prognosis of hepatocellular carcinoma (HCC. By bioinformatics analysis, we identified several single nucleotide polymorphisms (SNPs within a newly identified long non-coding RNA (lncRNA AC016683.6 as expression quantitative trait loci (eQTLs for PAX8. Hence, we hypothesized that PAX8eQTLs in lncRNA AC016683.6 may influence the HCC prognosis. We then performed a case-only study to assess the association between the two SNPs as well as the prognosis of HCC in 331 HBV-positive HCC patients without surgical treatment. Cox proportional hazard models were used for survival analysis with adjustments for the age, gender, smoking status, drinking status, Barcelona-Clinic Liver Cancer (BCLC stage, and chemotherapy or TACE (transcatheter hepatic arterial chemoembolization status. We found that the G allele of rs1110839 and the T allele of rs4848320 in PAX8was significantly associated with a better prognosis compared with the T allele of rs1110839 and the C allele of rs4848320 (adjusted HR = 0.74, 95% CI = 0.61-0.91, P = 0.004 for rs1110839 and adjusted HR = 0.71, 95% CI = 0.54-0.94, P = 0.015 for rs4848320 in the additive model. Furthermore, the combined effect of the variant genotypes for these two SNPs was more prominent in patients with the BCLC-C stage orpatients with chemotherapy or TACE. Although the exact biological function remains to be explored, our findings suggest a possible association of PAX8eQTLs in lncRNA AC016683.6 with the HCC prognosis inthe Chinese population. Further large and functional studies are needed to confirm our findings.

A genome-wide association study identifies protein quantitative trait loci (pQTLs.

Directory of Open Access Journals (Sweden)

David Melzer

2008-05-01

locations. The identification of protein quantitative trait loci (pQTLs may be a powerful complementary method of improving our understanding of disease pathways.

Interactions between Glu-1 and Glu-3 loci and associations of selected molecular markers with quality traits in winter wheat (Triticum aestivum L.) DH lines.

Science.gov (United States)

Krystkowiak, Karolina; Langner, Monika; Adamski, Tadeusz; Salmanowicz, Bolesław P; Kaczmarek, Zygmunt; Krajewski, Paweł; Surma, Maria

2017-02-01

The quality of wheat depends on a large complex of genes and environmental factors. The objective of this study was to identify quantitative trait loci controlling technological quality traits and their stability across environments, and to assess the impact of interaction between alleles at loci Glu-1 and Glu-3 on grain quality. DH lines were evaluated in field experiments over a period of 4 years, and genotyped using simple sequence repeat markers. Lines were analysed for grain yield (GY), thousand grain weight (TGW), protein content (PC), starch content (SC), wet gluten content (WG), Zeleny sedimentation value (ZS), alveograph parameter W (APW), hectolitre weight (HW), and grain hardness (GH). A number of QTLs for these traits were identified in all chromosome groups. The Glu-D1 locus influenced TGW, PC, SC, WG, ZS, APW, GH, while locus Glu-B1 affected only PC, ZS, and WG. Most important marker-trait associations were found on chromosomes 1D and 5D. Significant effects of interaction between Glu-1 and Glu-3 loci on technological properties were recorded, and in all types of this interaction positive effects of Glu-D1 locus on grain quality were observed, whereas effects of Glu-B1 locus depended on alleles at Glu-3 loci. Effects of Glu-A3 and Glu-D3 loci per se were not significant, while their interaction with alleles present at other loci encoding HMW and LMW were important. These results indicate that selection of wheat genotypes with predicted good bread-making properties should be based on the allelic composition both in Glu-1 and Glu-3 loci, and confirm the predominant effect of Glu-D1d allele on technological properties of wheat grains.

High-throughput SNP genotyping in Cucurbita pepo for map construction and quantitative trait loci mapping.

Science.gov (United States)

Esteras, Cristina; Gómez, Pedro; Monforte, Antonio J; Blanca, José; Vicente-Dólera, Nelly; Roig, Cristina; Nuez, Fernando; Picó, Belén

2012-02-22

Cucurbita pepo is a member of the Cucurbitaceae family, the second- most important horticultural family in terms of economic importance after Solanaceae. The "summer squash" types, including Zucchini and Scallop, rank among the highest-valued vegetables worldwide. There are few genomic tools available for this species.The first Cucurbita transcriptome, along with a large collection of Single Nucleotide Polymorphisms (SNP), was recently generated using massive sequencing. A set of 384 SNP was selected to generate an Illumina GoldenGate assay in order to construct the first SNP-based genetic map of Cucurbita and map quantitative trait loci (QTL). We herein present the construction of the first SNP-based genetic map of Cucurbita pepo using a population derived from the cross of two varieties with contrasting phenotypes, representing the main cultivar groups of the species' two subspecies: Zucchini (subsp. pepo) × Scallop (subsp. ovifera). The mapping population was genotyped with 384 SNP, a set of selected EST-SNP identified in silico after massive sequencing of the transcriptomes of both parents, using the Illumina GoldenGate platform. The global success rate of the assay was higher than 85%. In total, 304 SNP were mapped, along with 11 SSR from a previous map, giving a map density of 5.56 cM/marker. This map was used to infer syntenic relationships between C. pepo and cucumber and to successfully map QTL that control plant, flowering and fruit traits that are of benefit to squash breeding. The QTL effects were validated in backcross populations. Our results show that massive sequencing in different genotypes is an excellent tool for SNP discovery, and that the Illumina GoldenGate platform can be successfully applied to constructing genetic maps and performing QTL analysis in Cucurbita. This is the first SNP-based genetic map in the Cucurbita genus and is an invaluable new tool for biological research, especially considering that most of these markers are located in

Discovery and Fine-Mapping of Glycaemic and Obesity-Related Trait Loci Using High-Density Imputation.

Directory of Open Access Journals (Sweden)

Momoko Horikoshi

2015-07-01

Full Text Available Reference panels from the 1000 Genomes (1000G Project Consortium provide near complete coverage of common and low-frequency genetic variation with minor allele frequency ≥0.5% across European ancestry populations. Within the European Network for Genetic and Genomic Epidemiology (ENGAGE Consortium, we have undertaken the first large-scale meta-analysis of genome-wide association studies (GWAS, supplemented by 1000G imputation, for four quantitative glycaemic and obesity-related traits, in up to 87,048 individuals of European ancestry. We identified two loci for body mass index (BMI at genome-wide significance, and two for fasting glucose (FG, none of which has been previously reported in larger meta-analysis efforts to combine GWAS of European ancestry. Through conditional analysis, we also detected multiple distinct signals of association mapping to established loci for waist-hip ratio adjusted for BMI (RSPO3 and FG (GCK and G6PC2. The index variant for one association signal at the G6PC2 locus is a low-frequency coding allele, H177Y, which has recently been demonstrated to have a functional role in glucose regulation. Fine-mapping analyses revealed that the non-coding variants most likely to drive association signals at established and novel loci were enriched for overlap with enhancer elements, which for FG mapped to promoter and transcription factor binding sites in pancreatic islets, in particular. Our study demonstrates that 1000G imputation and genetic fine-mapping of common and low-frequency variant association signals at GWAS loci, integrated with genomic annotation in relevant tissues, can provide insight into the functional and regulatory mechanisms through which their effects on glycaemic and obesity-related traits are mediated.

Mapping quantitative trait loci (QTLs for fatty acid composition in an interspecific cross of oil palm

Directory of Open Access Journals (Sweden)

Sharma Mukesh

2009-08-01

Full Text Available Abstract Background Marker Assisted Selection (MAS is well suited to a perennial crop like oil palm, in which the economic products are not produced until several years after planting. The use of DNA markers for selection in such crops can greatly reduce the number of breeding cycles needed. With the use of DNA markers, informed decisions can be made at the nursery stage, regarding which individuals should be retained as breeding stock, which are satisfactory for agricultural production, and which should be culled. The trait associated with oil quality, measured in terms of its fatty acid composition, is an important agronomic trait that can eventually be tracked using molecular markers. This will speed up the production of new and improved oil palm planting materials. Results A map was constructed using AFLP, RFLP and SSR markers for an interspecific cross involving a Colombian Elaeis oleifera (UP1026 and a Nigerian E. guinneensis (T128. A framework map was generated for the male parent, T128, using Joinmap ver. 4.0. In the paternal (E. guineensis map, 252 markers (199 AFLP, 38 RFLP and 15 SSR could be ordered in 21 linkage groups (1815 cM. Interval mapping and multiple-QTL model (MQM mapping (also known as composite interval mapping, CIM were used to detect quantitative trait loci (QTLs controlling oil quality (measured in terms of iodine value and fatty acid composition. At a 5% genome-wide significance threshold level, QTLs associated with iodine value (IV, myristic acid (C14:0, palmitic acid (C16:0, palmitoleic acid (C16:1, stearic acid (C18:0, oleic acid (C18:1 and linoleic acid (C18:2 content were detected. One genomic region on Group 1 appears to be influencing IV, C14:0, C16:0, C18:0 and C18:1 content. Significant QTL for C14:0, C16:1, C18:0 and C18:1 content was detected around the same locus on Group 15, thus revealing another major locus influencing fatty acid composition in oil palm. Additional QTL for C18:0 was detected on Group 3

Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits.

Science.gov (United States)

Justice, Anne E; Winkler, Thomas W; Feitosa, Mary F; Graff, Misa; Fisher, Virginia A; Young, Kristin; Barata, Llilda; Deng, Xuan; Czajkowski, Jacek; Hadley, David; Ngwa, Julius S; Ahluwalia, Tarunveer S; Chu, Audrey Y; Heard-Costa, Nancy L; Lim, Elise; Perez, Jeremiah; Eicher, John D; Kutalik, Zoltán; Xue, Luting; Mahajan, Anubha; Renström, Frida; Wu, Joseph; Qi, Qibin; Ahmad, Shafqat; Alfred, Tamuno; Amin, Najaf; Bielak, Lawrence F; Bonnefond, Amelie; Bragg, Jennifer; Cadby, Gemma; Chittani, Martina; Coggeshall, Scott; Corre, Tanguy; Direk, Nese; Eriksson, Joel; Fischer, Krista; Gorski, Mathias; Neergaard Harder, Marie; Horikoshi, Momoko; Huang, Tao; Huffman, Jennifer E; Jackson, Anne U; Justesen, Johanne Marie; Kanoni, Stavroula; Kinnunen, Leena; Kleber, Marcus E; Komulainen, Pirjo; Kumari, Meena; Lim, Unhee; Luan, Jian'an; Lyytikäinen, Leo-Pekka; Mangino, Massimo; Manichaikul, Ani; Marten, Jonathan; Middelberg, Rita P S; Müller-Nurasyid, Martina; Navarro, Pau; Pérusse, Louis; Pervjakova, Natalia; Sarti, Cinzia; Smith, Albert Vernon; Smith, Jennifer A; Stančáková, Alena; Strawbridge, Rona J; Stringham, Heather M; Sung, Yun Ju; Tanaka, Toshiko; Teumer, Alexander; Trompet, Stella; van der Laan, Sander W; van der Most, Peter J; Van Vliet-Ostaptchouk, Jana V; Vedantam, Sailaja L; Verweij, Niek; Vink, Jacqueline M; Vitart, Veronique; Wu, Ying; Yengo, Loic; Zhang, Weihua; Hua Zhao, Jing; Zimmermann, Martina E; Zubair, Niha; Abecasis, Gonçalo R; Adair, Linda S; Afaq, Saima; Afzal, Uzma; Bakker, Stephan J L; Bartz, Traci M; Beilby, John; Bergman, Richard N; Bergmann, Sven; Biffar, Reiner; Blangero, John; Boerwinkle, Eric; Bonnycastle, Lori L; Bottinger, Erwin; Braga, Daniele; Buckley, Brendan M; Buyske, Steve; Campbell, Harry; Chambers, John C; Collins, Francis S; Curran, Joanne E; de Borst, Gert J; de Craen, Anton J M; de Geus, Eco J C; Dedoussis, George; Delgado, Graciela E; den Ruijter, Hester M; Eiriksdottir, Gudny; Eriksson, Anna L; Esko, Tõnu; Faul, Jessica D; Ford, Ian; Forrester, Terrence; Gertow, Karl; Gigante, Bruna; Glorioso, Nicola; Gong, Jian; Grallert, Harald; Grammer, Tanja B; Grarup, Niels; Haitjema, Saskia; Hallmans, Göran; Hamsten, Anders; Hansen, Torben; Harris, Tamara B; Hartman, Catharina A; Hassinen, Maija; Hastie, Nicholas D; Heath, Andrew C; Hernandez, Dena; Hindorff, Lucia; Hocking, Lynne J; Hollensted, Mette; Holmen, Oddgeir L; Homuth, Georg; Jan Hottenga, Jouke; Huang, Jie; Hung, Joseph; Hutri-Kähönen, Nina; Ingelsson, Erik; James, Alan L; Jansson, John-Olov; Jarvelin, Marjo-Riitta; Jhun, Min A; Jørgensen, Marit E; Juonala, Markus; Kähönen, Mika; Karlsson, Magnus; Koistinen, Heikki A; Kolcic, Ivana; Kolovou, Genovefa; Kooperberg, Charles; Krämer, Bernhard K; Kuusisto, Johanna; Kvaløy, Kirsti; Lakka, Timo A; Langenberg, Claudia; Launer, Lenore J; Leander, Karin; Lee, Nanette R; Lind, Lars; Lindgren, Cecilia M; Linneberg, Allan; Lobbens, Stephane; Loh, Marie; Lorentzon, Mattias; Luben, Robert; Lubke, Gitta; Ludolph-Donislawski, Anja; Lupoli, Sara; Madden, Pamela A F; Männikkö, Reija; Marques-Vidal, Pedro; Martin, Nicholas G; McKenzie, Colin A; McKnight, Barbara; Mellström, Dan; Menni, Cristina; Montgomery, Grant W; Musk, Aw Bill; Narisu, Narisu; Nauck, Matthias; Nolte, Ilja M; Oldehinkel, Albertine J; Olden, Matthias; Ong, Ken K; Padmanabhan, Sandosh; Peyser, Patricia A; Pisinger, Charlotta; Porteous, David J; Raitakari, Olli T; Rankinen, Tuomo; Rao, D C; Rasmussen-Torvik, Laura J; Rawal, Rajesh; Rice, Treva; Ridker, Paul M; Rose, Lynda M; Bien, Stephanie A; Rudan, Igor; Sanna, Serena; Sarzynski, Mark A; Sattar, Naveed; Savonen, Kai; Schlessinger, David; Scholtens, Salome; Schurmann, Claudia; Scott, Robert A; Sennblad, Bengt; Siemelink, Marten A; Silbernagel, Günther; Slagboom, P Eline; Snieder, Harold; Staessen, Jan A; Stott, David J; Swertz, Morris A; Swift, Amy J; Taylor, Kent D; Tayo, Bamidele O; Thorand, Barbara; Thuillier, Dorothee; Tuomilehto, Jaakko; Uitterlinden, Andre G; Vandenput, Liesbeth; Vohl, Marie-Claude; Völzke, Henry; Vonk, Judith M; Waeber, Gérard; Waldenberger, Melanie; Westendorp, R G J; Wild, Sarah; Willemsen, Gonneke; Wolffenbuttel, Bruce H R; Wong, Andrew; Wright, Alan F; Zhao, Wei; Zillikens, M Carola; Baldassarre, Damiano; Balkau, Beverley; Bandinelli, Stefania; Böger, Carsten A; Boomsma, Dorret I; Bouchard, Claude; Bruinenberg, Marcel; Chasman, Daniel I; Chen, Yii-DerIda; Chines, Peter S; Cooper, Richard S; Cucca, Francesco; Cusi, Daniele; Faire, Ulf de; Ferrucci, Luigi; Franks, Paul W; Froguel, Philippe; Gordon-Larsen, Penny; Grabe, Hans-Jörgen; Gudnason, Vilmundur; Haiman, Christopher A; Hayward, Caroline; Hveem, Kristian; Johnson, Andrew D; Wouter Jukema, J; Kardia, Sharon L R; Kivimaki, Mika; Kooner, Jaspal S; Kuh, Diana; Laakso, Markku; Lehtimäki, Terho; Marchand, Loic Le; März, Winfried; McCarthy, Mark I; Metspalu, Andres; Morris, Andrew P; Ohlsson, Claes; Palmer, Lyle J; Pasterkamp, Gerard; Pedersen, Oluf; Peters, Annette; Peters, Ulrike; Polasek, Ozren; Psaty, Bruce M; Qi, Lu; Rauramaa, Rainer; Smith, Blair H; Sørensen, Thorkild I A; Strauch, Konstantin; Tiemeier, Henning; Tremoli, Elena; van der Harst, Pim; Vestergaard, Henrik; Vollenweider, Peter; Wareham, Nicholas J; Weir, David R; Whitfield, John B; Wilson, James F; Tyrrell, Jessica; Frayling, Timothy M; Barroso, Inês; Boehnke, Michael; Deloukas, Panagiotis; Fox, Caroline S; Hirschhorn, Joel N; Hunter, David J; Spector, Tim D; Strachan, David P; van Duijn, Cornelia M; Heid, Iris M; Mohlke, Karen L; Marchini, Jonathan; Loos, Ruth J F; Kilpeläinen, Tuomas O; Liu, Ching-Ti; Borecki, Ingrid B; North, Kari E; Cupples, L Adrienne

2017-04-26

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution.

High Resolution Consensus Mapping of Quantitative Trait Loci for Fiber Strength, Length and Micronaire on Chromosome 25 of the Upland Cotton (Gossypium hirsutum L.).

Science.gov (United States)

Zhang, Zhen; Li, Junwen; Muhammad, Jamshed; Cai, Juan; Jia, Fei; Shi, Yuzhen; Gong, Juwu; Shang, Haihong; Liu, Aiying; Chen, Tingting; Ge, Qun; Palanga, Koffi Kibalou; Lu, Quanwei; Deng, Xiaoying; Tan, Yunna; Li, Wei; Sun, Linyang; Gong, Wankui; Yuan, Youlu

2015-01-01

Cotton (Gossypium hirsutum L.) is an important agricultural crop that provides renewable natural fiber resources for the global textile industry. Technological developments in the textile industry and improvements in human living standards have increased the requirement for supplies and better quality cotton. Upland cotton 0-153 is an elite cultivar harboring strong fiber strength genes. To conduct quantitative trait locus (QTL) mapping for fiber quality in 0-153, we developed a population of 196 recombinant inbred lines (RILs) from a cross between 0-153 and sGK9708. The fiber quality traits in 11 environments were measured and a genetic linkage map of chromosome 25 comprising 210 loci was constructed using this RIL population, mainly using simple sequence repeat markers and single nucleotide polymorphism markers. QTLs were identified across diverse environments using the composite interval mapping method. A total of 37 QTLs for fiber quality traits were identified on chromosome 25, of which 17 were stably expressed in at least in two environments. A stable fiber strength QTL, qFS-chr25-4, which was detected in seven environments and was located in the marker interval between CRI-SNP120491 and BNL2572, could explain 6.53%-11.83% of the observed phenotypic variations. Meta-analysis also confirmed the above QTLs with previous reports. Application of these QTLs could contribute to improving fiber quality and provide information for marker-assisted selection.

Whole Genome Scan to Detect Chromosomal Regions Affecting Multiple Traits in Dairy Cattle

NARCIS (Netherlands)

Schrooten, C.; Bink, M.C.A.M.; Bovenhuis, H.

2004-01-01

Chromosomal regions affecting multiple traits ( multiple trait quantitative trait regions or MQR) in dairy cattle were detected using a method based on results from single trait analyses to detect quantitative trait loci (QTL). The covariance between contrasts for different traits in single trait

A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

NARCIS (Netherlands)

Ried, Janina S; Jeff M, Janina; Bragg-Gresham, Jennifer L; van Dongen, Jenny; Huffman, Jennifer E; Ahluwalia, Tarunveer S; Cadby, Gemma; Eklund, Niina; Eriksson, Joel; Esko, Tõnu; Feitosa, Mary F; Goel, Anuj; Gorski, Mathias; Hayward, Caroline; Heard-Costa, Nancy L; Jackson, Anne U; Jokinen, Eero; Kanoni, Stavroula; Kristiansson, Kati; Kutalik, Zoltán; Lahti, Jari; Luan, Jian'an; Mägi, Reedik; Mahajan, Anubha; Mangino, Massimo; Medina-Gomez, Carolina; Monda, Keri L; Nolte, Ilja M; Pérusse, Louis; Prokopenko, Inga; Qi, Lu; Rose, Lynda M; Salvi, Erika; Smith, Megan T; Snieder, Harold; Stančáková, Alena; Ju Sung, Yun; Tachmazidou, Ioanna; Teumer, Alexander; Thorleifsson, Gudmar; van der Harst, Pim; Walker, Ryan W; Wang, Sophie R; Wild, Sarah H; Willems, Sara M; Wong, Andrew; Zhang, Weihua; Albrecht, Eva; Couto Alves, Alexessander; Bakker, Stephan J L; Barlassina, Cristina; Bartz, Traci M; Beilby, John; Bellis, Claire; Bergman, Richard N; Bergmann, Sven; Blangero, John; Blüher, Matthias; Boerwinkle, Eric; Bonnycastle, Lori L; Bornstein, Stefan R; Bruinenberg, Marcel; Campbell, Harry; Chen, Yii-Der Ida; Chiang, Charleston W K; Chines, Peter S; Collins, Francis S; Cucca, Fracensco; Cupples, L Adrienne; D'Avila, Francesca; de Geus, Eco J C; Dedoussis, George; Dimitriou, Maria; Döring, Angela; Eriksson, Johan G; Farmaki, Aliki-Eleni; Farrall, Martin; Ferreira, Teresa; Fischer, Krista; Forouhi, Nita G; Friedrich, Nele; Gjesing, Anette Prior; Glorioso, Nicola; Graff, Mariaelisa; Grallert, Harald; Grarup, Niels; Gräßler, Jürgen; Grewal, Jagvir; Hamsten, Anders; Harder, Marie Neergaard; Hartman, Catharina A; Hassinen, Maija; Hastie, Nicholas; Hattersley, Andrew Tym; Havulinna, Aki S; Heliövaara, Markku; Hillege, Hans; Hofman, Albert; Holmen, Oddgeir; Homuth, Georg; Hottenga, Jouke-Jan; Hui, Jennie; Husemoen, Lise Lotte; Hysi, Pirro G; Isaacs, Aaron; Ittermann, Till; Jalilzadeh, Shapour; James, Alan L; Jørgensen, Torben; Jousilahti, Pekka; Jula, Antti; Marie Justesen, Johanne; Justice, Anne E; Kähönen, Mika; Karaleftheri, Maria; Tee Khaw, Kay; Keinanen-Kiukaanniemi, Sirkka M; Kinnunen, Leena; Knekt, Paul B; Koistinen, Heikki A; Kolcic, Ivana; Kooner, Ishminder K; Koskinen, Seppo; Kovacs, Peter; Kyriakou, Theodosios; Laitinen, Tomi; Langenberg, Claudia; Lewin, Alexandra M; Lichtner, Peter; Lindgren, Cecilia M; Lindström, Jaana; Linneberg, Allan; Lorbeer, Roberto; Lorentzon, Mattias; Luben, Robert; Lyssenko, Valeriya; Männistö, Satu; Manunta, Paolo; Leach, Irene Mateo; McArdle, Wendy L; Mcknight, Barbara; Mohlke, Karen L; Mihailov, Evelin; Milani, Lili; Mills, Rebecca; Montasser, May E; Morris, Andrew P; Müller, Gabriele; Musk, Arthur W; Narisu, Narisu; Ong, Ken K; Oostra, Ben A; Osmond, Clive; Palotie, Aarno; Pankow, James S; Paternoster, Lavinia; Penninx, Brenda W; Pichler, Irene; Pilia, Maria G; Polašek, Ozren; Pramstaller, Peter P; Raitakari, Olli T; Rankinen, Tuomo; Rao, D C; Rayner, Nigel W; Ribel-Madsen, Rasmus; Rice, Treva K; Richards, Marcus; Ridker, Paul M; Rivadeneira, Fernando; Ryan, Kathy A; Sanna, Serena; Sarzynski, Mark A; Scholtens, Salome; Scott, Robert A; Sebert, Sylvain; Southam, Lorraine; Sparsø, Thomas Hempel; Steinthorsdottir, Valgerdur; Stirrups, Kathleen; Stolk, Ronald P; Strauch, Konstantin; Stringham, Heather M; Swertz, Morris A; Swift, Amy J; Tönjes, Anke; Tsafantakis, Emmanouil; van der Most, Peter J; Van Vliet-Ostaptchouk, Jana V; Vandenput, Liesbeth; Vartiainen, Erkki; Venturini, Cristina; Verweij, Niek; Viikari, Jorma S; Vitart, Veronique; Vohl, Marie-Claude; Vonk, Judith M; Waeber, Gérard; Widén, Elisabeth; Willemsen, Gonneke; Wilsgaard, Tom; Winkler, Thomas W; Wright, Alan F; Yerges-Armstrong, Laura M; Hua Zhao, Jing; Carola Zillikens, M; Boomsma, Dorret I; Bouchard, Claude; Chambers, John C; Chasman, Daniel I; Cusi, Daniele; Gansevoort, Ron T; Gieger, Christian; Hansen, Torben; Hicks, Andrew A; Hu, Frank; Hveem, Kristian; Jarvelin, Marjo-Riitta; Kajantie, Eero; Kooner, Jaspal S; Kuh, Diana; Kuusisto, Johanna; Laakso, Markku; Lakka, Timo A; Lehtimäki, Terho; Metspalu, Andres; Njølstad, Inger; Ohlsson, Claes; Oldehinkel, Albertine J; Palmer, Lyle J; Pedersen, Oluf; Perola, Markus; Peters, Annette; Psaty, Bruce M; Puolijoki, Hannu; Rauramaa, Rainer; Rudan, Igor; Salomaa, Veikko; Schwarz, Peter E H; Shudiner, Alan R; Smit, Jan H; Sørensen, Thorkild I A; Spector, Timothy D; Stefansson, Kari; Stumvoll, Michael; Tremblay, Angelo; Tuomilehto, Jaakko; Uitterlinden, André G; Uusitupa, Matti; Völker, Uwe; Vollenweider, Peter; Wareham, Nicholas J; Watkins, Hugh; Wilson, James F; Zeggini, Eleftheria; Abecasis, Goncalo R; Boehnke, Michael; Borecki, Ingrid B; Deloukas, Panos; van Duijn, Cornelia M; Fox, Caroline; Groop, Leif C; Heid, Iris M; Hunter, David J; Kaplan, Robert C; McCarthy, Mark I; North, Kari E; O'Connell, Jeffrey R; Schlessinger, David; Thorsteinsdottir, Unnur; Strachan, David P; Frayling, Timothy; Hirschhorn, Joel N; Müller-Nurasyid, Martina; Loos, Ruth J F

2016-01-01

Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates

A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

DEFF Research Database (Denmark)

Ried, Janina S; Jeff M, Janina; Chu, Audrey Y

2016-01-01

Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculate...

A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

NARCIS (Netherlands)

J.S. Ried (Janina); J. Jeff (Janina); A.Y. Chu (Audrey Y); Bragg-Gresham, J.L. (Jennifer L.); J. van Dongen (Jenny); J.E. Huffman (Jennifer); T.S. Ahluwalia (Tarunveer Singh); G. Cadby (Gemma); N. Eklund (Niina); J. Eriksson (Joel); T. Esko (Tõnu); M.F. Feitosa (Mary Furlan); A. Goel (Anuj); M. Gorski (Mathias); C. Hayward (Caroline); N.L. Heard-Costa (Nancy); A.U. Jackson (Anne); Jokinen, E. (Eero); S. Kanoni (Stavroula); K. Kristiansson (Kati); Z. Kutalik (Zoltán); J. Lahti (Jari); J. Luan (Jian'An); R. Mägi (Reedik); A. Mahajan (Anubha); M. Mangino (Massimo); M.C. Medina-Gomez (Carolina); K.L. Monda (Keri); I.M. Nolte (Ilja); L. Perusse (Louis); I. Prokopenko (Inga); Qi, L. (Lu); L.M. Rose (Lynda); Salvi, E. (Erika); Smith, M.T. (Megan T.); H. Snieder (Harold); Standáková, A. (Alena); Ju Sung, Y. (Yun); I. Tachmazidou (Ioanna); A. Teumer (Alexander); G. Thorleifsson (Gudmar); P. van der Harst (Pim); Walker, R.W. (Ryan W.); S.R. Wang (Sophie); S.H. Wild (Sarah); S.M. Willems (Sara); A. Wong (Andrew); W. Zhang (Weihua); E. Albrecht (Eva); A. Couto-Alves (Alexessander); S.J.L. Bakker (Stephan); Barlassina, C. (Cristina); T.M. Bartz (Traci M.); J.P. Beilby (John); C. Bellis (Claire); Bergman, R.N. (Richard N.); S.M. Bergmann (Sven); J. Blangero (John); M. Blüher (Matthias); E.A. Boerwinkle (Eric); L.L. Bonnycastle (Lori); S.R. Bornstein (Stefan R.); M. Bruinenberg (M.); H. Campbell (Harry); Y.-D.I. Chen (Yii-Der Ida); Chiang, C.W.K. (Charleston W. K.); P.S. Chines (Peter); F.S. Collins (Francis); Cucca, F. (Fracensco); L.A. Cupples (Adrienne); D'avila, F. (Francesca); E.J.C. de Geus (Eco); G.V. Dedoussis (George); M. Dimitriou (Maria); A. Döring (Angela); K. Hagen (Knut); A.-E. Farmaki (Aliki-Eleni); M. Farrall (Martin); T. Ferreira (Teresa); K. Fischer (Krista); N.G. Forouhi (Nita); N. Friedrich (Nele); A.P. Gjesing (Anette); N. Glorioso (Nicola); M.J. Graff (Maud J.L.); H. Grallert (Harald); N. Grarup (Niels); J. Gräßler (Jürgen); J. Grewal (Jagvir); A. Hamsten (Anders); Harder, M.N. (Marie Neergaard); Hartman, C.A. (Catharina A.); Hassinen, M. (Maija); N. Hastie (Nick); A.T. Hattersley (Andrew); A.S. Havulinna (Aki); M. Heliovaara (Markku); H.L. Hillege (Hans); A. Hofman (Albert); O.L. Holmen (Oddgeir); G. Homuth (Georg); J.J. Hottenga (Jouke Jan); J. Hui (Jennie); L.L.N. Husemoen (Lise Lotte); P.G. Hysi (Pirro); A.J. Isaacs (Aaron); T. Ittermann (Till); S. Jalilzadeh (Shapour); A. James (Alan); T. Jorgensen (Torben); P. Jousilahti (Pekka); A. Jula (Antti); Marie Justesen, J. (Johanne); A.E. Justice (Anne); M. Kähönen (Mika); M. Karaleftheri (Maria); Tee Khaw, K. (Kay); S. Keinanen-Kiukaanniemi (Sirkka); L. Kinnunen (Leena); P. Knekt; H. Koistinen (Heikki); I. Kolcic (Ivana); I.K. Kooner (Ishminder K.); S. Koskinen (Seppo); P. Kovacs (Peter); T. Kyriakou (Theodosios); Laitinen, T. (Tomi); C. Langenberg (Claudia); A. Lewin (Alex); P. Lichtner (Peter); C.M. Lindgren (Cecilia); J. Lindström (Jaana); A. Linneberg (Allan); R. Lorbeer (Roberto); M. Lorentzon (Mattias); R.N. Luben (Robert); V. Lyssenko (Valeriya); S. Männistö (Satu); P. Manunta (Paolo); I.M. Leach (Irene Mateo); W.L. McArdle (Wendy); Mcknight, B. (Barbara); K.L. Mohlke (Karen); E. Mihailov (Evelin); L. Milani (Lili); R. Mills (Rebecca); M.E. Montasser (May E.); A.P. Morris (Andrew); G. Müller (Gabriele); Musk, A.W. (Arthur W.); N. Narisu (Narisu); K.K. Ong (Ken K.); B.A. Oostra (Ben); C. Osmond (Clive); A. Palotie (Aarno); J.S. Pankow (James); L. Paternoster (Lavinia); B.W.J.H. Penninx (Brenda); I. Pichler (Irene); M.G. Pilia (Maria Grazia); O. Polasek (Ozren); P.P. Pramstaller (Peter Paul); O.T. Raitakari (Olli T.); T. Rankinen (Tuomo); Rao, D.C.; N.W. Rayner (Nigel William); Ribel-Madsen, R. (Rasmus); Rice, T.K. (Treva K.); Richards, M. (Marcus); P.M. Ridker (Paul); F. Rivadeneira Ramirez (Fernando); Ryan, K.A. (Kathy A.); S. Sanna (Serena); M.A. Sarzynski (Mark A.); S. Scholtens (Salome); R.A. Scott (Robert); S. Sebert (Sylvain); L. Southam (Lorraine); T. Sparsø (Thomas); V. Steinthorsdottir (Valgerdur); K. Stirrups (Kathy); R.P. Stolk (Ronald); K. Strauch (Konstantin); H.M. Stringham (Heather); M. Swertz (Morris); A.J. Swift (Amy); A. Tönjes (Anke); E. Tsafantakis (Emmanouil); P.J. van der Most (Peter); J.V. van Vliet-Ostaptchouk (Jana); L. Vandenput (Liesbeth); Vartiainen, E. (Erkki); C. Venturini (Cristina); N. Verweij (Niek); J. Viikari (Jorma); Vitart, V. (Veronique); M.-C. Vohl (Marie-Claude); J.M. Vonk (Judith); G. Waeber (Gérard); E. Widen (Elisabeth); G.A.H.M. Willemsen (Gonneke); T. Wilsgaard (Tom); T.W. Winkler (Thomas W.); A.F. Wright (Alan); L.M. Yerges-Armstrong (Laura); Zhao, J.H. (Jing Hua); M.C. Zillikens (Carola); D.I. Boomsma (Dorret); C. Bouchard (Claude); J.C. Chambers (John); D.I. Chasman (Daniel); D. Cusi (Daniele); R.T. Gansevoort (Ron); C. Gieger (Christian); T. Hansen (T.); A.A. Hicks (Andrew); Hu, F. (Frank); K. Hveem (Kristian); M.-R. Jarvelin (Marjo-Riitta); E. Kajantie (Eero); J.S. Kooner (Jaspal S.); D. Kuh (Diana); J. Kuusisto (Johanna); M. Laakso (Markku); T.A. Lakka (Timo); T. Lehtimäki (Terho); A. Metspalu (Andres); I. Njølstad (Inger); C. Ohlsson (Claes); A.J. Oldehinkel (Albertine); Palmer, L.J. (Lyle J.); O. Pedersen (Oluf); M. Perola (Markus); A. Peters (Annette); B.M. Psaty (Bruce); Puolijoki, H. (Hannu); R. Rauramaa (Rainer); I. Rudan (Igor); V. Salomaa (Veikko); P.E.H. Schwarz (Peter); Shudiner, A.R. (Alan R.); J.H. Smit (Jan); T.I.A. Sørensen (Thorkild); T.D. Spector (Timothy); J-A. Zwart (John-Anker); M. Stumvoll (Michael); Tremblay, A. (Angelo); J. Tuomilehto (Jaakko); A.G. Uitterlinden (André); Uusitupa, M. (Matti); U. Völker (Uwe); P. Vollenweider (Peter); N.J. Wareham (Nick); H. Watkins (Hugh); J.F. Wilson (James); E. Zeggini (Eleftheria); G.R. Abecasis (Gonçalo); M. Boehnke (Michael); I.B. Borecki (Ingrid); P. Deloukas (Panagiotis); C.M. van Duijn (Cornelia); C.S. Fox (Caroline); L. Groop (Leif); I.M. Heid (Iris); Hunter, D.J. (David J.); R.C. Kaplan (Robert); M.I. McCarthy (Mark); K.E. North (Kari); J.R. O´Connell; Schlessinger, D. (David); U. Thorsteinsdottir (Unnur); D.P. Strachan (David); T.M. Frayling (Timothy); J.N. Hirschhorn (Joel); M. Müller-Nurasyid (Martina); R.J.F. Loos (Ruth)

2016-01-01

textabstractLarge consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that

Quantitative Trait Loci and Inter-Organ Partitioning for Essential Metal and Toxic Analogue Accumulation in Barley.

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Stefan Reuscher

Full Text Available The concentrations of both essential nutrients and chemically similar toxic analogues accumulated in cereal grains have a major impact on the nutritional quality and safety of crops. Naturally occurring genetic diversity can be exploited for the breeding of improved varieties through introgression lines (ILs. In this study, multi-element analysis was conducted on vegetative leaves, senesced flag leaves and mature grains of a set of 54 ILs of the wild ancestral Hordeum vulgare ssp. spontaneum in the cultivated variety Hordeum vulgare ssp. vulgare cv. Scarlett. Plants were cultivated on an anthropogenically heavy metal-contaminated soil collected in an agricultural field, thus allowing simultaneous localization of quantitative trait loci (QTL for the accumulation of both essential nutrients and toxic trace elements in barley as a model cereal crop. For accumulation of the micronutrients Fe and Zn and the interfering toxin Cd, we identified 25, 16 and 5 QTL, respectively. By examining the gene content of the introgressions, we associated QTL with candidate genes based on homology to known metal homeostasis genes of Arabidopsis and rice. Global comparative analyses suggested the preferential remobilization of Cu and Fe, over Cd, from the flag leaf to developing grains. Our data identifies grain micronutrient filling as a regulated and nutrient-specific process, which operates differently from vegetative micronutrient homoeostasis. In summary, this study provides novel QTL for micronutrient accumulation in the presence of toxic analogues and supports a higher degree of metal specificity of trace element partitioning during grain filling in barley than previously reported for other cereals.

Quantitative trait loci associated with longevity of lettuce seeds under conventional and controlled deterioration storage conditions.

Science.gov (United States)

Schwember, Andrés R; Bradford, Kent J

2010-10-01

Lettuce (Lactuca sativa L.) seeds have poor shelf life and exhibit thermoinhibition (fail to germinate) above ∼25°C. Seed priming (controlled hydration followed by drying) alleviates thermoinhibition by increasing the maximum germination temperature, but reduces lettuce seed longevity. Controlled deterioration (CD) or accelerated ageing storage conditions (i.e. elevated temperature and relative humidity) are used to study seed longevity and to predict potential seed lifetimes under conventional storage conditions. Seeds produced in 2002 and 2006 of a recombinant inbred line (RIL) population derived from a cross between L. sativa cv. Salinas×L. serriola accession UC96US23 were utilized to identify quantitative trait loci (QTLs) associated with seed longevity under CD and conventional storage conditions. Multiple longevity-associated QTLs were identified under both conventional and CD storage conditions for control (non-primed) and primed seeds. However, seed longevity was poorly correlated between the two storage conditions, suggesting that deterioration processes under CD conditions are not predictive of ageing in conventional storage conditions. Additionally, the same QTLs were not identified when RIL populations were grown in different years, indicating that lettuce seed longevity is strongly affected by production environment. Nonetheless, a major QTL on chromosome 4 [Seed longevity 4.1 (Slg4.1)] was responsible for almost 23% of the phenotypic variation in viability of the conventionally stored control seeds of the 2006 RIL population, with improved longevity conferred by the Salinas allele. QTL analyses may enable identification of mechanisms responsible for the sensitivity of primed seeds to CD conditions and breeding for improved seed longevity.

Quantitative trait loci for live animal and carcass composition traits in Jersey and Limousin back-cross cattle finished on pasture or feedlot.

Science.gov (United States)

Morris, C A; Pitchford, W S; Cullen, N G; Esmailizadeh, A K; Hickey, S M; Hyndman, D; Dodds, K G; Afolayan, R A; Crawford, A M; Bottema, C D K

2009-10-01

A quantitative trait locus (QTL) study was carried out in two countries, recording live animal and carcass composition traits. Back-cross calves (385 heifers and 398 steers) were generated, with Jersey and Limousin breed backgrounds. The New Zealand cattle were reared on pasture to carcass weights averaging 229 kg, whilst the Australian cattle were reared on grass and finished on grain (for at least 180 days) to carcass weights averaging 335 kg. From 11 live animal traits and 31 carcass composition traits respectively, 5 and 22 QTL were detected in combined-sire analyses, which were significant (P < 0.05) on a genome-wise basis. Fourteen significant traits for carcass composition QTL were on chromosome 2 and these were traits associated with muscling and fatness. This chromosome carried a variant myostatin allele (F94L), segregating from the Limousin ancestry. Despite very different cattle management systems between the two countries, the two populations had a large number of QTL in common. Of the 18 traits which were common to both countries, and which had significant QTL at the genome-wise level, eight were significant in both countries.

Identification of X-linked quantitative trait loci affecting cold tolerance in Drosophila melanogaster and fine mapping by selective sweep analysis.

Science.gov (United States)

Svetec, Nicolas; Werzner, Annegret; Wilches, Ricardo; Pavlidis, Pavlos; Alvarez-Castro, José M; Broman, Karl W; Metzler, Dirk; Stephan, Wolfgang

2011-02-01

Drosophila melanogaster is a cosmopolitan species that colonizes a great variety of environments. One trait that shows abundant evidence for naturally segregating genetic variance in different populations of D. melanogaster is cold tolerance. Previous work has found quantitative trait loci (QTL) exclusively on the second and the third chromosomes. To gain insight into the genetic architecture of cold tolerance on the X chromosome and to compare the results with our analyses of selective sweeps, a mapping population was derived from a cross between substitution lines that solely differed in the origin of their X chromosome: one originates from a European inbred line and the other one from an African inbred line. We found a total of six QTL for cold tolerance factors on the X chromosome of D. melanogaster. Although the composite interval mapping revealed slightly different QTL profiles between sexes, a coherent model suggests that most QTL overlapped between sexes, and each explained around 5-14% of the genetic variance (which may be slightly overestimated). The allelic effects were largely additive, but we also detected two significant interactions. Taken together, this provides evidence for multiple QTL that are spread along the entire X chromosome and whose effects range from low to intermediate. One detected transgressive QTL influences cold tolerance in different ways for the two sexes. While females benefit from the European allele increasing their cold tolerance, males tend to do better with the African allele. Finally, using selective sweep mapping, the candidate gene CG16700 for cold tolerance colocalizing with a QTL was identified. © 2010 Blackwell Publishing Ltd.

Alternative models for detection of quantitative trait loci (QTL) for growth and carcass traits in pigs chromosomes 4, 5 and 7

NARCIS (Netherlands)

Moraes Gonçalves, de T.; Nunes de Oliveira, H.; Bovenhuis, H.; Bink, M.C.A.M.; Arendonk, van J.A.M.

2005-01-01

Genome scans can be used to identify chromosomal regions and eventually genes that control quantitative traits (QTL) of economic importance. In an experimental cross between Meishan (male) and Dutch Large White and Landrace lines (female), 298 F1 and 831 F2 animals were evaluated for intramuscular

DISSECTING QUANTITATIVE TRAIT LOCI FOR AGRONOMIC TRAITS RESPONDING TO IRON DEFICEINCY IN MUNGBEAN [Vigna radiata (L. Wilczek

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Prakit Somta

2014-06-01

Full Text Available Calcareous soil is prevalent in many areas of the world agricultural land causing substantial yield loss of crops. We previously identified two quantitative trait locus (QTL qIDC3.1 and qIDC2.1 controlling leaf chlorosis in mungbean grown in calcareous soil in two years (2010 and 2011 using visual score and SPAD measurement in a RIL population derived from KPS2 (susceptible and NM10-12-1 (resistant. The two QTLs together accounted for 50% of the total leaf chlorosis variation and only qIDC3.1 was confirmed, although heritability estimated for the traits was as high as 91.96%. In this study, we detected QTLs associated with days to flowering , plant height, number of pods per plants, number of seeds per pods, and seed yield per plants in the same population grown under the same environment with the aim to identify additional QTLs controlling resistance to calcareous soil in mungbean. Single marker analysis revealed 18 simple sequence repeat markers, while composite interval mapping identified 33 QTLs on six linkage groups (1A, 2, 3, 4, 5 and 9 controlling the five agronomic traits. QTL cluster on LG 3 coincided with the position of qIDC3.1, while QTL cluster on LG 2 was not far from qIDC2.1. The results confirmed the importance of qIDC3.1 and qIDC2.1 and revealed four new QTLs for the resistance to calcareous soil.

High Resolution Consensus Mapping of Quantitative Trait Loci for Fiber Strength, Length and Micronaire on Chromosome 25 of the Upland Cotton (Gossypium hirsutum L..

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Zhen Zhang

Full Text Available Cotton (Gossypium hirsutum L. is an important agricultural crop that provides renewable natural fiber resources for the global textile industry. Technological developments in the textile industry and improvements in human living standards have increased the requirement for supplies and better quality cotton. Upland cotton 0-153 is an elite cultivar harboring strong fiber strength genes. To conduct quantitative trait locus (QTL mapping for fiber quality in 0-153, we developed a population of 196 recombinant inbred lines (RILs from a cross between 0-153 and sGK9708. The fiber quality traits in 11 environments were measured and a genetic linkage map of chromosome 25 comprising 210 loci was constructed using this RIL population, mainly using simple sequence repeat markers and single nucleotide polymorphism markers. QTLs were identified across diverse environments using the composite interval mapping method. A total of 37 QTLs for fiber quality traits were identified on chromosome 25, of which 17 were stably expressed in at least in two environments. A stable fiber strength QTL, qFS-chr25-4, which was detected in seven environments and was located in the marker interval between CRI-SNP120491 and BNL2572, could explain 6.53%-11.83% of the observed phenotypic variations. Meta-analysis also confirmed the above QTLs with previous reports. Application of these QTLs could contribute to improving fiber quality and provide information for marker-assisted selection.

Quantitative trait loci and candidate genes underlying genotype by environment interaction in the response of Arabidopsis thaliana to drought

NARCIS (Netherlands)

El-Soda, M.; Kruijer, Willem; Malosetti, M.; Koornneef, M.; Aarts, M.G.M.

2015-01-01

Drought stress was imposed on two sets of Arabidopsis thaliana genotypes grown in sand under short-day conditions and analysed for several shoot and root growth traits. The response to drought was assessed for quantitative trait locus (QTL) mapping in a genetically diverse set of Arabidopsis

Validation and dissection of quantitative trait loci for leaf traits in ...

Indian Academy of Sciences (India)

Validation and dissection of a QTL region for leaf traits in rice which has been reported in a number of independent studies were conducted. Three sets of near isogenic lines (NILs) were originated from a residual heterozygous line derived the indica cross Zhenshan 97B/Milyang 46. They were overlapping and totally ...

Genotype-dependent participation of coat color gene loci in the behavioral traits of laboratory mice.

Science.gov (United States)

Yamamuro, Yutaka; Shiraishi, Aya

2011-10-01

To evaluate if loci responsible for coat color phenotypes contribute to behavioral characteristics, we specified novel gene loci associated with social exploratory behavior and examined the effects of the frequency of each allele at distinct loci on behavioral expression. We used the F2 generation, which arose from the mating of F1 mice obtained by interbreeding DBA/2 and ICR mice. Phenotypic analysis indicated that the agouti and albino loci affect behavioral traits. A genotype-based analysis revealed that novel exploratory activity was suppressed in a manner dependent on the frequency of the dominant wild-type allele at the agouti, but not albino, locus. The allele-dependent suppression was restricted to colored mice and was not seen in albino mice. The present results suggest that the agouti locus contributes to a particular behavioral trait in the presence of a wild-type allele at the albino locus, which encodes a structural gene for tyrosinase. Copyright © 2011 Elsevier B.V. All rights reserved.

Identification of quantitative trait Loci for resistance to southern leaf blight and days to anthesis in a maize recombinant inbred line population.

Science.gov (United States)

Balint-Kurti, P J; Krakowsky, M D; Jines, M P; Robertson, L A; Molnár, T L; Goodman, M M; Holl, J B

2006-10-01

ABSTRACT A recombinant inbred line population derived from a cross between the maize lines NC300 (resistant) and B104 (susceptible) was evaluated for resistance to southern leaf blight (SLB) disease caused by Cochliobolus heterostrophus race O and for days to anthesis in four environments (Clayton, NC, and Tifton, GA, in both 2004 and 2005). Entry mean and average genetic correlations between disease ratings in different environments were high (0.78 to 0.89 and 0.9, respectively) and the overall entry mean heritability for SLB resistance was 0.89. When weighted mean disease ratings were fitted to a model using multiple interval mapping, seven potential quantitative trait loci (QTL) were identified, the two strongest being on chromosomes 3 (bin 3.04) and 9 (bin 9.03-9.04). These QTL explained a combined 80% of the phenotypic variation for SLB resistance. Some time-point-specific SLB resistance QTL were also identified. There was no significant correlation between disease resistance and days to anthesis. Six putative QTL for time to anthesis were identified, none of which coincided with any SLB resistance QTL.

A principal component meta-analysis on multiple anthropometric traits identifies novel loci for body shape

Science.gov (United States)

Ried, Janina S.; Jeff M., Janina; Chu, Audrey Y.; Bragg-Gresham, Jennifer L.; van Dongen, Jenny; Huffman, Jennifer E.; Ahluwalia, Tarunveer S.; Cadby, Gemma; Eklund, Niina; Eriksson, Joel; Esko, Tõnu; Feitosa, Mary F.; Goel, Anuj; Gorski, Mathias; Hayward, Caroline; Heard-Costa, Nancy L.; Jackson, Anne U.; Jokinen, Eero; Kanoni, Stavroula; Kristiansson, Kati; Kutalik, Zoltán; Lahti, Jari; Luan, Jian'an; Mägi, Reedik; Mahajan, Anubha; Mangino, Massimo; Medina-Gomez, Carolina; Monda, Keri L.; Nolte, Ilja M.; Pérusse, Louis; Prokopenko, Inga; Qi, Lu; Rose, Lynda M.; Salvi, Erika; Smith, Megan T.; Snieder, Harold; Stančáková, Alena; Ju Sung, Yun; Tachmazidou, Ioanna; Teumer, Alexander; Thorleifsson, Gudmar; van der Harst, Pim; Walker, Ryan W.; Wang, Sophie R.; Wild, Sarah H.; Willems, Sara M.; Wong, Andrew; Zhang, Weihua; Albrecht, Eva; Couto Alves, Alexessander; Bakker, Stephan J. L.; Barlassina, Cristina; Bartz, Traci M.; Beilby, John; Bellis, Claire; Bergman, Richard N.; Bergmann, Sven; Blangero, John; Blüher, Matthias; Boerwinkle, Eric; Bonnycastle, Lori L.; Bornstein, Stefan R.; Bruinenberg, Marcel; Campbell, Harry; Chen, Yii-Der Ida; Chiang, Charleston W. K.; Chines, Peter S.; Collins, Francis S; Cucca, Fracensco; Cupples, L Adrienne; D'Avila, Francesca; de Geus, Eco J .C.; Dedoussis, George; Dimitriou, Maria; Döring, Angela; Eriksson, Johan G.; Farmaki, Aliki-Eleni; Farrall, Martin; Ferreira, Teresa; Fischer, Krista; Forouhi, Nita G.; Friedrich, Nele; Gjesing, Anette Prior; Glorioso, Nicola; Graff, Mariaelisa; Grallert, Harald; Grarup, Niels; Gräßler, Jürgen; Grewal, Jagvir; Hamsten, Anders; Harder, Marie Neergaard; Hartman, Catharina A.; Hassinen, Maija; Hastie, Nicholas; Hattersley, Andrew Tym; Havulinna, Aki S.; Heliövaara, Markku; Hillege, Hans; Hofman, Albert; Holmen, Oddgeir; Homuth, Georg; Hottenga, Jouke-Jan; Hui, Jennie; Husemoen, Lise Lotte; Hysi, Pirro G.; Isaacs, Aaron; Ittermann, Till; Jalilzadeh, Shapour; James, Alan L.; Jørgensen, Torben; Jousilahti, Pekka; Jula, Antti; Marie Justesen, Johanne; Justice, Anne E.; Kähönen, Mika; Karaleftheri, Maria; Tee Khaw, Kay; Keinanen-Kiukaanniemi, Sirkka M.; Kinnunen, Leena; Knekt, Paul B.; Koistinen, Heikki A.; Kolcic, Ivana; Kooner, Ishminder K.; Koskinen, Seppo; Kovacs, Peter; Kyriakou, Theodosios; Laitinen, Tomi; Langenberg, Claudia; Lewin, Alexandra M.; Lichtner, Peter; Lindgren, Cecilia M.; Lindström, Jaana; Linneberg, Allan; Lorbeer, Roberto; Lorentzon, Mattias; Luben, Robert; Lyssenko, Valeriya; Männistö, Satu; Manunta, Paolo; Leach, Irene Mateo; McArdle, Wendy L.; Mcknight, Barbara; Mohlke, Karen L.; Mihailov, Evelin; Milani, Lili; Mills, Rebecca; Montasser, May E.; Morris, Andrew P.; Müller, Gabriele; Musk, Arthur W.; Narisu, Narisu; Ong, Ken K.; Oostra, Ben A.; Osmond, Clive; Palotie, Aarno; Pankow, James S.; Paternoster, Lavinia; Penninx, Brenda W.; Pichler, Irene; Pilia, Maria G.; Polašek, Ozren; Pramstaller, Peter P.; Raitakari, Olli T; Rankinen, Tuomo; Rao, D. C.; Rayner, Nigel W.; Ribel-Madsen, Rasmus; Rice, Treva K.; Richards, Marcus; Ridker, Paul M.; Rivadeneira, Fernando; Ryan, Kathy A.; Sanna, Serena; Sarzynski, Mark A.; Scholtens, Salome; Scott, Robert A.; Sebert, Sylvain; Southam, Lorraine; Sparsø, Thomas Hempel; Steinthorsdottir, Valgerdur; Stirrups, Kathleen; Stolk, Ronald P.; Strauch, Konstantin; Stringham, Heather M.; Swertz, Morris A.; Swift, Amy J.; Tönjes, Anke; Tsafantakis, Emmanouil; van der Most, Peter J.; Van Vliet-Ostaptchouk, Jana V.; Vandenput, Liesbeth; Vartiainen, Erkki; Venturini, Cristina; Verweij, Niek; Viikari, Jorma S.; Vitart, Veronique; Vohl, Marie-Claude; Vonk, Judith M.; Waeber, Gérard; Widén, Elisabeth; Willemsen, Gonneke; Wilsgaard, Tom; Winkler, Thomas W.; Wright, Alan F.; Yerges-Armstrong, Laura M.; Hua Zhao, Jing; Carola Zillikens, M.; Boomsma, Dorret I.; Bouchard, Claude; Chambers, John C.; Chasman, Daniel I.; Cusi, Daniele; Gansevoort, Ron T.; Gieger, Christian; Hansen, Torben; Hicks, Andrew A.; Hu, Frank; Hveem, Kristian; Jarvelin, Marjo-Riitta; Kajantie, Eero; Kooner, Jaspal S.; Kuh, Diana; Kuusisto, Johanna; Laakso, Markku; Lakka, Timo A.; Lehtimäki, Terho; Metspalu, Andres; Njølstad, Inger; Ohlsson, Claes; Oldehinkel, Albertine J.; Palmer, Lyle J.; Pedersen, Oluf; Perola, Markus; Peters, Annette; Psaty, Bruce M.; Puolijoki, Hannu; Rauramaa, Rainer; Rudan, Igor; Salomaa, Veikko; Schwarz, Peter E. H.; Shudiner, Alan R.; Smit, Jan H.; Sørensen, Thorkild I. A.; Spector, Timothy D.; Stefansson, Kari; Stumvoll, Michael; Tremblay, Angelo; Tuomilehto, Jaakko; Uitterlinden, André G.; Uusitupa, Matti; Völker, Uwe; Vollenweider, Peter; Wareham, Nicholas J.; Watkins, Hugh; Wilson, James F.; Zeggini, Eleftheria; Abecasis, Goncalo R.; Boehnke, Michael; Borecki, Ingrid B.; Deloukas, Panos; van Duijn, Cornelia M.; Fox, Caroline; Groop, Leif C.; Heid, Iris M.; Hunter, David J.; Kaplan, Robert C.; McCarthy, Mark I.; North, Kari E.; O'Connell, Jeffrey R.; Schlessinger, David; Thorsteinsdottir, Unnur; Strachan, David P.; Frayling, Timothy; Hirschhorn, Joel N.; Müller-Nurasyid, Martina; Loos, Ruth J. F.

2016-01-01

Large consortia have revealed hundreds of genetic loci associated with anthropometric traits, one trait at a time. We examined whether genetic variants affect body shape as a composite phenotype that is represented by a combination of anthropometric traits. We developed an approach that calculates averaged PCs (AvPCs) representing body shape derived from six anthropometric traits (body mass index, height, weight, waist and hip circumference, waist-to-hip ratio). The first four AvPCs explain >99% of the variability, are heritable, and associate with cardiometabolic outcomes. We performed genome-wide association analyses for each body shape composite phenotype across 65 studies and meta-analysed summary statistics. We identify six novel loci: LEMD2 and CD47 for AvPC1, RPS6KA5/C14orf159 and GANAB for AvPC3, and ARL15 and ANP32 for AvPC4. Our findings highlight the value of using multiple traits to define complex phenotypes for discovery, which are not captured by single-trait analyses, and may shed light onto new pathways. PMID:27876822

Large-scale in silico mapping of complex quantitative traits in inbred mice.

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Pengyuan Liu

2007-07-01

Full Text Available Understanding the genetic basis of common disease and disease-related quantitative traits will aid in the development of diagnostics and therapeutics. The processs of gene discovery can be sped up by rapid and effective integration of well-defined mouse genome and phenome data resources. We describe here an in silico gene-discovery strategy through genome-wide association (GWA scans in inbred mice with a wide range of genetic variation. We identified 937 quantitative trait loci (QTLs from a survey of 173 mouse phenotypes, which include models of human disease (atherosclerosis, cardiovascular disease, cancer and obesity as well as behavioral, hematological, immunological, metabolic, and neurological traits. 67% of QTLs were refined into genomic regions <0.5 Mb with approximately 40-fold increase in mapping precision as compared with classical linkage analysis. This makes for more efficient identification of the genes that underlie disease. We have identified two QTL genes, Adam12 and Cdh2, as causal genetic variants for atherogenic diet-induced obesity. Our findings demonstrate that GWA analysis in mice has the potential to resolve multiple tightly linked QTLs and achieve single-gene resolution. These high-resolution QTL data can serve as a primary resource for positional cloning and gene identification in the research community.

Quantitative genetic analysis of life-history traits of Caenorhabditis elegans in stressful environments

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Shorto Alison

2008-01-01

Full Text Available Abstract Background Organisms live in environments that vary. For life-history traits that vary across environments, fitness will be maximised when the phenotype is appropriately matched to the environmental conditions. For the free-living nematode Caenorhabditis elegans, we have investigated how two major life-history traits, (i the development of environmentally resistant dauer larvae and (ii reproduction, respond to environmental stress (high population density and low food availability, and how these traits vary between lines and the genetic basis of this variation. Results We found that lines of C. elegans vary in their phenotypic plasticity of dauer larva development, i.e. there is variation in the likelihood of developing into a dauer larva for the same environmental change. There was also variation in how lifetime fecundity and the rate of reproduction changed under conditions of environmental stress. These traits were related, such that lines that are highly plastic for dauer larva development also maintain a high population growth rate when stressed. We identified quantitative trait loci (QTL on two chromosomes that control the dauer larva development and population size phenotypes. The QTLs affecting the dauer larva development and population size phenotypes on chromosome II are closely linked, but are genetically separable. This chromosome II QTL controlling dauer larva development does not encompass any loci previously identified to control dauer larva development. This chromosome II region contains many predicted 7-transmembrane receptors. Such proteins are often involved in information transduction, which is clearly relevant to the control of dauer larva development. Conclusion C. elegans alters both its larval development and adult reproductive strategy in response to environmental stress. Together the phenotypic and genotypic data suggest that these two major life-history traits are co-ordinated responses to environmental stress

Quantitative trait loci for resistance to trichostrongylid infection in Spanish Churra sheep

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Primitivo Fermin San

2009-10-01

Full Text Available Abstract Background For ruminants reared on grazing systems, gastrointestinal nematode (GIN parasite infections represent the class of diseases with the greatest impact on animal health and productivity. Among the many possible strategies for controlling GIN infection, the enhancement of host resistance through the selection of resistant animals has been suggested by many authors. Because of the difficulty of routinely collecting phenotypic indicators of parasite resistance, information derived from molecular markers may be used to improve the efficiency of classical genetic breeding. Methods A total of 181 microsatellite markers evenly distributed along the 26 sheep autosomes were used in a genome scan analysis performed in a commercial population of Spanish Churra sheep to detect chromosomal regions associated with parasite resistance. Following a daughter design, we analysed 322 ewes distributed in eight half-sib families. The phenotypes studied included two faecal egg counts (LFEC0 and LFEC1, anti-Teladorsagia circumcincta LIV IgA levels (IgA and serum pepsinogen levels (Peps. Results The regression analysis revealed one QTL at the 5% genome-wise significance level on chromosome 6 for LFEC1 within the marker interval BM4621-CSN3. This QTL was found to be segregating in three out of the eight families analysed. Four other QTL were identified at the 5% chromosome-wise level on chromosomes 1, 10 and 14. Three of these QTL influenced faecal egg count, and the other one had an effect on IgA levels. Conclusion This study has successfully identified segregating QTL for parasite resistance traits in a commercial population. For some of the QTL detected, we have identified interesting coincidences with QTL previously reported in sheep, although most of those studies have been focused on young animals. Some of these coincidences might indicate that some common underlying loci affect parasite resistance traits in different sheep breeds. The

Identifying Quantitative Trait Loci (QTLs) and Developing Diagnostic Markers Linked to Orange Rust Resistance in Sugarcane (Saccharum spp.).

Science.gov (United States)

Yang, Xiping; Islam, Md S; Sood, Sushma; Maya, Stephanie; Hanson, Erik A; Comstock, Jack; Wang, Jianping

2018-01-01

Sugarcane ( Saccharum spp.) is an important economic crop, contributing up to 80% of table sugar used in the world and has become a promising feedstock for biofuel production. Sugarcane production has been threatened by many diseases, and fungicide applications for disease control have been opted out for sustainable agriculture. Orange rust is one of the major diseases impacting sugarcane production worldwide. Identifying quantitative trait loci (QTLs) and developing diagnostic markers are valuable for breeding programs to expedite release of superior sugarcane cultivars for disease control. In this study, an F 1 segregating population derived from a cross between two hybrid sugarcane clones, CP95-1039 and CP88-1762, was evaluated for orange rust resistance in replicated trails. Three QTLs controlling orange rust resistance in sugarcane (qORR109, qORR4 and qORR102) were identified for the first time ever, which can explain 58, 12 and 8% of the phenotypic variation, separately. We also characterized 1,574 sugarcane putative resistance ( R ) genes. These sugarcane putative R genes and simple sequence repeats in the QTL intervals were further used to develop diagnostic markers for marker-assisted selection of orange rust resistance. A PCR-based Resistance gene-derived maker, G1 was developed, which showed significant association with orange rust resistance. The putative QTLs and marker developed in this study can be effectively utilized in sugarcane breeding programs to facilitate the selection process, thus contributing to the sustainable agriculture for orange rust disease control.

Identification of quantitative trait loci affecting resistance to gastrointestinal parasites in a double backcross population of Red Maasai and Dorper sheep.

Science.gov (United States)

Silva, M V B; Sonstegard, T S; Hanotte, O; Mugambi, J M; Garcia, J F; Nagda, S; Gibson, J P; Iraqi, F A; McClintock, A E; Kemp, S J; Boettcher, P J; Malek, M; Van Tassell, C P; Baker, R L

2012-02-01

A genome-wide scan for quantitative trait loci (QTL) affecting gastrointestinal nematode resistance in sheep was completed using a double backcross population derived from Red Maasai and Dorper ewes bred to F(1) rams. This design provided an opportunity to map potentially unique genetic variation associated with a parasite-tolerant breed like Red Maasai, a breed developed to survive East African grazing conditions. Parasite indicator phenotypes (blood packed cell volume - PCV and faecal egg count - FEC) were collected on a weekly basis from 1064 lambs during a single 3-month post-weaning grazing challenge on infected pastures. The averages of last measurements for FEC (AVFEC) and PCV (AVPCV), along with decline in PCV from challenge start to end (PCVD), were used to select lambs (N = 371) for genotyping that represented the tails (10% threshold) of the phenotypic distributions. Marker genotypes for 172 microsatellite loci covering 25 of 26 autosomes (1560.7 cm) were scored and corrected by Genoprob prior to qxpak analysis that included Box-Cox transformed AVFEC and arcsine transformed PCV statistics. Significant QTL for AVFEC and AVPCV were detected on four chromosomes, and this included a novel AVFEC QTL on chromosome 6 that would have remained undetected without Box-Cox transformation methods. The most significant P-values for AVFEC, AVPCV and PCVD overlapped the same marker interval on chromosome 22, suggesting the potential for a single causative mutation, which remains unknown. In all cases, the favourable QTL allele was always contributed from Red Maasai, providing support for the idea that future marker-assisted selection for genetic improvement of production in East Africa will rely on markers in linkage disequilibrium with these QTL. © 2011 The Authors, Animal Genetics © 2011 Stichting International Foundation for Animal Genetics.

Quantitative trait loci analysis of individual and total isoflavone ...

Indian Academy of Sciences (India)

2014-08-19

Aug 19, 2014 ... 2Seed Management Station of Jilin Province, Changchun 130062, Jilin, ... daidzein (DC), genistein (GeC), glycitein (GlC) and total isoflavone contents (TIC) in ..... ing and height) and quality (oil and protein content) traits.

Detection of quantitative trait loci controlling grain zinc concentration using Australian wild rice, Oryza meridionalis, a potential genetic resource for biofortification of rice.

Science.gov (United States)

Ishikawa, Ryo; Iwata, Masahide; Taniko, Kenta; Monden, Gotaro; Miyazaki, Naoya; Orn, Chhourn; Tsujimura, Yuki; Yoshida, Shusaku; Ma, Jian Feng; Ishii, Takashige

2017-01-01

Zinc (Zn) is one of the essential mineral elements for both plants and humans. Zn deficiency in human is one of the major causes of hidden hunger, a serious health problem observed in many developing countries. Therefore, increasing Zn concentration in edible part is an important issue for improving human Zn nutrition. Here, we found that an Australian wild rice O. meridionalis showed higher grain Zn concentrations compared with cultivated and other wild rice species. The quantitative trait loci (QTL) analysis was then performed to identify the genomic regions controlling grain Zn levels using backcross recombinant inbred lines derived from O. sativa 'Nipponbare' and O. meridionalis W1627. Four QTLs responsible for high grain Zn were detected on chromosomes 2, 9, and 10. The QTL on the chromosome 9 (named qGZn9), which showed the largest effect on grain Zn concentration was confirmed with the introgression line, which had a W1627 chromosomal segment covering the qGZn9 region in the genetic background of O. sativa 'Nipponbare'. Fine mapping of this QTL resulted in identification of two tightly linked loci, qGZn9a and qGZn9b. The candidate regions of qGZn9a and qGZn9b were estimated to be 190 and 950 kb, respectively. Furthermore, we also found that plants having a wild chromosomal segment covering qGZn9a, but not qGZn9b, is associated with fertility reduction. qGZn9b, therefore, provides a valuable allele for breeding rice with high Zn in the grains.

Detection of quantitative trait loci controlling grain zinc concentration using Australian wild rice, Oryza meridionalis, a potential genetic resource for biofortification of rice.

Directory of Open Access Journals (Sweden)

Ryo Ishikawa

Full Text Available Zinc (Zn is one of the essential mineral elements for both plants and humans. Zn deficiency in human is one of the major causes of hidden hunger, a serious health problem observed in many developing countries. Therefore, increasing Zn concentration in edible part is an important issue for improving human Zn nutrition. Here, we found that an Australian wild rice O. meridionalis showed higher grain Zn concentrations compared with cultivated and other wild rice species. The quantitative trait loci (QTL analysis was then performed to identify the genomic regions controlling grain Zn levels using backcross recombinant inbred lines derived from O. sativa 'Nipponbare' and O. meridionalis W1627. Four QTLs responsible for high grain Zn were detected on chromosomes 2, 9, and 10. The QTL on the chromosome 9 (named qGZn9, which showed the largest effect on grain Zn concentration was confirmed with the introgression line, which had a W1627 chromosomal segment covering the qGZn9 region in the genetic background of O. sativa 'Nipponbare'. Fine mapping of this QTL resulted in identification of two tightly linked loci, qGZn9a and qGZn9b. The candidate regions of qGZn9a and qGZn9b were estimated to be 190 and 950 kb, respectively. Furthermore, we also found that plants having a wild chromosomal segment covering qGZn9a, but not qGZn9b, is associated with fertility reduction. qGZn9b, therefore, provides a valuable allele for breeding rice with high Zn in the grains.

Determination of gene action for some biometrical traits in Lens ...

Indian Academy of Sciences (India)

RESEARCH NOTE. Determination ... limitation of this design is that if the testers do not differ at all loci for ... the traits under study indicating the presence of epistasis for these traits ... Quantitative genetic analysis for yield traits in lentil. Table 1.

Genotyping-by-sequencing markers facilitate the identification of quantitative trait loci controlling resistance to Penicillium expansum in Malus sieversii.

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John L Norelli

Full Text Available Blue mold caused by Penicillium expansum is the most important postharvest disease of apple worldwide and results in significant financial losses. There are no defined sources of resistance to blue mold in domesticated apple. However, resistance has been described in wild Malus sieversii accessions, including plant introduction (PI613981. The objective of the present study was to identify the genetic loci controlling resistance to blue mold in this accession. We describe the first quantitative trait loci (QTL reported in the Rosaceae tribe Maleae conditioning resistance to P. expansum on genetic linkage group 3 (qM-Pe3.1 and linkage group 10 (qM-Pe10.1. These loci were identified in a M.× domestica 'Royal Gala' X M. sieversii PI613981 family (GMAL4593 based on blue mold lesion diameter seven days post-inoculation in mature, wounded apple fruit inoculated with P. expansum. Phenotypic analyses were conducted in 169 progeny over a four year period. PI613981 was the source of the resistance allele for qM-Pe3.1, a QTL with a major effect on blue mold resistance, accounting for 27.5% of the experimental variability. The QTL mapped from 67.3 to 74 cM on linkage group 3 of the GMAL4593 genetic linkage map. qM-Pe10.1 mapped from 73.6 to 81.8 cM on linkage group 10. It had less of an effect on resistance, accounting for 14% of the experimental variation. 'Royal Gala' was the primary contributor to the resistance effect of this QTL. However, resistance-associated alleles in both parents appeared to contribute to the least square mean blue mold lesion diameter in an additive manner at qM-Pe10.1. A GMAL4593 genetic linkage map composed of simple sequence repeats and 'Golden Delicious' single nucleotide polymorphism markers was able to detect qM-Pe10.1, but failed to detect qM-Pe3.1. The subsequent addition of genotyping-by-sequencing markers to the linkage map provided better coverage of the PI613981 genome on linkage group 3 and facilitated discovery of q

Induced mutations for quantitative traits in rice

International Nuclear Information System (INIS)

Chakrabarti, B.N.

1974-01-01

The characteristics and frequency of micro-mutations induced in quantitative traits by radiation treatment and the extent of heterozygotic effects of different recessive chlorophyll-mutant-genes on quantitative trait has been presented. Mutagenic treatments increased the variance for quantitative traits in all cases although the magnitude of increase varied depending on the treatment and the selection procedure adopted. The overall superiority of the chlorophyll-mutant heterozygotes over the corresponding wild homozygotes, as noted in consecutive two seasons, was not observed when these were grown at a high level of nitrogen fertiliser. (author)

A three-component system incorporating Ppd-D1, copy number variation at Ppd-B1, and numerous small-effect quantitative trait loci facilitates adaptation of heading time in winter wheat cultivars of worldwide origin.

Science.gov (United States)

Würschum, Tobias; Langer, Simon M; Longin, C Friedrich H; Tucker, Matthew R; Leiser, Willmar L

2018-06-01

The broad adaptability of heading time has contributed to the global success of wheat in a diverse array of climatic conditions. Here, we investigated the genetic architecture underlying heading time in a large panel of 1,110 winter wheat cultivars of worldwide origin. Genome-wide association mapping, in combination with the analysis of major phenology loci, revealed a three-component system that facilitates the adaptation of heading time in winter wheat. The photoperiod sensitivity locus Ppd-D1 was found to account for almost half of the genotypic variance in this panel and can advance or delay heading by many days. In addition, copy number variation at Ppd-B1 was the second most important source of variation in heading, explaining 8.3% of the genotypic variance. Results from association mapping and genomic prediction indicated that the remaining variation is attributed to numerous small-effect quantitative trait loci that facilitate fine-tuning of heading to the local climatic conditions. Collectively, our results underpin the importance of the two Ppd-1 loci for the adaptation of heading time in winter wheat and illustrate how the three components have been exploited for wheat breeding globally. © 2018 John Wiley & Sons Ltd.

Quantitative traits and diversification.

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FitzJohn, Richard G

2010-12-01

Quantitative traits have long been hypothesized to affect speciation and extinction rates. For example, smaller body size or increased specialization may be associated with increased rates of diversification. Here, I present a phylogenetic likelihood-based method (quantitative state speciation and extinction [QuaSSE]) that can be used to test such hypotheses using extant character distributions. This approach assumes that diversification follows a birth-death process where speciation and extinction rates may vary with one or more traits that evolve under a diffusion model. Speciation and extinction rates may be arbitrary functions of the character state, allowing much flexibility in testing models of trait-dependent diversification. I test the approach using simulated phylogenies and show that a known relationship between speciation and a quantitative character could be recovered in up to 80% of the cases on large trees (500 species). Consistent with other approaches, detecting shifts in diversification due to differences in extinction rates was harder than when due to differences in speciation rates. Finally, I demonstrate the application of QuaSSE to investigate the correlation between body size and diversification in primates, concluding that clade-specific differences in diversification may be more important than size-dependent diversification in shaping the patterns of diversity within this group.

A Major Locus for Quantitatively Measured Shank Skin Color Traits in Korean Native Chicken

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S. Jin

2016-11-01

Full Text Available Shank skin color of Korean native chicken (KNC shows large color variations. It varies from white, yellow, green, bluish or grey to black, whilst in the majority of European breeds the shanks are typically yellow-colored. Three shank skin color-related traits (i.e., lightness [L*], redness [a*], and yellowness [b*] were measured by a spectrophotometer in 585 progeny from 68 nuclear families in the KNC resource population. We performed genome scan linkage analysis to identify loci that affect quantitatively measured shank skin color traits in KNC. All these birds were genotyped with 167 DNA markers located throughout the 26 autosomes. The SOLAR program was used to conduct multipoint variance-component quantitative trait locus (QTL analyses. We detected a major QTL that affects b* value (logarithm of odds [LOD] = 47.5, p = 1.60×10−49 on GGA24 (GGA for Gallus gallus. At the same location, we also detected a QTL that influences a* value (LOD = 14.2, p = 6.14×10−16. Additionally, beta-carotene dioxygenase 2 (BCDO2, the obvious positional candidate gene under the linkage peaks on GGA24, was investigated by the two association tests: i.e., measured genotype association (MGA and quantitative transmission disequilibrium test (QTDT. Significant associations were detected between BCDO2 g.9367 A>C and a* (PMGA = 1.69×10−28; PQTDT = 2.40×10−25. The strongest associations were between BCDO2 g.9367 A>C and b* (PMGA = 3.56×10−66; PQTDT = 1.68×10−65. However, linkage analyses conditional on the single nucleotide polymorphism indicated that other functional variants should exist. Taken together, we demonstrate for the first time the linkage and association between the BCDO2 locus on GGA24 and quantitatively measured shank skin color traits in KNC.

Mapping of quantitative trait loci for grain yield and its components in a US popular winter wheat TAM 111 using 90K SNPs.

Directory of Open Access Journals (Sweden)

Silvano O Assanga

Full Text Available Stable quantitative trait loci (QTL are important for deployment in marker assisted selection in wheat (Triticum aestivum L. and other crops. We reported QTL discovery in wheat using a population of 217 recombinant inbred lines and multiple statistical approach including multi-environment, multi-trait and epistatic interactions analysis. We detected nine consistent QTL linked to different traits on chromosomes 1A, 2A, 2B, 5A, 5B, 6A, 6B and 7A. Grain yield QTL were detected on chromosomes 2B.1 and 5B across three or four models of GenStat, MapQTL, and QTLNetwork while the QTL on chromosomes 5A.1, 6A.2, and 7A.1 were only significant with yield from one or two models. The phenotypic variation explained (PVE by the QTL on 2B.1 ranged from 3.3-25.1% based on single and multi-environment models in GenStat and was pleiotropic or co-located with maturity (days to heading and yield related traits (test weight, thousand kernel weight, harvest index. The QTL on 5B at 211 cM had PVE range of 1.8-9.3% and had no significant pleiotropic effects. Other consistent QTL detected in this study were linked to yield related traits and agronomic traits. The QTL on 1A was consistent for the number of spikes m-2 across environments and all the four analysis models with a PVE range of 5.8-8.6%. QTL for kernels spike-1 were found in chromosomes 1A, 2A.1, 2B.1, 6A.2, and 7A.1 with PVE ranged from 5.6-12.8% while QTL for thousand kernel weight were located on chromosomes 1A, 2B.1, 5A.1, 6A.2, 6B.1 and 7A.1 with PVEranged from 2.7-19.5%. Among the consistent QTL, five QTL had significant epistatic interactions (additive × additive at least for one trait and none revealed significant additive × additive × environment interactions. Comparative analysis revealed that the region within the confidence interval of the QTL on 5B from 211.4-244.2 cM is also linked to genes for aspartate-semialdehyde dehydrogenase, splicing regulatory glutamine/lysine-rich protein 1 isoform X1

A population genetic interpretation of GWAS findings for human quantitative traits

Science.gov (United States)

Bullaughey, Kevin; Hudson, Richard R.; Sella, Guy

2018-01-01

Human genome-wide association studies (GWASs) are revealing the genetic architecture of anthropomorphic and biomedical traits, i.e., the frequencies and effect sizes of variants that contribute to heritable variation in a trait. To interpret these findings, we need to understand how genetic architecture is shaped by basic population genetics processes—notably, by mutation, natural selection, and genetic drift. Because many quantitative traits are subject to stabilizing selection and because genetic variation that affects one trait often affects many others, we model the genetic architecture of a focal trait that arises under stabilizing selection in a multidimensional trait space. We solve the model for the phenotypic distribution and allelic dynamics at steady state and derive robust, closed-form solutions for summary statistics of the genetic architecture. Our results provide a simple interpretation for missing heritability and why it varies among traits. They predict that the distribution of variances contributed by loci identified in GWASs is well approximated by a simple functional form that depends on a single parameter: the expected contribution to genetic variance of a strongly selected site affecting the trait. We test this prediction against the results of GWASs for height and body mass index (BMI) and find that it fits the data well, allowing us to make inferences about the degree of pleiotropy and mutational target size for these traits. Our findings help to explain why the GWAS for height explains more of the heritable variance than the similarly sized GWAS for BMI and to predict the increase in explained heritability with study sample size. Considering the demographic history of European populations, in which these GWASs were performed, we further find that most of the associations they identified likely involve mutations that arose shortly before or during the Out-of-Africa bottleneck at sites with selection coefficients around s = 10−3. PMID

Quantitative trait locus affecting birth weight on bovine chromosome 5 in a F2 Gyr x Holstein population

Directory of Open Access Journals (Sweden)

Gustavo Gasparin

2005-12-01

Full Text Available Segregation between a genetic marker and a locus influencing a quantitative trait in a well delineated population is the basis for success in mapping quantitative trait loci (QTL. To detect bovine chromosome 5 (BTA5 birth weight QTL we genotyped 294 F2 Gyr (Bos indicus x Holstein (Bos taurus crossbreed cattle for five microsatellite markers. A linkage map was constructed for the markers and an interval analysis for the presence of QTL was performed. The linkage map indicated differences in the order of two markers relative to the reference map (http://www.marc.usda.gov. Interval analysis detected a QTL controlling birth weight (p < 0.01 at 69 centimorgans (cM from the most centromeric marker with an effect of 0.32 phenotypic standard-error. These results support other studies with crossbred Bos taurus x Bos indicus populations.

Preliminary evidence for associations between molecular markers and quantitative traits in a set of bread wheat (Triticum aestivum L.) cultivars and breeding lines.

Science.gov (United States)

Abdollahi Mandoulakani, Babak; Nasri, Shilan; Dashchi, Sahar; Arzhang, Sorour; Bernousi, Iraj; Abbasi Holasou, Hossein

The identification of polymorphic markers associated with various quantitative traits allows us to test their performance for the exploitation of the extensive quantitative variation maintained in gene banks. In the current study, a set of 97 wheat germplasm accessions including 48 cultivars and 49 breeding lines were evaluated for 18 agronomic traits. The accessions were also genotyped with 23 ISSR, nine IRAP and 20 REMAP markers, generating a total of 658 clear and scorable bands, 86% of which were polymorphic. Both neighbor-joining dendrogram and Bayesian analysis of clustering of individuals revealed that the accessions could be divided into four genetically distinct groups, indicating the presence of a population structure in current wheat germplasm. Associations between molecular markers and 18 agronomic traits were analyzed using the mixed linear model (MLM) approach. A total of 94 loci were found to be significantly associated with agronomic traits (P≤0.01). The highest number of bands significantly associated with the 18 traits varied from 11 for number of spikelets spike -1 (NSS) to two for grain yield in row (GRY). Loci ISSR16-9 and REMAP13-10 were associated with three different traits. The results of the current study provide useful information about the performance of retrotransposon-based and ISSR molecular markers that could be helpful in selecting potentially elite gene bank samples for wheat-breeding programs. Copyright © 2017 Académie des sciences. Published by Elsevier Masson SAS. All rights reserved.

A PQL (protein quantity loci) analysis of mature pea seed proteins identifies loci determining seed protein composition.

Science.gov (United States)

Bourgeois, Michael; Jacquin, Françoise; Cassecuelle, Florence; Savois, Vincent; Belghazi, Maya; Aubert, Grégoire; Quillien, Laurence; Huart, Myriam; Marget, Pascal; Burstin, Judith

2011-05-01

Legume seeds are a major source of dietary proteins for humans and animals. Deciphering the genetic control of their accumulation is thus of primary significance towards their improvement. At first, we analysed the genetic variability of the pea seed proteome of three genotypes over 3 years of cultivation. This revealed that seed protein composition variability was under predominant genetic control, with as much as 60% of the spots varying quantitatively among the three genotypes. Then, by combining proteomic and quantitative trait loci (QTL) mapping approaches, we uncovered the genetic architecture of seed proteome variability. Protein quantity loci (PQL) were searched for 525 spots detected on 2-D gels obtained for 157 recombinant inbred lines. Most protein quantity loci mapped in clusters, suggesting that the accumulation of the major storage protein families was under the control of a limited number of loci. While convicilin accumulation was mainly under the control of cis-regulatory regions, vicilins and legumins were controlled by both cis- and trans-regulatory regions. Some loci controlled both seed protein composition and protein content and a locus on LGIIa appears to be a major regulator of protein composition and of protein in vitro digestibility. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Mapping of shoot fly tolerance loci in sorghum using SSR markers

Indian Academy of Sciences (India)

Identification of the genomic regions containing quantitative trait loci (QTLs) for ... Journal of Genetics, Vol. .... gant analysis were utilized further for genotyping of the ran- ..... Financial support to PLK in the form of research grants from Indian.

Quantitative traits for the tail suspension test: automation, optimization, and BXD RI mapping.

Science.gov (United States)

Lad, Heena V; Liu, Lin; Payá-Cano, José L; Fernandes, Cathy; Schalkwyk, Leonard C

2007-07-01

Immobility in the tail suspension test (TST) is considered a model of despair in a stressful situation, and acute treatment with antidepressants reduces immobility. Inbred strains of mouse exhibit widely differing baseline levels of immobility in the TST and several quantitative trait loci (QTLs) have been nominated. The labor of manual scoring and various scoring criteria make obtaining robust data and comparisons across different laboratories problematic. Several studies have validated strain gauge and video analysis methods by comparison with manual scoring. We set out to find objective criteria for automated scoring parameters that maximize the biological information obtained, using a video tracking system on tapes of tail suspension tests of 24 lines of the BXD recombinant inbred panel and the progenitor strains C57BL/6J and DBA/2J. The maximum genetic effect size is captured using the highest time resolution and a low mobility threshold. Dissecting the trait further by comparing genetic association of multiple measures reveals good evidence for loci involved in immobility on chromosomes 4 and 15. These are best seen when using a high threshold for immobility, despite the overall better heritability at the lower threshold. A second trial of the test has greater duration of immobility and a completely different genetic profile. Frequency of mobility is also an independent phenotype, with a distal chromosome 1 locus.

Mapping and validation of quantitative trait loci for resistance to Cercospora zeae-maydis infection in tropical maize (Zea mays L.).

Science.gov (United States)

Pozar, Gilberto; Butruille, David; Silva, Heyder Diniz; McCuddin, Zoe Patterson; Penna, Julio Cesar Viglioni

2009-02-01

Breeding for resistance to gray leaf spot, caused by Cercospora zeae-maydis (Cz) is paramount for many maize environments, in particular under warm and humid growing conditions. In this study, we mapped and characterized quantitative trait loci (QTL) involved in the resistance of maize against Cz. We confirmed the impact of the QTL on disease severity using near-isogenic lines (NILs), and estimated their effects on three major agronomic traits using their respective near isogenic hybrids (NIHs), which we obtained by crossing the NILs with an inbred from a complementary heterotic pool. We further validated three of the four QTL that were mapped using the Multiple Interval Mapping approach and showed LOD values>2.5. NILs genotype included all combinations between favorable alleles of the two QTL located in chromosome 1 (Q1 in bin 1.05 and Q2 in bin 1.07), and the allele in chromosome 3 (Q3 in bin 3.07). Each of the three QTL separately significantly reduced the severity of Cz. However, we found an unfavorable epistatic interaction between Q1 and Q2: presence of the favorable allele at one of the QTL allele effectively nullified the effect of the favorable allele at the other. In contrast, the interaction between Q2 and Q3 was additive, promoting the reduction of the severity to a greater extent than the sum of their individual effects. When evaluating the NIH we found significant individual effects for Q1 and Q3 on gray leaf spot severity, for Q2 on stalk lodging and grain yield, and for Q3 on grain moisture and stalk lodging. We detected significant epitasis between Q1 and Q2 for grain moisture and between Q1 and Q3 for stalk lodging. These results suggest that the combination of QTL impacts the effectiveness of marker-assisted selection procedures in commercial product development programs.

Major Quantitative Trait Loci and Putative Candidate Genes for Powdery Mildew Resistance and Fruit-Related Traits Revealed by an Intraspecific Genetic Map for Watermelon (Citrullus lanatus var. lanatus)

Science.gov (United States)

Kim, Kwang-Hwan; Hwang, Ji-Hyun; Han, Dong-Yeup; Park, Minkyu; Kim, Seungill; Choi, Doil; Kim, Yongjae; Lee, Gung Pyo; Kim, Sun-Tae; Park, Young-Hoon

2015-01-01

An intraspecific genetic map for watermelon was constructed using an F2 population derived from ‘Arka Manik’ × ‘TS34’ and transcript sequence variants and quantitative trait loci (QTL) for resistance to powdery mildew (PMR), seed size (SS), and fruit shape (FS) were analyzed. The map consists of 14 linkage groups (LGs) defined by 174 cleaved amplified polymorphic sequences (CAPS), 2 derived-cleaved amplified polymorphic sequence markers, 20 sequence-characterized amplified regions, and 8 expressed sequence tag-simple sequence repeat markers spanning 1,404.3 cM, with a mean marker interval of 6.9 cM and an average of 14.6 markers per LG. Genetic inheritance and QTL analyses indicated that each of the PMR, SS, and FS traits is controlled by an incompletely dominant effect of major QTLs designated as pmr2.1, ss2.1, and fsi3.1, respectively. The pmr2.1, detected on chromosome 2 (Chr02), explained 80.0% of the phenotypic variation (LOD = 30.76). This QTL was flanked by two CAPS markers, wsb2-24 (4.00 cM) and wsb2-39 (13.97 cM). The ss2.1, located close to pmr2.1 and CAPS marker wsb2-13 (1.00 cM) on Chr02, explained 92.3% of the phenotypic variation (LOD = 68.78). The fsi3.1, detected on Chr03, explained 79.7% of the phenotypic variation (LOD = 31.37) and was flanked by two CAPS, wsb3-24 (1.91 cM) and wsb3-9 (7.00 cM). Candidate gene-based CAPS markers were developed from the disease resistance and fruit shape gene homologs located on Chr.02 and Chr03 and were mapped on the intraspecific map. Colocalization of these markers with the major QTLs indicated that watermelon orthologs of a nucleotide-binding site-leucine-rich repeat class gene containing an RPW8 domain and a member of SUN containing the IQ67 domain are candidate genes for pmr2.1 and fsi3.1, respectively. The results presented herein provide useful information for marker-assisted breeding and gene cloning for PMR and fruit-related traits. PMID:26700647

Major Quantitative Trait Loci and Putative Candidate Genes for Powdery Mildew Resistance and Fruit-Related Traits Revealed by an Intraspecific Genetic Map for Watermelon (Citrullus lanatus var. lanatus).

Science.gov (United States)

Kim, Kwang-Hwan; Hwang, Ji-Hyun; Han, Dong-Yeup; Park, Minkyu; Kim, Seungill; Choi, Doil; Kim, Yongjae; Lee, Gung Pyo; Kim, Sun-Tae; Park, Young-Hoon

2015-01-01

An intraspecific genetic map for watermelon was constructed using an F2 population derived from 'Arka Manik' × 'TS34' and transcript sequence variants and quantitative trait loci (QTL) for resistance to powdery mildew (PMR), seed size (SS), and fruit shape (FS) were analyzed. The map consists of 14 linkage groups (LGs) defined by 174 cleaved amplified polymorphic sequences (CAPS), 2 derived-cleaved amplified polymorphic sequence markers, 20 sequence-characterized amplified regions, and 8 expressed sequence tag-simple sequence repeat markers spanning 1,404.3 cM, with a mean marker interval of 6.9 cM and an average of 14.6 markers per LG. Genetic inheritance and QTL analyses indicated that each of the PMR, SS, and FS traits is controlled by an incompletely dominant effect of major QTLs designated as pmr2.1, ss2.1, and fsi3.1, respectively. The pmr2.1, detected on chromosome 2 (Chr02), explained 80.0% of the phenotypic variation (LOD = 30.76). This QTL was flanked by two CAPS markers, wsb2-24 (4.00 cM) and wsb2-39 (13.97 cM). The ss2.1, located close to pmr2.1 and CAPS marker wsb2-13 (1.00 cM) on Chr02, explained 92.3% of the phenotypic variation (LOD = 68.78). The fsi3.1, detected on Chr03, explained 79.7% of the phenotypic variation (LOD = 31.37) and was flanked by two CAPS, wsb3-24 (1.91 cM) and wsb3-9 (7.00 cM). Candidate gene-based CAPS markers were developed from the disease resistance and fruit shape gene homologs located on Chr.02 and Chr03 and were mapped on the intraspecific map. Colocalization of these markers with the major QTLs indicated that watermelon orthologs of a nucleotide-binding site-leucine-rich repeat class gene containing an RPW8 domain and a member of SUN containing the IQ67 domain are candidate genes for pmr2.1 and fsi3.1, respectively. The results presented herein provide useful information for marker-assisted breeding and gene cloning for PMR and fruit-related traits.

Identification and validation of quantitative trait loci for seed yield, oil and protein contents in two recombinant inbred line populations of soybean.

Science.gov (United States)

Wang, Xianzhi; Jiang, Guo-Liang; Green, Marci; Scott, Roy A; Song, Qijian; Hyten, David L; Cregan, Perry B

2014-10-01

Soybean seeds contain high levels of oil and protein, and are the important sources of vegetable oil and plant protein for human consumption and livestock feed. Increased seed yield, oil and protein contents are the main objectives of soybean breeding. The objectives of this study were to identify and validate quantitative trait loci (QTLs) associated with seed yield, oil and protein contents in two recombinant inbred line populations, and to evaluate the consistency of QTLs across different environments, studies and genetic backgrounds. Both the mapping population (SD02-4-59 × A02-381100) and validation population (SD02-911 × SD00-1501) were phenotyped for the three traits in multiple environments. Genetic analysis indicated that oil and protein contents showed high heritabilities while yield exhibited a lower heritability in both populations. Based on a linkage map constructed previously with the mapping population and using composite interval mapping and/or interval mapping analysis, 12 QTLs for seed yield, 16 QTLs for oil content and 11 QTLs for protein content were consistently detected in multiple environments and/or the average data over all environments. Of the QTLs detected in the mapping population, five QTLs for seed yield, eight QTLs for oil content and five QTLs for protein content were confirmed in the validation population by single marker analysis in at least one environment and the average data and by ANOVA over all environments. Eight of these validated QTLs were newly identified. Compared with the other studies, seven QTLs for seed yield, eight QTLs for oil content and nine QTLs for protein content further verified the previously reported QTLs. These QTLs will be useful for breeding higher yield and better quality cultivars, and help effectively and efficiently improve yield potential and nutritional quality in soybean.

Uncovering the genetic landscape for multiple sleep-wake traits.

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Christopher J Winrow

Full Text Available Despite decades of research in defining sleep-wake properties in mammals, little is known about the nature or identity of genes that regulate sleep, a fundamental behaviour that in humans occupies about one-third of the entire lifespan. While genome-wide association studies in humans and quantitative trait loci (QTL analyses in mice have identified candidate genes for an increasing number of complex traits and genetic diseases, the resources and time-consuming process necessary for obtaining detailed quantitative data have made sleep seemingly intractable to similar large-scale genomic approaches. Here we describe analysis of 20 sleep-wake traits from 269 mice from a genetically segregating population that reveals 52 significant QTL representing a minimum of 20 genomic loci. While many (28 QTL affected a particular sleep-wake trait (e.g., amount of wake across the full 24-hr day, other loci only affected a trait in the light or dark period while some loci had opposite effects on the trait during the light vs. dark. Analysis of a dataset for multiple sleep-wake traits led to previously undetected interactions (including the differential genetic control of number and duration of REM bouts, as well as possible shared genetic regulatory mechanisms for seemingly different unrelated sleep-wake traits (e.g., number of arousals and REM latency. Construction of a Bayesian network for sleep-wake traits and loci led to the identification of sub-networks of linkage not detectable in smaller data sets or limited single-trait analyses. For example, the network analyses revealed a novel chain of causal relationships between the chromosome 17@29cM QTL, total amount of wake, and duration of wake bouts in both light and dark periods that implies a mechanism whereby overall sleep need, mediated by this locus, in turn determines the length of each wake bout. Taken together, the present results reveal a complex genetic landscape underlying multiple sleep-wake traits

Identification of Genetic Loci Associated with Quality Traits in Almond via Association Mapping.

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Carolina Font i Forcada

Full Text Available To design an appropriate association study, we need to understand population structure and the structure of linkage disequilibrium within and among populations as well as in different regions of the genome in an organism. In this study, we have used a total of 98 almond accessions, from five continents located and maintained at the Centro de Investigación y Tecnología Agroalimentaria de Aragón (CITA; Spain, and 40 microsatellite markers. Population structure analysis performed in 'Structure' grouped the accessions into two principal groups; the Mediterranean (Western-Europe and the non-Mediterranean, with K = 3, being the best fit for our data. There was a strong subpopulation structure with linkage disequilibrium decaying with increasing genetic distance resulting in lower levels of linkage disequilibrium between more distant markers. A significant impact of population structure on linkage disequilibrium in the almond cultivar groups was observed. The mean r2 value for all intra-chromosomal loci pairs was 0.040, whereas, the r2 for the inter-chromosomal loci pairs was 0.036. For analysis of association between the markers and phenotypic traits, five models comprising both general linear models and mixed linear models were selected to test the marker trait associations. The mixed linear model (MLM approach using co-ancestry values from population structure and kinship estimates (K model as covariates identified a maximum of 16 significant associations for chemical traits and 12 for physical traits. This study reports for the first time the use of association mapping for determining marker-locus trait associations in a world-wide almond germplasm collection. It is likely that association mapping will have the most immediate and largest impact on the tier of crops such as almond with the greatest economic value.

A Genome Scan for Quantitative Trait Loci Affecting Average Daily ...

Indian Academy of Sciences (India)

reviewer

Sari, P.O. Box -578, Iran .... (2015) identified one SNP with genome wide significance effect within SYNE1 gene on ..... analysis of thirty one production, health, reproduction and body conformation traits in contemporary US Holstein cows. ... Problems involved in breeding for efficiency of food utilization. Proc .... 131, 210-216.

Fabp7 Maps to a Quantitative Trait Locus for a Schizophrenia Endophenotype

Science.gov (United States)

Watanabe, Akiko; Toyota, Tomoko; Owada, Yuji; Hayashi, Takeshi; Iwayama, Yoshimi; Matsumata, Miho; Ishitsuka, Yuichi; Nakaya, Akihiro; Maekawa, Motoko; Ohnishi, Tetsuo; Arai, Ryoichi; Sakurai, Katsuyasu; Yamada, Kazuo; Kondo, Hisatake; Hashimoto, Kenji; Osumi, Noriko; Yoshikawa, Takeo

2007-01-01

Deficits in prepulse inhibition (PPI) are a biological marker for schizophrenia. To unravel the mechanisms that control PPI, we performed quantitative trait loci (QTL) analysis on 1,010 F2 mice derived by crossing C57BL/6 (B6) animals that show high PPI with C3H/He (C3) animals that show low PPI. We detected six major loci for PPI, six for the acoustic startle response, and four for latency to response peak, some of which were sex-dependent. A promising candidate on the Chromosome 10-QTL was Fabp7 (fatty acid binding protein 7, brain), a gene with functional links to the N-methyl-D-aspartic acid (NMDA) receptor and expression in astrocytes. Fabp7-deficient mice showed decreased PPI and a shortened startle response latency, typical of the QTL's proposed effects. A quantitative complementation test supported Fabp7 as a potential PPI-QTL gene, particularly in male mice. Disruption of Fabp7 attenuated neurogenesis in vivo. Human FABP7 showed altered expression in schizophrenic brains and genetic association with schizophrenia, which were both evident in males when samples were divided by sex. These results suggest that FABP7 plays a novel and crucial role, linking the NMDA, neurodevelopmental, and glial theories of schizophrenia pathology and the PPI endophenotype, with larger or overt effects in males. We also discuss the results from the perspective of fetal programming. PMID:18001149

Fabp7 maps to a quantitative trait locus for a schizophrenia endophenotype.

Directory of Open Access Journals (Sweden)

Akiko Watanabe

2007-11-01

Full Text Available Deficits in prepulse inhibition (PPI are a biological marker for schizophrenia. To unravel the mechanisms that control PPI, we performed quantitative trait loci (QTL analysis on 1,010 F2 mice derived by crossing C57BL/6 (B6 animals that show high PPI with C3H/He (C3 animals that show low PPI. We detected six major loci for PPI, six for the acoustic startle response, and four for latency to response peak, some of which were sex-dependent. A promising candidate on the Chromosome 10-QTL was Fabp7 (fatty acid binding protein 7, brain, a gene with functional links to the N-methyl-D-aspartic acid (NMDA receptor and expression in astrocytes. Fabp7-deficient mice showed decreased PPI and a shortened startle response latency, typical of the QTL's proposed effects. A quantitative complementation test supported Fabp7 as a potential PPI-QTL gene, particularly in male mice. Disruption of Fabp7 attenuated neurogenesis in vivo. Human FABP7 showed altered expression in schizophrenic brains and genetic association with schizophrenia, which were both evident in males when samples were divided by sex. These results suggest that FABP7 plays a novel and crucial role, linking the NMDA, neurodevelopmental, and glial theories of schizophrenia pathology and the PPI endophenotype, with larger or overt effects in males. We also discuss the results from the perspective of fetal programming.

Quantitative trait loci and the relevance of phased haplotypes

DEFF Research Database (Denmark)

Gregersen, Vivi Raundahl

Genetic control of different production traits and diseases within livestock has been of great interest since domenstication. SNPs have greatly facilitated the use of QTL studies in the search of genomic regions affecting different phenotypes. The studies have been conducted to identify regions...... underlying gentic control both as traditional linkage studies relying on genetic maps and as GWAS where an approach of phasing haplotypes within the QTL have been conducted to validate the regions. Overall, regions of interest have been identified for chronic pleuritis and osteochondrosis in addition to meat...... quality and boar taint in pigs, and for improved chees production within cows...

Dissecting genetic architecture of grape proanthocyanidin composition through quantitative trait locus mapping

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Huang Yung-Fen

2012-02-01

Full Text Available Abstract Background Proanthocyanidins (PAs, or condensed tannins, are flavonoid polymers, widespread throughout the plant kingdom, which provide protection against herbivores while conferring organoleptic and nutritive values to plant-derived foods, such as wine. However, the genetic basis of qualitative and quantitative PA composition variation is still poorly understood. To elucidate the genetic architecture of the complex grape PA composition, we first carried out quantitative trait locus (QTL analysis on a 191-individual pseudo-F1 progeny. Three categories of PA variables were assessed: total content, percentages of constitutive subunits and composite ratio variables. For nine functional candidate genes, among which eight co-located with QTLs, we performed association analyses using a diversity panel of 141 grapevine cultivars in order to identify causal SNPs. Results Multiple QTL analysis revealed a total of 103 and 43 QTLs, respectively for seed and skin PA variables. Loci were mainly of additive effect while some loci were primarily of dominant effect. Results also showed a large involvement of pairwise epistatic interactions in shaping PA composition. QTLs for PA variables in skin and seeds differed in number, position, involvement of epistatic interaction and allelic effect, thus revealing different genetic determinisms for grape PA composition in seeds and skin. Association results were consistent with QTL analyses in most cases: four out of nine tested candidate genes (VvLAR1, VvMYBPA2, VvCHI1, VvMYBPA1 showed at least one significant association with PA variables, especially VvLAR1 revealed as of great interest for further functional investigation. Some SNP-phenotype associations were observed only in the diversity panel. Conclusions This study presents the first QTL analysis on grape berry PA composition with a comparison between skin and seeds, together with an association study. Our results suggest a complex genetic control for PA

Seventy-five genetic loci influencing the human red blood cell.

Science.gov (United States)

van der Harst, Pim; Zhang, Weihua; Mateo Leach, Irene; Rendon, Augusto; Verweij, Niek; Sehmi, Joban; Paul, Dirk S; Elling, Ulrich; Allayee, Hooman; Li, Xinzhong; Radhakrishnan, Aparna; Tan, Sian-Tsung; Voss, Katrin; Weichenberger, Christian X; Albers, Cornelis A; Al-Hussani, Abtehale; Asselbergs, Folkert W; Ciullo, Marina; Danjou, Fabrice; Dina, Christian; Esko, Tõnu; Evans, David M; Franke, Lude; Gögele, Martin; Hartiala, Jaana; Hersch, Micha; Holm, Hilma; Hottenga, Jouke-Jan; Kanoni, Stavroula; Kleber, Marcus E; Lagou, Vasiliki; Langenberg, Claudia; Lopez, Lorna M; Lyytikäinen, Leo-Pekka; Melander, Olle; Murgia, Federico; Nolte, Ilja M; O'Reilly, Paul F; Padmanabhan, Sandosh; Parsa, Afshin; Pirastu, Nicola; Porcu, Eleonora; Portas, Laura; Prokopenko, Inga; Ried, Janina S; Shin, So-Youn; Tang, Clara S; Teumer, Alexander; Traglia, Michela; Ulivi, Sheila; Westra, Harm-Jan; Yang, Jian; Zhao, Jing Hua; Anni, Franco; Abdellaoui, Abdel; Attwood, Antony; Balkau, Beverley; Bandinelli, Stefania; Bastardot, François; Benyamin, Beben; Boehm, Bernhard O; Cookson, William O; Das, Debashish; de Bakker, Paul I W; de Boer, Rudolf A; de Geus, Eco J C; de Moor, Marleen H; Dimitriou, Maria; Domingues, Francisco S; Döring, Angela; Engström, Gunnar; Eyjolfsson, Gudmundur Ingi; Ferrucci, Luigi; Fischer, Krista; Galanello, Renzo; Garner, Stephen F; Genser, Bernd; Gibson, Quince D; Girotto, Giorgia; Gudbjartsson, Daniel Fannar; Harris, Sarah E; Hartikainen, Anna-Liisa; Hastie, Claire E; Hedblad, Bo; Illig, Thomas; Jolley, Jennifer; Kähönen, Mika; Kema, Ido P; Kemp, John P; Liang, Liming; Lloyd-Jones, Heather; Loos, Ruth J F; Meacham, Stuart; Medland, Sarah E; Meisinger, Christa; Memari, Yasin; Mihailov, Evelin; Miller, Kathy; Moffatt, Miriam F; Nauck, Matthias; Novatchkova, Maria; Nutile, Teresa; Olafsson, Isleifur; Onundarson, Pall T; Parracciani, Debora; Penninx, Brenda W; Perseu, Lucia; Piga, Antonio; Pistis, Giorgio; Pouta, Anneli; Puc, Ursula; Raitakari, Olli; Ring, Susan M; Robino, Antonietta; Ruggiero, Daniela; Ruokonen, Aimo; Saint-Pierre, Aude; Sala, Cinzia; Salumets, Andres; Sambrook, Jennifer; Schepers, Hein; Schmidt, Carsten Oliver; Silljé, Herman H W; Sladek, Rob; Smit, Johannes H; Starr, John M; Stephens, Jonathan; Sulem, Patrick; Tanaka, Toshiko; Thorsteinsdottir, Unnur; Tragante, Vinicius; van Gilst, Wiek H; van Pelt, L Joost; van Veldhuisen, Dirk J; Völker, Uwe; Whitfield, John B; Willemsen, Gonneke; Winkelmann, Bernhard R; Wirnsberger, Gerald; Algra, Ale; Cucca, Francesco; d'Adamo, Adamo Pio; Danesh, John; Deary, Ian J; Dominiczak, Anna F; Elliott, Paul; Fortina, Paolo; Froguel, Philippe; Gasparini, Paolo; Greinacher, Andreas; Hazen, Stanley L; Jarvelin, Marjo-Riitta; Khaw, Kay Tee; Lehtimäki, Terho; Maerz, Winfried; Martin, Nicholas G; Metspalu, Andres; Mitchell, Braxton D; Montgomery, Grant W; Moore, Carmel; Navis, Gerjan; Pirastu, Mario; Pramstaller, Peter P; Ramirez-Solis, Ramiro; Schadt, Eric; Scott, James; Shuldiner, Alan R; Smith, George Davey; Smith, J Gustav; Snieder, Harold; Sorice, Rossella; Spector, Tim D; Stefansson, Kari; Stumvoll, Michael; Tang, W H Wilson; Toniolo, Daniela; Tönjes, Anke; Visscher, Peter M; Vollenweider, Peter; Wareham, Nicholas J; Wolffenbuttel, Bruce H R; Boomsma, Dorret I; Beckmann, Jacques S; Dedoussis, George V; Deloukas, Panos; Ferreira, Manuel A; Sanna, Serena; Uda, Manuela; Hicks, Andrew A; Penninger, Josef Martin; Gieger, Christian; Kooner, Jaspal S; Ouwehand, Willem H; Soranzo, Nicole; Chambers, John C

2012-12-20

Anaemia is a chief determinant of global ill health, contributing to cognitive impairment, growth retardation and impaired physical capacity. To understand further the genetic factors influencing red blood cells, we carried out a genome-wide association study of haemoglobin concentration and related parameters in up to 135,367 individuals. Here we identify 75 independent genetic loci associated with one or more red blood cell phenotypes at P < 10(-8), which together explain 4-9% of the phenotypic variance per trait. Using expression quantitative trait loci and bioinformatic strategies, we identify 121 candidate genes enriched in functions relevant to red blood cell biology. The candidate genes are expressed preferentially in red blood cell precursors, and 43 have haematopoietic phenotypes in Mus musculus or Drosophila melanogaster. Through open-chromatin and coding-variant analyses we identify potential causal genetic variants at 41 loci. Our findings provide extensive new insights into genetic mechanisms and biological pathways controlling red blood cell formation and function.

Analysis of natural allelic variation of Arabidopsis seed germination and seed longevity traits between the accessions Landberg erecta and Shakdara, using a new recombinant inbred line population

NARCIS (Netherlands)

Clerkx, E.J.M.; El-Lithy, M.E.M.; Vierling, E.; Ruijs, G.J.; Vries, de M.H.C.; Groot, S.P.C.; Vreugdenhil, D.; Koornneef, M.

2004-01-01

Quantitative trait loci (QTL) mapping was used to identify loci controlling various aspects of seed longevity during storage and germination. Similar locations for QTLs controlling different traits might be an indication for a common genetic control of such traits. For this analysis we used a new

A quantitative trait locus mixture model that avoids spurious LOD score peaks.

Science.gov (United States)

Feenstra, Bjarke; Skovgaard, Ib M

2004-06-01

In standard interval mapping of quantitative trait loci (QTL), the QTL effect is described by a normal mixture model. At any given location in the genome, the evidence of a putative QTL is measured by the likelihood ratio of the mixture model compared to a single normal distribution (the LOD score). This approach can occasionally produce spurious LOD score peaks in regions of low genotype information (e.g., widely spaced markers), especially if the phenotype distribution deviates markedly from a normal distribution. Such peaks are not indicative of a QTL effect; rather, they are caused by the fact that a mixture of normals always produces a better fit than a single normal distribution. In this study, a mixture model for QTL mapping that avoids the problems of such spurious LOD score peaks is presented.

Identification of Quantitative Trait Loci That Determine Plasma Total-Cholesterol and Triglyceride Concentrations in DDD/Sgn and C57BL/6J Inbred Mice

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Jun-ichi Suto

2017-01-01

Full Text Available DDD/Sgn mice have significantly higher plasma lipid concentrations than C57BL/6J mice. In the present study, we performed quantitative trait loci (QTL mapping for plasma total-cholesterol (CHO and triglyceride (TG concentrations in reciprocal F2 male intercross populations between the two strains. By single-QTL scans, we identified four significant QTL on chromosomes (Chrs 1, 5, 17, and 19 for CHO and two significant QTL on Chrs 1 and 12 for TG. By including cross direction as an interactive covariate, we identified separate significant QTL on Chr 17 for CHO but none for TG. When the large phenotypic effect of QTL on Chr 1 was controlled by composite interval mapping, we identified three additional significant QTL on Chrs 3, 4, and 9 for CHO but none for TG. QTL on Chr 19 was a novel QTL for CHO and the allelic effect of this QTL significantly differed between males and females. Whole-exome sequence analysis in DDD/Sgn mice suggested that Apoa2 and Acads were the plausible candidate genes underlying CHO QTL on Chrs 1 and 5, respectively. Thus, we identified a multifactorial basis for plasma lipid concentrations in male mice. These findings will provide insight into the genetic mechanisms of plasma lipid metabolism.

Single-trait and multi-trait genome-wide association analyses identify novel loci for blood pressure in African-ancestry populations

OpenAIRE

Liang, Jingjing; Le, Thu H.; Edwards, Digna R. Velez; Tayo, Bamidele O.; Gaulton, Kyle J.; Smith, Jennifer A.; Lu, Yingchang; Jensen, Richard A.; Chen, Guanjie; Yanek, Lisa R.; Schwander, Karen; Tajuddin, Salman M.; Sofer, Tamar; Kim, Wonji; Kayima, James

2017-01-01

© 2017 Public Library of Science. All Rights Reserved. Hypertension is a leading cause of global disease, mortality, and disability. While individuals of African descent suffer a disproportionate burden of hypertension and its complications, they have been underrepresented in genetic studies. To identify novel susceptibility loci for blood pressure and hypertension in people of African ancestry, we performed both single and multiple-trait genome-wide association analyses. We analyzed 21 genom...

Incorporation of covariates in simultaneous localization of two linked loci using affected relative pairs

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Liang Kung-Yee

2010-07-01

Full Text Available Abstract Background Many dichotomous traits for complex diseases are often involved more than one locus and/or associated with quantitative biomarkers or environmental factors. Incorporating these quantitative variables into linkage analysis as well as localizing two linked disease loci simultaneously could therefore improve the efficiency in mapping genes. We extended the robust multipoint Identity-by-Descent (IBD approach with incorporation of covariates developed previously to simultaneously estimate two linked loci using different types of affected relative pairs (ARPs. Results We showed that the efficiency was enhanced by incorporating a quantitative covariate parametrically or non-parametrically while localizing two disease loci using ARPs. In addition to its help in identifying factors associated with the disease and in improving the efficiency in estimating disease loci, this extension also allows investigators to account for heterogeneity in risk-ratios for different ARPs. Data released from the collaborative study on the genetics of alcoholism (COGA for Genetic Analysis Workshop 14 (GAW 14 were used to illustrate the application of this extended method. Conclusions The simulation studies and example illustrated that the efficiency in estimating disease loci was demonstratively enhanced by incorporating a quantitative covariate and by using all relative pairs while mapping two linked loci simultaneously.

An empirical Bayes method for updating inferences in analysis of quantitative trait loci using information from related genome scans.

Science.gov (United States)

Zhang, Kui; Wiener, Howard; Beasley, Mark; George, Varghese; Amos, Christopher I; Allison, David B

2006-08-01

Individual genome scans for quantitative trait loci (QTL) mapping often suffer from low statistical power and imprecise estimates of QTL location and effect. This lack of precision yields large confidence intervals for QTL location, which are problematic for subsequent fine mapping and positional cloning. In prioritizing areas for follow-up after an initial genome scan and in evaluating the credibility of apparent linkage signals, investigators typically examine the results of other genome scans of the same phenotype and informally update their beliefs about which linkage signals in their scan most merit confidence and follow-up via a subjective-intuitive integration approach. A method that acknowledges the wisdom of this general paradigm but formally borrows information from other scans to increase confidence in objectivity would be a benefit. We developed an empirical Bayes analytic method to integrate information from multiple genome scans. The linkage statistic obtained from a single genome scan study is updated by incorporating statistics from other genome scans as prior information. This technique does not require that all studies have an identical marker map or a common estimated QTL effect. The updated linkage statistic can then be used for the estimation of QTL location and effect. We evaluate the performance of our method by using extensive simulations based on actual marker spacing and allele frequencies from available data. Results indicate that the empirical Bayes method can account for between-study heterogeneity, estimate the QTL location and effect more precisely, and provide narrower confidence intervals than results from any single individual study. We also compared the empirical Bayes method with a method originally developed for meta-analysis (a closely related but distinct purpose). In the face of marked heterogeneity among studies, the empirical Bayes method outperforms the comparator.

Genetic mapping of quantitative trait loci for aseasonal reproduction in sheep.

Science.gov (United States)

Mateescu, R G; Thonney, M L

2010-10-01

The productivity and economic prosperity of sheep farming could benefit greatly from more effective methods of selection for year-round lambing. Identification of QTL for aseasonal reproduction in sheep could lead to more accurate selection and faster genetic improvement. One hundred and twenty microsatellite markers were genotyped on 159 backcross ewes from a Dorset × East Friesian crossbred pedigree. Interval mapping was undertaken to map the QTL underlying several traits describing aseasonal reproduction including the number of oestrous cycles, maximum level of progesterone prior to breeding, pregnancy status determined by progesterone level, pregnancy status determined by ultrasound, lambing status and number of lambs born. Seven chromosomes (1, 3, 12, 17, 19, 20 and 24) were identified to harbour putative QTL for one or more component traits used to describe aseasonal reproduction. Ovine chromosomes 12, 17, 19 and 24 harbour QTL significant at the 5% chromosome-wide level, chromosomes 3 and 20 harbour QTL that exceeded the threshold at the 1% chromosome-wide level, while the QTL identified on chromosome 1 exceeded the 1% experiment-wide significance level. These results are a first step towards understanding the genetic mechanism of this complex trait and show that variation in aseasonal reproduction is associated with multiple chromosomal regions. © 2010 The Authors, Animal Genetics © 2010 Stichting International Foundation for Animal Genetics.

Genome scan for nonadditive heterotic trait loci reveals mainly underdominant effects in Saccharomyces cerevisiae.

Science.gov (United States)

Laiba, Efrat; Glikaite, Ilana; Levy, Yael; Pasternak, Zohar; Fridman, Eyal

2016-04-01

The overdominant model of heterosis explains the superior phenotype of hybrids by synergistic allelic interaction within heterozygous loci. To map such genetic variation in yeast, we used a population doubling time dataset of Saccharomyces cerevisiae 16 × 16 diallel and searched for major contributing heterotic trait loci (HTL). Heterosis was observed for the majority of hybrids, as they surpassed their best parent growth rate. However, most of the local heterozygous loci identified by genome scan were surprisingly underdominant, i.e., reduced growth. We speculated that in these loci adverse effects on growth resulted from incompatible allelic interactions. To test this assumption, we eliminated these allelic interactions by creating hybrids with local hemizygosity for the underdominant HTLs, as well as for control random loci. Growth of hybrids was indeed elevated for most hemizygous to HTL genes but not for control genes, hence validating the results of our genome scan. Assessing the consequences of local heterozygosity by reciprocal hemizygosity and allele replacement assays revealed the influence of genetic background on the underdominant effects of HTLs. Overall, this genome-wide study on a multi-parental hybrid population provides a strong argument against single gene overdominance as a major contributor to heterosis, and favors the dominance complementation model.

Fine mapping and candidate gene prediction of a pleiotropic quantitative trait locus for yield-related trait in Zea mays.

Directory of Open Access Journals (Sweden)

Ruixiang Liu

Full Text Available The yield of maize grain is a highly complex quantitative trait that is controlled by multiple quantitative trait loci (QTLs with small effects, and is frequently influenced by multiple genetic and environmental factors. Thus, it is challenging to clone a QTL for grain yield in the maize genome. Previously, we identified a major QTL, qKNPR6, for kernel number per row (KNPR across multiple environments, and developed two nearly isogenic lines, SL57-6 and Ye478, which differ only in the allelic constitution at the short segment harboring the QTL. Recently, qKNPR6 was re-evaluated in segregating populations derived from SL57-6×Ye478, and was narrowed down to a 2.8 cM interval, which explained 56.3% of the phenotypic variance of KNPR in 201 F(2∶3 families. The QTL simultaneously affected ear length, kernel weight and grain yield. Furthermore, a large F(2 population with more than 12,800 plants, 191 recombinant chromosomes and 10 overlapping recombinant lines placed qKNPR6 into a 0.91 cM interval corresponding to 198Kb of the B73 reference genome. In this region, six genes with expressed sequence tag (EST evidence were annotated. The expression pattern and DNA diversity of the six genes were assayed in Ye478 and SL57-6. The possible candidate gene and the pathway involved in inflorescence development were discussed.

Identification of quantitative trait loci for carcass composition and meat quality traits in a commercial finishing cross

NARCIS (Netherlands)

Wijk, van H.J.; Dibbits, B.W.; Baron, E.E.; Brings, A.D.; Harlizius, B.; Groenen, M.A.M.; Knol, E.F.; Bovenhuis, H.

2006-01-01

A QTL study for carcass composition and meat quality traits was conducted on finisher pigs of a cross between a synthetic Pie¿train/Large White boar line and a commercial sow cross. The mapping population comprised 715 individuals evaluated for a total of 30 traits related to growth and fatness (4

Mapping of quantitative trait loci for oil content in cottonseed kernel

Indian Academy of Sciences (India)

(next to fiber) which serves as raw material for oil extraction or animal feed production ... systems that control the performance of these traits could facilitate the application of this information for cottonseed improvement that will help ensure ...

Fine mapping and candidate gene search of quantitative trait loci for growth and obesity using mouse intersubspecific subcongenic intercrosses and exome sequencing.

Directory of Open Access Journals (Sweden)

Akira Ishikawa

Full Text Available Although growth and body composition traits are quantitative traits of medical and agricultural importance, the genetic and molecular basis of those traits remains elusive. Our previous genome-wide quantitative trait locus (QTL analyses in an intersubspecific backcross population between C57BL/6JJcl (B6 and wild Mus musculus castaneus mice revealed a major growth QTL (named Pbwg1 on a proximal region of mouse chromosome 2. Using the B6.Cg-Pbwg1 intersubspecific congenic strain created, we revealed 12 closely linked QTLs for body weight and body composition traits on an approximately 44.1-Mb wild-derived congenic region. In this study, we narrowed down genomic regions harboring three (Pbwg1.12, Pbwg1.3 and Pbwg1.5 of the 12 linked QTLs and searched for possible candidate genes for the QTLs. By phenotypic analyses of F2 intercross populations between B6 and each of four B6.Cg-Pbwg1 subcongenic strains with overlapping and non-overlapping introgressed regions, we physically defined Pbwg1.12 affecting body weight to a 3.8-Mb interval (61.5-65.3 Mb on chromosome 2. We fine-mapped Pbwg1.3 for body length to an 8.0-Mb interval (57.3-65.3 and Pbwg1.5 for abdominal white fat weight to a 2.1-Mb interval (59.4-61.5. The wild-derived allele at Pbwg1.12 and Pbwg1.3 uniquely increased body weight and length despite the fact that the wild mouse has a smaller body size than that of B6, whereas it decreased fat weight at Pbwg1.5. Exome sequencing and candidate gene prioritization suggested that Gcg and Grb14 are putative candidate genes for Pbwg1.12 and that Ly75 and Itgb6 are putative candidate genes for Pbwg1.5. These genes had nonsynonymous SNPs, but the SNPs were predicted to be not harmful to protein functions. These results provide information helpful to identify wild-derived quantitative trait genes causing enhanced growth and resistance to obesity.

Identifying QTL for fur quality traits in mink (Neovison vison)

DEFF Research Database (Denmark)

Thirstrup, Janne Pia; Anistoroaei, Razvan Marian; Guldbrandtsen, Bernt

2012-01-01

Mapping of quantitative trait loci (QTL) affecting fur quality traits (guard hair length, guard hair thikness, and density of woll) was performed in a 3-generation population (F2-design). In the parental generation, Nordic wild mink were crossed reciprocally with American short nap mink. Twenty o...

Two alternative recessive quantitative trait loci influence resistance to spring black stem and leaf spot in Medicago truncatula

Directory of Open Access Journals (Sweden)

Oliver Richard P

2008-03-01

Full Text Available Abstract Background Knowledge of the genetic basis of plant resistance to necrotrophic pathogens is incomplete and has been characterised in relatively few pathosystems. In this study, the cytology and genetics of resistance to spring black stem and leaf spot caused by Phoma medicaginis, an economically important necrotrophic pathogen of Medicago spp., was examined in the model legume M. truncatula. Results Macroscopically, the resistant response of accession SA27063 was characterised by small, hypersensitive-like spots following inoculation while the susceptible interaction with accessions A17 and SA3054 showed necrotic lesions and spreading chlorosis. No unique cytological differences were observed during early infection (2 populations segregating for resistance to spring black stem and leaf spot were established between SA27063 and the two susceptible accessions, A17 and SA3054. The cross between SA27063 and A17 represented a wider cross than between SA27063 and SA3054, as evidenced by higher genetic polymorphism, reduced fertility and aberrant phenotypes of F2 progeny. In the SA27063 × A17 F2 population a highly significant quantitative trait locus (QTL, LOD = 7.37; P Phoma medicaginis one (rnpm1 genetically mapped to the top arm of linkage group 4 (LG4. rnpm1 explained 33.6% of the phenotypic variance in the population's response to infection depicted on a 1–5 scale and was tightly linked to marker AW256637. A second highly significant QTL (LOD = 6.77; P rnpm2, was located on the lower arm of LG8 in the SA27063 × SA3054 map. rnpm2 explained 29.6% of the phenotypic variance and was fine mapped to a 0.8 cM interval between markers h2_16a6a and h2_21h11d. rnpm1 is tightly linked to a cluster of Toll/Interleukin1 receptor-nucleotide binding site-leucine-rich repeat (TIR-NBS-LRR genes and disease resistance protein-like genes, while no resistance gene analogues (RGAs are apparent in the genomic sequence of the reference accession A17 at the

Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways

Science.gov (United States)

Scott, Robert A; Lagou, Vasiliki; Welch, Ryan P; Wheeler, Eleanor; Montasser, May E; Luan, Jian’an; Mägi, Reedik; Strawbridge, Rona J; Rehnberg, Emil; Gustafsson, Stefan; Kanoni, Stavroula; Rasmussen-Torvik, Laura J; Yengo, Loïc; Lecoeur, Cecile; Shungin, Dmitry; Sanna, Serena; Sidore, Carlo; Johnson, Paul C D; Jukema, J Wouter; Johnson, Toby; Mahajan, Anubha; Verweij, Niek; Thorleifsson, Gudmar; Hottenga, Jouke-Jan; Shah, Sonia; Smith, Albert V; Sennblad, Bengt; Gieger, Christian; Salo, Perttu; Perola, Markus; Timpson, Nicholas J; Evans, David M; Pourcain, Beate St; Wu, Ying; Andrews, Jeanette S; Hui, Jennie; Bielak, Lawrence F; Zhao, Wei; Horikoshi, Momoko; Navarro, Pau; Isaacs, Aaron; O’Connell, Jeffrey R; Stirrups, Kathleen; Vitart, Veronique; Hayward, Caroline; Esko, Tönu; Mihailov, Evelin; Fraser, Ross M; Fall, Tove; Voight, Benjamin F; Raychaudhuri, Soumya; Chen, Han; Lindgren, Cecilia M; Morris, Andrew P; Rayner, Nigel W; Robertson, Neil; Rybin, Denis; Liu, Ching-Ti; Beckmann, Jacques S; Willems, Sara M; Chines, Peter S; Jackson, Anne U; Kang, Hyun Min; Stringham, Heather M; Song, Kijoung; Tanaka, Toshiko; Peden, John F; Goel, Anuj; Hicks, Andrew A; An, Ping; Müller-Nurasyid, Martina; Franco-Cereceda, Anders; Folkersen, Lasse; Marullo, Letizia; Jansen, Hanneke; Oldehinkel, Albertine J; Bruinenberg, Marcel; Pankow, James S; North, Kari E; Forouhi, Nita G; Loos, Ruth J F; Edkins, Sarah; Varga, Tibor V; Hallmans, Göran; Oksa, Heikki; Antonella, Mulas; Nagaraja, Ramaiah; Trompet, Stella; Ford, Ian; Bakker, Stephan J L; Kong, Augustine; Kumari, Meena; Gigante, Bruna; Herder, Christian; Munroe, Patricia B; Caulfield, Mark; Antti, Jula; Mangino, Massimo; Small, Kerrin; Miljkovic, Iva; Liu, Yongmei; Atalay, Mustafa; Kiess, Wieland; James, Alan L; Rivadeneira, Fernando; Uitterlinden, Andre G; Palmer, Colin N A; Doney, Alex S F; Willemsen, Gonneke; Smit, Johannes H; Campbell, Susan; Polasek, Ozren; Bonnycastle, Lori L; Hercberg, Serge; Dimitriou, Maria; Bolton, Jennifer L; Fowkes, Gerard R; Kovacs, Peter; Lindström, Jaana; Zemunik, Tatijana; Bandinelli, Stefania; Wild, Sarah H; Basart, Hanneke V; Rathmann, Wolfgang; Grallert, Harald; Maerz, Winfried; Kleber, Marcus E; Boehm, Bernhard O; Peters, Annette; Pramstaller, Peter P; Province, Michael A; Borecki, Ingrid B; Hastie, Nicholas D; Rudan, Igor; Campbell, Harry; Watkins, Hugh; Farrall, Martin; Stumvoll, Michael; Ferrucci, Luigi; Waterworth, Dawn M; Bergman, Richard N; Collins, Francis S; Tuomilehto, Jaakko; Watanabe, Richard M; de Geus, Eco J C; Penninx, Brenda W; Hofman, Albert; Oostra, Ben A; Psaty, Bruce M; Vollenweider, Peter; Wilson, James F; Wright, Alan F; Hovingh, G Kees; Metspalu, Andres; Uusitupa, Matti; Magnusson, Patrik K E; Kyvik, Kirsten O; Kaprio, Jaakko; Price, Jackie F; Dedoussis, George V; Deloukas, Panos; Meneton, Pierre; Lind, Lars; Boehnke, Michael; Shuldiner, Alan R; van Duijn, Cornelia M; Morris, Andrew D; Toenjes, Anke; Peyser, Patricia A; Beilby, John P; Körner, Antje; Kuusisto, Johanna; Laakso, Markku; Bornstein, Stefan R; Schwarz, Peter E H; Lakka, Timo A; Rauramaa, Rainer; Adair, Linda S; Smith, George Davey; Spector, Tim D; Illig, Thomas; de Faire, Ulf; Hamsten, Anders; Gudnason, Vilmundur; Kivimaki, Mika; Hingorani, Aroon; Keinanen-Kiukaanniemi, Sirkka M; Saaristo, Timo E; Boomsma, Dorret I; Stefansson, Kari; van der Harst, Pim; Dupuis, Josée; Pedersen, Nancy L; Sattar, Naveed; Harris, Tamara B; Cucca, Francesco; Ripatti, Samuli; Salomaa, Veikko; Mohlke, Karen L; Balkau, Beverley; Froguel, Philippe; Pouta, Anneli; Jarvelin, Marjo-Riitta; Wareham, Nicholas J; Bouatia-Naji, Nabila; McCarthy, Mark I; Franks, Paul W; Meigs, James B; Teslovich, Tanya M; Florez, Jose C; Langenberg, Claudia; Ingelsson, Erik; Prokopenko, Inga; Barroso, Inês

2012-01-01

Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have raised the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes risk (q fasting insulin showed association with lipid levels and fat distribution, suggesting impact on insulin resistance. Gene-based analyses identified further biologically plausible loci, suggesting that additional loci beyond those reaching genome-wide significance are likely to represent real associations. This conclusion is supported by an excess of directionally consistent and nominally significant signals between discovery and follow-up studies. Functional follow-up of these newly discovered loci will further improve our understanding of glycemic control. PMID:22885924

QTLs for seedling traits under salinity stress in hexaploid wheat

OpenAIRE

Ren, Yongzhe; Xu, Yanhua; Teng, Wan; Li, Bin; Lin, Tongbao

2018-01-01

ABSTRACT: Soil salinity limits agricultural production and is a major obstacle for increasing crop yield. Common wheat is one of the most important crops with allohexaploid characteristic and a highly complex genome. QTL mapping is a useful way to identify genes for quantitative traits such as salinity tolerance in hexaploid wheat. In the present study, a hydroponic trial was carried out to identify quantitative trait loci (QTLs) associated with salinity tolerance of wheat under 150mM NaCl co...

Neutral mutation as the source of genetic variation in life history traits.

Science.gov (United States)

Brcić-Kostić, Krunoslav

2005-08-01

The mechanism underlying the maintenance of adaptive genetic variation is a long-standing question in evolutionary genetics. There are two concepts (mutation-selection balance and balancing selection) which are based on the phenotypic differences between alleles. Mutation - selection balance and balancing selection cannot properly explain the process of gene substitution, i.e. the molecular evolution of quantitative trait loci affecting fitness. I assume that such loci have non-essential functions (small effects on fitness), and that they have the potential to evolve into new functions and acquire new adaptations. Here I show that a high amount of neutral polymorphism at these loci can exist in real populations. Consistent with this, I propose a hypothesis for the maintenance of genetic variation in life history traits which can be efficient for the fixation of alleles with very small selective advantage. The hypothesis is based on neutral polymorphism at quantitative trait loci and both neutral and adaptive gene substitutions. The model of neutral - adaptive conversion (NAC) assumes that neutral alleles are not neutral indefinitely, and that in specific and very rare situations phenotypic (relative fitness) differences between them can appear. In this paper I focus on NAC due to phenotypic plasticity of neutral alleles. The important evolutionary consequence of NAC could be the increased adaptive potential of a population. Loci responsible for adaptation should be fast evolving genes with minimally discernible phenotypic effects, and the recent discovery of genes with such characteristics implicates them as suitable candidates for loci involved in adaptation.

Identification of distinct quantitative trait loci associated with defence against the closely related aphids Acyrthosiphon pisum and A. kondoi in Medicago truncatula

KAUST Repository

Guo, Su-Min

2012-03-21

Aphids are a major family of plant insect pests. Medicago truncatula and Acyrthosiphon pisum (pea aphid, PA) are model species with a suite of resources available to help dissect the mechanism underlying plant-aphid interactions. A previous study focused on monogenic and relatively strong resistance in M. truncatula to PA and other aphid species. In this study a moderate resistance to PA was characterized in detail in the M. truncatula line A17 and compared with the highly susceptible line A20 and the more resistant line Jester. The results show that PA resistance in A17 involves both antibiosis and tolerance, and that resistance is phloem based. Quantitative trait locus (QTL) analysis using a recombinant inbred line (RIL) population (n=114) from a cross between A17 and A20 revealed that one locus, which co-segregated with AIN (Acyrthosiphon-induced necrosis) on chromosome 3, is responsible for the reduction of aphid biomass (indicator of antibiosis) for both PA and bluegreen aphid (BGA, A. kondoi), albeit to a lesser degree for PA than BGA. Interestingly, two independent loci on chromosomes 5 and 3 were identified for the plant biomass reduction (indicator of plant tolerance) by PA and BGA, respectively, demonstrating that the plant\\'s tolerance response to these two closely related aphid species is distinct. Together with previously identified major resistant (R) genes, the QTLs identified in this study are powerful tools to understand fully the spectrum of plant defence against sap-sucking insects and provide opportunities for breeders to generate effective and sustainable strategies for aphid control. 2012 The Author.

Genome-wide Association Study for Calving Traits in Danish and Swedish Holstein Cattle

DEFF Research Database (Denmark)

Sahana, Goutam; Guldbrandtsen, Bernt; Lund, Mogens Sandø

2011-01-01

A total of 22 quantitative trait loci (QTL) were detected on 19 chromosomes for direct and maternal calving traits in cattle using a genome-wide association study. Calving performance is affected by the genotypes of both the calf (direct effect) and dam (maternal effect). To identify the QTL cont...

Fast empirical Bayesian LASSO for multiple quantitative trait locus mapping

Directory of Open Access Journals (Sweden)

Xu Shizhong

2011-05-01

Full Text Available Abstract Background The Bayesian shrinkage technique has been applied to multiple quantitative trait loci (QTLs mapping to estimate the genetic effects of QTLs on quantitative traits from a very large set of possible effects including the main and epistatic effects of QTLs. Although the recently developed empirical Bayes (EB method significantly reduced computation comparing with the fully Bayesian approach, its speed and accuracy are limited by the fact that numerical optimization is required to estimate the variance components in the QTL model. Results We developed a fast empirical Bayesian LASSO (EBLASSO method for multiple QTL mapping. The fact that the EBLASSO can estimate the variance components in a closed form along with other algorithmic techniques render the EBLASSO method more efficient and accurate. Comparing with the EB method, our simulation study demonstrated that the EBLASSO method could substantially improve the computational speed and detect more QTL effects without increasing the false positive rate. Particularly, the EBLASSO algorithm running on a personal computer could easily handle a linear QTL model with more than 100,000 variables in our simulation study. Real data analysis also demonstrated that the EBLASSO method detected more reasonable effects than the EB method. Comparing with the LASSO, our simulation showed that the current version of the EBLASSO implemented in Matlab had similar speed as the LASSO implemented in Fortran, and that the EBLASSO detected the same number of true effects as the LASSO but a much smaller number of false positive effects. Conclusions The EBLASSO method can handle a large number of effects possibly including both the main and epistatic QTL effects, environmental effects and the effects of gene-environment interactions. It will be a very useful tool for multiple QTL mapping.

Quantitative trait loci (QTL study identifies novel genomic regions associated to Chiari-like malformation in Griffon Bruxellois dogs.

Directory of Open Access Journals (Sweden)

Philippe Lemay

Full Text Available Chiari-like malformation (CM is a developmental abnormality of the craniocervical junction that is common in the Griffon Bruxellois (GB breed with an estimated prevalence of 65%. This disease is characterized by overcrowding of the neural parenchyma at the craniocervical junction and disturbance of cerebrospinal fluid (CSF flow. The most common clinical sign is pain either as a direct consequence of CM or neuropathic pain as a consequence of secondary syringomyelia. The etiology of CM remains unknown but genetic factors play an important role. To investigate the genetic complexity of the disease, a quantitative trait locus (QTL approach was adopted. A total of 14 quantitative skull and atlas measurements were taken and were tested for association to CM. Six traits were found to be associated to CM and were subjected to a whole-genome association study using the Illumina canine high density bead chip in 74 GB dogs (50 affected and 24 controls. Linear and mixed regression analyses identified associated single nucleotide polymorphisms (SNPs on 5 Canis Familiaris Autosomes (CFAs: CFA2, CFA9, CFA12, CFA14 and CFA24. A reconstructed haplotype of 0.53 Mb on CFA2 strongly associated to the height of the cranial fossa (diameter F and an haplotype of 2.5 Mb on CFA14 associated to both the height of the rostral part of the caudal cranial fossa (AE and the height of the brain (FG were significantly associated to CM after 10 000 permutations strengthening their candidacy for this disease (P = 0.0421, P = 0.0094 respectively. The CFA2 QTL harbours the Sall-1 gene which is an excellent candidate since its orthologue in humans is mutated in Townes-Brocks syndrome which has previously been associated to Chiari malformation I. Our study demonstrates the implication of multiple traits in the etiology of CM and has successfully identified two new QTL associated to CM and a potential candidate gene.

Identification of distinct quantitative trait loci associated with defence against the closely related aphids Acyrthosiphon pisum and A. kondoi in Medicago truncatula

KAUST Repository

Guo, Su-Min; Kamphuis, Lars G.; Gao, Ling-Ling; Klingler, John P.; Lichtenzveig, Judith; Edwards, Owain; Singh, Karam B.

2012-01-01

and the more resistant line Jester. The results show that PA resistance in A17 involves both antibiosis and tolerance, and that resistance is phloem based. Quantitative trait locus (QTL) analysis using a recombinant inbred line (RIL) population (n=114) from a

A PP2C-1 Allele Underlying a Quantitative Trait Locus Enhances Soybean 100-Seed Weight

Institute of Scientific and Technical Information of China (English)

Xiang Lu; Yong-Cai Lai; Wei-Guang Du; Wei-Qun Man; Shou-Yi Chen; Jin-Song Zhang; Qing Xiong; Tong Cheng; Qing-Tian Li; Xin-Lei Liu; Ying-Dong Bi; Wei Li; Wan-Ke Zhang; Biao Ma

2017-01-01

Cultivated soybeans may lose some useful genetic loci during domestication.Introgression of genes from wild soybeans could broaden the genetic background and improve soybean agronomic traits.In this study,through whole-genome sequencing of a recombinant inbred line population derived from a cross between a wild soybean ZYD7 and a cultivated soybean HN44,and mapping of quantitative trait loci for seed weight,we discovered that a phosphatase 2C-1 (PP2C-1) allele from wild soybean ZYD7 contributes to the increase in seed weight/size.PP2C-1 may achieve this function by enhancing cell size of integument and activating a subset of seed trait-related genes.We found that PP2C-1 is associated with GmBZR1,a soybean ortholog of Arabidopsis BZR1,one of key transcription factors in brassinosteroid (BR) signaling,and facilitate accumulation of dephosphorylated GmBZR1.In contrast,the PP2C-2 allele with variations of a few amino acids at the N-terminus did not exhibit this function.Moreover,we showed that GmBZR1 could promote seed weight/size in transgenic plants.Through analysis of cultivated soybean accessions,we found that 40％ of the examined accessions do not have the PP2C-1 allele,suggesting that these accessions can be improved by introduction of this allele.Taken together,our study identifies an elite allele PP2C-1,which can enhance seed weight and/or size in soybean,and pinpoints that manipulation of this allele by molecular-assisted breeding may increase production in soybean and other legumes/crops.

Estimation of loci involved in non-shattering of seeds in early rice domestication.

Science.gov (United States)

Ishikawa, Ryo; Nishimura, Akinori; Htun, Than Myint; Nishioka, Ryo; Oka, Yumi; Tsujimura, Yuki; Inoue, Chizuru; Ishii, Takashige

2017-04-01

Rice (Oryza sativa L.) is widely cultivated around the world and is known to be domesticated from its wild form, O. rufipogon. A loss of seed shattering is one of the most obvious phenotypic changes selected for during rice domestication. Previously, three seed-shattering loci, qSH1, sh4, and qSH3 were reported to be involved in non-shattering of seeds of Japonica-type cultivated rice, O. sativa cv. Nipponbare. In this study, we focused on non-shattering characteristics of O. sativa Indica cv. IR36 having functional allele at qSH1. We produced backcross recombinant inbred lines having chromosomal segments from IR36 in the genetic background of wild rice, O. rufipogon W630. Histological and quantitative trait loci analyses of abscission layer formation were conducted. In the analysis of quantitative trait loci, a strong peak was observed close to sh4. We, nevertheless, found that some lines showed complete abscission layer formation despite carrying the IR36 allele at sh4, implying that non-shattering of seeds of IR36 could be regulated by the combination of mutations at sh4 and other seed-shattering loci. We also genotyped qSH3, a recently identified seed-shattering locus. Lines that have the IR36 alleles at sh4 and qSH3 showed inhibition of abscission layer formation but the degree of seed shattering was different from that of IR36. On the basis of these results, we estimated that non-shattering of seeds in early rice domestication involved mutations in at least three loci, and these genetic materials produced in this study may help to identify novel seed-shattering loci.

Theory and Practice in Quantitative Genetics

DEFF Research Database (Denmark)

Posthuma, Daniëlle; Beem, A Leo; de Geus, Eco J C

2003-01-01

With the rapid advances in molecular biology, the near completion of the human genome, the development of appropriate statistical genetic methods and the availability of the necessary computing power, the identification of quantitative trait loci has now become a realistic prospect for quantitative...... geneticists. We briefly describe the theoretical biometrical foundations underlying quantitative genetics. These theoretical underpinnings are translated into mathematical equations that allow the assessment of the contribution of observed (using DNA samples) and unobserved (using known genetic relationships......) genetic variation to population variance in quantitative traits. Several statistical models for quantitative genetic analyses are described, such as models for the classical twin design, multivariate and longitudinal genetic analyses, extended twin analyses, and linkage and association analyses. For each...

Confirmation of dyslexia susceptibility loci on chromosomes 1p and 2p, but not 6p in a Dutch sib-pair collection.

NARCIS (Netherlands)

Kovel, C.G.F. de; Franke, B.; Hol, F.A.; Lebrec, J.J.; Maassen, B.A.M.; Brunner, H.G.; Padberg, G.W.A.M.; Platko, J.; Pauls, D.

2008-01-01

In this study, we attempted to confirm genetic linkage to developmental dyslexia and reading-related quantitative traits of loci that have been shown to be associated with dyslexia in previous studies. In our sample of 108 Dutch nuclear families, the categorical trait showed strongest linkage to

Accounting for genetic architecture improves sequence based genomic prediction for a Drosophila fitness trait.

Science.gov (United States)

Ober, Ulrike; Huang, Wen; Magwire, Michael; Schlather, Martin; Simianer, Henner; Mackay, Trudy F C

2015-01-01

The ability to predict quantitative trait phenotypes from molecular polymorphism data will revolutionize evolutionary biology, medicine and human biology, and animal and plant breeding. Efforts to map quantitative trait loci have yielded novel insights into the biology of quantitative traits, but the combination of individually significant quantitative trait loci typically has low predictive ability. Utilizing all segregating variants can give good predictive ability in plant and animal breeding populations, but gives little insight into trait biology. Here, we used the Drosophila Genetic Reference Panel to perform both a genome wide association analysis and genomic prediction for the fitness-related trait chill coma recovery time. We found substantial total genetic variation for chill coma recovery time, with a genetic architecture that differs between males and females, a small number of molecular variants with large main effects, and evidence for epistasis. Although the top additive variants explained 36% (17%) of the genetic variance among lines in females (males), the predictive ability using genomic best linear unbiased prediction and a relationship matrix using all common segregating variants was very low for females and zero for males. We hypothesized that the low predictive ability was due to the mismatch between the infinitesimal genetic architecture assumed by the genomic best linear unbiased prediction model and the true genetic architecture of chill coma recovery time. Indeed, we found that the predictive ability of the genomic best linear unbiased prediction model is markedly improved when we combine quantitative trait locus mapping with genomic prediction by only including the top variants associated with main and epistatic effects in the relationship matrix. This trait-associated prediction approach has the advantage that it yields biologically interpretable prediction models.

Quantitative genetic methods depending on the nature of the phenotypic trait.

Science.gov (United States)

de Villemereuil, Pierre

2018-01-24

A consequence of the assumptions of the infinitesimal model, one of the most important theoretical foundations of quantitative genetics, is that phenotypic traits are predicted to be most often normally distributed (so-called Gaussian traits). But phenotypic traits, especially those interesting for evolutionary biology, might be shaped according to very diverse distributions. Here, I show how quantitative genetics tools have been extended to account for a wider diversity of phenotypic traits using first the threshold model and then more recently using generalized linear mixed models. I explore the assumptions behind these models and how they can be used to study the genetics of non-Gaussian complex traits. I also comment on three recent methodological advances in quantitative genetics that widen our ability to study new kinds of traits: the use of "modular" hierarchical modeling (e.g., to study survival in the context of capture-recapture approaches for wild populations); the use of aster models to study a set of traits with conditional relationships (e.g., life-history traits); and, finally, the study of high-dimensional traits, such as gene expression. © 2018 New York Academy of Sciences.

Inter-simple sequence repeat (ISSR) loci mapping in the genome of perennial ryegrass

DEFF Research Database (Denmark)

Pivorienė, O; Pašakinskienė, I; Brazauskas, G

2008-01-01

The aim of this study was to identify and characterize new ISSR markers and their loci in the genome of perennial ryegrass. A subsample of the VrnA F2 mapping family of perennial ryegrass comprising 92 individuals was used to develop a linkage map including inter-simple sequence repeat markers...... demonstrated a 70% similarity to the Hordeum vulgare germin gene GerA. Inter-SSR mapping will provide useful information for gene targeting, quantitative trait loci mapping and marker-assisted selection in perennial ryegrass....

Genome-wide meta-analysis identifies new susceptibility loci for migraine.

Science.gov (United States)

Anttila, Verneri; Winsvold, Bendik S; Gormley, Padhraig; Kurth, Tobias; Bettella, Francesco; McMahon, George; Kallela, Mikko; Malik, Rainer; de Vries, Boukje; Terwindt, Gisela; Medland, Sarah E; Todt, Unda; McArdle, Wendy L; Quaye, Lydia; Koiranen, Markku; Ikram, M Arfan; Lehtimäki, Terho; Stam, Anine H; Ligthart, Lannie; Wedenoja, Juho; Dunham, Ian; Neale, Benjamin M; Palta, Priit; Hamalainen, Eija; Schürks, Markus; Rose, Lynda M; Buring, Julie E; Ridker, Paul M; Steinberg, Stacy; Stefansson, Hreinn; Jakobsson, Finnbogi; Lawlor, Debbie A; Evans, David M; Ring, Susan M; Färkkilä, Markus; Artto, Ville; Kaunisto, Mari A; Freilinger, Tobias; Schoenen, Jean; Frants, Rune R; Pelzer, Nadine; Weller, Claudia M; Zielman, Ronald; Heath, Andrew C; Madden, Pamela A F; Montgomery, Grant W; Martin, Nicholas G; Borck, Guntram; Göbel, Hartmut; Heinze, Axel; Heinze-Kuhn, Katja; Williams, Frances M K; Hartikainen, Anna-Liisa; Pouta, Anneli; van den Ende, Joyce; Uitterlinden, Andre G; Hofman, Albert; Amin, Najaf; Hottenga, Jouke-Jan; Vink, Jacqueline M; Heikkilä, Kauko; Alexander, Michael; Muller-Myhsok, Bertram; Schreiber, Stefan; Meitinger, Thomas; Wichmann, Heinz Erich; Aromaa, Arpo; Eriksson, Johan G; Traynor, Bryan; Trabzuni, Daniah; Rossin, Elizabeth; Lage, Kasper; Jacobs, Suzanne B R; Gibbs, J Raphael; Birney, Ewan; Kaprio, Jaakko; Penninx, Brenda W; Boomsma, Dorret I; van Duijn, Cornelia; Raitakari, Olli; Jarvelin, Marjo-Riitta; Zwart, John-Anker; Cherkas, Lynn; Strachan, David P; Kubisch, Christian; Ferrari, Michel D; van den Maagdenberg, Arn M J M; Dichgans, Martin; Wessman, Maija; Smith, George Davey; Stefansson, Kari; Daly, Mark J; Nyholt, Dale R; Chasman, Daniel; Palotie, Aarno

2013-08-01

Migraine is the most common brain disorder, affecting approximately 14% of the adult population, but its molecular mechanisms are poorly understood. We report the results of a meta-analysis across 29 genome-wide association studies, including a total of 23,285 individuals with migraine (cases) and 95,425 population-matched controls. We identified 12 loci associated with migraine susceptibility (P<5×10(-8)). Five loci are new: near AJAP1 at 1p36, near TSPAN2 at 1p13, within FHL5 at 6q16, within C7orf10 at 7p14 and near MMP16 at 8q21. Three of these loci were identified in disease subgroup analyses. Brain tissue expression quantitative trait locus analysis suggests potential functional candidate genes at four loci: APOA1BP, TBC1D7, FUT9, STAT6 and ATP5B.

cis-Acting Complex-Trait-Associated lincRNA Expression Correlates with Modulation of Chromosomal Architecture

Directory of Open Access Journals (Sweden)

Jennifer Yihong Tan

2017-02-01

Full Text Available Summary: Intergenic long noncoding RNAs (lincRNAs are the largest class of transcripts in the human genome. Although many have recently been linked to complex human traits, the underlying mechanisms for most of these transcripts remain undetermined. We investigated the regulatory roles of a high-confidence and reproducible set of 69 trait-relevant lincRNAs (TR-lincRNAs in human lymphoblastoid cells whose biological relevance is supported by their evolutionary conservation during recent human history and genetic interactions with other trait-associated loci. Their enrichment in enhancer-like chromatin signatures, interactions with nearby trait-relevant protein-coding loci, and preferential location at topologically associated domain (TAD boundaries provide evidence that TR-lincRNAs likely regulate proximal trait-relevant gene expression in cis by modulating local chromosomal architecture. This is consistent with the positive and significant correlation found between TR-lincRNA abundance and intra-TAD DNA-DNA contacts. Our results provide insights into the molecular mode of action by which TR-lincRNAs contribute to complex human traits. : Tan et al. identify and characterize 69 human complex trait/disease-associated lincRNAs in LCLs. They show that these loci are often associated with cis-regulation of gene expression and tend to be localized at TAD boundaries, suggesting that these lincRNAs may influence chromosomal architecture. Keywords: intergenic long noncoding RNA, lincRNA, GWAS, expression quantitative trait loci, eQTL, complex trait and disease, enhancer, cis-regulation, topologically associated domains, TAD

Statistical properties of interval mapping methods on quantitative trait loci location: impact on QTL/eQTL analyses

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Wang Xiaoqiang

2012-04-01

Full Text Available Abstract Background Quantitative trait loci (QTL detection on a huge amount of phenotypes, like eQTL detection on transcriptomic data, can be dramatically impaired by the statistical properties of interval mapping methods. One of these major outcomes is the high number of QTL detected at marker locations. The present study aims at identifying and specifying the sources of this bias, in particular in the case of analysis of data issued from outbred populations. Analytical developments were carried out in a backcross situation in order to specify the bias and to propose an algorithm to control it. The outbred population context was studied through simulated data sets in a wide range of situations. The likelihood ratio test was firstly analyzed under the "one QTL" hypothesis in a backcross population. Designs of sib families were then simulated and analyzed using the QTL Map software. On the basis of the theoretical results in backcross, parameters such as the population size, the density of the genetic map, the QTL effect and the true location of the QTL, were taken into account under the "no QTL" and the "one QTL" hypotheses. A combination of two non parametric tests - the Kolmogorov-Smirnov test and the Mann-Whitney-Wilcoxon test - was used in order to identify the parameters that affected the bias and to specify how much they influenced the estimation of QTL location. Results A theoretical expression of the bias of the estimated QTL location was obtained for a backcross type population. We demonstrated a common source of bias under the "no QTL" and the "one QTL" hypotheses and qualified the possible influence of several parameters. Simulation studies confirmed that the bias exists in outbred populations under both the hypotheses of "no QTL" and "one QTL" on a linkage group. The QTL location was systematically closer to marker locations than expected, particularly in the case of low QTL effect, small population size or low density of markers, i

Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways

NARCIS (Netherlands)

Scott, Robert A.; Lagou, Vasiliki; Welch, Ryan P.; Wheeler, Eleanor; Montasser, May E.; Luan, Jian'an; Mägi, Reedik; Strawbridge, Rona J.; Rehnberg, Emil; Gustafsson, Stefan; Kanoni, Stavroula; Rasmussen-Torvik, Laura J.; Yengo, Loïc; Lecoeur, Cecile; Shungin, Dmitry; Sanna, Serena; Sidore, Carlo; Johnson, Paul C. D.; Jukema, J. Wouter; Johnson, Toby; Mahajan, Anubha; Verweij, Niek; Thorleifsson, Gudmar; Hottenga, Jouke-Jan; Shah, Sonia; Smith, Albert V.; Sennblad, Bengt; Gieger, Christian; Salo, Perttu; Perola, Markus; Timpson, Nicholas J.; Evans, David M.; Pourcain, Beate St; Wu, Ying; Andrews, Jeanette S.; Hui, Jennie; Bielak, Lawrence F.; Zhao, Wei; Horikoshi, Momoko; Navarro, Pau; Isaacs, Aaron; O'Connell, Jeffrey R.; Stirrups, Kathleen; Vitart, Veronique; Hayward, Caroline; Esko, Tõnu; Mihailov, Evelin; Fraser, Ross M.; Fall, Tove; Voight, Benjamin F.; Raychaudhuri, Soumya; Chen, Han; Lindgren, Cecilia M.; Morris, Andrew P.; Rayner, Nigel W.; Robertson, Neil; Rybin, Denis; Liu, Ching-Ti; Beckmann, Jacques S.; Willems, Sara M.; Chines, Peter S.; Jackson, Anne U.; Kang, Hyun Min; Stringham, Heather M.; Song, Kijoung; Tanaka, Toshiko; Peden, John F.; Goel, Anuj; Hicks, Andrew A.; An, Ping; Müller-Nurasyid, Martina; Franco-Cereceda, Anders; Folkersen, Lasse; Marullo, Letizia; Jansen, Hanneke; Oldehinkel, Albertine J.; Bruinenberg, Marcel; Pankow, James S.; North, Kari E.; Forouhi, Nita G.; Loos, Ruth J. F.; Edkins, Sarah; Varga, Tibor V.; Hallmans, Göran; Oksa, Heikki; Antonella, Mulas; Nagaraja, Ramaiah; Trompet, Stella; Ford, Ian; Bakker, Stephan J. L.; Kong, Augustine; Kumari, Meena; Gigante, Bruna; Herder, Christian; Munroe, Patricia B.; Caulfield, Mark; Antti, Jula; Mangino, Massimo; Small, Kerrin; Miljkovic, Iva; Liu, Yongmei; Atalay, Mustafa; Kiess, Wieland; James, Alan L.; Rivadeneira, Fernando; Uitterlinden, Andre G.; Palmer, Colin N. A.; Doney, Alex S. F.; Willemsen, Gonneke; Smit, Johannes H.; Campbell, Susan; Polasek, Ozren; Bonnycastle, Lori L.; Hercberg, Serge; Dimitriou, Maria; Bolton, Jennifer L.; Fowkes, Gerard R.; Kovacs, Peter; Lindström, Jaana; Zemunik, Tatijana; Bandinelli, Stefania; Wild, Sarah H.; Basart, Hanneke V.; Rathmann, Wolfgang; Grallert, Harald; Maerz, Winfried; Kleber, Marcus E.; Boehm, Bernhard O.; Peters, Annette; Pramstaller, Peter P.; Province, Michael A.; Borecki, Ingrid B.; Hastie, Nicholas D.; Rudan, Igor; Campbell, Harry; Watkins, Hugh; Farrall, Martin; Stumvoll, Michael; Ferrucci, Luigi; Waterworth, Dawn M.; Bergman, Richard N.; Collins, Francis S.; Tuomilehto, Jaakko; Watanabe, Richard M.; de Geus, Eco J. C.; Penninx, Brenda W.; Hofman, Albert; Oostra, Ben A.; Psaty, Bruce M.; Vollenweider, Peter; Wilson, James F.; Wright, Alan F.; Hovingh, G. Kees; Metspalu, Andres; Uusitupa, Matti; Magnusson, Patrik K. E.; Kyvik, Kirsten O.; Kaprio, Jaakko; Price, Jackie F.; Dedoussis, George V.; Deloukas, Panos; Meneton, Pierre; Lind, Lars; Boehnke, Michael; Shuldiner, Alan R.; van Duijn, Cornelia M.; Morris, Andrew D.; Toenjes, Anke; Peyser, Patricia A.; Beilby, John P.; Körner, Antje; Kuusisto, Johanna; Laakso, Markku; Bornstein, Stefan R.; Schwarz, Peter E. H.; Lakka, Timo A.; Rauramaa, Rainer; Adair, Linda S.; Smith, George Davey; Spector, Tim D.; Illig, Thomas; de Faire, Ulf; Hamsten, Anders; Gudnason, Vilmundur; Kivimaki, Mika; Hingorani, Aroon; Keinanen-Kiukaanniemi, Sirkka M.; Saaristo, Timo E.; Boomsma, Dorret I.; Stefansson, Kari; van der Harst, Pim; Dupuis, Josée; Pedersen, Nancy L.; Sattar, Naveed; Harris, Tamara B.; Cucca, Francesco; Ripatti, Samuli; Salomaa, Veikko; Mohlke, Karen L.; Balkau, Beverley; Froguel, Philippe; Pouta, Anneli; Jarvelin, Marjo-Riitta; Wareham, Nicholas J.; Bouatia-Naji, Nabila; McCarthy, Mark I.; Franks, Paul W.; Meigs, James B.; Teslovich, Tanya M.; Florez, Jose C.; Langenberg, Claudia; Ingelsson, Erik; Prokopenko, Inga; Barroso, Inês

2012-01-01

Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes

Large-scale association analyses identify new loci influencing glycemic traits and provide insight into the underlying biological pathways

DEFF Research Database (Denmark)

Scott, Robert A; Lagou, Vasiliki; Welch, Ryan P

2012-01-01

Through genome-wide association meta-analyses of up to 133,010 individuals of European ancestry without diabetes, including individuals newly genotyped using the Metabochip, we have increased the number of confirmed loci influencing glycemic traits to 53, of which 33 also increase type 2 diabetes...

Marker-assisted selection for quantitative traits

Directory of Open Access Journals (Sweden)

Ivan Schuster

2011-01-01

Full Text Available Although thousands of scientific articles have been published on the subject of marker-assisted selection (MAS andquantitative trait loci (QTL, the application of MAS for QTL in plant breeding has been restricted. Among the main causes for thislimited use are the low accuracy of QTL mapping and the high costs of genotyping thousands of plants with tens or hundreds ofmolecular markers in routine breeding programs. Recently, new large-scale genotyping technologies have resulted in a costreduction. Nevertheless, the MAS for QTL has so far been limited to selection programs using several generations per year, wherephenotypic selection cannot be performed in all generations, mainly in recurrent selection programs. Methods of MAS for QTL inbreeding programs using self-pollination have been developed.

Accounting for genetic architecture improves sequence based genomic prediction for a Drosophila fitness trait.

Directory of Open Access Journals (Sweden)

Ulrike Ober

Full Text Available The ability to predict quantitative trait phenotypes from molecular polymorphism data will revolutionize evolutionary biology, medicine and human biology, and animal and plant breeding. Efforts to map quantitative trait loci have yielded novel insights into the biology of quantitative traits, but the combination of individually significant quantitative trait loci typically has low predictive ability. Utilizing all segregating variants can give good predictive ability in plant and animal breeding populations, but gives little insight into trait biology. Here, we used the Drosophila Genetic Reference Panel to perform both a genome wide association analysis and genomic prediction for the fitness-related trait chill coma recovery time. We found substantial total genetic variation for chill coma recovery time, with a genetic architecture that differs between males and females, a small number of molecular variants with large main effects, and evidence for epistasis. Although the top additive variants explained 36% (17% of the genetic variance among lines in females (males, the predictive ability using genomic best linear unbiased prediction and a relationship matrix using all common segregating variants was very low for females and zero for males. We hypothesized that the low predictive ability was due to the mismatch between the infinitesimal genetic architecture assumed by the genomic best linear unbiased prediction model and the true genetic architecture of chill coma recovery time. Indeed, we found that the predictive ability of the genomic best linear unbiased prediction model is markedly improved when we combine quantitative trait locus mapping with genomic prediction by only including the top variants associated with main and epistatic effects in the relationship matrix. This trait-associated prediction approach has the advantage that it yields biologically interpretable prediction models.

Effect of Box-Cox transformation on power of Haseman-Elston and maximum-likelihood variance components tests to detect quantitative trait Loci.

Science.gov (United States)

Etzel, C J; Shete, S; Beasley, T M; Fernandez, J R; Allison, D B; Amos, C I

2003-01-01

Non-normality of the phenotypic distribution can affect power to detect quantitative trait loci in sib pair studies. Previously, we observed that Winsorizing the sib pair phenotypes increased the power of quantitative trait locus (QTL) detection for both Haseman-Elston (HE) least-squares tests [Hum Hered 2002;53:59-67] and maximum likelihood-based variance components (MLVC) analysis [Behav Genet (in press)]. Winsorizing the phenotypes led to a slight increase in type 1 error in H-E tests and a slight decrease in type I error for MLVC analysis. Herein, we considered transforming the sib pair phenotypes using the Box-Cox family of transformations. Data were simulated for normal and non-normal (skewed and kurtic) distributions. Phenotypic values were replaced by Box-Cox transformed values. Twenty thousand replications were performed for three H-E tests of linkage and the likelihood ratio test (LRT), the Wald test and other robust versions based on the MLVC method. We calculated the relative nominal inflation rate as the ratio of observed empirical type 1 error divided by the set alpha level (5, 1 and 0.1% alpha levels). MLVC tests applied to non-normal data had inflated type I errors (rate ratio greater than 1.0), which were controlled best by Box-Cox transformation and to a lesser degree by Winsorizing. For example, for non-transformed, skewed phenotypes (derived from a chi2 distribution with 2 degrees of freedom), the rates of empirical type 1 error with respect to set alpha level=0.01 were 0.80, 4.35 and 7.33 for the original H-E test, LRT and Wald test, respectively. For the same alpha level=0.01, these rates were 1.12, 3.095 and 4.088 after Winsorizing and 0.723, 1.195 and 1.905 after Box-Cox transformation. Winsorizing reduced inflated error rates for the leptokurtic distribution (derived from a Laplace distribution with mean 0 and variance 8). Further, power (adjusted for empirical type 1 error) at the 0.01 alpha level ranged from 4.7 to 17.3% across all tests

Variant-aware saturating mutagenesis using multiple Cas9 nucleases identifies regulatory elements at trait-associated loci.

Science.gov (United States)

Canver, Matthew C; Lessard, Samuel; Pinello, Luca; Wu, Yuxuan; Ilboudo, Yann; Stern, Emily N; Needleman, Austen J; Galactéros, Frédéric; Brugnara, Carlo; Kutlar, Abdullah; McKenzie, Colin; Reid, Marvin; Chen, Diane D; Das, Partha Pratim; A Cole, Mitchel; Zeng, Jing; Kurita, Ryo; Nakamura, Yukio; Yuan, Guo-Cheng; Lettre, Guillaume; Bauer, Daniel E; Orkin, Stuart H

2017-04-01

Cas9-mediated, high-throughput, saturating in situ mutagenesis permits fine-mapping of function across genomic segments. Disease- and trait-associated variants identified in genome-wide association studies largely cluster at regulatory loci. Here we demonstrate the use of multiple designer nucleases and variant-aware library design to interrogate trait-associated regulatory DNA at high resolution. We developed a computational tool for the creation of saturating-mutagenesis libraries with single or multiple nucleases with incorporation of variants. We applied this methodology to the HBS1L-MYB intergenic region, which is associated with red-blood-cell traits, including fetal hemoglobin levels. This approach identified putative regulatory elements that control MYB expression. Analysis of genomic copy number highlighted potential false-positive regions, thus emphasizing the importance of off-target analysis in the design of saturating-mutagenesis experiments. Together, these data establish a widely applicable high-throughput and high-resolution methodology to identify minimal functional sequences within large disease- and trait-associated regions.

Genetic and physiological characterization of two clusters of quantitative trait Loci associated with seed dormancy and plant height in rice.

Science.gov (United States)

Ye, Heng; Beighley, Donn H; Feng, Jiuhuan; Gu, Xing-You

2013-02-01

Seed dormancy and plant height have been well-studied in plant genetics, but their relatedness and shared regulatory mechanisms in natural variants remain unclear. The introgression of chromosomal segments from weedy into cultivated rice (Oryza sativa) prompted the detection of two clusters (qSD1-2/qPH1 and qSD7-2/qPH7) of quantitative trait loci both associated with seed dormancy and plant height. Together, these two clusters accounted for >96% of the variances for plant height and ~71% of the variances for germination rate in an isogenic background across two environments. On the initial introgression segments, qSD1-2/qPH1 was dissected genetically from OsVp1 for vivipary and qSD7-2/qPH7 separated from Sdr4 for seed dormancy. The narrowed qSD1-2/qPH1 region encompasses the semidwarf1 (sd1) locus for gibberellin (GA) biosynthesis. The qSD1-2/qPH1 allele from the cultivar reduced germination and stem elongation and the mutant effects were recovered by exogenous GA, suggesting that sd1 is a candidate gene of the cluster. In contrast, the effect-reducing allele at qSD7-2/qPH7 was derived from the weedy line; this allele was GA-insensitive and blocked GA responses of qSD1-2/qPH1, including the transcription of a GA-inducible α-amylase gene in imbibed endosperm, suggesting that qSD7-2/qPH7 may work downstream from qSD1-2/qPH1 in GA signaling. Thus, this research established the seed dormancy-plant height association that is likely mediated by GA biosynthesis and signaling pathways in natural populations. The detected association contributed to weed mimicry for the plant stature in the agro-ecosystem dominated by semidwarf cultivars and revealed the potential benefit of semidwarf genes in resistance to preharvest sprouting.

Detection of quantitative trait loci causing abnormal spermatogenesis and reduced testis weight in the small testis (Smt) mutant mouse.

Science.gov (United States)

Bolor, Hasbaira; Wakasugi, Noboru; Zhao, Wei Dong; Ishikawa, Akira

2006-04-01

The small testis (Smt) mutant mouse is characterized by a small testis of one third to one half the size of a normal testis, and its spermatogenesis is mostly arrested at early stages of meiosis, although a small number of spermatocytes at the late prophase of meiosis and a few spermatids can sometimes be seen. We performed quantitative trait locus (QTL) analysis of these spermatogenic traits and testis weight using 221 F2 males obtained from a cross between Smt and MOM (Mus musculus molossinus) mice. At the genome-wide 5% level, we detected two QTLs affecting meiosis on chromosomes 4 and 13, and two QTLs for paired testis weight as a percentage of body weight on chromosomes 4 and X. In addition, we found several QTLs for degenerated germ cells and multinuclear giant cells on chromosomes 4, 7 and 13. Interestingly, for cell degeneration, the QTL on chromosome 13 interacted epistatically with the QTL on chromosome 4. These results reveal polygenic participation in the abnormal spermatogenesis and small testis size in the Smt mutant.

Evidences of local adaptation in quantitative traits in Prosopis alba (Leguminosae).

Science.gov (United States)

Bessega, C; Pometti, C; Ewens, M; Saidman, B O; Vilardi, J C

2015-02-01

Signals of selection on quantitative traits can be detected by the comparison between the genetic differentiation of molecular (neutral) markers and quantitative traits, by multivariate extensions of the same model and by the observation of the additive covariance among relatives. We studied, by three different tests, signals of occurrence of selection in Prosopis alba populations over 15 quantitative traits: three economically important life history traits: height, basal diameter and biomass, 11 leaf morphology traits that may be related with heat-tolerance and physiological responses and spine length that is very important from silvicultural purposes. We analyzed 172 G1-generation trees growing in a common garden belonging to 32 open pollinated families from eight sampling sites in Argentina. The multivariate phenotypes differ significantly among origins, and the highest differentiation corresponded to foliar traits. Molecular genetic markers (SSR) exhibited significant differentiation and allowed us to provide convincing evidence that natural selection is responsible for the patterns of morphological differentiation. The heterogeneous selection over phenotypic traits observed suggested different optima in each population and has important implications for gene resource management. The results suggest that the adaptive significance of traits should be considered together with population provenance in breeding program as a crucial point prior to any selecting program, especially in Prosopis where the first steps are under development.

Trans-ethnic fine-mapping of lipid loci identifies population-specific signals and allelic heterogeneity that increases the trait variance explained.

Directory of Open Access Journals (Sweden)

Ying Wu

2013-03-01

Full Text Available Genome-wide association studies (GWAS have identified ~100 loci associated with blood lipid levels, but much of the trait heritability remains unexplained, and at most loci the identities of the trait-influencing variants remain unknown. We conducted a trans-ethnic fine-mapping study at 18, 22, and 18 GWAS loci on the Metabochip for their association with triglycerides (TG, high-density lipoprotein cholesterol (HDL-C, and low-density lipoprotein cholesterol (LDL-C, respectively, in individuals of African American (n = 6,832, East Asian (n = 9,449, and European (n = 10,829 ancestry. We aimed to identify the variants with strongest association at each locus, identify additional and population-specific signals, refine association signals, and assess the relative significance of previously described functional variants. Among the 58 loci, 33 exhibited evidence of association at P<1 × 10(-4 in at least one ancestry group. Sequential conditional analyses revealed that ten, nine, and four loci in African Americans, Europeans, and East Asians, respectively, exhibited two or more signals. At these loci, accounting for all signals led to a 1.3- to 1.8-fold increase in the explained phenotypic variance compared to the strongest signals. Distinct signals across ancestry groups were identified at PCSK9 and APOA5. Trans-ethnic analyses narrowed the signals to smaller sets of variants at GCKR, PPP1R3B, ABO, LCAT, and ABCA1. Of 27 variants reported previously to have functional effects, 74% exhibited the strongest association at the respective signal. In conclusion, trans-ethnic high-density genotyping and analysis confirm the presence of allelic heterogeneity, allow the identification of population-specific variants, and limit the number of candidate SNPs for functional studies.

Detecting Genetic Interactions for Quantitative Traits Using m-Spacing Entropy Measure

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Jaeyong Yee

2015-01-01

Full Text Available A number of statistical methods for detecting gene-gene interactions have been developed in genetic association studies with binary traits. However, many phenotype measures are intrinsically quantitative and categorizing continuous traits may not always be straightforward and meaningful. Association of gene-gene interactions with an observed distribution of such phenotypes needs to be investigated directly without categorization. Information gain based on entropy measure has previously been successful in identifying genetic associations with binary traits. We extend the usefulness of this information gain by proposing a nonparametric evaluation method of conditional entropy of a quantitative phenotype associated with a given genotype. Hence, the information gain can be obtained for any phenotype distribution. Because any functional form, such as Gaussian, is not assumed for the entire distribution of a trait or a given genotype, this method is expected to be robust enough to be applied to any phenotypic association data. Here, we show its use to successfully identify the main effect, as well as the genetic interactions, associated with a quantitative trait.

Mapping of yield, yield stability, yield adaptability and other traits in barley using linkage disequilibrium mapping and linkage analysis

OpenAIRE

Kraakman, A.T.W.

2005-01-01

Plants is mostly done through linkage analysis. A segregating mapping population Identification and mappping of Quantitative Trait Loci (QTLs) in is created from a bi-parental cross and linkages between trait values and mapped markers reveal the positions ofQTLs. Inthisstudyweexploredlinkagedisequilibrium(LD)mappingof traits in a set of modernbarleycultivars. LDbetweenmolecularmarkerswasfoundup to a distance of 10 centimorgan,whichislargecomparedtootherspecies.Thelarge distancemightbeinducedb...

Mapping of yield, yield stability, yield adaptability and other traits in barley using linkage disequilibrium mapping and linkage analysis

NARCIS (Netherlands)

Kraakman, A.T.W.

2005-01-01

Plants is mostly done through linkage analysis. A segregating mapping population Identification and mappping of Quantitative Trait Loci (QTLs) in is created from a bi-parental cross and linkages between trait values and mapped markers reveal the positions ofQTLs. In

MAPPING AND GENETIC EFFECT ANALYSIS ON QUANTITATIVE TRAIT LOCI RELATED TO FEED CONVERSION RATIO OF COMMON CARP (CYPRINUS CARPIO L.)%鲤饲料转化率性状的QTL定位及遗传效应分析

Institute of Scientific and Technical Information of China (English)

王宣朋; 张晓峰; 李文升; 张天奇; 李超; 孙效文

2012-01-01

The common carp (Cyprinus carpio L.), one of the most important species for aquaculture in China, is a widespread freshwater fish of eutrophic waters in lakes and large rivers. The wild populations are considered vulnerable to extinction, but the species has also been domesticated and introduced into environments worldwide, and is often considered as an invasive species. However, genetic degeneration, such as low growth rate, small body size, weak disease-resistance, etc., emerged in common carp with the rapid development of its farming scale. Quantitative traits (for example, the feed conversion ratio of common carp) refer to phenotypes that vary in degree and can be attributed to polygenic effects, I.e., product of two or more genes, and their environment. Quantitative trait loci (QTLs) are stretches of DNA containing or linked to the genes that underlie a quantitative trait. Mapping regions of the genome that contain genes involved in specifying a quantitative trait is done using molecular tags such as SSR, EST or more commonly SNPs. This is an early step in identifying and sequencing the actual genes underlying trait variation. Researches of genetic diversity, kin discrimination, strain identification, genetic linkage map construction, trait-related marker screening, genetic evaluation and QTL are the effective way to solve these problems of breeding in common carp. In this paper, a group of F2 hybrids German mirror carp including 68 individuals was used to construct a linkage map by using 560 markers (174 SSR markers, 41EST-SSR markers and 345 SNP markers). Quantitative traits loci (QTLs) associated with feed conversion ratio were identified by interval mapping and MQM mapping of the software MapQTL5.0. A linkage group wide permutation test (1000 replicates) determined the significance of the maximum LOD value over the various intervals analyzed for each linkage group. The results indicated that fifteen QTLs were identified for feed conversion ratio on nine

Quantitative traits in wheat (Triticum aestivum L

African Journals Online (AJOL)

MSS

2012-11-13

Nov 13, 2012 ... Of the quantitative traits in wheat, spike length, number of spikes per m2, grain mass per spike, number ... design with four liming variants along with three replications, in which the experimental field .... The sampling was done.

Statistical mechanics and the evolution of polygenic quantitative traits

NARCIS (Netherlands)

Barton, N.H.; De Vladar, H.P.

The evolution of quantitative characters depends on the frequencies of the alleles involved, yet these frequencies cannot usually be measured. Previous groups have proposed an approximation to the dynamics of quantitative traits, based on an analogy with statistical mechanics. We present a modified

Quantitative trait locus mapping of deep rooting by linkage and association analysis in rice.

Science.gov (United States)

Lou, Qiaojun; Chen, Liang; Mei, Hanwei; Wei, Haibin; Feng, Fangjun; Wang, Pei; Xia, Hui; Li, Tiemei; Luo, Lijun

2015-08-01

Deep rooting is a very important trait for plants' drought avoidance, and it is usually represented by the ratio of deep rooting (RDR). Three sets of rice populations were used to determine the genetic base for RDR. A linkage mapping population with 180 recombinant inbred lines and an association mapping population containing 237 rice varieties were used to identify genes linked to RDR. Six quantitative trait loci (QTLs) of RDR were identified as being located on chromosomes 1, 2, 4, 7, and 10. Using 1 019 883 single-nucleotide polymorphisms (SNPs), a genome-wide association study of the RDR was performed. Forty-eight significant SNPs of the RDR were identified and formed a clear peak on the short arm of chromosome 1 in a Manhattan plot. Compared with the shallow-rooting group and the whole collection, the deep-rooting group had selective sweep regions on chromosomes 1 and 2, especially in the major QTL region on chromosome 2. Seven of the nine candidate SNPs identified by association mapping were verified in two RDR extreme groups. The findings from this study will be beneficial to rice drought-resistance research and breeding. © The Author 2015. Published by Oxford University Press on behalf of the Society for Experimental Biology.

Whole-genome modeling accurately predicts quantitative traits, as revealed in plants.

OpenAIRE

Tatarinova, Tatiana; Shin, Min-Gyoung; Marjoram, Paul; Nuzhdin, Sergey; Triska, Martin; Rickauer, Martina; Nikolsky, Yuri; Mazurier, Melanie; Gentzbittel, Laurent; Ben, Cecile

2016-01-01

Many adaptive events in natural populations, as well as response to artificial selection, are caused by polygenic action. Under selective pressure, the adaptive traits can quickly respond via small allele frequency shifts spread across numerous loci. We hypothesize that a large proportion of current phenotypic variation between individuals may be best explained by population admixture. We thus consider the complete, genome-wide universe of genetic variability, spread across several ancestral ...

Quantitative genetics of disease traits.

Science.gov (United States)

Wray, N R; Visscher, P M

2015-04-01

John James authored two key papers on the theory of risk to relatives for binary disease traits and the relationship between parameters on the observed binary scale and an unobserved scale of liability (James Annals of Human Genetics, 1971; 35: 47; Reich, James and Morris Annals of Human Genetics, 1972; 36: 163). These two papers are John James' most cited papers (198 and 328 citations, November 2014). They have been influential in human genetics and have recently gained renewed popularity because of their relevance to the estimation of quantitative genetics parameters for disease traits using SNP data. In this review, we summarize the two early papers and put them into context. We show recent extensions of the theory for ascertained case-control data and review recent applications in human genetics. © 2015 Blackwell Verlag GmbH.

In-silico QTL mapping of postpubertal mammary ductal development in the mouse uncovers potential human breast cancer risk loci

Science.gov (United States)

Genetic background plays a dominant role in mammary gland development and breast cancer (BrCa). Despite this, the role of genetics is only partially understood. This study used strain-dependent variation in an inbred mouse mapping panel, to identify quantitative trait loci (QTL) underlying structura...

Multivariate analysis of quantitative traits can effectively classify rapeseed germplasm

Directory of Open Access Journals (Sweden)

Jankulovska Mirjana

2014-01-01

Full Text Available In this study, the use of different multivariate approaches to classify rapeseed genotypes based on quantitative traits has been presented. Tree regression analysis, PCA analysis and two-way cluster analysis were applied in order todescribe and understand the extent of genetic variability in spring rapeseed genotype by trait data. The traits which highly influenced seed and oil yield in rapeseed were successfully identified by the tree regression analysis. Principal predictor for both response variables was number of pods per plant (NP. NP and 1000 seed weight could help in the selection of high yielding genotypes. High values for both traits and oil content could lead to high oil yielding genotypes. These traits may serve as indirect selection criteria and can lead to improvement of seed and oil yield in rapeseed. Quantitative traits that explained most of the variability in the studied germplasm were classified using principal component analysis. In this data set, five PCs were identified, out of which the first three PCs explained 63% of the total variance. It helped in facilitating the choice of variables based on which the genotypes’ clustering could be performed. The two-way cluster analysissimultaneously clustered genotypes and quantitative traits. The final number of clusters was determined using bootstrapping technique. This approach provided clear overview on the variability of the analyzed genotypes. The genotypes that have similar performance regarding the traits included in this study can be easily detected on the heatmap. Genotypes grouped in the clusters 1 and 8 had high values for seed and oil yield, and relatively short vegetative growth duration period and those in cluster 9, combined moderate to low values for vegetative growth duration and moderate to high seed and oil yield. These genotypes should be further exploited and implemented in the rapeseed breeding program. The combined application of these multivariate methods

Genetic Analysis of Kernel Traits in Maize-Teosinte Introgression Populations

Directory of Open Access Journals (Sweden)

Zhengbin Liu

2016-08-01

Full Text Available Seed traits have been targeted by human selection during the domestication of crop species as a way to increase the caloric and nutritional content of food during the transition from hunter-gather to early farming societies. The primary seed trait under selection was likely seed size/weight as it is most directly related to overall grain yield. Additional seed traits involved in seed shape may have also contributed to larger grain. Maize (Zea mays ssp. mays kernel weight has increased more than 10-fold in the 9000 years since domestication from its wild ancestor, teosinte (Z. mays ssp. parviglumis. In order to study how size and shape affect kernel weight, we analyzed kernel morphometric traits in a set of 10 maize-teosinte introgression populations using digital imaging software. We identified quantitative trait loci (QTL for kernel area and length with moderate allelic effects that colocalize with kernel weight QTL. Several genomic regions with strong effects during maize domestication were detected, and a genetic framework for kernel traits was characterized by complex pleiotropic interactions. Our results both confirm prior reports of kernel domestication loci and identify previously uncharacterized QTL with a range of allelic effects, enabling future research into the genetic basis of these traits.

Effects of Bos taurus autosome 9-located quantitative trait loci haplotypes on enzymatic mastitis indicators of milk from dairy cows experimentally inoculated with Escherichia coli

DEFF Research Database (Denmark)

Sørensen, Lars Peter; Engberg, Ricarda Greuel; Løvendahl, Peter

2015-01-01

The aim of this study was to investigate the effect of a quantitative trait locus associated with mastitis caused by Escherichia coli, with one haplotype being more susceptible (HH) and another being more resistant (HL) to E. coli mastitis, on the activity of 4 inflammatory related milk enzymes....... In particular, we investigated the suitability of β-glucuronidase (GLU) as an early indicator of E. coli mastitis. Besides GLU, the enzymes l-lactate dehydrogenase (LDH), N-acetyl-β-d-glucosaminidase (NAGase), and alkaline phosphatase were included. The study was conducted in an experimental setup with 31...... Holstein cows divided into 4 groups representing repeated experiments and, within group, divided according to quantitative trait locus haplotype. All cows were inoculated with viable E. coli, and milk samples were collected 27 times from −6 to 396 h post-E. coli inoculation (PI). Activity of the 4 enzymes...

Variance Component Quantitative Trait Locus Analysis for Body Weight Traits in Purebred Korean Native Chicken

Directory of Open Access Journals (Sweden)

Muhammad Cahyadi

2016-01-01

Full Text Available Quantitative trait locus (QTL is a particular region of the genome containing one or more genes associated with economically important quantitative traits. This study was conducted to identify QTL regions for body weight and growth traits in purebred Korean native chicken (KNC. F1 samples (n = 595 were genotyped using 127 microsatellite markers and 8 single nucleotide polymorphisms that covered 2,616.1 centi Morgan (cM of map length for 26 autosomal linkage groups. Body weight traits were measured every 2 weeks from hatch to 20 weeks of age. Weight of half carcass was also collected together with growth rate. A multipoint variance component linkage approach was used to identify QTLs for the body weight traits. Two significant QTLs for growth were identified on chicken chromosome 3 (GGA3 for growth 16 to18 weeks (logarithm of the odds [LOD] = 3.24, Nominal p value = 0.0001 and GGA4 for growth 6 to 8 weeks (LOD = 2.88, Nominal p value = 0.0003. Additionally, one significant QTL and three suggestive QTLs were detected for body weight traits in KNC; significant QTL for body weight at 4 weeks (LOD = 2.52, nominal p value = 0.0007 and suggestive QTL for 8 weeks (LOD = 1.96, Nominal p value = 0.0027 were detected on GGA4; QTLs were also detected for two different body weight traits: body weight at 16 weeks on GGA3 and body weight at 18 weeks on GGA19. Additionally, two suggestive QTLs for carcass weight were detected at 0 and 70 cM on GGA19. In conclusion, the current study identified several significant and suggestive QTLs that affect growth related traits in a unique resource pedigree in purebred KNC. This information will contribute to improving the body weight traits in native chicken breeds, especially for the Asian native chicken breeds.

Cracking anxiety in the mouse : a quantitative (epi)genetic approach

NARCIS (Netherlands)

Labots, M.

2017-01-01

The aim of this thesis was to improve existing methodologies and apply genetic strategies in order to identify (main-effect, epistatic, multiple and pleiotropic) quantitative trait loci and to decipher functional candidate genes for anxiety-related behavior and baseline blood plasma total

Mapping quantitative trait loci in plant breeding populations : Use of parental haplotype sharing

NARCIS (Netherlands)

Jansen, Ritsert C.; Jannink, Jean-Luc; Beavis, William D.

2003-01-01

Applied breeding programs evaluate large numbers of progeny derived from multiple related crosses for a wide range of agronomic traits and for tens to hundreds of molecular markers. This study was conducted to determine how these phenotypic and genetic data could be used for routinely mapping

Meta-analysis identifies 29 additional ulcerative colitis risk loci, increasing the number of confirmed associations to 47

DEFF Research Database (Denmark)

Anderson, Carl A; Boucher, Gabrielle; Lees, Charlie W

2011-01-01

Genome-wide association studies and candidate gene studies in ulcerative colitis have identified 18 susceptibility loci. We conducted a meta-analysis of six ulcerative colitis genome-wide association study datasets, comprising 6,687 cases and 19,718 controls, and followed up the top association...... signals in 9,628 cases and 12,917 controls. We identified 29 additional risk loci (P associated loci to 47. After annotating associated regions using GRAIL, expression quantitative trait loci data and correlations with non-synonymous SNPs, we...... identified many candidate genes that provide potentially important insights into disease pathogenesis, including IL1R2, IL8RA-IL8RB, IL7R, IL12B, DAP, PRDM1, JAK2, IRF5, GNA12 and LSP1. The total number of confirmed inflammatory bowel disease risk loci is now 99, including a minimum of 28 shared association...

CNV-association meta-analysis in 191,161 European adults reveals new loci associated with anthropometric traits

DEFF Research Database (Denmark)

Macé, Aurélien; Tuke, Marcus A; Deelen, Patrick

2017-01-01

at 1q21.1, 3q29, 7q11.23, 11p14.2, and 18q21.32 and confirms two known loci at 16p11.2 and 22q11.21, implicating at least one anthropometric trait. The discovered CNVs are recurrent and rare (0.01-0.2%), with large effects on height (>2.4 cm), weight (>5 kg), and body mass index (BMI) (>3.5 kg/m(2...

An improved procedure of mapping a quantitative trait locus via the ...

Indian Academy of Sciences (India)

Data on the quantitative trait under consideration and several codominant genetic markers with known genomic locations are collected from members of families and statistically .... Although the primary aim is to estimate , since the trait.

A Simple Test of Class-Level Genetic Association Can Reveal Novel Cardiometabolic Trait Loci.

Directory of Open Access Journals (Sweden)

Jing Qian

Full Text Available Characterizing the genetic determinants of complex diseases can be further augmented by incorporating knowledge of underlying structure or classifications of the genome, such as newly developed mappings of protein-coding genes, epigenetic marks, enhancer elements and non-coding RNAs.We apply a simple class-level testing framework, termed Genetic Class Association Testing (GenCAT, to identify protein-coding gene association with 14 cardiometabolic (CMD related traits across 6 publicly available genome wide association (GWA meta-analysis data resources. GenCAT uses SNP-level meta-analysis test statistics across all SNPs within a class of elements, as well as the size of the class and its unique correlation structure, to determine if the class is statistically meaningful. The novelty of findings is evaluated through investigation of regional signals. A subset of findings are validated using recently updated, larger meta-analysis resources. A simulation study is presented to characterize overall performance with respect to power, control of family-wise error and computational efficiency. All analysis is performed using the GenCAT package, R version 3.2.1.We demonstrate that class-level testing complements the common first stage minP approach that involves individual SNP-level testing followed by post-hoc ascribing of statistically significant SNPs to genes and loci. GenCAT suggests 54 protein-coding genes at 41 distinct loci for the 13 CMD traits investigated in the discovery analysis, that are beyond the discoveries of minP alone. An additional application to biological pathways demonstrates flexibility in defining genetic classes.We conclude that it would be prudent to include class-level testing as standard practice in GWA analysis. GenCAT, for example, can be used as a simple, complementary and efficient strategy for class-level testing that leverages existing data resources, requires only summary level data in the form of test statistics, and

Genetic susceptibility to obesity and related traits in childhood and adolescence

DEFF Research Database (Denmark)

den Hoed, Marcel; Ekelund, Ulf; Brage, Søren

2010-01-01

Large-scale genome-wide association (GWA) studies have thus far identified 16 loci incontrovertibly associated with obesity-related traits in adults. We examined associations of variants in these loci with anthropometric traits in children and adolescents.......Large-scale genome-wide association (GWA) studies have thus far identified 16 loci incontrovertibly associated with obesity-related traits in adults. We examined associations of variants in these loci with anthropometric traits in children and adolescents....

Multi-ethnic fine-mapping of 14 central adiposity loci

NARCIS (Netherlands)

Liu, C.T.; Buchkovich, M.L.; Winkler, T.W.; Heid, I.M.; Hottenga, J.J.; Boomsma, D.I.; de Geus, E.J.C.; Willemsen, G.; Borecki, I.B.; Fox, C.S.; Mohlke, K.L.; North, K.E.; Cupples, L.A.

2014-01-01

The Genetic Investigation of Anthropometric Traits (GIANT) consortium identified 14 loci in European Ancestry (EA) individuals associated with waist-to-hip ratio (WHR) adjusted for body mass index. These loci are wide and narrowingthe signalsremains necessary. Twelve of 14 loci identified inGIANTEA

Joint analysis of binary and quantitative traits with data sharing and outcome-dependent sampling.

Science.gov (United States)

Zheng, Gang; Wu, Colin O; Kwak, Minjung; Jiang, Wenhua; Joo, Jungnam; Lima, Joao A C

2012-04-01

We study the analysis of a joint association between a genetic marker with both binary (case-control) and quantitative (continuous) traits, where the quantitative trait values are only available for the cases due to data sharing and outcome-dependent sampling. Data sharing becomes common in genetic association studies, and the outcome-dependent sampling is the consequence of data sharing, under which a phenotype of interest is not measured for some subgroup. The trend test (or Pearson's test) and F-test are often, respectively, used to analyze the binary and quantitative traits. Because of the outcome-dependent sampling, the usual F-test can be applied using the subgroup with the observed quantitative traits. We propose a modified F-test by also incorporating the genotype frequencies of the subgroup whose traits are not observed. Further, a combination of this modified F-test and Pearson's test is proposed by Fisher's combination of their P-values as a joint analysis. Because of the correlation of the two analyses, we propose to use a Gamma (scaled chi-squared) distribution to fit the asymptotic null distribution for the joint analysis. The proposed modified F-test and the joint analysis can also be applied to test single trait association (either binary or quantitative trait). Through simulations, we identify the situations under which the proposed tests are more powerful than the existing ones. Application to a real dataset of rheumatoid arthritis is presented. © 2012 Wiley Periodicals, Inc.

Construction of a dense genetic linkage map and mapping quantitative trait loci for economic traits of a doubled haploid population of Pyropia haitanensis (Bangiales, Rhodophyta).

Science.gov (United States)

Xu, Yan; Huang, Long; Ji, Dehua; Chen, Changsheng; Zheng, Hongkun; Xie, Chaotian

2015-09-21

Pyropia haitanensis is one of the most economically important mariculture crops in China. A high-density genetic map has not been published yet and quantitative trait locus (QTL) mapping has not been undertaken for P. haitanensis because of a lack of sufficient molecular markers. Specific length amplified fragment sequencing (SLAF-seq) was developed recently for large-scale, high resolution de novo marker discovery and genotyping. In this study, SLAF-seq was used to obtain mass length polymorphic markers to construct a high-density genetic map for P. haitanensis. In total, 120.33 Gb of data containing 75.21 M pair-end reads was obtained after sequencing. The average coverage for each SLAF marker was 75.50-fold in the male parent, 74.02-fold in the female parent, and 6.14-fold average in each double haploid individual. In total, 188,982 SLAFs were detected, of which 6731 were length polymorphic SLAFs that could be used to construct a genetic map. The final map included 4550 length polymorphic markers that were combined into 740 bins on five linkage groups, with a length of 874.33 cM and an average distance of 1.18 cM between adjacent bins. This map was used for QTL mapping to identify chromosomal regions associated with six economically important traits: frond length, width, thickness, fresh weight, growth rates of frond length and growth rates of fresh weight. Fifteen QTLs were identified for these traits. The value of phenotypic variance explained by an individual QTL ranged from 9.59 to 16.61 %, and the confidence interval of each QTL ranged from 0.97 cM to 16.51 cM. The first high-density genetic linkage map for P. haitanensis was constructed, and fifteen QTLs associated with six economically important traits were identified. The results of this study not only provide a platform for gene and QTL fine mapping, map-based gene isolation, and molecular breeding for P. haitanensis, but will also serve as a reference for positioning sequence scaffolds on a physical

Comparative Mapping of Seed Dormancy Loci Between Tropical and Temperate Ecotypes of Weedy Rice (Oryza sativa L.

Directory of Open Access Journals (Sweden)

Lihua Zhang

2017-08-01

Full Text Available Genotypic variation at multiple loci for seed dormancy (SD contributes to plant adaptation to diverse ecosystems. Weedy rice (Oryza sativa was used as a model to address the similarity of SD genes between distinct ecotypes. A total of 12 quantitative trait loci (QTL for SD were identified in one primary and two advanced backcross (BC populations derived from a temperate ecotype of weedy rice (34.3°N Lat.. Nine (75% of the 12 loci were mapped to the same positions as those identified from a tropical ecotype of weedy rice (7.1°N Lat.. The high similarity suggested that the majority of SD genes were conserved during the ecotype differentiation. These common loci are largely those collocated/linked with the awn, hull color, pericarp color, or plant height loci. Phenotypic correlations observed in the populations support the notion that indirect selections for the wild-type morphological characteristics, together with direct selections for germination time, were major factors influencing allelic distributions of SD genes across ecotypes. Indirect selections for crop-mimic traits (e.g., plant height and flowering time could also alter allelic frequencies for some SD genes in agroecosystems. In addition, 3 of the 12 loci were collocated with segregation distortion loci, indicating that some gametophyte development genes could also influence the genetic equilibria of SD loci in hybrid populations. The SD genes with a major effect on germination across ecotypes could be used as silencing targets to develop transgene mitigation (TM strategies to reduce the risk of gene flow from genetically modified crops into weed/wild relatives.

Quantitative Trait Loci Mapping of Western Corn Rootworm (Coleoptera: Chrysomelidae) Host Plant Resistance in Two Populations of Doubled Haploid Lines in Maize (Zea mays L.).

Science.gov (United States)

Bohn, Martin O; Marroquin, Juan J; Flint-Garcia, Sherry; Dashiell, Kenton; Willmot, David B; Hibbard, Bruce E

2018-02-09

Over the last 70 yr, more than 12,000 maize accessions have been screened for their level of resistance to western corn rootworm, Diabrotica virgifera virgifera (LeConte; Coleoptera: Chrysomelidae), larval feeding. Less than 1% of this germplasm was selected for initiating recurrent selection or other breeding programs. Selected genotypes were mostly characterized by large root systems and superior root regrowth after root damage caused by western corn rootworm larvae. However, no hybrids claiming native (i.e., host plant) resistance to western corn rootworm larval feeding are currently commercially available. We investigated the genetic basis of western corn rootworm resistance in maize materials with improved levels of resistance using linkage disequilibrium mapping approaches. Two populations of topcrossed doubled haploid maize lines (DHLs) derived from crosses between resistant and susceptible maize lines were evaluated for their level of resistance in three to four different environments. For each DHL topcross an average root damage score was estimated and used for quantitative trait loci (QTL) analysis. We found genomic regions contributing to western corn rootworm resistance on all maize chromosomes, except for chromosome 4. Models fitting all QTL simultaneously explained about 30 to 50% of the genotypic variance for root damage scores in both mapping populations. Our findings confirm the complex genetic structure of host plant resistance against western corn rootworm larval feeding in maize. Interestingly, three of these QTL regions also carry genes involved in ascorbate biosynthesis, a key compound we hypothesize is involved in the expression of western corn rootworm resistance. © The Author(s) 2017. Published by Oxford University Press on behalf of Entomological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes

Science.gov (United States)

McKay, James D.; Hung, Rayjean J.; Han, Younghun; Zong, Xuchen; Carreras-Torres, Robert; Christiani, David C.; Caporaso, Neil E.; Johansson, Mattias; Xiao, Xiangjun; Li, Yafang; Byun, Jinyoung; Dunning, Alison; Pooley, Karen A.; Qian, David C.; Ji, Xuemei; Liu, Geoffrey; Timofeeva, Maria N.; Bojesen, Stig E.; Wu, Xifeng; Le Marchand, Loic; Albanes, Demetrios; Bickeböller, Heike; Aldrich, Melinda C.; Bush, William S.; Tardon, Adonina; Rennert, Gad; Teare, M. Dawn; Field, John K.; Kiemeney, Lambertus A.; Lazarus, Philip; Haugen, Aage; Lam, Stephen; Schabath, Matthew B.; Andrew, Angeline S.; Shen, Hongbing; Hong, Yun-Chul; Yuan, Jian-Min; Bertazzi, Pier Alberto; Pesatori, Angela C.; Ye, Yuanqing; Diao, Nancy; Su, Li; Zhang, Ruyang; Brhane, Yonathan; Leighl, Natasha; Johansen, Jakob S.; Mellemgaard, Anders; Saliba, Walid; Haiman, Christopher A.; Wilkens, Lynne R.; Fernandez-Somoano, Ana; Fernandez-Tardon, Guillermo; van der Heijden, Henricus F.M.; Kim, Jin Hee; Dai, Juncheng; Hu, Zhibin; Davies, Michael PA; Marcus, Michael W.; Brunnström, Hans; Manjer, Jonas; Melander, Olle; Muller, David C.; Overvad, Kim; Trichopoulou, Antonia; Tumino, Rosario; Doherty, Jennifer A.; Barnett, Matt P.; Chen, Chu; Goodman, Gary E.; Cox, Angela; Taylor, Fiona; Woll, Penella; Brüske, Irene; Wichmann, H.-Erich; Manz, Judith; Muley, Thomas R.; Risch, Angela; Rosenberger, Albert; Grankvist, Kjell; Johansson, Mikael; Shepherd, Frances A.; Tsao, Ming-Sound; Arnold, Susanne M.; Haura, Eric B.; Bolca, Ciprian; Holcatova, Ivana; Janout, Vladimir; Kontic, Milica; Lissowska, Jolanta; Mukeria, Anush; Ognjanovic, Simona; Orlowski, Tadeusz M.; Scelo, Ghislaine; Swiatkowska, Beata; Zaridze, David; Bakke, Per; Skaug, Vidar; Zienolddiny, Shanbeh; Duell, Eric J.; Butler, Lesley M.; Koh, Woon-Puay; Gao, Yu-Tang; Houlston, Richard S.; McLaughlin, John; Stevens, Victoria L.; Joubert, Philippe; Lamontagne, Maxime; Nickle, David C.; Obeidat, Ma’en; Timens, Wim; Zhu, Bin; Song, Lei; Kachuri, Linda; Artigas, María Soler; Tobin, Martin D.; Wain, Louise V.; Rafnar, Thorunn; Thorgeirsson, Thorgeir E.; Reginsson, Gunnar W.; Stefansson, Kari; Hancock, Dana B.; Bierut, Laura J.; Spitz, Margaret R.; Gaddis, Nathan C.; Lutz, Sharon M.; Gu, Fangyi; Johnson, Eric O.; Kamal, Ahsan; Pikielny, Claudio; Zhu, Dakai; Lindströem, Sara; Jiang, Xia; Tyndale, Rachel F.; Chenevix-Trench, Georgia; Beesley, Jonathan; Bossé, Yohan; Chanock, Stephen; Brennan, Paul; Landi, Maria Teresa; Amos, Christopher I.

2017-01-01

Summary While several lung cancer susceptibility loci have been identified, much of lung cancer heritability remains unexplained. Here, 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated GWAS analysis of lung cancer on 29,266 patients and 56,450 controls. We identified 18 susceptibility loci achieving genome wide significance, including 10 novel loci. The novel loci highlighted the striking heterogeneity in genetic susceptibility across lung cancer histological subtypes, with four loci associated with lung cancer overall and six with lung adenocarcinoma. Gene expression quantitative trait analysis (eQTL) in 1,425 normal lung tissues highlighted RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes, OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer. PMID:28604730

Sex-stratified Genome-wide Association Studies Including 270,000 Individuals Show Sexual Dimorphism in Genetic Loci for Anthropometric Traits

Science.gov (United States)

Jackson, Anne U.; Monda, Keri L.; Kilpeläinen, Tuomas O.; Esko, Tõnu; Mägi, Reedik; Li, Shengxu; Workalemahu, Tsegaselassie; Feitosa, Mary F.; Croteau-Chonka, Damien C.; Day, Felix R.; Fall, Tove; Ferreira, Teresa; Gustafsson, Stefan; Locke, Adam E.; Mathieson, Iain; Scherag, Andre; Vedantam, Sailaja; Wood, Andrew R.; Liang, Liming; Steinthorsdottir, Valgerdur; Thorleifsson, Gudmar; Dermitzakis, Emmanouil T.; Dimas, Antigone S.; Karpe, Fredrik; Min, Josine L.; Nicholson, George; Clegg, Deborah J.; Person, Thomas; Krohn, Jon P.; Bauer, Sabrina; Buechler, Christa; Eisinger, Kristina; Bonnefond, Amélie; Froguel, Philippe; Hottenga, Jouke-Jan; Prokopenko, Inga; Waite, Lindsay L.; Harris, Tamara B.; Smith, Albert Vernon; Shuldiner, Alan R.; McArdle, Wendy L.; Caulfield, Mark J.; Munroe, Patricia B.; Grönberg, Henrik; Chen, Yii-Der Ida; Li, Guo; Beckmann, Jacques S.; Johnson, Toby; Thorsteinsdottir, Unnur; Teder-Laving, Maris; Khaw, Kay-Tee; Wareham, Nicholas J.; Zhao, Jing Hua; Amin, Najaf; Oostra, Ben A.; Kraja, Aldi T.; Province, Michael A.; Cupples, L. Adrienne; Heard-Costa, Nancy L.; Kaprio, Jaakko; Ripatti, Samuli; Surakka, Ida; Collins, Francis S.; Saramies, Jouko; Tuomilehto, Jaakko; Jula, Antti; Salomaa, Veikko; Erdmann, Jeanette; Hengstenberg, Christian; Loley, Christina; Schunkert, Heribert; Lamina, Claudia; Wichmann, H. Erich; Albrecht, Eva; Gieger, Christian; Hicks, Andrew A.; Johansson, Åsa; Pramstaller, Peter P.; Kathiresan, Sekar; Speliotes, Elizabeth K.; Penninx, Brenda; Hartikainen, Anna-Liisa; Jarvelin, Marjo-Riitta; Gyllensten, Ulf; Boomsma, Dorret I.; Campbell, Harry; Wilson, James F.; Chanock, Stephen J.; Farrall, Martin; Goel, Anuj; Medina-Gomez, Carolina; Rivadeneira, Fernando; Estrada, Karol; Uitterlinden, André G.; Hofman, Albert; Zillikens, M. Carola; den Heijer, Martin; Kiemeney, Lambertus A.; Maschio, Andrea; Hall, Per; Tyrer, Jonathan; Teumer, Alexander; Völzke, Henry; Kovacs, Peter; Tönjes, Anke; Mangino, Massimo; Spector, Tim D.; Hayward, Caroline; Rudan, Igor; Hall, Alistair S.; Samani, Nilesh J.; Attwood, Antony Paul; Sambrook, Jennifer G.; Hung, Joseph; Palmer, Lyle J.; Lokki, Marja-Liisa; Sinisalo, Juha; Boucher, Gabrielle; Huikuri, Heikki; Lorentzon, Mattias; Ohlsson, Claes; Eklund, Niina; Eriksson, Johan G.; Barlassina, Cristina; Rivolta, Carlo; Nolte, Ilja M.; Snieder, Harold; Van der Klauw, Melanie M.; Van Vliet-Ostaptchouk, Jana V.; Gejman, Pablo V.; Shi, Jianxin; Jacobs, Kevin B.; Wang, Zhaoming; Bakker, Stephan J. L.; Mateo Leach, Irene; Navis, Gerjan; van der Harst, Pim; Martin, Nicholas G.; Medland, Sarah E.; Montgomery, Grant W.; Yang, Jian; Chasman, Daniel I.; Ridker, Paul M.; Rose, Lynda M.; Lehtimäki, Terho; Raitakari, Olli; Absher, Devin; Iribarren, Carlos; Basart, Hanneke; Hovingh, Kees G.; Hyppönen, Elina; Power, Chris; Anderson, Denise; Beilby, John P.; Hui, Jennie; Jolley, Jennifer; Sager, Hendrik; Bornstein, Stefan R.; Schwarz, Peter E. H.; Kristiansson, Kati; Perola, Markus; Lindström, Jaana; Swift, Amy J.; Uusitupa, Matti; Atalay, Mustafa; Lakka, Timo A.; Rauramaa, Rainer; Bolton, Jennifer L.; Fowkes, Gerry; Fraser, Ross M.; Price, Jackie F.; Fischer, Krista; KrjutÅ¡kov, Kaarel; Metspalu, Andres; Mihailov, Evelin; Langenberg, Claudia; Luan, Jian'an; Ong, Ken K.; Chines, Peter S.; Keinanen-Kiukaanniemi, Sirkka M.; Saaristo, Timo E.; Edkins, Sarah; Franks, Paul W.; Hallmans, Göran; Shungin, Dmitry; Morris, Andrew David; Palmer, Colin N. A.; Erbel, Raimund; Moebus, Susanne; Nöthen, Markus M.; Pechlivanis, Sonali; Hveem, Kristian; Narisu, Narisu; Hamsten, Anders; Humphries, Steve E.; Strawbridge, Rona J.; Tremoli, Elena; Grallert, Harald; Thorand, Barbara; Illig, Thomas; Koenig, Wolfgang; Müller-Nurasyid, Martina; Peters, Annette; Boehm, Bernhard O.; Kleber, Marcus E.; März, Winfried; Winkelmann, Bernhard R.; Kuusisto, Johanna; Laakso, Markku; Arveiler, Dominique; Cesana, Giancarlo; Kuulasmaa, Kari; Virtamo, Jarmo; Yarnell, John W. G.; Kuh, Diana; Wong, Andrew; Lind, Lars; de Faire, Ulf; Gigante, Bruna; Magnusson, Patrik K. E.; Pedersen, Nancy L.; Dedoussis, George; Dimitriou, Maria; Kolovou, Genovefa; Kanoni, Stavroula; Stirrups, Kathleen; Bonnycastle, Lori L.; Njølstad, Inger; Wilsgaard, Tom; Ganna, Andrea; Rehnberg, Emil; Hingorani, Aroon; Kivimaki, Mika; Kumari, Meena; Assimes, Themistocles L.; Barroso, Inês; Boehnke, Michael; Borecki, Ingrid B.; Deloukas, Panos; Fox, Caroline S.; Frayling, Timothy; Groop, Leif C.; Haritunians, Talin; Hunter, David; Ingelsson, Erik; Kaplan, Robert; Mohlke, Karen L.; O'Connell, Jeffrey R.; Schlessinger, David; Strachan, David P.; Stefansson, Kari; van Duijn, Cornelia M.; Abecasis, Gonçalo R.; McCarthy, Mark I.; Hirschhorn, Joel N.; Qi, Lu; Loos, Ruth J. F.; Lindgren, Cecilia M.; North, Kari E.; Heid, Iris M.

2013-01-01

Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10−8), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits. PMID:23754948

Sex-stratified genome-wide association studies including 270,000 individuals show sexual dimorphism in genetic loci for anthropometric traits.

Directory of Open Access Journals (Sweden)

Joshua C Randall

2013-06-01

Full Text Available Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals and took forward 348 SNPs into follow-up (additional 137,052 individuals in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%, including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9 and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG, all of which were genome-wide significant in women (P<5×10(-8, but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.

Association and Genetic Identification of Loci for Four Fruit Traits in Tomato Using InDel Markers

Directory of Open Access Journals (Sweden)

Xiaoxi Liu

2017-07-01

Full Text Available Tomato (Solanum lycopersicum fruit weight (FW, soluble solid content (SSC, fruit shape and fruit color are crucial for yield, quality and consumer acceptability. In this study, a 192 accessions tomato association panel comprising a mixture of wild species, cherry tomato, landraces, and modern varieties collected worldwide was genotyped with 547 InDel markers evenly distributed on 12 chromosomes and scored for FW, SSC, fruit shape index (FSI, and color parameters over 2 years with three replications each year. The association panel was sorted into two subpopulations. Linkage disequilibrium ranged from 3.0 to 47.2 Mb across 12 chromosomes. A set of 102 markers significantly (p < 1.19–1.30 × 10−4 associated with SSC, FW, fruit shape, and fruit color was identified on 11 of the 12 chromosomes using a mixed linear model. The associations were compared with the known gene/QTLs for the same traits. Genetic analysis using F2 populations detected 14 and 4 markers significantly (p < 0.05 associated with SSC and FW, respectively. Some loci were commonly detected by both association and linkage analysis. Particularly, one novel locus for FW on chromosome 4 detected by association analysis was also identified in F2 populations. The results demonstrated that association mapping using limited number of InDel markers and a relatively small population could not only complement and enhance previous QTL information, but also identify novel loci for marker-assisted selection of fruit traits in tomato.

Effect of small mapping population sizes on reliability of quantitative ...

African Journals Online (AJOL)

A limitation of quantitative trait loci (QTL) mapping is that accuracy of determining QTL position and effects are largely determined by population size. Despite the importance of this concept, known as the "Beavis effect there has generally been a lack of understanding by molecular geneticists and breeders. One possible ...

Identification of QTLs for grain yield and grain-related traits of maize (Zea mays L.) using an AFLP-map, different testers, and cofactor analysis

NARCIS (Netherlands)

Ajimone Marsan, P.; Gorni, C.; Chitto, A.; Redaelli, R.; Vijk, van R.; Stam, P.; Motto, M.

2001-01-01

Abstract We exploited the AFLP?1(AFLP? is a registered trademark of Keygene, N.V.) technique to map and characterise quantitative trait loci (QTLs) for grain yield and two grain-related traits of a maize segregating population. Two maize elite inbred lines were crossed to produce 229 F2 individuals

Large-scale association analysis identifies new lung cancer susceptibility loci and heterogeneity in genetic susceptibility across histological subtypes.

Science.gov (United States)

McKay, James D; Hung, Rayjean J; Han, Younghun; Zong, Xuchen; Carreras-Torres, Robert; Christiani, David C; Caporaso, Neil E; Johansson, Mattias; Xiao, Xiangjun; Li, Yafang; Byun, Jinyoung; Dunning, Alison; Pooley, Karen A; Qian, David C; Ji, Xuemei; Liu, Geoffrey; Timofeeva, Maria N; Bojesen, Stig E; Wu, Xifeng; Le Marchand, Loic; Albanes, Demetrios; Bickeböller, Heike; Aldrich, Melinda C; Bush, William S; Tardon, Adonina; Rennert, Gad; Teare, M Dawn; Field, John K; Kiemeney, Lambertus A; Lazarus, Philip; Haugen, Aage; Lam, Stephen; Schabath, Matthew B; Andrew, Angeline S; Shen, Hongbing; Hong, Yun-Chul; Yuan, Jian-Min; Bertazzi, Pier Alberto; Pesatori, Angela C; Ye, Yuanqing; Diao, Nancy; Su, Li; Zhang, Ruyang; Brhane, Yonathan; Leighl, Natasha; Johansen, Jakob S; Mellemgaard, Anders; Saliba, Walid; Haiman, Christopher A; Wilkens, Lynne R; Fernandez-Somoano, Ana; Fernandez-Tardon, Guillermo; van der Heijden, Henricus F M; Kim, Jin Hee; Dai, Juncheng; Hu, Zhibin; Davies, Michael P A; Marcus, Michael W; Brunnström, Hans; Manjer, Jonas; Melander, Olle; Muller, David C; Overvad, Kim; Trichopoulou, Antonia; Tumino, Rosario; Doherty, Jennifer A; Barnett, Matt P; Chen, Chu; Goodman, Gary E; Cox, Angela; Taylor, Fiona; Woll, Penella; Brüske, Irene; Wichmann, H-Erich; Manz, Judith; Muley, Thomas R; Risch, Angela; Rosenberger, Albert; Grankvist, Kjell; Johansson, Mikael; Shepherd, Frances A; Tsao, Ming-Sound; Arnold, Susanne M; Haura, Eric B; Bolca, Ciprian; Holcatova, Ivana; Janout, Vladimir; Kontic, Milica; Lissowska, Jolanta; Mukeria, Anush; Ognjanovic, Simona; Orlowski, Tadeusz M; Scelo, Ghislaine; Swiatkowska, Beata; Zaridze, David; Bakke, Per; Skaug, Vidar; Zienolddiny, Shanbeh; Duell, Eric J; Butler, Lesley M; Koh, Woon-Puay; Gao, Yu-Tang; Houlston, Richard S; McLaughlin, John; Stevens, Victoria L; Joubert, Philippe; Lamontagne, Maxime; Nickle, David C; Obeidat, Ma'en; Timens, Wim; Zhu, Bin; Song, Lei; Kachuri, Linda; Artigas, María Soler; Tobin, Martin D; Wain, Louise V; Rafnar, Thorunn; Thorgeirsson, Thorgeir E; Reginsson, Gunnar W; Stefansson, Kari; Hancock, Dana B; Bierut, Laura J; Spitz, Margaret R; Gaddis, Nathan C; Lutz, Sharon M; Gu, Fangyi; Johnson, Eric O; Kamal, Ahsan; Pikielny, Claudio; Zhu, Dakai; Lindströem, Sara; Jiang, Xia; Tyndale, Rachel F; Chenevix-Trench, Georgia; Beesley, Jonathan; Bossé, Yohan; Chanock, Stephen; Brennan, Paul; Landi, Maria Teresa; Amos, Christopher I

2017-07-01

Although several lung cancer susceptibility loci have been identified, much of the heritability for lung cancer remains unexplained. Here 14,803 cases and 12,262 controls of European descent were genotyped on the OncoArray and combined with existing data for an aggregated genome-wide association study (GWAS) analysis of lung cancer in 29,266 cases and 56,450 controls. We identified 18 susceptibility loci achieving genome-wide significance, including 10 new loci. The new loci highlight the striking heterogeneity in genetic susceptibility across the histological subtypes of lung cancer, with four loci associated with lung cancer overall and six loci associated with lung adenocarcinoma. Gene expression quantitative trait locus (eQTL) analysis in 1,425 normal lung tissue samples highlights RNASET2, SECISBP2L and NRG1 as candidate genes. Other loci include genes such as a cholinergic nicotinic receptor, CHRNA2, and the telomere-related genes OFBC1 and RTEL1. Further exploration of the target genes will continue to provide new insights into the etiology of lung cancer.

Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals.

OpenAIRE

Dastani, Z.; Hivert, M. F.; Timpson, N.; Perry, J. R.; Yuan, X.; Scott, R. A.; Henneman, P.; Heid, I. M.; Kizer, J. R.; Lyytikäinen, L. P.; Fuchsberger, C.; Tanaka, T.; Morris, A. P.; Small, K.; Isaacs, A.

2012-01-01

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a...

Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals.

OpenAIRE

Dastani, Zari; Hivert, Marie-France; Timpson, Nicholas; Perry, John Richard; Yuan, Xin; Scott, Robert; Henneman, Peter; Heid, Iris M; Kizer, Jorge R; Lyytikäinen, Leo-Pekka; Fuchsberger, Christian; Tanaka, Toshiko; Morris, Andrew P; Small, Kerrin; Isaacs, Aaron

2012-01-01

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = \\(4.5×10^{−8}–1.2×10^{−43}\\)). U...

Genetics of Obesity Traits: A Bivariate Genome-Wide Association Analysis

DEFF Research Database (Denmark)

Wu, Yili; Duan, Haiping; Tian, Xiaocao

2018-01-01

Previous genome-wide association studies on anthropometric measurements have identified more than 100 related loci, but only a small portion of heritability in obesity was explained. Here we present a bivariate twin study to look for the genetic variants associated with body mass index and waist......-hip ratio, and to explore the obesity-related pathways in Northern Han Chinese. Cholesky decompositionmodel for 242monozygotic and 140 dizygotic twin pairs indicated a moderate genetic correlation (r = 0.53, 95%CI: 0.42–0.64) between body mass index and waist-hip ratio. Bivariate genome-wide association.......05. Expression quantitative trait loci analysis identified rs2242044 as a significant cis-eQTL in both the normal adipose-subcutaneous (P = 1.7 × 10−9) and adipose-visceral (P = 4.4 × 10−15) tissue. These findings may provide an important entry point to unravel genetic pleiotropy in obesity traits....

Isolation and Manipulation of Quantitative Tra it Loci for DIsease Resistance in Rice Using a Candid ate Gene Approach

Institute of Scientific and Technical Information of China (English)

Ke-Ming Hu; De-Yun Qiu; Xiang-Ling Shen; Xiang-Hua Li; Shi-Ping Wang

2008-01-01

Bacterial blight caused by Xanthomonas oryzae pv.oryzae and fungal blast caused by Magnaporthe grisea result in heavy production losses in rice,a main staple food for approximately 50%of the world's population.Application of host resistance to these pathogens iS the most economical and environment-friendly approach to solve this problem.Quantitative trait loci(QTLs)controlling quantitative resistance are valuable sources for broad.spectrum and durable disease resistance.Although large numbers of QTLs for bacteriaI blight and blast resistance have been identified.these sources have not been used effectively in rice improvement because of the complex genetic controI of quantitative resistance and because the genes underlying resistance QTLs are unknown.To isolate disease resistance QTLs,we established a candidate gene strategy that integrates linkage map,expression profile,and functionaI complementation analyses.This strategy has proven to be applicable for identifying the genes underlying minor resistance QTLs in rice-Xoo and rice-M grisea systems and it may also help to shed light on disease resistance QTLs of other cereals.Our results also suggest that a single minor QTL can be used in rice improvement by modulating the expression of the gene underlying the QTL.Pyramiding two or three minor QTL genes,whose expression can be managed and that function in different defense signaI transduction pathways,may allow the breeding of rice cultivars that are highly resistant to bacteriaI blight and blast.

Genetic architecture of complex traits and accuracy of genomic prediction: coat colour, milk-fat percentage, and type in Holstein cattle as contrasting model traits.

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Ben J Hayes

2010-09-01

Full Text Available Prediction of genetic merit using dense SNP genotypes can be used for estimation of breeding values for selection of livestock, crops, and forage species; for prediction of disease risk; and for forensics. The accuracy of these genomic predictions depends in part on the genetic architecture of the trait, in particular number of loci affecting the trait and distribution of their effects. Here we investigate the difference among three traits in distribution of effects and the consequences for the accuracy of genomic predictions. Proportion of black coat colour in Holstein cattle was used as one model complex trait. Three loci, KIT, MITF, and a locus on chromosome 8, together explain 24% of the variation of proportion of black. However, a surprisingly large number of loci of small effect are necessary to capture the remaining variation. A second trait, fat concentration in milk, had one locus of large effect and a host of loci with very small effects. Both these distributions of effects were in contrast to that for a third trait, an index of scores for a number of aspects of cow confirmation ("overall type", which had only loci of small effect. The differences in distribution of effects among the three traits were quantified by estimating the distribution of variance explained by chromosome segments containing 50 SNPs. This approach was taken to account for the imperfect linkage disequilibrium between the SNPs and the QTL affecting the traits. We also show that the accuracy of predicting genetic values is higher for traits with a proportion of large effects (proportion black and fat percentage than for a trait with no loci of large effect (overall type, provided the method of analysis takes advantage of the distribution of loci effects.

QTLs for seedling traits under salinity stress in hexaploid wheat

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Yongzhe Ren

2018-03-01

Full Text Available ABSTRACT: Soil salinity limits agricultural production and is a major obstacle for increasing crop yield. Common wheat is one of the most important crops with allohexaploid characteristic and a highly complex genome. QTL mapping is a useful way to identify genes for quantitative traits such as salinity tolerance in hexaploid wheat. In the present study, a hydroponic trial was carried out to identify quantitative trait loci (QTLs associated with salinity tolerance of wheat under 150mM NaCl concentration using a recombinant inbred line population (Xiaoyan 54×Jing 411. Values of wheat seedling traits including maximum root length (MRL, root dry weight (RDW, shoot dry weight (SDW, total dry weight (TDW and the ratio of TDW of wheat plants between salt stress and control (TDWR were evaluated or calculated. A total of 19QTLs for five traits were detected through composite interval mapping method by using QTL Cartographer version 2.5 under normal and salt stress conditions. These QTLs distributed on 12 chromosomes explained the percentage of phenotypic variation by individual QTL varying from 7.9% to 19.0%. Among them, 11 and six QTLs were detected under normal and salt stress conditions, respectively and two QTLs were detected for TDWR. Some salt tolerance related loci may be pleiotropic. Chromosome 1A, 3A and 7A may harbor crucial candidate genes associated with wheat salt tolerance. Our results would be helpful for the marker assisted selection to breed wheat varieties with improved salt tolerance.

Principal Component Analysis of Some Quantitative and Qualitative Traits in Iranian Spinach Landraces

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Mohebodini Mehdi

2017-08-01

Full Text Available Landraces of spinach in Iran have not been sufficiently characterised for their morpho-agronomic traits. Such characterisation would be helpful in the development of new genetically improved cultivars. In this study 54 spinach accessions collected from the major spinach growing areas of Iran were evaluated to determine their phenotypic diversity profile of spinach genotypes on the basis of 10 quantitative and 9 qualitative morpho-agronomic traits. High coefficients of variation were recorded in some quantitative traits (dry yield and leaf area and all of the qualitative traits. Using principal component analysis, the first four principal components with eigen-values more than 1 contributed 87% of the variability among accessions for quantitative traits, whereas the first four principal components with eigen-values more than 0.8 contributed 79% of the variability among accessions for qualitative traits. The most important relations observed on the first two principal components were a strong positive association between leaf width and petiole length; between leaf length and leaf numbers in flowering; and among fresh yield, dry yield and petiole diameter; a near zero correlation between days to flowering with leaf width and petiole length. Prickly seeds, high percentage of female plants, smooth leaf texture, high numbers of leaves at flowering, greygreen leaves, erect petiole attitude and long petiole length are important characters for spinach breeding programmes.

Quantitative Trait Locus Mapping of Salt Tolerance and Identification of Salt-Tolerant Genes in Brassica napus L

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Lina Lang

2017-06-01

Full Text Available Salinity stress is one of typical abiotic stresses that seriously limit crop production. In this study, a genetic linkage map based on 532 molecular markers covering 1341.1 cM was constructed to identify the loci associated with salt tolerance in Brassica napus. Up to 45 quantitative trait loci (QTLs for 10 indicators were identified in the F2:3 populations. These QTLs can account for 4.80–51.14% of the phenotypic variation. A major QTL, qSPAD5 on LG5 associated with chlorophyll can be detected in three replicates. Two intron polymorphic (IP markers in this QTL region were developed successfully to narrow down the QTL location to a region of 390 kb. A salt tolerance related gene Bra003640 was primary identified as the candidate gene in this region. The full length of the candidate gene was 1,063 bp containing three exons and two introns in B. napus L. The open reading frame (ORF is 867 bp and encodes 287 amino acids. Three amino acid differences (34, 54, and 83 in the conserved domain (B-box were identified. RT-qPCR analysis showed that the gene expression had significant difference between the two parents. The study laid great foundation for salt tolerance related gene mapping and cloning in B. napus L.

Integration of gene-based markers in a pearl millet genetic map for identification of candidate genes underlying drought tolerance quantitative trait loci

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Sehgal Deepmala

2012-01-01

Full Text Available Abstract Background Identification of genes underlying drought tolerance (DT quantitative trait loci (QTLs will facilitate understanding of molecular mechanisms of drought tolerance, and also will accelerate genetic improvement of pearl millet through marker-assisted selection. We report a map based on genes with assigned functional roles in plant adaptation to drought and other abiotic stresses and demonstrate its use in identifying candidate genes underlying a major DT-QTL. Results Seventy five single nucleotide polymorphism (SNP and conserved intron spanning primer (CISP markers were developed from available expressed sequence tags (ESTs using four genotypes, H 77/833-2, PRLT 2/89-33, ICMR 01029 and ICMR 01004, representing parents of two mapping populations. A total of 228 SNPs were obtained from 30.5 kb sequenced region resulting in a SNP frequency of 1/134 bp. The positions of major pearl millet linkage group (LG 2 DT-QTLs (reported from crosses H 77/833-2 × PRLT 2/89-33 and 841B × 863B were added to the present consensus function map which identified 18 genes, coding for PSI reaction center subunit III, PHYC, actin, alanine glyoxylate aminotransferase, uridylate kinase, acyl-CoA oxidase, dipeptidyl peptidase IV, MADS-box, serine/threonine protein kinase, ubiquitin conjugating enzyme, zinc finger C- × 8-C × 5-C × 3-H type, Hd3, acetyl CoA carboxylase, chlorophyll a/b binding protein, photolyase, protein phosphatase1 regulatory subunit SDS22 and two hypothetical proteins, co-mapping in this DT-QTL interval. Many of these candidate genes were found to have significant association with QTLs of grain yield, flowering time and leaf rolling under drought stress conditions. Conclusions We have exploited available pearl millet EST sequences to generate a mapped resource of seventy five new gene-based markers for pearl millet and demonstrated its use in identifying candidate genes underlying a major DT-QTL in this species. The reported gene

Quantitative trait loci at the 11q23.3 chromosomal region related to dyslipidemia in the population of Andhra Pradesh, India.

Science.gov (United States)

Pranavchand, Rayabarapu; Reddy, Battini Mohan

2017-06-13

Given the characteristic atherogenic dyslipidemia of south Indian population and crucial role of APOA1, APOC3, APOA4 and APOA5 genes clustered in 11q23.3 chromosomal region in regulating lipoprotein metabolism and cholesterol homeostasis, a large number of recently identified variants are to be explored for their role in regulating the serum lipid parameters among south Indians. Using fluidigm SNP genotyping platform, a prioritized set of 96 SNPs of the 11q23.3 chromosomal region were genotyped on 516 individuals from Hyderabad, India, and its vicinity and aged >45 years. The linear regression analysis of the individual lipid traits viz., TC, LDLC, HDLC, VLDL and TG with each of the 78 SNPs that confirm to HWE and with minor allele frequency > 1%, suggests 23 of those to be significantly associated (p ≤ 0.05) with at least one of these quantitative traits. Most importantly, the variant rs632153 is involved in elevating TC, LDLC, TG and VLDLs and probably playing a crucial role in the manifestation of dyslipidemia. Additionally, another three SNPs rs633389, rs2187126 and rs1263163 are found risk conferring to dyslipidemia by elevating LDLC and TC levels in the present population. Further, the ROC (receiver operating curve) analysis for the risk scores and dyslipidemia status yielded a significant area under curve (AUC) = 0.675, suggesting high discriminative power of the risk variants towards the condition. The interaction analysis suggests rs10488699-rs2187126 pair of the BUD13 gene to confer significant risk (Interaction odds ratio = 14.38, P = 7.17 × 10 5 ) towards dyslipidemia by elevating the TC levels (β = 37.13, p = 6.614 × 10 5 ). On the other hand, the interaction between variants of APOA1 gene and BUD13 and/or ZPR1 regulatory genes at this region are associated with elevated TG and VLDL. The variants at 11q23.3 chromosomal region seem to determine the quantitative lipid traits and in turn dyslipidemia in the population of Hyderabad

Plants with useful traits and related methods

Science.gov (United States)

Mackenzie, Sally Ann; De la Rosa Santamaria, Roberto

2016-10-25

The present invention provides methods for obtaining plants that exhibit useful traits by transient suppression of the MSH1 gene of the plants. Methods for identifying genetic loci that provide for useful traits in plants and plants produced with those loci are also provided. In addition, plants that exhibit the useful traits, parts of the plants including seeds, and products of the plants are provided as well as methods of using the plants.

High-precision genetic mapping of behavioral traits in the diversity outbred mouse population

Science.gov (United States)

Logan, R W; Robledo, R F; Recla, J M; Philip, V M; Bubier, J A; Jay, J J; Harwood, C; Wilcox, T; Gatti, D M; Bult, C J; Churchill, G A; Chesler, E J

2013-01-01

Historically our ability to identify genetic variants underlying complex behavioral traits in mice has been limited by low mapping resolution of conventional mouse crosses. The newly developed Diversity Outbred (DO) population promises to deliver improved resolution that will circumvent costly fine-mapping studies. The DO is derived from the same founder strains as the Collaborative Cross (CC), including three wild-derived strains. Thus the DO provides more allelic diversity and greater potential for discovery compared to crosses involving standard mouse strains. We have characterized 283 male and female DO mice using open-field, light–dark box, tail-suspension and visual-cliff avoidance tests to generate 38 behavioral measures. We identified several quantitative trait loci (QTL) for these traits with support intervals ranging from 1 to 3 Mb in size. These intervals contain relatively few genes (ranging from 5 to 96). For a majority of QTL, using the founder allelic effects together with whole genome sequence data, we could further narrow the positional candidates. Several QTL replicate previously published loci. Novel loci were also identified for anxiety- and activity-related traits. Half of the QTLs are associated with wild-derived alleles, confirming the value to behavioral genetics of added genetic diversity in the DO. In the presence of wild-alleles we sometimes observe behaviors that are qualitatively different from the expected response. Our results demonstrate that high-precision mapping of behavioral traits can be achieved with moderate numbers of DO animals, representing a significant advance in our ability to leverage the mouse as a tool for behavioral genetics PMID:23433259

Integrating genome-wide association study and expression quantitative trait loci data identifies multiple genes and gene set associated with neuroticism.

Science.gov (United States)

Fan, Qianrui; Wang, Wenyu; Hao, Jingcan; He, Awen; Wen, Yan; Guo, Xiong; Wu, Cuiyan; Ning, Yujie; Wang, Xi; Wang, Sen; Zhang, Feng

2017-08-01

Neuroticism is a fundamental personality trait with significant genetic determinant. To identify novel susceptibility genes for neuroticism, we conducted an integrative analysis of genomic and transcriptomic data of genome wide association study (GWAS) and expression quantitative trait locus (eQTL) study. GWAS summary data was driven from published studies of neuroticism, totally involving 170,906 subjects. eQTL dataset containing 927,753 eQTLs were obtained from an eQTL meta-analysis of 5311 samples. Integrative analysis of GWAS and eQTL data was conducted by summary data-based Mendelian randomization (SMR) analysis software. To identify neuroticism associated gene sets, the SMR analysis results were further subjected to gene set enrichment analysis (GSEA). The gene set annotation dataset (containing 13,311 annotated gene sets) of GSEA Molecular Signatures Database was used. SMR single gene analysis identified 6 significant genes for neuroticism, including MSRA (p value=2.27×10 -10 ), MGC57346 (p value=6.92×10 -7 ), BLK (p value=1.01×10 -6 ), XKR6 (p value=1.11×10 -6 ), C17ORF69 (p value=1.12×10 -6 ) and KIAA1267 (p value=4.00×10 -6 ). Gene set enrichment analysis observed significant association for Chr8p23 gene set (false discovery rate=0.033). Our results provide novel clues for the genetic mechanism studies of neuroticism. Copyright © 2017. Published by Elsevier Inc.

A high-density genetic map and QTL analysis of agronomic traits in foxtail millet [Setaria italica (L.) P. Beauv.] using RAD-seq.

Science.gov (United States)

Wang, Jun; Wang, Zhilan; Du, Xiaofen; Yang, Huiqing; Han, Fang; Han, Yuanhuai; Yuan, Feng; Zhang, Linyi; Peng, Shuzhong; Guo, Erhu

2017-01-01

Foxtail millet (Setaria italica), a very important grain crop in China, has become a new model plant for cereal crops and biofuel grasses. Although its reference genome sequence was released recently, quantitative trait loci (QTLs) controlling complex agronomic traits remains limited. The development of massively parallel genotyping methods and next-generation sequencing technologies provides an excellent opportunity for developing single-nucleotide polymorphisms (SNPs) for linkage map construction and QTL analysis of complex quantitative traits. In this study, a high-throughput and cost-effective RAD-seq approach was employed to generate a high-density genetic map for foxtail millet. A total of 2,668,587 SNP loci were detected according to the reference genome sequence; meanwhile, 9,968 SNP markers were used to genotype 124 F2 progenies derived from the cross between Hongmiaozhangu and Changnong35; a high-density genetic map spanning 1648.8 cM, with an average distance of 0.17 cM between adjacent markers was constructed; 11 major QTLs for eight agronomic traits were identified; five co-dominant DNA markers were developed. These findings will be of value for the identification of candidate genes and marker-assisted selection in foxtail millet.

On coding genotypes for genetic markers with multiple alleles in genetic association study of quantitative traits

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Wang Tao

2011-09-01

Full Text Available Abstract Background In genetic association study of quantitative traits using F∞ models, how to code the marker genotypes and interpret the model parameters appropriately is important for constructing hypothesis tests and making statistical inferences. Currently, the coding of marker genotypes in building F∞ models has mainly focused on the biallelic case. A thorough work on the coding of marker genotypes and interpretation of model parameters for F∞ models is needed especially for genetic markers with multiple alleles. Results In this study, we will formulate F∞ genetic models under various regression model frameworks and introduce three genotype coding schemes for genetic markers with multiple alleles. Starting from an allele-based modeling strategy, we first describe a regression framework to model the expected genotypic values at given markers. Then, as extension from the biallelic case, we introduce three coding schemes for constructing fully parameterized one-locus F∞ models and discuss the relationships between the model parameters and the expected genotypic values. Next, under a simplified modeling framework for the expected genotypic values, we consider several reduced one-locus F∞ models from the three coding schemes on the estimability and interpretation of their model parameters. Finally, we explore some extensions of the one-locus F∞ models to two loci. Several fully parameterized as well as reduced two-locus F∞ models are addressed. Conclusions The genotype coding schemes provide different ways to construct F∞ models for association testing of multi-allele genetic markers with quantitative traits. Which coding scheme should be applied depends on how convenient it can provide the statistical inferences on the parameters of our research interests. Based on these F∞ models, the standard regression model fitting tools can be used to estimate and test for various genetic effects through statistical contrasts with the

Genome-wide association mapping of growth dynamics detects time-specific and general quantitative trait loci

NARCIS (Netherlands)

Bac-Molenaar, J.A.; Vreugdenhil, D.; Granier, C.; Keurentjes, J.J.B.

2015-01-01

Growth is a complex trait determined by the interplay between many genes, some of which play a role at a specific moment during development whereas others play a more general role. To identify the genetic basis of growth, natural variation in Arabidopsis rosette growth was followed in 324 accessions

Ancestral genes can control the ability of horizontally acquired loci to confer new traits.

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H Deborah Chen

2011-07-01

Full Text Available Horizontally acquired genes typically function as autonomous units conferring new abilities when introduced into different species. However, we reasoned that proteins preexisting in an organism might constrain the functionality of a horizontally acquired gene product if it operates on an ancestral pathway. Here, we determine how the horizontally acquired pmrD gene product activates the ancestral PmrA/PmrB two-component system in Salmonella enterica but not in the closely related bacterium Escherichia coli. The Salmonella PmrD protein binds to the phosphorylated PmrA protein (PmrA-P, protecting it from dephosphorylation by the PmrB protein. This results in transcription of PmrA-dependent genes, including those conferring polymyxin B resistance. We now report that the E. coli PmrD protein can activate the PmrA/PmrB system in Salmonella even though it cannot do it in E. coli, suggesting that these two species differ in an additional component controlling PmrA-P levels. We establish that the E. coli PmrB displays higher phosphatase activity towards PmrA-P than the Salmonella PmrB, and we identified a PmrB subdomain responsible for this property. Replacement of the E. coli pmrB gene with the Salmonella homolog was sufficient to render E. coli resistant to polymyxin B under PmrD-inducing conditions. Our findings provide a singular example whereby quantitative differences in the biochemical activities of orthologous ancestral proteins dictate the ability of a horizontally acquired gene product to confer species-specific traits. And they suggest that horizontally acquired genes can potentiate selection at ancestral loci.

Biological, clinical and population relevance of 95 loci for blood lipids

DEFF Research Database (Denmark)

Teslovich, Tanya M; Musunuru, Kiran; Smith, Albert V

2010-01-01

polymorphisms (SNPs) near known lipid regulators (for example, CYP7A1, NPC1L1 and SCARB1) as well as in scores of loci not previously implicated in lipoprotein metabolism. The 95 loci contribute not only to normal variation in lipid traits but also to extreme lipid phenotypes and have an impact on lipid traits...... in three non-European populations (East Asians, South Asians and African Americans). Our results identify several novel loci associated with plasma lipids that are also associated with CAD. Finally, we validated three of the novel genes-GALNT2, PPP1R3B and TTC39B-with experiments in mouse models. Taken...

Genome-Wide Association Study Identifies Two Novel Loci with Sex-Specific Effects for Type 2 Diabetes Mellitus and Glycemic Traits in a Korean Population

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Min Jin Go

2014-10-01

Full Text Available BackgroundUntil recently, genome-wide association study (GWAS-based findings have provided a substantial genetic contribution to type 2 diabetes mellitus (T2DM or related glycemic traits. However, identification of allelic heterogeneity and population-specific genetic variants under consideration of potential confounding factors will be very valuable for clinical applicability. To identify novel susceptibility loci for T2DM and glycemic traits, we performed a two-stage genetic association study in a Korean population.MethodsWe performed a logistic analysis for T2DM, and the first discovery GWAS was analyzed for 1,042 cases and 2,943 controls recruited from a population-based cohort (KARE, n=8,842. The second stage, de novo replication analysis, was performed in 1,216 cases and 1,352 controls selected from an independent population-based cohort (Health 2, n=8,500. A multiple linear regression analysis for glycemic traits was further performed in a total of 14,232 nondiabetic individuals consisting of 7,696 GWAS and 6,536 replication study participants. A meta-analysis was performed on the combined results using effect size and standard errors estimated for stage 1 and 2, respectively.ResultsA combined meta-analysis for T2DM identified two new (rs11065756 and rs2074356 loci reaching genome-wide significance in CCDC63 and C12orf51 on the 12q24 region. In addition, these variants were significantly associated with fasting plasma glucose and homeostasis model assessment of β-cell function. Interestingly, two independent single nucleotide polymorphisms were associated with sex-specific stratification in this study.ConclusionOur study showed a strong association between T2DM and glycemic traits. We further observed that two novel loci with multiple diverse effects were highly specific to males. Taken together, these findings may provide additional insights into the clinical assessment or subclassification of disease risk in a Korean population.

Comprehensive Comparison of Self-Administered Questionnaires for Measuring Quantitative Autistic Traits in Adults

Science.gov (United States)

Nishiyama, Takeshi; Suzuki, Masako; Adachi, Katsunori; Sumi, Satoshi; Okada, Kensuke; Kishino, Hirohisa; Sakai, Saeko; Kamio, Yoko; Kojima, Masayo; Suzuki, Sadao; Kanne, Stephen M.

2014-01-01

We comprehensively compared all available questionnaires for measuring quantitative autistic traits (QATs) in terms of reliability and construct validity in 3,147 non-clinical and 60 clinical subjects with normal intelligence. We examined four full-length forms, the Subthreshold Autism Trait Questionnaire (SATQ), the Broader Autism Phenotype…

Genome-wide association studies dissect the genetic networks underlying agronomical traits in soybean.

Science.gov (United States)

Fang, Chao; Ma, Yanming; Wu, Shiwen; Liu, Zhi; Wang, Zheng; Yang, Rui; Hu, Guanghui; Zhou, Zhengkui; Yu, Hong; Zhang, Min; Pan, Yi; Zhou, Guoan; Ren, Haixiang; Du, Weiguang; Yan, Hongrui; Wang, Yanping; Han, Dezhi; Shen, Yanting; Liu, Shulin; Liu, Tengfei; Zhang, Jixiang; Qin, Hao; Yuan, Jia; Yuan, Xiaohui; Kong, Fanjiang; Liu, Baohui; Li, Jiayang; Zhang, Zhiwu; Wang, Guodong; Zhu, Baoge; Tian, Zhixi

2017-08-24

Soybean (Glycine max [L.] Merr.) is one of the most important oil and protein crops. Ever-increasing soybean consumption necessitates the improvement of varieties for more efficient production. However, both correlations among different traits and genetic interactions among genes that affect a single trait pose a challenge to soybean breeding. To understand the genetic networks underlying phenotypic correlations, we collected 809 soybean accessions worldwide and phenotyped them for two years at three locations for 84 agronomic traits. Genome-wide association studies identified 245 significant genetic loci, among which 95 genetically interacted with other loci. We determined that 14 oil synthesis-related genes are responsible for fatty acid accumulation in soybean and function in line with an additive model. Network analyses demonstrated that 51 traits could be linked through the linkage disequilibrium of 115 associated loci and these links reflect phenotypic correlations. We revealed that 23 loci, including the known Dt1, E2, E1, Ln, Dt2, Fan, and Fap loci, as well as 16 undefined associated loci, have pleiotropic effects on different traits. This study provides insights into the genetic correlation among complex traits and will facilitate future soybean functional studies and breeding through molecular design.

Statistical equivalent of the classical TDT for quantitative traits and ...

Indian Academy of Sciences (India)

sion model to test the association for quantitative traits based on a trio design. We show that the method ... from the analyses and only one transmission is considered. Keywords. .... use the sample mean or median of Y, as an estimator of c in.

Construction of a high-density genetic map using specific length amplified fragment markers and identification of a quantitative trait locus for anthracnose resistance in walnut (Juglans regia L.).

Science.gov (United States)

Zhu, Yufeng; Yin, Yanfei; Yang, Keqiang; Li, Jihong; Sang, Yalin; Huang, Long; Fan, Shu

2015-08-18

Walnut (Juglans regia, 2n = 32, approximately 606 Mb per 1C genome) is an economically important tree crop. Resistance to anthracnose, caused by Colletotrichum gloeosporioides, is a major objective of walnut genetic improvement in China. The recently developed specific length amplified fragment sequencing (SLAF-seq) is an efficient strategy that can obtain large numbers of markers with sufficient sequence information to construct high-density genetic maps and permits detection of quantitative trait loci (QTLs) for molecular breeding. SLAF-seq generated 161.64 M paired-end reads. 153,820 SLAF markers were obtained, of which 49,174 were polymorphic. 13,635 polymorphic markers were sorted into five segregation types and 2,577 markers of them were used to construct genetic linkage maps: 2,395 of these fell into 16 linkage groups (LGs) for the female map, 448 markers for the male map, and 2,577 markers for the integrated map. Taking into account the size of all LGs, the marker coverage was 2,664.36 cM for the female map, 1,305.58 cM for the male map, and 2,457.82 cM for the integrated map. The average intervals between two adjacent mapped markers were 1.11 cM, 2.91 cM and 0.95 cM for three maps, respectively. 'SNP_only' markers accounted for 89.25% of the markers on the integrated map. Mapping markers contained 5,043 single nucleotide polymorphisms (SNPs) loci, which corresponded to two SNP loci per SLAF marker. According to the integrated map, we used interval mapping (Logarithm of odds, LOD > 3.0) to detect our quantitative trait. One QTL was detected for anthracnose resistance. The interval of this QTL ranged from 165.51 cM to 176.33 cM on LG14, and ten markers in this interval that were above the threshold value were considered to be linked markers to the anthracnose resistance trait. The phenotypic variance explained by each marker ranged from 16.2 to 19.9%, and their LOD scores varied from 3.22 to 4.04. High-density genetic maps for walnut containing 16

Genetic effects at pleiotropic loci are context-dependent with consequences for the maintenance of genetic variation in populations.

Directory of Open Access Journals (Sweden)

Heather A Lawson

2011-09-01

Full Text Available Context-dependent genetic effects, including genotype-by-environment and genotype-by-sex interactions, are a potential mechanism by which genetic variation of complex traits is maintained in populations. Pleiotropic genetic effects are also thought to play an important role in evolution, reflecting functional and developmental relationships among traits. We examine context-dependent genetic effects at pleiotropic loci associated with normal variation in multiple metabolic syndrome (MetS components (obesity, dyslipidemia, and diabetes-related traits. MetS prevalence is increasing in Western societies and, while environmental in origin, presents substantial variation in individual response. We identify 23 pleiotropic MetS quantitative trait loci (QTL in an F(16 advanced intercross between the LG/J and SM/J inbred mouse strains (Wustl:LG,SM-G16; n = 1002. Half of each family was fed a high-fat diet and half fed a low-fat diet; and additive, dominance, and parent-of-origin imprinting genotypic effects were examined in animals partitioned into sex, diet, and sex-by-diet cohorts. We examine the context-dependency of the underlying additive, dominance, and imprinting genetic effects of the traits associated with these pleiotropic QTL. Further, we examine sequence polymorphisms (SNPs between LG/J and SM/J as well as differential expression of positional candidate genes in these regions. We show that genetic associations are different in different sex, diet, and sex-by-diet settings. We also show that over- or underdominance and ecological cross-over interactions for single phenotypes may not be common, however multidimensional synthetic phenotypes at loci with pleiotropic effects can produce situations that favor the maintenance of genetic variation in populations. Our findings have important implications for evolution and the notion of personalized medicine.

Quantitative autistic trait measurements index background genetic risk for ASD in Hispanic families.

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Page, Joshua; Constantino, John Nicholas; Zambrana, Katherine; Martin, Eden; Tunc, Ilker; Zhang, Yi; Abbacchi, Anna; Messinger, Daniel

2016-01-01

Recent studies have indicated that quantitative autistic traits (QATs) of parents reflect inherited liabilities that may index background genetic risk for clinical autism spectrum disorder (ASD) in their offspring. Moreover, preferential mating for QATs has been observed as a potential factor in concentrating autistic liabilities in some families across generations. Heretofore, intergenerational studies of QATs have focused almost exclusively on Caucasian populations-the present study explored these phenomena in a well-characterized Hispanic population. The present study examined QAT scores in siblings and parents of 83 Hispanic probands meeting research diagnostic criteria for ASD, and 64 non-ASD controls, using the Social Responsiveness Scale-2 (SRS-2). Ancestry of the probands was characterized by genotype, using information from 541,929 single nucleotide polymorphic markers. In families of Hispanic children with an ASD diagnosis, the pattern of quantitative trait correlations observed between ASD-affected children and their first-degree relatives (ICCs on the order of 0.20), between unaffected first-degree relatives in ASD-affected families (sibling/mother ICC = 0.36; sibling/father ICC = 0.53), and between spouses (mother/father ICC = 0.48) were in keeping with the influence of transmitted background genetic risk and strong preferential mating for variation in quantitative autistic trait burden. Results from analysis of ancestry-informative genetic markers among probands in this sample were consistent with that from other Hispanic populations. Quantitative autistic traits represent measurable indices of inherited liability to ASD in Hispanic families. The accumulation of autistic traits occurs within generations, between spouses, and across generations, among Hispanic families affected by ASD. The occurrence of preferential mating for QATs-the magnitude of which may vary across cultures-constitutes a mechanism by which background genetic liability

Identification of multiple genetic loci in the mouse controlling immobility time in the tail suspension and forced swimming tests.

Science.gov (United States)

Abou-Elnaga, Ahmed F; Torigoe, Daisuke; Fouda, Mohamed M; Darwish, Ragab A; Abou-Ismail, Usama A; Morimatsu, Masami; Agui, Takashi

2015-05-01

Depression is one of the most famous psychiatric disorders in humans in all over the countries and considered a complex neurobehavioral trait and difficult to identify causal genes. Tail suspension test (TST) and forced swimming test (FST) are widely used for assessing depression-like behavior and antidepressant activity in mice. A variety of antidepressant agents are known to reduce immobility time in both TST and FST. To identify genetic determinants of immobility duration in both tests, we analyzed 101 F2 mice from an intercross between C57BL/6 and DBA/2 strains. Quantitative trait locus (QTL) mapping using 106 microsatellite markers revealed three loci (two significant and one suggestive) and five suggestive loci controlling immobility time in the TST and FST, respectively. Results of QTL analysis suggest a broad description of the genetic architecture underlying depression, providing underpinnings for identifying novel molecular targets for antidepressants to clear the complex genetic mechanisms of depressive disorders.

Genome-wide association studies of autoimmune vitiligo identify 23 new risk loci and highlight key pathways and regulatory variants.

Science.gov (United States)

Jin, Ying; Andersen, Genevieve; Yorgov, Daniel; Ferrara, Tracey M; Ben, Songtao; Brownson, Kelly M; Holland, Paulene J; Birlea, Stanca A; Siebert, Janet; Hartmann, Anke; Lienert, Anne; van Geel, Nanja; Lambert, Jo; Luiten, Rosalie M; Wolkerstorfer, Albert; Wietze van der Veen, J P; Bennett, Dorothy C; Taïeb, Alain; Ezzedine, Khaled; Kemp, E Helen; Gawkrodger, David J; Weetman, Anthony P; Kõks, Sulev; Prans, Ele; Kingo, Külli; Karelson, Maire; Wallace, Margaret R; McCormack, Wayne T; Overbeck, Andreas; Moretti, Silvia; Colucci, Roberta; Picardo, Mauro; Silverberg, Nanette B; Olsson, Mats; Valle, Yan; Korobko, Igor; Böhm, Markus; Lim, Henry W; Hamzavi, Iltefat; Zhou, Li; Mi, Qing-Sheng; Fain, Pamela R; Santorico, Stephanie A; Spritz, Richard A

2016-11-01

Vitiligo is an autoimmune disease in which depigmented skin results from the destruction of melanocytes, with epidemiological association with other autoimmune diseases. In previous linkage and genome-wide association studies (GWAS1 and GWAS2), we identified 27 vitiligo susceptibility loci in patients of European ancestry. We carried out a third GWAS (GWAS3) in European-ancestry subjects, with augmented GWAS1 and GWAS2 controls, genome-wide imputation, and meta-analysis of all three GWAS, followed by an independent replication. The combined analyses, with 4,680 cases and 39,586 controls, identified 23 new significantly associated loci and 7 suggestive loci. Most encode immune and apoptotic regulators, with some also associated with other autoimmune diseases, as well as several melanocyte regulators. Bioinformatic analyses indicate a predominance of causal regulatory variation, some of which corresponds to expression quantitative trait loci (eQTLs) at these loci. Together, the identified genes provide a framework for the genetic architecture and pathobiology of vitiligo, highlight relationships with other autoimmune diseases and melanoma, and offer potential targets for treatment.

Pleiotropy analysis of quantitative traits at gene level by multivariate functional linear models.

Science.gov (United States)

Wang, Yifan; Liu, Aiyi; Mills, James L; Boehnke, Michael; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao; Wu, Colin O; Fan, Ruzong

2015-05-01

In genetics, pleiotropy describes the genetic effect of a single gene on multiple phenotypic traits. A common approach is to analyze the phenotypic traits separately using univariate analyses and combine the test results through multiple comparisons. This approach may lead to low power. Multivariate functional linear models are developed to connect genetic variant data to multiple quantitative traits adjusting for covariates for a unified analysis. Three types of approximate F-distribution tests based on Pillai-Bartlett trace, Hotelling-Lawley trace, and Wilks's Lambda are introduced to test for association between multiple quantitative traits and multiple genetic variants in one genetic region. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and optimal sequence kernel association test (SKAT-O). Extensive simulations were performed to evaluate the false positive rates and power performance of the proposed models and tests. We show that the approximate F-distribution tests control the type I error rates very well. Overall, simultaneous analysis of multiple traits can increase power performance compared to an individual test of each trait. The proposed methods were applied to analyze (1) four lipid traits in eight European cohorts, and (2) three biochemical traits in the Trinity Students Study. The approximate F-distribution tests provide much more significant results than those of F-tests of univariate analysis and SKAT-O for the three biochemical traits. The approximate F-distribution tests of the proposed functional linear models are more sensitive than those of the traditional multivariate linear models that in turn are more sensitive than SKAT-O in the univariate case. The analysis of the four lipid traits and the three biochemical traits detects more association than SKAT-O in the univariate case. © 2015 WILEY PERIODICALS, INC.

Biallelic and Genome Wide Association Mapping of Germanium Tolerant Loci in Rice (Oryza sativa L..

Directory of Open Access Journals (Sweden)

Partha Talukdar

Full Text Available Rice plants accumulate high concentrations of silicon. Silicon has been shown to be involved in plant growth, high yield, and mitigating biotic and abiotic stresses. However, it has been demonstrated that inorganic arsenic is taken up by rice through silicon transporters under anaerobic conditions, thus the ability to efficiently take up silicon may be considered either a positive or a negative trait in rice. Germanium is an analogue of silicon that produces brown lesions in shoots and leaves, and germanium toxicity has been used to identify mutants in silicon and arsenic transport. In this study, two different genetic mapping methods were performed to determine the loci involved in germanium sensitivity in rice. Genetic mapping in the biparental cross of Bala × Azucena (an F6 population and a genome wide association (GWA study with 350 accessions from the Rice Diversity Panel 1 were conducted using 15 μM of germanic acid. This identified a number of germanium sensitive loci: some co-localised with previously identified quantitative trait loci (QTL for tissue silicon or arsenic concentration, none co-localised with Lsi1 or Lsi6, while one single nucleotide polymorphism (SNP was detected within 200 kb of Lsi2 (these are genes known to transport silicon, whose identity was discovered using germanium toxicity. However, examining candidate genes that are within the genomic region of the loci detected above reveals genes homologous to both Lsi1 and Lsi2, as well as a number of other candidate genes, which are discussed.

Identification of heterotic loci associated with yield-related traits in Chinese common wild rice (Oryza rufipogon Griff.).

Science.gov (United States)

Luo, Xiaojin; Wu, Shuang; Tian, Feng; Xin, Xiaoyun; Zha, Xiaojun; Dong, Xianxin; Fu, Yongcai; Wang, Xiangkun; Yang, Jinshui; Sun, Chuanqing

2011-07-01

Many rice breeding programs have currently reached yield plateaus as a result of limited genetic variability in parental strains. Dongxiang common wild rice (Oryza rufipogon Griff.) is the progenitor of cultivated rice (Oryza sativa L.) and serves as an important gene pool for the genetic improvement of rice cultivars. In this study, heterotic loci (HLs) associated with six yield-related traits were identified in wild and cultivated rice and investigated using a set of 265 introgression lines (ILs) of O. rufipogon Griff. in the background of the Indica high-yielding cultivar Guichao 2 (O. sativa L.). Forty-two HLs were detected by a single point analysis of mid-parent heterosis values from test cross F(1) offspring, and 30 (71.5%) of these HLs showed significantly positive effects, consistent with the superiority shown by the F(1) test cross population in the six yield-related traits under study. Genetic mapping of hsp11, a locus responsible for the number of spikelets per panicle, confirmed the utility of these HLs. The results indicate that favorable HLs capable of improving agronomic traits are available. The identification of HLs between wild rice and cultivated rice could lead to a new strategy for the application of heterosis in rice breeding. Copyright © 2011. Published by Elsevier Ireland Ltd.

Identification and characterization of pleiotropic and co-located resistance loci to leaf rust and stripe rust in bread wheat cultivar Sujata.

Science.gov (United States)

Lan, Caixia; Zhang, Yelun; Herrera-Foessel, Sybil A; Basnet, Bhoja R; Huerta-Espino, Julio; Lagudah, Evans S; Singh, Ravi P

2015-03-01

Two new co-located resistance loci, QLr.cim - 1AS/QYr.cim - 1AS and QLr.cim - 7BL/YrSuj , in combination with Lr46 / Yr29 and Lr67/Yr46 , and a new leaf rust resistance quantitative trait loci, conferred high resistance to rusts in adult plant stage. The tall Indian bread wheat cultivar Sujata displays high and low infection types to leaf rust and stripe rust, respectively, at the seedling stage in greenhouse tests. It was also highly resistant to both rusts at adult plant stage in field trials in Mexico. The genetic basis of this resistance was investigated in a population of 148 F5 recombinant inbred lines (RILs) derived from the cross Avocet × Sujata. The parents and RIL population were characterized in field trials for resistance to leaf rust during 2011 at El Batán, and 2012 and 2013 at Ciudad Obregón, Mexico, and for stripe rust during 2011 and 2012 at Toluca, Mexico; they were also characterized three times for stripe rust at seedling stage in the greenhouse. The RILs were genotyped with diversity arrays technology and simple sequence repeat markers. The final genetic map was constructed with 673 polymorphic markers. Inclusive composite interval mapping analysis detected two new significant co-located resistance loci, QLr.cim-1AS/QYr.cim-1AS and QLr.cim-7BL/YrSuj, on chromosomes 1AS and 7BL, respectively. The chromosomal position of QLr.cim-7BL overlapped with the seedling stripe rust resistance gene, temporarily designated as YrSuj. Two previously reported pleiotropic adult plant resistance genes, Lr46/Yr29 and Lr67/Yr46, and a new leaf rust resistance quantitative trait loci derived from Avocet were also mapped in the population. The two new co-located resistance loci are expected to contribute to breeding durable rust resistance in wheat. Closely linked molecular markers can be used to transfer all four resistance loci simultaneously to modern wheat varieties.

Evaluation of seven common lipid associated loci in a large Indian sib pair study.

Science.gov (United States)

Rafiq, Sajjad; Venkata, Kranthi Kumar M; Gupta, Vipin; Vinay, D G; Spurgeon, Charles J; Parameshwaran, Smitha; Madana, Sandeep N; Kinra, Sanjay; Bowen, Liza; Timpson, Nicholas J; Smith, George Davey; Dudbridge, Frank; Prabhakaran, Dorairaj; Ben-Shlomo, Yoav; Reddy, K Srinath; Ebrahim, Shah; Chandak, Giriraj R

2012-11-14

Genome wide association studies (GWAS), mostly in Europeans have identified several common variants as associated with key lipid traits. Replication of these genetic effects in South Asian populations is important since it would suggest wider relevance for these findings. Given the rising prevalence of metabolic disorders and heart disease in the Indian sub-continent, these studies could be of future clinical relevance. We studied seven common variants associated with a variety of lipid traits in previous GWASs. The study sample comprised of 3178 sib-pairs recruited as participants for the Indian Migration Study (IMS). Associations with various lipid parameters and quantitative traits were analyzed using the Fulker genetic association model. We replicated five of the 7 main effect associations with p-values ranging from 0.03 to 1.97x10(-7). We identified particularly strong association signals at rs662799 in APOA5 (beta=0.18 s.d, p=1.97 x 10(-7)), rs10503669 in LPL (beta =-0.18 s.d, p=1.0 x 10(-4)) and rs780094 in GCKR (beta=0.11 s.d, p=0.001) loci in relation to triglycerides. In addition, the GCKR variant was also associated with total cholesterol (beta=0.11 s.d, p=3.9x10(-4)). We also replicated the association of rs562338 in APOB (p=0.03) and rs4775041 in LIPC (p=0.007) with LDL-cholesterol and HDL-cholesterol respectively. We report associations of five loci with various lipid traits with the effect size consistent with the same reported in Europeans. These results indicate an overlap of genetic effects pertaining to lipid traits across the European and Indian populations.

Quantitative Linkage for Autism Spectrum Disorders Symptoms in Attention-Deficit/Hyperactivity Disorder : Significant Locus on Chromosome 7q11

NARCIS (Netherlands)

Nijmeijer, Judith; Arias-Vasquez, Alejandro; Rommelse, Nanda N. J.; Altink, Marieke E.; Buschgens, Cathelijne J. M.; Fliers, Ellen A.; Franke, Barbara; Minderaa, Rudolf; Sergeant, Joseph A.; Buitelaar, Jan K.; Hoekstra, Pieter J.; Hartman, Catharina A.

We studied 261 ADHD probands and 354 of their siblings to assess quantitative trait loci associated with autism spectrum disorder symptoms (as measured by the Children's Social Behavior Questionnaire (CSBQ)) using a genome-wide linkage approach, followed by locus-wide association analysis. A

Quantitative genetic analysis of anxiety trait in bipolar disorder.

Science.gov (United States)

Contreras, J; Hare, E; Chavarría, G; Raventós, H

2018-01-01

Bipolar disorder type I (BPI) affects approximately 1% of the world population. Although genetic influences on bipolar disorder are well established, identification of genes that predispose to the illness has been difficult. Most genetic studies are based on categorical diagnosis. One strategy to overcome this obstacle is the use of quantitative endophenotypes, as has been done for other medical disorders. We studied 619 individuals, 568 participants from 61 extended families and 51 unrelated healthy controls. The sample was 55% female and had a mean age of 43.25 (SD 13.90; range 18-78). Heritability and genetic correlation of the trait scale from the Anxiety State and Trait Inventory (STAI) was computed by using the general linear model (SOLAR package software). we observed that anxiety trait meets the following criteria for an endophenotype of bipolar disorder type I (BPI): 1) association with BPI (individuals with BPI showed the highest trait score (F = 15.20 [5,24], p = 0.009), 2) state-independence confirmed after conducting a test-retest in 321 subjects, 3) co-segregation within families 4) heritability of 0.70 (SE: 0.060), p = 2.33 × 10 -14 and 5) genetic correlation with BPI was 0.20, (SE = 0.17, p = 3.12 × 10 -5 ). Confounding factors such as comorbid disorders and pharmacological treatment could affect the clinical relationship between BPI and anxiety trait. Further research is needed to evaluate if anxiety traits are specially related to BPI in comparison with other traits such as anger, attention or response inhibition deficit, pathological impulsivity or low self-directedness. Anxiety trait is a heritable phenotype that follows a normal distribution when measured not only in subjects with BPI but also in unrelated healthy controls. It could be used as an endophenotype in BPI for the identification of genomic regions with susceptibility genes for this disorder. Published by Elsevier B.V.

Identification of Quantitative Trait Loci (QTL) and Candidate Genes for Cadmium Tolerance in Populus

Energy Technology Data Exchange (ETDEWEB)

Induri, Brahma R [West Virginia University; Ellis, Danielle R [West Virginia University; Slavov, Gancho [West Virginia University; Yin, Tongming [ORNL; Muchero, Wellington [ORNL; Tuskan, Gerald A [ORNL; DiFazio, Stephen P [West Virginia University

2012-01-01

Knowledge of genetic variation in response of Populus to heavy metals like cadmium (Cd) is an important step in understanding the underlying mechanisms of tolerance. In this study, a pseudo-backcross pedigree of Populus trichocarpa and Populus deltoides was characterized for Cd exposure. The pedigree showed significant variation for Cd tolerance thus enabling the identification of relatively tolerant and susceptible genotypes for intensive characterization. A total of 16 QTLs at logarithm of odds (LOD) ratio > 2.5, were found to be associated with total dry weight, its components, and root volume. Four major QTLs for total dry weight were mapped to different linkage groups in control (LG III) and Cd conditions (LG XVI) and had opposite allelic effects on Cd tolerance, suggesting that these genomic regions were differentially controlled. The phenotypic variation explained by Cd QTL for all traits under study varied from 5.9% to 11.6% and averaged 8.2% across all QTL. Leaf Cd contents also showed significant variation suggesting the phytoextraction potential of Populus genotypes, though heritability of this trait was low (0.22). A whole-genome microarray study was conducted by using two genotypes with extreme responses for Cd tolerance in the above study and differentially expressed genes were identified. Candidate genes including CAD2 (CADMIUM SENSITIVE 2), HMA5 (HEAVY METAL ATPase5), ATGTST1 (Arabidopsis thaliana Glutathione S-Transferase1), ATGPX6 (Glutathione peroxidase 6), and ATMRP 14 (Arabidopsis thaliana Multidrug Resistance associated Protein 14) were identified from QTL intervals and microarray study. Functional characterization of these candidate genes could enhance phytoremediation capabilities of Populus.

Searching for an Accurate Marker-Based Prediction of an Individual Quantitative Trait in Molecular Plant Breeding.

Science.gov (United States)

Fu, Yong-Bi; Yang, Mo-Hua; Zeng, Fangqin; Biligetu, Bill

2017-01-01

Molecular plant breeding with the aid of molecular markers has played an important role in modern plant breeding over the last two decades. Many marker-based predictions for quantitative traits have been made to enhance parental selection, but the trait prediction accuracy remains generally low, even with the aid of dense, genome-wide SNP markers. To search for more accurate trait-specific prediction with informative SNP markers, we conducted a literature review on the prediction issues in molecular plant breeding and on the applicability of an RNA-Seq technique for developing function-associated specific trait (FAST) SNP markers. To understand whether and how FAST SNP markers could enhance trait prediction, we also performed a theoretical reasoning on the effectiveness of these markers in a trait-specific prediction, and verified the reasoning through computer simulation. To the end, the search yielded an alternative to regular genomic selection with FAST SNP markers that could be explored to achieve more accurate trait-specific prediction. Continuous search for better alternatives is encouraged to enhance marker-based predictions for an individual quantitative trait in molecular plant breeding.

Quantitative trait loci on chromosomes 2p, 4p, and 13q influence bone mineral density of the forearm and hip in Mexican Americans.

Science.gov (United States)

Kammerer, Candace M; Schneider, Jennifer L; Cole, Shelley A; Hixson, James E; Samollow, Paul B; O'Connell, Jeffrey R; Perez, Reina; Dyer, Thomas D; Almasy, Laura; Blangero, John; Bauer, Richard L; Mitchell, Braxton D

2003-12-01

We performed a genome scan using BMD data of the forearm and hip on 664 individuals in 29 Mexican-American families. We obtained evidence for QTL on chromosome 4p, affecting forearm BMD overall, and on chromosomes 2p and 13q, affecting hip BMD in men. The San Antonio Family Osteoporosis Study (SAFOS) was designed to identify genes and environmental factors that influence bone mineral density (BMD) using data from large Mexican-American families. We performed a genome-wide linkage analysis using 416 highly polymorphic microsatellite markers spaced approximately 9.5 cM apart to locate and identify quantitative trait loci (QTL) that affect BMD of the forearm and hip. Multipoint variance components linkage analyses were done using data on all 664 subjects, as well as two subgroups of 259 men and 261 premenopausal women, from 29 families for which genotypic and phenotypic data were available. We obtained significant evidence for a QTL affecting forearm (radius midpoint) BMD in men and women combined on chromosome 4p near D4S2639 (maximum LOD = 4.33, genomic p = 0.006) and suggestive evidence for a QTL on chromosome 12q near locus D12S2070 (maximum conditional LOD = 2.35). We found suggestive evidence for a QTL influencing trochanter BMD on chromosome 6 (maximum LOD = 2.27), but no evidence for QTL affecting the femoral neck in men and women combined. In men, we obtained evidence for QTL affecting neck and trochanter BMD on chromosomes 2p near D2S1780 (maximum LOD = 3.98, genomic p = 0.013) and 13q near D13S788 (maximum LOD = 3.46, genomic p = 0.039), respectively. We found no evidence for QTL affecting forearm or hip BMD in premenopausal women. These results provide strong evidence that a QTL on chromosome 4p affects radius BMD in Mexican-American men and women, as well as evidence that QTL on chromosomes 2p and 13q affect hip BMD in men. Our results are consistent with some reports in humans and mice. J Bone Miner Res 2003;18:2245-2252

Fine-mapping diabetes-related traits, including insulin resistance, in heterogeneous stock rats

Science.gov (United States)

Holl, Katie L.; Oreper, Daniel; Xie, Yuying; Tsaih, Shirng-Wern; Valdar, William

2012-01-01

Type 2 diabetes (T2D) is a disease of relative insulin deficiency resulting from both insulin resistance and beta cell failure. We have previously used heterogeneous stock (HS) rats to fine-map a locus for glucose tolerance. We show here that glucose intolerance in the founder strains of the HS colony is mediated by different mechanisms: insulin resistance in WKY and an insulin secretion defect in ACI, and we demonstrate a high degree of variability for measures of insulin resistance and insulin secretion in HS rats. As such, our goal was to use HS rats to fine-map several diabetes-related traits within a region on rat chromosome 1. We measured blood glucose and plasma insulin levels after a glucose tolerance test in 782 male HS rats. Using 97 SSLP markers, we genotyped a 68 Mb region on rat chromosome 1 previously implicated in glucose and insulin regulation. We used linkage disequilibrium mapping by mixed model regression with inferred descent to identify a region from 198.85 to 205.9 that contains one or more quantitative trait loci (QTL) for fasting insulin and a measure of insulin resistance, the quantitative insulin sensitivity check index. This region also encompasses loci identified for fasting glucose and Insulin_AUC (area under the curve). A separate <3 Mb QTL was identified for body weight. Using a novel penalized regression method we then estimated effects of alternative haplotype pairings under each locus. These studies highlight the utility of HS rats for fine-mapping genetic loci involved in the underlying causes of T2D. PMID:22947656

Genome wide association studies for body conformation traits in the Chinese Holstein cattle population

DEFF Research Database (Denmark)

Wu, Xiaoping; Fang, Ming; Liu, Lin

2013-01-01

.Results: The Illumina BovineSNP50 BeadChip was used to identify single nucleotide polymorphisms (SNPs) that are associated with body conformation traits. A least absolute shrinkage and selection operator (LASSO) was applied to detect multiple SNPs simultaneously for 29 body conformation traits with 1,314 Chinese...... Holstein cattle and 52,166 SNPs. Totally, 59 genome-wide significant SNPs associated with 26 conformation traits were detected by genome-wide association analysis; five SNPs were within previously reported QTL regions (Animal Quantitative Trait Loci (QTL) database) and 11 were very close to the reported...... SNPs. Twenty-two SNPs were located within annotated gene regions, while the remainder were 0.6-826 kb away from known genes. Some of the genes had clear biological functions related to conformation traits. By combining information about the previously reported QTL regions and the biological functions...

Bovine Mastitis Resistance: Novel Quantitative Trait Loci and the Role of Bovine Mammary Epithelial Cells

OpenAIRE

Kurz, Jacqueline P.

2018-01-01

Bovine mastitis, or inflammation of the mammary gland, has substantial economic and animal welfare implications. A genetic basis for mastitis resistance traits is recognized and can be used to guide selective breeding programs. The discovery of regions of the genome associated with mastitis resistance, and knowledge of the underlying molecular mechanisms responsible, can facilitate development of efficient mastitis control and therapeutic strategies. The objectives of this dissertation resear...

Evaluation and Exploration of Favorable QTL Alleles for Salt Stress Related Traits in Cotton Cultivars (G. hirsutum L.)

Science.gov (United States)

Du, Lei; Cai, Caiping; Wu, Shuang; Zhang, Fang; Hou, Sen; Guo, Wangzhen

2016-01-01

Soil salinization is one of the major problems in global agricultural production. Cotton is a pioneer crop with regard to salt stress tolerance, and can be used for saline-alkali land improvement. The large-scale detection of salt tolerance traits in cotton accessions, and the identification of elite quantitative trait loci (QTLs)/genes for salt-tolerance have been very important in salt tolerance breeding. Here, 43 advanced salt-tolerant and 31 highly salt-sensitive cultivars were detected by analyzing ten salt tolerance related traits in 304 upland cotton cultivars. Among them, 11 advanced salt-tolerance and eight highly salt-sensitive cultivars were consistent with previously reported results. Association analysis of ten salt-tolerance related traits and 145 SSRs was performed, and a total of 95 significant associations were detected; 17, 41, and 37 of which were associated with germinative index, seedling stage physiological index, and four seedling stage biochemical indexes, respectively. Of these associations, 20 SSR loci were simultaneously associated with two or more traits. Furthermore, we detected 117 elite alleles associated with salt-tolerance traits, 4 of which were reported previously. Among these loci, 44 (37.60%) were rare alleles with a frequency of less than 5%, 6 only existed in advanced salt-tolerant cultivars, and 2 only in highly salt-sensitive cultivars. As a result, 13 advanced salt-tolerant cultivars were selected to assemble the optimal cross combinations by computer simulation for the development of salt-tolerant accessions. This study lays solid foundations for further improvements in cotton salt-tolerance by referencing elite germplasms, alleles associated with salt-tolerance traits, and optimal crosses. PMID:26943816

Two Novel SNPs of PPARγ Significantly Affect Weaning Growth Traits of Nanyang Cattle.

Science.gov (United States)

Huang, Jieping; Chen, Ningbo; Li, Xin; An, Shanshan; Zhao, Minghui; Sun, Taihong; Hao, Ruijie; Ma, Yun

2018-01-02

Peroxisome-proliferator-activated receptor gamma (PPARγ) is a key transcription factor that controls adipocyte differentiation and energy in mammals. Therefore, PPARγ is a potential factor influencing animal growth traits. This study primarily evaluates PPARγ as candidate gene for growth traits of cattle and identifies potential molecular marker for cattle breeding. Per previous studies, PPARγ mRNA was mainly expressed at extremely high levels in adipose tissues as shown by quantitative real-time polymerase chain reaction analysis. Three novel SNPs of the bovine PPARγ gene were identified in 514 individuals from six Chinese cattle breeds: SNP1 (AC_000179.1 g.57386668 C > G) in intron 2 and SNP2 (AC_000179.1 g.57431964 C > T) and SNP3 (AC_000179.1 g.57431994 T > C) in exon 7. The present study also investigated genetic characteristics of these SNP loci in six populations. Association analysis showed that SNP1 and SNP3 loci significantly affect weaning growth traits, especially body weight of Nanyang cattle. These results revealed that SNP1 and SNP3 are potential molecular markers for cattle breeding.

Protein quantitative trait locus study in obesity during weight-loss identifies a leptin regulator

DEFF Research Database (Denmark)

Carayol, Jérôme; Chabert, Christian; Di Cara, Alessandro

2017-01-01

of an organism. Proteome analysis especially can provide new insights into the molecular mechanisms of complex traits like obesity. The role of genetic variation in determining protein level variation has not been assessed in obesity. To address this, we design a large-scale protein quantitative trait locus (p...

Genome-wide meta-analysis of myopia and hyperopia provides evidence for replication of 11 loci.

Directory of Open Access Journals (Sweden)

Claire L Simpson

Full Text Available Refractive error (RE is a complex, multifactorial disorder characterized by a mismatch between the optical power of the eye and its axial length that causes object images to be focused off the retina. The two major subtypes of RE are myopia (nearsightedness and hyperopia (farsightedness, which represent opposite ends of the distribution of the quantitative measure of spherical refraction. We performed a fixed effects meta-analysis of genome-wide association results of myopia and hyperopia from 9 studies of European-derived populations: AREDS, KORA, FES, OGP-Talana, MESA, RSI, RSII, RSIII and ERF. One genome-wide significant region was observed for myopia, corresponding to a previously identified myopia locus on 8q12 (p = 1.25×10(-8, which has been reported by Kiefer et al. as significantly associated with myopia age at onset and Verhoeven et al. as significantly associated to mean spherical-equivalent (MSE refractive error. We observed two genome-wide significant associations with hyperopia. These regions overlapped with loci on 15q14 (minimum p value = 9.11×10(-11 and 8q12 (minimum p value 1.82×10(-11 previously reported for MSE and myopia age at onset. We also used an intermarker linkage- disequilibrium-based method for calculating the effective number of tests in targeted regional replication analyses. We analyzed myopia (which represents the closest phenotype in our data to the one used by Kiefer et al. and showed replication of 10 additional loci associated with myopia previously reported by Kiefer et al. This is the first replication of these loci using myopia as the trait under analysis. "Replication-level" association was also seen between hyperopia and 12 of Kiefer et al.'s published loci. For the loci that show evidence of association to both myopia and hyperopia, the estimated effect of the risk alleles were in opposite directions for the two traits. This suggests that these loci are important contributors to variation of

Searching for an Accurate Marker-Based Prediction of an Individual Quantitative Trait in Molecular Plant Breeding

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Yong-Bi Fu

2017-07-01

Full Text Available Molecular plant breeding with the aid of molecular markers has played an important role in modern plant breeding over the last two decades. Many marker-based predictions for quantitative traits have been made to enhance parental selection, but the trait prediction accuracy remains generally low, even with the aid of dense, genome-wide SNP markers. To search for more accurate trait-specific prediction with informative SNP markers, we conducted a literature review on the prediction issues in molecular plant breeding and on the applicability of an RNA-Seq technique for developing function-associated specific trait (FAST SNP markers. To understand whether and how FAST SNP markers could enhance trait prediction, we also performed a theoretical reasoning on the effectiveness of these markers in a trait-specific prediction, and verified the reasoning through computer simulation. To the end, the search yielded an alternative to regular genomic selection with FAST SNP markers that could be explored to achieve more accurate trait-specific prediction. Continuous search for better alternatives is encouraged to enhance marker-based predictions for an individual quantitative trait in molecular plant breeding.

Searching for an Accurate Marker-Based Prediction of an Individual Quantitative Trait in Molecular Plant Breeding

Science.gov (United States)

Fu, Yong-Bi; Yang, Mo-Hua; Zeng, Fangqin; Biligetu, Bill

2017-01-01

Molecular plant breeding with the aid of molecular markers has played an important role in modern plant breeding over the last two decades. Many marker-based predictions for quantitative traits have been made to enhance parental selection, but the trait prediction accuracy remains generally low, even with the aid of dense, genome-wide SNP markers. To search for more accurate trait-specific prediction with informative SNP markers, we conducted a literature review on the prediction issues in molecular plant breeding and on the applicability of an RNA-Seq technique for developing function-associated specific trait (FAST) SNP markers. To understand whether and how FAST SNP markers could enhance trait prediction, we also performed a theoretical reasoning on the effectiveness of these markers in a trait-specific prediction, and verified the reasoning through computer simulation. To the end, the search yielded an alternative to regular genomic selection with FAST SNP markers that could be explored to achieve more accurate trait-specific prediction. Continuous search for better alternatives is encouraged to enhance marker-based predictions for an individual quantitative trait in molecular plant breeding. PMID:28729875

Mapping of quantitative trait locus (QTLs that contribute to germination and early seedling drought tolerance in the interspecific cross Setaria italica×Setaria viridis.

Directory of Open Access Journals (Sweden)

Lufeng Qie

Full Text Available Drought tolerance is an important breeding target for enhancing the yields of grain crop species in arid and semi-arid regions of the world. Two species of Setaria, domesticated foxtail millet (S. italica and its wild ancestor green foxtail (S. viridis are becoming widely adopted as models for functional genomics studies in the Panicoid grasses. In this study, the genomic regions controlling germination and early seedling drought tolerance in Setaria were identified using 190 F7 lines derived from a cross between Yugu1, a S. italica cultivar developed in China, and a wild S. viridis genotype collected from Uzbekistan. Quantitative trait loci were identified which contribute to a number of traits including promptness index, radical root length, coleoptile length and lateral root number at germinating stage and seedling survival rate was characterized by the ability of desiccated seedlings to revive after rehydration. A genetic map with 128 SSR markers which spans 1293.9 cM with an average of 14 markers per linkage group of the 9 linkage groups was constructed. A total of eighteen QTLs were detected which included nine that explained over 10% of the phenotypic variance for a given trait. Both the wild green foxtail genotype and the foxtail millet cultivar contributed the favorite alleles for traits detected in this trial, indicating that wild Setaria viridis populations may serve as a reservoir for novel stress tolerance alleles which could be employed in foxtail millet breeding.

Mapping of quantitative trait locus (QTLs) that contribute to germination and early seedling drought tolerance in the interspecific cross Setaria italica×Setaria viridis.

Science.gov (United States)

Qie, Lufeng; Jia, Guanqing; Zhang, Wenying; Schnable, James; Shang, Zhonglin; Li, Wei; Liu, Binhui; Li, Mingzhe; Chai, Yang; Zhi, Hui; Diao, Xianmin

2014-01-01

Drought tolerance is an important breeding target for enhancing the yields of grain crop species in arid and semi-arid regions of the world. Two species of Setaria, domesticated foxtail millet (S. italica) and its wild ancestor green foxtail (S. viridis) are becoming widely adopted as models for functional genomics studies in the Panicoid grasses. In this study, the genomic regions controlling germination and early seedling drought tolerance in Setaria were identified using 190 F7 lines derived from a cross between Yugu1, a S. italica cultivar developed in China, and a wild S. viridis genotype collected from Uzbekistan. Quantitative trait loci were identified which contribute to a number of traits including promptness index, radical root length, coleoptile length and lateral root number at germinating stage and seedling survival rate was characterized by the ability of desiccated seedlings to revive after rehydration. A genetic map with 128 SSR markers which spans 1293.9 cM with an average of 14 markers per linkage group of the 9 linkage groups was constructed. A total of eighteen QTLs were detected which included nine that explained over 10% of the phenotypic variance for a given trait. Both the wild green foxtail genotype and the foxtail millet cultivar contributed the favorite alleles for traits detected in this trial, indicating that wild Setaria viridis populations may serve as a reservoir for novel stress tolerance alleles which could be employed in foxtail millet breeding.

Genome-wide association mapping of root traits in a japonica rice panel.

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Brigitte Courtois

Full Text Available Rice is a crop prone to drought stress in upland and rainfed lowland ecosystems. A deep root system is recognized as the best drought avoidance mechanism. Genome-wide association mapping offers higher resolution for locating quantitative trait loci (QTLs than QTL mapping in biparental populations. We performed an association mapping study for root traits using a panel of 167 japonica accessions, mostly of tropical origin. The panel was genotyped at an average density of one marker per 22.5 kb using genotyping by sequencing technology. The linkage disequilibrium in the panel was high (r(2>0.6, on average, for 20 kb mean distances between markers. The plants were grown in transparent 50 cm × 20 cm × 2 cm Plexiglas nailboard sandwiches filled with 1.5 mm glass beads through which a nutrient solution was circulated. Root system architecture and biomass traits were measured in 30-day-old plants. The panel showed a moderate to high diversity in the various traits, particularly for deep (below 30 cm depth root mass and the number of deep roots. Association analyses were conducted using a mixed model involving both population structure and kinship to control for false positives. Nineteen associations were significant at P<1e-05, and 78 were significant at P<1e-04. The greatest numbers of significant associations were detected for deep root mass and the number of deep roots, whereas no significant associations were found for total root biomass or deep root proportion. Because several QTLs for different traits were co-localized, 51 unique loci were detected; several co-localized with meta-QTLs for root traits, but none co-localized with rice genes known to be involved in root growth. Several likely candidate genes were found in close proximity to these loci. Additional work is necessary to assess whether these markers are relevant in other backgrounds and whether the genes identified are robust candidates.

Characterization of Novel Gene Yr79 and Four Additional Quantitative Trait Loci for All-Stage and High-Temperature Adult-Plant Resistance to Stripe Rust in Spring Wheat PI 182103.

Science.gov (United States)

Feng, Junyan; Wang, Meinan; See, Deven R; Chao, Shiaoman; Zheng, Youliang; Chen, Xianming

2018-06-01

Stripe rust, caused by Puccinia striiformis f. sp. tritici, is an important disease of wheat worldwide. Exploring new resistance genes is essential for breeding resistant wheat cultivars. PI 182103, a spring wheat landrace originally from Pakistan, has shown a high level of resistance to stripe rust in fields for many years, but genes for resistance to stripe rust in the variety have not been studied. To map the resistance gene(s) in PI 182103, 185 recombinant inbred lines (RILs) were developed from a cross with Avocet Susceptible (AvS). The RIL population was genotyped with simple sequence repeat (SSR) and single nucleotide polymorphism markers and tested with races PST-100 and PST-114 at the seedling stage under controlled greenhouse conditions and at the adult-plant stage in fields at Pullman and Mt. Vernon, Washington under natural infection by the stripe rust pathogen in 2011, 2012, and 2013. A total of five quantitative trait loci (QTL) were detected. QyrPI182103.wgp-2AS and QyrPI182103.wgp-3AL were detected at the seedling stage, QyrPI182103.wgp-4DL was detected only in Mt. Vernon field tests, and QyrPI182103.wgp-5BS was detected in both seedling and field tests. QyrPI182103.wgp-7BL was identified as a high-temperature adult-plant resistance gene and detected in all field tests. Interactions among the QTL were mostly additive, but some negative interactions were detected. The 7BL QTL was mapped in chromosomal bin 7BL 0.40 to 0.45 and identified as a new gene, permanently designated as Yr79. SSR markers Xbarc72 and Xwmc335 flanking the Yr79 locus were highly polymorphic in various wheat genotypes, indicating that the molecular markers are useful for incorporating the new gene for potentially durable stripe rust resistance into new wheat cultivars.

Identification of Loci Associated with Drought Resistance Traits in Heterozygous Autotetraploid Alfalfa (Medicago sativa L.) Using Genome-Wide Association Studies with Genotyping by Sequencing.

Science.gov (United States)

Zhang, Tiejun; Yu, Long-Xi; Zheng, Ping; Li, Yajun; Rivera, Martha; Main, Dorrie; Greene, Stephanie L

2015-01-01

Drought resistance is an important breeding target for enhancing alfalfa productivity in arid and semi-arid regions. Identification of genes involved in drought tolerance will facilitate breeding for improving drought resistance and water use efficiency in alfalfa. Our objective was to use a diversity panel of alfalfa accessions comprised of 198 cultivars and landraces to identify genes involved in drought tolerance. The panel was selected from the USDA-ARS National Plant Germplasm System alfalfa collection and genotyped using genotyping by sequencing. A greenhouse procedure was used for phenotyping two important traits associated with drought tolerance: drought resistance index (DRI) and relative leaf water content (RWC). Marker-trait association identified nineteen and fifteen loci associated with DRI and RWC, respectively. Alignments of target sequences flanking to the resistance loci against the reference genome of M. truncatula revealed multiple chromosomal locations. Markers associated with DRI are located on all chromosomes while markers associated with RWC are located on chromosomes 1, 2, 3, 4, 5, 6 and 7. Co-localizations of significant markers between DRI and RWC were found on chromosomes 3, 5 and 7. Most loci associated with DRI in this work overlap with the reported QTLs associated with biomass under drought in alfalfa. Additional significant markers were targeted to several contigs with unknown chromosomal locations. BLAST search using their flanking sequences revealed homology to several annotated genes with functions in stress tolerance. With further validation, these markers may be used for marker-assisted breeding new alfalfa varieties with drought resistance and enhanced water use efficiency.

Modeling heterogeneous (co)variances from adjacent-SNP groups improves genomic prediction for milk protein composition traits

DEFF Research Database (Denmark)

Gebreyesus, Grum; Lund, Mogens Sandø; Buitenhuis, Albert Johannes

2017-01-01

Accurate genomic prediction requires a large reference population, which is problematic for traits that are expensive to measure. Traits related to milk protein composition are not routinely recorded due to costly procedures and are considered to be controlled by a few quantitative trait loci...... of large effect. The amount of variation explained may vary between regions leading to heterogeneous (co)variance patterns across the genome. Genomic prediction models that can efficiently take such heterogeneity of (co)variances into account can result in improved prediction reliability. In this study, we...... developed and implemented novel univariate and bivariate Bayesian prediction models, based on estimates of heterogeneous (co)variances for genome segments (BayesAS). Available data consisted of milk protein composition traits measured on cows and de-regressed proofs of total protein yield derived for bulls...

Strategic marker selection to detect quantitative trait loci in chicken Seleção estratégica de marcadores para detecção locos para características quantitativas em aves

Directory of Open Access Journals (Sweden)

Deborah Clea Ruy

2005-04-01

Full Text Available Selective genotyping for a certain trait in individuals with extreme phenotypes contributes sufficient information to determine linkage between molecular markers and quantitative trait loci (QTL. In this experiment an F2 population, developed by crossing males from a broiler line with females from a layer line, was employed to detect QTL on chromosomes 3 and 5. Twenty-eight performance and carcass traits were measured in F2 offspring, and phenotypic correlations between traits were calculated. Body weight at 42 days (BW42 presented the greatest positive correlations with most other traits, with correlation between body weights at 35 and 41 days, weight gain between birth and 35, 41 and 42 days, as well as weights of carcass and some body parts superior to 0.8. One hundred-and-seventy F2 offspring, representing the top (4.5% and the bottom (4.5% of a normal distribution curve of BW42, were selected with equal proportions of males and females, and within dam family. Samples were genotyped for 19 informative markers on chromosome 3, and 11 markers on chromosome 5. Marker allelic frequencies of phenotypic groups with high and low BW42 were compared with a chi-square test. Four regions on chromosome 3 and three regions on chromosome 5 had markers that were suggestively associated with BW42 (P A genotipagem seletiva de indivíduos com fenótipos extremos para uma determinada característica contribui com informação suficiente para determinar a ligação entre marcadores moleculares e locos para características quantitativas (QTL. Neste estudo uma população F2, formada a partir do cruzamento de uma linha parental de aves para corte com uma linha de postura foi empregada para obtenção de medidas fenotípicas e genotipagem por marcadores microssatélites, posicionados nos cromossomos 3 e 5. Foram medidas 28 características de desempenho e carcaça e determinada a correlação fenotípica entre elas. A característica peso vivo aos 42 dias (BW42

Quantitative Linkage for Autism Spectrum Disorders Symptoms in Attention-Deficit/Hyperactivity Disorder: Significant Locus on Chromosome 7q11

Science.gov (United States)

Nijmeijer, Judith S.; Arias-Vásquez, Alejandro; Rommelse, Nanda N.; Altink, Marieke E.; Buschgens, Cathelijne J.; Fliers, Ellen A.; Franke, Barbara; Minderaa, Ruud B.; Sergeant, Joseph A.; Buitelaar, Jan K.; Hoekstra, Pieter J.; Hartman, Catharina A.

2014-01-01

We studied 261 ADHD probands and 354 of their siblings to assess quantitative trait loci associated with autism spectrum disorder symptoms (as measured by the Children's Social Behavior Questionnaire (CSBQ) using a genome-wide linkage approach, followed by locus-wide association analysis. A genome-wide significant locus for the CSBQ subscale…

Signatures of positive selection: from selective sweeps at individual loci to subtle allele frequency changes in polygenic adaptation.

Science.gov (United States)

Stephan, Wolfgang

2016-01-01

In the past 15 years, numerous methods have been developed to detect selective sweeps underlying adaptations. These methods are based on relatively simple population genetic models, including one or two loci at which positive directional selection occurs, and one or two marker loci at which the impact of selection on linked neutral variation is quantified. Information about the phenotype under selection is not included in these models (except for fitness). In contrast, in the quantitative genetic models of adaptation, selection acts on one or more phenotypic traits, such that a genotype-phenotype map is required to bridge the gap to population genetics theory. Here I describe the range of population genetic models from selective sweeps in a panmictic population of constant size to evolutionary traffic when simultaneous sweeps at multiple loci interfere, and I also consider the case of polygenic selection characterized by subtle allele frequency shifts at many loci. Furthermore, I present an overview of the statistical tests that have been proposed based on these population genetics models to detect evidence for positive selection in the genome. © 2015 John Wiley & Sons Ltd.

Genetic dissection of hybrid incompatibilities between Drosophila simulans and D. mauritiana. II. Mapping hybrid male sterility loci on the third chromosome.

Science.gov (United States)

Tao, Yun; Zeng, Zhao-Bang; Li, Jian; Hartl, Daniel L; Laurie, Cathy C

2003-08-01

Hybrid male sterility (HMS) is a rapidly evolving mechanism of reproductive isolation in Drosophila. Here we report a genetic analysis of HMS in third-chromosome segments of Drosophila mauritiana that were introgressed into a D. simulans background. Qualitative genetic mapping was used to localize 10 loci on 3R and a quantitative trait locus (QTL) procedure (multiple-interval mapping) was used to identify 19 loci on the entire chromosome. These genetic incompatibilities often show dominance and complex patterns of epistasis. Most of the HMS loci have relatively small effects and generally at least two or three of them are required to produce complete sterility. Only one small region of the third chromosome of D. mauritiana by itself causes a high level of infertility when introgressed into D. simulans. By comparison with previous studies of the X chromosome, we infer that HMS loci are only approximately 40% as dense on this autosome as they are on the X chromosome. These results are consistent with the gradual evolution of hybrid incompatibilities as a by-product of genetic divergence in allopatric populations.

GWAPower: a statistical power calculation software for genome-wide association studies with quantitative traits.

Science.gov (United States)

Feng, Sheng; Wang, Shengchu; Chen, Chia-Cheng; Lan, Lan

2011-01-21

In designing genome-wide association (GWA) studies it is important to calculate statistical power. General statistical power calculation procedures for quantitative measures often require information concerning summary statistics of distributions such as mean and variance. However, with genetic studies, the effect size of quantitative traits is traditionally expressed as heritability, a quantity defined as the amount of phenotypic variation in the population that can be ascribed to the genetic variants among individuals. Heritability is hard to transform into summary statistics. Therefore, general power calculation procedures cannot be used directly in GWA studies. The development of appropriate statistical methods and a user-friendly software package to address this problem would be welcomed. This paper presents GWAPower, a statistical software package of power calculation designed for GWA studies with quantitative traits, where genetic effect is defined as heritability. Based on several popular one-degree-of-freedom genetic models, this method avoids the need to specify the non-centrality parameter of the F-distribution under the alternative hypothesis. Therefore, it can use heritability information directly without approximation. In GWAPower, the power calculation can be easily adjusted for adding covariates and linkage disequilibrium information. An example is provided to illustrate GWAPower, followed by discussions. GWAPower is a user-friendly free software package for calculating statistical power based on heritability in GWA studies with quantitative traits. The software is freely available at: http://dl.dropbox.com/u/10502931/GWAPower.zip.

Genomic expression analysis of rat chromosome 4 for skeletal traits at femoral neck

OpenAIRE

Alam, Imranul; Sun, Qiwei; Liu, Lixiang; Koller, Daniel L.; Liu, Yunlong; Edenberg, Howard J.; Econs, Michael J.; Foroud, Tatiana; Turner, Charles H.

2008-01-01

Hip fracture is the most devastating osteoporotic fracture type with significant morbidity and mortality. Several studies in humans and animal models identified chromosomal regions linked to hip size and bone mass. Previously, we identified that the region of 4q21-q41 on rat chromosome (Chr) 4 harbors multiple femoral neck quantitative trait loci (QTLs) in inbred Fischer 344 (F344) and Lewis (LEW) rats. The purpose of this study is to identify the candidate genes for femoral neck structure an...

Systematic Evaluation of Pleiotropy Identifies 6 Further Loci Associated With Coronary Artery Disease

NARCIS (Netherlands)

Webb, Thomas R.; Erdmann, Jeanette; Stirrups, Kathleen E.; Stitziel, Nathan O.; Masca, Nicholas G. D.; Jansen, Henning; Kanoni, Stavroula; Nelson, Christopher P.; Ferrario, Paola G.; König, Inke R.; Eicher, John D.; Johnson, Andrew D.; Hamby, Stephen E.; Betsholtz, Christer; Ruusalepp, Arno; Franzén, Oscar; Schadt, Eric E.; Björkegren, Johan L. M.; Weeke, Peter E.; Auer, Paul L.; Schick, Ursula M.; Lu, Yingchang; Zhang, He; Dube, Marie-Pierre; Goel, Anuj; Farrall, Martin; Peloso, Gina M.; Won, Hong-Hee; Do, Ron; van Iperen, Erik; Kruppa, Jochen; Mahajan, Anubha; Scott, Robert A.; Willenborg, Christina; Braund, Peter S.; van Capelleveen, Julian C.; Doney, Alex S. F.; Donnelly, Louise A.; Asselta, Rosanna; Merlini, Pier A.; Duga, Stefano; Marziliano, Nicola; Denny, Josh C.; Shaffer, Christian; El-Mokhtari, Nour Eddine; Franke, Andre; Heilmann, Stefanie; Hengstenberg, Christian; Hoffmann, Per; Holmen, Oddgeir L.; Hveem, Kristian; Jansson, Jan-Håkan; Jöckel, Karl-Heinz; Kessler, Thorsten; Kriebel, Jennifer; Laugwitz, Karl L.; Marouli, Eirini; Martinelli, Nicola; McCarthy, Mark I.; van Zuydam, Natalie R.; Meisinger, Christa; Esko, Tõnu; Mihailov, Evelin; Escher, Stefan A.; Alver, Maris; Moebus, Susanne; Morris, Andrew D.; Virtamo, Jarma; Nikpay, Majid; Olivieri, Oliviero; Provost, Sylvie; AlQarawi, Alaa; Robertson, Neil R.; Akinsansya, Karen O.; Reilly, Dermot F.; Vogt, Thomas F.; Yin, Wu; Asselbergs, Folkert W.; Kooperberg, Charles; Jackson, Rebecca D.; Stahl, Eli; Müller-Nurasyid, Martina; Strauch, Konstantin; Varga, Tibor V.; Waldenberger, Melanie; Zeng, Lingyao; Chowdhury, Rajiv; Salomaa, Veikko; Ford, Ian; Jukema, J. Wouter; Amouyel, Philippe; Kontto, Jukka; Nordestgaard, Børge G.; Ferrières, Jean; Saleheen, Danish; Sattar, Naveed; Surendran, Praveen; Wagner, Aline; Young, Robin; Howson, Joanna M. M.; Butterworth, Adam S.; Danesh, John; Ardissino, Diego; Bottinger, Erwin P.; Erbel, Raimund; Franks, Paul W.; Girelli, Domenico; Hall, Alistair S.; Hovingh, G. Kees; Kastrati, Adnan; Lieb, Wolfgang; Meitinger, Thomas; Kraus, William E.; Shah, Svati H.; McPherson, Ruth; Orho-Melander, Marju; Melander, Olle; Metspalu, Andres; Palmer, Colin N. A.; Peters, Annette; Rader, Daniel J.; Reilly, Muredach P.; Loos, Ruth J. F.; Reiner, Alex P.; Roden, Dan M.; Tardif, Jean-Claude; Thompson, John R.; Wareham, Nicholas J.; Watkins, Hugh; Willer, Cristen J.; Samani, Nilesh J.; Schunkert, Heribert; Deloukas, Panos; Kathiresan, Sekar

2017-01-01

Genome-wide association studies have so far identified 56 loci associated with risk of coronary artery disease (CAD). Many CAD loci show pleiotropy; that is, they are also associated with other diseases or traits. This study sought to systematically test if genetic variants identified for non-CAD

Qualitative trait loci analysis for seed yield and component traits in ...

African Journals Online (AJOL)

VANITHA

2014-02-05

Feb 5, 2014 ... improvement, plant breeders deal with several qualitative traits. However, the most ... Table 1. Characteristics of parental lines. Character ..... Sunflower, an agronomic crop, adapted to fundamental and applied biotechnology.

A method to prioritize quantitative traits and individuals for sequencing in family-based studies.

Directory of Open Access Journals (Sweden)

Kaanan P Shah

Full Text Available Owing to recent advances in DNA sequencing, it is now technically feasible to evaluate the contribution of rare variation to complex traits and diseases. However, it is still cost prohibitive to sequence the whole genome (or exome of all individuals in each study. For quantitative traits, one strategy to reduce cost is to sequence individuals in the tails of the trait distribution. However, the next challenge becomes how to prioritize traits and individuals for sequencing since individuals are often characterized for dozens of medically relevant traits. In this article, we describe a new method, the Rare Variant Kinship Test (RVKT, which leverages relationship information in family-based studies to identify quantitative traits that are likely influenced by rare variants. Conditional on nuclear families and extended pedigrees, we evaluate the power of the RVKT via simulation. Not unexpectedly, the power of our method depends strongly on effect size, and to a lesser extent, on the frequency of the rare variant and the number and type of relationships in the sample. As an illustration, we also apply our method to data from two genetic studies in the Old Order Amish, a founder population with extensive genealogical records. Remarkably, we implicate the presence of a rare variant that lowers fasting triglyceride levels in the Heredity and Phenotype Intervention (HAPI Heart study (p = 0.044, consistent with the presence of a previously identified null mutation in the APOC3 gene that lowers fasting triglyceride levels in HAPI Heart study participants.

Genes and quality trait loci (QTLs) associated with firmness in Malus x domestica

KAUST Repository

Marondedze, Claudius; Thomas, Ludivine

2013-01-01

, crunchiness and crispness. Fruit firmness is affected by the inheritance of alleles at multiple loci and their possible interactions with the environment. Identification of these loci is key for the determination of genetic candidate markers that can

Mapping of quantitative trait loci for thermosensitive genic male sterility in indica rice Mapeamento de controladores de caracteres quantitativos de macho-esterilidade gênica termossensível em arroz indica

Directory of Open Access Journals (Sweden)

Antonio Alberto Neves de Alcochete

2005-12-01

Full Text Available The objective of this work was to select and use microsatellite markers, to map genomic regions associated with the genetic control of thermosensitive genic male sterility (TGMS in rice. An F2 population, derived from the cross between fertile and TGMS indica lines, was used to construct a microsatellite-based genetic map of rice. The TGMS phenotype showed a continuous variation in the segregant population. A low level of segregation distortion was detected in the F2 (14.65%, whose cause was found to be zygotic selection. There was no evidence suggesting a cause-effect relationship between zygotic selection and the control of TGMS in this cross. A linkage map comprising 1,213.3 cM was constructed based on the segregation data of the F2 population. Ninety-five out of 116 microsatellite polymorphic markers were assembled into 11 linkage groups, with an average of 12.77 cM between two adjacent marker loci. The phenotypic and genotypic data allowed for the identification of three new quantitative trait loci (QTL for thermosensitive genic male sterility in indica rice. Two of the QTL were mapped on chromosomes that, so far, have not been associated with the genetic control of the TGMS trait (chromosomes 1 and 12. The third QTL was mapped on chromosome 7, where a TGMS locus (tms2 has recently been mapped. Allelic tests will have to be developed, in order to clarify if the two regions are the same or not.O objetivo deste estudo foi selecionar e utilizar marcadores microssatélites, para mapear as regi��es genômicas associadas ao controle genético de macho-esterilidade termossensível (TGMS em arroz. Uma popu- lação F2, derivada do cruzamento entre linhagens indica fértil e TGMS, foi usada para construir um mapa genético de arroz, baseado em marcadores microssatélites. O fenótipo TGMS analisado apresentou uma variação contínua na população segregante. Um baixo nível de distorção da segregação foi detectado na população segregante

Hundreds of variants clustered in genomic loci and biological pathways affect human height

DEFF Research Database (Denmark)

Lango Allen, Hana; Estrada, Karol; Lettre, Guillaume

2010-01-01

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions...

A high density genetic map and QTL for agronomic and yield traits in Foxtail millet [Setaria italica (L.) P. Beauv].

Science.gov (United States)

Fang, Xiaomei; Dong, Kongjun; Wang, Xiaoqin; Liu, Tianpeng; He, Jihong; Ren, Ruiyu; Zhang, Lei; Liu, Rui; Liu, Xueying; Li, Man; Huang, Mengzhu; Zhang, Zhengsheng; Yang, Tianyu

2016-05-04

Foxtail millet [Setaria italica (L.) P. Beauv.], a crop of historical importance in China, has been adopted as a model crop for studying C-4 photosynthesis, stress biology and biofuel traits. Construction of a high density genetic map and identification of stable quantitative trait loci (QTL) lay the foundation for marker-assisted selection for agronomic traits and yield improvement. A total of 10598 SSR markers were developed according to the reference genome sequence of foxtail millet cultivar 'Yugu1'. A total of 1013 SSR markers showing polymorphism between Yugu1 and Longgu7 were used to genotype 167 individuals from a Yugu1 × Longgu7 F2 population, and a high density genetic map was constructed. The genetic map contained 1035 loci and spanned 1318.8 cM with an average distance of 1.27 cM between adjacent markers. Based on agronomic and yield traits identified in 2 years, 29 QTL were identified for 11 traits with combined analysis and single environment analysis. These QTL explained from 7.0 to 14.3 % of phenotypic variation. Favorable QTL alleles for peduncle length originated from Longgu7 whereas favorable alleles for the other traits originated from Yugu1 except for qLMS6.1. New SSR markers, a high density genetic map and QTL identified for agronomic and yield traits lay the ground work for functional gene mapping, map-based cloning and marker-assisted selection in foxtail millet.

Hundreds of variants clustered in genomic loci and biological pathways affect human height

NARCIS (Netherlands)

H.L. Allen; K. Estrada Gil (Karol); G. Lettre (Guillaume); S.I. Berndt (Sonja); F. Rivadeneira Ramirez (Fernando); C.J. Willer (Cristen); A.U. Jackson (Anne); S. Vedantam (Sailaja); S. Raychaudhuri (Soumya); T. Ferreira (Teresa); A.R. Wood (Andrew); R.J. Weyant (Robert); A.V. Segrè (Ayellet); E.K. Speliotes (Elizabeth); E. Wheeler (Eleanor); N. Soranzo (Nicole); J.H. Park; J. Yang (Joanna); D.F. Gudbjartsson (Daniel); N.L. Heard-Costa (Nancy); J.C. Randall (Joshua); L. Qi (Lu); A.V. Smith (Albert Vernon); R. Mägi (Reedik); T. Pastinen (Tomi); L. Liang (Liming); I.M. Heid (Iris); J. Luan; G. Thorleifsson (Gudmar); T.W. Winkler (Thomas); M.E. Goddard (Michael); K.S. Lo; C. Palmer (Cameron); T. Workalemahu (Tsegaselassie); Y.S. Aulchenko (Yurii); A. Johansson (Åsa); M.C. Zillikens (Carola); M.F. Feitosa (Mary Furlan); T. Esko (Tõnu); T. Johnson (Toby); S. Ketkar (Shamika); P. Kraft (Peter); M. Mangino (Massimo); I. Prokopenko (Inga); D. Absher (Devin); E. Albrecht (Eva); F.D.J. Ernst (Florian); N.L. Glazer (Nicole); C. Hayward (Caroline); J.J. Hottenga (Jouke Jan); K.B. Jacobs (Kevin); J.W. Knowles (Joshua); Z. Kutalik (Zoltán); K.L. Monda (Keri); O. Polasek (Ozren); M. Preuss (Michael); N.W. Rayner (Nigel William); N.R. Robertson (Neil); V. Steinthorsdottir (Valgerdur); J.P. Tyrer (Jonathan); B.F. Voight (Benjamin); F. Wiklund (Fredrik); J. Xu (Jianfeng); J.H. Zhao (Jing Hua); D.R. Nyholt (Dale); N. Pellikka (Niina); M. Perola (Markus); J.R.B. Perry (John); I. Surakka (Ida); M.L. Tammesoo; E.L. Altmaier (Elizabeth); N. Amin (Najaf); T. Aspelund (Thor); T. Bhangale (Tushar); G. Boucher (Gabrielle); D.I. Chasman (Daniel); C. Chen (Constance); L. Coin (Lachlan); M.N. Cooper (Matthew); A.L. Dixon (Anna); Q. Gibson (Quince); E. Grundberg (Elin); K. Hao (Ke); M.J. Junttila (Juhani); R.C. Kaplan (Robert); J. Kettunen (Johannes); I.R. König (Inke); T. Kwan (Tony); R.W. Lawrence (Robert); D.F. Levinson (Douglas); M. Lorentzon (Mattias); B. McKnight (Barbara); A.D. Morris (Andrew); M. Müller (Martina); J.S. Ngwa; S. Purcell (Shaun); S. Rafelt (Suzanne); R.M. Salem (Rany); E. Salvi (Erika); S. Sanna (Serena); J. Shi (Jianxin); U. Sovio (Ulla); J.R. Thompson (John); M.C. Turchin (Michael); L. Vandenput (Liesbeth); D.J. Verlaan (Dominique); V. Vitart (Veronique); C.C. White (Charles); A. Ziegler (Andreas); P. Almgren (Peter); A.J. Balmforth (Anthony); H. Campbell (Harry); L. Citterio (Lorena); A. de Grandi (Alessandro); A. Dominiczak (Anna); J. Duan (Jubao); P. Elliott (Paul); R. Elosua (Roberto); J.G. Eriksson (Johan); N.B. Freimer (Nelson); E.J.C. de Geus (Eco); N. Glorioso (Nicola); S. Haiqing (Shen); A.L. Hartikainen; A.S. Havulinna (Aki); A.A. Hicks (Andrew); J. Hui (Jennie); W. Igl (Wilmar); T. Illig (Thomas); A. Jula (Antti); E. Kajantie (Eero); T.O. Kilpeläinen (Tuomas); M. Koiranen (Markku); I. Kolcic (Ivana); S. Koskinen (Seppo); P. Kovacs (Peter); J. Laitinen (Jaana); J. Liu (Jianjun); M.L. Lokki; A. Marusic (Ana); A. Maschio; T. Meitinger (Thomas); A. Mulas (Antonella); G. Paré (Guillaume); A.N. Parker (Alex); J. Peden (John); A. Petersmann (Astrid); I. Pichler (Irene); K.H. Pietilainen (Kirsi Hannele); A. Pouta (Anneli); M. Ridderstråle (Martin); J.I. Rotter (Jerome); J.G. Sambrook (Jennifer); A.R. Sanders (Alan); C.O. Schmidt (Carsten Oliver); J. Sinisalo (Juha); J.H. Smit (Jan); H.M. Stringham (Heather); G.B. Walters (Bragi); E. Widen (Elisabeth); S.H. Wild (Sarah); G.A.H.M. Willemsen (Gonneke); L. Zagato (Laura); L. Zgaga (Lina); P. Zitting (Paavo); H. Alavere (Helene); M. Farrall (Martin); W.L. McArdle (Wendy); M. Nelis (Mari); M.J. Peters (Marjolein); S. Ripatti (Samuli); J.B.J. van Meurs (Joyce); K.K.H. Aben (Katja); J.S. Beckmann (Jacques); J.P. Beilby (John); R.N. Bergman (Richard); S.M. Bergmann (Sven); F.S. Collins (Francis); D. Cusi (Daniele); M. den Heijer (Martin); G. Eiriksdottir (Gudny); P.V. Gejman (Pablo); A.S. Hall (Alistair); A. Hamsten (Anders); H.V. Huikuri (Heikki); C. Iribarren (Carlos); M. Kähönen (Mika); J. Kaprio (Jaakko); S. Kathiresan (Sekar); L.A.L.M. Kiemeney (Bart); T. Kocher (Thomas); L.J. Launer (Lenore); T. Lehtimäki (Terho); O. Melander (Olle); T.H. Mosley (Thomas); A.W. Musk (Arthur); M.S. Nieminen (Markku); C.J. O'Donnell (Christopher); C. Ohlsson (Claes); B.A. Oostra (Ben); O. Raitakari (Olli); P.M. Ridker (Paul); J.D. Rioux (John); A. Rissanen (Aila); C. Rivolta (Carlo); H. Schunkert (Heribert); A.R. Shuldiner (Alan); D.S. Siscovick (David); M. Stumvoll (Michael); A. Tönjes (Anke); J. Tuomilehto (Jaakko); G.J. van Ommen (Gert); J. Viikari (Jorma); A.C. Heath (Andrew); N.G. Martin (Nicholas); G.W. Montgomery (Grant); M.A. Province (Mike); M.H. Kayser (Manfred); A.M. Arnold (Alice); L.D. Atwood (Larry); E.A. Boerwinkle (Eric); S.J. Chanock (Stephen); P. Deloukas (Panagiotis); C. Gieger (Christian); H. Grönberg (Henrik); A.T. Hattersley (Andrew); C. Hengstenberg (Christian); W. Hoffman (Wolfgang); G.M. Lathrop (Mark); V. Salomaa (Veikko); S. Schreiber (Stefan); M. Uda (Manuela); D. Waterworth (Dawn); A.F. Wright (Alan); T.L. Assimes (Themistocles); I.E. Barroso (Inês); A. Hofman (Albert); K.L. Mohlke (Karen); D.I. Boomsma (Dorret); M. Caulfield (Mark); L.A. Cupples (Adrienne); C.S. Fox (Caroline); V. Gudnason (Vilmundur); U. Gyllensten (Ulf); T.B. Harris (Tamara); R.B. Hayes (Richard); M.R. Järvelin; V. Mooser (Vincent); P. Munroe (Patricia); W.H. Ouwehand (Willem); B.W.J.H. Penninx (Brenda); P.P. Pramstaller (Peter Paul); T. Quertermous (Thomas); I. Rudan (Igor); N.J. Samani (Nilesh); T.D. Spector (Timothy); H. Völzke (Henry); H. Watkins (Hugh); J.F. Wilson (James); L. Groop (Leif); T. Haritunians (Talin); F.B. Hu (Frank); A. Metspalu (Andres); K.E. North (Kari); D. Schlessinger; N.J. Wareham (Nick); D.J. Hunter (David); J.R. O´Connell; D.P. Strachan (David); H.E. Wichmann (Heinz Erich); I.B. Borecki (Ingrid); C.M. van Duijn (Cornelia); E.E. Schadt (Eric); U. Thorsteinsdottir (Unnur); L. Peltonen (Leena Johanna); A.G. Uitterlinden (André); P.M. Visscher (Peter); N. Chatterjee (Nilanjan); J. Erdmann (Jeanette); R.J.F. Loos (Ruth); M. Boehnke (Michael); M.I. McCarthy (Mark); E. Ingelsson (Erik); C.M. Lindgren (Cecilia); G.R. Abecasis (Gonçalo); K. Stefansson (Kari); T.M. Frayling (Timothy); J.N. Hirschhorn (Joel); K.G. Ardlie (Kristin); M.N. Weedon (Michael)

2010-01-01

textabstractMost common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits1, but these typically explain small

Hundreds of variants clustered in genomic loci and biological pathways affect human height

NARCIS (Netherlands)

Allen, Hana Lango; Estrada, Karol; Lettre, Guillaume; Berndt, Sonja I.; Weedon, Michael N.; Rivadeneira, Fernando; Willer, Cristen J.; Jackson, Anne U.; Vedantam, Sailaja; Raychaudhuri, Soumya; Ferreira, Teresa; Wood, Andrew R.; Weyant, Robert J.; Segre, Ayellet V.; Speliotes, Elizabeth K.; Wheeler, Eleanor; Soranzo, Nicole; Park, Ju-Hyun; Yang, Jian; Gudbjartsson, Daniel; Heard-Costa, Nancy L.; Randall, Joshua C.; Qi, Lu; Smith, Albert Vernon; Maegi, Reedik; Pastinen, Tomi; Liang, Liming; Heid, Iris M.; Luan, Jian'an; Thorleifsson, Gudmar; Winkler, Thomas W.; Goddard, Michael E.; Lo, Ken Sin; Palmer, Cameron; Workalemahu, Tsegaselassie; Aulchenko, Yurii S.; Johansson, Asa; Zillikens, M. Carola; Feitosa, Mary F.; Esko, Tonu; Johnson, Toby; Ketkar, Shamika; Kraft, Peter; Mangino, Massimo; Prokopenko, Inga; Absher, Devin; Albrecht, Eva; Ernst, Florian; Zhao, Jing Hua; Chen, Constance

2010-01-01

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits(1), but these typically explain small fractions

Regression Association Analysis of Yield-Related Traits with RAPD Molecular Markers in Pistachio (Pistacia vera L.

Directory of Open Access Journals (Sweden)

Saeid Mirzaei

2017-10-01

Full Text Available Introduction: The pistachio (Pistacia vera, a member of the cashew family, is a small tree originating from Central Asia and the Middle East. The tree produces seeds that are widely consumed as food. Pistacia vera often is confused with other species in the genus Pistacia that are also known as pistachio. These other species can be distinguished by their geographic distributions and their seeds which are much smaller and have a soft shell. Continual advances in crop improvement through plant breeding are driven by the available genetic diversity. Therefore, the recognition and measurement of such diversity is crucial to breeding programs. In the past 20 years, the major effort in plant breeding has changed from quantitative to molecular genetics with emphasis on quantitative trait loci (QTL identification and marker assisted selection (MAS. The germplasm-regression-combined association studies not only allow mapping of genes/QTLs with higher level of confidence, but also allow detection of genes/QTLs, which will otherwise escape detection in linkage-based QTL studies based on the planned populations. The development of the marker-based technology offers a fast, reliable, and easy way to perform multiple regression analysis and comprise an alternative approach to breeding in diverse species of plants. The availability of many makers and morphological traits can help to regression analysis between these markers and morphological traits. Materials and Methods: In this study, 20 genotypes of Pistachio were studied and yield related traits were measured. Young well-expanded leaves were collected for DNA extraction and total genomic DNA was extracted. Genotyping was performed using 15 RAPD primers and PCR amplification products were visualized by gel electrophoresis. The reproducible RAPD fragments were scored on the basis of present (1 or absent (0 bands and a binary matrix constructed using each molecular marker. Association analysis between

Genome-Wide Meta-Analyses of Breast, Ovarian, and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by at Least Two Cancer Types

DEFF Research Database (Denmark)

Kar, Siddhartha P; Beesley, Jonathan; Amin Al Olama, Ali

2016-01-01

UNLABELLED: Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis, but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112...... (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell......-type-specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P cancer meta-analysis. SIGNIFICANCE...

Functional linear models for association analysis of quantitative traits.

Science.gov (United States)

Fan, Ruzong; Wang, Yifan; Mills, James L; Wilson, Alexander F; Bailey-Wilson, Joan E; Xiong, Momiao

2013-11-01

Functional linear models are developed in this paper for testing associations between quantitative traits and genetic variants, which can be rare variants or common variants or the combination of the two. By treating multiple genetic variants of an individual in a human population as a realization of a stochastic process, the genome of an individual in a chromosome region is a continuum of sequence data rather than discrete observations. The genome of an individual is viewed as a stochastic function that contains both linkage and linkage disequilibrium (LD) information of the genetic markers. By using techniques of functional data analysis, both fixed and mixed effect functional linear models are built to test the association between quantitative traits and genetic variants adjusting for covariates. After extensive simulation analysis, it is shown that the F-distributed tests of the proposed fixed effect functional linear models have higher power than that of sequence kernel association test (SKAT) and its optimal unified test (SKAT-O) for three scenarios in most cases: (1) the causal variants are all rare, (2) the causal variants are both rare and common, and (3) the causal variants are common. The superior performance of the fixed effect functional linear models is most likely due to its optimal utilization of both genetic linkage and LD information of multiple genetic variants in a genome and similarity among different individuals, while SKAT and SKAT-O only model the similarities and pairwise LD but do not model linkage and higher order LD information sufficiently. In addition, the proposed fixed effect models generate accurate type I error rates in simulation studies. We also show that the functional kernel score tests of the proposed mixed effect functional linear models are preferable in candidate gene analysis and small sample problems. The methods are applied to analyze three biochemical traits in data from the Trinity Students Study. © 2013 WILEY

Using SNP markers to dissect linkage disequilibrium at a major quantitative trait locus for resistance to the potato cyst nematode Globodera pallida on potato chromosome V.

Science.gov (United States)

Achenbach, Ute; Paulo, Joao; Ilarionova, Evgenyia; Lübeck, Jens; Strahwald, Josef; Tacke, Eckhard; Hofferbert, Hans-Reinhard; Gebhardt, Christiane

2009-02-01

The damage caused by the parasitic root cyst nematode Globodera pallida is a major yield-limiting factor in potato cultivation . Breeding for resistance is facilitated by the PCR-based marker 'HC', which is diagnostic for an allele conferring high resistance against G. pallida pathotype Pa2/3 that has been introgressed from the wild potato species Solanum vernei into the Solanum tuberosum tetraploid breeding pool. The major quantitative trait locus (QTL) controlling this nematode resistance maps on potato chromosome V in a hot spot for resistance to various pathogens including nematodes and the oomycete Phytophthora infestans. An unstructured sample of 79 tetraploid, highly heterozygous varieties and breeding clones was selected based on presence (41 genotypes) or absence (38 genotypes) of the HC marker. Testing the clones for resistance to G. pallida confirmed the diagnostic power of the HC marker. The 79 individuals were genotyped for 100 single nucleotide polymorphisms (SNPs) at 10 loci distributed over 38 cM on chromosome V. Forty-five SNPs at six loci spanning 2 cM in the interval between markers GP21-GP179 were associated with resistance to G. pallida. Based on linkage disequilibrium (LD) between SNP markers, six LD groups comprising between 2 and 18 SNPs were identified. The LD groups indicated the existence of multiple alleles at a single resistance locus or at several, physically linked resistance loci. LD group C comprising 18 SNPs corresponded to the 'HC' marker. LD group E included 16 SNPs and showed an association peak, which positioned one nematode resistance locus physically close to the R1 gene family.

Comparative mapping of quantitative trait loci for tassel-related traits ...

Indian Academy of Sciences (India)

cultivated area and yield in the country (United Nations Food and Agriculture Organization, FAO, .... Gene action was judged according to the criteria of Stuber et al. (1987) ..... of tassel branch number in maize and its implications for a selection.

Quantitative trait loci for rice yield-related traits using recombinant ...

Indian Academy of Sciences (India)

2011-08-19

Aug 19, 2011 ... lated by map-based cloning strategy (Ashikari et al. 2005). ... 2000; Kojima et al. 2002; Doi et al. 2004). ... and PH but also on rice yield (Xue et al. 2008; Yan et al. ..... Cho Y. C., Suh J. P., Choi I. S., Hong H. C., Baek M. K., Kang K. H. et al. .... Yan C. J., Liang G. H., Chen F., Li X., Tang S. Z., Yi C. D. et al.

Evolution of branched regulatory genetic pathways: directional selection on pleiotropic loci accelerates developmental system drift.

Science.gov (United States)

Johnson, Norman A; Porter, Adam H

2007-01-01

Developmental systems are regulated by a web of interacting loci. One common and useful approach in studying the evolution of development is to focus on classes of interacting elements within these systems. Here, we use individual-based simulations to study the evolution of traits controlled by branched developmental pathways involving three loci, where one locus regulates two different traits. We examined the system under a variety of selective regimes. In the case where one branch was under stabilizing selection and the other under directional selection, we observed "developmental system drift": the trait under stabilizing selection showed little phenotypic change even though the loci underlying that trait showed considerable evolutionary divergence. This occurs because the pleiotropic locus responds to directional selection and compensatory mutants are then favored in the pathway under stabilizing selection. Though developmental system drift may be caused by other mechanisms, it seems likely that it is accelerated by the same underlying genetic mechanism as that producing the Dobzhansky-Muller incompatibilities that lead to speciation in both linear and branched pathways. We also discuss predictions of our model for developmental system drift and how different selective regimes affect probabilities of speciation in the branched pathway system.

Inheritance of quantitative traits in opium poppy (Papaver somniferum L.

Directory of Open Access Journals (Sweden)

Yadav H.K.

2011-01-01

Full Text Available Generation mean analysis was carried out using five parameter model on five cross combinations with five generations i.e. parents, F1s, F2s, and F3s randomly selected from partial diallel breeding experiment. The aim of study was to investigate the mode of gene actions involved in the inheritance of quantitative traits viz. days to 50% flowering, plant height, leaves/plant, capsules/plant, capsule size, capsule weight/plant, seed yield/plant and opium yield/plant. C and D scaling test showed the presence of non allelic interaction in the inheritance for all the traits except for plant height, seed yield/plant (ND1001xIS13 and capsule size (NBR5xND1002 which showed non interacting mode of inheritance. In general, the interaction effect together i.e. additive x additive [i] and dominance x dominance [l] found in higher magnitude than the combined main effects of additive [d] and dominance [h] effects for all the traits in all the five crosses. Dominance effect [h] was found pronounced for most of the traits except days to 50% flowering where additive effect [d] was found prevalent. Among the interaction effects dominance x dominance [l] was predominant over additive x additive [i] for all traits in all the five crosses except capsules/plant and capsule size in cross ND1001xNBRI11 and leaves/plant and opium yield/plant in cross NBRI5xND1002. As per sign of dominance (h and dominance x dominance (l duplicate epistasis were noticed for all the traits except plant height and leaves/plant in cross ND1001xUO1285. Potence ratio indicated presence of over dominance for almost all the traits. Substantial amount of realized heterosis, residual heterosis in F2 and F3 progenies and high heritability with moderate to high genetic advance in F2 progeny and significant correlation among important traits in desirable direction were observed. A breeding strategy of diallel selective mating or biparental mating in early segregating generation followed by recurrent

Pollinator choice in Petunia depends on two major genetic Loci for floral scent production.

Science.gov (United States)

Klahre, Ulrich; Gurba, Alexandre; Hermann, Katrin; Saxenhofer, Moritz; Bossolini, Eligio; Guerin, Patrick M; Kuhlemeier, Cris

2011-05-10

Differences in floral traits, such as petal color, scent, morphology, or nectar quality and quantity, can lead to specific interactions with pollinators and may thereby cause reproductive isolation. Petunia provides an attractive model system to study the role of floral characters in reproductive isolation and speciation. The night-active hawkmoth pollinator Manduca sexta relies on olfactory cues provided by Petunia axillaris. In contrast, Petunia exserta, which displays a typical hummingbird pollination syndrome, is devoid of scent. The two species can easily be crossed in the laboratory, which makes it possible to study the genetic basis of the evolution of scent production and the importance of scent for pollinator behavior. In an F2 population derived from an interspecific cross between P. axillaris and P. exserta, we identified two quantitative trait loci (QTL) that define the difference between the two species' ability to produce benzenoid volatiles. One of these loci was identified as the MYB transcription factor ODORANT1. Reciprocal introgressions of scent QTL were used for choice experiments under controlled conditions. These experiments demonstrated that the hawkmoth M. sexta prefers scented plants and that scent determines choice at a short distance. When exposed to conflicting cues of color versus scent, the insects display no preference, indicating that color and scent are equivalent cues. Our results show that scent is an important flower trait that defines plant-pollinator interactions at the level of individual plants. The genetic basis underlying such a major phenotypic difference appears to be relatively simple and may enable rapid loss or gain of scent through hybridization. Copyright © 2011 Elsevier Ltd. All rights reserved.

Systematic Evaluation of Pleiotropy Identifies 6 Further Loci Associated With Coronary Artery Disease

NARCIS (Netherlands)

Webb, Thomas R; Erdmann, Jeanette; Stirrups, Kathleen E; Stitziel, Nathan O; Masca, Nicholas G D; Jansen, Henning; Kanoni, Stavroula; Nelson, Christopher P; Ferrario, Paola G; König, Inke R; Eicher, John D; Johnson, Andrew D; Hamby, Stephen E; Betsholtz, Christer; Ruusalepp, Arno; Franzén, Oscar; Schadt, Eric E; Björkegren, Johan L M; Weeke, Peter E; Auer, Paul L; Schick, Ursula M; Lu, Yingchang; Zhang, He; Dube, Marie-Pierre; Goel, Anuj; Farrall, Martin; Peloso, Gina M; Won, Hong-Hee; Do, Ron; van Iperen, Erik; Kruppa, Jochen; Mahajan, Anubha; Scott, Robert A; Willenborg, Christina; Braund, Peter S; van Capelleveen, Julian C; Doney, Alex S F; Donnelly, Louise A; Asselta, Rosanna; Merlini, Pier A; Duga, Stefano; Marziliano, Nicola; Denny, Josh C; Shaffer, Christian; El-Mokhtari, Nour Eddine; Franke, Andre; Heilmann, Stefanie; Hengstenberg, Christian; Hoffmann, Per; Holmen, Oddgeir L; Hveem, Kristian; Jansson, Jan-Håkan; Jöckel, Karl-Heinz; Kessler, Thorsten; Kriebel, Jennifer; Laugwitz, Karl L; Marouli, Eirini; Martinelli, Nicola; McCarthy, Mark I; Van Zuydam, Natalie R; Meisinger, Christa; Esko, Tõnu; Mihailov, Evelin; Escher, Stefan A; Alver, Maris; Moebus, Susanne; Morris, Andrew D; Virtamo, Jarma; Nikpay, Majid; Olivieri, Oliviero; Provost, Sylvie; AlQarawi, Alaa; Robertson, Neil R; Akinsansya, Karen O; Reilly, Dermot F; Vogt, Thomas F; Yin, Wu; Asselbergs, Folkert W; Kooperberg, Charles; Jackson, Rebecca D; Stahl, Eli; Müller-Nurasyid, Martina; Strauch, Konstantin; Varga, Tibor V; Waldenberger, Melanie; Zeng, Lingyao; Chowdhury, Rajiv; Salomaa, Veikko; Ford, Ian; Jukema, J Wouter; Amouyel, Philippe; Kontto, Jukka; Nordestgaard, Børge G; Ferrières, Jean; Saleheen, Danish; Sattar, Naveed; Surendran, Praveen; Wagner, Aline; Young, Robin; Howson, Joanna M M; Butterworth, Adam S; Danesh, John; Ardissino, Diego; Bottinger, Erwin P; Erbel, Raimund; Franks, Paul W; Girelli, Domenico; Hall, Alistair S; Hovingh, G Kees; Kastrati, Adnan; Lieb, Wolfgang; Meitinger, Thomas; Kraus, William E; Shah, Svati H; McPherson, Ruth; Orho-Melander, Marju; Melander, Olle; Metspalu, Andres; Palmer, Colin N A; Peters, Annette; Rader, Daniel J; Reilly, Muredach P; Loos, Ruth J F; Reiner, Alex P; Roden, Dan M; Tardif, Jean-Claude; Thompson, John R; Wareham, Nicholas J; Watkins, Hugh; Willer, Cristen J; Samani, Nilesh J; Schunkert, Heribert; Deloukas, Panos; Kathiresan, Sekar

2017-01-01

BACKGROUND: Genome-wide association studies have so far identified 56 loci associated with risk of coronary artery disease (CAD). Many CAD loci show pleiotropy; that is, they are also associated with other diseases or traits. OBJECTIVES: This study sought to systematically test if genetic variants

Comparative mapping of Phytophthora resistance loci in pepper germplasm: evidence for conserved resistance loci across Solanaceae and for a large genetic diversity.

Science.gov (United States)

Thabuis, A; Palloix, A; Pflieger, S; Daubèze, A-M; Caranta, C; Lefebvre, V

2003-05-01

Phytophthora capsici Leonian, known as the causal agent of the stem, collar and root rot, is one of the most serious problems limiting the pepper crop in many areas in the world. Genetic resistance to the parasite displays complex inheritance. Quantitative trait locus (QTL) analysis was performed in three intraspecific pepper populations, each involving an unrelated resistant accession. Resistance was evaluated by artificial inoculations of roots and stems, allowing the measurement of four components involved in different steps of the plant-pathogen interaction. The three genetic maps were aligned using common markers, which enabled the detection of QTLs involved in each resistance component and the comparison of resistance factors existing among the three resistant accessions. The major resistance factor was found to be common to the three populations. Another resistance factor was found conserved between two populations, the others being specific to a single cross. This comparison across intraspecific germplasm revealed a large variability for quantitative resistance loci to P. capsici. It also provided insights both into the allelic relationships between QTLs across pepper germplasm and for the comparative mapping of resistance factors across the Solanaceae.

RAS1, a quantitative trait locus for salt tolerance and ABA sensitivity in Arabidopsis

KAUST Repository

Ren, Zhonghai; Zheng, Zhimin; Chinnusamy, Viswanathan; Zhu, Jianhua; Cui, Xinping; Iida, Kei; Zhu, Jian-Kang

2010-01-01

Soil salinity limits agricultural production and is a major obstacle for feeding the growing world population. We used natural genetic variation in salt tolerance among different Arabidopsis accessions to map a major quantitative trait locus (QTL

Genetic and Quantitative Trait Locus Analysis for Bio-Oil Compounds after Fast Pyrolysis in Maize Cobs.

Directory of Open Access Journals (Sweden)

Brandon Jeffrey

Full Text Available Fast pyrolysis has been identified as one of the biorenewable conversion platforms that could be a part of an alternative energy future, but it has not yet received the same attention as cellulosic ethanol in the analysis of genetic inheritance within potential feedstocks such as maize. Ten bio-oil compounds were measured via pyrolysis/gas chromatography-mass spectrometry (Py/GC-MS in maize cobs. 184 recombinant inbred lines (RILs of the intermated B73 x Mo17 (IBM Syn4 population were analyzed in two environments, using 1339 markers, for quantitative trait locus (QTL mapping. QTL mapping was performed using composite interval mapping with significance thresholds established by 1000 permutations at α = 0.05. 50 QTL were found in total across those ten traits with R2 values ranging from 1.7 to 5.8%, indicating a complex quantitative inheritance of these traits.

Quantitative trait locus (QTL) analysis of pod related traits in different ...

African Journals Online (AJOL)

Administrator

2011-09-26

Sep 26, 2011 ... assistant breeding selection. Key words: Soybean, pod traits, QTL, different environments. INTRODUCTION. Yield related traits in soybean are generally controlled by multiple genes and environmental dependent (Kwon and. Torrie, 1964). Epigenetics of genes controlling these traits also affect the yield.

Enriching an intraspecific genetic map and identifying QTL for fiber quality and yield component traits across multiple environments in Upland cotton (Gossypium hirsutum L.).

Science.gov (United States)

Liu, Xueying; Teng, Zhonghua; Wang, Jinxia; Wu, Tiantian; Zhang, Zhiqin; Deng, Xianping; Fang, Xiaomei; Tan, Zhaoyun; Ali, Iftikhar; Liu, Dexin; Zhang, Jian; Liu, Dajun; Liu, Fang; Zhang, Zhengsheng

2017-12-01

Cotton is a significant commercial crop that plays an indispensable role in many domains. Constructing high-density genetic maps and identifying stable quantitative trait locus (QTL) controlling agronomic traits are necessary prerequisites for marker-assisted selection (MAS). A total of 14,899 SSR primer pairs designed from the genome sequence of G. raimondii were screened for polymorphic markers between mapping parents CCRI 35 and Yumian 1, and 712 SSR markers showing polymorphism were used to genotype 180 lines from a (CCRI 35 × Yumian 1) recombinant inbred line (RIL) population. Genetic linkage analysis was conducted on 726 loci obtained from the 712 polymorphic SSR markers, along with 1379 SSR loci obtained in our previous study, and a high-density genetic map with 2051 loci was constructed, which spanned 3508.29 cM with an average distance of 1.71 cM between adjacent markers. Marker orders on the linkage map are highly consistent with the corresponding physical orders on a G. hirsutum genome sequence. Based on fiber quality and yield component trait data collected from six environments, 113 QTLs were identified through two analytical methods. Among these 113 QTLs, 50 were considered stable (detected in multiple environments or for which phenotypic variance explained by additive effect was greater than environment effect), and 18 of these 50 were identified with stability by both methods. These 18 QTLs, including eleven for fiber quality and seven for yield component traits, could be priorities for MAS.

Genomic Regions Influencing Seminal Root Traits in Barley

Directory of Open Access Journals (Sweden)

Hannah Robinson

2016-03-01

Full Text Available Water availability is a major limiting factor for crop production, making drought adaptation and its many component traits a desirable attribute of plant cultivars. Previous studies in cereal crops indicate that root traits expressed at early plant developmental stages, such as seminal root angle and root number, are associated with water extraction at different depths. Here, we conducted the first study to map seminal root traits in barley ( L.. Using a recently developed high-throughput phenotyping method, a panel of 30 barley genotypes and a doubled-haploid (DH population (ND24260 × ‘Flagship’ comprising 330 lines genotyped with diversity array technology (DArT markers were evaluated for seminal root angle (deviation from vertical and root number under controlled environmental conditions. A high degree of phenotypic variation was observed in the panel of 30 genotypes: 13.5 to 82.2 and 3.6 to 6.9° for root angle and root number, respectively. A similar range was observed in the DH population: 16.4 to 70.5 and 3.6 to 6.5° for root angle and number, respectively. Seven quantitative trait loci (QTL for seminal root traits (root angle, two QTL; root number, five QTL were detected in the DH population. A major QTL influencing both root angle and root number (/ was positioned on chromosome 5HL. Across-species analysis identified 10 common genes underlying root trait QTL in barley, wheat ( L., and sorghum [ (L. Moench]. Here, we provide insight into seminal root phenotypes and provide a first look at the genetics controlling these traits in barley.

A genome scan for quantitative trait loci affecting the Salmonella carrier-state in the chicken

Directory of Open Access Journals (Sweden)

Bumstead Nat

2005-09-01

Full Text Available Abstract Selection for increased resistance to Salmonella colonisation and excretion could reduce the risk of foodborne Salmonella infection. In order to identify potential loci affecting resistance, differences in resistance were identified between the N and 61 inbred lines and two QTL research performed. In an F2 cross, the animals were inoculated at one week of age with Salmonella enteritidis and cloacal swabs were carried out 4 and 5 wk post inoculation (thereafter called CSW4F2 and CSW4F2 and caecal contamination (CAECF2 was assessed 1 week later. The animals from the (N × 61 × N backcross were inoculated at six weeks of age with Salmonella typhimurium and cloacal swabs were studied from wk 1 to 4 (thereafter called CSW1BC to CSW4BC. A total of 33 F2 and 46 backcross progeny were selectively genotyped for 103 and 135 microsatellite markers respectively. The analysis used least-squares-based and non-parametric interval mapping. Two genome-wise significant QTL were observed on Chromosome 1 for CSW2BC and on Chromosome 2 for CSW4F2, and four suggestive QTL for CSW5F2 on Chromosome 2, for CSW5F2 and CSW2BC on chromosome 5 and for CAECF2 on chromosome 16. These results suggest new regions of interest and the putative role of SAL1.

Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

KAUST Repository

Liu, Guozheng

2016-07-06

Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat.

Directory of Open Access Journals (Sweden)

Guozheng Liu

Full Text Available Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1 examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2 explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3 investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L. and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs, but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

KAUST Repository

Liu, Guozheng; Zhao, Yusheng; Gowda, Manje; Longin, C. Friedrich H.; Reif, Jochen C.; Mette, Michael F.

2016-01-01

Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population.

Predicting Hybrid Performances for Quality Traits through Genomic-Assisted Approaches in Central European Wheat

Science.gov (United States)

Liu, Guozheng; Zhao, Yusheng; Gowda, Manje; Longin, C. Friedrich H.; Reif, Jochen C.; Mette, Michael F.

2016-01-01

Bread-making quality traits are central targets for wheat breeding. The objectives of our study were to (1) examine the presence of major effect QTLs for quality traits in a Central European elite wheat population, (2) explore the optimal strategy for predicting the hybrid performance for wheat quality traits, and (3) investigate the effects of marker density and the composition and size of the training population on the accuracy of prediction of hybrid performance. In total 135 inbred lines of Central European bread wheat (Triticum aestivum L.) and 1,604 hybrids derived from them were evaluated for seven quality traits in up to six environments. The 135 parental lines were genotyped using a 90k single-nucleotide polymorphism array. Genome-wide association mapping initially suggested presence of several quantitative trait loci (QTLs), but cross-validation rather indicated the absence of major effect QTLs for all quality traits except of 1000-kernel weight. Genomic selection substantially outperformed marker-assisted selection in predicting hybrid performance. A resampling study revealed that increasing the effective population size in the estimation set of hybrids is relevant to boost the accuracy of prediction for an unrelated test population. PMID:27383841

Genome-wide meta-analysis uncovers novel loci influencing circulating leptin levels

DEFF Research Database (Denmark)

Kilpeläinen, Tuomas O; Carli, Jayne F Martin; Skowronski, Alicja A

2016-01-01

. Therefore, we performed a genome-wide association study (GWAS) of circulating leptin levels from 32,161 individuals and followed up loci reaching PFTO....... Although the association of the FTO obesity locus with leptin levels is abolished by adjustment for BMI, associations of the four other loci are independent of adiposity. The GCKR locus was found associated with multiple metabolic traits in previous GWAS and the CCNL1 locus with birth weight. Knockdown...

Genetic Parameters and Combining Ability Effects of Parents for Seed Yield and other Quantitative Traits in Black Gram [Vigna mungo (L. Hepper

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Supriyo CHAKRABORTY

2010-06-01

Full Text Available Line x tester analysis was carried out in black gram [Vigna mungo (L. Hepper], an edible legume, to estimate the gca (general combining ability effects of parents (3 lines and 3 testers and the SCA (specific combining ability effects of 9 crosses for seed yield and other eleven quantitative traits. Though additive and nonadditive gene actions governed the expression of quantitative traits, the magnitude of nonadditive gene action was higher than that of additive gene action for each quantitative trait. Two parents viz. UG157 and DPU915 were good general combiners. Two crosses namely PDB 88-31/DPU 915 and PLU 277/KAU7 had high per se performance along with positive significant SCA effect for seed yield/plant. The degree of dominance revealed overdominance for all the traits except clusters/plant with partial dominance. The predictability ratio also revealed the predominant role of nonadditive gene action in the genetic control of quantitative traits. Narrow sense heritability was also low for each trait. Recurrent selection or biparental mating followed by selection which can exploit both additive and nonadditive gene actions would be of interest for yield improvement in black gram. Due to presence of high magnitude of nonadditive gene action, heterosis breeding could also be attempted to develop low cost hybrid variety using genetic male sterility system in black gram.

Identifying the genes underlying quantitative traits: a rationale for the QTN programme.

Science.gov (United States)

Lee, Young Wha; Gould, Billie A; Stinchcombe, John R

2014-01-01

The goal of identifying the genes or even nucleotides underlying quantitative and adaptive traits has been characterized as the 'QTN programme' and has recently come under severe criticism. Part of the reason for this criticism is that much of the QTN programme has asserted that finding the genes and nucleotides for adaptive and quantitative traits is a fundamental goal, without explaining why it is such a hallowed goal. Here we outline motivations for the QTN programme that offer general insight, regardless of whether QTNs are of large or small effect, and that aid our understanding of the mechanistic dynamics of adaptive evolution. We focus on five areas: (i) vertical integration of insight across different levels of biological organization, (ii) genetic parallelism and the role of pleiotropy in shaping evolutionary dynamics, (iii) understanding the forces maintaining genetic variation in populations, (iv) distinguishing between adaptation from standing variation and new mutation, and (v) the role of genomic architecture in facilitating adaptation. We argue that rather than abandoning the QTN programme, we should refocus our efforts on topics where molecular data will be the most effective for testing hypotheses about phenotypic evolution.

Identifying the genes underlying quantitative traits: a rationale for the QTN programme

Science.gov (United States)

Lee, Young Wha; Gould, Billie A.; Stinchcombe, John R.

2014-01-01

The goal of identifying the genes or even nucleotides underlying quantitative and adaptive traits has been characterized as the ‘QTN programme’ and has recently come under severe criticism. Part of the reason for this criticism is that much of the QTN programme has asserted that finding the genes and nucleotides for adaptive and quantitative traits is a fundamental goal, without explaining why it is such a hallowed goal. Here we outline motivations for the QTN programme that offer general insight, regardless of whether QTNs are of large or small effect, and that aid our understanding of the mechanistic dynamics of adaptive evolution. We focus on five areas: (i) vertical integration of insight across different levels of biological organization, (ii) genetic parallelism and the role of pleiotropy in shaping evolutionary dynamics, (iii) understanding the forces maintaining genetic variation in populations, (iv) distinguishing between adaptation from standing variation and new mutation, and (v) the role of genomic architecture in facilitating adaptation. We argue that rather than abandoning the QTN programme, we should refocus our efforts on topics where molecular data will be the most effective for testing hypotheses about phenotypic evolution. PMID:24790125

QTL Analysis of Kernel-Related Traits in Maize Using an Immortalized F2 Population

Science.gov (United States)

Hu, Yanmin; Li, Weihua; Fu, Zhiyuan; Ding, Dong; Li, Haochuan; Qiao, Mengmeng; Tang, Jihua

2014-01-01

Kernel size and weight are important determinants of grain yield in maize. In this study, multivariate conditional and unconditional quantitative trait loci (QTL), and digenic epistatic analyses were utilized in order to elucidate the genetic basis for these kernel-related traits. Five kernel-related traits, including kernel weight (KW), volume (KV), length (KL), thickness (KT), and width (KWI), were collected from an immortalized F2 (IF2) maize population comprising of 243 crosses performed at two separate locations over a span of two years. A total of 54 unconditional main QTL for these five kernel-related traits were identified, many of which were clustered in chromosomal bins 6.04–6.06, 7.02–7.03, and 10.06–10.07. In addition, qKL3, qKWI6, qKV10a, qKV10b, qKW10a, and qKW7a were detected across multiple environments. Sixteen main QTL were identified for KW conditioned on the other four kernel traits (KL, KWI, KT, and KV). Thirteen main QTL were identified for KV conditioned on three kernel-shape traits. Conditional mapping analysis revealed that KWI and KV had the strongest influence on KW at the individual QTL level, followed by KT, and then KL; KV was mostly strongly influenced by KT, followed by KWI, and was least impacted by KL. Digenic epistatic analysis identified 18 digenic interactions involving 34 loci over the entire genome. However, only a small proportion of them were identical to the main QTL we detected. Additionally, conditional digenic epistatic analysis revealed that the digenic epistasis for KW and KV were entirely determined by their constituent traits. The main QTL identified in this study for determining kernel-related traits with high broad-sense heritability may play important roles during kernel development. Furthermore, digenic interactions were shown to exert relatively large effects on KL (the highest AA and DD effects were 4.6% and 6.7%, respectively) and KT (the highest AA effects were 4.3%). PMID:24586932

QTL detection and elite alleles mining for stigma traits in Oryza sativa by association mapping

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Xiaojing Dang

2016-08-01

Full Text Available Stigma traits are very important for hybrid seed production in Oryza sativa, which is a self-pollinated crop; however, the genetic mechanism controlling the traits is poorly understood. In this study, we investigated the phenotypic data of 227 accessions across two years and assessed their genotypic variation with 249 simple sequence repeat (SSR markers. By combining phenotypic and genotypic data, a genome-wide association (GWA map was generated. Large phenotypic variations in stigma length (STL, stigma brush-shaped part length (SBPL and stigma non-brush-shaped part length (SNBPL were found. Significant positive correlations were identified among stigma traits. In total, 2,072 alleles were detected among 227 accessions, with an average of 8.3 alleles per SSR locus. GWA mapping detected 6 quantitative trait loci (QTLs for the STL, 2 QTLs for the SBPL and 7 QTLs for the SNBPL. Eleven, 5, and 12 elite alleles were found for the STL, SBPL and SNBPL, respectively. Optimal cross designs were predicted for improving the target traits. The detected genetic variation in stigma traits and QTLs provides helpful information for cloning candidate STL genes and breeding rice cultivars with longer STLs in the future.

Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals.

Directory of Open Access Journals (Sweden)

Zari Dastani

Full Text Available Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8-1.2×10(-43. Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans, we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10(-4. We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10(-3, n = 22,044, increased triglycerides (p = 2.6×10(-14, n = 93,440, increased waist-to-hip ratio (p = 1.8×10(-5, n = 77,167, increased glucose two hours post oral glucose tolerance testing (p = 4.4×10(-3, n = 15,234, increased fasting insulin (p = 0.015, n = 48,238, but with lower in HDL-cholesterol concentrations (p = 4.5×10(-13, n = 96,748 and decreased BMI (p = 1.4×10(-4, n = 121,335. These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.

Novel loci for adiponectin levels and their influence on type 2 diabetes and metabolic traits: a multi-ethnic meta-analysis of 45,891 individuals.

Science.gov (United States)

Dastani, Zari; Hivert, Marie-France; Timpson, Nicholas; Perry, John R B; Yuan, Xin; Scott, Robert A; Henneman, Peter; Heid, Iris M; Kizer, Jorge R; Lyytikäinen, Leo-Pekka; Fuchsberger, Christian; Tanaka, Toshiko; Morris, Andrew P; Small, Kerrin; Isaacs, Aaron; Beekman, Marian; Coassin, Stefan; Lohman, Kurt; Qi, Lu; Kanoni, Stavroula; Pankow, James S; Uh, Hae-Won; Wu, Ying; Bidulescu, Aurelian; Rasmussen-Torvik, Laura J; Greenwood, Celia M T; Ladouceur, Martin; Grimsby, Jonna; Manning, Alisa K; Liu, Ching-Ti; Kooner, Jaspal; Mooser, Vincent E; Vollenweider, Peter; Kapur, Karen A; Chambers, John; Wareham, Nicholas J; Langenberg, Claudia; Frants, Rune; Willems-Vandijk, Ko; Oostra, Ben A; Willems, Sara M; Lamina, Claudia; Winkler, Thomas W; Psaty, Bruce M; Tracy, Russell P; Brody, Jennifer; Chen, Ida; Viikari, Jorma; Kähönen, Mika; Pramstaller, Peter P; Evans, David M; St Pourcain, Beate; Sattar, Naveed; Wood, Andrew R; Bandinelli, Stefania; Carlson, Olga D; Egan, Josephine M; Böhringer, Stefan; van Heemst, Diana; Kedenko, Lyudmyla; Kristiansson, Kati; Nuotio, Marja-Liisa; Loo, Britt-Marie; Harris, Tamara; Garcia, Melissa; Kanaya, Alka; Haun, Margot; Klopp, Norman; Wichmann, H-Erich; Deloukas, Panos; Katsareli, Efi; Couper, David J; Duncan, Bruce B; Kloppenburg, Margreet; Adair, Linda S; Borja, Judith B; Wilson, James G; Musani, Solomon; Guo, Xiuqing; Johnson, Toby; Semple, Robert; Teslovich, Tanya M; Allison, Matthew A; Redline, Susan; Buxbaum, Sarah G; Mohlke, Karen L; Meulenbelt, Ingrid; Ballantyne, Christie M; Dedoussis, George V; Hu, Frank B; Liu, Yongmei; Paulweber, Bernhard; Spector, Timothy D; Slagboom, P Eline; Ferrucci, Luigi; Jula, Antti; Perola, Markus; Raitakari, Olli; Florez, Jose C; Salomaa, Veikko; Eriksson, Johan G; Frayling, Timothy M; Hicks, Andrew A; Lehtimäki, Terho; Smith, George Davey; Siscovick, David S; Kronenberg, Florian; van Duijn, Cornelia; Loos, Ruth J F; Waterworth, Dawn M; Meigs, James B; Dupuis, Josee; Richards, J Brent; Voight, Benjamin F; Scott, Laura J; Steinthorsdottir, Valgerdur; Dina, Christian; Welch, Ryan P; Zeggini, Eleftheria; Huth, Cornelia; Aulchenko, Yurii S; Thorleifsson, Gudmar; McCulloch, Laura J; Ferreira, Teresa; Grallert, Harald; Amin, Najaf; Wu, Guanming; Willer, Cristen J; Raychaudhuri, Soumya; McCarroll, Steve A; Hofmann, Oliver M; Segrè, Ayellet V; van Hoek, Mandy; Navarro, Pau; Ardlie, Kristin; Balkau, Beverley; Benediktsson, Rafn; Bennett, Amanda J; Blagieva, Roza; Boerwinkle, Eric; Bonnycastle, Lori L; Boström, Kristina Bengtsson; Bravenboer, Bert; Bumpstead, Suzannah; Burtt, Noël P; Charpentier, Guillaume; Chines, Peter S; Cornelis, Marilyn; Crawford, Gabe; Doney, Alex S F; Elliott, Katherine S; Elliott, Amanda L; Erdos, Michael R; Fox, Caroline S; Franklin, Christopher S; Ganser, Martha; Gieger, Christian; Grarup, Niels; Green, Todd; Griffin, Simon; Groves, Christopher J; Guiducci, Candace; Hadjadj, Samy; Hassanali, Neelam; Herder, Christian; Isomaa, Bo; Jackson, Anne U; Johnson, Paul R V; Jørgensen, Torben; Kao, Wen H L; Kong, Augustine; Kraft, Peter; Kuusisto, Johanna; Lauritzen, Torsten; Li, Man; Lieverse, Aloysius; Lindgren, Cecilia M; Lyssenko, Valeriya; Marre, Michel; Meitinger, Thomas; Midthjell, Kristian; Morken, Mario A; Narisu, Narisu; Nilsson, Peter; Owen, Katharine R; Payne, Felicity; Petersen, Ann-Kristin; Platou, Carl; Proença, Christine; Prokopenko, Inga; Rathmann, Wolfgang; Rayner, N William; Robertson, Neil R; Rocheleau, Ghislain; Roden, Michael; Sampson, Michael J; Saxena, Richa; Shields, Beverley M; Shrader, Peter; Sigurdsson, Gunnar; Sparsø, Thomas; Strassburger, Klaus; Stringham, Heather M; Sun, Qi; Swift, Amy J; Thorand, Barbara; Tichet, Jean; Tuomi, Tiinamaija; van Dam, Rob M; van Haeften, Timon W; van Herpt, Thijs; van Vliet-Ostaptchouk, Jana V; Walters, G Bragi; Weedon, Michael N; Wijmenga, Cisca; Witteman, Jacqueline; Bergman, Richard N; Cauchi, Stephane; Collins, Francis S; Gloyn, Anna L; Gyllensten, Ulf; Hansen, Torben; Hide, Winston A; Hitman, Graham A; Hofman, Albert; Hunter, David J; Hveem, Kristian; Laakso, Markku; Morris, Andrew D; Palmer, Colin N A; Rudan, Igor; Sijbrands, Eric; Stein, Lincoln D; Tuomilehto, Jaakko; Uitterlinden, Andre; Walker, Mark; Watanabe, Richard M; Abecasis, Goncalo R; Boehm, Bernhard O; Campbell, Harry; Daly, Mark J; Hattersley, Andrew T; Pedersen, Oluf; Barroso, Inês; Groop, Leif; Sladek, Rob; Thorsteinsdottir, Unnur; Wilson, James F; Illig, Thomas; Froguel, Philippe; van Duijn, Cornelia M; Stefansson, Kari; Altshuler, David; Boehnke, Michael; McCarthy, Mark I; Soranzo, Nicole; Wheeler, Eleanor; Glazer, Nicole L; Bouatia-Naji, Nabila; Mägi, Reedik; Randall, Joshua; Elliott, Paul; Rybin, Denis; Dehghan, Abbas; Hottenga, Jouke Jan; Song, Kijoung; Goel, Anuj; Lajunen, Taina; Doney, Alex; Cavalcanti-Proença, Christine; Kumari, Meena; Timpson, Nicholas J; Zabena, Carina; Ingelsson, Erik; An, Ping; O'Connell, Jeffrey; Luan, Jian'an; Elliott, Amanda; McCarroll, Steven A; Roccasecca, Rosa Maria; Pattou, François; Sethupathy, Praveen; Ariyurek, Yavuz; Barter, Philip; Beilby, John P; Ben-Shlomo, Yoav; Bergmann, Sven; Bochud, Murielle; Bonnefond, Amélie; Borch-Johnsen, Knut; Böttcher, Yvonne; Brunner, Eric; Bumpstead, Suzannah J; Chen, Yii-Der Ida; Chines, Peter; Clarke, Robert; Coin, Lachlan J M; Cooper, Matthew N; Crisponi, Laura; Day, Ian N M; de Geus, Eco J C; Delplanque, Jerome; Fedson, Annette C; Fischer-Rosinsky, Antje; Forouhi, Nita G; Franzosi, Maria Grazia; Galan, Pilar; Goodarzi, Mark O; Graessler, Jürgen; Grundy, Scott; Gwilliam, Rhian; Hallmans, Göran; Hammond, Naomi; Han, Xijing; Hartikainen, Anna-Liisa; Hayward, Caroline; Heath, Simon C; Hercberg, Serge; Hillman, David R; Hingorani, Aroon D; Hui, Jennie; Hung, Joe; Kaakinen, Marika; Kaprio, Jaakko; Kesaniemi, Y Antero; Kivimaki, Mika; Knight, Beatrice; Koskinen, Seppo; Kovacs, Peter; Kyvik, Kirsten Ohm; Lathrop, G Mark; Lawlor, Debbie A; Le Bacquer, Olivier; Lecoeur, Cécile; Li, Yun; Mahley, Robert; Mangino, Massimo; Martínez-Larrad, María Teresa; McAteer, Jarred B; McPherson, Ruth; Meisinger, Christa; Melzer, David; Meyre, David; Mitchell, Braxton D; Mukherjee, Sutapa; Naitza, Silvia; Neville, Matthew J; Orrù, Marco; Pakyz, Ruth; Paolisso, Giuseppe; Pattaro, Cristian; Pearson, Daniel; Peden, John F; Pedersen, Nancy L; Pfeiffer, Andreas F H; Pichler, Irene; Polasek, Ozren; Posthuma, Danielle; Potter, Simon C; Pouta, Anneli; Province, Michael A; Rayner, Nigel W; Rice, Kenneth; Ripatti, Samuli; Rivadeneira, Fernando; Rolandsson, Olov; Sandbaek, Annelli; Sandhu, Manjinder; Sanna, Serena; Sayer, Avan Aihie; Scheet, Paul; Seedorf, Udo; Sharp, Stephen J; Shields, Beverley; Sigurðsson, Gunnar; Sijbrands, Eric J G; Silveira, Angela; Simpson, Laila; Singleton, Andrew; Smith, Nicholas L; Sovio, Ulla; Swift, Amy; Syddall, Holly; Syvänen, Ann-Christine; Tönjes, Anke; Uitterlinden, André G; van Dijk, Ko Willems; Varma, Dhiraj; Visvikis-Siest, Sophie; Vitart, Veronique; Vogelzangs, Nicole; Waeber, Gérard; Wagner, Peter J; Walley, Andrew; Ward, Kim L; Watkins, Hugh; Wild, Sarah H; Willemsen, Gonneke; Witteman, Jaqueline C M; Yarnell, John W G; Zelenika, Diana; Zethelius, Björn; Zhai, Guangju; Zhao, Jing Hua; Zillikens, M Carola; Borecki, Ingrid B; Meneton, Pierre; Magnusson, Patrik K E; Nathan, David M; Williams, Gordon H; Silander, Kaisa; Bornstein, Stefan R; Schwarz, Peter; Spranger, Joachim; Karpe, Fredrik; Shuldiner, Alan R; Cooper, Cyrus; Serrano-Ríos, Manuel; Lind, Lars; Palmer, Lyle J; Hu, Frank B; Franks, Paul W; Ebrahim, Shah; Marmot, Michael; Kao, W H Linda; Pramstaller, Peter Paul; Wright, Alan F; Stumvoll, Michael; Hamsten, Anders; Buchanan, Thomas A; Valle, Timo T; Rotter, Jerome I; Penninx, Brenda W J H; Boomsma, Dorret I; Cao, Antonio; Scuteri, Angelo; Schlessinger, David; Uda, Manuela; Ruokonen, Aimo; Jarvelin, Marjo-Riitta; Peltonen, Leena; Mooser, Vincent; Sladek, Robert; Musunuru, Kiran; Smith, Albert V; Edmondson, Andrew C; Stylianou, Ioannis M; Koseki, Masahiro; Pirruccello, James P; Chasman, Daniel I; Johansen, Christopher T; Fouchier, Sigrid W; Peloso, Gina M; Barbalic, Maja; Ricketts, Sally L; Bis, Joshua C; Feitosa, Mary F; Orho-Melander, Marju; Melander, Olle; Li, Xiaohui; Li, Mingyao; Cho, Yoon Shin; Go, Min Jin; Kim, Young Jin; Lee, Jong-Young; Park, Taesung; Kim, Kyunga; Sim, Xueling; Ong, Rick Twee-Hee; Croteau-Chonka, Damien C; Lange, Leslie A; Smith, Joshua D; Ziegler, Andreas; Zhang, Weihua; Zee, Robert Y L; Whitfield, John B; Thompson, John R; Surakka, Ida; Spector, Tim D; Smit, Johannes H; Sinisalo, Juha; Scott, James; Saharinen, Juha; Sabatti, Chiara; Rose, Lynda M; Roberts, Robert; Rieder, Mark; Parker, Alex N; Pare, Guillaume; O'Donnell, Christopher J; Nieminen, Markku S; Nickerson, Deborah A; Montgomery, Grant W; McArdle, Wendy; Masson, David; Martin, Nicholas G; Marroni, Fabio; Lucas, Gavin; Luben, Robert; Lokki, Marja-Liisa; Lettre, Guillaume; Launer, Lenore J; Lakatta, Edward G; Laaksonen, Reijo; Kyvik, Kirsten O; König, Inke R; Khaw, Kay-Tee; Kaplan, Lee M; Johansson, Åsa; Janssens, A Cecile J W; Igl, Wilmar; Hovingh, G Kees; Hengstenberg, Christian; Havulinna, Aki S; Hastie, Nicholas D; Harris, Tamara B; Haritunians, Talin; Hall, Alistair S; Groop, Leif C; Gonzalez, Elena; Freimer, Nelson B; Erdmann, Jeanette; Ejebe, Kenechi G; Döring, Angela; Dominiczak, Anna F; Demissie, Serkalem; Deloukas, Panagiotis; de Faire, Ulf; Crawford, Gabriel; Chen, Yii-der I; Caulfield, Mark J; Boekholdt, S Matthijs; Assimes, Themistocles L; Quertermous, Thomas; Seielstad, Mark; Wong, Tien Y; Tai, E-Shyong; Feranil, Alan B; Kuzawa, Christopher W; Taylor, Herman A; Gabriel, Stacey B; Holm, Hilma; Gudnason, Vilmundur; Krauss, Ronald M; Ordovas, Jose M; Munroe, Patricia B; Kooner, Jaspal S; Tall, Alan R; Hegele, Robert A; Kastelein, John J P; Schadt, Eric E; Strachan, David P; Reilly, Muredach P; Samani, Nilesh J; Schunkert, Heribert; Cupples, L Adrienne; Sandhu, Manjinder S; Ridker, Paul M; Rader, Daniel J; Kathiresan, Sekar

2012-01-01

Circulating levels of adiponectin, a hormone produced predominantly by adipocytes, are highly heritable and are inversely associated with type 2 diabetes mellitus (T2D) and other metabolic traits. We conducted a meta-analysis of genome-wide association studies in 39,883 individuals of European ancestry to identify genes associated with metabolic disease. We identified 8 novel loci associated with adiponectin levels and confirmed 2 previously reported loci (P = 4.5×10(-8)-1.2×10(-43)). Using a novel method to combine data across ethnicities (N = 4,232 African Americans, N = 1,776 Asians, and N = 29,347 Europeans), we identified two additional novel loci. Expression analyses of 436 human adipocyte samples revealed that mRNA levels of 18 genes at candidate regions were associated with adiponectin concentrations after accounting for multiple testing (p<3×10(-4)). We next developed a multi-SNP genotypic risk score to test the association of adiponectin decreasing risk alleles on metabolic traits and diseases using consortia-level meta-analytic data. This risk score was associated with increased risk of T2D (p = 4.3×10(-3), n = 22,044), increased triglycerides (p = 2.6×10(-14), n = 93,440), increased waist-to-hip ratio (p = 1.8×10(-5), n = 77,167), increased glucose two hours post oral glucose tolerance testing (p = 4.4×10(-3), n = 15,234), increased fasting insulin (p = 0.015, n = 48,238), but with lower in HDL-cholesterol concentrations (p = 4.5×10(-13), n = 96,748) and decreased BMI (p = 1.4×10(-4), n = 121,335). These findings identify novel genetic determinants of adiponectin levels, which, taken together, influence risk of T2D and markers of insulin resistance.

Natural Genetic Variation and Candidate Genes for Morphological Traits in Drosophila melanogaster

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Carreira, Valeria Paula; Mensch, Julián; Hasson, Esteban; Fanara, Juan José

2016-01-01

Body size is a complex character associated to several fitness related traits that vary within and between species as a consequence of environmental and genetic factors. Latitudinal and altitudinal clines for different morphological traits have been described in several species of Drosophila and previous work identified genomic regions associated with such variation in D. melanogaster. However, the genetic factors that orchestrate morphological variation have been barely studied. Here, our main objective was to investigate genetic variation for different morphological traits associated to the second chromosome in natural populations of D. melanogaster along latitudinal and altitudinal gradients in Argentina. Our results revealed weak clinal signals and a strong population effect on morphological variation. Moreover, most pairwise comparisons between populations were significant. Our study also showed important within-population genetic variation, which must be associated to the second chromosome, as the lines are otherwise genetically identical. Next, we examined the contribution of different candidate genes to natural variation for these traits. We performed quantitative complementation tests using a battery of lines bearing mutated alleles at candidate genes located in the second chromosome and six second chromosome substitution lines derived from natural populations which exhibited divergent phenotypes. Results of complementation tests revealed that natural variation at all candidate genes studied, invected, Fasciclin 3, toucan, Reticulon-like1, jing and CG14478, affects the studied characters, suggesting that they are Quantitative Trait Genes for morphological traits. Finally, the phenotypic patterns observed suggest that different alleles of each gene might contribute to natural variation for morphological traits. However, non-additive effects cannot be ruled out, as wild-derived strains differ at myriads of second chromosome loci that may interact

Genetic variability and population structure in loci related to milk production traits in native Argentine Creole and commercial Argentine Holstein cattle

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Golijow C.D.

1999-01-01

Full Text Available Many cattle breeds have been subjected to high selection pressure for production traits. Consequently, population genetic structure and allelic distribution could differ in breeds under high selection pressure compared to unselected breeds. Analysis of k-casein, aS1-casein and prolactin gene frequencies was made for Argentine Creole (AC and Argentine Holstein (AH cattle herds. The calculated FST values measured the degree of genetic differentiation of subpopulations, depending on the variances of gene frequencies.The AC breed had considerably more variation among herds at the aS1-casein and k-casein loci. Conservation strategies should consider the entire AC population in order to maintain the genetic variability found in this native breed.

Genome-wide Association Studies for Female Fertility Traits in Chinese and Nordic Holsteins.

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Liu, Aoxing; Wang, Yachun; Sahana, Goutam; Zhang, Qin; Liu, Lin; Lund, Mogens Sandø; Su, Guosheng

2017-08-16

Reduced female fertility could cause considerable economic loss and has become a worldwide problem in the modern dairy industry. The objective of this study was to detect quantitative trait loci (QTL) for female fertility traits in Chinese and Nordic Holsteins using various strategies. First, single-trait association analyses were performed for female fertility traits in Chinese and Nordic Holsteins. Second, the SNPs with P-value Nordic Holsteins. Third, the summary statistics from single-trait association analyses were combined into meta-analyses to: (1) identify common QTL for multiple fertility traits within each Holstein population; (2) detect SNPs which were associated with a female fertility trait across two Holstein populations. A large numbers of QTL were discovered or confirmed for female fertility traits. The QTL segregating at 31.4~34.1 Mb on BTA13, 48.3~51.9 Mb on BTA23 and 34.0~37.6 Mb on BTA28 shared between Chinese and Nordic Holsteins were further ascertained using a validation approach and meta-analyses. Furthermore, multiple novel variants identified in Chinese Holsteins were validated with Nordic data as well as meta-analyses. The genes IL6R, SLC39A12, CACNB2, ZEB1, ZMIZ1 and FAM213A were concluded to be strong candidate genes for female fertility in Holsteins.

Genome-wide Meta-analyses of Breast, Ovarian and Prostate Cancer Association Studies Identify Multiple New Susceptibility Loci Shared by At Least Two Cancer Types

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Kar, Siddhartha P.; Beesley, Jonathan; Al Olama, Ali Amin; Michailidou, Kyriaki; Tyrer, Jonathan; Kote-Jarai, ZSofia; Lawrenson, Kate; Lindstrom, Sara; Ramus, Susan J.; Thompson, Deborah J.; Kibel, Adam S.; Dansonka-Mieszkowska, Agnieszka; Michael, Agnieszka; Dieffenbach, Aida K.; Gentry-Maharaj, Aleksandra; Whittemore, Alice S.; Wolk, Alicja; Monteiro, Alvaro; Peixoto, Ana; Kierzek, Andrzej; Cox, Angela; Rudolph, Anja; Gonzalez-Neira, Anna; Wu, Anna H.; Lindblom, Annika; Swerdlow, Anthony; Ziogas, Argyrios; Ekici, Arif B.; Burwinkel, Barbara; Karlan, Beth Y.; Nordestgaard, Børge G.; Blomqvist, Carl; Phelan, Catherine; McLean, Catriona; Pearce, Celeste Leigh; Vachon, Celine; Cybulski, Cezary; Slavov, Chavdar; Stegmaier, Christa; Maier, Christiane; Ambrosone, Christine B.; Høgdall, Claus K.; Teerlink, Craig C.; Kang, Daehee; Tessier, Daniel C.; Schaid, Daniel J.; Stram, Daniel O.; Cramer, Daniel W.; Neal, David E.; Eccles, Diana; Flesch-Janys, Dieter; Velez Edwards, Digna R.; Wokozorczyk, Dominika; Levine, Douglas A.; Yannoukakos, Drakoulis; Sawyer, Elinor J.; Bandera, Elisa V.; Poole, Elizabeth M.; Goode, Ellen L.; Khusnutdinova, Elza; Høgdall, Estrid; Song, Fengju; Bruinsma, Fiona; Heitz, Florian; Modugno, Francesmary; Hamdy, Freddie C.; Wiklund, Fredrik; Giles, Graham G.; Olsson, Håkan; Wildiers, Hans; Ulmer, Hans-Ulrich; Pandha, Hardev; Risch, Harvey A.; Darabi, Hatef; Salvesen, Helga B.; Nevanlinna, Heli; Gronberg, Henrik; Brenner, Hermann; Brauch, Hiltrud; Anton-Culver, Hoda; Song, Honglin; Lim, Hui-Yi; McNeish, Iain; Campbell, Ian; Vergote, Ignace; Gronwald, Jacek; Lubiński, Jan; Stanford, Janet L.; Benítez, Javier; Doherty, Jennifer A.; Permuth, Jennifer B.; Chang-Claude, Jenny; Donovan, Jenny L.; Dennis, Joe; Schildkraut, Joellen M.; Schleutker, Johanna; Hopper, John L.; Kupryjanczyk, Jolanta; Park, Jong Y.; Figueroa, Jonine; Clements, Judith A.; Knight, Julia A.; Peto, Julian; Cunningham, Julie M.; Pow-Sang, Julio; Batra, Jyotsna; Czene, Kamila; Lu, Karen H.; Herkommer, Kathleen; Khaw, Kay-Tee; Matsuo, Keitaro; Muir, Kenneth; Offitt, Kenneth; Chen, Kexin; Moysich, Kirsten B.; Aittomäki, Kristiina; Odunsi, Kunle; Kiemeney, Lambertus A.; Massuger, Leon F.A.G.; Fitzgerald, Liesel M.; Cook, Linda S.; Cannon-Albright, Lisa; Hooning, Maartje J.; Pike, Malcolm C.; Bolla, Manjeet K.; Luedeke, Manuel; Teixeira, Manuel R.; Goodman, Marc T.; Schmidt, Marjanka K.; Riggan, Marjorie; Aly, Markus; Rossing, Mary Anne; Beckmann, Matthias W.; Moisse, Matthieu; Sanderson, Maureen; Southey, Melissa C.; Jones, Michael; Lush, Michael; Hildebrandt, Michelle A. T.; Hou, Ming-Feng; Schoemaker, Minouk J.; Garcia-Closas, Montserrat; Bogdanova, Natalia; Rahman, Nazneen; Le, Nhu D.; Orr, Nick; Wentzensen, Nicolas; Pashayan, Nora; Peterlongo, Paolo; Guénel, Pascal; Brennan, Paul; Paulo, Paula; Webb, Penelope M.; Broberg, Per; Fasching, Peter A.; Devilee, Peter; Wang, Qin; Cai, Qiuyin; Li, Qiyuan; Kaneva, Radka; Butzow, Ralf; Kopperud, Reidun Kristin; Schmutzler, Rita K.; Stephenson, Robert A.; MacInnis, Robert J.; Hoover, Robert N.; Winqvist, Robert; Ness, Roberta; Milne, Roger L.; Travis, Ruth C.; Benlloch, Sara; Olson, Sara H.; McDonnell, Shannon K.; Tworoger, Shelley S.; Maia, Sofia; Berndt, Sonja; Lee, Soo Chin; Teo, Soo-Hwang; Thibodeau, Stephen N.; Bojesen, Stig E.; Gapstur, Susan M.; Kjær, Susanne Krüger; Pejovic, Tanja; Tammela, Teuvo L.J.; Dörk, Thilo; Brüning, Thomas; Wahlfors, Tiina; Key, Tim J.; Edwards, Todd L.; Menon, Usha; Hamann, Ute; Mitev, Vanio; Kosma, Veli-Matti; Setiawan, Veronica Wendy; Kristensen, Vessela; Arndt, Volker; Vogel, Walther; Zheng, Wei; Sieh, Weiva; Blot, William J.; Kluzniak, Wojciech; Shu, Xiao-Ou; Gao, Yu-Tang; Schumacher, Fredrick; Freedman, Matthew L.; Berchuck, Andrew; Dunning, Alison M.; Simard, Jacques; Haiman, Christopher A.; Spurdle, Amanda; Sellers, Thomas A.; Hunter, David J.; Henderson, Brian E.; Kraft, Peter; Chanock, Stephen J.; Couch, Fergus J.; Hall, Per; Gayther, Simon A.; Easton, Douglas F.; Chenevix-Trench, Georgia; Eeles, Rosalind; Pharoah, Paul D.P.; Lambrechts, Diether

2016-01-01

Breast, ovarian, and prostate cancers are hormone-related and may have a shared genetic basis but this has not been investigated systematically by genome-wide association (GWA) studies. Meta-analyses combining the largest GWA meta-analysis data sets for these cancers totaling 112,349 cases and 116,421 controls of European ancestry, all together and in pairs, identified at P cancer loci: three associated with susceptibility to all three cancers (rs17041869/2q13/BCL2L11; rs7937840/11q12/INCENP; rs1469713/19p13/GATAD2A), two breast and ovarian cancer risk loci (rs200182588/9q31/SMC2; rs8037137/15q26/RCCD1), and two breast and prostate cancer risk loci (rs5013329/1p34/NSUN4; rs9375701/6q23/L3MBTL3). Index variants in five additional regions previously associated with only one cancer also showed clear association with a second cancer type. Cell-type specific expression quantitative trait locus and enhancer-gene interaction annotations suggested target genes with potential cross-cancer roles at the new loci. Pathway analysis revealed significant enrichment of death receptor signaling genes near loci with P cancer meta-analysis. PMID:27432226

Heterotic trait locus (HTL) mapping identifies intra-locus interactions that underlie reproductive hybrid vigor in Sorghum bicolor.

Science.gov (United States)

Ben-Israel, Imri; Kilian, Benjamin; Nida, Habte; Fridman, Eyal

2012-01-01

Identifying intra-locus interactions underlying heterotic variation among whole-genome hybrids is a key to understanding mechanisms of heterosis and exploiting it for crop and livestock improvement. In this study, we present the development and first use of the heterotic trait locus (HTL) mapping approach to associate specific intra-locus interactions with an overdominant heterotic mode of inheritance in a diallel population using Sorghum bicolor as the model. This method combines the advantages of ample genetic diversity and the possibility of studying non-additive inheritance. Furthermore, this design enables dissecting the latter to identify specific intra-locus interactions. We identified three HTLs (3.5% of loci tested) with synergistic intra-locus effects on overdominant grain yield heterosis in 2 years of field trials. These loci account for 19.0% of the heterotic variation, including a significant interaction found between two of them. Moreover, analysis of one of these loci (hDPW4.1) in a consecutive F2 population confirmed a significant 21% increase in grain yield of heterozygous vs. homozygous plants in this locus. Notably, two of the three HTLs for grain yield are in synteny with previously reported overdominant quantitative trait loci for grain yield in maize. A mechanism for the reproductive heterosis found in this study is suggested, in which grain yield increase is achieved by releasing the compensatory tradeoffs between biomass and reproductive output, and between seed number and weight. These results highlight the power of analyzing a diverse set of inbreds and their hybrids for unraveling hitherto unknown allelic interactions mediating heterosis.

Genome-wide analysis identifies 12 loci influencing human reproductive behavior

Science.gov (United States)

Barban, Nicola; Jansen, Rick; de Vlaming, Ronald; Vaez, Ahmad; Mandemakers, Jornt J.; Tropf, Felix C.; Shen, Xia; Wilson, James F.; Chasman, Daniel I.; Nolte, Ilja M.; Tragante, Vinicius; van der Laan, Sander W.; Perry, John R. B.; Kong, Augustine; Ahluwalia, Tarunveer; Albrecht, Eva; Yerges-Armstrong, Laura; Atzmon, Gil; Auro, Kirsi; Ayers, Kristin; Bakshi, Andrew; Ben-Avraham, Danny; Berger, Klaus; Bergman, Aviv; Bertram, Lars; Bielak, Lawrence F.; Bjornsdottir, Gyda; Bonder, Marc Jan; Broer, Linda; Bui, Minh; Barbieri, Caterina; Cavadino, Alana; Chavarro, Jorge E; Turman, Constance; Concas, Maria Pina; Cordell, Heather J.; Davies, Gail; Eibich, Peter; Eriksson, Nicholas; Esko, Tõnu; Eriksson, Joel; Falahi, Fahimeh; Felix, Janine F.; Fontana, Mark Alan; Franke, Lude; Gandin, Ilaria; Gaskins, Audrey J.; Gieger, Christian; Gunderson, Erica P.; Guo, Xiuqing; Hayward, Caroline; He, Chunyan; Hofer, Edith; Huang, Hongyan; Joshi, Peter K.; Kanoni, Stavroula; Karlsson, Robert; Kiechl, Stefan; Kifley, Annette; Kluttig, Alexander; Kraft, Peter; Lagou, Vasiliki; Lecoeur, Cecile; Lahti, Jari; Li-Gao, Ruifang; Lind, Penelope A.; Liu, Tian; Makalic, Enes; Mamasoula, Crysovalanto; Matteson, Lindsay; Mbarek, Hamdi; McArdle, Patrick F.; McMahon, George; Meddens, S. Fleur W.; Mihailov, Evelin; Miller, Mike; Missmer, Stacey A.; Monnereau, Claire; van der Most, Peter J.; Myhre, Ronny; Nalls, Mike A.; Nutile, Teresa; Panagiota, Kalafati Ioanna; Porcu, Eleonora; Prokopenko, Inga; Rajan, Kumar B.; Rich-Edwards, Janet; Rietveld, Cornelius A.; Robino, Antonietta; Rose, Lynda M.; Rueedi, Rico; Ryan, Kathy; Saba, Yasaman; Schmidt, Daniel; Smith, Jennifer A.; Stolk, Lisette; Streeten, Elizabeth; Tonjes, Anke; Thorleifsson, Gudmar; Ulivi, Sheila; Wedenoja, Juho; Wellmann, Juergen; Willeit, Peter; Yao, Jie; Yengo, Loic; Zhao, Jing Hua; Zhao, Wei; Zhernakova, Daria V.; Amin, Najaf; Andrews, Howard; Balkau, Beverley; Barzilai, Nir; Bergmann, Sven; Biino, Ginevra; Bisgaard, Hans; Bønnelykke, Klaus; Boomsma, Dorret I.; Buring, Julie E.; Campbell, Harry; Cappellani, Stefania; Ciullo, Marina; Cox, Simon R.; Cucca, Francesco; Daniela, Toniolo; Davey-Smith, George; Deary, Ian J.; Dedoussis, George; Deloukas, Panos; van Duijn, Cornelia M.; de Geus, Eco JC.; Eriksson, Johan G.; Evans, Denis A.; Faul, Jessica D.; Felicita, Sala Cinzia; Froguel, Philippe; Gasparini, Paolo; Girotto, Giorgia; Grabe, Hans-Jörgen; Greiser, Karin Halina; Groenen, Patrick J.F.; de Haan, Hugoline G.; Haerting, Johannes; Harris, Tamara B.; Heath, Andrew C.; Heikkilä, Kauko; Hofman, Albert; Homuth, Georg; Holliday, Elizabeth G; Hopper, John; Hypponen, Elina; Jacobsson, Bo; Jaddoe, Vincent W. V.; Johannesson, Magnus; Jugessur, Astanand; Kähönen, Mika; Kajantie, Eero; Kardia, Sharon L.R.; Keavney, Bernard; Kolcic, Ivana; Koponen, Päivikki; Kovacs, Peter; Kronenberg, Florian; Kutalik, Zoltan; La Bianca, Martina; Lachance, Genevieve; Iacono, William; Lai, Sandra; Lehtimäki, Terho; Liewald, David C; Lindgren, Cecilia; Liu, Yongmei; Luben, Robert; Lucht, Michael; Luoto, Riitta; Magnus, Per; Magnusson, Patrik K.E.; Martin, Nicholas G.; McGue, Matt; McQuillan, Ruth; Medland, Sarah E.; Meisinger, Christa; Mellström, Dan; Metspalu, Andres; Michela, Traglia; Milani, Lili; Mitchell, Paul; Montgomery, Grant W.; Mook-Kanamori, Dennis; de Mutsert, Renée; Nohr, Ellen A; Ohlsson, Claes; Olsen, Jørn; Ong, Ken K.; Paternoster, Lavinia; Pattie, Alison; Penninx, Brenda WJH; Perola, Markus; Peyser, Patricia A.; Pirastu, Mario; Polasek, Ozren; Power, Chris; Kaprio, Jaakko; Raffel, Leslie J.; Räikkönen, Katri; Raitakari, Olli; Ridker, Paul M.; Ring, Susan M.; Roll, Kathryn; Rudan, Igor; Ruggiero, Daniela; Rujescu, Dan; Salomaa, Veikko; Schlessinger, David; Schmidt, Helena; Schmidt, Reinhold; Schupf, Nicole; Smit, Johannes; Sorice, Rossella; Spector, Tim D.; Starr, John M.; Stöckl, Doris; Strauch, Konstantin; Stumvoll, Michael; Swertz, Morris A.; Thorsteinsdottir, Unnur; Thurik, A. Roy; Timpson, Nicholas J.; Tönjes, Anke; Tung, Joyce Y.; Uitterlinden, André G.; Vaccargiu, Simona; Viikari, Jorma; Vitart, Veronique; Völzke, Henry; Vollenweider, Peter; Vuckovic, Dragana; Waage, Johannes; Wagner, Gert G.; Wang, Jie Jin; Wareham, Nicholas J.; Weir, David R.; Willemsen, Gonneke; Willeit, Johann; Wright, Alan F.; Zondervan, Krina T.; Stefansson, Kari; Krueger, Robert F.; Lee, James J.; Benjamin, Daniel J.; Cesarini, David; Koellinger, Philipp D.; den Hoed, Marcel; Snieder, Harold; Mills, Melinda C.

2017-01-01

The genetic architecture of human reproductive behavior – age at first birth (AFB) and number of children ever born (NEB) – has a strong relationship with fitness, human development, infertility and risk of neuropsychiatric disorders. However, very few genetic loci have been identified and the underlying mechanisms of AFB and NEB are poorly understood. We report the largest genome-wide association study to date of both sexes including 251,151 individuals for AFB and 343,072 for NEB. We identified 12 independent loci that are significantly associated with AFB and/or NEB in a SNP-based genome-wide association study, and four additional loci in a gene-based effort. These loci harbor genes that are likely to play a role – either directly or by affecting non-local gene expression – in human reproduction and infertility, thereby increasing our understanding of these complex traits. PMID:27798627

Razões entre componentes da variabilidade de características quantitativas simuladas com efeitos genéticos de dominância e sobredominância Ratios between variability components of simulated quantitative traits with genetic effects of dominance and overdominance

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Elizângela Emídio Cunha

2009-10-01

Full Text Available Foram avaliadas as razões entre componentes da variabilidade de características quantitativas simuladas a partir de genoma incorporando efeitos genéticos não-aditivos em populações de acasalamento ao acaso e de seleção fenotípica a curto prazo. Estudaram-se uma característica de baixa (h² = 0,10 e outra de alta herdabilidade (h² = 0,60 influenciadas por 600 locos bialélicos. Cinco modelos de ação gênica foram simulados, dos quais quatro incluíram dominância completa e positiva para 25, 50, 75 e 100% dos locos (D25, D50, D75 e D100, respectivamente; e um modelo incluiu sobredominância positiva para 50% dos locos. Todos os modelos incluíram efeitos aditivos dos alelos para 100% dos locos. As principais razões quantificadas foram d² (variância de dominância/variância fenotípica e d²a (variância de dominância/variância aditiva. Para as duas características, d² e d²a aumentaram de acordo com o acréscimo na variância de dominância, decorrente da inclusão crescente de locos com desvio da dominância e sob sobredominância. No mesmo modelo, ambas as razões, sobretudo d², são mais elevadas sob alta herdabilidade, o que indica que os efeitos da dominância explicam a maior parte da variabilidade total dessa característica sob seleção.Ratios were assessed between variability components of quantitative traits simulated from the genome incorporating non-additive genetic effects in random mating populations and short-term phenotypic selection. A trait of low (h² = 0.10 heritability and another of high (h² = 0.60 heritability were studied, both influenced by 600 bi-allelic loci. Five gene action models were simulated, of which four included complete and positive dominance for 25, 50, 75 and 100% of the loci (D25, D50, D75 and D100, respectively; and one model included positive overdominance for 50% of the loci. Every model included additive effects of the alleles for 100% of the loci. The main quantified ratios were

Discovery of novel heart rate-associated loci using the Exome Chip

DEFF Research Database (Denmark)

van den Berg, Marten E; Warren, Helen R; Cabrera, Claudia P

2017-01-01

Resting heart rate is a heritable trait, and an increase in heart rate is associated with increased mortality risk. Genome-wide association study analyses have found loci associated with resting heart rate, at the time of our study these loci explained 0.9% of the variation. This study aims to di......) and fetal muscle samples by including our novel variants.Our findings advance the knowledge of the genetic architecture of heart rate, and indicate new candidate genes for follow-up functional studies....

Quantitative trait loci for organ weights and adipose fat composition in Jersey and Limousin back-cross cattle finished on pasture or feedlot.

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Morris, C A; Bottema, C D K; Cullen, N G; Hickey, S M; Esmailizadeh, A K; Siebert, B D; Pitchford, W S

2010-12-01

A QTL study of live animal and carcass traits in beef cattle was carried out in New Zealand and Australia. Back-cross calves (385 heifers and 398 steers) were generated, with Jersey and Limousin backgrounds. This paper reports on weights of eight organs (heart, liver, lungs, kidneys, spleen, gastro-intestinal tract, fat, and rumen contents) and 12 fat composition traits (fatty acid (FA) percentages, saturated and monounsaturated FA subtotals, and fat melting point). The New Zealand cattle were reared and finished on pasture, whilst Australian cattle were reared on grass and finished on grain for at least 180 days. For organ weights and fat composition traits, 10 and 12 significant QTL locations (PGenetics © 2010 Stichting International Foundation for Animal Genetics.

Genomic Regions Influencing Seminal Root Traits in Barley.

Science.gov (United States)

Robinson, Hannah; Hickey, Lee; Richard, Cecile; Mace, Emma; Kelly, Alison; Borrell, Andrew; Franckowiak, Jerome; Fox, Glen

2016-03-01

Water availability is a major limiting factor for crop production, making drought adaptation and its many component traits a desirable attribute of plant cultivars. Previous studies in cereal crops indicate that root traits expressed at early plant developmental stages, such as seminal root angle and root number, are associated with water extraction at different depths. Here, we conducted the first study to map seminal root traits in barley ( L.). Using a recently developed high-throughput phenotyping method, a panel of 30 barley genotypes and a doubled-haploid (DH) population (ND24260 × 'Flagship') comprising 330 lines genotyped with diversity array technology (DArT) markers were evaluated for seminal root angle (deviation from vertical) and root number under controlled environmental conditions. A high degree of phenotypic variation was observed in the panel of 30 genotypes: 13.5 to 82.2 and 3.6 to 6.9° for root angle and root number, respectively. A similar range was observed in the DH population: 16.4 to 70.5 and 3.6 to 6.5° for root angle and number, respectively. Seven quantitative trait loci (QTL) for seminal root traits (root angle, two QTL; root number, five QTL) were detected in the DH population. A major QTL influencing both root angle and root number (/) was positioned on chromosome 5HL. Across-species analysis identified 10 common genes underlying root trait QTL in barley, wheat ( L.), and sorghum [ (L.) Moench]. Here, we provide insight into seminal root phenotypes and provide a first look at the genetics controlling these traits in barley. Copyright © 2016 Crop Science Society of America.