Long- and short-term selective forces on malaria parasite genomes

KAUST Repository

Nygaard, Sanne

2010-09-09

Plasmodium parasites, the causal agents of malaria, result in more than 1 million deaths annually. Plasmodium are unicellular eukaryotes with small ~23 Mb genomes encoding ~5200 protein-coding genes. The protein-coding genes comprise about half of these genomes. Although evolutionary processes have a significant impact on malaria control, the selective pressures within Plasmodium genomes are poorly understood, particularly in the non-protein-coding portion of the genome. We use evolutionary methods to describe selective processes in both the coding and non-coding regions of these genomes. Based on genome alignments of seven Plasmodium species, we show that protein-coding, intergenic and intronic regions are all subject to purifying selection and we identify 670 conserved non-genic elements. We then use genome-wide polymorphism data from P. falciparum to describe short-term selective processes in this species and identify some candidate genes for balancing (diversifying) selection. Our analyses suggest that there are many functional elements in the non-genic regions of these genomes and that adaptive evolution has occurred more frequently in the protein-coding regions of the genome. © 2010 Nygaard et al.

Genome-wide selection signatures in Pinzgau cattle

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Radovan Kasarda

2015-08-01

Full Text Available The aim of this study was to identify the evidence of recent selection based on estimation of the integrated Haplotype Score (iHS, population differentiation index (FST and characterize affected regions near QTL associated with traits under strong selection in Pinzgau cattle. In total 21 Austrian and 19 Slovak purebreed bulls genotyped with Illumina bovineHD and  bovineSNP50 BeadChip were used to identify genomic regions under selection. Only autosomal loci with call rate higher than 90%, minor allele frequency higher than 0.01 and Hardy-Weinberg equlibrium limit of 0.001 were included in the subsequent analyses of selection sweeps presence. The final dataset was consisted from 30538 SNPs with 81.86 kb average adjacent SNPs spacing. The iHS score were averaged into non-overlapping 500 kb segments across the genome. The FST values were also plotted against genome position based on sliding windows approach and averaged over 8 consecutive SNPs. Based on integrated Haplotype Score evaluation only 7 regions with iHS score higher than 1.7 was found. The average iHS score observed for each adjacent syntenic regions indicated slight effect of recent selection in analysed group of Pinzgau bulls. The level of genetic differentiation between Austrian and Slovak bulls estimated based on FST index was low. Only 24% of FST values calculated for each SNP was greather than 0.01. By using sliding windows approach was found that 5% of analysed windows had higher value than 0.01. Our results indicated use of similar selection scheme in breeding programs of Slovak and Austrian Pinzgau bulls. The evidence for genome-wide association between signatures of selection and regions affecting complex traits such as milk production was insignificant, because the loci in segments identified as affected by selection were very distant from each other. Identification of genomic regions that may be under pressure of selection for phenotypic traits to better understanding of the

Integrating genomic selection into dairy cattle breeding programmes: a review.

Science.gov (United States)

Bouquet, A; Juga, J

2013-05-01

Extensive genetic progress has been achieved in dairy cattle populations on many traits of economic importance because of efficient breeding programmes. Success of these programmes has relied on progeny testing of the best young males to accurately assess their genetic merit and hence their potential for breeding. Over the last few years, the integration of dense genomic information into statistical tools used to make selection decisions, commonly referred to as genomic selection, has enabled gains in predicting accuracy of breeding values for young animals without own performance. The possibility to select animals at an early stage allows defining new breeding strategies aimed at boosting genetic progress while reducing costs. The first objective of this article was to review methods used to model and optimize breeding schemes integrating genomic selection and to discuss their relative advantages and limitations. The second objective was to summarize the main results and perspectives on the use of genomic selection in practical breeding schemes, on the basis of the example of dairy cattle populations. Two main designs of breeding programmes integrating genomic selection were studied in dairy cattle. Genomic selection can be used either for pre-selecting males to be progeny tested or for selecting males to be used as active sires in the population. The first option produces moderate genetic gains without changing the structure of breeding programmes. The second option leads to large genetic gains, up to double those of conventional schemes because of a major reduction in the mean generation interval, but it requires greater changes in breeding programme structure. The literature suggests that genomic selection becomes more attractive when it is coupled with embryo transfer technologies to further increase selection intensity on the dam-to-sire pathway. The use of genomic information also offers new opportunities to improve preservation of genetic variation. However

Sunflower Hybrid Breeding: From Markers to Genomic Selection.

Science.gov (United States)

Dimitrijevic, Aleksandra; Horn, Renate

2017-01-01

In sunflower, molecular markers for simple traits as, e.g., fertility restoration, high oleic acid content, herbicide tolerance or resistances to Plasmopara halstedii, Puccinia helianthi , or Orobanche cumana have been successfully used in marker-assisted breeding programs for years. However, agronomically important complex quantitative traits like yield, heterosis, drought tolerance, oil content or selection for disease resistance, e.g., against Sclerotinia sclerotiorum have been challenging and will require genome-wide approaches. Plant genetic resources for sunflower are being collected and conserved worldwide that represent valuable resources to study complex traits. Sunflower association panels provide the basis for genome-wide association studies, overcoming disadvantages of biparental populations. Advances in technologies and the availability of the sunflower genome sequence made novel approaches on the whole genome level possible. Genotype-by-sequencing, and whole genome sequencing based on next generation sequencing technologies facilitated the production of large amounts of SNP markers for high density maps as well as SNP arrays and allowed genome-wide association studies and genomic selection in sunflower. Genome wide or candidate gene based association studies have been performed for traits like branching, flowering time, resistance to Sclerotinia head and stalk rot. First steps in genomic selection with regard to hybrid performance and hybrid oil content have shown that genomic selection can successfully address complex quantitative traits in sunflower and will help to speed up sunflower breeding programs in the future. To make sunflower more competitive toward other oil crops higher levels of resistance against pathogens and better yield performance are required. In addition, optimizing plant architecture toward a more complex growth type for higher plant densities has the potential to considerably increase yields per hectare. Integrative approaches

Sunflower Hybrid Breeding: From Markers to Genomic Selection

Directory of Open Access Journals (Sweden)

Aleksandra Dimitrijevic

2018-01-01

Full Text Available In sunflower, molecular markers for simple traits as, e.g., fertility restoration, high oleic acid content, herbicide tolerance or resistances to Plasmopara halstedii, Puccinia helianthi, or Orobanche cumana have been successfully used in marker-assisted breeding programs for years. However, agronomically important complex quantitative traits like yield, heterosis, drought tolerance, oil content or selection for disease resistance, e.g., against Sclerotinia sclerotiorum have been challenging and will require genome-wide approaches. Plant genetic resources for sunflower are being collected and conserved worldwide that represent valuable resources to study complex traits. Sunflower association panels provide the basis for genome-wide association studies, overcoming disadvantages of biparental populations. Advances in technologies and the availability of the sunflower genome sequence made novel approaches on the whole genome level possible. Genotype-by-sequencing, and whole genome sequencing based on next generation sequencing technologies facilitated the production of large amounts of SNP markers for high density maps as well as SNP arrays and allowed genome-wide association studies and genomic selection in sunflower. Genome wide or candidate gene based association studies have been performed for traits like branching, flowering time, resistance to Sclerotinia head and stalk rot. First steps in genomic selection with regard to hybrid performance and hybrid oil content have shown that genomic selection can successfully address complex quantitative traits in sunflower and will help to speed up sunflower breeding programs in the future. To make sunflower more competitive toward other oil crops higher levels of resistance against pathogens and better yield performance are required. In addition, optimizing plant architecture toward a more complex growth type for higher plant densities has the potential to considerably increase yields per hectare

Sunflower Hybrid Breeding: From Markers to Genomic Selection

Science.gov (United States)

Dimitrijevic, Aleksandra; Horn, Renate

2018-01-01

In sunflower, molecular markers for simple traits as, e.g., fertility restoration, high oleic acid content, herbicide tolerance or resistances to Plasmopara halstedii, Puccinia helianthi, or Orobanche cumana have been successfully used in marker-assisted breeding programs for years. However, agronomically important complex quantitative traits like yield, heterosis, drought tolerance, oil content or selection for disease resistance, e.g., against Sclerotinia sclerotiorum have been challenging and will require genome-wide approaches. Plant genetic resources for sunflower are being collected and conserved worldwide that represent valuable resources to study complex traits. Sunflower association panels provide the basis for genome-wide association studies, overcoming disadvantages of biparental populations. Advances in technologies and the availability of the sunflower genome sequence made novel approaches on the whole genome level possible. Genotype-by-sequencing, and whole genome sequencing based on next generation sequencing technologies facilitated the production of large amounts of SNP markers for high density maps as well as SNP arrays and allowed genome-wide association studies and genomic selection in sunflower. Genome wide or candidate gene based association studies have been performed for traits like branching, flowering time, resistance to Sclerotinia head and stalk rot. First steps in genomic selection with regard to hybrid performance and hybrid oil content have shown that genomic selection can successfully address complex quantitative traits in sunflower and will help to speed up sunflower breeding programs in the future. To make sunflower more competitive toward other oil crops higher levels of resistance against pathogens and better yield performance are required. In addition, optimizing plant architecture toward a more complex growth type for higher plant densities has the potential to considerably increase yields per hectare. Integrative approaches

Signatures of selection in tilapia revealed by whole genome resequencing.

Science.gov (United States)

Xia, Jun Hong; Bai, Zhiyi; Meng, Zining; Zhang, Yong; Wang, Le; Liu, Feng; Jing, Wu; Wan, Zi Yi; Li, Jiale; Lin, Haoran; Yue, Gen Hua

2015-09-16

Natural selection and selective breeding for genetic improvement have left detectable signatures within the genome of a species. Identification of selection signatures is important in evolutionary biology and for detecting genes that facilitate to accelerate genetic improvement. However, selection signatures, including artificial selection and natural selection, have only been identified at the whole genome level in several genetically improved fish species. Tilapia is one of the most important genetically improved fish species in the world. Using next-generation sequencing, we sequenced the genomes of 47 tilapia individuals. We identified a total of 1.43 million high-quality SNPs and found that the LD block sizes ranged from 10-100 kb in tilapia. We detected over a hundred putative selective sweep regions in each line of tilapia. Most selection signatures were located in non-coding regions of the tilapia genome. The Wnt signaling, gonadotropin-releasing hormone receptor and integrin signaling pathways were under positive selection in all improved tilapia lines. Our study provides a genome-wide map of genetic variation and selection footprints in tilapia, which could be important for genetic studies and accelerating genetic improvement of tilapia.

Review. Promises, pitfalls and challenges of genomic selection in breeding programs

Energy Technology Data Exchange (ETDEWEB)

Ibanez-Escriche, N.; Gonzalez-Recio, O.

2011-07-01

The aim of this work was to review the main challenges and pitfalls of the implementation of genomic selection in the breeding programs of different livestock species. Genomic selection is now one of the main challenges in animal breeding and genetics. Its application could considerably increase the genetic gain in traits of interest. However, the success of its practical implementation depends on the selection scheme characteristics, and these must be studied for each particular case. In dairy cattle, especially in Holsteins, genomic selection is a reality. However, in other livestock species (beef cattle, small ruminants, monogastrics and fish) genomic selection has mainly been used experimentally. The main limitation for its implementation in the mentioned livestock species is the high geno typing costs compared to the low selection value of the candidate. Nevertheless, nowadays the possibility of using single-nucleotide polymorphism (SNP) chips of low density to make genomic selection applications economically feasible is under study. Economic studies may optimize the benefits of genomic selection (GS) to include new traits in the breeding goals. It is evident that genomic selection offers great potential; however, a suitable geno typing strategy and recording system for each case is needed in order to properly exploit it. (Author) 50 refs.

Will genomic selection be a practical method for plant breeding?

OpenAIRE

Nakaya, Akihiro; Isobe, Sachiko N.

2012-01-01

Background Genomic selection or genome-wide selection (GS) has been highlighted as a new approach for marker-assisted selection (MAS) in recent years. GS is a form of MAS that selects favourable individuals based on genomic estimated breeding values. Previous studies have suggested the utility of GS, especially for capturing small-effect quantitative trait loci, but GS has not become a popular methodology in the field of plant breeding, possibly because there is insufficient information avail...

Genome size variation affects song attractiveness in grasshoppers: evidence for sexual selection against large genomes.

Science.gov (United States)

Schielzeth, Holger; Streitner, Corinna; Lampe, Ulrike; Franzke, Alexandra; Reinhold, Klaus

2014-12-01

Genome size is largely uncorrelated to organismal complexity and adaptive scenarios. Genetic drift as well as intragenomic conflict have been put forward to explain this observation. We here study the impact of genome size on sexual attractiveness in the bow-winged grasshopper Chorthippus biguttulus. Grasshoppers show particularly large variation in genome size due to the high prevalence of supernumerary chromosomes that are considered (mildly) selfish, as evidenced by non-Mendelian inheritance and fitness costs if present in high numbers. We ranked male grasshoppers by song characteristics that are known to affect female preferences in this species and scored genome sizes of attractive and unattractive individuals from the extremes of this distribution. We find that attractive singers have significantly smaller genomes, demonstrating that genome size is reflected in male courtship songs and that females prefer songs of males with small genomes. Such a genome size dependent mate preference effectively selects against selfish genetic elements that tend to increase genome size. The data therefore provide a novel example of how sexual selection can reinforce natural selection and can act as an agent in an intragenomic arms race. Furthermore, our findings indicate an underappreciated route of how choosy females could gain indirect benefits. © 2014 The Author(s). Evolution © 2014 The Society for the Study of Evolution.

A primer on high-throughput computing for genomic selection.

Science.gov (United States)

Wu, Xiao-Lin; Beissinger, Timothy M; Bauck, Stewart; Woodward, Brent; Rosa, Guilherme J M; Weigel, Kent A; Gatti, Natalia de Leon; Gianola, Daniel

2011-01-01

High-throughput computing (HTC) uses computer clusters to solve advanced computational problems, with the goal of accomplishing high-throughput over relatively long periods of time. In genomic selection, for example, a set of markers covering the entire genome is used to train a model based on known data, and the resulting model is used to predict the genetic merit of selection candidates. Sophisticated models are very computationally demanding and, with several traits to be evaluated sequentially, computing time is long, and output is low. In this paper, we present scenarios and basic principles of how HTC can be used in genomic selection, implemented using various techniques from simple batch processing to pipelining in distributed computer clusters. Various scripting languages, such as shell scripting, Perl, and R, are also very useful to devise pipelines. By pipelining, we can reduce total computing time and consequently increase throughput. In comparison to the traditional data processing pipeline residing on the central processors, performing general-purpose computation on a graphics processing unit provide a new-generation approach to massive parallel computing in genomic selection. While the concept of HTC may still be new to many researchers in animal breeding, plant breeding, and genetics, HTC infrastructures have already been built in many institutions, such as the University of Wisconsin-Madison, which can be leveraged for genomic selection, in terms of central processing unit capacity, network connectivity, storage availability, and middleware connectivity. Exploring existing HTC infrastructures as well as general-purpose computing environments will further expand our capability to meet increasing computing demands posed by unprecedented genomic data that we have today. We anticipate that HTC will impact genomic selection via better statistical models, faster solutions, and more competitive products (e.g., from design of marker panels to realized

Recent and ongoing selection in the human genome

DEFF Research Database (Denmark)

Nielsen, Rasmus; Hellmann, Ines; Hubisz, Melissa

2007-01-01

The recent availability of genome-scale genotyping data has led to the identification of regions of the human genome that seem to have been targeted by selection. These findings have increased our understanding of the evolutionary forces that affect the human genome, have augmented our knowledge...... of gene function and promise to increase our understanding of the genetic basis of disease. However, inferences of selection are challenged by several confounding factors, especially the complex demographic history of human populations, and concordance between studies is variable. Although such studies...

Annotation-Based Whole Genomic Prediction and Selection

DEFF Research Database (Denmark)

Kadarmideen, Haja; Do, Duy Ngoc; Janss, Luc

Genomic selection is widely used in both animal and plant species, however, it is performed with no input from known genomic or biological role of genetic variants and therefore is a black box approach in a genomic era. This study investigated the role of different genomic regions and detected QTLs...... in their contribution to estimated genomic variances and in prediction of genomic breeding values by applying SNP annotation approaches to feed efficiency. Ensembl Variant Predictor (EVP) and Pig QTL database were used as the source of genomic annotation for 60K chip. Genomic prediction was performed using the Bayes...... classes. Predictive accuracy was 0.531, 0.532, 0.302, and 0.344 for DFI, RFI, ADG and BF, respectively. The contribution per SNP to total genomic variance was similar among annotated classes across different traits. Predictive performance of SNP classes did not significantly differ from randomized SNP...

Multiple-Trait Genomic Selection Methods Increase Genetic Value Prediction Accuracy

Science.gov (United States)

Jia, Yi; Jannink, Jean-Luc

2012-01-01

Genetic correlations between quantitative traits measured in many breeding programs are pervasive. These correlations indicate that measurements of one trait carry information on other traits. Current single-trait (univariate) genomic selection does not take advantage of this information. Multivariate genomic selection on multiple traits could accomplish this but has been little explored and tested in practical breeding programs. In this study, three multivariate linear models (i.e., GBLUP, BayesA, and BayesCπ) were presented and compared to univariate models using simulated and real quantitative traits controlled by different genetic architectures. We also extended BayesA with fixed hyperparameters to a full hierarchical model that estimated hyperparameters and BayesCπ to impute missing phenotypes. We found that optimal marker-effect variance priors depended on the genetic architecture of the trait so that estimating them was beneficial. We showed that the prediction accuracy for a low-heritability trait could be significantly increased by multivariate genomic selection when a correlated high-heritability trait was available. Further, multiple-trait genomic selection had higher prediction accuracy than single-trait genomic selection when phenotypes are not available on all individuals and traits. Additional factors affecting the performance of multiple-trait genomic selection were explored. PMID:23086217

A Primer on High-Throughput Computing for Genomic Selection

Directory of Open Access Journals (Sweden)

Xiao-Lin eWu

2011-02-01

Full Text Available High-throughput computing (HTC uses computer clusters to solve advanced computational problems, with the goal of accomplishing high throughput over relatively long periods of time. In genomic selection, for example, a set of markers covering the entire genome is used to train a model based on known data, and the resulting model is used to predict the genetic merit of selection candidates. Sophisticated models are very computationally demanding and, with several traits to be evaluated sequentially, computing time is long and output is low. In this paper, we present scenarios and basic principles of how HTC can be used in genomic selection, implemented using various techniques from simple batch processing to pipelining in distributed computer clusters. Various scripting languages, such as shell scripting, Perl and R, are also very useful to devise pipelines. By pipelining, we can reduce total computing time and consequently increase throughput. In comparison to the traditional data processing pipeline residing on the central processors, performing general purpose computation on a graphics processing unit (GPU provide a new-generation approach to massive parallel computing in genomic selection. While the concept of HTC may still be new to many researchers in animal breeding, plant breeding, and genetics, HTC infrastructures have already been built in many institutions, such as the University of Wisconsin – Madison, which can be leveraged for genomic selection, in terms of central processing unit (CPU capacity, network connectivity, storage availability, and middleware connectivity. Exploring existing HTC infrastructures as well as general purpose computing environments will further expand our capability to meet increasing computing demands posed by unprecedented genomic data that we have today. We anticipate that HTC will impact genomic selection via better statistical models, faster solutions, and more competitive products (e.g., from design of

Selection on Optimal Haploid Value Increases Genetic Gain and Preserves More Genetic Diversity Relative to Genomic Selection.

Science.gov (United States)

Daetwyler, Hans D; Hayden, Matthew J; Spangenberg, German C; Hayes, Ben J

2015-08-01

Doubled haploids are routinely created and phenotypically selected in plant breeding programs to accelerate the breeding cycle. Genomic selection, which makes use of both phenotypes and genotypes, has been shown to further improve genetic gain through prediction of performance before or without phenotypic characterization of novel germplasm. Additional opportunities exist to combine genomic prediction methods with the creation of doubled haploids. Here we propose an extension to genomic selection, optimal haploid value (OHV) selection, which predicts the best doubled haploid that can be produced from a segregating plant. This method focuses selection on the haplotype and optimizes the breeding program toward its end goal of generating an elite fixed line. We rigorously tested OHV selection breeding programs, using computer simulation, and show that it results in up to 0.6 standard deviations more genetic gain than genomic selection. At the same time, OHV selection preserved a substantially greater amount of genetic diversity in the population than genomic selection, which is important to achieve long-term genetic gain in breeding populations. Copyright © 2015 by the Genetics Society of America.

[Genomic selection of milk cattle. The practical application over five years].

Science.gov (United States)

Smaragdov, M G

2013-11-01

Genomic selection is a method based on the use of single nucleotide polymorphisms (SNPs) as markers for detecting animal or plant genotype values. The review describes the genomic selection of milk cattle 5 years after the design of dense SNP chips. References to the application of genomic selection to other animal and plant species are given. The main principles of constructing linear and nonlinear mathematical models that allow one to determine genomic estimates in animals are briefly described. Particular attention is focused on the accuracy and the phenomenon of the additivity ofgenomic estimates, as well as to the prospective use of various genomic selection schemes that consider it over dozens of generations. Information including international organizations that provide the consolidation of genomic information from different countries aimed at designing global reference populations of milk cattle is reported. The results of the practical application of genomic selection to detecting of the breeding value of milk cattle over 5 years are demonstrated in the table, which makes it possible to visually assess the achievements of this highly technological field of cattle breeding.

Genomic Selection for Drought Tolerance Using Genome-Wide SNPs in Maize

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Thirunavukkarasu Nepolean

2017-04-01

Full Text Available Traditional breeding strategies for selecting superior genotypes depending on phenotypic traits have proven to be of limited success, as this direct selection is hindered by low heritability, genetic interactions such as epistasis, environmental-genotype interactions, and polygenic effects. With the advent of new genomic tools, breeders have paved a way for selecting superior breeds. Genomic selection (GS has emerged as one of the most important approaches for predicting genotype performance. Here, we tested the breeding values of 240 maize subtropical lines phenotyped for drought at different environments using 29,619 cured SNPs. Prediction accuracies of seven genomic selection models (ridge regression, LASSO, elastic net, random forest, reproducing kernel Hilbert space, Bayes A and Bayes B were tested for their agronomic traits. Though prediction accuracies of Bayes B, Bayes A and RKHS were comparable, Bayes B outperformed the other models by predicting highest Pearson correlation coefficient in all three environments. From Bayes B, a set of the top 1053 significant SNPs with higher marker effects was selected across all datasets to validate the genes and QTLs. Out of these 1053 SNPs, 77 SNPs associated with 10 drought-responsive transcription factors. These transcription factors were associated with different physiological and molecular functions (stomatal closure, root development, hormonal signaling and photosynthesis. Of several models, Bayes B has been shown to have the highest level of prediction accuracy for our data sets. Our experiments also highlighted several SNPs based on their performance and relative importance to drought tolerance. The result of our experiments is important for the selection of superior genotypes and candidate genes for breeding drought-tolerant maize hybrids.

Maximizing Crossbred Performance through Purebred Genomic Selection

DEFF Research Database (Denmark)

Esfandyari, Hadi; Sørensen, Anders Christian; Bijma, Pieter

Genomic selection (GS) can be used to select purebreds for crossbred performance (CP). As dominance is the likely genetic basis of heterosis, explicitly including dominance in the GS model may be beneficial for selection of purebreds for CP, when estimating allelic effects from pure line data. Th...

Does genomic selection have a future in plant breeding?

Science.gov (United States)

Jonas, Elisabeth; de Koning, Dirk-Jan

2013-09-01

Plant breeding largely depends on phenotypic selection in plots and only for some, often disease-resistance-related traits, uses genetic markers. The more recently developed concept of genomic selection, using a black box approach with no need of prior knowledge about the effect or function of individual markers, has also been proposed as a great opportunity for plant breeding. Several empirical and theoretical studies have focused on the possibility to implement this as a novel molecular method across various species. Although we do not question the potential of genomic selection in general, in this Opinion, we emphasize that genomic selection approaches from dairy cattle breeding cannot be easily applied to complex plant breeding. Copyright © 2013 Elsevier Ltd. All rights reserved.

Efficient oligonucleotide probe selection for pan-genomic tiling arrays

Directory of Open Access Journals (Sweden)

Zhang Wei

2009-09-01

Full Text Available Abstract Background Array comparative genomic hybridization is a fast and cost-effective method for detecting, genotyping, and comparing the genomic sequence of unknown bacterial isolates. This method, as with all microarray applications, requires adequate coverage of probes targeting the regions of interest. An unbiased tiling of probes across the entire length of the genome is the most flexible design approach. However, such a whole-genome tiling requires that the genome sequence is known in advance. For the accurate analysis of uncharacterized bacteria, an array must query a fully representative set of sequences from the species' pan-genome. Prior microarrays have included only a single strain per array or the conserved sequences of gene families. These arrays omit potentially important genes and sequence variants from the pan-genome. Results This paper presents a new probe selection algorithm (PanArray that can tile multiple whole genomes using a minimal number of probes. Unlike arrays built on clustered gene families, PanArray uses an unbiased, probe-centric approach that does not rely on annotations, gene clustering, or multi-alignments. Instead, probes are evenly tiled across all sequences of the pan-genome at a consistent level of coverage. To minimize the required number of probes, probes conserved across multiple strains in the pan-genome are selected first, and additional probes are used only where necessary to span polymorphic regions of the genome. The viability of the algorithm is demonstrated by array designs for seven different bacterial pan-genomes and, in particular, the design of a 385,000 probe array that fully tiles the genomes of 20 different Listeria monocytogenes strains with overlapping probes at greater than twofold coverage. Conclusion PanArray is an oligonucleotide probe selection algorithm for tiling multiple genome sequences using a minimal number of probes. It is capable of fully tiling all genomes of a species on

Practical Approaches for Detecting Selection in Microbial Genomes

OpenAIRE

Hedge, Jessica; Wilson, Daniel J.

2016-01-01

Microbial genome evolution is shaped by a variety of selective pressures. Understanding how these processes occur can help to address important problems in microbiology by explaining observed differences in phenotypes, including virulence and resistance to antibiotics. Greater access to whole-genome sequencing provides microbiologists with the opportunity to perform large-scale analyses of selection in novel settings, such as within individual hosts. This tutorial aims to guide researchers th...

Genomic Selection in Multi-environment Crop Trials.

Science.gov (United States)

Oakey, Helena; Cullis, Brian; Thompson, Robin; Comadran, Jordi; Halpin, Claire; Waugh, Robbie

2016-05-03

Genomic selection in crop breeding introduces modeling challenges not found in animal studies. These include the need to accommodate replicate plants for each line, consider spatial variation in field trials, address line by environment interactions, and capture nonadditive effects. Here, we propose a flexible single-stage genomic selection approach that resolves these issues. Our linear mixed model incorporates spatial variation through environment-specific terms, and also randomization-based design terms. It considers marker, and marker by environment interactions using ridge regression best linear unbiased prediction to extend genomic selection to multiple environments. Since the approach uses the raw data from line replicates, the line genetic variation is partitioned into marker and nonmarker residual genetic variation (i.e., additive and nonadditive effects). This results in a more precise estimate of marker genetic effects. Using barley height data from trials, in 2 different years, of up to 477 cultivars, we demonstrate that our new genomic selection model improves predictions compared to current models. Analyzing single trials revealed improvements in predictive ability of up to 5.7%. For the multiple environment trial (MET) model, combining both year trials improved predictive ability up to 11.4% compared to a single environment analysis. Benefits were significant even when fewer markers were used. Compared to a single-year standard model run with 3490 markers, our partitioned MET model achieved the same predictive ability using between 500 and 1000 markers depending on the trial. Our approach can be used to increase accuracy and confidence in the selection of the best lines for breeding and/or, to reduce costs by using fewer markers. Copyright © 2016 Oakey et al.

Genomic Selection Using Extreme Phenotypes and Pre-Selection of SNPs in Large Yellow Croaker (Larimichthys crocea).

Science.gov (United States)

Dong, Linsong; Xiao, Shijun; Chen, Junwei; Wan, Liang; Wang, Zhiyong

2016-10-01

Genomic selection (GS) is an effective method to improve predictive accuracies of genetic values. However, high cost in genotyping will limit the application of this technology in some species. Therefore, it is necessary to find some methods to reduce the genotyping costs in genomic selection. Large yellow croaker is one of the most commercially important marine fish species in southeast China and Eastern Asia. In this study, genotyping-by-sequencing was used to construct the libraries for the NGS sequencing and find 29,748 SNPs in the genome. Two traits, eviscerated weight (EW) and the ratio between eviscerated weight and whole body weight (REW), were chosen to study. Two strategies to reduce the costs were proposed as follows: selecting extreme phenotypes (EP) for genotyping in reference population or pre-selecting SNPs to construct low-density marker panels in candidates. Three methods of pre-selection of SNPs, i.e., pre-selecting SNPs by absolute effects (SE), by single marker analysis (SMA), and by fixed intervals of sequence number (EL), were studied. The results showed that using EP was a feasible method to save the genotyping costs in reference population. Heritability did not seem to have obvious influences on the predictive abilities estimated by EP. Using SMA was the most feasible method to save the genotyping costs in candidates. In addition, the combination of EP and SMA in genomic selection also showed good results, especially for trait of REW. We also described how to apply the new methods in genomic selection and compared the genotyping costs before and after using the new methods. Our study may not only offer a reference for aquatic genomic breeding but also offer a reference for genomic prediction in other species including livestock and plants, etc.

Annotation of selection strengths in viral genomes

DEFF Research Database (Denmark)

McCauley, Stephen; de Groot, Saskia; Mailund, Thomas

2007-01-01

Motivation: Viral genomes tend to code in overlapping reading frames to maximize information content. This may result in atypical codon bias and particular evolutionary constraints. Due to the fast mutation rate of viruses, there is additional strong evidence for varying selection between intra......- and intergenomic regions. The presence of multiple coding regions complicates the concept of Ka/Ks ratio, and thus begs for an alternative approach when investigating selection strengths. Building on the paper by McCauley & Hein (2006), we develop a method for annotating a viral genome coding in overlapping...... may thus achieve an annotation both of coding regions as well as selection strengths, allowing us to investigate different selection patterns and hypotheses. Results: We illustrate our method by applying it to a multiple alignment of four HIV2 sequences, as well as four Hepatitis B sequences. We...

Assessing Predictive Properties of Genome-Wide Selection in Soybeans

Directory of Open Access Journals (Sweden)

Alencar Xavier

2016-08-01

Full Text Available Many economically important traits in plant breeding have low heritability or are difficult to measure. For these traits, genomic selection has attractive features and may boost genetic gains. Our goal was to evaluate alternative scenarios to implement genomic selection for yield components in soybean (Glycine max L. merr. We used a nested association panel with cross validation to evaluate the impacts of training population size, genotyping density, and prediction model on the accuracy of genomic prediction. Our results indicate that training population size was the factor most relevant to improvement in genome-wide prediction, with greatest improvement observed in training sets up to 2000 individuals. We discuss assumptions that influence the choice of the prediction model. Although alternative models had minor impacts on prediction accuracy, the most robust prediction model was the combination of reproducing kernel Hilbert space regression and BayesB. Higher genotyping density marginally improved accuracy. Our study finds that breeding programs seeking efficient genomic selection in soybeans would best allocate resources by investing in a representative training set.

Assessing Predictive Properties of Genome-Wide Selection in Soybeans.

Science.gov (United States)

Xavier, Alencar; Muir, William M; Rainey, Katy Martin

2016-08-09

Many economically important traits in plant breeding have low heritability or are difficult to measure. For these traits, genomic selection has attractive features and may boost genetic gains. Our goal was to evaluate alternative scenarios to implement genomic selection for yield components in soybean (Glycine max L. merr). We used a nested association panel with cross validation to evaluate the impacts of training population size, genotyping density, and prediction model on the accuracy of genomic prediction. Our results indicate that training population size was the factor most relevant to improvement in genome-wide prediction, with greatest improvement observed in training sets up to 2000 individuals. We discuss assumptions that influence the choice of the prediction model. Although alternative models had minor impacts on prediction accuracy, the most robust prediction model was the combination of reproducing kernel Hilbert space regression and BayesB. Higher genotyping density marginally improved accuracy. Our study finds that breeding programs seeking efficient genomic selection in soybeans would best allocate resources by investing in a representative training set. Copyright © 2016 Xavie et al.

Maximizing crossbred performance through purebred genomic selection

DEFF Research Database (Denmark)

Esfandyari, Hadi; Sørensen, Anders Christian; Bijma, Piter

2015-01-01

Background In livestock production, many animals are crossbred, with two distinct advantages: heterosis and breed complementarity. Genomic selection (GS) can be used to select purebred parental lines for crossbred performance (CP). Dominance being the likely genetic basis of heterosis, explicitly...

Performance of Genomic Selection in Mice

OpenAIRE

Legarra, Andrés; Robert-Granié, Christèle; Manfredi, Eduardo; Elsen, Jean-Michel

2008-01-01

Selection plans in plant and animal breeding are driven by genetic evaluation. Recent developments suggest using massive genetic marker information, known as “genomic selection.” There is little evidence of its performance, though. We empirically compared three strategies for selection: (1) use of pedigree and phenotypic information, (2) use of genomewide markers and phenotypic information, and (3) the combination of both. We analyzed four traits from a heterogeneous mouse population (http://...

Practical Approaches for Detecting Selection in Microbial Genomes.

Science.gov (United States)

Hedge, Jessica; Wilson, Daniel J

2016-02-01

Microbial genome evolution is shaped by a variety of selective pressures. Understanding how these processes occur can help to address important problems in microbiology by explaining observed differences in phenotypes, including virulence and resistance to antibiotics. Greater access to whole-genome sequencing provides microbiologists with the opportunity to perform large-scale analyses of selection in novel settings, such as within individual hosts. This tutorial aims to guide researchers through the fundamentals underpinning popular methods for measuring selection in pathogens. These methods are transferable to a wide variety of organisms, and the exercises provided are designed for researchers with any level of programming experience.

Rocksalt MgS solar blind ultra-violet detectors

Directory of Open Access Journals (Sweden)

Ying-Hoi Lai

2012-03-01

Full Text Available Studies using in-situ Auger electron spectroscopy and reflection high energy electron diffraction, and ex-situ high resolution X-ray diffraction and electron backscatter diffraction reveal that a MgS thin film grown directly on a GaAs (100 substrate by molecular beam epitaxy adopts its most stable phase, the rocksalt structure, with a lattice constant of 5.20 Å. A Au/MgS/n+-GaAs (100 Schottky-barrier photodiode was fabricated and its room temperature photoresponse was measured to have a sharp fall-off edge at 235 nm with rejection of more than three orders at 400 nm and higher than five orders at 500 nm, promising for various solar-blind UV detection applications.

Genome-Wide Association Mapping and Genomic Selection for Alfalfa (Medicago sativa) Forage Quality Traits.

Science.gov (United States)

Biazzi, Elisa; Nazzicari, Nelson; Pecetti, Luciano; Brummer, E Charles; Palmonari, Alberto; Tava, Aldo; Annicchiarico, Paolo

2017-01-01

Genetic progress for forage quality has been poor in alfalfa (Medicago sativa L.), the most-grown forage legume worldwide. This study aimed at exploring opportunities for marker-assisted selection (MAS) and genomic selection of forage quality traits based on breeding values of parent plants. Some 154 genotypes from a broadly-based reference population were genotyped by genotyping-by-sequencing (GBS), and phenotyped for leaf-to-stem ratio, leaf and stem contents of protein, neutral detergent fiber (NDF) and acid detergent lignin (ADL), and leaf and stem NDF digestibility after 24 hours (NDFD), of their dense-planted half-sib progenies in three growing conditions (summer harvest, full irrigation; summer harvest, suspended irrigation; autumn harvest). Trait-marker analyses were performed on progeny values averaged over conditions, owing to modest germplasm × condition interaction. Genomic selection exploited 11,450 polymorphic SNP markers, whereas a subset of 8,494 M. truncatula-aligned markers were used for a genome-wide association study (GWAS). GWAS confirmed the polygenic control of quality traits and, in agreement with phenotypic correlations, indicated substantially different genetic control of a given trait in stems and leaves. It detected several SNPs in different annotated genes that were highly linked to stem protein content. Also, it identified a small genomic region on chromosome 8 with high concentration of annotated genes associated with leaf ADL, including one gene probably involved in the lignin pathway. Three genomic selection models, i.e., Ridge-regression BLUP, Bayes B and Bayesian Lasso, displayed similar prediction accuracy, whereas SVR-lin was less accurate. Accuracy values were moderate (0.3-0.4) for stem NDFD and leaf protein content, modest for leaf ADL and NDFD, and low to very low for the other traits. Along with previous results for the same germplasm set, this study indicates that GBS data can be exploited to improve both quality traits

Practical Approaches for Detecting Selection in Microbial Genomes.

Directory of Open Access Journals (Sweden)

Jessica Hedge

2016-02-01

Full Text Available Microbial genome evolution is shaped by a variety of selective pressures. Understanding how these processes occur can help to address important problems in microbiology by explaining observed differences in phenotypes, including virulence and resistance to antibiotics. Greater access to whole-genome sequencing provides microbiologists with the opportunity to perform large-scale analyses of selection in novel settings, such as within individual hosts. This tutorial aims to guide researchers through the fundamentals underpinning popular methods for measuring selection in pathogens. These methods are transferable to a wide variety of organisms, and the exercises provided are designed for researchers with any level of programming experience.

Evaluation of genomic selection for replacement strategies using selection index theory.

Science.gov (United States)

Calus, M P L; Bijma, P; Veerkamp, R F

2015-09-01

Our objective was to investigate the economic effect of prioritizing heifers for replacement at the herd level based on genomic estimated breeding values, and to compute break-even genotyping costs across a wide range of scenarios. Specifically, we aimed to determine the optimal proportion of preselection based on parent average information for all scenarios considered. Considered replacement strategies include a range of different selection intensities by considering different numbers of heifers available for replacement (15-45 in a herd with 100 dairy cows) as well as different replacement rates (15-40%). Use of conventional versus sexed semen was considered, where the latter resulted in having twice as many heifers available for replacement. The baseline scenario relies on prioritization of replacement heifers based on parent average. The first alternative scenario involved genomic selection of heifers, considering that all heifers were genotyped. The benefits of genomic selection in this scenario were computed using a simple formula that only requires the number of lactating animals, the difference in accuracy between parent average and genomic selection (GS), and the selection intensity as input. When all heifers were genotyped, using GS for replacement of heifers was beneficial in most scenarios for current genotyping prices, provided some room exists for selection, in the sense that at least 2 more heifers are available than needed for replacement. In those scenarios, minimum break-even genotyping costs were equal to half the economic value of a standard deviation of the breeding goal. The second alternative scenario involved a preselection based on parent average, followed by GS among all the preselected heifers. It was in almost all cases beneficial to genotype all heifers when conventional semen was used (i.e., to do no preselection). The optimal proportion of preselection based on parent average was at least 0.63 when sexed semen was used. Use of sexed

The Gravity Field of Mars From MGS, Mars Odyssey, and MRO Radio Science

Science.gov (United States)

Genova, Antonio; Goossens, Sander; Lemoine, Frank G.; Mazarico, Erwan; Smith, David E.; Zuber, Maria T.

2015-01-01

The Mars Global Surveyor (MGS), Mars Odyssey (ODY), and Mars Reconnaissance Orbiter (MRO) missions have enabled NASA to conduct reconnaissance and exploration of Mars from orbit for sixteen consecutive years. These radio systems on these spacecraft enabled radio science in orbit around Mars to improve the knowledge of the static structure of the Martian gravitational field. The continuity of the radio tracking data, which cover more than a solar cycle, also provides useful information to characterize the temporal variability of the gravity field, relevant to the planet's internal dynamics and the structure and dynamics of the atmosphere [1]. MGS operated for more than 7 years, between 1999 and 2006, in a frozen sun-synchronous, near-circular, polar orbit with the periapsis at approximately 370 km altitude. ODY and MRO have been orbiting Mars in two separate sun-synchronous orbits at different local times and altitudes. ODY began its mapping phase in 2002 with the periapis at approximately 390 km altitude and 4-5pm Local Solar Time (LST), whereas the MRO science mission started in November 2006 with the periapis at approximately 255 km altitude and 3pm LST. The 16 years of radio tracking data provide useful information on the atmospheric density in the Martian upper atmosphere. We used ODY and MRO radio data to recover the long-term periodicity of the major atmospheric constituents -- CO2, O, and He -- at the orbit altitudes of these two spacecraft [2]. The improved atmospheric model provides a better prediction of the annual and semi-annual variability of the dominant species. Therefore, the inclusion of the recovered model leads to improved orbit determination and an improved gravity field model of Mars with MGS, ODY, and MRO radio tracking data.

Accuracy of genomic selection in European maize elite breeding populations.

Science.gov (United States)

Zhao, Yusheng; Gowda, Manje; Liu, Wenxin; Würschum, Tobias; Maurer, Hans P; Longin, Friedrich H; Ranc, Nicolas; Reif, Jochen C

2012-03-01

Genomic selection is a promising breeding strategy for rapid improvement of complex traits. The objective of our study was to investigate the prediction accuracy of genomic breeding values through cross validation. The study was based on experimental data of six segregating populations from a half-diallel mating design with 788 testcross progenies from an elite maize breeding program. The plants were intensively phenotyped in multi-location field trials and fingerprinted with 960 SNP markers. We used random regression best linear unbiased prediction in combination with fivefold cross validation. The prediction accuracy across populations was higher for grain moisture (0.90) than for grain yield (0.58). The accuracy of genomic selection realized for grain yield corresponds to the precision of phenotyping at unreplicated field trials in 3-4 locations. As for maize up to three generations are feasible per year, selection gain per unit time is high and, consequently, genomic selection holds great promise for maize breeding programs.

Long- and short-term selective forces on malaria parasite genomes

KAUST Repository

Nygaard, Sanne; Braunstein, Alexander; Malsen, Gareth; Van Dongen, Stijn; Gardner, Paul P.; Krogh, Anders; Otto, Thomas D.; Pain, Arnab; Berriman, Matthew; McAuliffe, Jon; Dermitzakis, Emmanouil T.; Jeffares, Daniel C.

2010-01-01

of these genomes. Although evolutionary processes have a significant impact on malaria control, the selective pressures within Plasmodium genomes are poorly understood, particularly in the non-protein-coding portion of the genome. We use evolutionary methods

Genomic selection in maritime pine.

Science.gov (United States)

Isik, Fikret; Bartholomé, Jérôme; Farjat, Alfredo; Chancerel, Emilie; Raffin, Annie; Sanchez, Leopoldo; Plomion, Christophe; Bouffier, Laurent

2016-01-01

A two-generation maritime pine (Pinus pinaster Ait.) breeding population (n=661) was genotyped using 2500 SNP markers. The extent of linkage disequilibrium and utility of genomic selection for growth and stem straightness improvement were investigated. The overall intra-chromosomal linkage disequilibrium was r(2)=0.01. Linkage disequilibrium corrected for genomic relationships derived from markers was smaller (rV(2)=0.006). Genomic BLUP, Bayesian ridge regression and Bayesian LASSO regression statistical models were used to obtain genomic estimated breeding values. Two validation methods (random sampling 50% of the population and 10% of the progeny generation as validation sets) were used with 100 replications. The average predictive ability across statistical models and validation methods was about 0.49 for stem sweep, and 0.47 and 0.43 for total height and tree diameter, respectively. The sensitivity analysis suggested that prior densities (variance explained by markers) had little or no discernible effect on posterior means (residual variance) in Bayesian prediction models. Sampling from the progeny generation for model validation increased the predictive ability of markers for tree diameter and stem sweep but not for total height. The results are promising despite low linkage disequilibrium and low marker coverage of the genome (∼1.39 markers/cM). Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Detection of selection signatures of population-specific genomic regions selected during domestication process in Jinhua pigs.

Science.gov (United States)

Li, Zhengcao; Chen, Jiucheng; Wang, Zhen; Pan, Yuchun; Wang, Qishan; Xu, Ningying; Wang, Zhengguang

2016-12-01

Chinese pigs have been undergoing both natural and artificial selection for thousands of years. Jinhua pigs are of great importance, as they can be a valuable model for exploring the genetic mechanisms linked to meat quality and other traits such as disease resistance, reproduction and production. The purpose of this study was to identify distinctive footprints of selection between Jinhua pigs and other breeds utilizing genome-wide SNP data. Genotyping by genome reducing and sequencing was implemented in order to perform cross-population extended haplotype homozygosity to reveal strong signatures of selection for those economically important traits. This work was performed at a 2% genome level, which comprised 152 006 SNPs genotyped in a total of 517 individuals. Population-specific footprints of selective sweeps were searched for in the genome of Jinhua pigs using six native breeds and three European breeds as reference groups. Several candidate genes associated with meat quality, health and reproduction, such as GH1, CRHR2, TRAF4 and CCK, were found to be overlapping with the significantly positive outliers. Additionally, the results revealed that some genomic regions associated with meat quality, immune response and reproduction in Jinhua pigs have evolved directionally under domestication and subsequent selections. The identified genes and biological pathways in Jinhua pigs showed different selection patterns in comparison with the Chinese and European breeds. © 2016 Stichting International Foundation for Animal Genetics.

[Genomic selection and its application].

Science.gov (United States)

Li, Heng-De; Bao, Zhen-Min; Sun, Xiao-Wen

2011-12-01

Selective breeding is very important in agricultural production and breeding value estimation is the core of selective breeding. With the development of genetic markers, especially high throughput genotyping technology, it becomes available to estimate breeding value at genome level, i.e. genomic selection (GS). In this review, the methods of GS was categorized into two groups: one is to predict genomic estimated breeding value (GEBV) based on the allele effect, such as least squares, random regression - best linear unbiased prediction (RR-BLUP), Bayes and principle component analysis, etc; the other is to predict GEBV with genetic relationship matrix, which constructs genetic relationship matrix via high throughput genetic markers and then predicts GEBV through linear mixed model, i.e. GBLUP. The basic principles of these methods were also introduced according to the above two classifications. Factors affecting GS accuracy include markers of type and density, length of haplotype, the size of reference population, the extent between marker-QTL and so on. Among the methods of GS, Bayes and GBLUP are usually more accurate than the others and least squares is the worst. GBLUP is time-efficient and can combine pedigree with genotypic information, hence it is superior to other methods. Although progress was made in GS, there are still some challenges, for examples, united breeding, long-term genetic gain with GS, and disentangling markers with and without contribution to the traits. GS has been applied in animal and plant breeding practice and also has the potential to predict genetic predisposition in humans and study evolutionary dynamics. GS, which is more precise than the traditional method, is a breakthrough at measuring genetic relationship. Therefore, GS will be a revolutionary event in the history of animal and plant breeding.

Genomic selection improves response to selection in resilience by exploiting genotype by environment interactions

Directory of Open Access Journals (Sweden)

Han Mulder

2016-10-01

Full Text Available Genotype by environment interactions (GxE are very common in livestock and hamper genetic improvement. On the other hand, GxE is a source of genetic variation: genetic variation in response to environment, e.g. environmental perturbations such as heat stress or disease. In livestock breeding, there is tendency to ignore GxE because of increased complexity of models for genetic evaluations and lack of accuracy in extreme environments. GxE, however, creates opportunities to increase resilience of animals towards environmental perturbations. The main aim of the paper is to investigate to which extent GxE can be exploited with traditional and genomic selection methods. Furthermore, we investigated the benefit of reaction norm models compared to conventional methods ignoring GxE. The questions were addressed with selection index theory. GxE was modelled according to a linear reaction norm model in which the environmental gradient is the contemporary group mean. Economic values were based on linear and non-linear profit equations.Accuracies of environment-specific (GEBV were highest in intermediate environments and lowest in extreme environments. Reaction norm models had higher accuracies of (GEBV in extreme environments than conventional models ignoring GxE. Genomic selection always resulted in higher response to selection in all environments than sib or progeny testing schemes. The increase in response was with genomic selection between 9% and 140% compared to sib testing and between 11% and 114% compared to progeny testing when the reference population consisted of 1 million animals across all environments. When the aim was to decrease environmental sensitivity, the response in slope of the reaction norm model with genomic selection was between 1.09 and 319 times larger than with sib or progeny testing and in the right direction in contrast to sib and progeny testing that still increased environmental sensitivity. This shows that genomic selection

CpG islands undermethylation in human genomic regions under selective pressure.

Directory of Open Access Journals (Sweden)

Sergio Cocozza

Full Text Available DNA methylation at CpG islands (CGIs is one of the most intensively studied epigenetic mechanisms. It is fundamental for cellular differentiation and control of transcriptional potential. DNA methylation is involved also in several processes that are central to evolutionary biology, including phenotypic plasticity and evolvability. In this study, we explored the relationship between CpG islands methylation and signatures of selective pressure in Homo Sapiens, using a computational biology approach. By analyzing methylation data of 25 cell lines from the Encyclopedia of DNA Elements (ENCODE Consortium, we compared the DNA methylation of CpG islands in genomic regions under selective pressure with the methylation of CpG islands in the remaining part of the genome. To define genomic regions under selective pressure, we used three different methods, each oriented to provide distinct information about selective events. Independently of the method and of the cell type used, we found evidences of undermethylation of CGIs in human genomic regions under selective pressure. Additionally, by analyzing SNP frequency in CpG islands, we demonstrated that CpG islands in regions under selective pressure show lower genetic variation. Our findings suggest that the CpG islands in regions under selective pressure seem to be somehow more "protected" from methylation when compared with other regions of the genome.

Selection on Optimal Haploid Value Increases Genetic Gain and Preserves More Genetic Diversity Relative to Genomic Selection

OpenAIRE

Daetwyler, Hans D.; Hayden, Matthew J.; Spangenberg, German C.; Hayes, Ben J.

2015-01-01

Doubled haploids are routinely created and phenotypically selected in plant breeding programs to accelerate the breeding cycle. Genomic selection, which makes use of both phenotypes and genotypes, has been shown to further improve genetic gain through prediction of performance before or without phenotypic characterization of novel germplasm. Additional opportunities exist to combine genomic prediction methods with the creation of doubled haploids. Here we propose an extension to genomic selec...

Prediction of malting quality traits in barley based on genome-wide marker data to assess the potential of genomic selection.

Science.gov (United States)

Schmidt, Malthe; Kollers, Sonja; Maasberg-Prelle, Anja; Großer, Jörg; Schinkel, Burkhard; Tomerius, Alexandra; Graner, Andreas; Korzun, Viktor

2016-02-01

Genomic prediction of malting quality traits in barley shows the potential of applying genomic selection to improve selection for malting quality and speed up the breeding process. Genomic selection has been applied to various plant species, mostly for yield or yield-related traits such as grain dry matter yield or thousand kernel weight, and improvement of resistances against diseases. Quality traits have not been the main scope of analysis for genomic selection, but have rather been addressed by marker-assisted selection. In this study, the potential to apply genomic selection to twelve malting quality traits in two commercial breeding programs of spring and winter barley (Hordeum vulgare L.) was assessed. Phenotypic means were calculated combining multilocational field trial data from 3 or 4 years, depending on the trait investigated. Three to five locations were available in each of these years. Heritabilities for malting traits ranged between 0.50 and 0.98. Predictive abilities (PA), as derived from cross validation, ranged between 0.14 to 0.58 for spring barley and 0.40-0.80 for winter barley. Small training sets were shown to be sufficient to obtain useful PAs, possibly due to the narrow genetic base in this breeding material. Deployment of genomic selection in malting barley breeding clearly has the potential to reduce cost intensive phenotyping for quality traits, increase selection intensity and to shorten breeding cycles.

Patterns of positive selection in six Mammalian genomes

DEFF Research Database (Denmark)

Kosiol, Carolin; Vinar, Tomás; da Fonseca, Rute R

2008-01-01

Genome-wide scans for positively selected genes (PSGs) in mammals have provided insight into the dynamics of genome evolution, the genetic basis of differences between species, and the functions of individual genes. However, previous scans have been limited in power and accuracy owing to small...... several new lineage- and clade-specific tests to be applied. Of approximately 16,500 human genes with high-confidence orthologs in at least two other species, 400 genes showed significant evidence of positive selection (FDR... showed evidence of positive selection on particular lineages or clades. As in previous studies, the identified PSGs were enriched for roles in defense/immunity, chemosensory perception, and reproduction, but enrichments were also evident for more specific functions, such as complement-mediated immunity...

Genomic Selection Improves Heat Tolerance in Dairy Cattle

Science.gov (United States)

Garner, J. B.; Douglas, M. L.; Williams, S. R. O; Wales, W. J.; Marett, L. C.; Nguyen, T. T. T.; Reich, C. M.; Hayes, B. J.

2016-01-01

Dairy products are a key source of valuable proteins and fats for many millions of people worldwide. Dairy cattle are highly susceptible to heat-stress induced decline in milk production, and as the frequency and duration of heat-stress events increases, the long term security of nutrition from dairy products is threatened. Identification of dairy cattle more tolerant of heat stress conditions would be an important progression towards breeding better adapted dairy herds to future climates. Breeding for heat tolerance could be accelerated with genomic selection, using genome wide DNA markers that predict tolerance to heat stress. Here we demonstrate the value of genomic predictions for heat tolerance in cohorts of Holstein cows predicted to be heat tolerant and heat susceptible using controlled-climate chambers simulating a moderate heatwave event. Not only was the heat challenge stimulated decline in milk production less in cows genomically predicted to be heat-tolerant, physiological indicators such as rectal and intra-vaginal temperatures had reduced increases over the 4 day heat challenge. This demonstrates that genomic selection for heat tolerance in dairy cattle is a step towards securing a valuable source of nutrition and improving animal welfare facing a future with predicted increases in heat stress events. PMID:27682591

Goals and hurdles for a successful implementation of genomic selection in breeding programme for selected annual and perennial crops.

Science.gov (United States)

Jonas, Elisabeth; de Koning, Dirk Jan

Genomic Selection is an important topic in quantitative genetics and breeding. Not only does it allow the full use of current molecular genetic technologies, it stimulates also the development of new methods and models. Genomic selection, if fully implemented in commercial farming, should have a major impact on the productivity of various agricultural systems. But suggested approaches need to be applicable in commercial breeding populations. Many of the published research studies focus on methodologies. We conclude from the reviewed publications, that a stronger focus on strategies for the implementation of genomic selection in advanced breeding lines, introduction of new varieties, hybrids or multi-line crosses is needed. Efforts to find solutions for a better prediction and integration of environmental influences need to continue within applied breeding schemes. Goals of the implementation of genomic selection into crop breeding should be carefully defined and crop breeders in the private sector will play a substantial part in the decision-making process. However, the lack of published results from studies within, or in collaboration with, private companies diminishes the knowledge on the status of genomic selection within applied breeding programmes. Studies on the implementation of genomic selection in plant breeding need to evaluate models and methods with an enhanced emphasis on population-specific requirements and production environments. Adaptation of methods to breeding schemes or changes to breeding programmes for a better integration of genomic selection strategies are needed across species. More openness with a continuous exchange will contribute to successes.

GGRaSP: A R-package for selecting representative genomes using Gaussian mixture models.

Science.gov (United States)

Clarke, Thomas H; Brinkac, Lauren M; Sutton, Granger; Fouts, Derrick E

2018-04-14

The vast number of available sequenced bacterial genomes occasionally exceeds the facilities of comparative genomic methods or is dominated by a single outbreak strain, and thus a diverse and representative subset is required. Generation of the reduced subset currently requires a priori supervised clustering and sequence-only selection of medoid genomic sequences, independent of any additional genome metrics or strain attributes. The GGRaSP R-package described below generates a reduced subset of genomes that prioritizes maintaining genomes of interest to the user as well as minimizing the loss of genetic variation. The package also allows for unsupervised clustering by modeling the genomic relationships using a Gaussian Mixture Model to select an appropriate cluster threshold. We demonstrate the capabilities of GGRaSP by generating a reduced list of 315 genomes from a genomic dataset of 4600 Escherichia coli genomes, prioritizing selection by type strain and by genome completeness. GGRaSP is available at https://github.com/JCVenterInstitute/ggrasp/. tclarke@jcvi.org. Supplementary data are available at the GitHub site.

Strong signatures of selection in the domestic pig genome

DEFF Research Database (Denmark)

Rubin, Carl-Johan; Megens, Hendrik-Jan; Barrio, Alvaro Martinez

2012-01-01

Domestication of wild boar (Sus scrofa) and subsequent selection have resulted in dramatic phenotypic changes in domestic pigs for a number of traits, including behavior, body composition, reproduction, and coat color. Here we have used whole-genome resequencing to reveal some of the loci that un...... to strong directional selection.......Domestication of wild boar (Sus scrofa) and subsequent selection have resulted in dramatic phenotypic changes in domestic pigs for a number of traits, including behavior, body composition, reproduction, and coat color. Here we have used whole-genome resequencing to reveal some of the loci...... that underlie phenotypic evolution in European domestic pigs. Selective sweep analyses revealed strong signatures of selection at three loci harboring quantitative trait loci that explain a considerable part of one of the most characteristic morphological changes in the domestic pig—the elongation of the back...

Background selection as baseline for nucleotide variation across the Drosophila genome.

Directory of Open Access Journals (Sweden)

Josep M Comeron

2014-06-01

Full Text Available The constant removal of deleterious mutations by natural selection causes a reduction in neutral diversity and efficacy of selection at genetically linked sites (a process called Background Selection, BGS. Population genetic studies, however, often ignore BGS effects when investigating demographic events or the presence of other types of selection. To obtain a more realistic evolutionary expectation that incorporates the unavoidable consequences of deleterious mutations, we generated high-resolution landscapes of variation across the Drosophila melanogaster genome under a BGS scenario independent of polymorphism data. We find that BGS plays a significant role in shaping levels of variation across the entire genome, including long introns and intergenic regions distant from annotated genes. We also find that a very large percentage of the observed variation in diversity across autosomes can be explained by BGS alone, up to 70% across individual chromosome arms at 100-kb scale, thus indicating that BGS predictions can be used as baseline to infer additional types of selection and demographic events. This approach allows detecting several outlier regions with signal of recent adaptive events and selective sweeps. The use of a BGS baseline, however, is particularly appropriate to investigate the presence of balancing selection and our study exposes numerous genomic regions with the predicted signature of higher polymorphism than expected when a BGS context is taken into account. Importantly, we show that these conclusions are robust to the mutation and selection parameters of the BGS model. Finally, analyses of protein evolution together with previous comparisons of genetic maps between Drosophila species, suggest temporally variable recombination landscapes and, thus, local BGS effects that may differ between extant and past phases. Because genome-wide BGS and temporal changes in linkage effects can skew approaches to estimate demographic and

Accelerating the Switchgrass (Panicum virgatum L.) Breeding Cycle Using Genomic Selection Approaches

Science.gov (United States)

Lipka, Alexander E.; Lu, Fei; Cherney, Jerome H.; Buckler, Edward S.; Casler, Michael D.; Costich, Denise E.

2014-01-01

Switchgrass (Panicum virgatum L.) is a perennial grass undergoing development as a biofuel feedstock. One of the most important factors hindering breeding efforts in this species is the need for accurate measurement of biomass yield on a per-hectare basis. Genomic selection on simple-to-measure traits that approximate biomass yield has the potential to significantly speed up the breeding cycle. Recent advances in switchgrass genomic and phenotypic resources are now making it possible to evaluate the potential of genomic selection of such traits. We leveraged these resources to study the ability of three widely-used genomic selection models to predict phenotypic values of morphological and biomass quality traits in an association panel consisting of predominantly northern adapted upland germplasm. High prediction accuracies were obtained for most of the traits, with standability having the highest ten-fold cross validation prediction accuracy (0.52). Moreover, the morphological traits generally had higher prediction accuracies than the biomass quality traits. Nevertheless, our results suggest that the quality of current genomic and phenotypic resources available for switchgrass is sufficiently high for genomic selection to significantly impact breeding efforts for biomass yield. PMID:25390940

Genomic analysis and selected molecular pathways in rare cancers

International Nuclear Information System (INIS)

Liu, Stephen V; Lenkiewicz, Elizabeth; Evers, Lisa; Holley, Tara; Kiefer, Jeffrey; Demeure, Michael J; Ramanathan, Ramesh K; Von Hoff, Daniel D; Barrett, Michael T; Ruiz, Christian; Glatz, Katharina; Bubendorf, Lukas; Eng, Cathy

2012-01-01

It is widely accepted that many cancers arise as a result of an acquired genomic instability and the subsequent evolution of tumor cells with variable patterns of selected and background aberrations. The presence and behaviors of distinct neoplastic cell populations within a patient's tumor may underlie multiple clinical phenotypes in cancers. A goal of many current cancer genome studies is the identification of recurring selected driver events that can be advanced for the development of personalized therapies. Unfortunately, in the majority of rare tumors, this type of analysis can be particularly challenging. Large series of specimens for analysis are simply not available, allowing recurring patterns to remain hidden. In this paper, we highlight the use of DNA content-based flow sorting to identify and isolate DNA-diploid and DNA-aneuploid populations from tumor biopsies as a strategy to comprehensively study the genomic composition and behaviors of individual cancers in a series of rare solid tumors: intrahepatic cholangiocarcinoma, anal carcinoma, adrenal leiomyosarcoma, and pancreatic neuroendocrine tumors. We propose that the identification of highly selected genomic events in distinct tumor populations within each tumor can identify candidate driver events that can facilitate the development of novel, personalized treatment strategies for patients with cancer. (paper)

Selfing for the design of genomic selection experiments in biparental plant populations.

Science.gov (United States)

McClosky, Benjamin; LaCombe, Jason; Tanksley, Steven D

2013-11-01

Self-fertilization (selfing) is commonly used for population development in plant breeding, and it is well established that selfing increases genetic variance between lines, thus increasing response to phenotypic selection. Furthermore, numerous studies have explored how selfing can be deployed to maximal benefit in the context of traditional plant breeding programs (Cornish in Heredity 65:201-211,1990a, Heredity 65:213-220,1990b; Liu et al. in Theor Appl Genet 109:370-376, 2004; Pooni and Jinks in Heredity 54:255-260, 1985). However, the impact of selfing on response to genomic selection has not been explored. In the current study we examined how selfing impacts the two key aspects of genomic selection-GEBV prediction (training) and selection response. We reach the following conclusions: (1) On average, selfing increases genomic selection gains by more than 70 %. (2) The gains in genomic selection response attributable to selfing hold over a wide range population sizes (100-500), heritabilities (0.2-0.8), and selection intensities (0.01-0.1). However, the benefits of selfing are dramatically reduced as the number of QTLs drops below 20. (3) The major cause of the improved response to genomic selection with selfing is through an increase in the occurrence of superior genotypes and not through improved GEBV predictions. While performance of the training population improves with selfing (especially with low heritability and small population sizes), the magnitude of these improvements is relatively small compared with improvements observed in the selection population. To illustrate the value of these insights, we propose a practical genomic selection scheme that substantially shortens the number of generations required to fully capture the benefits of selfing. Specifically, we provide simulation evidence that indicates the proposed scheme matches or exceeds the selection gains observed in advanced populations (i.e. F 8 and doubled haploid) across a broad range of

Genome wide selection in Citrus breeding.

Science.gov (United States)

Gois, I B; Borém, A; Cristofani-Yaly, M; de Resende, M D V; Azevedo, C F; Bastianel, M; Novelli, V M; Machado, M A

2016-10-17

Genome wide selection (GWS) is essential for the genetic improvement of perennial species such as Citrus because of its ability to increase gain per unit time and to enable the efficient selection of characteristics with low heritability. This study assessed GWS efficiency in a population of Citrus and compared it with selection based on phenotypic data. A total of 180 individual trees from a cross between Pera sweet orange (Citrus sinensis Osbeck) and Murcott tangor (Citrus sinensis Osbeck x Citrus reticulata Blanco) were evaluated for 10 characteristics related to fruit quality. The hybrids were genotyped using 5287 DArT_seq TM (diversity arrays technology) molecular markers and their effects on phenotypes were predicted using the random regression - best linear unbiased predictor (rr-BLUP) method. The predictive ability, prediction bias, and accuracy of GWS were estimated to verify its effectiveness for phenotype prediction. The proportion of genetic variance explained by the markers was also computed. The heritability of the traits, as determined by markers, was 16-28%. The predictive ability of these markers ranged from 0.53 to 0.64, and the regression coefficients between predicted and observed phenotypes were close to unity. Over 35% of the genetic variance was accounted for by the markers. Accuracy estimates with GWS were lower than those obtained by phenotypic analysis; however, GWS was superior in terms of genetic gain per unit time. Thus, GWS may be useful for Citrus breeding as it can predict phenotypes early and accurately, and reduce the length of the selection cycle. This study demonstrates the feasibility of genomic selection in Citrus.

Association Mapping and the Genomic Consequences of Selection in Sunflower

Science.gov (United States)

Mandel, Jennifer R.; Nambeesan, Savithri; Bowers, John E.; Marek, Laura F.; Ebert, Daniel; Rieseberg, Loren H.; Knapp, Steven J.; Burke, John M.

2013-01-01

The combination of large-scale population genomic analyses and trait-based mapping approaches has the potential to provide novel insights into the evolutionary history and genome organization of crop plants. Here, we describe the detailed genotypic and phenotypic analysis of a sunflower (Helianthus annuus L.) association mapping population that captures nearly 90% of the allelic diversity present within the cultivated sunflower germplasm collection. We used these data to characterize overall patterns of genomic diversity and to perform association analyses on plant architecture (i.e., branching) and flowering time, successfully identifying numerous associations underlying these agronomically and evolutionarily important traits. Overall, we found variable levels of linkage disequilibrium (LD) across the genome. In general, islands of elevated LD correspond to genomic regions underlying traits that are known to have been targeted by selection during the evolution of cultivated sunflower. In many cases, these regions also showed significantly elevated levels of differentiation between the two major sunflower breeding groups, consistent with the occurrence of divergence due to strong selection. One of these regions, which harbors a major branching locus, spans a surprisingly long genetic interval (ca. 25 cM), indicating the occurrence of an extended selective sweep in an otherwise recombinogenic interval. PMID:23555290

Genomic Selection in Plant Breeding: Methods, Models, and Perspectives.

Science.gov (United States)

Crossa, José; Pérez-Rodríguez, Paulino; Cuevas, Jaime; Montesinos-López, Osval; Jarquín, Diego; de Los Campos, Gustavo; Burgueño, Juan; González-Camacho, Juan M; Pérez-Elizalde, Sergio; Beyene, Yoseph; Dreisigacker, Susanne; Singh, Ravi; Zhang, Xuecai; Gowda, Manje; Roorkiwal, Manish; Rutkoski, Jessica; Varshney, Rajeev K

2017-11-01

Genomic selection (GS) facilitates the rapid selection of superior genotypes and accelerates the breeding cycle. In this review, we discuss the history, principles, and basis of GS and genomic-enabled prediction (GP) as well as the genetics and statistical complexities of GP models, including genomic genotype×environment (G×E) interactions. We also examine the accuracy of GP models and methods for two cereal crops and two legume crops based on random cross-validation. GS applied to maize breeding has shown tangible genetic gains. Based on GP results, we speculate how GS in germplasm enhancement (i.e., prebreeding) programs could accelerate the flow of genes from gene bank accessions to elite lines. Recent advances in hyperspectral image technology could be combined with GS and pedigree-assisted breeding. Copyright © 2017 Elsevier Ltd. All rights reserved.

A genome-wide scan for selection signatures in Nellore cattle.

Science.gov (United States)

Somavilla, A L; Sonstegard, T S; Higa, R H; Rosa, A N; Siqueira, F; Silva, L O C; Torres Júnior, R A A; Coutinho, L L; Mudadu, M A; Alencar, M M; Regitano, L C A

2014-12-01

Brazilian Nellore cattle (Bos indicus) have been selected for growth traits for over more than four decades. In recent years, reproductive and meat quality traits have become more important because of increasing consumption, exports and consumer demand. The identification of genome regions altered by artificial selection can potentially permit a better understanding of the biology of specific phenotypes that are useful for the development of tools designed to increase selection efficiency. Therefore, the aims of this study were to detect evidence of recent selection signatures in Nellore cattle using extended haplotype homozygosity methodology and BovineHD marker genotypes (>777,000 single nucleotide polymorphisms) as well as to identify corresponding genes underlying these signals. Thirty-one significant regions (P meat quality, fatty acid profiles and immunity. In addition, 545 genes were identified in regions harboring selection signatures. Within this group, 58 genes were associated with growth, muscle and adipose tissue metabolism, reproductive traits or the immune system. Using relative extended haplotype homozygosity to analyze high-density single nucleotide polymorphism marker data allowed for the identification of regions potentially under artificial selection pressure in the Nellore genome, which might be used to better understand autozygosity and the effects of selection on the Nellore genome. © 2014 Stichting International Foundation for Animal Genetics.

A note on mate allocation for dominance handling in genomic selection

Directory of Open Access Journals (Sweden)

Toro Miguel A

2010-08-01

Full Text Available Abstract Estimation of non-additive genetic effects in animal breeding is important because it increases the accuracy of breeding value prediction and the value of mate allocation procedures. With the advent of genomic selection these ideas should be revisited. The objective of this study was to quantify the efficiency of including dominance effects and practising mating allocation under a whole-genome evaluation scenario. Four strategies of selection, carried out during five generations, were compared by simulation techniques. In the first scenario (MS, individuals were selected based on their own phenotypic information. In the second (GSA, they were selected based on the prediction generated by the Bayes A method of whole-genome evaluation under an additive model. In the third (GSD, the model was expanded to include dominance effects. These three scenarios used random mating to construct future generations, whereas in the fourth one (GSD + MA, matings were optimized by simulated annealing. The advantage of GSD over GSA ranges from 9 to 14% of the expected response and, in addition, using mate allocation (GSD + MA provides an additional response ranging from 6% to 22%. However, mate selection can improve the expected genetic response over random mating only in the first generation of selection. Furthermore, the efficiency of genomic selection is eroded after a few generations of selection, thus, a continued collection of phenotypic data and re-evaluation will be required.

Identifying artificial selection signals in the chicken genome.

Directory of Open Access Journals (Sweden)

Yunlong Ma

Full Text Available Identifying the signals of artificial selection can contribute to further shaping economically important traits. Here, a chicken 600k SNP-array was employed to detect the signals of artificial selection using 331 individuals from 9 breeds, including Jingfen (JF, Jinghong (JH, Araucanas (AR, White Leghorn (WL, Pekin-Bantam (PB, Shamo (SH, Gallus-Gallus-Spadiceus (GA, Rheinlander (RH and Vorwerkhuhn (VO. Per the population genetic structure, 9 breeds were combined into 5 breed-pools, and a 'two-step' strategy was used to reveal the signals of artificial selection. GA, which has little artificial selection, was defined as the reference population, and a total of 204, 155, 305 and 323 potential artificial selection signals were identified in AR_VO, PB, RH_WL and JH_JF, respectively. We also found signals derived from standing and de-novo genetic variations have contributed to adaptive evolution during artificial selection. Further enrichment analysis suggests that the genomic regions of artificial selection signals harbour genes, including THSR, PTHLH and PMCH, responsible for economic traits, such as fertility, growth and immunization. Overall, this study found a series of genes that contribute to the improvement of chicken breeds and revealed the genetic mechanisms of adaptive evolution, which can be used as fundamental information in future chicken functional genomics study.

Genomic selection needs to be carefully assessed to meet specific requirements in livestock breeding programs

Directory of Open Access Journals (Sweden)

Elisabeth eJonas

2015-02-01

Full Text Available Genomic selection is a promising development in agriculture, aiming improved production by exploiting molecular genetic markers to design novel breeding programs and to develop new markers-based models for genetic evaluation. It opens opportunities for research, as novel algorithms and lab methodologies are developed. Genomic selection can be applied in many breeds and species. Further research on the implementation of genomic selection in breeding programs is highly desirable not only for the common good, but also the private sector (breeding companies. It has been projected that this approach will improve selection routines, especially in species with long reproduction cycles, late or sex-limited or expensive trait recording and for complex traits. The task of integrating genomic selection into existing breeding programs is, however, not straightforward. Despite successful integration into breeding programs for dairy cattle, it has yet to be shown how much emphasis can be given to the genomic information and how much additional phenotypic information is needed from new selection candidates. Genomic selection is already part of future planning in many breeding companies of pigs and beef cattle among others, but further research is needed to fully estimate how effective the use of genomic information will be for the prediction of the performance of future breeding stock. Genomic prediction of production in crossbreeding and across-breed schemes, costs and choice of individuals for genotyping are reasons for a reluctance to fully rely on genomic information for selection decisions. Breeding objectives are highly dependent on the industry and the additional gain when using genomic information has to be considered carefully. This review synthesizes some of the suggested approaches in selected livestock species including cattle, pig, chicken and fish. It outlines tasks to help understanding possible consequences when applying genomic information in

Experimental assessment of the accuracy of genomic selection in sugarcane.

Science.gov (United States)

Gouy, M; Rousselle, Y; Bastianelli, D; Lecomte, P; Bonnal, L; Roques, D; Efile, J-C; Rocher, S; Daugrois, J; Toubi, L; Nabeneza, S; Hervouet, C; Telismart, H; Denis, M; Thong-Chane, A; Glaszmann, J C; Hoarau, J-Y; Nibouche, S; Costet, L

2013-10-01

Sugarcane cultivars are interspecific hybrids with an aneuploid, highly heterozygous polyploid genome. The complexity of the sugarcane genome is the main obstacle to the use of marker-assisted selection in sugarcane breeding. Given the promising results of recent studies of plant genomic selection, we explored the feasibility of genomic selection in this complex polyploid crop. Genetic values were predicted in two independent panels, each composed of 167 accessions representing sugarcane genetic diversity worldwide. Accessions were genotyped with 1,499 DArT markers. One panel was phenotyped in Reunion Island and the other in Guadeloupe. Ten traits concerning sugar and bagasse contents, digestibility and composition of the bagasse, plant morphology, and disease resistance were used. We used four statistical predictive models: bayesian LASSO, ridge regression, reproducing kernel Hilbert space, and partial least square regression. The accuracy of the predictions was assessed through the correlation between observed and predicted genetic values by cross validation within each panel and between the two panels. We observed equivalent accuracy among the four predictive models for a given trait, and marked differences were observed among traits. Depending on the trait concerned, within-panel cross validation yielded median correlations ranging from 0.29 to 0.62 in the Reunion Island panel and from 0.11 to 0.5 in the Guadeloupe panel. Cross validation between panels yielded correlations ranging from 0.13 for smut resistance to 0.55 for brix. This level of correlations is promising for future implementations. Our results provide the first validation of genomic selection in sugarcane.

A Genomic Map of the Effects of Linked Selection in Drosophila.

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Eyal Elyashiv

2016-08-01

Full Text Available Natural selection at one site shapes patterns of genetic variation at linked sites. Quantifying the effects of "linked selection" on levels of genetic diversity is key to making reliable inference about demography, building a null model in scans for targets of adaptation, and learning about the dynamics of natural selection. Here, we introduce the first method that jointly infers parameters of distinct modes of linked selection, notably background selection and selective sweeps, from genome-wide diversity data, functional annotations and genetic maps. The central idea is to calculate the probability that a neutral site is polymorphic given local annotations, substitution patterns, and recombination rates. Information is then combined across sites and samples using composite likelihood in order to estimate genome-wide parameters of distinct modes of selection. In addition to parameter estimation, this approach yields a map of the expected neutral diversity levels along the genome. To illustrate the utility of our approach, we apply it to genome-wide resequencing data from 125 lines in Drosophila melanogaster and reliably predict diversity levels at the 1Mb scale. Our results corroborate estimates of a high fraction of beneficial substitutions in proteins and untranslated regions (UTR. They allow us to distinguish between the contribution of sweeps and other modes of selection around amino acid substitutions and to uncover evidence for pervasive sweeps in untranslated regions (UTRs. Our inference further suggests a substantial effect of other modes of linked selection and of adaptation in particular. More generally, we demonstrate that linked selection has had a larger effect in reducing diversity levels and increasing their variance in D. melanogaster than previously appreciated.

A Genomic Map of the Effects of Linked Selection in Drosophila.

Science.gov (United States)

Elyashiv, Eyal; Sattath, Shmuel; Hu, Tina T; Strutsovsky, Alon; McVicker, Graham; Andolfatto, Peter; Coop, Graham; Sella, Guy

2016-08-01

Natural selection at one site shapes patterns of genetic variation at linked sites. Quantifying the effects of "linked selection" on levels of genetic diversity is key to making reliable inference about demography, building a null model in scans for targets of adaptation, and learning about the dynamics of natural selection. Here, we introduce the first method that jointly infers parameters of distinct modes of linked selection, notably background selection and selective sweeps, from genome-wide diversity data, functional annotations and genetic maps. The central idea is to calculate the probability that a neutral site is polymorphic given local annotations, substitution patterns, and recombination rates. Information is then combined across sites and samples using composite likelihood in order to estimate genome-wide parameters of distinct modes of selection. In addition to parameter estimation, this approach yields a map of the expected neutral diversity levels along the genome. To illustrate the utility of our approach, we apply it to genome-wide resequencing data from 125 lines in Drosophila melanogaster and reliably predict diversity levels at the 1Mb scale. Our results corroborate estimates of a high fraction of beneficial substitutions in proteins and untranslated regions (UTR). They allow us to distinguish between the contribution of sweeps and other modes of selection around amino acid substitutions and to uncover evidence for pervasive sweeps in untranslated regions (UTRs). Our inference further suggests a substantial effect of other modes of linked selection and of adaptation in particular. More generally, we demonstrate that linked selection has had a larger effect in reducing diversity levels and increasing their variance in D. melanogaster than previously appreciated.

Most of the benefits from genomic selection can be realised by genotyping a proportion of selection candidates

DEFF Research Database (Denmark)

Henryon, Mark; Berg, Peer; Sørensen, Anders Christian

2012-01-01

allocated to male and female candidates at ratios of 100:0, 75:25, 50:50, 25:75, and 0:100. For genotyped candidates, a direct-genomic value (DGV) was sampled with reliabilities 0.10, 0.50, and 0.90. Ten sires and 300 dams with the highest breeding values after genotyping were selected at each generation......We reasoned that there are diminishing marginal returns from genomic selection as the proportion of genotyped selection candidates is increased and breeding values based on a priori information are used to choose the candidates that are genotyped. We tested this premise by stochastic simulation...... of breeding schemes that resembled those used for pigs. We estimated rates of genetic gain and inbreeding realized by genomic selection in breeding schemes where candidates were phenotyped before genotyping and 0-100% of the candidates were genotyped based on predicted breeding values. Genotypings were...

Interplay of recombination and selection in the genomes of Chlamydia trachomatis

Directory of Open Access Journals (Sweden)

Dean Deborah

2011-05-01

Full Text Available Abstract Background Chlamydia trachomatis is an obligate intracellular bacterial parasite, which causes several severe and debilitating diseases in humans. This study uses comparative genomic analyses of 12 complete published C. trachomatis genomes to assess the contribution of recombination and selection in this pathogen and to understand the major evolutionary forces acting on the genome of this bacterium. Results The conserved core genes of C. trachomatis are a large proportion of the pan-genome: we identified 836 core genes in C. trachomatis out of a range of 874-927 total genes in each genome. The ratio of recombination events compared to mutation (ρ/θ was 0.07 based on ancestral reconstructions using the ClonalFrame tool, but recombination had a significant effect on genetic diversification (r/m = 0.71. The distance-dependent decay of linkage disequilibrium also indicated that C. trachomatis populations behaved intermediately between sexual and clonal extremes. Fifty-five genes were identified as having a history of recombination and 92 were under positive selection based on statistical tests. Twenty-three genes showed evidence of being under both positive selection and recombination, which included genes with a known role in virulence and pathogencity (e.g., ompA, pmps, tarp. Analysis of inter-clade recombination flux indicated non-uniform currents of recombination between clades, which suggests the possibility of spatial population structure in C. trachomatis infections. Conclusions C. trachomatis is the archetype of a bacterial species where recombination is relatively frequent yet gene gains by horizontal gene transfer (HGT and losses (by deletion are rare. Gene conversion occurs at sites across the whole C. trachomatis genome but may be more often fixed in genes that are under diversifying selection. Furthermore, genome sequencing will reveal patterns of serotype specific gene exchange and selection that will generate important

Electronic and structural properties of MgS and CaS

International Nuclear Information System (INIS)

Madu, C.A.; Onwuagba, B.N.

2005-12-01

The electronic and structural properties of MgS and CaS rocksalt structure are studied with the first principle full Potential Linearized Augmented Plane Wave (FP-LAPW) method. The exchange-correlation potential was calculated within the Generalized Gradient Approximation (GGA) using the Perdew-Burke-Ernzerhof (PBE-GGA) scheme. The scalar relativistic approach was adopted for the valence states, whereas the core states are treated fully relativistically. Energy band structures, density of states and structural parameters of both compounds are presented and discussed in context with the available theoretical and experimental studies. Our results are good and show reasonable agreement with previous results even though sufficient experimental values are not available for more realistic comparison. (author)

Prospects for genomic selection in cassava breeding

Science.gov (United States)

Cassava (Manihot esculenta Crantz) is a clonally propagated staple food crop in the tropics. Genomic selection (GS) has been implemented at three breeding institutions in Africa in order to reduce cycle times. Initial studies provided promising estimates of predictive abilities. Here, we expand on p...

Implications of structural genomics target selection strategies: Pfam5000, whole genome, and random approaches

Energy Technology Data Exchange (ETDEWEB)

Chandonia, John-Marc; Brenner, Steven E.

2004-07-14

The structural genomics project is an international effort to determine the three-dimensional shapes of all important biological macromolecules, with a primary focus on proteins. Target proteins should be selected according to a strategy which is medically and biologically relevant, of good value, and tractable. As an option to consider, we present the Pfam5000 strategy, which involves selecting the 5000 most important families from the Pfam database as sources for targets. We compare the Pfam5000 strategy to several other proposed strategies that would require similar numbers of targets. These include including complete solution of several small to moderately sized bacterial proteomes, partial coverage of the human proteome, and random selection of approximately 5000 targets from sequenced genomes. We measure the impact that successful implementation of these strategies would have upon structural interpretation of the proteins in Swiss-Prot, TrEMBL, and 131 complete proteomes (including 10 of eukaryotes) from the Proteome Analysis database at EBI. Solving the structures of proteins from the 5000 largest Pfam families would allow accurate fold assignment for approximately 68 percent of all prokaryotic proteins (covering 59 percent of residues) and 61 percent of eukaryotic proteins (40 percent of residues). More fine-grained coverage which would allow accurate modeling of these proteins would require an order of magnitude more targets. The Pfam5000 strategy may be modified in several ways, for example to focus on larger families, bacterial sequences, or eukaryotic sequences; as long as secondary consideration is given to large families within Pfam, coverage results vary only slightly. In contrast, focusing structural genomics on a single tractable genome would have only a limited impact in structural knowledge of other proteomes: a significant fraction (about 30-40 percent of the proteins, and 40-60 percent of the residues) of each proteome is classified in small

Genomic selection needs to be carefully assessed to meet specific requirements in livestock breeding programs.

Science.gov (United States)

Jonas, Elisabeth; de Koning, Dirk-Jan

2015-01-01

Genomic selection is a promising development in agriculture, aiming improved production by exploiting molecular genetic markers to design novel breeding programs and to develop new markers-based models for genetic evaluation. It opens opportunities for research, as novel algorithms and lab methodologies are developed. Genomic selection can be applied in many breeds and species. Further research on the implementation of genomic selection (GS) in breeding programs is highly desirable not only for the common good, but also the private sector (breeding companies). It has been projected that this approach will improve selection routines, especially in species with long reproduction cycles, late or sex-limited or expensive trait recording and for complex traits. The task of integrating GS into existing breeding programs is, however, not straightforward. Despite successful integration into breeding programs for dairy cattle, it has yet to be shown how much emphasis can be given to the genomic information and how much additional phenotypic information is needed from new selection candidates. Genomic selection is already part of future planning in many breeding companies of pigs and beef cattle among others, but further research is needed to fully estimate how effective the use of genomic information will be for the prediction of the performance of future breeding stock. Genomic prediction of production in crossbreeding and across-breed schemes, costs and choice of individuals for genotyping are reasons for a reluctance to fully rely on genomic information for selection decisions. Breeding objectives are highly dependent on the industry and the additional gain when using genomic information has to be considered carefully. This review synthesizes some of the suggested approaches in selected livestock species including cattle, pig, chicken, and fish. It outlines tasks to help understanding possible consequences when applying genomic information in breeding scenarios.

Natural selection and the distribution of identity-by-descent in the human genome

DEFF Research Database (Denmark)

Albrechtsen, Anders; Moltke, Ida; Nielsen, Rasmus

2010-01-01

There has recently been considerable interest in detecting natural selection in the human genome. Selection will usually tend to increase identity-by-descent (IBD) among individuals in a population, and many methods for detecting recent and ongoing positive selection indirectly take advantage...... of this. In this article we show that excess IBD sharing is a general property of natural selection and we show that this fact makes it possible to detect several types of selection including a type that is otherwise difficult to detect: selection acting on standing genetic variation. Motivated by this......, we use a recently developed method for identifying IBD sharing among individuals from genome-wide data to scan populations from the new HapMap phase 3 project for regions with excess IBD sharing in order to identify regions in the human genome that have been under strong, very recent selection...

Allele frequency changes due to hitch-hiking in genomic selection programs

DEFF Research Database (Denmark)

Liu, Huiming; Sørensen, Anders Christian; Meuwissen, Theo H E

2014-01-01

of inbreeding due to changes in allele frequencies and hitch-hiking. This study aimed at understanding the impact of using long-term genomic selection on changes in allele frequencies, genetic variation and the level of inbreeding. Methods Selection was performed in simulated scenarios with a population of 400......-BLUP, Genomic BLUP and Bayesian Lasso. Changes in allele frequencies at QTL, markers and linked neutral loci were investigated for the different selection criteria and different scenarios, along with the loss of favourable alleles and the rate of inbreeding measured by pedigree and runs of homozygosity. Results...

Selective constraint on noncoding regions of hominid genomes.

Directory of Open Access Journals (Sweden)

Eliot C Bush

2005-12-01

Full Text Available An important challenge for human evolutionary biology is to understand the genetic basis of human-chimpanzee differences. One influential idea holds that such differences depend, to a large extent, on adaptive changes in gene expression. An important step in assessing this hypothesis involves gaining a better understanding of selective constraint on noncoding regions of hominid genomes. In noncoding sequence, functional elements are frequently small and can be separated by large nonfunctional regions. For this reason, constraint in hominid genomes is likely to be patchy. Here we use conservation in more distantly related mammals and amniotes as a way of identifying small sequence windows that are likely to be functional. We find that putatively functional noncoding elements defined in this manner are subject to significant selective constraint in hominids.

Selective Constraint on Noncoding Regions of Hominid Genomes.

Directory of Open Access Journals (Sweden)

2005-12-01

Full Text Available An important challenge for human evolutionary biology is to understand the genetic basis of human-chimpanzee differences. One influential idea holds that such differences depend, to a large extent, on adaptive changes in gene expression. An important step in assessing this hypothesis involves gaining a better understanding of selective constraint on noncoding regions of hominid genomes. In noncoding sequence, functional elements are frequently small and can be separated by large nonfunctional regions. For this reason, constraint in hominid genomes is likely to be patchy. Here we use conservation in more distantly related mammals and amniotes as a way of identifying small sequence windows that are likely to be functional. We find that putatively functional noncoding elements defined in this manner are subject to significant selective constraint in hominids.

Targets of balancing selection in the human genome

DEFF Research Database (Denmark)

Andrés, Aida M; Hubisz, Melissa J; Indap, Amit

2009-01-01

Balancing selection is potentially an important biological force for maintaining advantageous genetic diversity in populations, including variation that is responsible for long-term adaptation to the environment. By serving as a means to maintain genetic variation, it may be particularly relevant...... to maintaining phenotypic variation in natural populations. Nevertheless, its prevalence and specific targets in the human genome remain largely unknown. We have analyzed the patterns of diversity and divergence of 13,400 genes in two human populations using an unbiased single-nucleotide polymorphism data set......, a genome-wide approach, and a method that incorporates demography in neutrality tests. We identified an unbiased catalog of genes with signatures of long-term balancing selection, which includes immunity genes as well as genes encoding keratins and membrane channels; the catalog also shows enrichment...

Improving the baking quality of bread wheat by genomic selection in early generations.

Science.gov (United States)

Michel, Sebastian; Kummer, Christian; Gallee, Martin; Hellinger, Jakob; Ametz, Christian; Akgöl, Batuhan; Epure, Doru; Löschenberger, Franziska; Buerstmayr, Hermann

2018-02-01

Genomic selection shows great promise for pre-selecting lines with superior bread baking quality in early generations, 3 years ahead of labour-intensive, time-consuming, and costly quality analysis. The genetic improvement of baking quality is one of the grand challenges in wheat breeding as the assessment of the associated traits often involves time-consuming, labour-intensive, and costly testing forcing breeders to postpone sophisticated quality tests to the very last phases of variety development. The prospect of genomic selection for complex traits like grain yield has been shown in numerous studies, and might thus be also an interesting method to select for baking quality traits. Hence, we focused in this study on the accuracy of genomic selection for laborious and expensive to phenotype quality traits as well as its selection response in comparison with phenotypic selection. More than 400 genotyped wheat lines were, therefore, phenotyped for protein content, dough viscoelastic and mixing properties related to baking quality in multi-environment trials 2009-2016. The average prediction accuracy across three independent validation populations was r = 0.39 and could be increased to r = 0.47 by modelling major QTL as fixed effects as well as employing multi-trait prediction models, which resulted in an acceptable prediction accuracy for all dough rheological traits (r = 0.38-0.63). Genomic selection can furthermore be applied 2-3 years earlier than direct phenotypic selection, and the estimated selection response was nearly twice as high in comparison with indirect selection by protein content for baking quality related traits. This considerable advantage of genomic selection could accordingly support breeders in their selection decisions and aid in efficiently combining superior baking quality with grain yield in newly developed wheat varieties.

Positive Selection Driving Cytoplasmic Genome Evolution of the Medicinally Important Ginseng Plant Genus Panax.

Science.gov (United States)

Jiang, Peng; Shi, Feng-Xue; Li, Ming-Rui; Liu, Bao; Wen, Jun; Xiao, Hong-Xing; Li, Lin-Feng

2018-01-01

Panax L. (the ginseng genus) is a shade-demanding group within the family Araliaceae and all of its species are of crucial significance in traditional Chinese medicine. Phylogenetic and biogeographic analyses demonstrated that two rounds of whole genome duplications accompanying with geographic and ecological isolations promoted the diversification of Panax species. However, contributions of the cytoplasmic genomes to the adaptive evolution of Panax species remained largely uninvestigated. In this study, we sequenced the chloroplast and mitochondrial genomes of 11 accessions belonging to seven Panax species. Our results show that heterogeneity in nucleotide substitution rate is abundant in both of the two cytoplasmic genomes, with the mitochondrial genome possessing more variants at the total level but the chloroplast showing higher sequence polymorphisms at the genic regions. Genome-wide scanning of positive selection identified five and 12 genes from the chloroplast and mitochondrial genomes, respectively. Functional analyses further revealed that these selected genes play important roles in plant development, cellular metabolism and adaptation. We therefore conclude that positive selection might be one of the potential evolutionary forces that shaped nucleotide variation pattern of these Panax species. In particular, the mitochondrial genes evolved under stronger selective pressure compared to the chloroplast genes.

Accuracy of Genomic Selection in a Rice Synthetic Population Developed for Recurrent Selection Breeding.

Science.gov (United States)

Grenier, Cécile; Cao, Tuong-Vi; Ospina, Yolima; Quintero, Constanza; Châtel, Marc Henri; Tohme, Joe; Courtois, Brigitte; Ahmadi, Nourollah

2015-01-01

Genomic selection (GS) is a promising strategy for enhancing genetic gain. We investigated the accuracy of genomic estimated breeding values (GEBV) in four inter-related synthetic populations that underwent several cycles of recurrent selection in an upland rice-breeding program. A total of 343 S2:4 lines extracted from those populations were phenotyped for flowering time, plant height, grain yield and panicle weight, and genotyped with an average density of one marker per 44.8 kb. The relative effect of the linkage disequilibrium (LD) and minor allele frequency (MAF) thresholds for selecting markers, the relative size of the training population (TP) and of the validation population (VP), the selected trait and the genomic prediction models (frequentist and Bayesian) on the accuracy of GEBVs was investigated in 540 cross validation experiments with 100 replicates. The effect of kinship between the training and validation populations was tested in an additional set of 840 cross validation experiments with a single genomic prediction model. LD was high (average r2 = 0.59 at 25 kb) and decreased slowly, distribution of allele frequencies at individual loci was markedly skewed toward unbalanced frequencies (MAF average value 15.2% and median 9.6%), and differentiation between the four synthetic populations was low (FST ≤0.06). The accuracy of GEBV across all cross validation experiments ranged from 0.12 to 0.54 with an average of 0.30. Significant differences in accuracy were observed among the different levels of each factor investigated. Phenotypic traits had the biggest effect, and the size of the incidence matrix had the smallest. Significant first degree interaction was observed for GEBV accuracy between traits and all the other factors studied, and between prediction models and LD, MAF and composition of the TP. The potential of GS to accelerate genetic gain and breeding options to increase the accuracy of predictions are discussed.

Accuracy of multi-trait genomic selection using different methods

NARCIS (Netherlands)

Calus, M.P.L.; Veerkamp, R.F.

2011-01-01

Background Genomic selection has become a very important tool in animal genetics and is rapidly emerging in plant genetics. It holds the promise to be particularly beneficial to select for traits that are difficult or expensive to measure, such as traits that are measured in one environment and

Chemical rationale for selection of isolates for genome sequencing

DEFF Research Database (Denmark)

Rank, Christian; Larsen, Thomas Ostenfeld; Frisvad, Jens Christian

The advances in gene sequencing will in the near future enable researchers to affordably acquire the full genomes of handpicked isolates. We here present a method to evaluate the chemical potential of an entire species and select representatives for genome sequencing. The selection criteria for new...... strains to be sequenced can be manifold, but for studying the functional phenotype, using a metabolome based approach offers a cheap and rapid assessment of critical strains to cover the chemical diversity. We have applied this methodology on the complex A. flavus/A. oryzae group. Though these two species...... are in principal identical, they represent two different phenotypes. This is clearly presented through a correspondence analysis of selected extrolites, in which the subtle chemical differences are visually dispersed. The results points to a handful of strains, which, if sequenced, will likely enhance our...

A Ranking Approach to Genomic Selection.

Science.gov (United States)

Blondel, Mathieu; Onogi, Akio; Iwata, Hiroyoshi; Ueda, Naonori

2015-01-01

Genomic selection (GS) is a recent selective breeding method which uses predictive models based on whole-genome molecular markers. Until now, existing studies formulated GS as the problem of modeling an individual's breeding value for a particular trait of interest, i.e., as a regression problem. To assess predictive accuracy of the model, the Pearson correlation between observed and predicted trait values was used. In this paper, we propose to formulate GS as the problem of ranking individuals according to their breeding value. Our proposed framework allows us to employ machine learning methods for ranking which had previously not been considered in the GS literature. To assess ranking accuracy of a model, we introduce a new measure originating from the information retrieval literature called normalized discounted cumulative gain (NDCG). NDCG rewards more strongly models which assign a high rank to individuals with high breeding value. Therefore, NDCG reflects a prerequisite objective in selective breeding: accurate selection of individuals with high breeding value. We conducted a comparison of 10 existing regression methods and 3 new ranking methods on 6 datasets, consisting of 4 plant species and 25 traits. Our experimental results suggest that tree-based ensemble methods including McRank, Random Forests and Gradient Boosting Regression Trees achieve excellent ranking accuracy. RKHS regression and RankSVM also achieve good accuracy when used with an RBF kernel. Traditional regression methods such as Bayesian lasso, wBSR and BayesC were found less suitable for ranking. Pearson correlation was found to correlate poorly with NDCG. Our study suggests two important messages. First, ranking methods are a promising research direction in GS. Second, NDCG can be a useful evaluation measure for GS.

Landscape genomics: natural selection drives the evolution of mitogenome in penguins

OpenAIRE

Ramos, Barbara; González-Acuña, Daniel; Loyola, David E.; Johnson, Warren E.; Parker, Patricia G.; Massaro, Melanie; Dantas, Gisele P. M.; Miranda, Marcelo D.; Vianna, Juliana A.

2018-01-01

Background Mitochondria play a key role in the balance of energy and heat production, and therefore the mitochondrial genome is under natural selection by environmental temperature and food availability, since starvation can generate more efficient coupling of energy production. However, selection over mitochondrial DNA (mtDNA) genes has usually been evaluated at the population level. We sequenced by NGS 12 mitogenomes and with four published genomes, assessed genetic variation in ten penguin...

Cow genotyping strategies for genomic selection in a small dairy cattle population.

Science.gov (United States)

Jenko, J; Wiggans, G R; Cooper, T A; Eaglen, S A E; Luff, W G de L; Bichard, M; Pong-Wong, R; Woolliams, J A

2017-01-01

This study compares how different cow genotyping strategies increase the accuracy of genomic estimated breeding values (EBV) in dairy cattle breeds with low numbers. In these breeds, few sires have progeny records, and genotyping cows can improve the accuracy of genomic EBV. The Guernsey breed is a small dairy cattle breed with approximately 14,000 recorded individuals worldwide. Predictions of phenotypes of milk yield, fat yield, protein yield, and calving interval were made for Guernsey cows from England and Guernsey Island using genomic EBV, with training sets including 197 de-regressed proofs of genotyped bulls, with cows selected from among 1,440 genotyped cows using different genotyping strategies. Accuracies of predictions were tested using 10-fold cross-validation among the cows. Genomic EBV were predicted using 4 different methods: (1) pedigree BLUP, (2) genomic BLUP using only bulls, (3) univariate genomic BLUP using bulls and cows, and (4) bivariate genomic BLUP. Genotyping cows with phenotypes and using their data for the prediction of single nucleotide polymorphism effects increased the correlation between genomic EBV and phenotypes compared with using only bulls by 0.163±0.022 for milk yield, 0.111±0.021 for fat yield, and 0.113±0.018 for protein yield; a decrease of 0.014±0.010 for calving interval from a low base was the only exception. Genetic correlation between phenotypes from bulls and cows were approximately 0.6 for all yield traits and significantly different from 1. Only a very small change occurred in correlation between genomic EBV and phenotypes when using the bivariate model. It was always better to genotype all the cows, but when only half of the cows were genotyped, a divergent selection strategy was better compared with the random or directional selection approach. Divergent selection of 30% of the cows remained superior for the yield traits in 8 of 10 folds. Copyright © 2017 American Dairy Science Association. Published by

Genomic selection accuracy using multi-family prediction models in a wheat breeding program

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Genomic selection (GS) uses genome-wide molecular marker data to predict the genetic value of selection candidates in breeding programs. In plant breeding, the ability to produce large numbers of progeny per cross allows GS to be conducted within each family. However, this approach requires phenotyp...

Conditional Selection of Genomic Alterations Dictates Cancer Evolution and Oncogenic Dependencies.

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Mina, Marco; Raynaud, Franck; Tavernari, Daniele; Battistello, Elena; Sungalee, Stephanie; Saghafinia, Sadegh; Laessle, Titouan; Sanchez-Vega, Francisco; Schultz, Nikolaus; Oricchio, Elisa; Ciriello, Giovanni

2017-08-14

Cancer evolves through the emergence and selection of molecular alterations. Cancer genome profiling has revealed that specific events are more or less likely to be co-selected, suggesting that the selection of one event depends on the others. However, the nature of these evolutionary dependencies and their impact remain unclear. Here, we designed SELECT, an algorithmic approach to systematically identify evolutionary dependencies from alteration patterns. By analyzing 6,456 genomes from multiple tumor types, we constructed a map of oncogenic dependencies associated with cellular pathways, transcriptional readouts, and therapeutic response. Finally, modeling of cancer evolution shows that alteration dependencies emerge only under conditional selection. These results provide a framework for the design of strategies to predict cancer progression and therapeutic response. Copyright © 2017 Elsevier Inc. All rights reserved.

Accuracy of genomic selection for alfalfa biomass yield in different reference populations.

Science.gov (United States)

Annicchiarico, Paolo; Nazzicari, Nelson; Li, Xuehui; Wei, Yanling; Pecetti, Luciano; Brummer, E Charles

2015-12-01

Genomic selection based on genotyping-by-sequencing (GBS) data could accelerate alfalfa yield gains, if it displayed moderate ability to predict parent breeding values. Its interest would be enhanced by predicting ability also for germplasm/reference populations other than those for which it was defined. Predicting accuracy may be influenced by statistical models, SNP calling procedures and missing data imputation strategies. Landrace and variety material from two genetically-contrasting reference populations, i.e., 124 elite genotypes adapted to the Po Valley (sub-continental climate; PV population) and 154 genotypes adapted to Mediterranean-climate environments (Me population), were genotyped by GBS and phenotyped in separate environments for dry matter yield of their dense-planted half-sib progenies. Both populations showed no sub-population genetic structure. Predictive accuracy was higher by joint rather than separate SNP calling for the two data sets, and using random forest imputation of missing data. Highest accuracy was obtained using Support Vector Regression (SVR) for PV, and Ridge Regression BLUP and SVR for Me germplasm. Bayesian methods (Bayes A, Bayes B and Bayesian Lasso) tended to be less accurate. Random Forest Regression was the least accurate model. Accuracy attained about 0.35 for Me in the range of 0.30-0.50 missing data, and 0.32 for PV at 0.50 missing data, using at least 10,000 SNP markers. Cross-population predictions based on a smaller subset of common SNPs implied a relative loss of accuracy of about 25% for Me and 30% for PV. Genome-wide association analyses based on large subsets of M. truncatula-aligned markers revealed many SNPs with modest association with yield, and some genome areas hosting putative QTLs. A comparison of genomic vs. conventional selection for parent breeding value assuming 1-year vs. 5-year selection cycles, respectively, indicated over three-fold greater predicted yield gain per unit time for genomic selection

A genome scan for positive selection in thoroughbred horses.

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Gu, Jingjing; Orr, Nick; Park, Stephen D; Katz, Lisa M; Sulimova, Galina; MacHugh, David E; Hill, Emmeline W

2009-06-02

Thoroughbred horses have been selected for exceptional racing performance resulting in system-wide structural and functional adaptations contributing to elite athletic phenotypes. Because selection has been recent and intense in a closed population that stems from a small number of founder animals Thoroughbreds represent a unique population within which to identify genomic contributions to exercise-related traits. Employing a population genetics-based hitchhiking mapping approach we performed a genome scan using 394 autosomal and X chromosome microsatellite loci and identified positively selected loci in the extreme tail-ends of the empirical distributions for (1) deviations from expected heterozygosity (Ewens-Watterson test) in Thoroughbred (n = 112) and (2) global differentiation among four geographically diverse horse populations (F(ST)). We found positively selected genomic regions in Thoroughbred enriched for phosphoinositide-mediated signalling (3.2-fold enrichment; PThoroughbred athletic phenotype. We report for the first time candidate athletic-performance genes within regions targeted by selection in Thoroughbred horses that are principally responsible for fatty acid oxidation, increased insulin sensitivity and muscle strength: ACSS1 (acyl-CoA synthetase short-chain family member 1), ACTA1 (actin, alpha 1, skeletal muscle), ACTN2 (actinin, alpha 2), ADHFE1 (alcohol dehydrogenase, iron containing, 1), MTFR1 (mitochondrial fission regulator 1), PDK4 (pyruvate dehydrogenase kinase, isozyme 4) and TNC (tenascin C). Understanding the genetic basis for exercise adaptation will be crucial for the identification of genes within the complex molecular networks underlying obesity and its consequential pathologies, such as type 2 diabetes. Therefore, we propose Thoroughbred as a novel in vivo large animal model for understanding molecular protection against metabolic disease.

Detecting Genomic Signatures of Natural Selection with Principal Component Analysis: Application to the 1000 Genomes Data.

Science.gov (United States)

Duforet-Frebourg, Nicolas; Luu, Keurcien; Laval, Guillaume; Bazin, Eric; Blum, Michael G B

2016-04-01

To characterize natural selection, various analytical methods for detecting candidate genomic regions have been developed. We propose to perform genome-wide scans of natural selection using principal component analysis (PCA). We show that the common FST index of genetic differentiation between populations can be viewed as the proportion of variance explained by the principal components. Considering the correlations between genetic variants and each principal component provides a conceptual framework to detect genetic variants involved in local adaptation without any prior definition of populations. To validate the PCA-based approach, we consider the 1000 Genomes data (phase 1) considering 850 individuals coming from Africa, Asia, and Europe. The number of genetic variants is of the order of 36 millions obtained with a low-coverage sequencing depth (3×). The correlations between genetic variation and each principal component provide well-known targets for positive selection (EDAR, SLC24A5, SLC45A2, DARC), and also new candidate genes (APPBPP2, TP1A1, RTTN, KCNMA, MYO5C) and noncoding RNAs. In addition to identifying genes involved in biological adaptation, we identify two biological pathways involved in polygenic adaptation that are related to the innate immune system (beta defensins) and to lipid metabolism (fatty acid omega oxidation). An additional analysis of European data shows that a genome scan based on PCA retrieves classical examples of local adaptation even when there are no well-defined populations. PCA-based statistics, implemented in the PCAdapt R package and the PCAdapt fast open-source software, retrieve well-known signals of human adaptation, which is encouraging for future whole-genome sequencing project, especially when defining populations is difficult. © The Author(s) 2015. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Performance comparison of two efficient genomic selection methods (gsbay & MixP) applied in aquacultural organisms

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Su, Hailin; Li, Hengde; Wang, Shi; Wang, Yangfan; Bao, Zhenmin

2017-02-01

Genomic selection is more and more popular in animal and plant breeding industries all around the world, as it can be applied early in life without impacting selection candidates. The objective of this study was to bring the advantages of genomic selection to scallop breeding. Two different genomic selection tools MixP and gsbay were applied on genomic evaluation of simulated data and Zhikong scallop ( Chlamys farreri) field data. The data were compared with genomic best linear unbiased prediction (GBLUP) method which has been applied widely. Our results showed that both MixP and gsbay could accurately estimate single-nucleotide polymorphism (SNP) marker effects, and thereby could be applied for the analysis of genomic estimated breeding values (GEBV). In simulated data from different scenarios, the accuracy of GEBV acquired was ranged from 0.20 to 0.78 by MixP; it was ranged from 0.21 to 0.67 by gsbay; and it was ranged from 0.21 to 0.61 by GBLUP. Estimations made by MixP and gsbay were expected to be more reliable than those estimated by GBLUP. Predictions made by gsbay were more robust, while with MixP the computation is much faster, especially in dealing with large-scale data. These results suggested that both algorithms implemented by MixP and gsbay are feasible to carry out genomic selection in scallop breeding, and more genotype data will be necessary to produce genomic estimated breeding values with a higher accuracy for the industry.

Accuracy of Genomic Selection in a Rice Synthetic Population Developed for Recurrent Selection Breeding.

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Cécile Grenier

Full Text Available Genomic selection (GS is a promising strategy for enhancing genetic gain. We investigated the accuracy of genomic estimated breeding values (GEBV in four inter-related synthetic populations that underwent several cycles of recurrent selection in an upland rice-breeding program. A total of 343 S2:4 lines extracted from those populations were phenotyped for flowering time, plant height, grain yield and panicle weight, and genotyped with an average density of one marker per 44.8 kb. The relative effect of the linkage disequilibrium (LD and minor allele frequency (MAF thresholds for selecting markers, the relative size of the training population (TP and of the validation population (VP, the selected trait and the genomic prediction models (frequentist and Bayesian on the accuracy of GEBVs was investigated in 540 cross validation experiments with 100 replicates. The effect of kinship between the training and validation populations was tested in an additional set of 840 cross validation experiments with a single genomic prediction model. LD was high (average r2 = 0.59 at 25 kb and decreased slowly, distribution of allele frequencies at individual loci was markedly skewed toward unbalanced frequencies (MAF average value 15.2% and median 9.6%, and differentiation between the four synthetic populations was low (FST ≤0.06. The accuracy of GEBV across all cross validation experiments ranged from 0.12 to 0.54 with an average of 0.30. Significant differences in accuracy were observed among the different levels of each factor investigated. Phenotypic traits had the biggest effect, and the size of the incidence matrix had the smallest. Significant first degree interaction was observed for GEBV accuracy between traits and all the other factors studied, and between prediction models and LD, MAF and composition of the TP. The potential of GS to accelerate genetic gain and breeding options to increase the accuracy of predictions are discussed.

Genomic hypomethylation in the human germline associates with selective structural mutability in the human genome.

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Jian Li

Full Text Available The hotspots of structural polymorphisms and structural mutability in the human genome remain to be explained mechanistically. We examine associations of structural mutability with germline DNA methylation and with non-allelic homologous recombination (NAHR mediated by low-copy repeats (LCRs. Combined evidence from four human sperm methylome maps, human genome evolution, structural polymorphisms in the human population, and previous genomic and disease studies consistently points to a strong association of germline hypomethylation and genomic instability. Specifically, methylation deserts, the ~1% fraction of the human genome with the lowest methylation in the germline, show a tenfold enrichment for structural rearrangements that occurred in the human genome since the branching of chimpanzee and are highly enriched for fast-evolving loci that regulate tissue-specific gene expression. Analysis of copy number variants (CNVs from 400 human samples identified using a custom-designed array comparative genomic hybridization (aCGH chip, combined with publicly available structural variation data, indicates that association of structural mutability with germline hypomethylation is comparable in magnitude to the association of structural mutability with LCR-mediated NAHR. Moreover, rare CNVs occurring in the genomes of individuals diagnosed with schizophrenia, bipolar disorder, and developmental delay and de novo CNVs occurring in those diagnosed with autism are significantly more concentrated within hypomethylated regions. These findings suggest a new connection between the epigenome, selective mutability, evolution, and human disease.

High-throughput phenotyping and genomic selection: the frontiers of crop breeding converge.

Science.gov (United States)

Cabrera-Bosquet, Llorenç; Crossa, José; von Zitzewitz, Jarislav; Serret, María Dolors; Araus, José Luis

2012-05-01

Genomic selection (GS) and high-throughput phenotyping have recently been captivating the interest of the crop breeding community from both the public and private sectors world-wide. Both approaches promise to revolutionize the prediction of complex traits, including growth, yield and adaptation to stress. Whereas high-throughput phenotyping may help to improve understanding of crop physiology, most powerful techniques for high-throughput field phenotyping are empirical rather than analytical and comparable to genomic selection. Despite the fact that the two methodological approaches represent the extremes of what is understood as the breeding process (phenotype versus genome), they both consider the targeted traits (e.g. grain yield, growth, phenology, plant adaptation to stress) as a black box instead of dissecting them as a set of secondary traits (i.e. physiological) putatively related to the target trait. Both GS and high-throughput phenotyping have in common their empirical approach enabling breeders to use genome profile or phenotype without understanding the underlying biology. This short review discusses the main aspects of both approaches and focuses on the case of genomic selection of maize flowering traits and near-infrared spectroscopy (NIRS) and plant spectral reflectance as high-throughput field phenotyping methods for complex traits such as crop growth and yield. © 2012 Institute of Botany, Chinese Academy of Sciences.

Effects of genomic selection on genetic improvement, inbreeding, and merit of young versus proven bulls

NARCIS (Netherlands)

Roos, de A.P.W.; Schrooten, C.; Veerkamp, R.F.; Arendonk, van J.A.M.

2011-01-01

Genomic selection has the potential to revolutionize dairy cattle breeding because young animals can be accurately selected as parents, leading to a much shorter generation interval and higher rates of genetic gain. The aims of this study were to assess the effects of genomic selection and reduction

New transformation mechanism for a zinc-blende to rocksalt phase transformation in MgS

International Nuclear Information System (INIS)

Durandurdu, Murat

2009-01-01

The stability of the zinc-blende structured MgS is studied using a constant pressure ab initio molecular dynamics technique. A phase transition into a rocksalt structure is observed through the simulation. The zinc-blende to rocksalt phase transformation proceeds via two rhombohedral intermediate phases within R3m (No:160) and R3-barm (No:166) symmetries and does not involve any bond breaking. This mechanism is different from the previously observed mechanism in molecular dynamics simulations. (fast track communication)

Will genomic selection be a practical method for plant breeding?

Science.gov (United States)

Nakaya, Akihiro; Isobe, Sachiko N

2012-11-01

Genomic selection or genome-wide selection (GS) has been highlighted as a new approach for marker-assisted selection (MAS) in recent years. GS is a form of MAS that selects favourable individuals based on genomic estimated breeding values. Previous studies have suggested the utility of GS, especially for capturing small-effect quantitative trait loci, but GS has not become a popular methodology in the field of plant breeding, possibly because there is insufficient information available on GS for practical use. In this review, GS is discussed from a practical breeding viewpoint. Statistical approaches employed in GS are briefly described, before the recent progress in GS studies is surveyed. GS practices in plant breeding are then reviewed before future prospects are discussed. Statistical concepts used in GS are discussed with genetic models and variance decomposition, heritability, breeding value and linear model. Recent progress in GS studies is reviewed with a focus on empirical studies. For the practice of GS in plant breeding, several specific points are discussed including linkage disequilibrium, feature of populations and genotyped markers and breeding scheme. Currently, GS is not perfect, but it is a potent, attractive and valuable approach for plant breeding. This method will be integrated into many practical breeding programmes in the near future with further advances and the maturing of its theory.

Selective whole genome amplification for resequencing target microbial species from complex natural samples.

Science.gov (United States)

Leichty, Aaron R; Brisson, Dustin

2014-10-01

Population genomic analyses have demonstrated power to address major questions in evolutionary and molecular microbiology. Collecting populations of genomes is hindered in many microbial species by the absence of a cost effective and practical method to collect ample quantities of sufficiently pure genomic DNA for next-generation sequencing. Here we present a simple method to amplify genomes of a target microbial species present in a complex, natural sample. The selective whole genome amplification (SWGA) technique amplifies target genomes using nucleotide sequence motifs that are common in the target microbe genome, but rare in the background genomes, to prime the highly processive phi29 polymerase. SWGA thus selectively amplifies the target genome from samples in which it originally represented a minor fraction of the total DNA. The post-SWGA samples are enriched in target genomic DNA, which are ideal for population resequencing. We demonstrate the efficacy of SWGA using both laboratory-prepared mixtures of cultured microbes as well as a natural host-microbe association. Targeted amplification of Borrelia burgdorferi mixed with Escherichia coli at genome ratios of 1:2000 resulted in >10(5)-fold amplification of the target genomes with genomic extracts from Wolbachia pipientis-infected Drosophila melanogaster resulted in up to 70% of high-throughput resequencing reads mapping to the W. pipientis genome. By contrast, 2-9% of sequencing reads were derived from W. pipientis without prior amplification. The SWGA technique results in high sequencing coverage at a fraction of the sequencing effort, thus allowing population genomic studies at affordable costs. Copyright © 2014 by the Genetics Society of America.

PSP: rapid identification of orthologous coding genes under positive selection across multiple closely related prokaryotic genomes.

Science.gov (United States)

Su, Fei; Ou, Hong-Yu; Tao, Fei; Tang, Hongzhi; Xu, Ping

2013-12-27

With genomic sequences of many closely related bacterial strains made available by deep sequencing, it is now possible to investigate trends in prokaryotic microevolution. Positive selection is a sub-process of microevolution, in which a particular mutation is favored, causing the allele frequency to continuously shift in one direction. Wide scanning of prokaryotic genomes has shown that positive selection at the molecular level is much more frequent than expected. Genes with significant positive selection may play key roles in bacterial adaption to different environmental pressures. However, selection pressure analyses are computationally intensive and awkward to configure. Here we describe an open access web server, which is designated as PSP (Positive Selection analysis for Prokaryotic genomes) for performing evolutionary analysis on orthologous coding genes, specially designed for rapid comparison of dozens of closely related prokaryotic genomes. Remarkably, PSP facilitates functional exploration at the multiple levels by assignments and enrichments of KO, GO or COG terms. To illustrate this user-friendly tool, we analyzed Escherichia coli and Bacillus cereus genomes and found that several genes, which play key roles in human infection and antibiotic resistance, show significant evidence of positive selection. PSP is freely available to all users without any login requirement at: http://db-mml.sjtu.edu.cn/PSP/. PSP ultimately allows researchers to do genome-scale analysis for evolutionary selection across multiple prokaryotic genomes rapidly and easily, and identify the genes undergoing positive selection, which may play key roles in the interactions of host-pathogen and/or environmental adaptation.

A privacy-preserving solution for compressed storage and selective retrieval of genomic data.

Science.gov (United States)

Huang, Zhicong; Ayday, Erman; Lin, Huang; Aiyar, Raeka S; Molyneaux, Adam; Xu, Zhenyu; Fellay, Jacques; Steinmetz, Lars M; Hubaux, Jean-Pierre

2016-12-01

In clinical genomics, the continuous evolution of bioinformatic algorithms and sequencing platforms makes it beneficial to store patients' complete aligned genomic data in addition to variant calls relative to a reference sequence. Due to the large size of human genome sequence data files (varying from 30 GB to 200 GB depending on coverage), two major challenges facing genomics laboratories are the costs of storage and the efficiency of the initial data processing. In addition, privacy of genomic data is becoming an increasingly serious concern, yet no standard data storage solutions exist that enable compression, encryption, and selective retrieval. Here we present a privacy-preserving solution named SECRAM (Selective retrieval on Encrypted and Compressed Reference-oriented Alignment Map) for the secure storage of compressed aligned genomic data. Our solution enables selective retrieval of encrypted data and improves the efficiency of downstream analysis (e.g., variant calling). Compared with BAM, the de facto standard for storing aligned genomic data, SECRAM uses 18% less storage. Compared with CRAM, one of the most compressed nonencrypted formats (using 34% less storage than BAM), SECRAM maintains efficient compression and downstream data processing, while allowing for unprecedented levels of security in genomic data storage. Compared with previous work, the distinguishing features of SECRAM are that (1) it is position-based instead of read-based, and (2) it allows random querying of a subregion from a BAM-like file in an encrypted form. Our method thus offers a space-saving, privacy-preserving, and effective solution for the storage of clinical genomic data. © 2016 Huang et al.; Published by Cold Spring Harbor Laboratory Press.

Genome-wide detection of selection and other evolutionary forces

DEFF Research Database (Denmark)

Xu, Zhuofei; Zhou, Rui

2015-01-01

As is well known, pathogenic microbes evolve rapidly to escape from the host immune system and antibiotics. Genetic variations among microbial populations occur frequently during the long-term pathogen–host evolutionary arms race, and individual mutation beneficial for the fitness can be fixed...... to scan genome-wide alignments for evidence of positive Darwinian selection, recombination, and other evolutionary forces operating on the coding regions. In this chapter, we describe an integrative analysis pipeline and its application to tracking featured evolutionary trajectories on the genome...

Natural selection affects multiple aspects of genetic variation at putatively neutral sites across the human genome.

Science.gov (United States)

Lohmueller, Kirk E; Albrechtsen, Anders; Li, Yingrui; Kim, Su Yeon; Korneliussen, Thorfinn; Vinckenbosch, Nicolas; Tian, Geng; Huerta-Sanchez, Emilia; Feder, Alison F; Grarup, Niels; Jørgensen, Torben; Jiang, Tao; Witte, Daniel R; Sandbæk, Annelli; Hellmann, Ines; Lauritzen, Torsten; Hansen, Torben; Pedersen, Oluf; Wang, Jun; Nielsen, Rasmus

2011-10-01

A major question in evolutionary biology is how natural selection has shaped patterns of genetic variation across the human genome. Previous work has documented a reduction in genetic diversity in regions of the genome with low recombination rates. However, it is unclear whether other summaries of genetic variation, like allele frequencies, are also correlated with recombination rate and whether these correlations can be explained solely by negative selection against deleterious mutations or whether positive selection acting on favorable alleles is also required. Here we attempt to address these questions by analyzing three different genome-wide resequencing datasets from European individuals. We document several significant correlations between different genomic features. In particular, we find that average minor allele frequency and diversity are reduced in regions of low recombination and that human diversity, human-chimp divergence, and average minor allele frequency are reduced near genes. Population genetic simulations show that either positive natural selection acting on favorable mutations or negative natural selection acting against deleterious mutations can explain these correlations. However, models with strong positive selection on nonsynonymous mutations and little negative selection predict a stronger negative correlation between neutral diversity and nonsynonymous divergence than observed in the actual data, supporting the importance of negative, rather than positive, selection throughout the genome. Further, we show that the widespread presence of weakly deleterious alleles, rather than a small number of strongly positively selected mutations, is responsible for the correlation between neutral genetic diversity and recombination rate. This work suggests that natural selection has affected multiple aspects of linked neutral variation throughout the human genome and that positive selection is not required to explain these observations.

Uninformative polymorphisms bias genome scans for signatures of selection

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Roesti Marius

2012-06-01

Full Text Available Abstract Background With the establishment of high-throughput sequencing technologies and new methods for rapid and extensive single nucleotide (SNP discovery, marker-based genome scans in search of signatures of divergent selection between populations occupying ecologically distinct environments are becoming increasingly popular. Methods and Results On the basis of genome-wide SNP marker data generated by RAD sequencing of lake and stream stickleback populations, we show that the outcome of such studies can be systematically biased if markers with a low minor allele frequency are included in the analysis. The reason is that these ‘uninformative’ polymorphisms lack the adequate potential to capture signatures of drift and hitchhiking, the focal processes in ecological genome scans. Bias associated with uninformative polymorphisms is not eliminated by just avoiding technical artifacts in the data (PCR and sequencing errors, as a high proportion of SNPs with a low minor allele frequency is a general biological feature of natural populations. Conclusions We suggest that uninformative markers should be excluded from genome scans based on empirical criteria derived from careful inspection of the data, and that these criteria should be reported explicitly. Together, this should increase the quality and comparability of genome scans, and hence promote our understanding of the processes driving genomic differentiation.

Different selective pressures lead to different genomic outcomes as newly-formed hybrid yeasts evolve

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Piotrowski Jeff S

2012-04-01

Full Text Available Abstract Background Interspecific hybridization occurs in every eukaryotic kingdom. While hybrid progeny are frequently at a selective disadvantage, in some instances their increased genome size and complexity may result in greater stress resistance than their ancestors, which can be adaptively advantageous at the edges of their ancestors' ranges. While this phenomenon has been repeatedly documented in the field, the response of hybrid populations to long-term selection has not often been explored in the lab. To fill this knowledge gap we crossed the two most distantly related members of the Saccharomyces sensu stricto group, S. cerevisiae and S. uvarum, and established a mixed population of homoploid and aneuploid hybrids to study how different types of selection impact hybrid genome structure. Results As temperature was raised incrementally from 31°C to 46.5°C over 500 generations of continuous culture, selection favored loss of the S. uvarum genome, although the kinetics of genome loss differed among independent replicates. Temperature-selected isolates exhibited greater inherent and induced thermal tolerance than parental species and founding hybrids, and also exhibited ethanol resistance. In contrast, as exogenous ethanol was increased from 0% to 14% over 500 generations of continuous culture, selection favored euploid S. cerevisiae x S. uvarum hybrids. Ethanol-selected isolates were more ethanol tolerant than S. uvarum and one of the founding hybrids, but did not exhibit resistance to temperature stress. Relative to parental and founding hybrids, temperature-selected strains showed heritable differences in cell wall structure in the forms of increased resistance to zymolyase digestion and Micafungin, which targets cell wall biosynthesis. Conclusions This is the first study to show experimentally that the genomic fate of newly-formed interspecific hybrids depends on the type of selection they encounter during the course of evolution

Comparison of analyses of the QTLMAS XIII common dataset. I: genomic selection

NARCIS (Netherlands)

Bastiaansen, J.W.M.; Bink, M.C.A.M.; Coster, A.; Maliepaard, C.A.; Calus, M.P.L.

2010-01-01

Background - Genomic selection, the use of markers across the whole genome, receives increasing amounts of attention and is having more and more impact on breeding programs. Development of statistical and computational methods to estimate breeding values based on markers is a very active area of

Positive selection for unpreferred codon usage in eukaryotic genomes

Directory of Open Access Journals (Sweden)

Galagan James E

2007-07-01

Full Text Available Abstract Background Natural selection has traditionally been understood as a force responsible for pushing genes to states of higher translational efficiency, whereas lower translational efficiency has been explained by neutral mutation and genetic drift. We looked for evidence of directional selection resulting in increased unpreferred codon usage (and presumably reduced translational efficiency in three divergent clusters of eukaryotic genomes using a simple optimal-codon-based metric (Kp/Ku. Results Here we show that for some genes natural selection is indeed responsible for causing accelerated unpreferred codon substitution, and document the scope of this selection. In Cryptococcus and to a lesser extent Drosophila, we find many genes showing a statistically significant signal of selection for unpreferred codon usage in one or more lineages. We did not find evidence for this type of selection in Saccharomyces. The signal of positive selection observed from unpreferred synonymous codon substitutions is coincident in Cryptococcus and Drosophila with the distribution of upstream open reading frames (uORFs, another genic feature known to reduce translational efficiency. Functional enrichment analysis of genes exhibiting low Kp/Ku ratios reveals that genes in regulatory roles are particularly subject to this type of selection. Conclusion Through genome-wide scans, we find recent selection for unpreferred codon usage at approximately 1% of genetic loci in a Cryptococcus and several genes in Drosophila. Unpreferred codons can impede translation efficiency, and we find that genes with translation-impeding uORFs are enriched for this selection signal. We find that regulatory genes are particularly likely to be subject to selection for unpreferred codon usage. Given that expression noise can propagate through regulatory cascades, and that low translational efficiency can reduce expression noise, this finding supports the hypothesis that translational

Accounting for linkage disequilibrium in genome scans for selection without individual genotypes: The local score approach.

Science.gov (United States)

Fariello, María Inés; Boitard, Simon; Mercier, Sabine; Robelin, David; Faraut, Thomas; Arnould, Cécile; Recoquillay, Julien; Bouchez, Olivier; Salin, Gérald; Dehais, Patrice; Gourichon, David; Leroux, Sophie; Pitel, Frédérique; Leterrier, Christine; SanCristobal, Magali

2017-07-01

Detecting genomic footprints of selection is an important step in the understanding of evolution. Accounting for linkage disequilibrium in genome scans increases detection power, but haplotype-based methods require individual genotypes and are not applicable on pool-sequenced samples. We propose to take advantage of the local score approach to account for linkage disequilibrium in genome scans for selection, cumulating (possibly small) signals from single markers over a genomic segment, to clearly pinpoint a selection signal. Using computer simulations, we demonstrate that this approach detects selection with higher power than several state-of-the-art single-marker, windowing or haplotype-based approaches. We illustrate this on two benchmark data sets including individual genotypes, for which we obtain similar results with the local score and one haplotype-based approach. Finally, we apply the local score approach to Pool-Seq data obtained from a divergent selection experiment on behaviour in quail and obtain precise and biologically coherent selection signals: while competing methods fail to highlight any clear selection signature, our method detects several regions involving genes known to act on social responsiveness or autistic traits. Although we focus here on the detection of positive selection from multiple population data, the local score approach is general and can be applied to other genome scans for selection or other genomewide analyses such as GWAS. © 2017 John Wiley & Sons Ltd.

Accuracy and responses of genomic selection on key traits in apple breeding

NARCIS (Netherlands)

Muranty, Hélène; Troggio, Michela; Sadok, Ben Inès; Rifaï, Al Mehdi; Auwerkerken, Annemarie; Banchi, E.; Velasco, Riccardo; Stevanato, P.; Weg, van de W.E.; Guardo, Di M.; Kumar, S.; Laurens, François; Bink, M.C.A.M.

2015-01-01

The application of genomic selection in fruit tree crops is expected to enhance breeding efficiency by increasing prediction accuracy, increasing selection intensity and decreasing generation interval. The objectives of this study were to assess the accuracy of prediction and selection response in

Accuracy of genomic selection in biparental populations of flax (Linum usitatissimum L.

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Frank M. You

2016-08-01

Full Text Available Flax is an important economic crop for seed oil and stem fiber. Phenotyping of traits such as seed yield, seed quality, stem fiber yield, and quality characteristics is expensive and time consuming. Genomic selection (GS refers to a breeding approach aimed at selecting preferred individuals based on genomic estimated breeding values predicted by a statistical model based on the relationship between phenotypes and genome-wide genetic markers. We evaluated the prediction accuracy of GS (rMP and the efficiency of GS relative to phenotypic selection (RE for three GS models: ridge regression best linear unbiased prediction (RR-BLUP, Bayesian LASSO (BL, and Bayesian ridge regression (BRR, for seed yield, oil content, iodine value, linoleic, and linolenic acid content with a full and a common set of genome-wide simple sequence repeat markers in each of three biparental populations. The three GS models generated similar rMP and RE, while BRR displayed a higher coefficient of determination (R2 of the fitted models than did RR-BLUP or BL. The mean rMP and RE varied for traits with different heritabilities and was affected by the genetic variation of the traits in the populations. GS for seed yield generated a mean RE of 1.52 across populations and marker sets, a value significantly superior to that for direct phenotypic selection. Our empirical results provide the first validation of GS in flax and demonstrate that GS could increase genetic gain per unit time for linseed breeding. Further studies for selection of training populations and markers are warranted.

Identification of genomic variants putatively targeted by selection during dog domestication.

Science.gov (United States)

Cagan, Alex; Blass, Torsten

2016-01-12

Dogs [Canis lupus familiaris] were the first animal species to be domesticated and continue to occupy an important place in human societies. Recent studies have begun to reveal when and where dog domestication occurred. While much progress has been made in identifying the genetic basis of phenotypic differences between dog breeds we still know relatively little about the genetic changes underlying the phenotypes that differentiate all dogs from their wild progenitors, wolves [Canis lupus]. In particular, dogs generally show reduced aggression and fear towards humans compared to wolves. Therefore, selection for tameness was likely a necessary prerequisite for dog domestication. With the increasing availability of whole-genome sequence data it is possible to try and directly identify the genetic variants contributing to the phenotypic differences between dogs and wolves. We analyse the largest available database of genome-wide polymorphism data in a global sample of dogs 69 and wolves 7. We perform a scan to identify regions of the genome that are highly differentiated between dogs and wolves. We identify putatively functional genomic variants that are segregating or at high frequency [> = 0.75 Fst] for alternative alleles between dogs and wolves. A biological pathways analysis of the genes containing these variants suggests that there has been selection on the 'adrenaline and noradrenaline biosynthesis pathway', well known for its involvement in the fight-or-flight response. We identify 11 genes with putatively functional variants fixed for alternative alleles between dogs and wolves. The segregating variants in these genes are strong candidates for having been targets of selection during early dog domestication. We present the first genome-wide analysis of the different categories of putatively functional variants that are fixed or segregating at high frequency between a global sampling of dogs and wolves. We find evidence that selection has been strongest

Genomic prediction for Nordic Red Cattle using one-step and selection index blending

DEFF Research Database (Denmark)

Guosheng, Su; Madsen, Per; Nielsen, Ulrik Sander

2012-01-01

This study investigated the accuracy of direct genomic breeding values (DGV) using a genomic BLUP model, genomic enhanced breeding values (GEBV) using a one-step blending approach, and GEBV using a selection index blending approach for 15 traits of Nordic Red Cattle. The data comprised 6,631 bulls...... genotyped and nongenotyped bulls for one-step blending, and to scale DGV and its expected reliability in the selection index blending. Weighting (scaling) factors had a small influence on reliabilities of GEBV, but a large influence on the variation of GEBV. Based on the validation analyses, averaged over...... the 15 traits, the reliability of DGV for bulls without daughter records was 11.0 percentage points higher than the reliability of conventional pedigree index. Further gain of 0.9 percentage points was achieved by combining information from conventional pedigree index using the selection index blending...

A genome scan for positive selection in thoroughbred horses.

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Jingjing Gu

2009-06-01

Full Text Available Thoroughbred horses have been selected for exceptional racing performance resulting in system-wide structural and functional adaptations contributing to elite athletic phenotypes. Because selection has been recent and intense in a closed population that stems from a small number of founder animals Thoroughbreds represent a unique population within which to identify genomic contributions to exercise-related traits. Employing a population genetics-based hitchhiking mapping approach we performed a genome scan using 394 autosomal and X chromosome microsatellite loci and identified positively selected loci in the extreme tail-ends of the empirical distributions for (1 deviations from expected heterozygosity (Ewens-Watterson test in Thoroughbred (n = 112 and (2 global differentiation among four geographically diverse horse populations (F(ST. We found positively selected genomic regions in Thoroughbred enriched for phosphoinositide-mediated signalling (3.2-fold enrichment; P<0.01, insulin receptor signalling (5.0-fold enrichment; P<0.01 and lipid transport (2.2-fold enrichment; P<0.05 genes. We found a significant overrepresentation of sarcoglycan complex (11.1-fold enrichment; P<0.05 and focal adhesion pathway (1.9-fold enrichment; P<0.01 genes highlighting the role for muscle strength and integrity in the Thoroughbred athletic phenotype. We report for the first time candidate athletic-performance genes within regions targeted by selection in Thoroughbred horses that are principally responsible for fatty acid oxidation, increased insulin sensitivity and muscle strength: ACSS1 (acyl-CoA synthetase short-chain family member 1, ACTA1 (actin, alpha 1, skeletal muscle, ACTN2 (actinin, alpha 2, ADHFE1 (alcohol dehydrogenase, iron containing, 1, MTFR1 (mitochondrial fission regulator 1, PDK4 (pyruvate dehydrogenase kinase, isozyme 4 and TNC (tenascin C. Understanding the genetic basis for exercise adaptation will be crucial for the identification of genes

Selective Gene Delivery for Integrating Exogenous DNA into Plastid and Mitochondrial Genomes Using Peptide-DNA Complexes.

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Yoshizumi, Takeshi; Oikawa, Kazusato; Chuah, Jo-Ann; Kodama, Yutaka; Numata, Keiji

2018-05-14

Selective gene delivery into organellar genomes (mitochondrial and plastid genomes) has been limited because of a lack of appropriate platform technology, even though these organelles are essential for metabolite and energy production. Techniques for selective organellar modification are needed to functionally improve organelles and produce transplastomic/transmitochondrial plants. However, no method for mitochondrial genome modification has yet been established for multicellular organisms including plants. Likewise, modification of plastid genomes has been limited to a few plant species and algae. In the present study, we developed ionic complexes of fusion peptides containing organellar targeting signal and plasmid DNA for selective delivery of exogenous DNA into the plastid and mitochondrial genomes of intact plants. This is the first report of exogenous DNA being integrated into the mitochondrial genomes of not only plants, but also multicellular organisms in general. This fusion peptide-mediated gene delivery system is a breakthrough platform for both plant organellar biotechnology and gene therapy for mitochondrial diseases in animals.

The impacts of drift and selection on genomic evolution in insects

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K. Jun Tong

2017-04-01

Full Text Available Genomes evolve through a combination of mutation, drift, and selection, all of which act heterogeneously across genes and lineages. This leads to differences in branch-length patterns among gene trees. Genes that yield trees with the same branch-length patterns can be grouped together into clusters. Here, we propose a novel phylogenetic approach to explain the factors that influence the number and distribution of these gene-tree clusters. We apply our method to a genomic dataset from insects, an ancient and diverse group of organisms. We find some evidence that when drift is the dominant evolutionary process, each cluster tends to contain a large number of fast-evolving genes. In contrast, strong negative selection leads to many distinct clusters, each of which contains only a few slow-evolving genes. Our work, although preliminary in nature, illustrates the use of phylogenetic methods to shed light on the factors driving rate variation in genomic evolution.

Signatures of selection in the Iberian honey bee: a genome wide approach using single nucleotide polymorphisms (SNPs)

OpenAIRE

Chavez-Galarza, Julio; Johnston, J. Spencer; Azevedo, João; Muñoz, Irene; De la Rúa, Pilar; Patton, John C.; Pinto, M. Alice

2011-01-01

Dissecting genome-wide (expansions, contractions, admixture) from genome-specific effects (selection) is a goal of central importance in evolutionary biology because it leads to more robust inferences of demographic history and to identification of adaptive divergence. The publication of the honey bee genome and the development of high-density SNPs genotyping, provide us with powerful tools, allowing us to identify signatures of selection in the honey bee genome. These signatur...

Genome-Wide Footprints of Pig Domestication and Selection Revealed through Massive Parallel Sequencing of Pooled DNA

NARCIS (Netherlands)

Amaral, A.J.; Ferretti, L.; Megens, H.J.W.C.; Crooijmans, R.P.M.A.; Nie, H.; Ramos-Onsins, S.E.; Perez-Enciso, M.; Schook, L.B.; Groenen, M.A.M.

2011-01-01

Background Artificial selection has caused rapid evolution in domesticated species. The identification of selection footprints across domesticated genomes can contribute to uncover the genetic basis of phenotypic diversity. Methodology/Main Findings Genome wide footprints of pig domestication and

Prediction of Cacao (Theobroma cacao) Resistance to Moniliophthora spp. Diseases via Genome-Wide Association Analysis and Genomic Selection.

Science.gov (United States)

McElroy, Michel S; Navarro, Alberto J R; Mustiga, Guiliana; Stack, Conrad; Gezan, Salvador; Peña, Geover; Sarabia, Widem; Saquicela, Diego; Sotomayor, Ignacio; Douglas, Gavin M; Migicovsky, Zoë; Amores, Freddy; Tarqui, Omar; Myles, Sean; Motamayor, Juan C

2018-01-01

Cacao ( Theobroma cacao ) is a globally important crop, and its yield is severely restricted by disease. Two of the most damaging diseases, witches' broom disease (WBD) and frosty pod rot disease (FPRD), are caused by a pair of related fungi: Moniliophthora perniciosa and Moniliophthora roreri , respectively. Resistant cultivars are the most effective long-term strategy to address Moniliophthora diseases, but efficiently generating resistant and productive new cultivars will require robust methods for screening germplasm before field testing. Marker-assisted selection (MAS) and genomic selection (GS) provide two potential avenues for predicting the performance of new genotypes, potentially increasing the selection gain per unit time. To test the effectiveness of these two approaches, we performed a genome-wide association study (GWAS) and GS on three related populations of cacao in Ecuador genotyped with a 15K single nucleotide polymorphism (SNP) microarray for three measures of WBD infection (vegetative broom, cushion broom, and chirimoya pod), one of FPRD (monilia pod) and two productivity traits (total fresh weight of pods and % healthy pods produced). GWAS yielded several SNPs associated with disease resistance in each population, but none were significantly correlated with the same trait in other populations. Genomic selection, using one population as a training set to estimate the phenotypes of the remaining two (composed of different families), varied among traits, from a mean prediction accuracy of 0.46 (vegetative broom) to 0.15 (monilia pod), and varied between training populations. Simulations demonstrated that selecting seedlings using GWAS markers alone generates no improvement over selecting at random, but that GS improves the selection process significantly. Our results suggest that the GWAS markers discovered here are not sufficiently predictive across diverse germplasm to be useful for MAS, but that using all markers in a GS framework holds

Prediction of Cacao (Theobroma cacao Resistance to Moniliophthora spp. Diseases via Genome-Wide Association Analysis and Genomic Selection

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Michel S. McElroy

2018-03-01

Full Text Available Cacao (Theobroma cacao is a globally important crop, and its yield is severely restricted by disease. Two of the most damaging diseases, witches’ broom disease (WBD and frosty pod rot disease (FPRD, are caused by a pair of related fungi: Moniliophthora perniciosa and Moniliophthora roreri, respectively. Resistant cultivars are the most effective long-term strategy to address Moniliophthora diseases, but efficiently generating resistant and productive new cultivars will require robust methods for screening germplasm before field testing. Marker-assisted selection (MAS and genomic selection (GS provide two potential avenues for predicting the performance of new genotypes, potentially increasing the selection gain per unit time. To test the effectiveness of these two approaches, we performed a genome-wide association study (GWAS and GS on three related populations of cacao in Ecuador genotyped with a 15K single nucleotide polymorphism (SNP microarray for three measures of WBD infection (vegetative broom, cushion broom, and chirimoya pod, one of FPRD (monilia pod and two productivity traits (total fresh weight of pods and % healthy pods produced. GWAS yielded several SNPs associated with disease resistance in each population, but none were significantly correlated with the same trait in other populations. Genomic selection, using one population as a training set to estimate the phenotypes of the remaining two (composed of different families, varied among traits, from a mean prediction accuracy of 0.46 (vegetative broom to 0.15 (monilia pod, and varied between training populations. Simulations demonstrated that selecting seedlings using GWAS markers alone generates no improvement over selecting at random, but that GS improves the selection process significantly. Our results suggest that the GWAS markers discovered here are not sufficiently predictive across diverse germplasm to be useful for MAS, but that using all markers in a GS framework holds

Genome-wide single-generation signatures of local selection in the panmictic European eel

DEFF Research Database (Denmark)

Pujolar, J. M.; Jacobsen, M. W.; Als, Thomas Damm

2014-01-01

Next-generation sequencing and the collection of genome-wide data allow identifying adaptive variation and footprints of directional selection. Using a large SNP data set from 259 RAD-sequenced European eel individuals (glass eels) from eight locations between 34 and 64oN, we examined the patterns...... of genome-wide genetic diversity across locations. We tested for local selection by searching for increased population differentiation using FST-based outlier tests and by testing for significant associations between allele frequencies and environmental variables. The overall low genetic differentiation...... with single-generation signatures of spatially varying selection acting on glass eels. After screening 50 354 SNPs, a total of 754 potentially locally selected SNPs were identified. Candidate genes for local selection constituted a wide array of functions, including calcium signalling, neuroactive ligand...

Does selection against transcriptional interference shape retroelement-free regions in mammalian genomes?

DEFF Research Database (Denmark)

Mourier, Tobias; Willerslev, Eske

2008-01-01

in generating and maintaining retroelement-free regions in the human genome. METHODOLOGY/PRINCIPAL FINDINGS: Based on the known transcriptional properties of retroelements, we expect long interspersed elements (LINEs) to be able to display a high degree of transcriptional interference. In contrast, we expect......BACKGROUND: Eukaryotic genomes are scattered with retroelements that proliferate through retrotransposition. Although retroelements make up around 40 percent of the human genome, large regions are found to be completely devoid of retroelements. This has been hypothesised to be a result of genomic...... activity of LINEs has been identified previously. CONCLUSIONS/SIGNIFICANCE: Our observations are consistent with the notion that selection against transcriptional interference has contributed to the maintenance and/or generation of retroelement-free regions in the human genome....

Natural selection affects multiple aspects of genetic variation at putatively peutral sites across the human genome

DEFF Research Database (Denmark)

Lohmueller, Kirk E; Albrechtsen, Anders; Li, Yingrui

2011-01-01

A major question in evolutionary biology is how natural selection has shaped patterns of genetic variation across the human genome. Previous work has documented a reduction in genetic diversity in regions of the genome with low recombination rates. However, it is unclear whether other summaries...... these questions by analyzing three different genome-wide resequencing datasets from European individuals. We document several significant correlations between different genomic features. In particular, we find that average minor allele frequency and diversity are reduced in regions of low recombination...... and that human diversity, human-chimp divergence, and average minor allele frequency are reduced near genes. Population genetic simulations show that either positive natural selection acting on favorable mutations or negative natural selection acting against deleterious mutations can explain these correlations...

Does selection against transcriptional interference shape retroelement-free regions in mammalian genomes?

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Tobias Mourier

Full Text Available BACKGROUND: Eukaryotic genomes are scattered with retroelements that proliferate through retrotransposition. Although retroelements make up around 40 percent of the human genome, large regions are found to be completely devoid of retroelements. This has been hypothesised to be a result of genomic regions being intolerant to insertions of retroelements. The inadvertent transcriptional activity of retroelements may affect neighbouring genes, which in turn could be detrimental to an organism. We speculate that such retroelement transcription, or transcriptional interference, is a contributing factor in generating and maintaining retroelement-free regions in the human genome. METHODOLOGY/PRINCIPAL FINDINGS: Based on the known transcriptional properties of retroelements, we expect long interspersed elements (LINEs to be able to display a high degree of transcriptional interference. In contrast, we expect short interspersed elements (SINEs to display very low levels of transcriptional interference. We find that genomic regions devoid of long interspersed elements (LINEs are enriched for protein-coding genes, but that this is not the case for regions devoid of short interspersed elements (SINEs. This is expected if genes are subject to selection against transcriptional interference. We do not find microRNAs to be associated with genomic regions devoid of either SINEs or LINEs. We further observe an increased relative activity of genes overlapping LINE-free regions during early embryogenesis, where activity of LINEs has been identified previously. CONCLUSIONS/SIGNIFICANCE: Our observations are consistent with the notion that selection against transcriptional interference has contributed to the maintenance and/or generation of retroelement-free regions in the human genome.

The importance of identity-by-state information for the accuracy of genomic selection

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Luan Tu

2012-08-01

Full Text Available Abstract Background It is commonly assumed that prediction of genome-wide breeding values in genomic selection is achieved by capitalizing on linkage disequilibrium between markers and QTL but also on genetic relationships. Here, we investigated the reliability of predicting genome-wide breeding values based on population-wide linkage disequilibrium information, based on identity-by-descent relationships within the known pedigree, and to what extent linkage disequilibrium information improves predictions based on identity-by-descent genomic relationship information. Methods The study was performed on milk, fat, and protein yield, using genotype data on 35 706 SNP and deregressed proofs of 1086 Italian Brown Swiss bulls. Genome-wide breeding values were predicted using a genomic identity-by-state relationship matrix and a genomic identity-by-descent relationship matrix (averaged over all marker loci. The identity-by-descent matrix was calculated by linkage analysis using one to five generations of pedigree data. Results We showed that genome-wide breeding values prediction based only on identity-by-descent genomic relationships within the known pedigree was as or more reliable than that based on identity-by-state, which implicitly also accounts for genomic relationships that occurred before the known pedigree. Furthermore, combining the two matrices did not improve the prediction compared to using identity-by-descent alone. Including different numbers of generations in the pedigree showed that most of the information in genome-wide breeding values prediction comes from animals with known common ancestors less than four generations back in the pedigree. Conclusions Our results show that, in pedigreed breeding populations, the accuracy of genome-wide breeding values obtained by identity-by-descent relationships was not improved by identity-by-state information. Although, in principle, genomic selection based on identity-by-state does not require

Whole genome detection of signature of positive selection in African cattle reveals selection for thermotolerance.

Science.gov (United States)

Taye, Mengistie; Lee, Wonseok; Caetano-Anolles, Kelsey; Dessie, Tadelle; Hanotte, Olivier; Mwai, Okeyo Ally; Kemp, Stephen; Cho, Seoae; Oh, Sung Jong; Lee, Hak-Kyo; Kim, Heebal

2017-12-01

As African indigenous cattle evolved in a hot tropical climate, they have developed an inherent thermotolerance; survival mechanisms include a light-colored and shiny coat, increased sweating, and cellular and molecular mechanisms to cope with high environmental temperature. Here, we report the positive selection signature of genes in African cattle breeds which contribute for their heat tolerance mechanisms. We compared the genomes of five indigenous African cattle breeds with the genomes of four commercial cattle breeds using cross-population composite likelihood ratio (XP-CLR) and cross-population extended haplotype homozygosity (XP-EHH) statistical methods. We identified 296 (XP-EHH) and 327 (XP-CLR) positively selected genes. Gene ontology analysis resulted in 41 biological process terms and six Kyoto Encyclopedia of Genes and Genomes pathways. Several genes and pathways were found to be involved in oxidative stress response, osmotic stress response, heat shock response, hair and skin properties, sweat gland development and sweating, feed intake and metabolism, and reproduction functions. The genes and pathways identified directly or indirectly contribute to the superior heat tolerance mechanisms in African cattle populations. The result will improve our understanding of the biological mechanisms of heat tolerance in African cattle breeds and opens an avenue for further study. © 2017 Japanese Society of Animal Science.

Single-Molecule FISH Reveals Non-selective Packaging of Rift Valley Fever Virus Genome Segments.

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Paul J Wichgers Schreur

2016-08-01

Full Text Available The bunyavirus genome comprises a small (S, medium (M, and large (L RNA segment of negative polarity. Although genome segmentation confers evolutionary advantages by enabling genome reassortment events with related viruses, genome segmentation also complicates genome replication and packaging. Accumulating evidence suggests that genomes of viruses with eight or more genome segments are incorporated into virions by highly selective processes. Remarkably, little is known about the genome packaging process of the tri-segmented bunyaviruses. Here, we evaluated, by single-molecule RNA fluorescence in situ hybridization (FISH, the intracellular spatio-temporal distribution and replication kinetics of the Rift Valley fever virus (RVFV genome and determined the segment composition of mature virions. The results reveal that the RVFV genome segments start to replicate near the site of infection before spreading and replicating throughout the cytoplasm followed by translocation to the virion assembly site at the Golgi network. Despite the average intracellular S, M and L genome segments approached a 1:1:1 ratio, major differences in genome segment ratios were observed among cells. We also observed a significant amount of cells lacking evidence of M-segment replication. Analysis of two-segmented replicons and four-segmented viruses subsequently confirmed the previous notion that Golgi recruitment is mediated by the Gn glycoprotein. The absence of colocalization of the different segments in the cytoplasm and the successful rescue of a tri-segmented variant with a codon shuffled M-segment suggested that inter-segment interactions are unlikely to drive the copackaging of the different segments into a single virion. The latter was confirmed by direct visualization of RNPs inside mature virions which showed that the majority of virions lack one or more genome segments. Altogether, this study suggests that RVFV genome packaging is a non-selective process.

Identification of genomic regions associated with phenotypic variation between dog breeds using selection mapping.

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Amaury Vaysse

2011-10-01

Full Text Available The extraordinary phenotypic diversity of dog breeds has been sculpted by a unique population history accompanied by selection for novel and desirable traits. Here we perform a comprehensive analysis using multiple test statistics to identify regions under selection in 509 dogs from 46 diverse breeds using a newly developed high-density genotyping array consisting of >170,000 evenly spaced SNPs. We first identify 44 genomic regions exhibiting extreme differentiation across multiple breeds. Genetic variation in these regions correlates with variation in several phenotypic traits that vary between breeds, and we identify novel associations with both morphological and behavioral traits. We next scan the genome for signatures of selective sweeps in single breeds, characterized by long regions of reduced heterozygosity and fixation of extended haplotypes. These scans identify hundreds of regions, including 22 blocks of homozygosity longer than one megabase in certain breeds. Candidate selection loci are strongly enriched for developmental genes. We chose one highly differentiated region, associated with body size and ear morphology, and characterized it using high-throughput sequencing to provide a list of variants that may directly affect these traits. This study provides a catalogue of genomic regions showing extreme reduction in genetic variation or population differentiation in dogs, including many linked to phenotypic variation. The many blocks of reduced haplotype diversity observed across the genome in dog breeds are the result of both selection and genetic drift, but extended blocks of homozygosity on a megabase scale appear to be best explained by selection. Further elucidation of the variants under selection will help to uncover the genetic basis of complex traits and disease.

Bayesian genomic selection: the effect of haplotype lenghts and priors

DEFF Research Database (Denmark)

Villumsen, Trine Michelle; Janss, Luc

2009-01-01

Breeding values for animals with marker data are estimated using a genomic selection approach where data is analyzed using Bayesian multi-marker association models. Fourteen model scenarios with varying haplotype lengths, hyper parameter and prior distributions were compared to find the scenario ...

A genome-wide scan for signatures of directional selection in domesticated pigs.

Science.gov (United States)

Moon, Sunjin; Kim, Tae-Hun; Lee, Kyung-Tai; Kwak, Woori; Lee, Taeheon; Lee, Si-Woo; Kim, Myung-Jick; Cho, Kyuho; Kim, Namshin; Chung, Won-Hyong; Sung, Samsun; Park, Taesung; Cho, Seoae; Groenen, Martien Am; Nielsen, Rasmus; Kim, Yuseob; Kim, Heebal

2015-02-25

Animal domestication involved drastic phenotypic changes driven by strong artificial selection and also resulted in new populations of breeds, established by humans. This study aims to identify genes that show evidence of recent artificial selection during pig domestication. Whole-genome resequencing of 30 individual pigs from domesticated breeds, Landrace and Yorkshire, and 10 Asian wild boars at ~16-fold coverage was performed resulting in over 4.3 million SNPs for 19,990 genes. We constructed a comprehensive genome map of directional selection by detecting selective sweeps using an F ST-based approach that detects directional selection in lineages leading to the domesticated breeds and using a haplotype-based test that detects ongoing selective sweeps within the breeds. We show that candidate genes under selection are significantly enriched for loci implicated in quantitative traits important to pig reproduction and production. The candidate gene with the strongest signals of directional selection belongs to group III of the metabolomics glutamate receptors, known to affect brain functions associated with eating behavior, suggesting that loci under strong selection include loci involved in behaviorial traits in domesticated pigs including tameness. We show that a significant proportion of selection signatures coincide with loci that were previously inferred to affect phenotypic variation in pigs. We further identify functional enrichment related to behavior, such as signal transduction and neuronal activities, for those targets of selection during domestication in pigs.

Integration of genomic information into sport horse breeding programs for optimization of accuracy of selection.

Science.gov (United States)

Haberland, A M; König von Borstel, U; Simianer, H; König, S

2012-09-01

Reliable selection criteria are required for young riding horses to increase genetic gain by increasing accuracy of selection and decreasing generation intervals. In this study, selection strategies incorporating genomic breeding values (GEBVs) were evaluated. Relevant stages of selection in sport horse breeding programs were analyzed by applying selection index theory. Results in terms of accuracies of indices (r(TI) ) and relative selection response indicated that information on single nucleotide polymorphism (SNP) genotypes considerably increases the accuracy of breeding values estimated for young horses without own or progeny performance. In a first scenario, the correlation between the breeding value estimated from the SNP genotype and the true breeding value (= accuracy of GEBV) was fixed to a relatively low value of r(mg) = 0.5. For a low heritability trait (h(2) = 0.15), and an index for a young horse based only on information from both parents, additional genomic information doubles r(TI) from 0.27 to 0.54. Including the conventional information source 'own performance' into the before mentioned index, additional SNP information increases r(TI) by 40%. Thus, particularly with regard to traits of low heritability, genomic information can provide a tool for well-founded selection decisions early in life. In a further approach, different sources of breeding values (e.g. GEBV and estimated breeding values (EBVs) from different countries) were combined into an overall index when altering accuracies of EBVs and correlations between traits. In summary, we showed that genomic selection strategies have the potential to contribute to a substantial reduction in generation intervals in horse breeding programs.

Genetic association of marbling score with intragenic nucleotide variants at selection signals of the bovine genome.

Science.gov (United States)

Ryu, J; Lee, C

2016-04-01

Selection signals of Korean cattle might be attributed largely to artificial selection for meat quality. Rapidly increased intragenic markers of newly annotated genes in the bovine genome would help overcome limited findings of genetic markers associated with meat quality at the selection signals in a previous study. The present study examined genetic associations of marbling score (MS) with intragenic nucleotide variants at selection signals of Korean cattle. A total of 39 092 nucleotide variants of 407 Korean cattle were utilized in the association analysis. A total of 129 variants were selected within newly annotated genes in the bovine genome. Their genetic associations were analyzed using the mixed model with random polygenic effects based on identical-by-state genetic relationships among animals in order to control for spurious associations produced by population structure. Genetic associations of MS were found (Pdirectional selection for greater MS and remain selection signals in the bovine genome. Further studies of fine mapping would be useful to incorporate favorable alleles in marker-assisted selection for MS of Korean cattle.

Genomic Selection Accuracy using Multifamily Prediction Models in a Wheat Breeding Program

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Elliot L. Heffner

2011-03-01

Full Text Available Genomic selection (GS uses genome-wide molecular marker data to predict the genetic value of selection candidates in breeding programs. In plant breeding, the ability to produce large numbers of progeny per cross allows GS to be conducted within each family. However, this approach requires phenotypes of lines from each cross before conducting GS. This will prolong the selection cycle and may result in lower gains per year than approaches that estimate marker-effects with multiple families from previous selection cycles. In this study, phenotypic selection (PS, conventional marker-assisted selection (MAS, and GS prediction accuracy were compared for 13 agronomic traits in a population of 374 winter wheat ( L. advanced-cycle breeding lines. A cross-validation approach that trained and validated prediction accuracy across years was used to evaluate effects of model selection, training population size, and marker density in the presence of genotype × environment interactions (G×E. The average prediction accuracies using GS were 28% greater than with MAS and were 95% as accurate as PS. For net merit, the average accuracy across six selection indices for GS was 14% greater than for PS. These results provide empirical evidence that multifamily GS could increase genetic gain per unit time and cost in plant breeding.

Systematic differences in the response of genetic variation to pedigree and genome-based selection methods.

Science.gov (United States)

Heidaritabar, M; Vereijken, A; Muir, W M; Meuwissen, T; Cheng, H; Megens, H-J; Groenen, M A M; Bastiaansen, J W M

2014-12-01

Genomic selection (GS) is a DNA-based method of selecting for quantitative traits in animal and plant breeding, and offers a potentially superior alternative to traditional breeding methods that rely on pedigree and phenotype information. Using a 60 K SNP chip with markers spaced throughout the entire chicken genome, we compared the impact of GS and traditional BLUP (best linear unbiased prediction) selection methods applied side-by-side in three different lines of egg-laying chickens. Differences were demonstrated between methods, both at the level and genomic distribution of allele frequency changes. In all three lines, the average allele frequency changes were larger with GS, 0.056 0.064 and 0.066, compared with BLUP, 0.044, 0.045 and 0.036 for lines B1, B2 and W1, respectively. With BLUP, 35 selected regions (empirical P selected regions were identified. Empirical thresholds for local allele frequency changes were determined from gene dropping, and differed considerably between GS (0.167-0.198) and BLUP (0.105-0.126). Between lines, the genomic regions with large changes in allele frequencies showed limited overlap. Our results show that GS applies selection pressure much more locally than BLUP, resulting in larger allele frequency changes. With these results, novel insights into the nature of selection on quantitative traits have been gained and important questions regarding the long-term impact of GS are raised. The rapid changes to a part of the genetic architecture, while another part may not be selected, at least in the short term, require careful consideration, especially when selection occurs before phenotypes are observed.

Impact of reduced marker set estimation of genomic relationship matrices on genomic selection for feed efficiency in Angus cattle

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Northcutt Sally L

2010-04-01

Full Text Available Abstract Background Molecular estimates of breeding value are expected to increase selection response due to improvements in the accuracy of selection and a reduction in generation interval, particularly for traits that are difficult or expensive to record or are measured late in life. Several statistical methods for incorporating molecular data into breeding value estimation have been proposed, however, most studies have utilized simulated data in which the generated linkage disequilibrium may not represent the targeted livestock population. A genomic relationship matrix was developed for 698 Angus steers and 1,707 Angus sires using 41,028 single nucleotide polymorphisms and breeding values were estimated using feed efficiency phenotypes (average daily feed intake, residual feed intake, and average daily gain recorded on the steers. The number of SNPs needed to accurately estimate a genomic relationship matrix was evaluated in this population. Results Results were compared to estimates produced from pedigree-based mixed model analysis of 862 Angus steers with 34,864 identified paternal relatives but no female ancestors. Estimates of additive genetic variance and breeding value accuracies were similar for AFI and RFI using the numerator and genomic relationship matrices despite fewer animals in the genomic analysis. Bootstrap analyses indicated that 2,500-10,000 markers are required for robust estimation of genomic relationship matrices in cattle. Conclusions This research shows that breeding values and their accuracies may be estimated for commercially important sires for traits recorded in experimental populations without the need for pedigree data to establish identity by descent between members of the commercial and experimental populations when at least 2,500 SNPs are available for the generation of a genomic relationship matrix.

The genomic landscape shaped by selection on transposable elements across 18 mouse strains.

Science.gov (United States)

Nellåker, Christoffer; Keane, Thomas M; Yalcin, Binnaz; Wong, Kim; Agam, Avigail; Belgard, T Grant; Flint, Jonathan; Adams, David J; Frankel, Wayne N; Ponting, Chris P

2012-06-15

Transposable element (TE)-derived sequence dominates the landscape of mammalian genomes and can modulate gene function by dysregulating transcription and translation. Our current knowledge of TEs in laboratory mouse strains is limited primarily to those present in the C57BL/6J reference genome, with most mouse TEs being drawn from three distinct classes, namely short interspersed nuclear elements (SINEs), long interspersed nuclear elements (LINEs) and the endogenous retrovirus (ERV) superfamily. Despite their high prevalence, the different genomic and gene properties controlling whether TEs are preferentially purged from, or are retained by, genetic drift or positive selection in mammalian genomes remain poorly defined. Using whole genome sequencing data from 13 classical laboratory and 4 wild-derived mouse inbred strains, we developed a comprehensive catalogue of 103,798 polymorphic TE variants. We employ this extensive data set to characterize TE variants across the Mus lineage, and to infer neutral and selective processes that have acted over 2 million years. Our results indicate that the majority of TE variants are introduced though the male germline and that only a minority of TE variants exert detectable changes in gene expression. However, among genes with differential expression across the strains there are twice as many TE variants identified as being putative causal variants as expected. Most TE variants that cause gene expression changes appear to be purged rapidly by purifying selection. Our findings demonstrate that past TE insertions have often been highly deleterious, and help to prioritize TE variants according to their likely contribution to gene expression or phenotype variation.

Genomic and environmental selection patterns in two distinct lettuce crop–wild hybrid crosses

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Hartman, Yorike; Uwimana, Brigitte; Hooftman, Danny A P; Schranz, Michael E; van de Wiel, Clemens C M; Smulders, Marinus J M; Visser, Richard G F; van Tienderen, Peter H

2013-01-01

Genomic selection patterns and hybrid performance influence the chance that crop (trans)genes can spread to wild relatives. We measured fitness(-related) traits in two different field environments employing two different crop–wild crosses of lettuce. We performed quantitative trait loci (QTL) analyses and estimated the fitness distribution of early- and late-generation hybrids. We detected consistent results across field sites and crosses for a fitness QTL at linkage group 7, where a selective advantage was conferred by the wild allele. Two fitness QTL were detected on linkage group 5 and 6, which were unique to one of the crop–wild crosses. Average hybrid fitness was lower than the fitness of the wild parent, but several hybrid lineages outperformed the wild parent, especially in a novel habitat for the wild type. In early-generation hybrids, this may partly be due to heterosis effects, whereas in late-generation hybrids transgressive segregation played a major role. The study of genomic selection patterns can identify crop genomic regions under negative selection across multiple environments and cultivar–wild crosses that might be applicable in transgene mitigation strategies. At the same time, results were cultivar-specific, so that a case-by-case environmental risk assessment is still necessary, decreasing its general applicability. PMID:23789025

Genomic and environmental selection patterns in two distinct lettuce crop-wild hybrid crosses.

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Hartman, Yorike; Uwimana, Brigitte; Hooftman, Danny A P; Schranz, Michael E; van de Wiel, Clemens C M; Smulders, Marinus J M; Visser, Richard G F; van Tienderen, Peter H

2013-06-01

Genomic selection patterns and hybrid performance influence the chance that crop (trans)genes can spread to wild relatives. We measured fitness(-related) traits in two different field environments employing two different crop-wild crosses of lettuce. We performed quantitative trait loci (QTL) analyses and estimated the fitness distribution of early- and late-generation hybrids. We detected consistent results across field sites and crosses for a fitness QTL at linkage group 7, where a selective advantage was conferred by the wild allele. Two fitness QTL were detected on linkage group 5 and 6, which were unique to one of the crop-wild crosses. Average hybrid fitness was lower than the fitness of the wild parent, but several hybrid lineages outperformed the wild parent, especially in a novel habitat for the wild type. In early-generation hybrids, this may partly be due to heterosis effects, whereas in late-generation hybrids transgressive segregation played a major role. The study of genomic selection patterns can identify crop genomic regions under negative selection across multiple environments and cultivar-wild crosses that might be applicable in transgene mitigation strategies. At the same time, results were cultivar-specific, so that a case-by-case environmental risk assessment is still necessary, decreasing its general applicability.

Natural selection among Eurasians at genomic regions associated with HIV-1 control

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Allison David B

2011-06-01

Full Text Available Abstract Background HIV susceptibility and pathogenicity exhibit both interindividual and intergroup variability. The etiology of intergroup variability is still poorly understood, and could be partly linked to genetic differences among racial/ethnic groups. These genetic differences may be traceable to different regimes of natural selection in the 60,000 years since the human radiation out of Africa. Here, we examine population differentiation and haplotype patterns at several loci identified through genome-wide association studies on HIV-1 control, as determined by viral-load setpoint, in European and African-American populations. We use genome-wide data from the Human Genome Diversity Project, consisting of 53 world-wide populations, to compare measures of FST and relative extended haplotype homozygosity (REHH at these candidate loci to the rest of the respective chromosome. Results We find that the Europe-Middle East and Europe-South Asia pairwise FST in the most strongly associated region are elevated compared to most pairwise comparisons with the sub-Saharan African group, which exhibit very low FST. We also find genetic signatures of recent positive selection (higher REHH at these associated regions among all groups except for sub-Saharan Africans and Native Americans. This pattern is consistent with one in which genetic differentiation, possibly due to diversifying/positive selection, occurred at these loci among Eurasians. Conclusions These findings are concordant with those from earlier studies suggesting recent evolutionary change at immunity-related genomic regions among Europeans, and shed light on the potential genetic and evolutionary origin of population differences in HIV-1 control.

Landscape genomics: natural selection drives the evolution of mitogenome in penguins.

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Ramos, Barbara; González-Acuña, Daniel; Loyola, David E; Johnson, Warren E; Parker, Patricia G; Massaro, Melanie; Dantas, Gisele P M; Miranda, Marcelo D; Vianna, Juliana A

2018-01-16

Mitochondria play a key role in the balance of energy and heat production, and therefore the mitochondrial genome is under natural selection by environmental temperature and food availability, since starvation can generate more efficient coupling of energy production. However, selection over mitochondrial DNA (mtDNA) genes has usually been evaluated at the population level. We sequenced by NGS 12 mitogenomes and with four published genomes, assessed genetic variation in ten penguin species distributed from the equator to Antarctica. Signatures of selection of 13 mitochondrial protein-coding genes were evaluated by comparing among species within and among genera (Spheniscus, Pygoscelis, Eudyptula, Eudyptes and Aptenodytes). The genetic data were correlated with environmental data obtained through remote sensing (sea surface temperature [SST], chlorophyll levels [Chl] and a combination of SST and Chl [COM]) through the distribution of these species. We identified the complete mtDNA genomes of several penguin species, including ND6 and 8 tRNAs on the light strand and 12 protein coding genes, 14 tRNAs and two rRNAs positioned on the heavy strand. The highest diversity was found in NADH dehydrogenase genes and the lowest in COX genes. The lowest evolutionary divergence among species was between Humboldt (Spheniscus humboldti) and Galapagos (S. mendiculus) penguins (0.004), while the highest was observed between little penguin (Eudyptula minor) and Adélie penguin (Pygoscelis adeliae) (0.097). We identified a signature of purifying selection (Ka/Ks penguins. In contrast, COX1 had a signature of strong negative selection. ND4 Ka/Ks ratios were highly correlated with SST (Mantel, p-value: 0.0001; GLM, p-value: 0.00001) and thus may be related to climate adaptation throughout penguin speciation. These results identify mtDNA candidate genes under selection which could be involved in broad-scale adaptations of penguins to their environment. Such knowledge may be

Genome characterization of the selected long- and short-sleep mouse lines.

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Dowell, Robin; Odell, Aaron; Richmond, Phillip; Malmer, Daniel; Halper-Stromberg, Eitan; Bennett, Beth; Larson, Colin; Leach, Sonia; Radcliffe, Richard A

2016-12-01

The Inbred Long- and Short-Sleep (ILS, ISS) mouse lines were selected for differences in acute ethanol sensitivity using the loss of righting response (LORR) as the selection trait. The lines show an over tenfold difference in LORR and, along with a recombinant inbred panel derived from them (the LXS), have been widely used to dissect the genetic underpinnings of acute ethanol sensitivity. Here we have sequenced the genomes of the ILS and ISS to investigate the DNA variants that contribute to their sensitivity difference. We identified ~2.7 million high-confidence SNPs and small indels and ~7000 structural variants between the lines; variants were found to occur in 6382 annotated genes. Using a hidden Markov model, we were able to reconstruct the genome-wide ancestry patterns of the eight inbred progenitor strains from which the ILS and ISS were derived, and found that quantitative trait loci that have been mapped for LORR were slightly enriched for DNA variants. Finally, by mapping and quantifying RNA-seq reads from the ILS and ISS to their strain-specific genomes rather than to the reference genome, we found a substantial improvement in a differential expression analysis between the lines. This work will help in identifying and characterizing the DNA sequence variants that contribute to the difference in ethanol sensitivity between the ILS and ISS and will also aid in accurate quantification of RNA-seq data generated from the LXS RIs.

Genome-wide prediction of traits with different genetic architecture through efficient variable selection.

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Wimmer, Valentin; Lehermeier, Christina; Albrecht, Theresa; Auinger, Hans-Jürgen; Wang, Yu; Schön, Chris-Carolin

2013-10-01

In genome-based prediction there is considerable uncertainty about the statistical model and method required to maximize prediction accuracy. For traits influenced by a small number of quantitative trait loci (QTL), predictions are expected to benefit from methods performing variable selection [e.g., BayesB or the least absolute shrinkage and selection operator (LASSO)] compared to methods distributing effects across the genome [ridge regression best linear unbiased prediction (RR-BLUP)]. We investigate the assumptions underlying successful variable selection by combining computer simulations with large-scale experimental data sets from rice (Oryza sativa L.), wheat (Triticum aestivum L.), and Arabidopsis thaliana (L.). We demonstrate that variable selection can be successful when the number of phenotyped individuals is much larger than the number of causal mutations contributing to the trait. We show that the sample size required for efficient variable selection increases dramatically with decreasing trait heritabilities and increasing extent of linkage disequilibrium (LD). We contrast and discuss contradictory results from simulation and experimental studies with respect to superiority of variable selection methods over RR-BLUP. Our results demonstrate that due to long-range LD, medium heritabilities, and small sample sizes, superiority of variable selection methods cannot be expected in plant breeding populations even for traits like FRIGIDA gene expression in Arabidopsis and flowering time in rice, assumed to be influenced by a few major QTL. We extend our conclusions to the analysis of whole-genome sequence data and infer upper bounds for the number of causal mutations which can be identified by LASSO. Our results have major impact on the choice of statistical method needed to make credible inferences about genetic architecture and prediction accuracy of complex traits.

Genetic improvement of Pacific white shrimp (Penaeus (Litopenaeus vannamei: perspectives for genomic selection

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Héctor eCastillo-Juárez

2015-03-01

Full Text Available The use of breeding programs for the Pacific white shrimp (Penaeus (Litopenaeus vannamei based on mixed linear models with pedigreed data are described. The application of these classic breeding methods yielded continuous progress of great value to increase the profitability of the shrimp industry in several countries. Recent advances in such areas as genomics in shrimp will allow for the development of new breeding programs in the near future that will increase genetic progress. In particular, these novel techniques may help increase disease resistance to specific emerging diseases, which is today a very important component of shrimp breeding programs. Thanks to increased selection accuracy, simulated genetic advance using genomic selection for survival to a disease challenge was up to 2.6 times that of phenotypic sib selection.

The role of parasite-driven selection in shaping landscape genomic structure in red grouse (Lagopus lagopus scotica).

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Wenzel, Marius A; Douglas, Alex; James, Marianne C; Redpath, Steve M; Piertney, Stuart B

2016-01-01

Landscape genomics promises to provide novel insights into how neutral and adaptive processes shape genome-wide variation within and among populations. However, there has been little emphasis on examining whether individual-based phenotype-genotype relationships derived from approaches such as genome-wide association (GWAS) manifest themselves as a population-level signature of selection in a landscape context. The two may prove irreconcilable as individual-level patterns become diluted by high levels of gene flow and complex phenotypic or environmental heterogeneity. We illustrate this issue with a case study that examines the role of the highly prevalent gastrointestinal nematode Trichostrongylus tenuis in shaping genomic signatures of selection in red grouse (Lagopus lagopus scotica). Individual-level GWAS involving 384 SNPs has previously identified five SNPs that explain variation in T. tenuis burden. Here, we examine whether these same SNPs display population-level relationships between T. tenuis burden and genetic structure across a small-scale landscape of 21 sites with heterogeneous parasite pressure. Moreover, we identify adaptive SNPs showing signatures of directional selection using F(ST) outlier analysis and relate population- and individual-level patterns of multilocus neutral and adaptive genetic structure to T. tenuis burden. The five candidate SNPs for parasite-driven selection were neither associated with T. tenuis burden on a population level, nor under directional selection. Similarly, there was no evidence of parasite-driven selection in SNPs identified as candidates for directional selection. We discuss these results in the context of red grouse ecology and highlight the broader consequences for the utility of landscape genomics approaches for identifying signatures of selection. © 2015 John Wiley & Sons Ltd.

Natural Selection and Recombination Rate Variation Shape Nucleotide Polymorphism Across the Genomes of Three Related Populus Species.

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Wang, Jing; Street, Nathaniel R; Scofield, Douglas G; Ingvarsson, Pär K

2016-03-01

A central aim of evolutionary genomics is to identify the relative roles that various evolutionary forces have played in generating and shaping genetic variation within and among species. Here we use whole-genome resequencing data to characterize and compare genome-wide patterns of nucleotide polymorphism, site frequency spectrum, and population-scaled recombination rates in three species of Populus: Populus tremula, P. tremuloides, and P. trichocarpa. We find that P. tremuloides has the highest level of genome-wide variation, skewed allele frequencies, and population-scaled recombination rates, whereas P. trichocarpa harbors the lowest. Our findings highlight multiple lines of evidence suggesting that natural selection, due to both purifying and positive selection, has widely shaped patterns of nucleotide polymorphism at linked neutral sites in all three species. Differences in effective population sizes and rates of recombination largely explain the disparate magnitudes and signatures of linked selection that we observe among species. The present work provides the first phylogenetic comparative study on a genome-wide scale in forest trees. This information will also improve our ability to understand how various evolutionary forces have interacted to influence genome evolution among related species. Copyright © 2016 by the Genetics Society of America.

Both selective and neutral processes drive GC content evolution in the human genome

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Cagliani Rachele

2008-03-01

Full Text Available Abstract Background Mammalian genomes consist of regions differing in GC content, referred to as isochores or GC-content domains. The scientific debate is still open as to whether such compositional heterogeneity is a selected or neutral trait. Results Here we analyze SNP allele frequencies, retrotransposon insertion polymorphisms (RIPs, as well as fixed substitutions accumulated in the human lineage since its divergence from chimpanzee to indicate that biased gene conversion (BGC has been playing a role in within-genome GC content variation. Yet, a distinct contribution to GC content evolution is accounted for by a selective process. Accordingly, we searched for independent evidences that GC content distribution does not conform to neutral expectations. Indeed, after correcting for possible biases, we show that intron GC content and size display isochore-specific correlations. Conclusion We consider that the more parsimonious explanation for our results is that GC content is subjected to the action of both weak selection and BGC in the human genome with features such as nucleosome positioning or chromatin conformation possibly representing the final target of selective processes. This view might reconcile previous contrasting findings and add some theoretical background to recent evidences suggesting that GC content domains display different behaviors with respect to highly regulated biological processes such as developmentally-stage related gene expression and programmed replication timing during neural stem cell differentiation.

Genomic regions under selection in crop-wild hybrids of lettuce: implications for crop breeding and environmental risk assessment

NARCIS (Netherlands)

Hartman, Y.

2012-01-01

The results of this thesis show that the probability of introgression of a putative transgene to wild relatives indeed depends strongly on the insertion location of the transgene. The study of genomic selection patterns can identify crop genomic regions under negative selection in multiple

Selection for silage yield and composition did not affect genomic diversity within the Wisconsin Quality Synthetic maize population.

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Lorenz, Aaron J; Beissinger, Timothy M; Silva, Renato Rodrigues; de Leon, Natalia

2015-02-02

Maize silage is forage of high quality and yield, and represents the second most important use of maize in the United States. The Wisconsin Quality Synthetic (WQS) maize population has undergone five cycles of recurrent selection for silage yield and composition, resulting in a genetically improved population. The application of high-density molecular markers allows breeders and geneticists to identify important loci through association analysis and selection mapping, as well as to monitor changes in the distribution of genetic diversity across the genome. The objectives of this study were to identify loci controlling variation for maize silage traits through association analysis and the assessment of selection signatures and to describe changes in the genomic distribution of gene diversity through selection and genetic drift in the WQS recurrent selection program. We failed to find any significant marker-trait associations using the historical phenotypic data from WQS breeding trials combined with 17,719 high-quality, informative single nucleotide polymorphisms. Likewise, no strong genomic signatures were left by selection on silage yield and quality in the WQS despite genetic gain for these traits. These results could be due to the genetic complexity underlying these traits, or the role of selection on standing genetic variation. Variation in loss of diversity through drift was observed across the genome. Some large regions experienced much greater loss in diversity than what is expected, suggesting limited recombination combined with small populations in recurrent selection programs could easily lead to fixation of large swaths of the genome. Copyright © 2015 Lorenz et al.

Nuclease Target Site Selection for Maximizing On-target Activity and Minimizing Off-target Effects in Genome Editing

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Lee, Ciaran M; Cradick, Thomas J; Fine, Eli J; Bao, Gang

2016-01-01

The rapid advancement in targeted genome editing using engineered nucleases such as ZFNs, TALENs, and CRISPR/Cas9 systems has resulted in a suite of powerful methods that allows researchers to target any genomic locus of interest. A complementary set of design tools has been developed to aid researchers with nuclease design, target site selection, and experimental validation. Here, we review the various tools available for target selection in designing engineered nucleases, and for quantifying nuclease activity and specificity, including web-based search tools and experimental methods. We also elucidate challenges in target selection, especially in predicting off-target effects, and discuss future directions in precision genome editing and its applications. PMID:26750397

Analysis of adaptive evolution in Lyssavirus genomes reveals pervasive diversifying selection during species diversification.

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Voloch, Carolina M; Capellão, Renata T; Mello, Beatriz; Schrago, Carlos G

2014-11-19

Lyssavirus is a diverse genus of viruses that infect a variety of mammalian hosts, typically causing encephalitis. The evolution of this lineage, particularly the rabies virus, has been a focus of research because of the extensive occurrence of cross-species transmission, and the distinctive geographical patterns present throughout the diversification of these viruses. Although numerous studies have examined pattern-related questions concerning Lyssavirus evolution, analyses of the evolutionary processes acting on Lyssavirus diversification are scarce. To clarify the relevance of positive natural selection in Lyssavirus diversification, we conducted a comprehensive scan for episodic diversifying selection across all lineages and codon sites of the five coding regions in lyssavirus genomes. Although the genomes of these viruses are generally conserved, the glycoprotein (G), RNA-dependent RNA polymerase (L) and polymerase (P) genes were frequently targets of adaptive evolution during the diversification of the genus. Adaptive evolution is particularly manifest in the glycoprotein gene, which was inferred to have experienced the highest density of positively selected codon sites along branches. Substitutions in the L gene were found to be associated with the early diversification of phylogroups. A comparison between the number of positively selected sites inferred along the branches of RABV population branches and Lyssavirus intespecies branches suggested that the occurrence of positive selection was similar on the five coding regions of the genome in both groups.

Analysis of Adaptive Evolution in Lyssavirus Genomes Reveals Pervasive Diversifying Selection during Species Diversification

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Carolina M. Voloch

2014-11-01

Full Text Available Lyssavirus is a diverse genus of viruses that infect a variety of mammalian hosts, typically causing encephalitis. The evolution of this lineage, particularly the rabies virus, has been a focus of research because of the extensive occurrence of cross-species transmission, and the distinctive geographical patterns present throughout the diversification of these viruses. Although numerous studies have examined pattern-related questions concerning Lyssavirus evolution, analyses of the evolutionary processes acting on Lyssavirus diversification are scarce. To clarify the relevance of positive natural selection in Lyssavirus diversification, we conducted a comprehensive scan for episodic diversifying selection across all lineages and codon sites of the five coding regions in lyssavirus genomes. Although the genomes of these viruses are generally conserved, the glycoprotein (G, RNA-dependent RNA polymerase (L and polymerase (P genes were frequently targets of adaptive evolution during the diversification of the genus. Adaptive evolution is particularly manifest in the glycoprotein gene, which was inferred to have experienced the highest density of positively selected codon sites along branches. Substitutions in the L gene were found to be associated with the early diversification of phylogroups. A comparison between the number of positively selected sites inferred along the branches of RABV population branches and Lyssavirus intespecies branches suggested that the occurrence of positive selection was similar on the five coding regions of the genome in both groups.

Genomic selection to improve livestock production in developing countries with a focus on India

DEFF Research Database (Denmark)

Kadarmideen, Haja; Do, Duy Ngoc

2015-01-01

growth will increase the demand for food as well as animal products, particularly in emerging economic giants like India. Moreover, the urbanization has considerable impact on patterns of food consumption in general and on demand for livestock products, in particular and the increased income growth led......Global livestock production has increased substantially during the last decades, in both number of animals and productivity. Meanwhile, the human population is projected to reach 9.6 billions by 2050 and most of the increase in the projection takes place in developing countries. Rapid population...... production (OPU-IVP) of embryos will have a considerable impact in the future. This paper attempts to provide basic concepts of using genomic tools for livestock production with the focus on genomic prediction and selection methods and discuss about the potential application of genomic selection to increase...

Signatures of Selection in the Genomes of Commercial and Non-Commercial Chicken Breeds

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Elferink, Martin G.; Megens, Hendrik-Jan; Vereijken, Addie; Hu, Xiaoxiang; Crooijmans, Richard P. M. A.; Groenen, Martien A. M.

2012-01-01

Identifying genomics regions that are affected by selection is important to understand the domestication and selection history of the domesticated chicken, as well as understanding molecular pathways underlying phenotypic traits and breeding goals. While whole-genome approaches, either high-density SNP chips or massively parallel sequencing, have been successfully applied to identify evidence for selective sweeps in chicken, it has been difficult to distinguish patterns of selection and stochastic and breed specific effects. Here we present a study to identify selective sweeps in a large number of chicken breeds (67 in total) using a high-density (58 K) SNP chip. We analyzed commercial chickens representing all major breeding goals. In addition, we analyzed non-commercial chicken diversity for almost all recognized traditional Dutch breeds and a selection of representative breeds from China. Based on their shared history or breeding goal we in silico grouped the breeds into 14 breed groups. We identified 396 chromosomal regions that show suggestive evidence of selection in at least one breed group with 26 of these regions showing strong evidence of selection. Of these 26 regions, 13 were previously described and 13 yield new candidate genes for performance traits in chicken. Our approach demonstrates the strength of including many different populations with similar, and breed groups with different selection histories to reduce stochastic effects based on single populations. PMID:22384281

Selective recruitment of nuclear factors to productively replicating herpes simplex virus genomes.

Science.gov (United States)

Dembowski, Jill A; DeLuca, Neal A

2015-05-01

Much of the HSV-1 life cycle is carried out in the cell nucleus, including the expression, replication, repair, and packaging of viral genomes. Viral proteins, as well as cellular factors, play essential roles in these processes. Isolation of proteins on nascent DNA (iPOND) was developed to label and purify cellular replication forks. We adapted aspects of this method to label viral genomes to both image, and purify replicating HSV-1 genomes for the identification of associated proteins. Many viral and cellular factors were enriched on viral genomes, including factors that mediate DNA replication, repair, chromatin remodeling, transcription, and RNA processing. As infection proceeded, packaging and structural components were enriched to a greater extent. Among the more abundant proteins that copurified with genomes were the viral transcription factor ICP4 and the replication protein ICP8. Furthermore, all seven viral replication proteins were enriched on viral genomes, along with cellular PCNA and topoisomerases, while other cellular replication proteins were not detected. The chromatin-remodeling complexes present on viral genomes included the INO80, SWI/SNF, NURD, and FACT complexes, which may prevent chromatinization of the genome. Consistent with this conclusion, histones were not readily recovered with purified viral genomes, and imaging studies revealed an underrepresentation of histones on viral genomes. RNA polymerase II, the mediator complex, TFIID, TFIIH, and several other transcriptional activators and repressors were also affinity purified with viral DNA. The presence of INO80, NURD, SWI/SNF, mediator, TFIID, and TFIIH components is consistent with previous studies in which these complexes copurified with ICP4. Therefore, ICP4 is likely involved in the recruitment of these key cellular chromatin remodeling and transcription factors to viral genomes. Taken together, iPOND is a valuable method for the study of viral genome dynamics during infection and

Comparing strategies for selection of low-density SNPs for imputation-mediated genomic prediction in U. S. Holsteins.

Science.gov (United States)

He, Jun; Xu, Jiaqi; Wu, Xiao-Lin; Bauck, Stewart; Lee, Jungjae; Morota, Gota; Kachman, Stephen D; Spangler, Matthew L

2018-04-01

SNP chips are commonly used for genotyping animals in genomic selection but strategies for selecting low-density (LD) SNPs for imputation-mediated genomic selection have not been addressed adequately. The main purpose of the present study was to compare the performance of eight LD (6K) SNP panels, each selected by a different strategy exploiting a combination of three major factors: evenly-spaced SNPs, increased minor allele frequencies, and SNP-trait associations either for single traits independently or for all the three traits jointly. The imputation accuracies from 6K to 80K SNP genotypes were between 96.2 and 98.2%. Genomic prediction accuracies obtained using imputed 80K genotypes were between 0.817 and 0.821 for daughter pregnancy rate, between 0.838 and 0.844 for fat yield, and between 0.850 and 0.863 for milk yield. The two SNP panels optimized on the three major factors had the highest genomic prediction accuracy (0.821-0.863), and these accuracies were very close to those obtained using observed 80K genotypes (0.825-0.868). Further exploration of the underlying relationships showed that genomic prediction accuracies did not respond linearly to imputation accuracies, but were significantly affected by genotype (imputation) errors of SNPs in association with the traits to be predicted. SNPs optimal for map coverage and MAF were favorable for obtaining accurate imputation of genotypes whereas trait-associated SNPs improved genomic prediction accuracies. Thus, optimal LD SNP panels were the ones that combined both strengths. The present results have practical implications on the design of LD SNP chips for imputation-enabled genomic prediction.

A genomic portrait of haplotype diversity and signatures of selection in indigenous southern African populations.

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Emile R Chimusa

2015-03-01

Full Text Available We report a study of genome-wide, dense SNP (∼ 900K and copy number polymorphism data of indigenous southern Africans. We demonstrate the genetic contribution to southern and eastern African populations, which involved admixture between indigenous San, Niger-Congo-speaking and populations of Eurasian ancestry. This finding illustrates the need to account for stratification in genome-wide association studies, and that admixture mapping would likely be a successful approach in these populations. We developed a strategy to detect the signature of selection prior to and following putative admixture events. Several genomic regions show an unusual excess of Niger-Kordofanian, and unusual deficiency of both San and Eurasian ancestry, which were considered the footprints of selection after population admixture. Several SNPs with strong allele frequency differences were observed predominantly between the admixed indigenous southern African populations, and their ancestral Eurasian populations. Interestingly, many candidate genes, which were identified within the genomic regions showing signals for selection, were associated with southern African-specific high-risk, mostly communicable diseases, such as malaria, influenza, tuberculosis, and human immunodeficiency virus/AIDs. This observation suggests a potentially important role that these genes might have played in adapting to the environment. Additionally, our analyses of haplotype structure, linkage disequilibrium, recombination, copy number variation and genome-wide admixture highlight, and support the unique position of San relative to both African and non-African populations. This study contributes to a better understanding of population ancestry and selection in south-eastern African populations; and the data and results obtained will support research into the genetic contributions to infectious as well as non-communicable diseases in the region.

A genomic portrait of haplotype diversity and signatures of selection in indigenous southern African populations.

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Chimusa, Emile R; Meintjies, Ayton; Tchanga, Milaine; Mulder, Nicola; Seoighe, Cathal; Seioghe, Cathal; Soodyall, Himla; Ramesar, Rajkumar

2015-03-01

We report a study of genome-wide, dense SNP (∼ 900K) and copy number polymorphism data of indigenous southern Africans. We demonstrate the genetic contribution to southern and eastern African populations, which involved admixture between indigenous San, Niger-Congo-speaking and populations of Eurasian ancestry. This finding illustrates the need to account for stratification in genome-wide association studies, and that admixture mapping would likely be a successful approach in these populations. We developed a strategy to detect the signature of selection prior to and following putative admixture events. Several genomic regions show an unusual excess of Niger-Kordofanian, and unusual deficiency of both San and Eurasian ancestry, which were considered the footprints of selection after population admixture. Several SNPs with strong allele frequency differences were observed predominantly between the admixed indigenous southern African populations, and their ancestral Eurasian populations. Interestingly, many candidate genes, which were identified within the genomic regions showing signals for selection, were associated with southern African-specific high-risk, mostly communicable diseases, such as malaria, influenza, tuberculosis, and human immunodeficiency virus/AIDs. This observation suggests a potentially important role that these genes might have played in adapting to the environment. Additionally, our analyses of haplotype structure, linkage disequilibrium, recombination, copy number variation and genome-wide admixture highlight, and support the unique position of San relative to both African and non-African populations. This study contributes to a better understanding of population ancestry and selection in south-eastern African populations; and the data and results obtained will support research into the genetic contributions to infectious as well as non-communicable diseases in the region.

Genomic selection in plant breeding: from theory to practice.

Science.gov (United States)

Jannink, Jean-Luc; Lorenz, Aaron J; Iwata, Hiroyoshi

2010-03-01

We intuitively believe that the dramatic drop in the cost of DNA marker information we have experienced should have immediate benefits in accelerating the delivery of crop varieties with improved yield, quality and biotic and abiotic stress tolerance. But these traits are complex and affected by many genes, each with small effect. Traditional marker-assisted selection has been ineffective for such traits. The introduction of genomic selection (GS), however, has shifted that paradigm. Rather than seeking to identify individual loci significantly associated with a trait, GS uses all marker data as predictors of performance and consequently delivers more accurate predictions. Selection can be based on GS predictions, potentially leading to more rapid and lower cost gains from breeding. The objectives of this article are to review essential aspects of GS and summarize the important take-home messages from recent theoretical, simulation and empirical studies. We then look forward and consider research needs surrounding methodological questions and the implications of GS for long-term selection.

Inhibitory effect of etodolac, a selective cyclooxygenase-2 inhibitor, on stomach carcinogenesis in Helicobacter pylori-infected Mongolian gerbils

International Nuclear Information System (INIS)

Magari, Hirohito; Shimizu, Yasuhito; Inada, Ken-ichi; Enomoto, Shotaro; Tomeki, Tatsuji; Yanaoka, Kimihiko; Tamai, Hideyuki; Arii, Kenji; Nakata, Hiroya; Oka, Masashi; Utsunomiya, Hirotoshi; Tsutsumi, Yutaka; Tsukamoto, Tetsuya; Tatematsu, Masae; Ichinose, Masao

2005-01-01

The effect of the selective COX-2 inhibitor, etodolac, on Helicobacter pylori (Hp)-associated stomach carcinogenesis was investigated in Mongolian gerbils (MGs). Hp-infected MGs were fed for 23 weeks with drinking water containing 10 ppm N-methyl-N-nitrosourea. They were then switched to distilled water and placed on a diet containing 5-30 mg/kg/day etodolac for 30 weeks. We found that etodolac dose-dependently inhibited the development of gastric cancer, and no cancer was detected at a dose of 30 mg/kg/day. Etodolac did not affect the extent of inflammatory cell infiltration or oxidative DNA damage, but it significantly inhibited mucosal cell proliferation and dose-dependently repressed the development of intestinal metaplasia in the stomachs of Hp-infected MGs. These results suggest that COX-2 is a key molecule in inflammation-mediated stomach carcinogenesis and that chemoprevention of stomach cancer should be possible by controlling COX-2 expression or activity

Genomic selection using indicator traits to reduce the environmental impact of milk production

DEFF Research Database (Denmark)

Hansen Axelsson, H; Fikse, W F; Kargo, Morten

2013-01-01

The aim of this simulation study was to test the hypothesis that phenotype information of specific indicator traits of environmental importance recorded on a small-scale can be implemented in breeding schemes with genomic selection to reduce the environmental impact of milk production. A stochastic...... was, however, best in the scenarios where the genetic correlation between IT and EI was ≥0.30 and the accuracy of direct genomic value was ≥0.40. The genetic gain in EI was 26 to 34% higher when indicator traits such as greenhouse gases in the breath of the cow and methane recorded in respiration...... of direct genomic values will be reasonably high...

SNP Discovery for mapping alien introgressions in wheat

Science.gov (United States)

2014-01-01

Background Monitoring alien introgressions in crop plants is difficult due to the lack of genetic and molecular mapping information on the wild crop relatives. The tertiary gene pool of wheat is a very important source of genetic variability for wheat improvement against biotic and abiotic stresses. By exploring the 5Mg short arm (5MgS) of Aegilops geniculata, we can apply chromosome genomics for the discovery of SNP markers and their use for monitoring alien introgressions in wheat (Triticum aestivum L). Results The short arm of chromosome 5Mg of Ae. geniculata Roth (syn. Ae. ovata L.; 2n = 4x = 28, UgUgMgMg) was flow-sorted from a wheat line in which it is maintained as a telocentric chromosome. DNA of the sorted arm was amplified and sequenced using an Illumina Hiseq 2000 with ~45x coverage. The sequence data was used for SNP discovery against wheat homoeologous group-5 assemblies. A total of 2,178 unique, 5MgS-specific SNPs were discovered. Randomly selected samples of 59 5MgS-specific SNPs were tested (44 by KASPar assay and 15 by Sanger sequencing) and 84% were validated. Of the selected SNPs, 97% mapped to a chromosome 5Mg addition to wheat (the source of t5MgS), and 94% to 5Mg introgressed from a different accession of Ae. geniculata substituting for chromosome 5D of wheat. The validated SNPs also identified chromosome segments of 5MgS origin in a set of T5D-5Mg translocation lines; eight SNPs (25%) mapped to TA5601 [T5DL · 5DS-5MgS(0.75)] and three (8%) to TA5602 [T5DL · 5DS-5MgS (0.95)]. SNPs (gsnp_5ms83 and gsnp_5ms94), tagging chromosome T5DL · 5DS-5MgS(0.95) with the smallest introgression carrying resistance to leaf rust (Lr57) and stripe rust (Yr40), were validated in two released germplasm lines with Lr57 and Yr40 genes. Conclusion This approach should be widely applicable for the identification of species/genome-specific SNPs. The development of a large number of SNP markers will facilitate the precise introgression and

SNP Discovery for mapping alien introgressions in wheat.

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Tiwari, Vijay K; Wang, Shichen; Sehgal, Sunish; Vrána, Jan; Friebe, Bernd; Kubaláková, Marie; Chhuneja, Praveen; Doležel, Jaroslav; Akhunov, Eduard; Kalia, Bhanu; Sabir, Jamal; Gill, Bikram S

2014-04-10

Monitoring alien introgressions in crop plants is difficult due to the lack of genetic and molecular mapping information on the wild crop relatives. The tertiary gene pool of wheat is a very important source of genetic variability for wheat improvement against biotic and abiotic stresses. By exploring the 5Mg short arm (5MgS) of Aegilops geniculata, we can apply chromosome genomics for the discovery of SNP markers and their use for monitoring alien introgressions in wheat (Triticum aestivum L). The short arm of chromosome 5Mg of Ae. geniculata Roth (syn. Ae. ovata L.; 2n = 4x = 28, UgUgMgMg) was flow-sorted from a wheat line in which it is maintained as a telocentric chromosome. DNA of the sorted arm was amplified and sequenced using an Illumina Hiseq 2000 with ~45x coverage. The sequence data was used for SNP discovery against wheat homoeologous group-5 assemblies. A total of 2,178 unique, 5MgS-specific SNPs were discovered. Randomly selected samples of 59 5MgS-specific SNPs were tested (44 by KASPar assay and 15 by Sanger sequencing) and 84% were validated. Of the selected SNPs, 97% mapped to a chromosome 5Mg addition to wheat (the source of t5MgS), and 94% to 5Mg introgressed from a different accession of Ae. geniculata substituting for chromosome 5D of wheat. The validated SNPs also identified chromosome segments of 5MgS origin in a set of T5D-5Mg translocation lines; eight SNPs (25%) mapped to TA5601 [T5DL · 5DS-5MgS(0.75)] and three (8%) to TA5602 [T5DL · 5DS-5MgS (0.95)]. SNPs (gsnp_5ms83 and gsnp_5ms94), tagging chromosome T5DL · 5DS-5MgS(0.95) with the smallest introgression carrying resistance to leaf rust (Lr57) and stripe rust (Yr40), were validated in two released germplasm lines with Lr57 and Yr40 genes. This approach should be widely applicable for the identification of species/genome-specific SNPs. The development of a large number of SNP markers will facilitate the precise introgression and monitoring of alien segments in crop

Comparison of genome-wide selection strategies to identify furfural tolerance genes in Escherichia coli.

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Glebes, Tirzah Y; Sandoval, Nicholas R; Gillis, Jacob H; Gill, Ryan T

2015-01-01

Engineering both feedstock and product tolerance is important for transitioning towards next-generation biofuels derived from renewable sources. Tolerance to chemical inhibitors typically results in complex phenotypes, for which multiple genetic changes must often be made to confer tolerance. Here, we performed a genome-wide search for furfural-tolerant alleles using the TRackable Multiplex Recombineering (TRMR) method (Warner et al. (2010), Nature Biotechnology), which uses chromosomally integrated mutations directed towards increased or decreased expression of virtually every gene in Escherichia coli. We employed various growth selection strategies to assess the role of selection design towards growth enrichments. We also compared genes with increased fitness from our TRMR selection to those from a previously reported genome-wide identification study of furfural tolerance genes using a plasmid-based genomic library approach (Glebes et al. (2014) PLOS ONE). In several cases, growth improvements were observed for the chromosomally integrated promoter/RBS mutations but not for the plasmid-based overexpression constructs. Through this assessment, four novel tolerance genes, ahpC, yhjH, rna, and dicA, were identified and confirmed for their effect on improving growth in the presence of furfural. © 2014 Wiley Periodicals, Inc.

Relaxation of selective constraints causes independent selenoprotein extinction in insect genomes.

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Charles E Chapple

Full Text Available BACKGROUND: Selenoproteins are a diverse family of proteins notable for the presence of the 21st amino acid, selenocysteine. Until very recently, all metazoan genomes investigated encoded selenoproteins, and these proteins had therefore been believed to be essential for animal life. Challenging this assumption, recent comparative analyses of insect genomes have revealed that some insect genomes appear to have lost selenoprotein genes. METHODOLOGY/PRINCIPAL FINDINGS: In this paper we investigate in detail the fate of selenoproteins, and that of selenoprotein factors, in all available arthropod genomes. We use a variety of in silico comparative genomics approaches to look for known selenoprotein genes and factors involved in selenoprotein biosynthesis. We have found that five insect species have completely lost the ability to encode selenoproteins and that selenoprotein loss in these species, although so far confined to the Endopterygota infraclass, cannot be attributed to a single evolutionary event, but rather to multiple, independent events. Loss of selenoproteins and selenoprotein factors is usually coupled to the deletion of the entire no-longer functional genomic region, rather than to sequence degradation and consequent pseudogenisation. Such dynamics of gene extinction are consistent with the high rate of genome rearrangements observed in Drosophila. We have also found that, while many selenoprotein factors are concomitantly lost with the selenoproteins, others are present and conserved in all investigated genomes, irrespective of whether they code for selenoproteins or not, suggesting that they are involved in additional, non-selenoprotein related functions. CONCLUSIONS/SIGNIFICANCE: Selenoproteins have been independently lost in several insect species, possibly as a consequence of the relaxation in insects of the selective constraints acting across metazoans to maintain selenoproteins. The dispensability of selenoproteins in insects may

On causal roles and selected effects: our genome is mostly junk.

Science.gov (United States)

Doolittle, W Ford; Brunet, Tyler D P

2017-12-05

The idea that much of our genome is irrelevant to fitness-is not the product of positive natural selection at the organismal level-remains viable. Claims to the contrary, and specifically that the notion of "junk DNA" should be abandoned, are based on conflating meanings of the word "function". Recent estimates suggest that perhaps 90% of our DNA, though biochemically active, does not contribute to fitness in any sequence-dependent way, and possibly in no way at all. Comparisons to vertebrates with much larger and smaller genomes (the lungfish and the pufferfish) strongly align with such a conclusion, as they have done for the last half-century.

Efficient Breeding by Genomic Mating.

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Akdemir, Deniz; Sánchez, Julio I

2016-01-01

Selection in breeding programs can be done by using phenotypes (phenotypic selection), pedigree relationship (breeding value selection) or molecular markers (marker assisted selection or genomic selection). All these methods are based on truncation selection, focusing on the best performance of parents before mating. In this article we proposed an approach to breeding, named genomic mating, which focuses on mating instead of truncation selection. Genomic mating uses information in a similar fashion to genomic selection but includes information on complementation of parents to be mated. Following the efficiency frontier surface, genomic mating uses concepts of estimated breeding values, risk (usefulness) and coefficient of ancestry to optimize mating between parents. We used a genetic algorithm to find solutions to this optimization problem and the results from our simulations comparing genomic selection, phenotypic selection and the mating approach indicate that current approach for breeding complex traits is more favorable than phenotypic and genomic selection. Genomic mating is similar to genomic selection in terms of estimating marker effects, but in genomic mating the genetic information and the estimated marker effects are used to decide which genotypes should be crossed to obtain the next breeding population.

Optimizing the allocation of resources for genomic selection in one breeding cycle.

Science.gov (United States)

Riedelsheimer, Christian; Melchinger, Albrecht E

2013-11-01

We developed a universally applicable planning tool for optimizing the allocation of resources for one cycle of genomic selection in a biparental population. The framework combines selection theory with constraint numerical optimization and considers genotype  ×  environment interactions. Genomic selection (GS) is increasingly implemented in plant breeding programs to increase selection gain but little is known how to optimally allocate the resources under a given budget. We investigated this problem with model calculations by combining quantitative genetic selection theory with constraint numerical optimization. We assumed one selection cycle where both the training and prediction sets comprised double haploid (DH) lines from the same biparental population. Grain yield for testcrosses of maize DH lines was used as a model trait but all parameters can be adjusted in a freely available software implementation. An extension of the expected selection accuracy given by Daetwyler et al. (2008) was developed to correctly balance between the number of environments for phenotyping the training set and its population size in the presence of genotype × environment interactions. Under small budget, genotyping costs mainly determine whether GS is superior over phenotypic selection. With increasing budget, flexibility in resource allocation increases greatly but selection gain leveled off quickly requiring balancing the number of populations with the budget spent for each population. The use of an index combining phenotypic and GS predicted values in the training set was especially beneficial under limited resources and large genotype × environment interactions. Once a sufficiently high selection accuracy is achieved in the prediction set, further selection gain can be achieved most efficiently by massively expanding its size. Thus, with increasing budget, reducing the costs for producing a DH line becomes increasingly crucial for successfully exploiting the

Introgression of a Block of Genome Under Infinitesimal Selection.

Science.gov (United States)

Sachdeva, Himani; Barton, Nicholas H

2018-06-12

Adaptive introgression is common in nature and can be driven by selection acting on multiple, linked genes. We explore the effects of polygenic selection on introgression under the infinitesimal model with linkage. This model assumes that the introgressing block has an effectively infinite number of loci, each with an infinitesimal effect on the trait under selection. The block is assumed to introgress under directional selection within a native population that is genetically homogeneous. We use individual-based simulations and a branching process approximation to compute various statistics of the introgressing block, and explore how these depend on parameters such as the map length and initial trait value associated with the introgressing block, the genetic variability along the block, and the strength of selection. Our results show that the introgression dynamics of a block under infinitesimal selection are qualitatively different from the dynamics of neutral introgression. We also find that in the long run, surviving descendant blocks are likely to have intermediate lengths, and clarify how their length is shaped by the interplay between linkage and infinitesimal selection. Our results suggest that it may be difficult to distinguish the long-term introgression of a block of genome with a single strongly selected locus from the introgression of a block with multiple, tightly linked and weakly selected loci. Copyright © 2018, Genetics.

A scan for positively selected genes in the genomes of humans and chimpanzees.

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Rasmus Nielsen

2005-06-01

Full Text Available Since the divergence of humans and chimpanzees about 5 million years ago, these species have undergone a remarkable evolution with drastic divergence in anatomy and cognitive abilities. At the molecular level, despite the small overall magnitude of DNA sequence divergence, we might expect such evolutionary changes to leave a noticeable signature throughout the genome. We here compare 13,731 annotated genes from humans to their chimpanzee orthologs to identify genes that show evidence of positive selection. Many of the genes that present a signature of positive selection tend to be involved in sensory perception or immune defenses. However, the group of genes that show the strongest evidence for positive selection also includes a surprising number of genes involved in tumor suppression and apoptosis, and of genes involved in spermatogenesis. We hypothesize that positive selection in some of these genes may be driven by genomic conflict due to apoptosis during spermatogenesis. Genes with maximal expression in the brain show little or no evidence for positive selection, while genes with maximal expression in the testis tend to be enriched with positively selected genes. Genes on the X chromosome also tend to show an elevated tendency for positive selection. We also present polymorphism data from 20 Caucasian Americans and 19 African Americans for the 50 annotated genes showing the strongest evidence for positive selection. The polymorphism analysis further supports the presence of positive selection in these genes by showing an excess of high-frequency derived nonsynonymous mutations.

How to Make a Dolphin: Molecular Signature of Positive Selection in Cetacean Genome.

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Mariana F Nery

Full Text Available Cetaceans are unique in being the only mammals completely adapted to an aquatic environment. This adaptation has required complex changes and sometimes a complete restructuring of physiology, behavior and morphology. Identifying genes that have been subjected to selection pressure during cetacean evolution would greatly enhance our knowledge of the ways in which genetic variation in this mammalian order has been shaped by natural selection. Here, we performed a genome-wide scan for positive selection in the dolphin lineage. We employed models of codon substitution that account for variation of selective pressure over branches on the tree and across sites in a sequence. We analyzed 7,859 nuclear-coding ortholog genes and using a series of likelihood ratio tests (LRTs, we identified 376 genes (4.8% with molecular signatures of positive selection in the dolphin lineage. We used the cow as the sister group and compared estimates of selection in the cetacean genome to this using the same methods. This allowed us to define which genes have been exclusively under positive selection in the dolphin lineage. The enrichment analysis found that the identified positively selected genes are significantly over-represented for three exclusive functional categories only in the dolphin lineage: segment specification, mesoderm development and system development. Of particular interest for cetacean adaptation to an aquatic life are the following GeneOntology targets under positive selection: genes related to kidney, heart, lung, eye, ear and nervous system development.

Genome-wide analysis reveals signatures of selection for important traits in domestic sheep from different ecoregions.

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Liu, Zhaohua; Ji, Zhibin; Wang, Guizhi; Chao, Tianle; Hou, Lei; Wang, Jianmin

2016-11-03

Throughout a long period of adaptation and selection, sheep have thrived in a diverse range of ecological environments. Mongolian sheep is the common ancestor of the Chinese short fat-tailed sheep. Migration to different ecoregions leads to changes in selection pressures and results in microevolution. Mongolian sheep and its subspecies differ in a number of important traits, especially reproductive traits. Genome-wide intraspecific variation is required to dissect the genetic basis of these traits. This research resequenced 3 short fat-tailed sheep breeds with a 43.2-fold coverage of the sheep genome. We report more than 17 million single nucleotide polymorphisms and 2.9 million indels and identify 143 genomic regions with reduced pooled heterozygosity or increased genetic distance to each other breed that represent likely targets for selection during the migration. These regions harbor genes related to developmental processes, cellular processes, multicellular organismal processes, biological regulation, metabolic processes, reproduction, localization, growth and various components of the stress responses. Furthermore, we examined the haplotype diversity of 3 genomic regions involved in reproduction and found significant differences in TSHR and PRL gene regions among 8 sheep breeds. Our results provide useful genomic information for identifying genes or causal mutations associated with important economic traits in sheep and for understanding the genetic basis of adaptation to different ecological environments.

Natural selection shaped the rise and fall of passenger pigeon genomic diversity.

Science.gov (United States)

Murray, Gemma G R; Soares, André E R; Novak, Ben J; Schaefer, Nathan K; Cahill, James A; Baker, Allan J; Demboski, John R; Doll, Andrew; Da Fonseca, Rute R; Fulton, Tara L; Gilbert, M Thomas P; Heintzman, Peter D; Letts, Brandon; McIntosh, George; O'Connell, Brendan L; Peck, Mark; Pipes, Marie-Lorraine; Rice, Edward S; Santos, Kathryn M; Sohrweide, A Gregory; Vohr, Samuel H; Corbett-Detig, Russell B; Green, Richard E; Shapiro, Beth

2017-11-17

The extinct passenger pigeon was once the most abundant bird in North America, and possibly the world. Although theory predicts that large populations will be more genetically diverse, passenger pigeon genetic diversity was surprisingly low. To investigate this disconnect, we analyzed 41 mitochondrial and 4 nuclear genomes from passenger pigeons and 2 genomes from band-tailed pigeons, which are passenger pigeons' closest living relatives. Passenger pigeons' large population size appears to have allowed for faster adaptive evolution and removal of harmful mutations, driving a huge loss in their neutral genetic diversity. These results demonstrate the effect that selection can have on a vertebrate genome and contradict results that suggested that population instability contributed to this species's surprisingly rapid extinction. Copyright © 2017, American Association for the Advancement of Science.

Genome patterns of selection and introgression of haplotypes in natural populations of the house mouse (Mus musculus.

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Fabian Staubach

Full Text Available General parameters of selection, such as the frequency and strength of positive selection in natural populations or the role of introgression, are still insufficiently understood. The house mouse (Mus musculus is a particularly well-suited model system to approach such questions, since it has a defined history of splits into subspecies and populations and since extensive genome information is available. We have used high-density single-nucleotide polymorphism (SNP typing arrays to assess genomic patterns of positive selection and introgression of alleles in two natural populations of each of the subspecies M. m. domesticus and M. m. musculus. Applying different statistical procedures, we find a large number of regions subject to apparent selective sweeps, indicating frequent positive selection on rare alleles or novel mutations. Genes in the regions include well-studied imprinted loci (e.g. Plagl1/Zac1, homologues of human genes involved in adaptations (e.g. alpha-amylase genes or in genetic diseases (e.g. Huntingtin and Parkin. Haplotype matching between the two subspecies reveals a large number of haplotypes that show patterns of introgression from specific populations of the respective other subspecies, with at least 10% of the genome being affected by partial or full introgression. Using neutral simulations for comparison, we find that the size and the fraction of introgressed haplotypes are not compatible with a pure migration or incomplete lineage sorting model. Hence, it appears that introgressed haplotypes can rise in frequency due to positive selection and thus can contribute to the adaptive genomic landscape of natural populations. Our data support the notion that natural genomes are subject to complex adaptive processes, including the introgression of haplotypes from other differentiated populations or species at a larger scale than previously assumed for animals. This implies that some of the admixture found in inbred strains of mice

Selective recruitment of nuclear factors to productively replicating herpes simplex virus genomes.

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Jill A Dembowski

2015-05-01

Full Text Available Much of the HSV-1 life cycle is carried out in the cell nucleus, including the expression, replication, repair, and packaging of viral genomes. Viral proteins, as well as cellular factors, play essential roles in these processes. Isolation of proteins on nascent DNA (iPOND was developed to label and purify cellular replication forks. We adapted aspects of this method to label viral genomes to both image, and purify replicating HSV-1 genomes for the identification of associated proteins. Many viral and cellular factors were enriched on viral genomes, including factors that mediate DNA replication, repair, chromatin remodeling, transcription, and RNA processing. As infection proceeded, packaging and structural components were enriched to a greater extent. Among the more abundant proteins that copurified with genomes were the viral transcription factor ICP4 and the replication protein ICP8. Furthermore, all seven viral replication proteins were enriched on viral genomes, along with cellular PCNA and topoisomerases, while other cellular replication proteins were not detected. The chromatin-remodeling complexes present on viral genomes included the INO80, SWI/SNF, NURD, and FACT complexes, which may prevent chromatinization of the genome. Consistent with this conclusion, histones were not readily recovered with purified viral genomes, and imaging studies revealed an underrepresentation of histones on viral genomes. RNA polymerase II, the mediator complex, TFIID, TFIIH, and several other transcriptional activators and repressors were also affinity purified with viral DNA. The presence of INO80, NURD, SWI/SNF, mediator, TFIID, and TFIIH components is consistent with previous studies in which these complexes copurified with ICP4. Therefore, ICP4 is likely involved in the recruitment of these key cellular chromatin remodeling and transcription factors to viral genomes. Taken together, iPOND is a valuable method for the study of viral genome dynamics

Selection for Unequal Densities of Sigma70 Promoter-like Signalsin Different Regions of Large Bacterial Genomes

Energy Technology Data Exchange (ETDEWEB)

Huerta, Araceli M.; Francino, M. Pilar; Morett, Enrique; Collado-Vides, Julio

2006-03-01

The evolutionary processes operating in the DNA regions that participate in the regulation of gene expression are poorly understood. In Escherichia coli, we have established a sequence pattern that distinguishes regulatory from nonregulatory regions. The density of promoter-like sequences, that are recognizable by RNA polymerase and may function as potential promoters, is high within regulatory regions, in contrast to coding regions and regions located between convergently-transcribed genes. Moreover, functional promoter sites identified experimentally are often found in the subregions of highest density of promoter-like signals, even when individual sites with higher binding affinity for RNA polymerase exist elsewhere within the regulatory region. In order to investigate the generality of this pattern, we have used position weight matrices describing the -35 and -10 promoter boxes of E. coli to search for these motifs in 43 additional genomes belonging to most established bacterial phyla, after specific calibration of the matrices according to the base composition of the noncoding regions of each genome. We have found that all bacterial species analyzed contain similar promoter-like motifs, and that, in most cases, these motifs follow the same genomic distribution observed in E. coli. Differential densities between regulatory and nonregulatory regions are detectable in most bacterial genomes, with the exception of those that have experienced evolutionary extreme genome reduction. Thus, the phylogenetic distribution of this pattern mirrors that of genes and other genomic features that require weak selection to be effective in order to persist. On this basis, we suggest that the loss of differential densities in the reduced genomes of host-restricted pathogens and symbionts is the outcome of a process of genome degradation resulting from the decreased efficiency of purifying selection in highly structured small populations. This implies that the differential

Strategies for implementing genomic selection in family-based aquaculture breeding schemes: double haploid sib test populations

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Nirea Kahsay G

2012-10-01

Full Text Available Abstract Background Simulation studies have shown that accuracy and genetic gain are increased in genomic selection schemes compared to traditional aquaculture sib-based schemes. In genomic selection, accuracy of selection can be maximized by increasing the precision of the estimation of SNP effects and by maximizing the relationships between test sibs and candidate sibs. Another means of increasing the accuracy of the estimation of SNP effects is to create individuals in the test population with extreme genotypes. The latter approach was studied here with creation of double haploids and use of non-random mating designs. Methods Six alternative breeding schemes were simulated in which the design of the test population was varied: test sibs inherited maternal (Mat, paternal (Pat or a mixture of maternal and paternal (MatPat double haploid genomes or test sibs were obtained by maximum coancestry mating (MaxC, minimum coancestry mating (MinC, or random (RAND mating. Three thousand test sibs and 3000 candidate sibs were genotyped. The test sibs were recorded for a trait that could not be measured on the candidates and were used to estimate SNP effects. Selection was done by truncation on genome-wide estimated breeding values and 100 individuals were selected as parents each generation, equally divided between both sexes. Results Results showed a 7 to 19% increase in selection accuracy and a 6 to 22% increase in genetic gain in the MatPat scheme compared to the RAND scheme. These increases were greater with lower heritabilities. Among all other scenarios, i.e. Mat, Pat, MaxC, and MinC, no substantial differences in selection accuracy and genetic gain were observed. Conclusions In conclusion, a test population designed with a mixture of paternal and maternal double haploids, i.e. the MatPat scheme, increases substantially the accuracy of selection and genetic gain. This will be particularly interesting for traits that cannot be recorded on the

Evaluation of genome-enabled selection for bacterial cold water disease resistance using progeny performance data in Rainbow Trout: Insights on genotyping methods and genomic prediction models

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Bacterial cold water disease (BCWD) causes significant economic losses in salmonid aquaculture, and traditional family-based breeding programs aimed at improving BCWD resistance have been limited to exploiting only between-family variation. We used genomic selection (GS) models to predict genomic br...

Optimization of multi-environment trials for genomic selection based on crop models.

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Rincent, R; Kuhn, E; Monod, H; Oury, F-X; Rousset, M; Allard, V; Le Gouis, J

2017-08-01

We propose a statistical criterion to optimize multi-environment trials to predict genotype × environment interactions more efficiently, by combining crop growth models and genomic selection models. Genotype × environment interactions (GEI) are common in plant multi-environment trials (METs). In this context, models developed for genomic selection (GS) that refers to the use of genome-wide information for predicting breeding values of selection candidates need to be adapted. One promising way to increase prediction accuracy in various environments is to combine ecophysiological and genetic modelling thanks to crop growth models (CGM) incorporating genetic parameters. The efficiency of this approach relies on the quality of the parameter estimates, which depends on the environments composing this MET used for calibration. The objective of this study was to determine a method to optimize the set of environments composing the MET for estimating genetic parameters in this context. A criterion called OptiMET was defined to this aim, and was evaluated on simulated and real data, with the example of wheat phenology. The MET defined with OptiMET allowed estimating the genetic parameters with lower error, leading to higher QTL detection power and higher prediction accuracies. MET defined with OptiMET was on average more efficient than random MET composed of twice as many environments, in terms of quality of the parameter estimates. OptiMET is thus a valuable tool to determine optimal experimental conditions to best exploit MET and the phenotyping tools that are currently developed.

Genomic Footprints in Selected and Unselected Beef Cattle Breeds in Korea.

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Dajeong Lim

Full Text Available Korean Hanwoo cattle have been subjected to intensive artificial selection over the past four decades to improve meat production traits. Another three cattle varieties very closely related to Hanwoo reside in Korea (Jeju Black and Brindle and in China (Yanbian. These breeds have not been part of a breeding scheme to improve production traits. Here, we compare the selected Hanwoo against these similar but presumed to be unselected populations to identify genomic regions that have been under recent selection pressure due to the breeding program. Rsb statistics were used to contrast the genomes of Hanwoo versus a pooled sample of the three unselected population (UN. We identified 37 significant SNPs (FDR corrected in the HW/UN comparison and 21 known protein coding genes were within 1 MB to the identified SNPs. These genes were previously reported to affect traits important for meat production (14 genes, reproduction including mammary gland development (3 genes, coat color (2 genes, and genes affecting behavioral traits in a broader sense (2 genes. We subsequently sequenced (Illumina HiSeq 2000 platform 10 individuals of the brown Hanwoo and the Chinese Yanbian to identify SNPs within the candidate genomic regions. Based on allele frequency differences, haplotype structures, and literature research, we singled out one non-synonymous SNP in the APP gene (APP: c.569C>T, Ala199Val and predicted the mutational effect on the protein structure. We found that protein-protein interactions might be impaired due to increased exposed hydrophobic surfaces of the mutated protein. The APP gene has also been reported to affect meat tenderness in pigs and obesity in humans. Meat tenderness has been linked to intramuscular fat content, which is one of the main breeding goals for brown Hanwoo, potentially supporting a causal influence of the herein described nsSNP in the APP gene.

Genomic Footprints in Selected and Unselected Beef Cattle Breeds in Korea.

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Lim, Dajeong; Strucken, Eva M; Choi, Bong Hwan; Chai, Han Ha; Cho, Yong Min; Jang, Gul Won; Kim, Tae-Hun; Gondro, Cedric; Lee, Seung Hwan

2016-01-01

Korean Hanwoo cattle have been subjected to intensive artificial selection over the past four decades to improve meat production traits. Another three cattle varieties very closely related to Hanwoo reside in Korea (Jeju Black and Brindle) and in China (Yanbian). These breeds have not been part of a breeding scheme to improve production traits. Here, we compare the selected Hanwoo against these similar but presumed to be unselected populations to identify genomic regions that have been under recent selection pressure due to the breeding program. Rsb statistics were used to contrast the genomes of Hanwoo versus a pooled sample of the three unselected population (UN). We identified 37 significant SNPs (FDR corrected) in the HW/UN comparison and 21 known protein coding genes were within 1 MB to the identified SNPs. These genes were previously reported to affect traits important for meat production (14 genes), reproduction including mammary gland development (3 genes), coat color (2 genes), and genes affecting behavioral traits in a broader sense (2 genes). We subsequently sequenced (Illumina HiSeq 2000 platform) 10 individuals of the brown Hanwoo and the Chinese Yanbian to identify SNPs within the candidate genomic regions. Based on allele frequency differences, haplotype structures, and literature research, we singled out one non-synonymous SNP in the APP gene (APP: c.569C>T, Ala199Val) and predicted the mutational effect on the protein structure. We found that protein-protein interactions might be impaired due to increased exposed hydrophobic surfaces of the mutated protein. The APP gene has also been reported to affect meat tenderness in pigs and obesity in humans. Meat tenderness has been linked to intramuscular fat content, which is one of the main breeding goals for brown Hanwoo, potentially supporting a causal influence of the herein described nsSNP in the APP gene.

Whole-genome resequencing of honeybee drones to detect genomic selection in a population managed for royal jelly.

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Wragg, David; Marti-Marimon, Maria; Basso, Benjamin; Bidanel, Jean-Pierre; Labarthe, Emmanuelle; Bouchez, Olivier; Le Conte, Yves; Vignal, Alain

2016-06-03

Four main evolutionary lineages of A. mellifera have been described including eastern Europe (C) and western and northern Europe (M). Many apiculturists prefer bees from the C lineage due to their docility and high productivity. In France, the routine importation of bees from the C lineage has resulted in the widespread admixture of bees from the M lineage. The haplodiploid nature of the honeybee Apis mellifera, and its small genome size, permits affordable and extensive genomics studies. As a pilot study of a larger project to characterise French honeybee populations, we sequenced 60 drones sampled from two commercial populations managed for the production of honey and royal jelly. Results indicate a C lineage origin, whilst mitochondrial analysis suggests two drones originated from the O lineage. Analysis of heterozygous SNPs identified potential copy number variants near to genes encoding odorant binding proteins and several cytochrome P450 genes. Signatures of selection were detected using the hapFLK haplotype-based method, revealing several regions under putative selection for royal jelly production. The framework developed during this study will be applied to a broader sampling regime, allowing the genetic diversity of French honeybees to be characterised in detail.

Genomic analysis of natural selection and phenotypic variation in high-altitude mongolians.

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Jinchuan Xing

Full Text Available Deedu (DU Mongolians, who migrated from the Mongolian steppes to the Qinghai-Tibetan Plateau approximately 500 years ago, are challenged by environmental conditions similar to native Tibetan highlanders. Identification of adaptive genetic factors in this population could provide insight into coordinated physiological responses to this environment. Here we examine genomic and phenotypic variation in this unique population and present the first complete analysis of a Mongolian whole-genome sequence. High-density SNP array data demonstrate that DU Mongolians share genetic ancestry with other Mongolian as well as Tibetan populations, specifically in genomic regions related with adaptation to high altitude. Several selection candidate genes identified in DU Mongolians are shared with other Asian groups (e.g., EDAR, neighboring Tibetan populations (including high-altitude candidates EPAS1, PKLR, and CYP2E1, as well as genes previously hypothesized to be associated with metabolic adaptation (e.g., PPARG. Hemoglobin concentration, a trait associated with high-altitude adaptation in Tibetans, is at an intermediate level in DU Mongolians compared to Tibetans and Han Chinese at comparable altitude. Whole-genome sequence from a DU Mongolian (Tianjiao1 shows that about 2% of the genomic variants, including more than 300 protein-coding changes, are specific to this individual. Our analyses of DU Mongolians and the first Mongolian genome provide valuable insight into genetic adaptation to extreme environments.

Island-Model Genomic Selection for Long-Term Genetic Improvement of Autogamous Crops.

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Yabe, Shiori; Yamasaki, Masanori; Ebana, Kaworu; Hayashi, Takeshi; Iwata, Hiroyoshi

2016-01-01

Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS), which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an "island model" inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the potential of genomic

Island-Model Genomic Selection for Long-Term Genetic Improvement of Autogamous Crops.

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Shiori Yabe

Full Text Available Acceleration of genetic improvement of autogamous crops such as wheat and rice is necessary to increase cereal production in response to the global food crisis. Population and pedigree methods of breeding, which are based on inbred line selection, are used commonly in the genetic improvement of autogamous crops. These methods, however, produce a few novel combinations of genes in a breeding population. Recurrent selection promotes recombination among genes and produces novel combinations of genes in a breeding population, but it requires inaccurate single-plant evaluation for selection. Genomic selection (GS, which can predict genetic potential of individuals based on their marker genotype, might have high reliability of single-plant evaluation and might be effective in recurrent selection. To evaluate the efficiency of recurrent selection with GS, we conducted simulations using real marker genotype data of rice cultivars. Additionally, we introduced the concept of an "island model" inspired by evolutionary algorithms that might be useful to maintain genetic variation through the breeding process. We conducted GS simulations using real marker genotype data of rice cultivars to evaluate the efficiency of recurrent selection and the island model in an autogamous species. Results demonstrated the importance of producing novel combinations of genes through recurrent selection. An initial population derived from admixture of multiple bi-parental crosses showed larger genetic gains than a population derived from a single bi-parental cross in whole cycles, suggesting the importance of genetic variation in an initial population. The island-model GS better maintained genetic improvement in later generations than the other GS methods, suggesting that the island-model GS can utilize genetic variation in breeding and can retain alleles with small effects in the breeding population. The island-model GS will become a new breeding method that enhances the

Non-Random Inversion Landscapes in Prokaryotic Genomes Are Shaped by Heterogeneous Selection Pressures.

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Repar, Jelena; Warnecke, Tobias

2017-08-01

Inversions are a major contributor to structural genome evolution in prokaryotes. Here, using a novel alignment-based method, we systematically compare 1,651 bacterial and 98 archaeal genomes to show that inversion landscapes are frequently biased toward (symmetric) inversions around the origin-terminus axis. However, symmetric inversion bias is not a universal feature of prokaryotic genome evolution but varies considerably across clades. At the extremes, inversion landscapes in Bacillus-Clostridium and Actinobacteria are dominated by symmetric inversions, while there is little or no systematic bias favoring symmetric rearrangements in archaea with a single origin of replication. Within clades, we find strong but clade-specific relationships between symmetric inversion bias and different features of adaptive genome architecture, including the distance of essential genes to the origin of replication and the preferential localization of genes on the leading strand. We suggest that heterogeneous selection pressures have converged to produce similar patterns of structural genome evolution across prokaryotes. © The Author 2017. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

Short communication: Genomic selection in a crossbred cattle population using data from the Dairy Genetics East Africa Project.

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Brown, A; Ojango, J; Gibson, J; Coffey, M; Okeyo, M; Mrode, R

2016-09-01

Due to the absence of accurate pedigree information, it has not been possible to implement genetic evaluations for crossbred cattle in African small-holder systems. Genomic selection techniques that do not rely on pedigree information could, therefore, be a useful alternative. The objective of this study was to examine the feasibility of using genomic selection techniques in a crossbred cattle population using data from Kenya provided by the Dairy Genetics East Africa Project. Genomic estimated breeding values for milk yield were estimated using 2 prediction methods, GBLUP and BayesC, and accuracies were calculated as the correlation between yield deviations and genomic breeding values included in the estimation process, mimicking the situation for young bulls. The accuracy of evaluation ranged from 0.28 to 0.41, depending on the validation population and prediction method used. No significant differences were found in accuracy between the 2 prediction methods. The results suggest that there is potential for implementing genomic selection for young bulls in crossbred small-holder cattle populations, and targeted genotyping and phenotyping should be pursued to facilitate this. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Whole-genome sequencing of two North American Drosophila melanogaster populations reveals genetic differentiation and positive selection.

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Campo, D; Lehmann, K; Fjeldsted, C; Souaiaia, T; Kao, J; Nuzhdin, S V

2013-10-01

The prevailing demographic model for Drosophila melanogaster suggests that the colonization of North America occurred very recently from a subset of European flies that rapidly expanded across the continent. This model implies a sudden population growth and range expansion consistent with very low or no population subdivision. As flies adapt to new environments, local adaptation events may be expected. To describe demographic and selective events during North American colonization, we have generated a data set of 35 individual whole-genome sequences from inbred lines of D. melanogaster from a west coast US population (Winters, California, USA) and compared them with a public genome data set from Raleigh (Raleigh, North Carolina, USA). We analysed nuclear and mitochondrial genomes and described levels of variation and divergence within and between these two North American D. melanogaster populations. Both populations exhibit negative values of Tajima's D across the genome, a common signature of demographic expansion. We also detected a low but significant level of genome-wide differentiation between the two populations, as well as multiple allele surfing events, which can be the result of gene drift in local subpopulations on the edge of an expansion wave. In contrast to this genome-wide pattern, we uncovered a 50-kilobase segment in chromosome arm 3L that showed all the hallmarks of a soft selective sweep in both populations. A comparison of allele frequencies within this divergent region among six populations from three continents allowed us to cluster these populations in two differentiated groups, providing evidence for the action of natural selection on a global scale. © 2013 John Wiley & Sons Ltd.

Ancestry variation and footprints of natural selection along the genome in Latin American populations.

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Deng, Lian; Ruiz-Linares, Andrés; Xu, Shuhua; Wang, Sijia

2016-02-18

Latin American populations stem from the admixture of Europeans, Africans and Native Americans, which started over 400 years ago and had lasted for several centuries. Extreme deviation over the genome-wide average in ancestry estimations at certain genomic locations could reflect recent natural selection. We evaluated the distribution of ancestry estimations using 678 genome-wide microsatellite markers in 249 individuals from 13 admixed populations across Latin America. We found significant deviations in ancestry estimations including three locations with more than 3.5 times standard deviations from the genome-wide average: an excess of European ancestry at 1p36 and 14q32, and an excess of African ancestry at 6p22. Using simulations, we could show that at least the deviation at 6p22 was unlikely to result from genetic drift alone. By applying different linguistic groups as well as the most likely ancestral Native American populations as the ancestry, we showed that the choice of Native American ancestry could affect the local ancestry estimation. However, the signal at 6p22 consistently appeared in most of the analyses using various ancestral groups. This study provided important insights for recent natural selection in the context of the unique history of the New World and implications for disease mapping.

Long-term response to genomic selection: effects of estimation method and reference population structure for different genetic architectures.

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Bastiaansen, John W M; Coster, Albart; Calus, Mario P L; van Arendonk, Johan A M; Bovenhuis, Henk

2012-01-24

Genomic selection has become an important tool in the genetic improvement of animals and plants. The objective of this study was to investigate the impacts of breeding value estimation method, reference population structure, and trait genetic architecture, on long-term response to genomic selection without updating marker effects. Three methods were used to estimate genomic breeding values: a BLUP method with relationships estimated from genome-wide markers (GBLUP), a Bayesian method, and a partial least squares regression method (PLSR). A shallow (individuals from one generation) or deep reference population (individuals from five generations) was used with each method. The effects of the different selection approaches were compared under four different genetic architectures for the trait under selection. Selection was based on one of the three genomic breeding values, on pedigree BLUP breeding values, or performed at random. Selection continued for ten generations. Differences in long-term selection response were small. For a genetic architecture with a very small number of three to four quantitative trait loci (QTL), the Bayesian method achieved a response that was 0.05 to 0.1 genetic standard deviation higher than other methods in generation 10. For genetic architectures with approximately 30 to 300 QTL, PLSR (shallow reference) or GBLUP (deep reference) had an average advantage of 0.2 genetic standard deviation over the Bayesian method in generation 10. GBLUP resulted in 0.6% and 0.9% less inbreeding than PLSR and BM and on average a one third smaller reduction of genetic variance. Responses in early generations were greater with the shallow reference population while long-term response was not affected by reference population structure. The ranking of estimation methods was different with than without selection. Under selection, applying GBLUP led to lower inbreeding and a smaller reduction of genetic variance while a similar response to selection was

Direct imaging and new technologies to search for substellar companions around MGs cool dwarfs

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Burningham B.

2011-07-01

Full Text Available We describe here our project based in a search for sub-stellar companions (brown dwarfs and exo-planets around young ultra-cool dwarfs (UCDs and characterise their properties. We will use current and future technology (high contrast imaging, high-precision Doppler determinations from the ground and space (VLT, ELT and JWST, to find companions to young objects. Members of young moving groups (MGs have clear advantages in this field. We compiled a catalogue of young UCD objects and studied their membership to five known young moving groups: Local Association (Pleiades moving group, 20–150 Myr, Ursa Mayor group (Sirius supercluster, 300 Myr, Hyades supercluster (600 Myr, IC 2391 supercluster (35 Myr and Castor moving group (200 Myr. To assess them as members we used different kinematic and spectroscopic criteria.

Twenty years of artificial directional selection have shaped the genome of the Italian Large White pig breed.

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Schiavo, G; Galimberti, G; Calò, D G; Samorè, A B; Bertolini, F; Russo, V; Gallo, M; Buttazzoni, L; Fontanesi, L

2016-04-01

In this study, we investigated at the genome-wide level if 20 years of artificial directional selection based on boar genetic evaluation obtained with a classical BLUP animal model shaped the genome of the Italian Large White pig breed. The most influential boars of this breed (n = 192), born from 1992 (the beginning of the selection program of this breed) to 2012, with an estimated breeding value reliability of >0.85, were genotyped with the Illumina Porcine SNP60 BeadChip. After grouping the boars in eight classes according to their year of birth, filtered single nucleotide polymorphisms (SNPs) were used to evaluate the effects of time on genotype frequency changes using multinomial logistic regression models. Of these markers, 493 had a PBonferroni  selection program. The obtained results indicated that the genome of the Italian Large White pigs was shaped by a directional selection program derived by the application of methodologies assuming the infinitesimal model that captured a continuous trend of allele frequency changes in the boar population. © 2015 Stichting International Foundation for Animal Genetics.

The impact of selection, gene flow and demographic history on heterogeneous genomic divergence: three-spine sticklebacks in divergent environments.

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Ferchaud, Anne-Laure; Hansen, Michael M

2016-01-01

Heterogeneous genomic divergence between populations may reflect selection, but should also be seen in conjunction with gene flow and drift, particularly population bottlenecks. Marine and freshwater three-spine stickleback (Gasterosteus aculeatus) populations often exhibit different lateral armour plate morphs. Moreover, strikingly parallel genomic footprints across different marine-freshwater population pairs are interpreted as parallel evolution and gene reuse. Nevertheless, in some geographic regions like the North Sea and Baltic Sea, different patterns are observed. Freshwater populations in coastal regions are often dominated by marine morphs, suggesting that gene flow overwhelms selection, and genomic parallelism may also be less pronounced. We used RAD sequencing for analysing 28 888 SNPs in two marine and seven freshwater populations in Denmark, Europe. Freshwater populations represented a variety of environments: river populations accessible to gene flow from marine sticklebacks and large and small isolated lakes with and without fish predators. Sticklebacks in an accessible river environment showed minimal morphological and genomewide divergence from marine populations, supporting the hypothesis of gene flow overriding selection. Allele frequency spectra suggested bottlenecks in all freshwater populations, and particularly two small lake populations. However, genomic footprints ascribed to selection could nevertheless be identified. No genomic regions were consistent freshwater-marine outliers, and parallelism was much lower than in other comparable studies. Two genomic regions previously described to be under divergent selection in freshwater and marine populations were outliers between different freshwater populations. We ascribe these patterns to stronger environmental heterogeneity among freshwater populations in our study as compared to most other studies, although the demographic history involving bottlenecks should also be considered in the

Genome-wide scan of gastrointestinal nematode resistance in closed Angus population selected for minimized influence of MHC.

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Kim, Eui-Soo; Sonstegard, Tad S; da Silva, Marcos V G B; Gasbarre, Louis C; Van Tassell, Curtis P

2015-01-01

Genetic markers associated with parasite indicator traits are ideal targets for study of marker assisted selection aimed at controlling infections that reduce herd use of anthelminthics. For this study, we collected gastrointestinal (GI) nematode fecal egg count (FEC) data from post-weaning animals of an Angus resource population challenged to a 26 week natural exposure on pasture. In all, data from 487 animals was collected over a 16 year period between 1992 and 2007, most of which were selected for a specific DRB1 allele to reduce the influence of potential allelic variant effects of the MHC locus. A genome-wide association study (GWAS) based on BovineSNP50 genotypes revealed six genomic regions located on bovine Chromosomes 3, 5, 8, 15 and 27; which were significantly associated (-log10 p=4.3) with Box-Cox transformed mean FEC (BC-MFEC). DAVID analysis of the genes within the significant genomic regions suggested a correlation between our results and annotation for genes involved in inflammatory response to infection. Furthermore, ROH and selection signature analyses provided strong evidence that the genomic regions associated BC-MFEC have not been affected by local autozygosity or recent experimental selection. These findings provide useful information for parasite resistance prediction for young grazing cattle and suggest new candidate gene targets for development of disease-modifying therapies or future studies of host response to GI parasite infection.

Systematic differences in the response of genetic variation to pedigree and genome-based selection methods

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Heidaritabar, M.; Vereijken, A.; Muir, W.M.; Meuwissen, T.H.E.; Cheng, H.; Megens, H.J.W.C.; Groenen, M.; Bastiaansen, J.W.M.

2014-01-01

Genomic selection (GS) is a DNA-based method of selecting for quantitative traits in animal and plant breeding, and offers a potentially superior alternative to traditional breeding methods that rely on pedigree and phenotype information. Using a 60¿K SNP chip with markers spaced throughout the

GRAbB : Selective Assembly of Genomic Regions, a New Niche for Genomic Research

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Brankovics, Balázs; Zhang, Hao; van Diepeningen, Anne D; van der Lee, Theo A J; Waalwijk, Cees; de Hoog, G Sybren

GRAbB (Genomic Region Assembly by Baiting) is a new program that is dedicated to assemble specific genomic regions from NGS data. This approach is especially useful when dealing with multi copy regions, such as mitochondrial genome and the rDNA repeat region, parts of the genome that are often

Rapid Cycling Genomic Selection in a Multiparental Tropical Maize Population.

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Zhang, Xuecai; Pérez-Rodríguez, Paulino; Burgueño, Juan; Olsen, Michael; Buckler, Edward; Atlin, Gary; Prasanna, Boddupalli M; Vargas, Mateo; San Vicente, Félix; Crossa, José

2017-07-05

Genomic selection (GS) increases genetic gain by reducing the length of the selection cycle, as has been exemplified in maize using rapid cycling recombination of biparental populations. However, no results of GS applied to maize multi-parental populations have been reported so far. This study is the first to show realized genetic gains of rapid cycling genomic selection (RCGS) for four recombination cycles in a multi-parental tropical maize population. Eighteen elite tropical maize lines were intercrossed twice, and self-pollinated once, to form the cycle 0 (C 0 ) training population. A total of 1000 ear-to-row C 0 families was genotyped with 955,690 genotyping-by-sequencing SNP markers; their testcrosses were phenotyped at four optimal locations in Mexico to form the training population. Individuals from families with the best plant types, maturity, and grain yield were selected and intermated to form RCGS cycle 1 (C 1 ). Predictions of the genotyped individuals forming cycle C 1 were made, and the best predicted grain yielders were selected as parents of C 2 ; this was repeated for more cycles (C 2 , C 3 , and C 4 ), thereby achieving two cycles per year. Multi-environment trials of individuals from populations C 0, C 1 , C 2 , C 3 , and C 4 , together with four benchmark checks were evaluated at two locations in Mexico. Results indicated that realized grain yield from C 1 to C 4 reached 0.225 ton ha -1 per cycle, which is equivalent to 0.100 ton ha -1  yr -1 over a 4.5-yr breeding period from the initial cross to the last cycle. Compared with the original 18 parents used to form cycle 0 (C 0 ), genetic diversity narrowed only slightly during the last GS cycles (C 3 and C 4 ). Results indicate that, in tropical maize multi-parental breeding populations, RCGS can be an effective breeding strategy for simultaneously conserving genetic diversity and achieving high genetic gains in a short period of time. Copyright © 2017 Zhang et al.

Genome Scan for Selection in Structured Layer Chicken Populations Exploiting Linkage Disequilibrium Information.

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Mahmood Gholami

Full Text Available An increasing interest is being placed in the detection of genes, or genomic regions, that have been targeted by selection because identifying signatures of selection can lead to a better understanding of genotype-phenotype relationships. A common strategy for the detection of selection signatures is to compare samples from distinct populations and to search for genomic regions with outstanding genetic differentiation. The aim of this study was to detect selective signatures in layer chicken populations using a recently proposed approach, hapFLK, which exploits linkage disequilibrium information while accounting appropriately for the hierarchical structure of populations. We performed the analysis on 70 individuals from three commercial layer breeds (White Leghorn, White Rock and Rhode Island Red, genotyped for approximately 1 million SNPs. We found a total of 41 and 107 regions with outstanding differentiation or similarity using hapFLK and its single SNP counterpart FLK respectively. Annotation of selection signature regions revealed various genes and QTL corresponding to productions traits, for which layer breeds were selected. A number of the detected genes were associated with growth and carcass traits, including IGF-1R, AGRP and STAT5B. We also annotated an interesting gene associated with the dark brown feather color mutational phenotype in chickens (SOX10. We compared FST, FLK and hapFLK and demonstrated that exploiting linkage disequilibrium information and accounting for hierarchical population structure decreased the false detection rate.

Accounting for Genotype-by-Environment Interactions and Residual Genetic Variation in Genomic Selection for Water-Soluble Carbohydrate Concentration in Wheat.

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Ovenden, Ben; Milgate, Andrew; Wade, Len J; Rebetzke, Greg J; Holland, James B

2018-05-31

Abiotic stress tolerance traits are often complex and recalcitrant targets for conventional breeding improvement in many crop species. This study evaluated the potential of genomic selection to predict water-soluble carbohydrate concentration (WSCC), an important drought tolerance trait, in wheat under field conditions. A panel of 358 varieties and breeding lines constrained for maturity was evaluated under rainfed and irrigated treatments across two locations and two years. Whole-genome marker profiles and factor analytic mixed models were used to generate genomic estimated breeding values (GEBVs) for specific environments and environment groups. Additive genetic variance was smaller than residual genetic variance for WSCC, such that genotypic values were dominated by residual genetic effects rather than additive breeding values. As a result, GEBVs were not accurate predictors of genotypic values of the extant lines, but GEBVs should be reliable selection criteria to choose parents for intermating to produce new populations. The accuracy of GEBVs for untested lines was sufficient to increase predicted genetic gain from genomic selection per unit time compared to phenotypic selection if the breeding cycle is reduced by half by the use of GEBVs in off-season generations. Further, genomic prediction accuracy depended on having phenotypic data from environments with strong correlations with target production environments to build prediction models. By combining high-density marker genotypes, stress-managed field evaluations, and mixed models that model simultaneously covariances among genotypes and covariances of complex trait performance between pairs of environments, we were able to train models with good accuracy to facilitate genetic gain from genomic selection. Copyright © 2018 Ovenden et al.

Detection of genomic variation by selection of a 9 mb DNA region and high throughput sequencing.

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Sergey I Nikolaev

Full Text Available Detection of the rare polymorphisms and causative mutations of genetic diseases in a targeted genomic area has become a major goal in order to understand genomic and phenotypic variability. We have interrogated repeat-masked regions of 8.9 Mb on human chromosomes 21 (7.8 Mb and 7 (1.1 Mb from an individual from the International HapMap Project (NA12872. We have optimized a method of genomic selection for high throughput sequencing. Microarray-based selection and sequencing resulted in 260-fold enrichment, with 41% of reads mapping to the target region. 83% of SNPs in the targeted region had at least 4-fold sequence coverage and 54% at least 15-fold. When assaying HapMap SNPs in NA12872, our sequence genotypes are 91.3% concordant in regions with coverage > or = 4-fold, and 97.9% concordant in regions with coverage > or = 15-fold. About 81% of the SNPs recovered with both thresholds are listed in dbSNP. We observed that regions with low sequence coverage occur in close proximity to low-complexity DNA. Validation experiments using Sanger sequencing were performed for 46 SNPs with 15-20 fold coverage, with a confirmation rate of 96%, suggesting that DNA selection provides an accurate and cost-effective method for identifying rare genomic variants.

Genomic and environmental selection patterns in two distinct lettuce crop-wild hybrid crosses

NARCIS (Netherlands)

Hartman, Y.; Uwimana, B; Hooftman, D.A.P.; Schranz, M.E.; van de Wiel, C.C.M.; Smulders, M.J.M.; Visser, R.G.F.; van Tienderen, P.H.

2013-01-01

Genomic selection patterns and hybrid performance influence the chance that crop (trans)genes can spread to wild relatives. We measured fitness(-related) traits in two different field environments employing two different crop-wild crosses of lettuce. We performed quantitative trait loci (QTL)

Genomic and environmental selection patterns in two distinct lettuce crop-wild hybrid crosses

NARCIS (Netherlands)

Hartman, Y.; Uwimana, B.; Hooftman, D.A.P.; Schranz, M.E.; Wiel, van de C.C.M.; Smulders, M.J.M.; Visser, R.G.F.; Tienderen, van P.H.

2013-01-01

Genomic selection patterns and hybrid performance influence the chance that crop (trans)genes can spread to wild relatives. We measured fitness(-related) traits in two different field environments employing two different crop–wild crosses of lettuce. We performed quantitative trait loci (QTL)

Genome-wide scans between two honeybee populations reveal putative signatures of human-mediated selection.

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Parejo, M; Wragg, D; Henriques, D; Vignal, A; Neuditschko, M

2017-12-01

Human-mediated selection has left signatures in the genomes of many domesticated animals, including the European dark honeybee, Apis mellifera mellifera, which has been selected by apiculturists for centuries. Using whole-genome sequence information, we investigated selection signatures in spatially separated honeybee subpopulations (Switzerland, n = 39 and France, n = 17). Three different test statistics were calculated in windows of 2 kb (fixation index, cross-population extended haplotype homozygosity and cross-population composite likelihood ratio) and combined into a recently developed composite selection score. Applying a stringent false discovery rate of 0.01, we identified six significant selective sweeps distributed across five chromosomes covering eight genes. These genes are associated with multiple molecular and biological functions, including regulation of transcription, receptor binding and signal transduction. Of particular interest is a selection signature on chromosome 1, which corresponds to the WNT4 gene, the family of which is conserved across the animal kingdom with a variety of functions. In Drosophila melanogaster, WNT4 alleles have been associated with differential wing, cross vein and abdominal phenotypes. Defining phenotypic characteristics of different Apis mellifera ssp., which are typically used as selection criteria, include colour and wing venation pattern. This signal is therefore likely to be a good candidate for human mediated-selection arising from different applied breeding practices in the two managed populations. © 2017 The Authors. Animal Genetics published by John Wiley & Sons Ltd on behalf of Stichting International Foundation for Animal Genetics.

A map of recent positive selection in the human genome.

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Benjamin F Voight

2006-03-01

Full Text Available The identification of signals of very recent positive selection provides information about the adaptation of modern humans to local conditions. We report here on a genome-wide scan for signals of very recent positive selection in favor of variants that have not yet reached fixation. We describe a new analytical method for scanning single nucleotide polymorphism (SNP data for signals of recent selection, and apply this to data from the International HapMap Project. In all three continental groups we find widespread signals of recent positive selection. Most signals are region-specific, though a significant excess are shared across groups. Contrary to some earlier low resolution studies that suggested a paucity of recent selection in sub-Saharan Africans, we find that by some measures our strongest signals of selection are from the Yoruba population. Finally, since these signals indicate the existence of genetic variants that have substantially different fitnesses, they must indicate loci that are the source of significant phenotypic variation. Though the relevant phenotypes are generally not known, such loci should be of particular interest in mapping studies of complex traits. For this purpose we have developed a set of SNPs that can be used to tag the strongest approximately 250 signals of recent selection in each population.

Potential of Genomic Selection in Mass Selection Breeding of an Allogamous Crop: An Empirical Study to Increase Yield of Common Buckwheat.

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Yabe, Shiori; Hara, Takashi; Ueno, Mariko; Enoki, Hiroyuki; Kimura, Tatsuro; Nishimura, Satoru; Yasui, Yasuo; Ohsawa, Ryo; Iwata, Hiroyoshi

2018-01-01

To evaluate the potential of genomic selection (GS), a selection experiment with GS and phenotypic selection (PS) was performed in an allogamous crop, common buckwheat ( Fagopyrum esculentum Moench). To indirectly select for seed yield per unit area, which cannot be measured on a single-plant basis, a selection index was constructed from seven agro-morphological traits measurable on a single plant basis. Over 3 years, we performed two GS and one PS cycles per year for improvement in the selection index. In GS, a prediction model was updated every year on the basis of genotypes of 14,598-50,000 markers and phenotypes. Plants grown from seeds derived from a series of generations of GS and PS populations were evaluated for the traits in the selection index and other yield-related traits. GS resulted in a 20.9% increase and PS in a 15.0% increase in the selection index in comparison with the initial population. Although the level of linkage disequilibrium in the breeding population was low, the target trait was improved with GS. Traits with higher weights in the selection index were improved more than those with lower weights, especially when prediction accuracy was high. No trait changed in an unintended direction in either GS or PS. The accuracy of genomic prediction models built in the first cycle decreased in the later cycles because the genetic bottleneck through the selection cycles changed linkage disequilibrium patterns in the breeding population. The present study emphasizes the importance of updating models in GS and demonstrates the potential of GS in mass selection of allogamous crop species, and provided a pilot example of successful application of GS to plant breeding.

Genome-wide Selective Sweeps in Natural Bacterial Populations Revealed by Time-series Metagenomics

Energy Technology Data Exchange (ETDEWEB)

Chan, Leong-Keat; Bendall, Matthew L.; Malfatti, Stephanie; Schwientek, Patrick; Tremblay, Julien; Schackwitz, Wendy; Martin, Joel; Pati, Amrita; Bushnell, Brian; Foster, Brian; Kang, Dongwan; Tringe, Susannah G.; Bertilsson, Stefan; Moran, Mary Ann; Shade, Ashley; Newton, Ryan J.; Stevens, Sarah; McMcahon, Katherine D.; Mamlstrom, Rex R.

2014-05-12

Multiple evolutionary models have been proposed to explain the formation of genetically and ecologically distinct bacterial groups. Time-series metagenomics enables direct observation of evolutionary processes in natural populations, and if applied over a sufficiently long time frame, this approach could capture events such as gene-specific or genome-wide selective sweeps. Direct observations of either process could help resolve how distinct groups form in natural microbial assemblages. Here, from a three-year metagenomic study of a freshwater lake, we explore changes in single nucleotide polymorphism (SNP) frequencies and patterns of gene gain and loss in populations of Chlorobiaceae and Methylophilaceae. SNP analyses revealed substantial genetic heterogeneity within these populations, although the degree of heterogeneity varied considerably among closely related, co-occurring Methylophilaceae populations. SNP allele frequencies, as well as the relative abundance of certain genes, changed dramatically over time in each population. Interestingly, SNP diversity was purged at nearly every genome position in one of the Chlorobiaceae populations over the course of three years, while at the same time multiple genes either swept through or were swept from this population. These patterns were consistent with a genome-wide selective sweep, a process predicted by the ecotype model? of diversification, but not previously observed in natural populations.

Genome-wide Selective Sweeps in Natural Bacterial Populations Revealed by Time-series Metagenomics

Energy Technology Data Exchange (ETDEWEB)

Chan, Leong-Keat; Bendall, Matthew L.; Malfatti, Stephanie; Schwientek, Patrick; Tremblay, Julien; Schackwitz, Wendy; Martin, Joel; Pati, Amrita; Bushnell, Brian; Foster, Brian; Kang, Dongwan; Tringe, Susannah G.; Bertilsson, Stefan; Moran, Mary Ann; Shade, Ashley; Newton, Ryan J.; Stevens, Sarah; McMahon, Katherine D.; Malmstrom, Rex R.

2014-06-18

Multiple evolutionary models have been proposed to explain the formation of genetically and ecologically distinct bacterial groups. Time-series metagenomics enables direct observation of evolutionary processes in natural populations, and if applied over a sufficiently long time frame, this approach could capture events such as gene-specific or genome-wide selective sweeps. Direct observations of either process could help resolve how distinct groups form in natural microbial assemblages. Here, from a three-year metagenomic study of a freshwater lake, we explore changes in single nucleotide polymorphism (SNP) frequencies and patterns of gene gain and loss in populations of Chlorobiaceae and Methylophilaceae. SNP analyses revealed substantial genetic heterogeneity within these populations, although the degree of heterogeneity varied considerably among closely related, co-occurring Methylophilaceae populations. SNP allele frequencies, as well as the relative abundance of certain genes, changed dramatically over time in each population. Interestingly, SNP diversity was purged at nearly every genome position in one of the Chlorobiaceae populations over the course of three years, while at the same time multiple genes either swept through or were swept from this population. These patterns were consistent with a genome-wide selective sweep, a process predicted by the ‘ecotype model’ of diversification, but not previously observed in natural populations.

Sequence- vs. chip-assisted genomic selection: accurate biological information is advised.

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Pérez-Enciso, Miguel; Rincón, Juan C; Legarra, Andrés

2015-05-09

The development of next-generation sequencing technologies (NGS) has made the use of whole-genome sequence data for routine genetic evaluations possible, which has triggered a considerable interest in animal and plant breeding fields. Here, we investigated whether complete or partial sequence data can improve upon existing SNP (single nucleotide polymorphism) array-based selection strategies by simulation using a mixed coalescence - gene-dropping approach. We simulated 20 or 100 causal mutations (quantitative trait nucleotides, QTN) within 65 predefined 'gene' regions, each 10 kb long, within a genome composed of ten 3-Mb chromosomes. We compared prediction accuracy by cross-validation using a medium-density chip (7.5 k SNPs), a high-density (HD, 17 k) and sequence data (335 k). Genetic evaluation was based on a GBLUP method. The simulations showed: (1) a law of diminishing returns with increasing number of SNPs; (2) a modest effect of SNP ascertainment bias in arrays; (3) a small advantage of using whole-genome sequence data vs. HD arrays i.e. ~4%; (4) a minor effect of NGS errors except when imputation error rates are high (≥20%); and (5) if QTN were known, prediction accuracy approached 1. Since this is obviously unrealistic, we explored milder assumptions. We showed that, if all SNPs within causal genes were included in the prediction model, accuracy could also dramatically increase by ~40%. However, this criterion was highly sensitive to either misspecification (including wrong genes) or to the use of an incomplete gene list; in these cases, accuracy fell rapidly towards that reached when all SNPs from sequence data were blindly included in the model. Our study shows that, unless an accurate prior estimate on the functionality of SNPs can be included in the predictor, there is a law of diminishing returns with increasing SNP density. As a result, use of whole-genome sequence data may not result in a highly increased selection response over high

Genome-wide association study, genomic prediction and marker-assisted selection for seed weight in soybean (Glycine max).

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Zhang, Jiaoping; Song, Qijian; Cregan, Perry B; Jiang, Guo-Liang

2016-01-01

Twenty-two loci for soybean SW and candidate genes conditioning seed development were identified; and prediction accuracies of GS and MAS were estimated through cross-validation and validation with unrelated populations. Soybean (Glycine max) is a major crop for plant protein and oil production, and seed weight (SW) is important for yield and quality in food/vegetable uses of soybean. However, our knowledge of genes controlling SW remains limited. To better understand the molecular mechanism underlying the trait and explore marker-based breeding approaches, we conducted a genome-wide association study in a population of 309 soybean germplasm accessions using 31,045 single nucleotide polymorphisms (SNPs), and estimated the prediction accuracy of genomic selection (GS) and marker-assisted selection (MAS) for SW. Twenty-two loci of minor effect associated with SW were identified, including hotspots on Gm04 and Gm19. The mixed model containing these loci explained 83.4% of phenotypic variation. Candidate genes with Arabidopsis orthologs conditioning SW were also proposed. The prediction accuracies of GS and MAS by cross-validation were 0.75-0.87 and 0.62-0.75, respectively, depending on the number of SNPs used and the size of training population. GS also outperformed MAS when the validation was performed using unrelated panels across a wide range of maturities, with an average prediction accuracy of 0.74 versus 0.53. This study convincingly demonstrated that soybean SW is controlled by numerous minor-effect loci. It greatly enhances our understanding of the genetic basis of SW in soybean and facilitates the identification of genes controlling the trait. It also suggests that GS holds promise for accelerating soybean breeding progress. The results are helpful for genetic improvement and genomic prediction of yield in soybean.

Genome-wide scan of gastrointestinal nematode resistance in closed Angus population selected for minimized influence of MHC.

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Eui-Soo Kim

Full Text Available Genetic markers associated with parasite indicator traits are ideal targets for study of marker assisted selection aimed at controlling infections that reduce herd use of anthelminthics. For this study, we collected gastrointestinal (GI nematode fecal egg count (FEC data from post-weaning animals of an Angus resource population challenged to a 26 week natural exposure on pasture. In all, data from 487 animals was collected over a 16 year period between 1992 and 2007, most of which were selected for a specific DRB1 allele to reduce the influence of potential allelic variant effects of the MHC locus. A genome-wide association study (GWAS based on BovineSNP50 genotypes revealed six genomic regions located on bovine Chromosomes 3, 5, 8, 15 and 27; which were significantly associated (-log10 p=4.3 with Box-Cox transformed mean FEC (BC-MFEC. DAVID analysis of the genes within the significant genomic regions suggested a correlation between our results and annotation for genes involved in inflammatory response to infection. Furthermore, ROH and selection signature analyses provided strong evidence that the genomic regions associated BC-MFEC have not been affected by local autozygosity or recent experimental selection. These findings provide useful information for parasite resistance prediction for young grazing cattle and suggest new candidate gene targets for development of disease-modifying therapies or future studies of host response to GI parasite infection.

Investigating Drought Tolerance in Chickpea Using Genome-Wide Association Mapping and Genomic Selection Based on Whole-Genome Resequencing Data.

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Li, Yongle; Ruperao, Pradeep; Batley, Jacqueline; Edwards, David; Khan, Tanveer; Colmer, Timothy D; Pang, Jiayin; Siddique, Kadambot H M; Sutton, Tim

2018-01-01

Drought tolerance is a complex trait that involves numerous genes. Identifying key causal genes or linked molecular markers can facilitate the fast development of drought tolerant varieties. Using a whole-genome resequencing approach, we sequenced 132 chickpea varieties and advanced breeding lines and found more than 144,000 single nucleotide polymorphisms (SNPs). We measured 13 yield and yield-related traits in three drought-prone environments of Western Australia. The genotypic effects were significant for all traits, and many traits showed highly significant correlations, ranging from 0.83 between grain yield and biomass to -0.67 between seed weight and seed emergence rate. To identify candidate genes, the SNP and trait data were incorporated into the SUPER genome-wide association study (GWAS) model, a modified version of the linear mixed model. We found that several SNPs from auxin-related genes, including auxin efflux carrier protein (PIN3), p-glycoprotein, and nodulin MtN21/EamA-like transporter, were significantly associated with yield and yield-related traits under drought-prone environments. We identified four genetic regions containing SNPs significantly associated with several different traits, which was an indication of pleiotropic effects. We also investigated the possibility of incorporating the GWAS results into a genomic selection (GS) model, which is another approach to deal with complex traits. Compared to using all SNPs, application of the GS model using subsets of SNPs significantly associated with the traits under investigation increased the prediction accuracies of three yield and yield-related traits by more than twofold. This has important implication for implementing GS in plant breeding programs.

Rhipicephalus microplus dataset of nonredundant raw sequence reads from 454 GS FLX sequencing of Cot-selected (Cot = 660) genomic DNA

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A reassociation kinetics-based approach was used to reduce the complexity of genomic DNA from the Deutsch laboratory strain of the cattle tick, Rhipicephalus microplus, to facilitate genome sequencing. Selected genomic DNA (Cot value = 660) was sequenced using 454 GS FLX technology, resulting in 356...

Identification and analysis of genome-wide SNPs provide insight into signatures of selection and domestication in channel catfish (Ictalurus punctatus.

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Luyang Sun

Full Text Available Domestication and selection for important performance traits can impact the genome, which is most often reflected by reduced heterozygosity in and surrounding genes related to traits affected by selection. In this study, analysis of the genomic impact caused by domestication and artificial selection was conducted by investigating the signatures of selection using single nucleotide polymorphisms (SNPs in channel catfish (Ictalurus punctatus. A total of 8.4 million candidate SNPs were identified by using next generation sequencing. On average, the channel catfish genome harbors one SNP per 116 bp. Approximately 6.6 million, 5.3 million, 4.9 million, 7.1 million and 6.7 million SNPs were detected in the Marion, Thompson, USDA103, Hatchery strain, and wild population, respectively. The allele frequencies of 407,861 SNPs differed significantly between the domestic and wild populations. With these SNPs, 23 genomic regions with putative selective sweeps were identified that included 11 genes. Although the function for the majority of the genes remain unknown in catfish, several genes with known function related to aquaculture performance traits were included in the regions with selective sweeps. These included hypoxia-inducible factor 1β. HIFιβ.. and the transporter gene ATP-binding cassette sub-family B member 5 (ABCB5. HIF1β. is important for response to hypoxia and tolerance to low oxygen levels is a critical aquaculture trait. The large numbers of SNPs identified from this study are valuable for the development of high-density SNP arrays for genetic and genomic studies of performance traits in catfish.

Pooled-DNA sequencing identifies genomic regions of selection in Nigerian isolates of Plasmodium falciparum.

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Oyebola, Kolapo M; Idowu, Emmanuel T; Olukosi, Yetunde A; Awolola, Taiwo S; Amambua-Ngwa, Alfred

2017-06-29

The burden of falciparum malaria is especially high in sub-Saharan Africa. Differences in pressure from host immunity and antimalarial drugs lead to adaptive changes responsible for high level of genetic variations within and between the parasite populations. Population-specific genetic studies to survey for genes under positive or balancing selection resulting from drug pressure or host immunity will allow for refinement of interventions. We performed a pooled sequencing (pool-seq) of the genomes of 100 Plasmodium falciparum isolates from Nigeria. We explored allele-frequency based neutrality test (Tajima's D) and integrated haplotype score (iHS) to identify genes under selection. Fourteen shared iHS regions that had at least 2 SNPs with a score > 2.5 were identified. These regions code for genes that were likely to have been under strong directional selection. Two of these genes were the chloroquine resistance transporter (CRT) on chromosome 7 and the multidrug resistance 1 (MDR1) on chromosome 5. There was a weak signature of selection in the dihydrofolate reductase (DHFR) gene on chromosome 4 and MDR5 genes on chromosome 13, with only 2 and 3 SNPs respectively identified within the iHS window. We observed strong selection pressure attributable to continued chloroquine and sulfadoxine-pyrimethamine use despite their official proscription for the treatment of uncomplicated malaria. There was also a major selective sweep on chromosome 6 which had 32 SNPs within the shared iHS region. Tajima's D of circumsporozoite protein (CSP), erythrocyte-binding antigen (EBA-175), merozoite surface proteins - MSP3 and MSP7, merozoite surface protein duffy binding-like (MSPDBL2) and serine repeat antigen (SERA-5) were 1.38, 1.29, 0.73, 0.84 and 0.21, respectively. We have demonstrated the use of pool-seq to understand genomic patterns of selection and variability in P. falciparum from Nigeria, which bears the highest burden of infections. This investigation identified known

Genome-scale detection of positive selection in nine primates predicts human-virus evolutionary conflicts.

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van der Lee, Robin; Wiel, Laurens; van Dam, Teunis J P; Huynen, Martijn A

2017-10-13

Hotspots of rapid genome evolution hold clues about human adaptation. We present a comparative analysis of nine whole-genome sequenced primates to identify high-confidence targets of positive selection. We find strong statistical evidence for positive selection in 331 protein-coding genes (3%), pinpointing 934 adaptively evolving codons (0.014%). Our new procedure is stringent and reveals substantial artefacts (20% of initial predictions) that have inflated previous estimates. The final 331 positively selected genes (PSG) are strongly enriched for innate and adaptive immunity, secreted and cell membrane proteins (e.g. pattern recognition, complement, cytokines, immune receptors, MHC, Siglecs). We also find evidence for positive selection in reproduction and chromosome segregation (e.g. centromere-associated CENPO, CENPT), apolipoproteins, smell/taste receptors and mitochondrial proteins. Focusing on the virus-host interaction, we retrieve most evolutionary conflicts known to influence antiviral activity (e.g. TRIM5, MAVS, SAMHD1, tetherin) and predict 70 novel cases through integration with virus-human interaction data. Protein structure analysis further identifies positive selection in the interaction interfaces between viruses and their cellular receptors (CD4-HIV; CD46-measles, adenoviruses; CD55-picornaviruses). Finally, primate PSG consistently show high sequence variation in human exomes, suggesting ongoing evolution. Our curated dataset of positive selection is a rich source for studying the genetics underlying human (antiviral) phenotypes. Procedures and data are available at https://github.com/robinvanderlee/positive-selection. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Population genomics identifies the origin and signatures of selection of Korean weedy rice

OpenAIRE

He, Qiang; Kim, Kyu?Won; Park, Yong?Jin

2016-01-01

Summary Weedy rice is the same biological species as cultivated rice (Oryza sativa); it is also a noxious weed infesting rice fields worldwide. Its formation and population?selective or ?adaptive signatures are poorly understood. In this study, we investigated the phylogenetics, population structure and signatures of selection of Korean weedy rice by determining the whole genomes of 30 weedy rice, 30 landrace rice and ten wild rice samples. The phylogenetic tree and results of ancestry infere...

Comparisons of single-stage and two-stage approaches to genomic selection.

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Schulz-Streeck, Torben; Ogutu, Joseph O; Piepho, Hans-Peter

2013-01-01

Genomic selection (GS) is a method for predicting breeding values of plants or animals using many molecular markers that is commonly implemented in two stages. In plant breeding the first stage usually involves computation of adjusted means for genotypes which are then used to predict genomic breeding values in the second stage. We compared two classical stage-wise approaches, which either ignore or approximate correlations among the means by a diagonal matrix, and a new method, to a single-stage analysis for GS using ridge regression best linear unbiased prediction (RR-BLUP). The new stage-wise method rotates (orthogonalizes) the adjusted means from the first stage before submitting them to the second stage. This makes the errors approximately independently and identically normally distributed, which is a prerequisite for many procedures that are potentially useful for GS such as machine learning methods (e.g. boosting) and regularized regression methods (e.g. lasso). This is illustrated in this paper using componentwise boosting. The componentwise boosting method minimizes squared error loss using least squares and iteratively and automatically selects markers that are most predictive of genomic breeding values. Results are compared with those of RR-BLUP using fivefold cross-validation. The new stage-wise approach with rotated means was slightly more similar to the single-stage analysis than the classical two-stage approaches based on non-rotated means for two unbalanced datasets. This suggests that rotation is a worthwhile pre-processing step in GS for the two-stage approaches for unbalanced datasets. Moreover, the predictive accuracy of stage-wise RR-BLUP was higher (5.0-6.1%) than that of componentwise boosting.

Resource allocation for maximizing prediction accuracy and genetic gain of genomic selection in plant breeding: a simulation experiment.

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Lorenz, Aaron J

2013-03-01

Allocating resources between population size and replication affects both genetic gain through phenotypic selection and quantitative trait loci detection power and effect estimation accuracy for marker-assisted selection (MAS). It is well known that because alleles are replicated across individuals in quantitative trait loci mapping and MAS, more resources should be allocated to increasing population size compared with phenotypic selection. Genomic selection is a form of MAS using all marker information simultaneously to predict individual genetic values for complex traits and has widely been found superior to MAS. No studies have explicitly investigated how resource allocation decisions affect success of genomic selection. My objective was to study the effect of resource allocation on response to MAS and genomic selection in a single biparental population of doubled haploid lines by using computer simulation. Simulation results were compared with previously derived formulas for the calculation of prediction accuracy under different levels of heritability and population size. Response of prediction accuracy to resource allocation strategies differed between genomic selection models (ridge regression best linear unbiased prediction [RR-BLUP], BayesCπ) and multiple linear regression using ordinary least-squares estimation (OLS), leading to different optimal resource allocation choices between OLS and RR-BLUP. For OLS, it was always advantageous to maximize population size at the expense of replication, but a high degree of flexibility was observed for RR-BLUP. Prediction accuracy of doubled haploid lines included in the training set was much greater than of those excluded from the training set, so there was little benefit to phenotyping only a subset of the lines genotyped. Finally, observed prediction accuracies in the simulation compared well to calculated prediction accuracies, indicating these theoretical formulas are useful for making resource allocation

Potential of Genomic Selection in Mass Selection Breeding of an Allogamous Crop: An Empirical Study to Increase Yield of Common Buckwheat

Directory of Open Access Journals (Sweden)

Shiori Yabe

2018-03-01

Full Text Available To evaluate the potential of genomic selection (GS, a selection experiment with GS and phenotypic selection (PS was performed in an allogamous crop, common buckwheat (Fagopyrum esculentum Moench. To indirectly select for seed yield per unit area, which cannot be measured on a single-plant basis, a selection index was constructed from seven agro-morphological traits measurable on a single plant basis. Over 3 years, we performed two GS and one PS cycles per year for improvement in the selection index. In GS, a prediction model was updated every year on the basis of genotypes of 14,598–50,000 markers and phenotypes. Plants grown from seeds derived from a series of generations of GS and PS populations were evaluated for the traits in the selection index and other yield-related traits. GS resulted in a 20.9% increase and PS in a 15.0% increase in the selection index in comparison with the initial population. Although the level of linkage disequilibrium in the breeding population was low, the target trait was improved with GS. Traits with higher weights in the selection index were improved more than those with lower weights, especially when prediction accuracy was high. No trait changed in an unintended direction in either GS or PS. The accuracy of genomic prediction models built in the first cycle decreased in the later cycles because the genetic bottleneck through the selection cycles changed linkage disequilibrium patterns in the breeding population. The present study emphasizes the importance of updating models in GS and demonstrates the potential of GS in mass selection of allogamous crop species, and provided a pilot example of successful application of GS to plant breeding.

AFLP genome scans suggest divergent selection on colour patterning in allopatric colour morphs of a cichlid fish.

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Mattersdorfer, Karin; Koblmüller, Stephan; Sefc, Kristina M

2012-07-01

Genome scan-based tests for selection are directly applicable to natural populations to study the genetic and evolutionary mechanisms behind phenotypic differentiation. We conducted AFLP genome scans in three distinct geographic colour morphs of the cichlid fish Tropheus moorii to assess whether the extant, allopatric colour pattern differentiation can be explained by drift and to identify markers mapping to genomic regions possibly involved in colour patterning. The tested morphs occupy adjacent shore sections in southern Lake Tanganyika and are separated from each other by major habitat barriers. The genome scans revealed significant genetic structure between morphs, but a very low proportion of loci fixed for alternative AFLP alleles in different morphs. This high level of polymorphism within morphs suggested that colour pattern differentiation did not result exclusively from neutral processes. Outlier detection methods identified six loci with excess differentiation in the comparison between a bluish and a yellow-blotch morph and five different outlier loci in comparisons of each of these morphs with a red morph. As population expansions and the genetic structure of Tropheus make the outlier approach prone to false-positive signals of selection, we examined the correlation between outlier locus alleles and colour phenotypes in a genetic and phenotypic cline between two morphs. Distributions of allele frequencies at one outlier locus were indeed consistent with linkage to a colour locus. Despite the challenges posed by population structure and demography, our results encourage the cautious application of genome scans to studies of divergent selection in subdivided and recently expanded populations. © 2012 Blackwell Publishing Ltd.

Genome-wide characterization of genetic variants and putative regions under selection in meat and egg-type chicken lines.

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Boschiero, Clarissa; Moreira, Gabriel Costa Monteiro; Gheyas, Almas Ara; Godoy, Thaís Fernanda; Gasparin, Gustavo; Mariani, Pilar Drummond Sampaio Corrêa; Paduan, Marcela; Cesar, Aline Silva Mello; Ledur, Mônica Corrêa; Coutinho, Luiz Lehmann

2018-01-25

Meat and egg-type chickens have been selected for several generations for different traits. Artificial and natural selection for different phenotypes can change frequency of genetic variants, leaving particular genomic footprints throghtout the genome. Thus, the aims of this study were to sequence 28 chickens from two Brazilian lines (meat and white egg-type) and use this information to characterize genome-wide genetic variations, identify putative regions under selection using Fst method, and find putative pathways under selection. A total of 13.93 million SNPs and 1.36 million INDELs were identified, with more variants detected from the broiler (meat-type) line. Although most were located in non-coding regions, we identified 7255 intolerant non-synonymous SNPs, 512 stopgain/loss SNPs, 1381 frameshift and 1094 non-frameshift INDELs that may alter protein functions. Genes harboring intolerant non-synonymous SNPs affected metabolic pathways related mainly to reproduction and endocrine systems in the white-egg layer line, and lipid metabolism and metabolic diseases in the broiler line. Fst analysis in sliding windows, using SNPs and INDELs separately, identified over 300 putative regions of selection overlapping with more than 250 genes. For the first time in chicken, INDEL variants were considered for selection signature analysis, showing high level of correlation in results between SNP and INDEL data. The putative regions of selection signatures revealed interesting candidate genes and pathways related to important phenotypic traits in chicken, such as lipid metabolism, growth, reproduction, and cardiac development. In this study, Fst method was applied to identify high confidence putative regions under selection, providing novel insights into selection footprints that can help elucidate the functional mechanisms underlying different phenotypic traits relevant to meat and egg-type chicken lines. In addition, we generated a large catalog of line-specific and common

Investigating Drought Tolerance in Chickpea Using Genome-Wide Association Mapping and Genomic Selection Based on Whole-Genome Resequencing Data

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Yongle Li

2018-02-01

Full Text Available Drought tolerance is a complex trait that involves numerous genes. Identifying key causal genes or linked molecular markers can facilitate the fast development of drought tolerant varieties. Using a whole-genome resequencing approach, we sequenced 132 chickpea varieties and advanced breeding lines and found more than 144,000 single nucleotide polymorphisms (SNPs. We measured 13 yield and yield-related traits in three drought-prone environments of Western Australia. The genotypic effects were significant for all traits, and many traits showed highly significant correlations, ranging from 0.83 between grain yield and biomass to -0.67 between seed weight and seed emergence rate. To identify candidate genes, the SNP and trait data were incorporated into the SUPER genome-wide association study (GWAS model, a modified version of the linear mixed model. We found that several SNPs from auxin-related genes, including auxin efflux carrier protein (PIN3, p-glycoprotein, and nodulin MtN21/EamA-like transporter, were significantly associated with yield and yield-related traits under drought-prone environments. We identified four genetic regions containing SNPs significantly associated with several different traits, which was an indication of pleiotropic effects. We also investigated the possibility of incorporating the GWAS results into a genomic selection (GS model, which is another approach to deal with complex traits. Compared to using all SNPs, application of the GS model using subsets of SNPs significantly associated with the traits under investigation increased the prediction accuracies of three yield and yield-related traits by more than twofold. This has important implication for implementing GS in plant breeding programs.

Genomic selection prediction accuracy in a perennial crop: case study of oil palm (Elaeis guineensis Jacq.).

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Cros, David; Denis, Marie; Sánchez, Leopoldo; Cochard, Benoit; Flori, Albert; Durand-Gasselin, Tristan; Nouy, Bruno; Omoré, Alphonse; Pomiès, Virginie; Riou, Virginie; Suryana, Edyana; Bouvet, Jean-Marc

2015-03-01

Genomic selection empirically appeared valuable for reciprocal recurrent selection in oil palm as it could account for family effects and Mendelian sampling terms, despite small populations and low marker density. Genomic selection (GS) can increase the genetic gain in plants. In perennial crops, this is expected mainly through shortened breeding cycles and increased selection intensity, which requires sufficient GS accuracy in selection candidates, despite often small training populations. Our objective was to obtain the first empirical estimate of GS accuracy in oil palm (Elaeis guineensis), the major world oil crop. We used two parental populations involved in conventional reciprocal recurrent selection (Deli and Group B) with 131 individuals each, genotyped with 265 SSR. We estimated within-population GS accuracies when predicting breeding values of non-progeny-tested individuals for eight yield traits. We used three methods to sample training sets and five statistical methods to estimate genomic breeding values. The results showed that GS could account for family effects and Mendelian sampling terms in Group B but only for family effects in Deli. Presumably, this difference between populations originated from their contrasting breeding history. The GS accuracy ranged from -0.41 to 0.94 and was positively correlated with the relationship between training and test sets. Training sets optimized with the so-called CDmean criterion gave the highest accuracies, ranging from 0.49 (pulp to fruit ratio in Group B) to 0.94 (fruit weight in Group B). The statistical methods did not affect the accuracy. Finally, Group B could be preselected for progeny tests by applying GS to key yield traits, therefore increasing the selection intensity. Our results should be valuable for breeding programs with small populations, long breeding cycles, or reduced effective size.

Impact of marker ascertainment bias on genomic selection accuracy and estimates of genetic diversity.

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Nicolas Heslot

Full Text Available Genome-wide molecular markers are often being used to evaluate genetic diversity in germplasm collections and for making genomic selections in breeding programs. To accurately predict phenotypes and assay genetic diversity, molecular markers should assay a representative sample of the polymorphisms in the population under study. Ascertainment bias arises when marker data is not obtained from a random sample of the polymorphisms in the population of interest. Genotyping-by-sequencing (GBS is rapidly emerging as a low-cost genotyping platform, even for the large, complex, and polyploid wheat (Triticum aestivum L. genome. With GBS, marker discovery and genotyping occur simultaneously, resulting in minimal ascertainment bias. The previous platform of choice for whole-genome genotyping in many species such as wheat was DArT (Diversity Array Technology and has formed the basis of most of our knowledge about cereals genetic diversity. This study compared GBS and DArT marker platforms for measuring genetic diversity and genomic selection (GS accuracy in elite U.S. soft winter wheat. From a set of 365 breeding lines, 38,412 single nucleotide polymorphism GBS markers were discovered and genotyped. The GBS SNPs gave a higher GS accuracy than 1,544 DArT markers on the same lines, despite 43.9% missing data. Using a bootstrap approach, we observed significantly more clustering of markers and ascertainment bias with DArT relative to GBS. The minor allele frequency distribution of GBS markers had a deficit of rare variants compared to DArT markers. Despite the ascertainment bias of the DArT markers, GS accuracy for three traits out of four was not significantly different when an equal number of markers were used for each platform. This suggests that the gain in accuracy observed using GBS compared to DArT markers was mainly due to a large increase in the number of markers available for the analysis.

Impact of Marker Ascertainment Bias on Genomic Selection Accuracy and Estimates of Genetic Diversity

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Heslot, Nicolas; Rutkoski, Jessica; Poland, Jesse; Jannink, Jean-Luc; Sorrells, Mark E.

2013-01-01

Genome-wide molecular markers are often being used to evaluate genetic diversity in germplasm collections and for making genomic selections in breeding programs. To accurately predict phenotypes and assay genetic diversity, molecular markers should assay a representative sample of the polymorphisms in the population under study. Ascertainment bias arises when marker data is not obtained from a random sample of the polymorphisms in the population of interest. Genotyping-by-sequencing (GBS) is rapidly emerging as a low-cost genotyping platform, even for the large, complex, and polyploid wheat (Triticum aestivum L.) genome. With GBS, marker discovery and genotyping occur simultaneously, resulting in minimal ascertainment bias. The previous platform of choice for whole-genome genotyping in many species such as wheat was DArT (Diversity Array Technology) and has formed the basis of most of our knowledge about cereals genetic diversity. This study compared GBS and DArT marker platforms for measuring genetic diversity and genomic selection (GS) accuracy in elite U.S. soft winter wheat. From a set of 365 breeding lines, 38,412 single nucleotide polymorphism GBS markers were discovered and genotyped. The GBS SNPs gave a higher GS accuracy than 1,544 DArT markers on the same lines, despite 43.9% missing data. Using a bootstrap approach, we observed significantly more clustering of markers and ascertainment bias with DArT relative to GBS. The minor allele frequency distribution of GBS markers had a deficit of rare variants compared to DArT markers. Despite the ascertainment bias of the DArT markers, GS accuracy for three traits out of four was not significantly different when an equal number of markers were used for each platform. This suggests that the gain in accuracy observed using GBS compared to DArT markers was mainly due to a large increase in the number of markers available for the analysis. PMID:24040295

MGS Radio Science Measurements of Atmospheric Dynamics on Mars

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Hinson, D. P.

2001-12-01

The Sun-synchronous, polar orbit of Mars Global Surveyor (MGS) provides frequent opportunities for radio occultation sounding of the neutral atmosphere. The basic result of each experiment is a profile of pressure and temperature versus planetocentric radius and geopotential. More than 4000 profiles were obtained during the 687-day mapping phase of the mission, and additional observations are underway. These measurements allow detailed characterization of planetary-scale dynamics, including stationary planetary (or Rossby) waves and transient waves produced by instability. For example, both types of dynamics were observed near 67° S during midwinter of the southern hemisphere (Ls=134° --160° ). Planetary waves are the most prominent dynamical feature in this subset of data. At zonal wave number s=1, both the temperature and geopotential fields tilt westward with increasing height, as expected for vertically-propagating planetary waves forced at the surface. The wave-2 structure is more nearly barotropic. The amplitude in geopotential height at Ls=150° increases from ~200 m near the surface to ~700 m at 10 Pa. The corresponding meridional wind speed increases from ~5 m s-1 near the surface to ~20 m s-1 at 10 Pa. Traveling ``baroclinic'' waves also appear intermittently during this interval. The dominant mode has a period of ~2 sols, s=3, and a peak amplitude of ~7 K at 300 Pa. Stong zonal variations in eddy amplitude signal the presence of a possible ``storm zone'' at 150° --330° E longitude. This talk will include other examples of these phenomena as well as comparisons with computer simulations by a Martian general circulation model (MGCM).

Ultrahigh-dimensional variable selection method for whole-genome gene-gene interaction analysis

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Ueki Masao

2012-05-01

Full Text Available Abstract Background Genome-wide gene-gene interaction analysis using single nucleotide polymorphisms (SNPs is an attractive way for identification of genetic components that confers susceptibility of human complex diseases. Individual hypothesis testing for SNP-SNP pairs as in common genome-wide association study (GWAS however involves difficulty in setting overall p-value due to complicated correlation structure, namely, the multiple testing problem that causes unacceptable false negative results. A large number of SNP-SNP pairs than sample size, so-called the large p small n problem, precludes simultaneous analysis using multiple regression. The method that overcomes above issues is thus needed. Results We adopt an up-to-date method for ultrahigh-dimensional variable selection termed the sure independence screening (SIS for appropriate handling of numerous number of SNP-SNP interactions by including them as predictor variables in logistic regression. We propose ranking strategy using promising dummy coding methods and following variable selection procedure in the SIS method suitably modified for gene-gene interaction analysis. We also implemented the procedures in a software program, EPISIS, using the cost-effective GPGPU (General-purpose computing on graphics processing units technology. EPISIS can complete exhaustive search for SNP-SNP interactions in standard GWAS dataset within several hours. The proposed method works successfully in simulation experiments and in application to real WTCCC (Wellcome Trust Case–control Consortium data. Conclusions Based on the machine-learning principle, the proposed method gives powerful and flexible genome-wide search for various patterns of gene-gene interaction.

Trait-specific long-term consequences of genomic selection in beef cattle.

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de Rezende Neves, Haroldo Henrique; Carvalheiro, Roberto; de Queiroz, Sandra Aidar

2018-02-01

Simulation studies allow addressing consequences of selection schemes, helping to identify effective strategies to enable genetic gain and maintain genetic diversity. The aim of this study was to evaluate the long-term impact of genomic selection (GS) in genetic progress and genetic diversity of beef cattle. Forward-in-time simulation generated a population with pattern of linkage disequilibrium close to that previously reported for real beef cattle populations. Different scenarios of GS and traditional pedigree-based BLUP (PBLUP) selection were simulated for 15 generations, mimicking selection for female reproduction and meat quality. For GS scenarios, an alternative selection criterion was simulated (wGBLUP), intended to enhance long-term gains by attributing more weight to favorable alleles with low frequency. GS allowed genetic progress up to 40% greater than PBLUP, for female reproduction and meat quality. The alternative criterion wGBLUP did not increase long-term response, although allowed reducing inbreeding rates and loss of favorable alleles. The results suggest that GS outperforms PBLUP when the selected trait is under less polygenic background and that attributing more weight to low-frequency favorable alleles can reduce inbreeding rates and loss of favorable alleles in GS.

Genetic Gain and Inbreeding from Genomic Selection in a Simulated Commercial Breeding Program for Perennial Ryegrass

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Zibei Lin

2016-03-01

Full Text Available Genomic selection (GS provides an attractive option for accelerating genetic gain in perennial ryegrass ( improvement given the long cycle times of most current breeding programs. The present study used simulation to investigate the level of genetic gain and inbreeding obtained from GS breeding strategies compared with traditional breeding strategies for key traits (persistency, yield, and flowering time. Base population genomes were simulated through random mating for 60,000 generations at an effective population size of 10,000. The degree of linkage disequilibrium (LD in the resulting population was compared with that obtained from empirical studies. Initial parental varieties were simulated to match diversity of current commercial cultivars. Genomic selection was designed to fit into a company breeding program at two selection points in the breeding cycle (spaced plants and miniplot. Genomic estimated breeding values (GEBVs for productivity traits were trained with phenotypes and genotypes from plots. Accuracy of GEBVs was 0.24 for persistency and 0.36 for yield for single plants, while for plots it was lower (0.17 and 0.19, respectively. Higher accuracy of GEBVs was obtained for flowering time (up to 0.7, partially as a result of the larger reference population size that was available from the clonal row stage. The availability of GEBVs permit a 4-yr reduction in cycle time, which led to at least a doubling and trebling genetic gain for persistency and yield, respectively, than the traditional program. However, a higher rate of inbreeding per cycle among varieties was also observed for the GS strategy.

Genetic Gain and Inbreeding from Genomic Selection in a Simulated Commercial Breeding Program for Perennial Ryegrass.

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Lin, Zibei; Cogan, Noel O I; Pembleton, Luke W; Spangenberg, German C; Forster, John W; Hayes, Ben J; Daetwyler, Hans D

2016-03-01

Genomic selection (GS) provides an attractive option for accelerating genetic gain in perennial ryegrass () improvement given the long cycle times of most current breeding programs. The present study used simulation to investigate the level of genetic gain and inbreeding obtained from GS breeding strategies compared with traditional breeding strategies for key traits (persistency, yield, and flowering time). Base population genomes were simulated through random mating for 60,000 generations at an effective population size of 10,000. The degree of linkage disequilibrium (LD) in the resulting population was compared with that obtained from empirical studies. Initial parental varieties were simulated to match diversity of current commercial cultivars. Genomic selection was designed to fit into a company breeding program at two selection points in the breeding cycle (spaced plants and miniplot). Genomic estimated breeding values (GEBVs) for productivity traits were trained with phenotypes and genotypes from plots. Accuracy of GEBVs was 0.24 for persistency and 0.36 for yield for single plants, while for plots it was lower (0.17 and 0.19, respectively). Higher accuracy of GEBVs was obtained for flowering time (up to 0.7), partially as a result of the larger reference population size that was available from the clonal row stage. The availability of GEBVs permit a 4-yr reduction in cycle time, which led to at least a doubling and trebling genetic gain for persistency and yield, respectively, than the traditional program. However, a higher rate of inbreeding per cycle among varieties was also observed for the GS strategy. Copyright © 2016 Crop Science Society of America.

Orchestrating the Selection and Packaging of Genomic RNA by Retroviruses: An Ensemble of Viral and Host Factors

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Kaddis Maldonado, Rebecca J.; Parent, Leslie J.

2016-01-01

Infectious retrovirus particles contain two copies of unspliced viral RNA that serve as the viral genome. Unspliced retroviral RNA is transcribed in the nucleus by the host RNA polymerase II and has three potential fates: (1) it can be spliced into subgenomic messenger RNAs (mRNAs) for the translation of viral proteins; or it can remain unspliced to serve as either (2) the mRNA for the translation of Gag and Gag–Pol; or (3) the genomic RNA (gRNA) that is packaged into virions. The Gag structural protein recognizes and binds the unspliced viral RNA to select it as a genome, which is selected in preference to spliced viral RNAs and cellular RNAs. In this review, we summarize the current state of understanding about how retroviral packaging is orchestrated within the cell and explore potential new mechanisms based on recent discoveries in the field. We discuss the cis-acting elements in the unspliced viral RNA and the properties of the Gag protein that are required for their interaction. In addition, we discuss the role of host factors in influencing the fate of the newly transcribed viral RNA, current models for how retroviruses distinguish unspliced viral mRNA from viral genomic RNA, and the possible subcellular sites of genomic RNA dimerization and selection by Gag. Although this review centers primarily on the wealth of data available for the alpharetrovirus Rous sarcoma virus, in which a discrete RNA packaging sequence has been identified, we have also summarized the cis- and trans-acting factors as well as the mechanisms governing gRNA packaging of other retroviruses for comparison. PMID:27657110

Genetic Study of the Manganese Use Efficiency Trait in Winter Barley (Hordeum vulgare L.) by Genome- Wide Association and Genomic Selection

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Leplat, Florian Jean Victor

Manganese (Mn) deficiency remains an unsolved nutritional problem affecting crop production worldwide. The tolerance to Mn limiting conditions, known as Mn efficiency, is a quantitative abiotic stress trait, generally controlled by several genes. However the underlying genetic background of Mn...... functionality in Mn dependent pathways and processes. In a the second step, a genuine statistical method to assist breeding programs in selecting new varieties, named Genomic Selection (GS), was applied. It was demonstrated that GS is an effective tool to be used in breeding programs for selecting more...

Sardinians genetic background explained by runs of homozygosity and genomic regions under positive selection.

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Cornelia Di Gaetano

Full Text Available The peculiar position of Sardinia in the Mediterranean sea has rendered its population an interesting biogeographical isolate. The aim of this study was to investigate the genetic population structure, as well as to estimate Runs of Homozygosity and regions under positive selection, using about 1.2 million single nucleotide polymorphisms genotyped in 1077 Sardinian individuals. Using four different methods--fixation index, inflation factor, principal component analysis and ancestry estimation--we were able to highlight, as expected for a genetic isolate, the high internal homogeneity of the island. Sardinians showed a higher percentage of genome covered by RoHs>0.5 Mb (F(RoH%0.5 when compared to peninsular Italians, with the only exception of the area surrounding Alghero. We furthermore identified 9 genomic regions showing signs of positive selection and, we re-captured many previously inferred signals. Other regions harbor novel candidate genes for positive selection, like TMEM252, or regions containing long non coding RNA. With the present study we confirmed the high genetic homogeneity of Sardinia that may be explained by the shared ancestry combined with the action of evolutionary forces.

A Scan for Positively Selected Genes in the Genomes of Humans and Chimpanzees

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Nielsen, Rasmus; Bustamente, Carlos; Clark, Andrew G.

2005-01-01

Since the divergence of humans and chimpanzees about 5 million years ago, these species have undergone a remarkable evolution with drastic divergence in anatomy and cognitive abilities. At the molecular level, despite the small overall magnitude of DNA sequence divergence, we might expect...... such evolutionary changes to leave a noticeable signature throughout the genome. We here compare 13,731 annotated genes from humans to their chimpanzee orthologs to identify genes that show evidence of positive selection. Many of the genes that present a signature of positive selection tend to be involved...

Variable selection models for genomic selection using whole-genome sequence data and singular value decomposition.

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Meuwissen, Theo H E; Indahl, Ulf G; Ødegård, Jørgen

2017-12-27

Non-linear Bayesian genomic prediction models such as BayesA/B/C/R involve iteration and mostly Markov chain Monte Carlo (MCMC) algorithms, which are computationally expensive, especially when whole-genome sequence (WGS) data are analyzed. Singular value decomposition (SVD) of the genotype matrix can facilitate genomic prediction in large datasets, and can be used to estimate marker effects and their prediction error variances (PEV) in a computationally efficient manner. Here, we developed, implemented, and evaluated a direct, non-iterative method for the estimation of marker effects for the BayesC genomic prediction model. The BayesC model assumes a priori that markers have normally distributed effects with probability [Formula: see text] and no effect with probability (1 - [Formula: see text]). Marker effects and their PEV are estimated by using SVD and the posterior probability of the marker having a non-zero effect is calculated. These posterior probabilities are used to obtain marker-specific effect variances, which are subsequently used to approximate BayesC estimates of marker effects in a linear model. A computer simulation study was conducted to compare alternative genomic prediction methods, where a single reference generation was used to estimate marker effects, which were subsequently used for 10 generations of forward prediction, for which accuracies were evaluated. SVD-based posterior probabilities of markers having non-zero effects were generally lower than MCMC-based posterior probabilities, but for some regions the opposite occurred, resulting in clear signals for QTL-rich regions. The accuracies of breeding values estimated using SVD- and MCMC-based BayesC analyses were similar across the 10 generations of forward prediction. For an intermediate number of generations (2 to 5) of forward prediction, accuracies obtained with the BayesC model tended to be slightly higher than accuracies obtained using the best linear unbiased prediction of SNP

Variation in Linked Selection and Recombination Drive Genomic Divergence during Allopatric Speciation of European and American Aspens.

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Wang, Jing; Street, Nathaniel R; Scofield, Douglas G; Ingvarsson, Pär K

2016-07-01

Despite the global economic and ecological importance of forest trees, the genomic basis of differential adaptation and speciation in tree species is still poorly understood. Populus tremula and Populus tremuloides are two of the most widespread tree species in the Northern Hemisphere. Using whole-genome re-sequencing data of 24 P. tremula and 22 P. tremuloides individuals, we find that the two species diverged ∼2.2-3.1 million years ago, coinciding with the severing of the Bering land bridge and the onset of dramatic climatic oscillations during the Pleistocene. Both species have experienced substantial population expansions following long-term declines after species divergence. We detect widespread and heterogeneous genomic differentiation between species, and in accordance with the expectation of allopatric speciation, coalescent simulations suggest that neutral evolutionary processes can account for most of the observed patterns of genetic differentiation. However, there is an excess of regions exhibiting extreme differentiation relative to those expected under demographic simulations, which is indicative of the action of natural selection. Overall genetic differentiation is negatively associated with recombination rate in both species, providing strong support for a role of linked selection in generating the heterogeneous genomic landscape of differentiation between species. Finally, we identify a number of candidate regions and genes that may have been subject to positive and/or balancing selection during the speciation process. © The Author 2016. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.

A comparison of statistical methods for genomic selection in a mice population

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Neves Haroldo HR

2012-11-01

Full Text Available Abstract Background The availability of high-density panels of SNP markers has opened new perspectives for marker-assisted selection strategies, such that genotypes for these markers are used to predict the genetic merit of selection candidates. Because the number of markers is often much larger than the number of phenotypes, marker effect estimation is not a trivial task. The objective of this research was to compare the predictive performance of ten different statistical methods employed in genomic selection, by analyzing data from a heterogeneous stock mice population. Results For the five traits analyzed (W6W: weight at six weeks, WGS: growth slope, BL: body length, %CD8+: percentage of CD8+ cells, CD4+/ CD8+: ratio between CD4+ and CD8+ cells, within-family predictions were more accurate than across-family predictions, although this superiority in accuracy varied markedly across traits. For within-family prediction, two kernel methods, Reproducing Kernel Hilbert Spaces Regression (RKHS and Support Vector Regression (SVR, were the most accurate for W6W, while a polygenic model also had comparable performance. A form of ridge regression assuming that all markers contribute to the additive variance (RR_GBLUP figured among the most accurate for WGS and BL, while two variable selection methods ( LASSO and Random Forest, RF had the greatest predictive abilities for %CD8+ and CD4+/ CD8+. RF, RKHS, SVR and RR_GBLUP outperformed the remainder methods in terms of bias and inflation of predictions. Conclusions Methods with large conceptual differences reached very similar predictive abilities and a clear re-ranking of methods was observed in function of the trait analyzed. Variable selection methods were more accurate than the remainder in the case of %CD8+ and CD4+/CD8+ and these traits are likely to be influenced by a smaller number of QTL than the remainder. Judged by their overall performance across traits and computational requirements, RR

Comparison of methods used to identify superior individuals in genomic selection in plant breeding.

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Bhering, L L; Junqueira, V S; Peixoto, L A; Cruz, C D; Laviola, B G

2015-09-10

The aim of this study was to evaluate different methods used in genomic selection, and to verify those that select a higher proportion of individuals with superior genotypes. Thus, F2 populations of different sizes were simulated (100, 200, 500, and 1000 individuals) with 10 replications each. These consisted of 10 linkage groups (LG) of 100 cM each, containing 100 equally spaced markers per linkage group, of which 200 controlled the characteristics, defined as the 20 initials of each LG. Genetic and phenotypic values were simulated assuming binomial distribution of effects for each LG, and the absence of dominance. For phenotypic values, heritabilities of 20, 50, and 80% were considered. To compare methodologies, the analysis processing time, coefficient of coincidence (selection of 5, 10, and 20% of superior individuals), and Spearman correlation between true genetic values, and the genomic values predicted by each methodology were determined. Considering the processing time, the three methodologies were statistically different, rrBLUP was the fastest, and Bayesian LASSO was the slowest. Spearman correlation revealed that the rrBLUP and GBLUP methodologies were equivalent, and Bayesian LASSO provided the lowest correlation values. Similar results were obtained in coincidence variables among the individuals selected, in which Bayesian LASSO differed statistically and presented a lower value than the other methodologies. Therefore, for the scenarios evaluated, rrBLUP is the best methodology for the selection of genetically superior individuals.

DETECTING SELECTION IN NATURAL POPULATIONS: MAKING SENSE OF GENOME SCANS AND TOWARDS ALTERNATIVE SOLUTIONS

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Haasl, Ryan J.; Payseur, Bret A.

2016-01-01

Genomewide scans for natural selection (GWSS) have become increasingly common over the last 15 years due to increased availability of genome-scale genetic data. Here, we report a representative survey of GWSS from 1999 to present and find that (i) between 1999 and 2009, 35 of 49 (71%) GWSS focused on human, while from 2010 to present, only 38 of 83 (46%) of GWSS focused on human, indicating increased focus on nonmodel organisms; (ii) the large majority of GWSS incorporate interpopulation or interspecific comparisons using, for example FST, cross-population extended haplotype homozygosity or the ratio of nonsynonymous to synonymous substitutions; (iii) most GWSS focus on detection of directional selection rather than other modes such as balancing selection; and (iv) in human GWSS, there is a clear shift after 2004 from microsatellite markers to dense SNP data. A survey of GWSS meant to identify loci positively selected in response to severe hypoxic conditions support an approach to GWSS in which a list of a priori candidate genes based on potential selective pressures are used to filter the list of significant hits a posteriori. We also discuss four frequently ignored determinants of genomic heterogeneity that complicate GWSS: mutation, recombination, selection and the genetic architecture of adaptive traits. We recommend that GWSS methodology should better incorporate aspects of genomewide heterogeneity using empirical estimates of relevant parameters and/or realistic, whole-chromosome simulations to improve interpretation of GWSS results. Finally, we argue that knowledge of potential selective agents improves interpretation of GWSS results and that new methods focused on correlations between environmental variables and genetic variation can help automate this approach. PMID:26224644

r2VIM: A new variable selection method for random forests in genome-wide association studies.

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Szymczak, Silke; Holzinger, Emily; Dasgupta, Abhijit; Malley, James D; Molloy, Anne M; Mills, James L; Brody, Lawrence C; Stambolian, Dwight; Bailey-Wilson, Joan E

2016-01-01

Machine learning methods and in particular random forests (RFs) are a promising alternative to standard single SNP analyses in genome-wide association studies (GWAS). RFs provide variable importance measures (VIMs) to rank SNPs according to their predictive power. However, in contrast to the established genome-wide significance threshold, no clear criteria exist to determine how many SNPs should be selected for downstream analyses. We propose a new variable selection approach, recurrent relative variable importance measure (r2VIM). Importance values are calculated relative to an observed minimal importance score for several runs of RF and only SNPs with large relative VIMs in all of the runs are selected as important. Evaluations on simulated GWAS data show that the new method controls the number of false-positives under the null hypothesis. Under a simple alternative hypothesis with several independent main effects it is only slightly less powerful than logistic regression. In an experimental GWAS data set, the same strong signal is identified while the approach selects none of the SNPs in an underpowered GWAS. The novel variable selection method r2VIM is a promising extension to standard RF for objectively selecting relevant SNPs in GWAS while controlling the number of false-positive results.

The Slow:Fast substitution ratio reveals changing patterns of natural selection in gamma-proteobacterial genomes

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Alm, Eric; Shapiro, B. Jesse

2009-04-15

Different microbial species are thought to occupy distinct ecological niches, subjecting each species to unique selective constraints, which may leave a recognizable signal in their genomes. Thus, it may be possible to extract insight into the genetic basis of ecological differences among lineages by identifying unusual patterns of substitutions in orthologous gene or protein sequences. We use the ratio of substitutions in slow versus fast-evolving sites (nucleotides in DNA, or amino acids in protein sequence) to quantify deviations from the typical pattern of selective constraint observed across bacterial lineages. We propose that elevated S:F in one branch (an excess of slow-site substitutions) can indicate a functionally-relevant change, due to either positive selection or relaxed evolutionary constraint. In a genome-wide comparative study of gamma-proteobacterial proteins, we find that cell-surface proteins involved with motility and secretion functions often have high S:F ratios, while information-processing genes do not. Change in evolutionary constraints in some species is evidenced by increased S:F ratios within functionally-related sets of genes (e.g., energy production in Pseudomonas fluorescens), while other species apparently evolve mostly by drift (e.g., uniformly elevated S:F across most genes in Buchnera spp.). Overall, S:F reveals several species-specific, protein-level changes with potential functional/ecological importance. As microbial genome projects yield more species-rich gene-trees, the S:F ratio will become an increasingly powerful tool for uncovering functional genetic differences among species.

Genomic selection and association mapping in rice (Oryza sativa): effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines.

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Spindel, Jennifer; Begum, Hasina; Akdemir, Deniz; Virk, Parminder; Collard, Bertrand; Redoña, Edilberto; Atlin, Gary; Jannink, Jean-Luc; McCouch, Susan R

2015-02-01

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline.

Genomic selection and association mapping in rice (Oryza sativa: effect of trait genetic architecture, training population composition, marker number and statistical model on accuracy of rice genomic selection in elite, tropical rice breeding lines.

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Jennifer Spindel

2015-02-01

Full Text Available Genomic Selection (GS is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline.

Genomic Selection and Association Mapping in Rice (Oryza sativa): Effect of Trait Genetic Architecture, Training Population Composition, Marker Number and Statistical Model on Accuracy of Rice Genomic Selection in Elite, Tropical Rice Breeding Lines

Science.gov (United States)

Spindel, Jennifer; Begum, Hasina; Akdemir, Deniz; Virk, Parminder; Collard, Bertrand; Redoña, Edilberto; Atlin, Gary; Jannink, Jean-Luc; McCouch, Susan R.

2015-01-01

Genomic Selection (GS) is a new breeding method in which genome-wide markers are used to predict the breeding value of individuals in a breeding population. GS has been shown to improve breeding efficiency in dairy cattle and several crop plant species, and here we evaluate for the first time its efficacy for breeding inbred lines of rice. We performed a genome-wide association study (GWAS) in conjunction with five-fold GS cross-validation on a population of 363 elite breeding lines from the International Rice Research Institute's (IRRI) irrigated rice breeding program and herein report the GS results. The population was genotyped with 73,147 markers using genotyping-by-sequencing. The training population, statistical method used to build the GS model, number of markers, and trait were varied to determine their effect on prediction accuracy. For all three traits, genomic prediction models outperformed prediction based on pedigree records alone. Prediction accuracies ranged from 0.31 and 0.34 for grain yield and plant height to 0.63 for flowering time. Analyses using subsets of the full marker set suggest that using one marker every 0.2 cM is sufficient for genomic selection in this collection of rice breeding materials. RR-BLUP was the best performing statistical method for grain yield where no large effect QTL were detected by GWAS, while for flowering time, where a single very large effect QTL was detected, the non-GS multiple linear regression method outperformed GS models. For plant height, in which four mid-sized QTL were identified by GWAS, random forest produced the most consistently accurate GS models. Our results suggest that GS, informed by GWAS interpretations of genetic architecture and population structure, could become an effective tool for increasing the efficiency of rice breeding as the costs of genotyping continue to decline. PMID:25689273

Genome-wide scan of 29,141 African Americans finds no evidence of directional selection since admixture.

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Bhatia, Gaurav; Tandon, Arti; Patterson, Nick; Aldrich, Melinda C; Ambrosone, Christine B; Amos, Christopher; Bandera, Elisa V; Berndt, Sonja I; Bernstein, Leslie; Blot, William J; Bock, Cathryn H; Caporaso, Neil; Casey, Graham; Deming, Sandra L; Diver, W Ryan; Gapstur, Susan M; Gillanders, Elizabeth M; Harris, Curtis C; Henderson, Brian E; Ingles, Sue A; Isaacs, William; De Jager, Phillip L; John, Esther M; Kittles, Rick A; Larkin, Emma; McNeill, Lorna H; Millikan, Robert C; Murphy, Adam; Neslund-Dudas, Christine; Nyante, Sarah; Press, Michael F; Rodriguez-Gil, Jorge L; Rybicki, Benjamin A; Schwartz, Ann G; Signorello, Lisa B; Spitz, Margaret; Strom, Sara S; Tucker, Margaret A; Wiencke, John K; Witte, John S; Wu, Xifeng; Yamamura, Yuko; Zanetti, Krista A; Zheng, Wei; Ziegler, Regina G; Chanock, Stephen J; Haiman, Christopher A; Reich, David; Price, Alkes L

2014-10-02

The extent of recent selection in admixed populations is currently an unresolved question. We scanned the genomes of 29,141 African Americans and failed to find any genome-wide-significant deviations in local ancestry, indicating no evidence of selection influencing ancestry after admixture. A recent analysis of data from 1,890 African Americans reported that there was evidence of selection in African Americans after their ancestors left Africa, both before and after admixture. Selection after admixture was reported on the basis of deviations in local ancestry, and selection before admixture was reported on the basis of allele-frequency differences between African Americans and African populations. The local-ancestry deviations reported by the previous study did not replicate in our very large sample, and we show that such deviations were expected purely by chance, given the number of hypotheses tested. We further show that the previous study's conclusion of selection in African Americans before admixture is also subject to doubt. This is because the FST statistics they used were inflated and because true signals of unusual allele-frequency differences between African Americans and African populations would be best explained by selection that occurred in Africa prior to migration to the Americas. Copyright © 2014 The American Society of Human Genetics. Published by Elsevier Inc. All rights reserved.

Genome-wide genetic diversity and differentially selected regions among Suffolk, Rambouillet, Columbia, Polypay, and Targhee sheep.

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Lifan Zhang

Full Text Available Sheep are among the major economically important livestock species worldwide because the animals produce milk, wool, skin, and meat. In the present study, the Illumina OvineSNP50 BeadChip was used to investigate genetic diversity and genome selection among Suffolk, Rambouillet, Columbia, Polypay, and Targhee sheep breeds from the United States. After quality-control filtering of SNPs (single nucleotide polymorphisms, we used 48,026 SNPs, including 46,850 SNPs on autosomes that were in Hardy-Weinberg equilibrium and 1,176 SNPs on chromosome × for analysis. Phylogenetic analysis based on all 46,850 SNPs clearly separated Suffolk from Rambouillet, Columbia, Polypay, and Targhee, which was not surprising as Rambouillet contributed to the synthesis of the later three breeds. Based on pair-wise estimates of F(ST, significant genetic differentiation appeared between Suffolk and Rambouillet (F(ST = 0.1621, while Rambouillet and Targhee had the closest relationship (F(ST = 0.0681. A scan of the genome revealed 45 and 41 differentially selected regions (DSRs between Suffolk and Rambouillet and among Rambouillet-related breed populations, respectively. Our data indicated that regions 13 and 24 between Suffolk and Rambouillet might be good candidates for evaluating breed differences. Furthermore, ovine genome v3.1 assembly was used as reference to link functionally known homologous genes to economically important traits covered by these differentially selected regions. In brief, our present study provides a comprehensive genome-wide view on within- and between-breed genetic differentiation, biodiversity, and evolution among Suffolk, Rambouillet, Columbia, Polypay, and Targhee sheep breeds. These results may provide new guidance for the synthesis of new breeds with different breeding objectives.

Minipig and beagle animal model genomes aid species selection in pharmaceutical discovery and development

Energy Technology Data Exchange (ETDEWEB)

Vamathevan, Jessica J., E-mail: jessica.j.vamathevan@gsk.com [Computational Biology, Quantitative Sciences, GlaxoSmithKline, Stevenage (United Kingdom); Hall, Matthew D.; Hasan, Samiul; Woollard, Peter M. [Computational Biology, Quantitative Sciences, GlaxoSmithKline, Stevenage (United Kingdom); Xu, Meng; Yang, Yulan; Li, Xin; Wang, Xiaoli [BGI-Shenzen, Shenzhen (China); Kenny, Steve [Safety Assessment, PTS, GlaxoSmithKline, Ware (United Kingdom); Brown, James R. [Computational Biology, Quantitative Sciences, GlaxoSmithKline, Collegeville, PA (United States); Huxley-Jones, Julie [UK Platform Technology Sciences (PTS) Operations and Planning, PTS, GlaxoSmithKline, Stevenage (United Kingdom); Lyon, Jon; Haselden, John [Safety Assessment, PTS, GlaxoSmithKline, Ware (United Kingdom); Min, Jiumeng [BGI-Shenzen, Shenzhen (China); Sanseau, Philippe [Computational Biology, Quantitative Sciences, GlaxoSmithKline, Stevenage (United Kingdom)

2013-07-15

Improving drug attrition remains a challenge in pharmaceutical discovery and development. A major cause of early attrition is the demonstration of safety signals which can negate any therapeutic index previously established. Safety attrition needs to be put in context of clinical translation (i.e. human relevance) and is negatively impacted by differences between animal models and human. In order to minimize such an impact, an earlier assessment of pharmacological target homology across animal model species will enhance understanding of the context of animal safety signals and aid species selection during later regulatory toxicology studies. Here we sequenced the genomes of the Sus scrofa Göttingen minipig and the Canis familiaris beagle, two widely used animal species in regulatory safety studies. Comparative analyses of these new genomes with other key model organisms, namely mouse, rat, cynomolgus macaque, rhesus macaque, two related breeds (S. scrofa Duroc and C. familiaris boxer) and human reveal considerable variation in gene content. Key genes in toxicology and metabolism studies, such as the UGT2 family, CYP2D6, and SLCO1A2, displayed unique duplication patterns. Comparisons of 317 known human drug targets revealed surprising variation such as species-specific positive selection, duplication and higher occurrences of pseudogenized targets in beagle (41 genes) relative to minipig (19 genes). These data will facilitate the more effective use of animals in biomedical research. - Highlights: • Genomes of the minipig and beagle dog, two species used in pharmaceutical studies. • First systematic comparative genome analysis of human and six experimental animals. • Key drug toxicology genes display unique duplication patterns across species. • Comparison of 317 drug targets show species-specific evolutionary patterns.

Minipig and beagle animal model genomes aid species selection in pharmaceutical discovery and development

International Nuclear Information System (INIS)

Vamathevan, Jessica J.; Hall, Matthew D.; Hasan, Samiul; Woollard, Peter M.; Xu, Meng; Yang, Yulan; Li, Xin; Wang, Xiaoli; Kenny, Steve; Brown, James R.; Huxley-Jones, Julie; Lyon, Jon; Haselden, John; Min, Jiumeng; Sanseau, Philippe

2013-01-01

Improving drug attrition remains a challenge in pharmaceutical discovery and development. A major cause of early attrition is the demonstration of safety signals which can negate any therapeutic index previously established. Safety attrition needs to be put in context of clinical translation (i.e. human relevance) and is negatively impacted by differences between animal models and human. In order to minimize such an impact, an earlier assessment of pharmacological target homology across animal model species will enhance understanding of the context of animal safety signals and aid species selection during later regulatory toxicology studies. Here we sequenced the genomes of the Sus scrofa Göttingen minipig and the Canis familiaris beagle, two widely used animal species in regulatory safety studies. Comparative analyses of these new genomes with other key model organisms, namely mouse, rat, cynomolgus macaque, rhesus macaque, two related breeds (S. scrofa Duroc and C. familiaris boxer) and human reveal considerable variation in gene content. Key genes in toxicology and metabolism studies, such as the UGT2 family, CYP2D6, and SLCO1A2, displayed unique duplication patterns. Comparisons of 317 known human drug targets revealed surprising variation such as species-specific positive selection, duplication and higher occurrences of pseudogenized targets in beagle (41 genes) relative to minipig (19 genes). These data will facilitate the more effective use of animals in biomedical research. - Highlights: • Genomes of the minipig and beagle dog, two species used in pharmaceutical studies. • First systematic comparative genome analysis of human and six experimental animals. • Key drug toxicology genes display unique duplication patterns across species. • Comparison of 317 drug targets show species-specific evolutionary patterns

Genome-Wide Specific Selection in Three Domestic Sheep Breeds.

Directory of Open Access Journals (Sweden)

Huihua Wang

Full Text Available Commercial sheep raised for mutton grow faster than traditional Chinese sheep breeds. Here, we aimed to evaluate genetic selection among three different types of sheep breed: two well-known commercial mutton breeds and one indigenous Chinese breed.We first combined locus-specific branch lengths and di statistical methods to detect candidate regions targeted by selection in the three different populations. The results showed that the genetic distances reached at least medium divergence for each pairwise combination. We found these two methods were highly correlated, and identified many growth-related candidate genes undergoing artificial selection. For production traits, APOBR and FTO are associated with body mass index. For meat traits, ALDOA, STK32B and FAM190A are related to marbling. For reproduction traits, CCNB2 and SLC8A3 affect oocyte development. We also found two well-known genes, GHR (which affects meat production and quality and EDAR (associated with hair thickness were associated with German mutton merino sheep. Furthermore, four genes (POL, RPL7, MSL1 and SHISA9 were associated with pre-weaning gain in our previous genome-wide association study.Our results indicated that combine locus-specific branch lengths and di statistical approaches can reduce the searching ranges for specific selection. And we got many credible candidate genes which not only confirm the results of previous reports, but also provide a suite of novel candidate genes in defined breeds to guide hybridization breeding.

Genome-Wide Specific Selection in Three Domestic Sheep Breeds.

Science.gov (United States)

Wang, Huihua; Zhang, Li; Cao, Jiaxve; Wu, Mingming; Ma, Xiaomeng; Liu, Zhen; Liu, Ruizao; Zhao, Fuping; Wei, Caihong; Du, Lixin

2015-01-01

Commercial sheep raised for mutton grow faster than traditional Chinese sheep breeds. Here, we aimed to evaluate genetic selection among three different types of sheep breed: two well-known commercial mutton breeds and one indigenous Chinese breed. We first combined locus-specific branch lengths and di statistical methods to detect candidate regions targeted by selection in the three different populations. The results showed that the genetic distances reached at least medium divergence for each pairwise combination. We found these two methods were highly correlated, and identified many growth-related candidate genes undergoing artificial selection. For production traits, APOBR and FTO are associated with body mass index. For meat traits, ALDOA, STK32B and FAM190A are related to marbling. For reproduction traits, CCNB2 and SLC8A3 affect oocyte development. We also found two well-known genes, GHR (which affects meat production and quality) and EDAR (associated with hair thickness) were associated with German mutton merino sheep. Furthermore, four genes (POL, RPL7, MSL1 and SHISA9) were associated with pre-weaning gain in our previous genome-wide association study. Our results indicated that combine locus-specific branch lengths and di statistical approaches can reduce the searching ranges for specific selection. And we got many credible candidate genes which not only confirm the results of previous reports, but also provide a suite of novel candidate genes in defined breeds to guide hybridization breeding.

Genomic Selection for Quantitative Adult Plant Stem Rust Resistance in Wheat

Directory of Open Access Journals (Sweden)

Jessica E. Rutkoski

2014-11-01

Full Text Available Quantitative adult plant resistance (APR to stem rust ( f. sp. is an important breeding target in wheat ( L. and a potential target for genomic selection (GS. To evaluate the relative importance of known APR loci in applying GS, we characterized a set of CIMMYT germplasm at important APR loci and on a genome-wide profile using genotyping-by-sequencing (GBS. Using this germplasm, we describe the genetic architecture and evaluate prediction models for APR using data from the international Ug99 stem rust screening nurseries. Prediction models incorporating markers linked to important APR loci and seedling phenotype scores as fixed effects were evaluated along with the classic prediction models: Multiple linear regression (MLR, Genomic best linear unbiased prediction (G-BLUP, Bayesian Lasso (BL, and Bayes Cπ (BCπ. We found the region to play an important role in APR in this germplasm. A model using linked markers as fixed effects in G-BLUP was more accurate than MLR with linked markers (-value = 0.12, and ordinary G-BLUP (-value = 0.15. Incorporating seedling phenotype information as fixed effects in G-BLUP did not consistently increase accuracy. Overall, levels of prediction accuracy found in this study indicate that GS can be effectively applied to improve stem rust APR in this germplasm, and if genotypes at linked markers are available, modeling these genotypes as fixed effects could lead to better predictions.

Trait variation and genetic diversity in a banana genomic selection training population

Science.gov (United States)

Nyine, Moses; Uwimana, Brigitte; Swennen, Rony; Batte, Michael; Brown, Allan; Christelová, Pavla; Hřibová, Eva; Lorenzen, Jim

2017-01-01

Banana (Musa spp.) is an important crop in the African Great Lakes region in terms of income and food security, with the highest per capita consumption worldwide. Pests, diseases and climate change hamper sustainable production of bananas. New breeding tools with increased crossbreeding efficiency are being investigated to breed for resistant, high yielding hybrids of East African Highland banana (EAHB). These include genomic selection (GS), which will benefit breeding through increased genetic gain per unit time. Understanding trait variation and the correlation among economically important traits is an essential first step in the development and selection of suitable GS models for banana. In this study, we tested the hypothesis that trait variations in bananas are not affected by cross combination, cycle, field management and their interaction with genotype. A training population created using EAHB breeding material and its progeny was phenotyped in two contrasting conditions. A high level of correlation among vegetative and yield related traits was observed. Therefore, genomic selection models could be developed for traits that are easily measured. It is likely that the predictive ability of traits that are difficult to phenotype will be similar to less difficult traits they are highly correlated with. Genotype response to cycle and field management practices varied greatly with respect to traits. Yield related traits accounted for 31–35% of principal component variation under low and high input field management conditions. Resistance to Black Sigatoka was stable across cycles but varied under different field management depending on the genotype. The best cross combination was 1201K-1xSH3217 based on selection response (R) of hybrids. Genotyping using simple sequence repeat (SSR) markers revealed that the training population was genetically diverse, reflecting a complex pedigree background, which was mostly influenced by the male parents. PMID:28586365

Trait variation and genetic diversity in a banana genomic selection training population.

Directory of Open Access Journals (Sweden)

Moses Nyine

Full Text Available Banana (Musa spp. is an important crop in the African Great Lakes region in terms of income and food security, with the highest per capita consumption worldwide. Pests, diseases and climate change hamper sustainable production of bananas. New breeding tools with increased crossbreeding efficiency are being investigated to breed for resistant, high yielding hybrids of East African Highland banana (EAHB. These include genomic selection (GS, which will benefit breeding through increased genetic gain per unit time. Understanding trait variation and the correlation among economically important traits is an essential first step in the development and selection of suitable GS models for banana. In this study, we tested the hypothesis that trait variations in bananas are not affected by cross combination, cycle, field management and their interaction with genotype. A training population created using EAHB breeding material and its progeny was phenotyped in two contrasting conditions. A high level of correlation among vegetative and yield related traits was observed. Therefore, genomic selection models could be developed for traits that are easily measured. It is likely that the predictive ability of traits that are difficult to phenotype will be similar to less difficult traits they are highly correlated with. Genotype response to cycle and field management practices varied greatly with respect to traits. Yield related traits accounted for 31-35% of principal component variation under low and high input field management conditions. Resistance to Black Sigatoka was stable across cycles but varied under different field management depending on the genotype. The best cross combination was 1201K-1xSH3217 based on selection response (R of hybrids. Genotyping using simple sequence repeat (SSR markers revealed that the training population was genetically diverse, reflecting a complex pedigree background, which was mostly influenced by the male parents.

Trait variation and genetic diversity in a banana genomic selection training population.

Science.gov (United States)

Nyine, Moses; Uwimana, Brigitte; Swennen, Rony; Batte, Michael; Brown, Allan; Christelová, Pavla; Hřibová, Eva; Lorenzen, Jim; Doležel, Jaroslav

2017-01-01

Banana (Musa spp.) is an important crop in the African Great Lakes region in terms of income and food security, with the highest per capita consumption worldwide. Pests, diseases and climate change hamper sustainable production of bananas. New breeding tools with increased crossbreeding efficiency are being investigated to breed for resistant, high yielding hybrids of East African Highland banana (EAHB). These include genomic selection (GS), which will benefit breeding through increased genetic gain per unit time. Understanding trait variation and the correlation among economically important traits is an essential first step in the development and selection of suitable GS models for banana. In this study, we tested the hypothesis that trait variations in bananas are not affected by cross combination, cycle, field management and their interaction with genotype. A training population created using EAHB breeding material and its progeny was phenotyped in two contrasting conditions. A high level of correlation among vegetative and yield related traits was observed. Therefore, genomic selection models could be developed for traits that are easily measured. It is likely that the predictive ability of traits that are difficult to phenotype will be similar to less difficult traits they are highly correlated with. Genotype response to cycle and field management practices varied greatly with respect to traits. Yield related traits accounted for 31-35% of principal component variation under low and high input field management conditions. Resistance to Black Sigatoka was stable across cycles but varied under different field management depending on the genotype. The best cross combination was 1201K-1xSH3217 based on selection response (R) of hybrids. Genotyping using simple sequence repeat (SSR) markers revealed that the training population was genetically diverse, reflecting a complex pedigree background, which was mostly influenced by the male parents.

Genome-wide association data classification and SNPs selection using two-stage quality-based Random Forests.

Science.gov (United States)

Nguyen, Thanh-Tung; Huang, Joshua; Wu, Qingyao; Nguyen, Thuy; Li, Mark

2015-01-01

Single-nucleotide polymorphisms (SNPs) selection and identification are the most important tasks in Genome-wide association data analysis. The problem is difficult because genome-wide association data is very high dimensional and a large portion of SNPs in the data is irrelevant to the disease. Advanced machine learning methods have been successfully used in Genome-wide association studies (GWAS) for identification of genetic variants that have relatively big effects in some common, complex diseases. Among them, the most successful one is Random Forests (RF). Despite of performing well in terms of prediction accuracy in some data sets with moderate size, RF still suffers from working in GWAS for selecting informative SNPs and building accurate prediction models. In this paper, we propose to use a new two-stage quality-based sampling method in random forests, named ts-RF, for SNP subspace selection for GWAS. The method first applies p-value assessment to find a cut-off point that separates informative and irrelevant SNPs in two groups. The informative SNPs group is further divided into two sub-groups: highly informative and weak informative SNPs. When sampling the SNP subspace for building trees for the forest, only those SNPs from the two sub-groups are taken into account. The feature subspaces always contain highly informative SNPs when used to split a node at a tree. This approach enables one to generate more accurate trees with a lower prediction error, meanwhile possibly avoiding overfitting. It allows one to detect interactions of multiple SNPs with the diseases, and to reduce the dimensionality and the amount of Genome-wide association data needed for learning the RF model. Extensive experiments on two genome-wide SNP data sets (Parkinson case-control data comprised of 408,803 SNPs and Alzheimer case-control data comprised of 380,157 SNPs) and 10 gene data sets have demonstrated that the proposed model significantly reduced prediction errors and outperformed

Genomic insights into natural selection in the common loon (Gavia immer): evidence for aquatic adaptation.

Science.gov (United States)

Gayk, Zach G; Le Duc, Diana; Horn, Jeffrey; Lindsay, Alec R

2018-04-27

The common loon (Gavia immer) is one of five species that comprise the avian order Gaviiformes. Loons are specialized divers, reaching depths up to 60 m while staying submerged for intervals up to three minutes. In this study we used comparative genomics to investigate the genetic basis of the common loon adaptations to its ecological niche. We used Illumina short read DNA sequence data from a female bird to produce a draft assembly of the common loon (Gavia immer) genome. We identified 14,169 common loon genes, which based on well-resolved avian genomes, represent approximately 80.7% of common loon genes. Evolutionary analyses between common loon and Adelie penguin (Pygoscelis adeliae), red-throated loon (Gavia stellata), chicken (Gallus gallus), northern fulmar (Fulmarus glacialis), and rock pigeon (Columba livia) show 164 positively selected genes in common and red-throated loons. These genes were enriched for a number of protein classes, including those involved in muscle tissue development, immunoglobulin function, hemoglobin iron binding, G-protein coupled receptors, and ATP metabolism. Signatures of positive selection in these areas suggest the genus Gavia may have adapted for underwater diving by modulating their oxidative and metabolic pathways. While more research is required, these adaptations likely result in (1) compensations in oxygen respiration and energetic metabolism, (2) low-light visual acuity, and (3) elevated solute exchange. This work represents the first effort to understand the genomic adaptations of the common loon as well as other Gavia and may have implications for subsequent studies that target particular genes for loon population genetic, ecological or conservation studies.

Ridge Regression and Other Kernels for Genomic Selection with R Package rrBLUP

Directory of Open Access Journals (Sweden)

Jeffrey B. Endelman

2011-11-01

Full Text Available Many important traits in plant breeding are polygenic and therefore recalcitrant to traditional marker-assisted selection. Genomic selection addresses this complexity by including all markers in the prediction model. A key method for the genomic prediction of breeding values is ridge regression (RR, which is equivalent to best linear unbiased prediction (BLUP when the genetic covariance between lines is proportional to their similarity in genotype space. This additive model can be broadened to include epistatic effects by using other kernels, such as the Gaussian, which represent inner products in a complex feature space. To facilitate the use of RR and nonadditive kernels in plant breeding, a new software package for R called rrBLUP has been developed. At its core is a fast maximum-likelihood algorithm for mixed models with a single variance component besides the residual error, which allows for efficient prediction with unreplicated training data. Use of the rrBLUP software is demonstrated through several examples, including the identification of optimal crosses based on superior progeny value. In cross-validation tests, the prediction accuracy with nonadditive kernels was significantly higher than RR for wheat ( L. grain yield but equivalent for several maize ( L. traits.

Genome Sequencing Reveals Loci under Artificial Selection that Underlie Disease Phenotypes in the Laboratory Rat

NARCIS (Netherlands)

Atanur, Santosh S.; Diaz, Ana Garcia; Maratou, Klio; Sarkis, Allison; Rotival, Maxime; Game, Laurence; Tschannen, Michael R.; Kaisaki, Pamela J.; Otto, Georg W.; Ma, Man Chun John; Keane, Thomas M.; Hummel, Oliver; Saar, Kathrin; Chen, Wei; Guryev, Victor; Gopalakrishnan, Kathirvel; Garrett, Michael R.; Joe, Bina; Citterio, Lorena; Bianchi, Giuseppe; McBride, Martin; Dominiczak, Anna; Adams, David J.; Serikawa, Tadao; Flicek, Paul; Cuppen, Edwin; Hubner, Norbert; Petretto, Enrico; Gauguier, Dominique; Kwitek, Anne; Jacob, Howard; Aitman, Timothy J.

2013-01-01

Large numbers of inbred laboratory rat strains have been developed for a range of complex disease phenotypes. To gain insights into the evolutionary pressures underlying selection for these phenotypes, we sequenced the genomes of 27 rat strains, including 11 models of hypertension, diabetes, and

Exploring evidence of positive selection reveals genetic basis of meat quality traits in Berkshire pigs through whole genome sequencing.

Science.gov (United States)

Jeong, Hyeonsoo; Song, Ki-Duk; Seo, Minseok; Caetano-Anollés, Kelsey; Kim, Jaemin; Kwak, Woori; Oh, Jae-Don; Kim, EuiSoo; Jeong, Dong Kee; Cho, Seoae; Kim, Heebal; Lee, Hak-Kyo

2015-08-20

Natural and artificial selection following domestication has led to the existence of more than a hundred pig breeds, as well as incredible variation in phenotypic traits. Berkshire pigs are regarded as having superior meat quality compared to other breeds. As the meat production industry seeks selective breeding approaches to improve profitable traits such as meat quality, information about genetic determinants of these traits is in high demand. However, most of the studies have been performed using trained sensory panel analysis without investigating the underlying genetic factors. Here we investigate the relationship between genomic composition and this phenotypic trait by scanning for signatures of positive selection in whole-genome sequencing data. We generated genomes of 10 Berkshire pigs at a total of 100.6 coverage depth, using the Illumina Hiseq2000 platform. Along with the genomes of 11 Landrace and 13 Yorkshire pigs, we identified genomic variants of 18.9 million SNVs and 3.4 million Indels in the mapped regions. We identified several associated genes related to lipid metabolism, intramuscular fatty acid deposition, and muscle fiber type which attribute to pork quality (TG, FABP1, AKIRIN2, GLP2R, TGFBR3, JPH3, ICAM2, and ERN1) by applying between population statistical tests (XP-EHH and XP-CLR). A statistical enrichment test was also conducted to detect breed specific genetic variation. In addition, de novo short sequence read assembly strategy identified several candidate genes (SLC25A14, IGF1, PI4KA, CACNA1A) as also contributing to lipid metabolism. Results revealed several candidate genes involved in Berkshire meat quality; most of these genes are involved in lipid metabolism and intramuscular fat deposition. These results can provide a basis for future research on the genomic characteristics of Berkshire pigs.

Genome-wide detection and characterization of positive selection in human populations.

Science.gov (United States)

Sabeti, Pardis C; Varilly, Patrick; Fry, Ben; Lohmueller, Jason; Hostetter, Elizabeth; Cotsapas, Chris; Xie, Xiaohui; Byrne, Elizabeth H; McCarroll, Steven A; Gaudet, Rachelle; Schaffner, Stephen F; Lander, Eric S; Frazer, Kelly A; Ballinger, Dennis G; Cox, David R; Hinds, David A; Stuve, Laura L; Gibbs, Richard A; Belmont, John W; Boudreau, Andrew; Hardenbol, Paul; Leal, Suzanne M; Pasternak, Shiran; Wheeler, David A; Willis, Thomas D; Yu, Fuli; Yang, Huanming; Zeng, Changqing; Gao, Yang; Hu, Haoran; Hu, Weitao; Li, Chaohua; Lin, Wei; Liu, Siqi; Pan, Hao; Tang, Xiaoli; Wang, Jian; Wang, Wei; Yu, Jun; Zhang, Bo; Zhang, Qingrun; Zhao, Hongbin; Zhao, Hui; Zhou, Jun; Gabriel, Stacey B; Barry, Rachel; Blumenstiel, Brendan; Camargo, Amy; Defelice, Matthew; Faggart, Maura; Goyette, Mary; Gupta, Supriya; Moore, Jamie; Nguyen, Huy; Onofrio, Robert C; Parkin, Melissa; Roy, Jessica; Stahl, Erich; Winchester, Ellen; Ziaugra, Liuda; Altshuler, David; Shen, Yan; Yao, Zhijian; Huang, Wei; Chu, Xun; He, Yungang; Jin, Li; Liu, Yangfan; Shen, Yayun; Sun, Weiwei; Wang, Haifeng; Wang, Yi; Wang, Ying; Xiong, Xiaoyan; Xu, Liang; Waye, Mary M Y; Tsui, Stephen K W; Xue, Hong; Wong, J Tze-Fei; Galver, Luana M; Fan, Jian-Bing; Gunderson, Kevin; Murray, Sarah S; Oliphant, Arnold R; Chee, Mark S; Montpetit, Alexandre; Chagnon, Fanny; Ferretti, Vincent; Leboeuf, Martin; Olivier, Jean-François; Phillips, Michael S; Roumy, Stéphanie; Sallée, Clémentine; Verner, Andrei; Hudson, Thomas J; Kwok, Pui-Yan; Cai, Dongmei; Koboldt, Daniel C; Miller, Raymond D; Pawlikowska, Ludmila; Taillon-Miller, Patricia; Xiao, Ming; Tsui, Lap-Chee; Mak, William; Song, You Qiang; Tam, Paul K H; Nakamura, Yusuke; Kawaguchi, Takahisa; Kitamoto, Takuya; Morizono, Takashi; Nagashima, Atsushi; Ohnishi, Yozo; Sekine, Akihiro; Tanaka, Toshihiro; Tsunoda, Tatsuhiko; Deloukas, Panos; Bird, Christine P; Delgado, Marcos; Dermitzakis, Emmanouil T; Gwilliam, Rhian; Hunt, Sarah; Morrison, Jonathan; Powell, Don; Stranger, Barbara E; Whittaker, Pamela; Bentley, David R; Daly, Mark J; de Bakker, Paul I W; Barrett, Jeff; Chretien, Yves R; Maller, Julian; McCarroll, Steve; Patterson, Nick; Pe'er, Itsik; Price, Alkes; Purcell, Shaun; Richter, Daniel J; Sabeti, Pardis; Saxena, Richa; Schaffner, Stephen F; Sham, Pak C; Varilly, Patrick; Altshuler, David; Stein, Lincoln D; Krishnan, Lalitha; Smith, Albert Vernon; Tello-Ruiz, Marcela K; Thorisson, Gudmundur A; Chakravarti, Aravinda; Chen, Peter E; Cutler, David J; Kashuk, Carl S; Lin, Shin; Abecasis, Gonçalo R; Guan, Weihua; Li, Yun; Munro, Heather M; Qin, Zhaohui Steve; Thomas, Daryl J; McVean, Gilean; Auton, Adam; Bottolo, Leonardo; Cardin, Niall; Eyheramendy, Susana; Freeman, Colin; Marchini, Jonathan; Myers, Simon; Spencer, Chris; Stephens, Matthew; Donnelly, Peter; Cardon, Lon R; Clarke, Geraldine; Evans, David M; Morris, Andrew P; Weir, Bruce S; Tsunoda, Tatsuhiko; Johnson, Todd A; Mullikin, James C; Sherry, Stephen T; Feolo, Michael; Skol, Andrew; Zhang, Houcan; Zeng, Changqing; Zhao, Hui; Matsuda, Ichiro; Fukushima, Yoshimitsu; Macer, Darryl R; Suda, Eiko; Rotimi, Charles N; Adebamowo, Clement A; Ajayi, Ike; Aniagwu, Toyin; Marshall, Patricia A; Nkwodimmah, Chibuzor; Royal, Charmaine D M; Leppert, Mark F; Dixon, Missy; Peiffer, Andy; Qiu, Renzong; Kent, Alastair; Kato, Kazuto; Niikawa, Norio; Adewole, Isaac F; Knoppers, Bartha M; Foster, Morris W; Clayton, Ellen Wright; Watkin, Jessica; Gibbs, Richard A; Belmont, John W; Muzny, Donna; Nazareth, Lynne; Sodergren, Erica; Weinstock, George M; Wheeler, David A; Yakub, Imtaz; Gabriel, Stacey B; Onofrio, Robert C; Richter, Daniel J; Ziaugra, Liuda; Birren, Bruce W; Daly, Mark J; Altshuler, David; Wilson, Richard K; Fulton, Lucinda L; Rogers, Jane; Burton, John; Carter, Nigel P; Clee, Christopher M; Griffiths, Mark; Jones, Matthew C; McLay, Kirsten; Plumb, Robert W; Ross, Mark T; Sims, Sarah K; Willey, David L; Chen, Zhu; Han, Hua; Kang, Le; Godbout, Martin; Wallenburg, John C; L'Archevêque, Paul; Bellemare, Guy; Saeki, Koji; Wang, Hongguang; An, Daochang; Fu, Hongbo; Li, Qing; Wang, Zhen; Wang, Renwu; Holden, Arthur L; Brooks, Lisa D; McEwen, Jean E; Guyer, Mark S; Wang, Vivian Ota; Peterson, Jane L; Shi, Michael; Spiegel, Jack; Sung, Lawrence M; Zacharia, Lynn F; Collins, Francis S; Kennedy, Karen; Jamieson, Ruth; Stewart, John

2007-10-18

With the advent of dense maps of human genetic variation, it is now possible to detect positive natural selection across the human genome. Here we report an analysis of over 3 million polymorphisms from the International HapMap Project Phase 2 (HapMap2). We used 'long-range haplotype' methods, which were developed to identify alleles segregating in a population that have undergone recent selection, and we also developed new methods that are based on cross-population comparisons to discover alleles that have swept to near-fixation within a population. The analysis reveals more than 300 strong candidate regions. Focusing on the strongest 22 regions, we develop a heuristic for scrutinizing these regions to identify candidate targets of selection. In a complementary analysis, we identify 26 non-synonymous, coding, single nucleotide polymorphisms showing regional evidence of positive selection. Examination of these candidates highlights three cases in which two genes in a common biological process have apparently undergone positive selection in the same population:LARGE and DMD, both related to infection by the Lassa virus, in West Africa;SLC24A5 and SLC45A2, both involved in skin pigmentation, in Europe; and EDAR and EDA2R, both involved in development of hair follicles, in Asia.

Genomics using the Assembly of the Mink Genome

DEFF Research Database (Denmark)

Guldbrandtsen, Bernt; Cai, Zexi; Sahana, Goutam

2018-01-01

The American Mink’s (Neovison vison) genome has recently been sequenced. This opens numerous avenues of research both for studying the basic genetics and physiology of the mink as well as genetic improvement in mink. Using genotyping-by-sequencing (GBS) generated marker data for 2,352 Danish farm...... mink runs of homozygosity (ROH) were detect in mink genomes. Detectable ROH made up on average 1.7% of the genome indicating the presence of at most a moderate level of genomic inbreeding. The fraction of genome regions found in ROH varied. Ten percent of the included regions were never found in ROH....... The ability to detect ROH in the mink genome also demonstrates the general reliability of the new mink genome assembly. Keywords: american mink, run of homozygosity, genome, selection, genomic inbreeding...

Training set optimization under population structure in genomic selection.

Science.gov (United States)

Isidro, Julio; Jannink, Jean-Luc; Akdemir, Deniz; Poland, Jesse; Heslot, Nicolas; Sorrells, Mark E

2015-01-01

Population structure must be evaluated before optimization of the training set population. Maximizing the phenotypic variance captured by the training set is important for optimal performance. The optimization of the training set (TRS) in genomic selection has received much interest in both animal and plant breeding, because it is critical to the accuracy of the prediction models. In this study, five different TRS sampling algorithms, stratified sampling, mean of the coefficient of determination (CDmean), mean of predictor error variance (PEVmean), stratified CDmean (StratCDmean) and random sampling, were evaluated for prediction accuracy in the presence of different levels of population structure. In the presence of population structure, the most phenotypic variation captured by a sampling method in the TRS is desirable. The wheat dataset showed mild population structure, and CDmean and stratified CDmean methods showed the highest accuracies for all the traits except for test weight and heading date. The rice dataset had strong population structure and the approach based on stratified sampling showed the highest accuracies for all traits. In general, CDmean minimized the relationship between genotypes in the TRS, maximizing the relationship between TRS and the test set. This makes it suitable as an optimization criterion for long-term selection. Our results indicated that the best selection criterion used to optimize the TRS seems to depend on the interaction of trait architecture and population structure.

Rhipicephalus (Boophilus) microplus strain Deutsch, whole genome shotgun sequencing project first submission of genome sequence

Science.gov (United States)

The size and repetitive nature of the Rhipicephalus microplus genome makes obtaining a full genome sequence difficult. Cot filtration/selection techniques were used to reduce the repetitive fraction of the tick genome and enrich for the fraction of DNA with gene-containing regions. The Cot-selected ...

Evaluation of methods and marker Systems in Genomic Selection of oil palm (Elaeis guineensis Jacq.).

Science.gov (United States)

Kwong, Qi Bin; Teh, Chee Keng; Ong, Ai Ling; Chew, Fook Tim; Mayes, Sean; Kulaveerasingam, Harikrishna; Tammi, Martti; Yeoh, Suat Hui; Appleton, David Ross; Harikrishna, Jennifer Ann

2017-12-11

Genomic selection (GS) uses genome-wide markers as an attempt to accelerate genetic gain in breeding programs of both animals and plants. This approach is particularly useful for perennial crops such as oil palm, which have long breeding cycles, and for which the optimal method for GS is still under debate. In this study, we evaluated the effect of different marker systems and modeling methods for implementing GS in an introgressed dura family derived from a Deli dura x Nigerian dura (Deli x Nigerian) with 112 individuals. This family is an important breeding source for developing new mother palms for superior oil yield and bunch characters. The traits of interest selected for this study were fruit-to-bunch (F/B), shell-to-fruit (S/F), kernel-to-fruit (K/F), mesocarp-to-fruit (M/F), oil per palm (O/P) and oil-to-dry mesocarp (O/DM). The marker systems evaluated were simple sequence repeats (SSRs) and single nucleotide polymorphisms (SNPs). RR-BLUP, Bayesian A, B, Cπ, LASSO, Ridge Regression and two machine learning methods (SVM and Random Forest) were used to evaluate GS accuracy of the traits. The kinship coefficient between individuals in this family ranged from 0.35 to 0.62. S/F and O/DM had the highest genomic heritability, whereas F/B and O/P had the lowest. The accuracies using 135 SSRs were low, with accuracies of the traits around 0.20. The average accuracy of machine learning methods was 0.24, as compared to 0.20 achieved by other methods. The trait with the highest mean accuracy was F/B (0.28), while the lowest were both M/F and O/P (0.18). By using whole genomic SNPs, the accuracies for all traits, especially for O/DM (0.43), S/F (0.39) and M/F (0.30) were improved. The average accuracy of machine learning methods was 0.32, compared to 0.31 achieved by other methods. Due to high genomic resolution, the use of whole-genome SNPs improved the efficiency of GS dramatically for oil palm and is recommended for dura breeding programs. Machine learning slightly

Comparative Genomics of Smut Pathogens: Insights From Orphans and Positively Selected Genes Into Host Specialization

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Juliana Benevenuto

2018-04-01

Full Text Available Host specialization is a key evolutionary process for the diversification and emergence of new pathogens. However, the molecular determinants of host range are poorly understood. Smut fungi are biotrophic pathogens that have distinct and narrow host ranges based on largely unknown genetic determinants. Hence, we aimed to expand comparative genomics analyses of smut fungi by including more species infecting different hosts and to define orphans and positively selected genes to gain further insights into the genetics basis of host specialization. We analyzed nine lineages of smut fungi isolated from eight crop and non-crop hosts: maize, barley, sugarcane, wheat, oats, Zizania latifolia (Manchurian rice, Echinochloa colona (a wild grass, and Persicaria sp. (a wild dicot plant. We assembled two new genomes: Ustilago hordei (strain Uhor01 isolated from oats and U. tritici (strain CBS 119.19 isolated from wheat. The smut genomes were of small sizes, ranging from 18.38 to 24.63 Mb. U. hordei species experienced genome expansions due to the proliferation of transposable elements and the amount of these elements varied among the two strains. Phylogenetic analysis confirmed that Ustilago is not a monophyletic genus and, furthermore, detected misclassification of the U. tritici specimen. The comparison between smut pathogens of crop and non-crop hosts did not reveal distinct signatures, suggesting that host domestication did not play a dominant role in shaping the evolution of smuts. We found that host specialization in smut fungi likely has a complex genetic basis: different functional categories were enriched in orphans and lineage-specific selected genes. The diversification and gain/loss of effector genes are probably the most important determinants of host specificity.

A proportion of mutations fixed in the genomes of in vitro selected isogenic drug-resistant Mycobacterium tuberculosis mutants can be detected as minority variants in the parent culture

KAUST Repository

Bergval, Indra; Coll, Francesc; Schuitema, Anja; de Ronde, Hans; Mallard, Kim; Pain, Arnab; McNerney, Ruth; Clark, Taane G.; Anthony, Richard M.

2015-01-01

We studied genomic variation in a previously selected collection of isogenic Mycobacterium tuberculosis laboratory strains subjected to one or two rounds of antibiotic selection. Whole genome sequencing analysis identified eleven single, unique mutations (four synonymous, six non-synonymous, one intergenic), in addition to drug resistance-conferring mutations, that were fixed in the genomes of six monoresistant strains. Eight loci, present as minority variants (five non-synonymous, three synonymous) in the genome of the susceptible parent strain, became fixed in the genomes of multiple daughter strains. None of these mutations are known to be involved with drug resistance. Our results confirm previously observed genomic stability for M. tuberculosis, although the parent strain had accumulated allelic variants at multiple locations in an antibiotic-free in vitro environment. It is therefore likely to assume that these so-called hitchhiking mutations were co-selected and fixed in multiple daughter strains during antibiotic selection. The presence of multiple allelic variations, accumulated under non-selective conditions, which become fixed during subsequent selective steps, deserves attention. The wider availability of 'deep' sequencing methods could help to detect multiple bacterial (sub)populations within patients with high resolution and would therefore be useful in assisting in the detailed investigation of transmission chains.

A proportion of mutations fixed in the genomes of in vitro selected isogenic drug-resistant Mycobacterium tuberculosis mutants can be detected as minority variants in the parent culture

KAUST Repository

Bergval, Indra

2015-01-09

We studied genomic variation in a previously selected collection of isogenic Mycobacterium tuberculosis laboratory strains subjected to one or two rounds of antibiotic selection. Whole genome sequencing analysis identified eleven single, unique mutations (four synonymous, six non-synonymous, one intergenic), in addition to drug resistance-conferring mutations, that were fixed in the genomes of six monoresistant strains. Eight loci, present as minority variants (five non-synonymous, three synonymous) in the genome of the susceptible parent strain, became fixed in the genomes of multiple daughter strains. None of these mutations are known to be involved with drug resistance. Our results confirm previously observed genomic stability for M. tuberculosis, although the parent strain had accumulated allelic variants at multiple locations in an antibiotic-free in vitro environment. It is therefore likely to assume that these so-called hitchhiking mutations were co-selected and fixed in multiple daughter strains during antibiotic selection. The presence of multiple allelic variations, accumulated under non-selective conditions, which become fixed during subsequent selective steps, deserves attention. The wider availability of \\'deep\\' sequencing methods could help to detect multiple bacterial (sub)populations within patients with high resolution and would therefore be useful in assisting in the detailed investigation of transmission chains.

Genomic selection strategies in breeding programs: Strong positive interaction between application of genotypic information and intensive use of young bulls on genetic gain

DEFF Research Database (Denmark)

Buch, Line Hjortø; Sørensen, Morten Kargo; Berg, Peer

2012-01-01

We tested the following hypotheses: (i) breeding schemes with genomic selection are superior to breeding schemes without genomic selection regarding annual genetic gain of the aggregate genotype (ΔGAG), annual genetic gain of the functional traits and rate of inbreeding per generation (ΔF), (ii......) a positive interaction exists between the use of genotypic information and a short generation interval on ΔGAG and (iii) the inclusion of an indicator trait in the selection index will only result in a negligible increase in ΔGAG if genotypic information about the breeding goal trait is known. We examined......, greater contributions of the functional trait to ΔGAG and lower ΔF than the two breeding schemes without genomic selection. Thus, the use of genotypic information may lead to more sustainable breeding schemes. In addition, a short generation interval increases the effect of using genotypic information...

Genomic selection for tolerance to heat stress in Australian dairy cattle.

Science.gov (United States)

Nguyen, Thuy T T; Bowman, Phil J; Haile-Mariam, Mekonnen; Pryce, Jennie E; Hayes, Benjamin J

2016-04-01

Temperature and humidity levels above a certain threshold decrease milk production in dairy cattle, and genetic variation is associated with the amount of lost production. To enable selection for improved heat tolerance, the aim of this study was to develop genomic estimated breeding values (GEBV) for heat tolerance in dairy cattle. Heat tolerance was defined as the rate of decline in production under heat stress. We combined herd test-day recording data from 366,835 Holstein and 76,852 Jersey cows with daily temperature and humidity measurements from weather stations closest to the tested herds for test days between 2003 and 2013. We used daily mean values of temperature-humidity index averaged for the day of test and the 4 previous days as the measure of heat stress. Tolerance to heat stress was estimated for each cow using a random regression model with a common threshold of temperature-humidity index=60 for all cows. The slope solutions for cows from this model were used to define the daughter trait deviations of their sires. Genomic best linear unbiased prediction was used to calculate GEBV for heat tolerance for milk, fat, and protein yield. Two reference populations were used, the first consisted of genotyped sires only (2,300 Holstein and 575 Jersey sires), and the other included genotyped sires and cows (2,189 Holstein and 1,188 Jersey cows). The remainder of the genotyped sires were used as a validation set. All animals had genotypes for 632,003 single nucleotide polymorphisms. When using only genotyped sires in the reference set and only the first parity data, the accuracy of GEBV for heat tolerance in relation to changes in milk, fat, and protein yield were 0.48, 0.50, and 0.49 in the Holstein validation sires and 0.44, 0.61, and 0.53 in the Jersey validation sires, respectively. Some slight improvement in the accuracy of prediction was achieved when cows were included in the reference population for Holsteins. No clear improvements in the accuracy of

Optimal Management Of Renewable-Based Mgs An Intelligent Approach Through The Evolutionary Algorithm

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Mehdi Nafar

2015-08-01

Full Text Available Abstract- This article proposes a probabilistic frame built on Scenario fabrication to considerate the uncertainties in the finest action managing of Micro Grids MGs. The MG contains different recoverable energy resources such as Wind Turbine WT Micro Turbine MT Photovoltaic PV Fuel Cell FC and one battery as the storing device. The advised frame is based on scenario generation and Roulette wheel mechanism to produce different circumstances for handling the uncertainties of altered factors. It habits typical spreading role as a probability scattering function of random factors. The uncertainties which are measured in this paper are grid bid alterations cargo request calculating error and PV and WT yield power productions. It is well-intentioned to asset that solving the MG difficult for 24 hours of a day by considering diverse uncertainties and different constraints needs one powerful optimization method that can converge fast when it doesnt fall in local optimal topic. Simultaneously single Group Search Optimization GSO system is presented to vision the total search space globally. The GSO algorithm is instigated from group active of beasts. Also the GSO procedure one change is similarly planned for this algorithm. The planned context and way is applied o one test grid-connected MG as a typical grid.

Shifts in the evolutionary rate and intensity of purifying selection between two Brassica genomes revealed by analyses of orthologous transposons and relics of a whole genome triplication.

Science.gov (United States)

Zhao, Meixia; Du, Jianchang; Lin, Feng; Tong, Chaobo; Yu, Jingyin; Huang, Shunmou; Wang, Xiaowu; Liu, Shengyi; Ma, Jianxin

2013-10-01

Recent sequencing of the Brassica rapa and Brassica oleracea genomes revealed extremely contrasting genomic features such as the abundance and distribution of transposable elements between the two genomes. However, whether and how these structural differentiations may have influenced the evolutionary rates of the two genomes since their split from a common ancestor are unknown. Here, we investigated and compared the rates of nucleotide substitution between two long terminal repeats (LTRs) of individual orthologous LTR-retrotransposons, the rates of synonymous and non-synonymous substitution among triplicated genes retained in both genomes from a shared whole genome triplication event, and the rates of genetic recombination estimated/deduced by the comparison of physical and genetic distances along chromosomes and ratios of solo LTRs to intact elements. Overall, LTR sequences and genic sequences showed more rapid nucleotide substitution in B. rapa than in B. oleracea. Synonymous substitution of triplicated genes retained from a shared whole genome triplication was detected at higher rates in B. rapa than in B. oleracea. Interestingly, non-synonymous substitution was observed at lower rates in the former than in the latter, indicating shifted densities of purifying selection between the two genomes. In addition to evolutionary asymmetry, orthologous genes differentially regulated and/or disrupted by transposable elements between the two genomes were also characterized. Our analyses suggest that local genomic and epigenomic features, such as recombination rates and chromatin dynamics reshaped by independent proliferation of transposable elements and elimination between the two genomes, are perhaps partially the causes and partially the outcomes of the observed inter-specific asymmetric evolution. © 2013 Purdue University The Plant Journal © 2013 John Wiley & Sons Ltd.

Simultaneous improvement of grain yield and protein content in durum wheat by different phenotypic indices and genomic selection.

Science.gov (United States)

Rapp, M; Lein, V; Lacoudre, F; Lafferty, J; Müller, E; Vida, G; Bozhanova, V; Ibraliu, A; Thorwarth, P; Piepho, H P; Leiser, W L; Würschum, T; Longin, C F H

2018-06-01

Simultaneous improvement of protein content and grain yield by index selection is possible but its efficiency largely depends on the weighting of the single traits. The genetic architecture of these indices is similar to that of the primary traits. Grain yield and protein content are of major importance in durum wheat breeding, but their negative correlation has hampered their simultaneous improvement. To account for this in wheat breeding, the grain protein deviation (GPD) and the protein yield were proposed as targets for selection. The aim of this work was to investigate the potential of different indices to simultaneously improve grain yield and protein content in durum wheat and to evaluate their genetic architecture towards genomics-assisted breeding. To this end, we investigated two different durum wheat panels comprising 159 and 189 genotypes, which were tested in multiple field locations across Europe and genotyped by a genotyping-by-sequencing approach. The phenotypic analyses revealed significant genetic variances for all traits and heritabilities of the phenotypic indices that were in a similar range as those of grain yield and protein content. The GPD showed a high and positive correlation with protein content, whereas protein yield was highly and positively correlated with grain yield. Thus, selecting for a high GPD would mainly increase the protein content whereas a selection based on protein yield would mainly improve grain yield, but a combination of both indices allows to balance this selection. The genome-wide association mapping revealed a complex genetic architecture for all traits with most QTL having small effects and being detected only in one germplasm set, thus limiting the potential of marker-assisted selection for trait improvement. By contrast, genome-wide prediction appeared promising but its performance strongly depends on the relatedness between training and prediction sets.

Genomic and environmental selection patterns in two distinct lettuce crop-wild hybrid crosses

OpenAIRE

Hartman, Y.; Uwimana, B.; Hooftman, D.A.P.; Schranz, M.E.; Wiel, van de, C.C.M.; Smulders, M.J.M.; Visser, R.G.F.; Tienderen, van, P.H.

2013-01-01

Genomic selection patterns and hybrid performance influence the chance that crop (trans)genes can spread to wild relatives. We measured fitness(-related) traits in two different field environments employing two different crop?wild crosses of lettuce. We performed quantitative trait loci (QTL) analyses and estimated the fitness distribution of early- and late-generation hybrids. We detected consistent results across field sites and crosses for a fitness QTL at linkage group 7, where a selectiv...

A genomic survey of positive selection in Burkholderia pseudomallei provides insights into the evolution of accidental virulence.

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Tannistha Nandi

2010-04-01

Full Text Available Certain environmental microorganisms can cause severe human infections, even in the absence of an obvious requirement for transition through an animal host for replication ("accidental virulence". To understand this process, we compared eleven isolate genomes of Burkholderia pseudomallei (Bp, a tropical soil microbe and causative agent of the human and animal disease melioidosis. We found evidence for the existence of several new genes in the Bp reference genome, identifying 282 novel genes supported by at least two independent lines of supporting evidence (mRNA transcripts, database homologs, and presence of ribosomal binding sites and 81 novel genes supported by all three lines. Within the Bp core genome, 211 genes exhibited significant levels of positive selection (4.5%, distributed across many cellular pathways including carbohydrate and secondary metabolism. Functional experiments revealed that certain positively selected genes might enhance mammalian virulence by interacting with host cellular pathways or utilizing host nutrients. Evolutionary modifications improving Bp environmental fitness may thus have indirectly facilitated the ability of Bp to colonize and survive in mammalian hosts. These findings improve our understanding of the pathogenesis of melioidosis, and establish Bp as a model system for studying the genetics of accidental virulence.

Identifying selected regions from heterozygosity and divergence using a light-coverage genomic dataset from two human populations.

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Taras K Oleksyk

2008-03-01

Full Text Available When a selective sweep occurs in the chromosomal region around a target gene in two populations that have recently separated, it produces three dramatic genomic consequences: 1 decreased multi-locus heterozygosity in the region; 2 elevated or diminished genetic divergence (F(ST of multiple polymorphic variants adjacent to the selected locus between the divergent populations, due to the alternative fixation of alleles; and 3 a consequent regional increase in the variance of F(ST (S(2F(ST for the same clustered variants, due to the increased alternative fixation of alleles in the loci surrounding the selection target. In the first part of our study, to search for potential targets of directional selection, we developed and validated a resampling-based computational approach; we then scanned an array of 31 different-sized moving windows of SNP variants (5-65 SNPs across the human genome in a set of European and African American population samples with 183,997 SNP loci after correcting for the recombination rate variation. The analysis revealed 180 regions of recent selection with very strong evidence in either population or both. In the second part of our study, we compared the newly discovered putative regions to those sites previously postulated in the literature, using methods based on inspecting patterns of linkage disequilibrium, population divergence and other methodologies. The newly found regions were cross-validated with those found in nine other studies that have searched for selection signals. Our study was replicated especially well in those regions confirmed by three or more studies. These validated regions were independently verified, using a combination of different methods and different databases in other studies, and should include fewer false positives. The main strength of our analysis method compared to others is that it does not require dense genotyping and therefore can be used with data from population-based genome SNP scans

AFLP genome scanning reveals divergent selection in natural populations of Liriodendron chinense (Magnoliaceae along a latitudinal transect

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Aihong eYang

2016-05-01

Full Text Available Understanding adaptive genetic variation and its relation to environmental factors are important for understanding how plants adapt to climate change and for managing genetic resources. Genome scans for the loci exhibiting either notably high or low levels of population differentiation (outlier loci provide one means of identifying genomic regions possibly associated with convergent or divergent selection. In this study, we combined AFLP genome scan and environmental association analysis to test for signals of natural selection in natural populations of Liriodendron chinense (Chinese Tulip Tree; Magnoliaceae along a latitudinal transect. We genotyped 276 individuals from 11 populations of L. chinense using 987 AFLP markers. Two complementary methods (Dfdist and BayeScan and association analysis between AFLP loci and climate factors were applied to detect outlier loci. Our analyses recovered both neutral and potentially adaptive genetic differentiation among populations of L. chinense. We found moderate genetic diversity within populations and high genetic differentiation among populations with reduced genetic diversity towards the periphery of the species ranges. Nine AFLP marker loci showed evidence of being outliers for population differentiation for both detection methods. Of these, six were strongly associated with at least one climate factor. Temperature, precipitation and radiation were found to be three important factors influencing local adaptation of L. chinense. The outlier AFLP loci are likely not the target of natural selection, but the neighboring genes of these loci might be involved in local adaptation. Hence, these candidates should be validated by further studies.

Prediction of Genes Related to Positive Selection Using Whole-Genome Resequencing in Three Commercial Pig Breeds

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HyoYoung Kim

2015-12-01

Full Text Available Selective sweep can cause genetic differentiation across populations, which allows for the identification of possible causative regions/genes underlying important traits. The pig has experienced a long history of allele frequency changes through artificial selection in the domestication process. We obtained an average of 329,482,871 sequence reads for 24 pigs from three pig breeds: Yorkshire (n = 5, Landrace (n = 13, and Duroc (n = 6. An average read depth of 11.7 was obtained using whole-genome resequencing on an Illumina HiSeq2000 platform. In this study, cross-population extended haplotype homozygosity and cross-population composite likelihood ratio tests were implemented to detect genes experiencing positive selection for the genome-wide resequencing data generated from three commercial pig breeds. In our results, 26, 7, and 14 genes from Yorkshire, Landrace, and Duroc, respectively were detected by two kinds of statistical tests. Significant evidence for positive selection was identified on genes ST6GALNAC2 and EPHX1 in Yorkshire, PARK2 in Landrace, and BMP6, SLA-DQA1, and PRKG1 in Duroc.These genes are reportedly relevant to lactation, reproduction, meat quality, and growth traits. To understand how these single nucleotide polymorphisms (SNPs related positive selection affect protein function, we analyzed the effect of non-synonymous SNPs. Three SNPs (rs324509622, rs80931851, and rs80937718 in the SLA-DQA1 gene were significant in the enrichment tests, indicating strong evidence for positive selection in Duroc. Our analyses identified genes under positive selection for lactation, reproduction, and meat-quality and growth traits in Yorkshire, Landrace, and Duroc, respectively.

Genomic signatures of local directional selection in a high gene flow marine organism, the Atlantic cod (Gadus morhua)

DEFF Research Database (Denmark)

Eg Nielsen, Einar; Hansen, Jakob Hemmer; Poulsen, Nina Aagaard

2009-01-01

-associated single nucleotide polymorphisms (SNPs) for evidence of selection in local populations of Atlantic cod (Gadus morhua L.) across the species distribution. Results: Our global genome scan analysis identified eight outlier gene loci with very high statistical support, likely to be subject to directional...... selection in local demes, or closely linked to loci under selection. Likewise, on a regional south/north transect of central and eastern Atlantic populations, seven loci displayed strongly elevated levels of genetic differentiation. Selection patterns among populations appeared to be relatively widespread...

A genome-wide signature of positive selection in ancient and recent invasive expansions of the honey bee Apis mellifera.

Science.gov (United States)

Zayed, Amro; Whitfield, Charles W

2008-03-04

Apis mellifera originated in Africa and extended its range into Eurasia in two or more ancient expansions. In 1956, honey bees of African origin were introduced into South America, their descendents admixing with previously introduced European bees, giving rise to the highly invasive and economically devastating "Africanized" honey bee. Here we ask whether the honey bee's out-of-Africa expansions, both ancient and recent (invasive), were associated with a genome-wide signature of positive selection, detected by contrasting genetic differentiation estimates (F(ST)) between coding and noncoding SNPs. In native populations, SNPs in protein-coding regions had significantly higher F(ST) estimates than those in noncoding regions, indicating adaptive evolution in the genome driven by positive selection. This signal of selection was associated with the expansion of honey bees from Africa into Western and Northern Europe, perhaps reflecting adaptation to temperate environments. We estimate that positive selection acted on a minimum of 852-1,371 genes or approximately 10% of the bee's coding genome. We also detected positive selection associated with the invasion of African-derived honey bees in the New World. We found that introgression of European-derived alleles into Africanized bees was significantly greater for coding than noncoding regions. Our findings demonstrate that Africanized bees exploited the genetic diversity present from preexisting introductions in an adaptive way. Finally, we found a significant negative correlation between F(ST) estimates and the local GC content surrounding coding SNPs, suggesting that AT-rich genes play an important role in adaptive evolution in the honey bee.

Meier-Gorlin syndrome Clinical genetics and genomics

NARCIS (Netherlands)

S. de Munnik (Sonja); E.H. Hoefsloot (Lies); J. Roukema (Jolt); J. Schoots (Jeroen); N.V.A.M. Knoers (Nine); H.G. Brunner; A.P. Jackson (Andrew); E. Bongers (Ernie)

2015-01-01

textabstractMeier-Gorlin syndrome (MGS) is a rare autosomal recessive primordial dwarfism disorder, characterized by microtia, patellar applasia/hypoplasia, and a proportionate short stature. Associated clinical features encompass feeding problems, congenital pulmonary emphysema, mammary hypoplasia

Identifying signatures of natural selection in Tibetan and Andean populations using dense genome scan data.

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Abigail Bigham

2010-09-01

Full Text Available High-altitude hypoxia (reduced inspired oxygen tension due to decreased barometric pressure exerts severe physiological stress on the human body. Two high-altitude regions where humans have lived for millennia are the Andean Altiplano and the Tibetan Plateau. Populations living in these regions exhibit unique circulatory, respiratory, and hematological adaptations to life at high altitude. Although these responses have been well characterized physiologically, their underlying genetic basis remains unknown. We performed a genome scan to identify genes showing evidence of adaptation to hypoxia. We looked across each chromosome to identify genomic regions with previously unknown function with respect to altitude phenotypes. In addition, groups of genes functioning in oxygen metabolism and sensing were examined to test the hypothesis that particular pathways have been involved in genetic adaptation to altitude. Applying four population genetic statistics commonly used for detecting signatures of natural selection, we identified selection-nominated candidate genes and gene regions in these two populations (Andeans and Tibetans separately. The Tibetan and Andean patterns of genetic adaptation are largely distinct from one another, with both populations showing evidence of positive natural selection in different genes or gene regions. Interestingly, one gene previously known to be important in cellular oxygen sensing, EGLN1 (also known as PHD2, shows evidence of positive selection in both Tibetans and Andeans. However, the pattern of variation for this gene differs between the two populations. Our results indicate that several key HIF-regulatory and targeted genes are responsible for adaptation to high altitude in Andeans and Tibetans, and several different chromosomal regions are implicated in the putative response to selection. These data suggest a genetic role in high-altitude adaption and provide a basis for future genotype/phenotype association

Genomic prediction by single-step genomic BLUP using cow reference population in Holstein crossbred cattle in India

DEFF Research Database (Denmark)

Nayee, Nilesh Kumar; Su, Guosheng; Gajjar, Swapnil

2018-01-01

Advantages of genomic selection in breeds with limited numbers of progeny tested bulls have been demonstrated by adding genotypes of females to the reference population (Thomasen et al., 2014). The current study was conducted to explore the feasibility of implementing genomic selection in a Holst......Advantages of genomic selection in breeds with limited numbers of progeny tested bulls have been demonstrated by adding genotypes of females to the reference population (Thomasen et al., 2014). The current study was conducted to explore the feasibility of implementing genomic selection...... in a Holstein Friesian crossbred population with cows kept under small holder conditions using test day records and single step genomic BLUP (ssGBLUP). Milk yield records from 10,797 daughters sired by 258 bulls were used Of these 2194 daughters and 109 sires were genotyped with customized genotyping chip...

Meier-Gorlin syndrome Clinical genetics and genomics

NARCIS (Netherlands)

De Munnik, Sonja A.; Hoefsloot, Elisabeth H.; Roukema, Jolt; Schoots, Jeroen; Knoers, Nine Vam; Brunner, Han G.; Jackson, Andrew P.; Bongers, Ernie Mhf

2015-01-01

Meier-Gorlin syndrome (MGS) is a rare autosomal recessive primordial dwarfism disorder, characterized by microtia, patellar applasia/hypoplasia, and a proportionate short stature. Associated clinical features encompass feeding problems, congenital pulmonary emphysema, mammary hypoplasia in females

Unsupervised binning of environmental genomic fragments based on an error robust selection of l-mers.

Science.gov (United States)

Yang, Bin; Peng, Yu; Leung, Henry Chi-Ming; Yiu, Siu-Ming; Chen, Jing-Chi; Chin, Francis Yuk-Lun

2010-04-16

With the rapid development of genome sequencing techniques, traditional research methods based on the isolation and cultivation of microorganisms are being gradually replaced by metagenomics, which is also known as environmental genomics. The first step, which is still a major bottleneck, of metagenomics is the taxonomic characterization of DNA fragments (reads) resulting from sequencing a sample of mixed species. This step is usually referred as "binning". Existing binning methods are based on supervised or semi-supervised approaches which rely heavily on reference genomes of known microorganisms and phylogenetic marker genes. Due to the limited availability of reference genomes and the bias and instability of marker genes, existing binning methods may not be applicable in many cases. In this paper, we present an unsupervised binning method based on the distribution of a carefully selected set of l-mers (substrings of length l in DNA fragments). From our experiments, we show that our method can accurately bin DNA fragments with various lengths and relative species abundance ratios without using any reference and training datasets. Another feature of our method is its error robustness. The binning accuracy decreases by less than 1% when the sequencing error rate increases from 0% to 5%. Note that the typical sequencing error rate of existing commercial sequencing platforms is less than 2%. We provide a new and effective tool to solve the metagenome binning problem without using any reference datasets or markers information of any known reference genomes (species). The source code of our software tool, the reference genomes of the species for generating the test datasets and the corresponding test datasets are available at http://i.cs.hku.hk/~alse/MetaCluster/.

MtDNA genomes reveal a relaxation of selective constraints in low-BMI individuals in a Uyghur population.

Science.gov (United States)

Zheng, Hong-Xiang; Li, Lei; Jiang, Xiao-Yan; Yan, Shi; Qin, Zhendong; Wang, Xiaofeng; Jin, Li

2017-10-01

Considerable attention has been focused on the effect of deleterious mutations caused by the recent relaxation of selective constraints on human health, including the prevalence of obesity, which might represent an adaptive response of energy-conserving metabolism under the conditions of modern society. Mitochondrial DNA (mtDNA) encoding 13 core subunits of oxidative phosphorylation plays an important role in metabolism. Therefore, we hypothesized that a relaxation of selection constraints on mtDNA and an increase in the proportion of deleterious mutations have played a role in obesity prevalence. In this study, we collected and sequenced the mtDNA genomes of 722 Uyghurs, a typical population with a high prevalence of obesity. We identified the variants that occurred in the Uyghur population for each sample and found that the number of nonsynonymous mutations carried by Uyghur individuals declined with elevation of their BMI (P = 0.015). We further calculated the nonsynonymous and synonymous ratio (N/S) of the high-BMI and low-BMI haplogroups, and the results showed that a significantly higher N/S occurred in the whole mtDNA genomes of the low-BMI haplogroups (0.64) than in that of the high-BMI haplogroups (0.35, P = 0.030) and ancestor haplotypes (0.41, P = 0.032); these findings indicated that low-BMI individuals showed a recent relaxation of selective constraints. In addition, we investigated six clinical characteristics and found that fasting plasma glucose might be correlated with the N/S and selective pressures. We hypothesized that a higher proportion of deleterious mutations led to mild mitochondrial dysfunction, which helps to drive glucose consumption and thereby prevents obesity. Our results provide new insights into the relationship between obesity predisposition and mitochondrial genome evolution.

Breeding schemes for the implementation of genomic selection in wheat (Triticum spp.).

Science.gov (United States)

Bassi, Filippo M; Bentley, Alison R; Charmet, Gilles; Ortiz, Rodomiro; Crossa, Jose

2016-01-01

In the last decade the breeding technology referred to as 'genomic selection' (GS) has been implemented in a variety of species, with particular success in animal breeding. Recent research shows the potential of GS to reshape wheat breeding. Many authors have concluded that the estimated genetic gain per year applying GS is several times that of conventional breeding. GS is, however, a new technology for wheat breeding and many programs worldwide are still struggling to identify the best strategy for its implementation. This article provides practical guidelines on the key considerations when implementing GS. A review of the existing GS literature for a range of species is provided and used to prime breeder-oriented considerations on the practical applications of GS. Furthermore, this article discusses potential breeding schemes for GS, genotyping considerations, and methods for effective training population design. The components of selection intensity, progress toward inbreeding in half- or full-sibs recurrent schemes, and the generation of selection are also presented. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Breeding Jatropha curcas by genomic selection: A pilot assessment of the accuracy of predictive models.

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Azevedo Peixoto, Leonardo de; Laviola, Bruno Galvêas; Alves, Alexandre Alonso; Rosado, Tatiana Barbosa; Bhering, Leonardo Lopes

2017-01-01

Genomic wide selection is a promising approach for improving the selection accuracy in plant breeding, particularly in species with long life cycles, such as Jatropha. Therefore, the objectives of this study were to estimate the genetic parameters for grain yield (GY) and the weight of 100 seeds (W100S) using restricted maximum likelihood (REML); to compare the performance of GWS methods to predict GY and W100S; and to estimate how many markers are needed to train the GWS model to obtain the maximum accuracy. Eight GWS models were compared in terms of predictive ability. The impact that the marker density had on the predictive ability was investigated using a varying number of markers, from 2 to 1,248. Because the genetic variance between evaluated genotypes was significant, it was possible to obtain selection gain. All of the GWS methods tested in this study can be used to predict GY and W100S in Jatropha. A training model fitted using 1,000 and 800 markers is sufficient to capture the maximum genetic variance and, consequently, maximum prediction ability of GY and W100S, respectively. This study demonstrated the applicability of genome-wide prediction to identify useful genetic sources of GY and W100S for Jatropha breeding. Further research is needed to confirm the applicability of the proposed approach to other complex traits.

Breeding Jatropha curcas by genomic selection: A pilot assessment of the accuracy of predictive models.

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Leonardo de Azevedo Peixoto

Full Text Available Genomic wide selection is a promising approach for improving the selection accuracy in plant breeding, particularly in species with long life cycles, such as Jatropha. Therefore, the objectives of this study were to estimate the genetic parameters for grain yield (GY and the weight of 100 seeds (W100S using restricted maximum likelihood (REML; to compare the performance of GWS methods to predict GY and W100S; and to estimate how many markers are needed to train the GWS model to obtain the maximum accuracy. Eight GWS models were compared in terms of predictive ability. The impact that the marker density had on the predictive ability was investigated using a varying number of markers, from 2 to 1,248. Because the genetic variance between evaluated genotypes was significant, it was possible to obtain selection gain. All of the GWS methods tested in this study can be used to predict GY and W100S in Jatropha. A training model fitted using 1,000 and 800 markers is sufficient to capture the maximum genetic variance and, consequently, maximum prediction ability of GY and W100S, respectively. This study demonstrated the applicability of genome-wide prediction to identify useful genetic sources of GY and W100S for Jatropha breeding. Further research is needed to confirm the applicability of the proposed approach to other complex traits.

Variable Selection in Heterogeneous Datasets: A Truncated-rank Sparse Linear Mixed Model with Applications to Genome-wide Association Studies.

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Wang, Haohan; Aragam, Bryon; Xing, Eric P

2018-04-26

A fundamental and important challenge in modern datasets of ever increasing dimensionality is variable selection, which has taken on renewed interest recently due to the growth of biological and medical datasets with complex, non-i.i.d. structures. Naïvely applying classical variable selection methods such as the Lasso to such datasets may lead to a large number of false discoveries. Motivated by genome-wide association studies in genetics, we study the problem of variable selection for datasets arising from multiple subpopulations, when this underlying population structure is unknown to the researcher. We propose a unified framework for sparse variable selection that adaptively corrects for population structure via a low-rank linear mixed model. Most importantly, the proposed method does not require prior knowledge of sample structure in the data and adaptively selects a covariance structure of the correct complexity. Through extensive experiments, we illustrate the effectiveness of this framework over existing methods. Further, we test our method on three different genomic datasets from plants, mice, and human, and discuss the knowledge we discover with our method. Copyright © 2018. Published by Elsevier Inc.

Prolonged Integration Site Selection of a Lentiviral Vector in the Genome of Human Keratinocytes.

Science.gov (United States)

Qian, Wei; Wang, Yong; Li, Rui-Fu; Zhou, Xin; Liu, Jing; Peng, Dai-Zhi

2017-03-03

BACKGROUND Lentiviral vectors have been successfully used for human skin cell gene transfer studies. Defining the selection of integration sites for retroviral vectors in the host genome is crucial in risk assessment analysis of gene therapy. However, genome-wide analyses of lentiviral integration sites in human keratinocytes, especially after prolonged growth, are poorly understood. MATERIAL AND METHODS In this study, 874 unique lentiviral vector integration sites in human HaCaT keratinocytes after long-term culture were identified and analyzed with the online tool GTSG-QuickMap and SPSS software. RESULTS The data indicated that lentiviral vectors showed integration site preferences for genes and gene-rich regions. CONCLUSIONS This study will likely assist in determining the relative risks of the lentiviral vector system and in the design of a safe lentiviral vector system in the gene therapy of skin diseases.

Oral cancer prognosis based on clinicopathologic and genomic markers using a hybrid of feature selection and machine learning methods

Science.gov (United States)

2013-01-01

Background Machine learning techniques are becoming useful as an alternative approach to conventional medical diagnosis or prognosis as they are good for handling noisy and incomplete data, and significant results can be attained despite a small sample size. Traditionally, clinicians make prognostic decisions based on clinicopathologic markers. However, it is not easy for the most skilful clinician to come out with an accurate prognosis by using these markers alone. Thus, there is a need to use genomic markers to improve the accuracy of prognosis. The main aim of this research is to apply a hybrid of feature selection and machine learning methods in oral cancer prognosis based on the parameters of the correlation of clinicopathologic and genomic markers. Results In the first stage of this research, five feature selection methods have been proposed and experimented on the oral cancer prognosis dataset. In the second stage, the model with the features selected from each feature selection methods are tested on the proposed classifiers. Four types of classifiers are chosen; these are namely, ANFIS, artificial neural network, support vector machine and logistic regression. A k-fold cross-validation is implemented on all types of classifiers due to the small sample size. The hybrid model of ReliefF-GA-ANFIS with 3-input features of drink, invasion and p63 achieved the best accuracy (accuracy = 93.81%; AUC = 0.90) for the oral cancer prognosis. Conclusions The results revealed that the prognosis is superior with the presence of both clinicopathologic and genomic markers. The selected features can be investigated further to validate the potential of becoming as significant prognostic signature in the oral cancer studies. PMID:23725313

Population genomic scan for candidate signatures of balancing selection to guide antigen characterization in malaria parasites.

Science.gov (United States)

Amambua-Ngwa, Alfred; Tetteh, Kevin K A; Manske, Magnus; Gomez-Escobar, Natalia; Stewart, Lindsay B; Deerhake, M Elizabeth; Cheeseman, Ian H; Newbold, Christopher I; Holder, Anthony A; Knuepfer, Ellen; Janha, Omar; Jallow, Muminatou; Campino, Susana; Macinnis, Bronwyn; Kwiatkowski, Dominic P; Conway, David J

2012-01-01

Acquired immunity in vertebrates maintains polymorphisms in endemic pathogens, leading to identifiable signatures of balancing selection. To comprehensively survey for genes under such selection in the human malaria parasite Plasmodium falciparum, we generated paired-end short-read sequences of parasites in clinical isolates from an endemic Gambian population, which were mapped to the 3D7 strain reference genome to yield high-quality genome-wide coding sequence data for 65 isolates. A minority of genes did not map reliably, including the hypervariable var, rifin, and stevor families, but 5,056 genes (90.9% of all in the genome) had >70% sequence coverage with minimum read depth of 5 for at least 50 isolates, of which 2,853 genes contained 3 or more single nucleotide polymorphisms (SNPs) for analysis of polymorphic site frequency spectra. Against an overall background of negatively skewed frequencies, as expected from historical population expansion combined with purifying selection, the outlying minority of genes with signatures indicating exceptionally intermediate frequencies were identified. Comparing genes with different stage-specificity, such signatures were most common in those with peak expression at the merozoite stage that invades erythrocytes. Members of clag, PfMC-2TM, surfin, and msp3-like gene families were highly represented, the strongest signature being in the msp3-like gene PF10_0355. Analysis of msp3-like transcripts in 45 clinical and 11 laboratory adapted isolates grown to merozoite-containing schizont stages revealed surprisingly low expression of PF10_0355. In diverse clonal parasite lines the protein product was expressed in a minority of mature schizonts (<1% in most lines and ∼10% in clone HB3), and eight sub-clones of HB3 cultured separately had an intermediate spectrum of positive frequencies (0.9 to 7.5%), indicating phase variable expression of this polymorphic antigen. This and other identified targets of balancing selection are now

Population genomic scan for candidate signatures of balancing selection to guide antigen characterization in malaria parasites.

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Alfred Amambua-Ngwa

Full Text Available Acquired immunity in vertebrates maintains polymorphisms in endemic pathogens, leading to identifiable signatures of balancing selection. To comprehensively survey for genes under such selection in the human malaria parasite Plasmodium falciparum, we generated paired-end short-read sequences of parasites in clinical isolates from an endemic Gambian population, which were mapped to the 3D7 strain reference genome to yield high-quality genome-wide coding sequence data for 65 isolates. A minority of genes did not map reliably, including the hypervariable var, rifin, and stevor families, but 5,056 genes (90.9% of all in the genome had >70% sequence coverage with minimum read depth of 5 for at least 50 isolates, of which 2,853 genes contained 3 or more single nucleotide polymorphisms (SNPs for analysis of polymorphic site frequency spectra. Against an overall background of negatively skewed frequencies, as expected from historical population expansion combined with purifying selection, the outlying minority of genes with signatures indicating exceptionally intermediate frequencies were identified. Comparing genes with different stage-specificity, such signatures were most common in those with peak expression at the merozoite stage that invades erythrocytes. Members of clag, PfMC-2TM, surfin, and msp3-like gene families were highly represented, the strongest signature being in the msp3-like gene PF10_0355. Analysis of msp3-like transcripts in 45 clinical and 11 laboratory adapted isolates grown to merozoite-containing schizont stages revealed surprisingly low expression of PF10_0355. In diverse clonal parasite lines the protein product was expressed in a minority of mature schizonts (<1% in most lines and ∼10% in clone HB3, and eight sub-clones of HB3 cultured separately had an intermediate spectrum of positive frequencies (0.9 to 7.5%, indicating phase variable expression of this polymorphic antigen. This and other identified targets of balancing

1000 Bull Genomes - Toward genomic Selectionf from whole genome sequence Data in Dairy and Beef Cattle

NARCIS (Netherlands)

Hayes, B.; Daetwyler, H.D.; Fries, R.; Guldbrandtsen, B.; Mogens Sando Lund, M.; Didier A. Boichard, D.A.; Stothard, P.; Veerkamp, R.F.; Hulsegge, B.; Rocha, D.; Tassell, C.; Mullaart, E.; Gredler, B.; Druet, T.; Bagnato, A.; Goddard, M.E.; Chamberlain, H.L.

2013-01-01

Genomic prediction of breeding values is now used as the basis for selection of dairy cattle, and in some cases beef cattle, in a number of countries. When genomic prediction was introduced most of the information was to thought to be derived from linkage disequilibrium between markers and causative

Target Selection and Deselection at the Berkeley StructuralGenomics Center

Energy Technology Data Exchange (ETDEWEB)

Chandonia, John-Marc; Kim, Sung-Hou; Brenner, Steven E.

2005-03-22

At the Berkeley Structural Genomics Center (BSGC), our goalis to obtain a near-complete structural complement of proteins in theminimal organisms Mycoplasma genitalium and M. pneumoniae, two closelyrelated pathogens. Current targets for structure determination have beenselected in six major stages, starting with those predicted to be mosttractable to high throughput study and likely to yield new structuralinformation. We report on the process used to select these proteins, aswell as our target deselection procedure. Target deselection reducesexperimental effort by eliminating targets similar to those recentlysolved by the structural biology community or other centers. We measurethe impact of the 69 structures solved at the BSGC as of July 2004 onstructure prediction coverage of the M. pneumoniae and M. genitaliumproteomes. The number of Mycoplasma proteins for which thefold couldfirst be reliably assigned based on structures solved at the BSGC (24 M.pneumoniae and 21 M. genitalium) is approximately 25 percent of the totalresulting from work at all structural genomics centers and the worldwidestructural biology community (94 M. pneumoniae and 86M. genitalium)during the same period. As the number of structures contributed by theBSGC during that period is less than 1 percent of the total worldwideoutput, the benefits of a focused target selection strategy are apparent.If the structures of all current targets were solved, the percentage ofM. pneumoniae proteins for which folds could be reliably assigned wouldincrease from approximately 57 percent (391 of 687) at present to around80 percent (550 of 687), and the percentage of the proteome that could beaccurately modeled would increase from around 37 percent (254 of 687) toabout 64 percent (438 of 687). In M. genitalium, the percentage of theproteome that could be structurally annotated based on structures of ourremaining targets would rise from 72 percent (348 of 486) to around 76percent (371 of 486), with the

Demographically-Based Evaluation of Genomic Regions under Selection in Domestic Dogs.

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Adam H Freedman

2016-03-01

Full Text Available Controlling for background demographic effects is important for accurately identifying loci that have recently undergone positive selection. To date, the effects of demography have not yet been explicitly considered when identifying loci under selection during dog domestication. To investigate positive selection on the dog lineage early in the domestication, we examined patterns of polymorphism in six canid genomes that were previously used to infer a demographic model of dog domestication. Using an inferred demographic model, we computed false discovery rates (FDR and identified 349 outlier regions consistent with positive selection at a low FDR. The signals in the top 100 regions were frequently centered on candidate genes related to brain function and behavior, including LHFPL3, CADM2, GRIK3, SH3GL2, MBP, PDE7B, NTAN1, and GLRA1. These regions contained significant enrichments in behavioral ontology categories. The 3rd top hit, CCRN4L, plays a major role in lipid metabolism, that is supported by additional metabolism related candidates revealed in our scan, including SCP2D1 and PDXC1. Comparing our method to an empirical outlier approach that does not directly account for demography, we found only modest overlaps between the two methods, with 60% of empirical outliers having no overlap with our demography-based outlier detection approach. Demography-aware approaches have lower-rates of false discovery. Our top candidates for selection, in addition to expanding the set of neurobehavioral candidate genes, include genes related to lipid metabolism, suggesting a dietary target of selection that was important during the period when proto-dogs hunted and fed alongside hunter-gatherers.

Natural selection interacts with recombination to shape the evolution of hybrid genomes.

Science.gov (United States)

Schumer, Molly; Xu, Chenling; Powell, Daniel L; Durvasula, Arun; Skov, Laurits; Holland, Chris; Blazier, John C; Sankararaman, Sriram; Andolfatto, Peter; Rosenthal, Gil G; Przeworski, Molly

2018-05-11

To investigate the consequences of hybridization between species, we studied three replicate hybrid populations that formed naturally between two swordtail fish species, estimating their fine-scale genetic map and inferring ancestry along the genomes of 690 individuals. In all three populations, ancestry from the "minor" parental species is more common in regions of high recombination and where there is linkage to fewer putative targets of selection. The same patterns are apparent in a reanalysis of human and archaic admixture. These results support models in which ancestry from the minor parental species is more likely to persist when rapidly uncoupled from alleles that are deleterious in hybrids. Our analyses further indicate that selection on swordtail hybrids stems predominantly from deleterious combinations of epistatically interacting alleles. Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.

Theory of microbial genome evolution

Science.gov (United States)

Koonin, Eugene

Bacteria and archaea have small genomes tightly packed with protein-coding genes. This compactness is commonly perceived as evidence of adaptive genome streamlining caused by strong purifying selection in large microbial populations. In such populations, even the small cost incurred by nonfunctional DNA because of extra energy and time expenditure is thought to be sufficient for this extra genetic material to be eliminated by selection. However, contrary to the predictions of this model, there exists a consistent, positive correlation between the strength of selection at the protein sequence level, measured as the ratio of nonsynonymous to synonymous substitution rates, and microbial genome size. By fitting the genome size distributions in multiple groups of prokaryotes to predictions of mathematical models of population evolution, we show that only models in which acquisition of additional genes is, on average, slightly beneficial yield a good fit to genomic data. Thus, the number of genes in prokaryotic genomes seems to reflect the equilibrium between the benefit of additional genes that diminishes as the genome grows and deletion bias. New genes acquired by microbial genomes, on average, appear to be adaptive. Evolution of bacterial and archaeal genomes involves extensive horizontal gene transfer and gene loss. Many microbes have open pangenomes, where each newly sequenced genome contains more than 10% `ORFans', genes without detectable homologues in other species. A simple, steady-state evolutionary model reveals two sharply distinct classes of microbial genes, one of which (ORFans) is characterized by effectively instantaneous gene replacement, whereas the other consists of genes with finite, distributed replacement rates. These findings imply a conservative estimate of at least a billion distinct genes in the prokaryotic genomic universe.

GRAbB: Selective Assembly of Genomic Regions, a New Niche for Genomic Research.

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Balázs Brankovics

2016-06-01

Full Text Available GRAbB (Genomic Region Assembly by Baiting is a new program that is dedicated to assemble specific genomic regions from NGS data. This approach is especially useful when dealing with multi copy regions, such as mitochondrial genome and the rDNA repeat region, parts of the genome that are often neglected or poorly assembled, although they contain interesting information from phylogenetic or epidemiologic perspectives, but also single copy regions can be assembled. The program is capable of targeting multiple regions within a single run. Furthermore, GRAbB can be used to extract specific loci from NGS data, based on homology, like sequences that are used for barcoding. To make the assembly specific, a known part of the region, such as the sequence of a PCR amplicon or a homologous sequence from a related species must be specified. By assembling only the region of interest, the assembly process is computationally much less demanding and may lead to assemblies of better quality. In this study the different applications and functionalities of the program are demonstrated such as: exhaustive assembly (rDNA region and mitochondrial genome, extracting homologous regions or genes (IGS, RPB1, RPB2 and TEF1a, as well as extracting multiple regions within a single run. The program is also compared with MITObim, which is meant for the exhaustive assembly of a single target based on a similar query sequence. GRAbB is shown to be more efficient than MITObim in terms of speed, memory and disk usage. The other functionalities (handling multiple targets simultaneously and extracting homologous regions of the new program are not matched by other programs. The program is available with explanatory documentation at https://github.com/b-brankovics/grabb. GRAbB has been tested on Ubuntu (12.04 and 14.04, Fedora (23, CentOS (7.1.1503 and Mac OS X (10.7. Furthermore, GRAbB is available as a docker repository: brankovics/grabb (https://hub.docker.com/r/brankovics/grabb/.

Selective forces and mutational biases drive stop codon usage in the human genome: a comparison with sense codon usage.

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Trotta, Edoardo

2016-05-17

The three stop codons UAA, UAG, and UGA signal the termination of mRNA translation. As a result of a mechanism that is not adequately understood, they are normally used with unequal frequencies. In this work, we showed that selective forces and mutational biases drive stop codon usage in the human genome. We found that, in respect to sense codons, stop codon usage was affected by stronger selective forces but was less influenced by neutral mutational biases. UGA is the most frequent termination codon in human genome. However, UAA was the preferred stop codon in genes with high breadth of expression, high level of expression, AT-rich coding sequences, housekeeping functions, and in gene ontology categories with the largest deviation from expected stop codon usage. Selective forces associated with the breadth and the level of expression favoured AT-rich sequences in the mRNA region including the stop site and its proximal 3'-UTR, but acted with scarce effects on sense codons, generating two regions, upstream and downstream of the stop codon, with strongly different base composition. By favouring low levels of GC-content, selection promoted labile local secondary structures at the stop site and its proximal 3'-UTR. The compositional and structural context favoured by selection was surprisingly emphasized in the class of ribosomal proteins and was consistent with sequence elements that increase the efficiency of translational termination. Stop codons were also heterogeneously distributed among chromosomes by a mechanism that was strongly correlated with the GC-content of coding sequences. In human genome, the nucleotide composition and the thermodynamic stability of stop codon site and its proximal 3'-UTR are correlated with the GC-content of coding sequences and with the breadth and the level of gene expression. In highly expressed genes stop codon usage is compositionally and structurally consistent with highly efficient translation termination signals.

Genome-wide analysis of mutations in mutant lineages selected following fast-neutron irradiation mutagenesis of Arabidopsis thaliana

KAUST Repository

Belfield, E.J.; Gan, X.; Mithani, A.; Brown, C.; Jiang, C.; Franklin, K.; Alvey, E.; Wibowo, A.; Jung, M.; Bailey, K.; Kalwani, S.; Ragoussis, J.; Mott, R.; Harberd, N.P.

2012-01-01

Ionizing radiation has long been known to induce heritable mutagenic change in DNA sequence. However, the genome-wide effect of radiation is not well understood. Here we report the molecular properties and frequency of mutations in phenotypically selected mutant lines isolated following exposure of the genetic model flowering plant Arabidopsis thaliana to fast neutrons (FNs). Previous studies suggested that FNs predominantly induce deletions longer than a kilobase in A. thaliana. However, we found a higher frequency of single base substitution than deletion mutations. While the overall frequency and molecular spectrum of fast-neutron (FN)-induced single base substitutions differed substantially from those of "background" mutations arising spontaneously in laboratory-grown plants, G:C>A:T transitions were favored in both. We found that FN-induced G:C>A:T transitions were concentrated at pyrimidine dinucleotide sites, suggesting that FNs promote the formation of mutational covalent linkages between adjacent pyrimidine residues. In addition, we found that FNs induced more single base than large deletions, and that these single base deletions were possibly caused by replication slippage. Our observations provide an initial picture of the genome-wide molecular profile of mutations induced in A. thaliana by FN irradiation and are particularly informative of the nature and extent of genome-wide mutation in lines selected on the basis of mutant phenotypes from FN-mutagenized A. thaliana populations.

Genome-wide analysis of mutations in mutant lineages selected following fast-neutron irradiation mutagenesis of Arabidopsis thaliana

KAUST Repository

Belfield, E.J.

2012-04-12

Ionizing radiation has long been known to induce heritable mutagenic change in DNA sequence. However, the genome-wide effect of radiation is not well understood. Here we report the molecular properties and frequency of mutations in phenotypically selected mutant lines isolated following exposure of the genetic model flowering plant Arabidopsis thaliana to fast neutrons (FNs). Previous studies suggested that FNs predominantly induce deletions longer than a kilobase in A. thaliana. However, we found a higher frequency of single base substitution than deletion mutations. While the overall frequency and molecular spectrum of fast-neutron (FN)-induced single base substitutions differed substantially from those of "background" mutations arising spontaneously in laboratory-grown plants, G:C>A:T transitions were favored in both. We found that FN-induced G:C>A:T transitions were concentrated at pyrimidine dinucleotide sites, suggesting that FNs promote the formation of mutational covalent linkages between adjacent pyrimidine residues. In addition, we found that FNs induced more single base than large deletions, and that these single base deletions were possibly caused by replication slippage. Our observations provide an initial picture of the genome-wide molecular profile of mutations induced in A. thaliana by FN irradiation and are particularly informative of the nature and extent of genome-wide mutation in lines selected on the basis of mutant phenotypes from FN-mutagenized A. thaliana populations.

Genome-wide comparative analysis of codon usage bias and codon context patterns among cyanobacterial genomes.

Science.gov (United States)

Prabha, Ratna; Singh, Dhananjaya P; Sinha, Swati; Ahmad, Khurshid; Rai, Anil

2017-04-01

With the increasing accumulation of genomic sequence information of prokaryotes, the study of codon usage bias has gained renewed attention. The purpose of this study was to examine codon selection pattern within and across cyanobacterial species belonging to diverse taxonomic orders and habitats. We performed detailed comparative analysis of cyanobacterial genomes with respect to codon bias. Our analysis reflects that in cyanobacterial genomes, A- and/or T-ending codons were used predominantly in the genes whereas G- and/or C-ending codons were largely avoided. Variation in the codon context usage of cyanobacterial genes corresponded to the clustering of cyanobacteria as per their GC content. Analysis of codon adaptation index (CAI) and synonymous codon usage order (SCUO) revealed that majority of genes are associated with low codon bias. Codon selection pattern in cyanobacterial genomes reflected compositional constraints as major influencing factor. It is also identified that although, mutational constraint may play some role in affecting codon usage bias in cyanobacteria, compositional constraint in terms of genomic GC composition coupled with environmental factors affected codon selection pattern in cyanobacterial genomes. Copyright © 2016 Elsevier B.V. All rights reserved.

Contrasting Patterns of Genomic Diversity Reveal Accelerated Genetic Drift but Reduced Directional Selection on X-Chromosome in Wild and Domestic Sheep Species.

Science.gov (United States)

Chen, Ze-Hui; Zhang, Min; Lv, Feng-Hua; Ren, Xue; Li, Wen-Rong; Liu, Ming-Jun; Nam, Kiwoong; Bruford, Michael W; Li, Meng-Hua

2018-04-01

Analyses of genomic diversity along the X chromosome and of its correlation with autosomal diversity can facilitate understanding of evolutionary forces in shaping sex-linked genomic architecture. Strong selective sweeps and accelerated genetic drift on the X-chromosome have been inferred in primates and other model species, but no such insight has yet been gained in domestic animals compared with their wild relatives. Here, we analyzed X-chromosome variability in a large ovine data set, including a BeadChip array for 943 ewes from the world's sheep populations and 110 whole genomes of wild and domestic sheep. Analyzing whole-genome sequences, we observed a substantially reduced X-to-autosome diversity ratio (∼0.6) compared with the value expected under a neutral model (0.75). In particular, one large X-linked segment (43.05-79.25 Mb) was found to show extremely low diversity, most likely due to a high density of coding genes, featuring highly conserved regions. In general, we observed higher nucleotide diversity on the autosomes, but a flat diversity gradient in X-linked segments, as a function of increasing distance from the nearest genes, leading to a decreased X: autosome (X/A) diversity ratio and contrasting to the positive correlation detected in primates and other model animals. Our evidence suggests that accelerated genetic drift but reduced directional selection on X chromosome, as well as sex-biased demographic events, explain low X-chromosome diversity in sheep species. The distinct patterns of X-linked and X/A diversity we observed between Middle Eastern and non-Middle Eastern sheep populations can be explained by multiple migrations, selection, and admixture during the domestic sheep's recent postdomestication demographic expansion, coupled with natural selection for adaptation to new environments. In addition, we identify important novel genes involved in abnormal behavioral phenotypes, metabolism, and immunity, under selection on the sheep X-chromosome.

Genomic selection for the improvement of antibody response to Newcastle disease and avian influenza virus in chickens.

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Tianfei Liu

Full Text Available Newcastle disease (ND and avian influenza (AI are the most feared diseases in the poultry industry worldwide. They can cause flock mortality up to 100%, resulting in a catastrophic economic loss. This is the first study to investigate the feasibility of genomic selection for antibody response to Newcastle disease virus (Ab-NDV and antibody response to Avian Influenza virus (Ab-AIV in chickens. The data were collected from a crossbred population. Breeding values for Ab-NDV and Ab-AIV were estimated using a pedigree-based best linear unbiased prediction model (BLUP and a genomic best linear unbiased prediction model (GBLUP. Single-trait and multiple-trait analyses were implemented. According to the analysis using the pedigree-based model, the heritability for Ab-NDV estimated from the single-trait and multiple-trait models was 0.478 and 0.487, respectively. The heritability for Ab-AIV estimated from the two models was 0.301 and 0.291, respectively. The estimated genetic correlation between the two traits was 0.438. A four-fold cross-validation was used to assess the accuracy of the estimated breeding values (EBV in the two validation scenarios. In the family sample scenario each half-sib family is randomly allocated to one of four subsets and in the random sample scenario the individuals are randomly divided into four subsets. In the family sample scenario, compared with the pedigree-based model, the accuracy of the genomic prediction increased from 0.086 to 0.237 for Ab-NDV and from 0.080 to 0.347 for Ab-AIV. In the random sample scenario, the accuracy was improved from 0.389 to 0.427 for Ab-NDV and from 0.281 to 0.367 for Ab-AIV. The multiple-trait GBLUP model led to a slightly higher accuracy of genomic prediction for both traits. These results indicate that genomic selection for antibody response to ND and AI in chickens is promising.

Genome-wide distribution of genetic diversity and linkage disequilibrium in a mass-selected population of maritime pine

Science.gov (United States)

2014-01-01

Background The accessibility of high-throughput genotyping technologies has contributed greatly to the development of genomic resources in non-model organisms. High-density genotyping arrays have only recently been developed for some economically important species such as conifers. The potential for using genomic technologies in association mapping and breeding depends largely on the genome wide patterns of diversity and linkage disequilibrium in current breeding populations. This study aims to deepen our knowledge regarding these issues in maritime pine, the first species used for reforestation in south western Europe. Results Using a new map merging algorithm, we first established a 1,712 cM composite linkage map (comprising 1,838 SNP markers in 12 linkage groups) by bringing together three already available genetic maps. Using rigorous statistical testing based on kernel density estimation and resampling we identified cold and hot spots of recombination. In parallel, 186 unrelated trees of a mass-selected population were genotyped using a 12k-SNP array. A total of 2,600 informative SNPs allowed to describe historical recombination, genetic diversity and genetic structure of this recently domesticated breeding pool that forms the basis of much of the current and future breeding of this species. We observe very low levels of population genetic structure and find no evidence that artificial selection has caused a reduction in genetic diversity. By combining these two pieces of information, we provided the map position of 1,671 SNPs corresponding to 1,192 different loci. This made it possible to analyze the spatial pattern of genetic diversity (H e ) and long distance linkage disequilibrium (LD) along the chromosomes. We found no particular pattern in the empirical variogram of H e across the 12 linkage groups and, as expected for an outcrossing species with large effective population size, we observed an almost complete lack of long distance LD. Conclusions These

Genomic prediction using subsampling

OpenAIRE

Xavier, Alencar; Xu, Shizhong; Muir, William; Rainey, Katy Martin

2017-01-01

Background Genome-wide assisted selection is a critical tool for the?genetic improvement of plants and animals. Whole-genome regression models in Bayesian framework represent the main family of prediction methods. Fitting such models with a large number of observations involves a prohibitive computational burden. We propose the use of subsampling bootstrap Markov chain in genomic prediction. Such method consists of fitting whole-genome regression models by subsampling observations in each rou...

Deleterious mutation accumulation in organelle genomes.

Science.gov (United States)

Lynch, M; Blanchard, J L

1998-01-01

It is well established on theoretical grounds that the accumulation of mildly deleterious mutations in nonrecombining genomes is a major extinction risk in obligately asexual populations. Sexual populations can also incur mutational deterioration in genomic regions that experience little or no recombination, i.e., autosomal regions near centromeres, Y chromosomes, and organelle genomes. Our results suggest, for a wide array of genes (transfer RNAs, ribosomal RNAs, and proteins) in a diverse collection of species (animals, plants, and fungi), an almost universal increase in the fixation probabilities of mildly deleterious mutations arising in mitochondrial and chloroplast genomes relative to those arising in the recombining nuclear genome. This enhanced width of the selective sieve in organelle genomes does not appear to be a consequence of relaxed selection, but can be explained by the decline in the efficiency of selection that results from the reduction of effective population size induced by uniparental inheritance. Because of the very low mutation rates of organelle genomes (on the order of 10(-4) per genome per year), the reduction in fitness resulting from mutation accumulation in such genomes is a very long-term process, not likely to imperil many species on time scales of less than a million years, but perhaps playing some role in phylogenetic lineage sorting on time scales of 10 to 100 million years.

Signatures of selection in the Iberian honey bee (Apis mellifera iberiensis) revealed by a genome scan analysis of single nucleotide polymorphisms.

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Chávez-Galarza, Julio; Henriques, Dora; Johnston, J Spencer; Azevedo, João C; Patton, John C; Muñoz, Irene; De la Rúa, Pilar; Pinto, M Alice

2013-12-01

Understanding the genetic mechanisms of adaptive population divergence is one of the most fundamental endeavours in evolutionary biology and is becoming increasingly important as it will allow predictions about how organisms will respond to global environmental crisis. This is particularly important for the honey bee, a species of unquestionable ecological and economical importance that has been exposed to increasing human-mediated selection pressures. Here, we conducted a single nucleotide polymorphism (SNP)-based genome scan in honey bees collected across an environmental gradient in Iberia and used four FST -based outlier tests to identify genomic regions exhibiting signatures of selection. Additionally, we analysed associations between genetic and environmental data for the identification of factors that might be correlated or act as selective pressures. With these approaches, 4.4% (17 of 383) of outlier loci were cross-validated by four FST -based methods, and 8.9% (34 of 383) were cross-validated by at least three methods. Of the 34 outliers, 15 were found to be strongly associated with one or more environmental variables. Further support for selection, provided by functional genomic information, was particularly compelling for SNP outliers mapped to different genes putatively involved in the same function such as vision, xenobiotic detoxification and innate immune response. This study enabled a more rigorous consideration of selection as the underlying cause of diversity patterns in Iberian honey bees, representing an important first step towards the identification of polymorphisms implicated in local adaptation and possibly in response to recent human-mediated environmental changes. © 2013 John Wiley & Sons Ltd.

Genomic prediction of traits related to canine hip dysplasia

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Enrique eSanchez-Molano

2015-03-01

Full Text Available Increased concern for the welfare of pedigree dogs has led to development of selection programs against inherited diseases. An example is canine hip dysplasia (CHD, which has a moderate heritability and a high prevalence in some large-sized breeds. To date, selection using phenotypes has led to only modest improvement, and alternative strategies such as genomic selection may prove more effective. The primary aims of this study were to compare the performance of pedigree- and genomic-based breeding against CHD in the UK Labrador retriever population and to evaluate the performance of different genomic selection methods. A sample of 1179 Labrador Retrievers evaluated for CHD according to the UK scoring method (hip score, HS was genotyped with the Illumina CanineHD BeadChip. Twelve functions of HS and its component traits were analyzed using different statistical methods (GBLUP, Bayes C and Single-Step methods, and results were compared with a pedigree-based approach (BLUP using cross-validation. Genomic methods resulted in similar or higher accuracies than pedigree-based methods with training sets of 944 individuals for all but the untransformed HS, suggesting that genomic selection is an effective strategy. GBLUP and Bayes C gave similar prediction accuracies for HS and related traits, indicating a polygenic architecture. This conclusion was also supported by the low accuracies obtained in additional GBLUP analyses performed using only the SNPs with highest test statistics, also indicating that marker-assisted selection would not be as effective as genomic selection. A Single-Step method that combines genomic and pedigree information also showed higher accuracy than GBLUP and Bayes C for the log-transformed HS, which is currently used for pedigree based evaluations in UK. In conclusion, genomic selection is a promising alternative to pedigree-based selection against CHD, requiring more phenotypes with genomic data to improve further the accuracy

Genomic and Transcriptomic Associations Identify a New Insecticide Resistance Phenotype for the Selective Sweep at the Cyp6g1 Locus of Drosophila melanogaster.

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Battlay, Paul; Schmidt, Joshua M; Fournier-Level, Alexandre; Robin, Charles

2016-08-09

Scans of the Drosophila melanogaster genome have identified organophosphate resistance loci among those with the most pronounced signature of positive selection. In this study, the molecular basis of resistance to the organophosphate insecticide azinphos-methyl was investigated using the Drosophila Genetic Reference Panel, and genome-wide association. Recently released full transcriptome data were used to extend the utility of the Drosophila Genetic Reference Panel resource beyond traditional genome-wide association studies to allow systems genetics analyses of phenotypes. We found that both genomic and transcriptomic associations independently identified Cyp6g1, a gene involved in resistance to DDT and neonicotinoid insecticides, as the top candidate for azinphos-methyl resistance. This was verified by transgenically overexpressing Cyp6g1 using natural regulatory elements from a resistant allele, resulting in a 6.5-fold increase in resistance. We also identified four novel candidate genes associated with azinphos-methyl resistance, all of which are involved in either regulation of fat storage, or nervous system development. In Cyp6g1, we find a demonstrable resistance locus, a verification that transcriptome data can be used to identify variants associated with insecticide resistance, and an overlap between peaks of a genome-wide association study, and a genome-wide selective sweep analysis. Copyright © 2016 Battlay et al.

Switches in Genomic GC Content Drive Shifts of Optimal Codons under Sustained Selection on Synonymous Sites

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Sun, Yu; Tamarit, Daniel

2017-01-01

Abstract The major codon preference model suggests that codons read by tRNAs in high concentrations are preferentially utilized in highly expressed genes. However, the identity of the optimal codons differs between species although the forces driving such changes are poorly understood. We suggest that these questions can be tackled by placing codon usage studies in a phylogenetic framework and that bacterial genomes with extreme nucleotide composition biases provide informative model systems. Switches in the background substitution biases from GC to AT have occurred in Gardnerella vaginalis (GC = 32%), and from AT to GC in Lactobacillus delbrueckii (GC = 62%) and Lactobacillus fermentum (GC = 63%). We show that despite the large effects on codon usage patterns by these switches, all three species evolve under selection on synonymous sites. In G. vaginalis, the dramatic codon frequency changes coincide with shifts of optimal codons. In contrast, the optimal codons have not shifted in the two Lactobacillus genomes despite an increased fraction of GC-ending codons. We suggest that all three species are in different phases of an on-going shift of optimal codons, and attribute the difference to a stronger background substitution bias and/or longer time since the switch in G. vaginalis. We show that comparative and correlative methods for optimal codon identification yield conflicting results for genomes in flux and discuss possible reasons for the mispredictions. We conclude that switches in the direction of the background substitution biases can drive major shifts in codon preference patterns even under sustained selection on synonymous codon sites. PMID:27540085

Genome-wide patterns of differentiation and spatially varying selection between postglacial recolonization lineages of Populus alba (Salicaceae), a widespread forest tree.

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Stölting, Kai N; Paris, Margot; Meier, Cécile; Heinze, Berthold; Castiglione, Stefano; Bartha, Denes; Lexer, Christian

2015-08-01

Studying the divergence continuum in plants is relevant to fundamental and applied biology because of the potential to reveal functionally important genetic variation. In this context, whole-genome sequencing (WGS) provides the necessary rigour for uncovering footprints of selection. We resequenced populations of two divergent phylogeographic lineages of Populus alba (n = 48), thoroughly characterized by microsatellites (n = 317), and scanned their genomes for regions of unusually high allelic differentiation and reduced diversity using > 1.7 million single nucleotide polymorphisms (SNPs) from WGS. Results were confirmed by Sanger sequencing. On average, 9134 high-differentiation (≥ 4 standard deviations) outlier SNPs were uncovered between populations, 848 of which were shared by ≥ three replicate comparisons. Annotation revealed that 545 of these were located in 437 predicted genes. Twelve percent of differentiation outlier genome regions exhibited significantly reduced genetic diversity. Gene ontology (GO) searches were successful for 327 high-differentiation genes, and these were enriched for 63 GO terms. Our results provide a snapshot of the roles of 'hard selective sweeps' vs divergent selection of standing genetic variation in distinct postglacial recolonization lineages of P. alba. Thus, this study adds to our understanding of the mechanisms responsible for the origin of functionally relevant variation in temperate trees. © 2015 The Authors. New Phytologist © 2015 New Phytologist Trust.

Seasonal and Static Gravity Field of Mars from MGS, Mars Odyssey and MRO Radio Science

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Genova, Antonio; Goossens, Sander; Lemoine, Frank G.; Mazarico, Erwan; Neumann, Gregory A.; Smith, David E.; Zuber, Maria T.

2016-01-01

We present a spherical harmonic solution of the static gravity field of Mars to degree and order 120, GMM-3, that has been calculated using the Deep Space Network tracking data of the NASA Mars missions, Mars Global Surveyor (MGS), Mars Odyssey (ODY), and the Mars Reconnaissance Orbiter (MRO). We have also jointly determined spherical harmonic solutions for the static and time-variable gravity field of Mars, and the Mars k 2 Love numbers, exclusive of the gravity contribution of the atmosphere. Consequently, the retrieved time-varying gravity coefficients and the Love number k 2 solely yield seasonal variations in the mass of the polar caps and the solid tides of Mars, respectively. We obtain a Mars Love number k 2 of 0.1697 +/-0.0027 (3- sigma). The inclusion of MRO tracking data results in improved seasonal gravity field coefficients C 30 and, for the first time, C 50 . Refinements of the atmospheric model in our orbit determination program have allowed us to monitor the odd zonal harmonic C 30 for approx.1.5 solar cycles (16 years). This gravity model shows improved correlations with MOLA topography up to 15% larger at higher harmonics ( l = 60–80) than previous solutions.

Complete plastid genome sequences suggest strong selection for retention of photosynthetic genes in the parasitic plant genus Cuscuta.

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McNeal, Joel R; Kuehl, Jennifer V; Boore, Jeffrey L; de Pamphilis, Claude W

2007-10-24

Plastid genome content and protein sequence are highly conserved across land plants and their closest algal relatives. Parasitic plants, which obtain some or all of their nutrition through an attachment to a host plant, are often a striking exception. Heterotrophy can lead to relaxed constraint on some plastid genes or even total gene loss. We sequenced plastid genomes of two species in the parasitic genus Cuscuta along with a non-parasitic relative, Ipomoea purpurea, to investigate changes in the plastid genome that may result from transition to the parasitic lifestyle. Aside from loss of all ndh genes, Cuscuta exaltata retains photosynthetic and photorespiratory genes that evolve under strong selective constraint. Cuscuta obtusiflora has incurred substantially more change to its plastid genome, including loss of all genes for the plastid-encoded RNA polymerase. Despite extensive change in gene content and greatly increased rate of overall nucleotide substitution, C. obtusiflora also retains all photosynthetic and photorespiratory genes with only one minor exception. Although Epifagus virginiana, the only other parasitic plant with its plastid genome sequenced to date, has lost a largely overlapping set of transfer-RNA and ribosomal genes as Cuscuta, it has lost all genes related to photosynthesis and maintains a set of genes which are among the most divergent in Cuscuta. Analyses demonstrate photosynthetic genes are under the highest constraint of any genes within the plastid genomes of Cuscuta, indicating a function involving RuBisCo and electron transport through photosystems is still the primary reason for retention of the plastid genome in these species.

Complete plastid genome sequences suggest strong selection for retention of photosynthetic genes in the parasitic plant genus Cuscuta

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Kuehl Jennifer V

2007-10-01

Full Text Available Abstract Background Plastid genome content and protein sequence are highly conserved across land plants and their closest algal relatives. Parasitic plants, which obtain some or all of their nutrition through an attachment to a host plant, are often a striking exception. Heterotrophy can lead to relaxed constraint on some plastid genes or even total gene loss. We sequenced plastid genomes of two species in the parasitic genus Cuscuta along with a non-parasitic relative, Ipomoea purpurea, to investigate changes in the plastid genome that may result from transition to the parasitic lifestyle. Results Aside from loss of all ndh genes, Cuscuta exaltata retains photosynthetic and photorespiratory genes that evolve under strong selective constraint. Cuscuta obtusiflora has incurred substantially more change to its plastid genome, including loss of all genes for the plastid-encoded RNA polymerase. Despite extensive change in gene content and greatly increased rate of overall nucleotide substitution, C. obtusiflora also retains all photosynthetic and photorespiratory genes with only one minor exception. Conclusion Although Epifagus virginiana, the only other parasitic plant with its plastid genome sequenced to date, has lost a largely overlapping set of transfer-RNA and ribosomal genes as Cuscuta, it has lost all genes related to photosynthesis and maintains a set of genes which are among the most divergent in Cuscuta. Analyses demonstrate photosynthetic genes are under the highest constraint of any genes within the plastid genomes of Cuscuta, indicating a function involving RuBisCo and electron transport through photosystems is still the primary reason for retention of the plastid genome in these species.

Family genome browser: visualizing genomes with pedigree information.

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Juan, Liran; Liu, Yongzhuang; Wang, Yongtian; Teng, Mingxiang; Zang, Tianyi; Wang, Yadong

2015-07-15

Families with inherited diseases are widely used in Mendelian/complex disease studies. Owing to the advances in high-throughput sequencing technologies, family genome sequencing becomes more and more prevalent. Visualizing family genomes can greatly facilitate human genetics studies and personalized medicine. However, due to the complex genetic relationships and high similarities among genomes of consanguineous family members, family genomes are difficult to be visualized in traditional genome visualization framework. How to visualize the family genome variants and their functions with integrated pedigree information remains a critical challenge. We developed the Family Genome Browser (FGB) to provide comprehensive analysis and visualization for family genomes. The FGB can visualize family genomes in both individual level and variant level effectively, through integrating genome data with pedigree information. Family genome analysis, including determination of parental origin of the variants, detection of de novo mutations, identification of potential recombination events and identical-by-decent segments, etc., can be performed flexibly. Diverse annotations for the family genome variants, such as dbSNP memberships, linkage disequilibriums, genes, variant effects, potential phenotypes, etc., are illustrated as well. Moreover, the FGB can automatically search de novo mutations and compound heterozygous variants for a selected individual, and guide investigators to find high-risk genes with flexible navigation options. These features enable users to investigate and understand family genomes intuitively and systematically. The FGB is available at http://mlg.hit.edu.cn/FGB/. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Genomic signatures of geographic isolation and natural selection in coral reef fishes.

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Gaither, Michelle R; Bernal, Moisés A; Coleman, Richard R; Bowen, Brian W; Jones, Shelley A; Simison, W Brian; Rocha, Luiz A

2015-04-01

The drivers of speciation remain among the most controversial topics in evolutionary biology. Initially, Darwin emphasized natural selection as a primary mechanism of speciation, but the architects of the modern synthesis largely abandoned that view in favour of divergence by geographic isolation. The balance between selection and isolation is still at the forefront of the evolutionary debate, especially for the world's tropical oceans where biodiversity is high, but isolating barriers are few. Here, we identify the drivers of speciation in Pacific reef fishes of the genus Acanthurus by comparative genome scans of two peripheral populations that split from a large Central-West Pacific lineage at roughly the same time. Mitochondrial sequences indicate that populations in the Hawaiian Archipelago and the Marquesas Islands became isolated approximately 0.5 Ma. The Hawaiian lineage is morphologically indistinguishable from the widespread Pacific form, but the Marquesan form is recognized as a distinct species that occupies an unusual tropical ecosystem characterized by upwelling, turbidity, temperature fluctuations, algal blooms and little coral cover. An analysis of 3737 SNPs reveals a strong signal of selection at the Marquesas, with 59 loci under disruptive selection including an opsin Rh2 locus. While both the Hawaiian and Marquesan populations indicate signals of drift, the former shows a weak signal of selection that is comparable with populations in the Central-West Pacific. This contrast between closely related lineages reveals one population diverging due primarily to geographic isolation and genetic drift, and the other achieving taxonomic species status under the influence of selection. © 2015 The Authors. Molecular Ecology Published by John Wiley & Sons Ltd.

Increased prediction accuracy in wheat breeding trials using a marker × environment interaction genomic selection model.

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Lopez-Cruz, Marco; Crossa, Jose; Bonnett, David; Dreisigacker, Susanne; Poland, Jesse; Jannink, Jean-Luc; Singh, Ravi P; Autrique, Enrique; de los Campos, Gustavo

2015-02-06

Genomic selection (GS) models use genome-wide genetic information to predict genetic values of candidates of selection. Originally, these models were developed without considering genotype × environment interaction(G×E). Several authors have proposed extensions of the single-environment GS model that accommodate G×E using either covariance functions or environmental covariates. In this study, we model G×E using a marker × environment interaction (M×E) GS model; the approach is conceptually simple and can be implemented with existing GS software. We discuss how the model can be implemented by using an explicit regression of phenotypes on markers or using co-variance structures (a genomic best linear unbiased prediction-type model). We used the M×E model to analyze three CIMMYT wheat data sets (W1, W2, and W3), where more than 1000 lines were genotyped using genotyping-by-sequencing and evaluated at CIMMYT's research station in Ciudad Obregon, Mexico, under simulated environmental conditions that covered different irrigation levels, sowing dates and planting systems. We compared the M×E model with a stratified (i.e., within-environment) analysis and with a standard (across-environment) GS model that assumes that effects are constant across environments (i.e., ignoring G×E). The prediction accuracy of the M×E model was substantially greater of that of an across-environment analysis that ignores G×E. Depending on the prediction problem, the M×E model had either similar or greater levels of prediction accuracy than the stratified analyses. The M×E model decomposes marker effects and genomic values into components that are stable across environments (main effects) and others that are environment-specific (interactions). Therefore, in principle, the interaction model could shed light over which variants have effects that are stable across environments and which ones are responsible for G×E. The data set and the scripts required to reproduce the analysis are

Factors affecting the accuracy of genomic selection for growth and wood quality traits in an advanced-breeding population of black spruce (Picea mariana).

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Lenz, Patrick R N; Beaulieu, Jean; Mansfield, Shawn D; Clément, Sébastien; Desponts, Mireille; Bousquet, Jean

2017-04-28

Genomic selection (GS) uses information from genomic signatures consisting of thousands of genetic markers to predict complex traits. As such, GS represents a promising approach to accelerate tree breeding, which is especially relevant for the genetic improvement of boreal conifers characterized by long breeding cycles. In the present study, we tested GS in an advanced-breeding population of the boreal black spruce (Picea mariana [Mill.] BSP) for growth and wood quality traits, and concurrently examined factors affecting GS model accuracy. The study relied on 734 25-year-old trees belonging to 34 full-sib families derived from 27 parents and that were established on two contrasting sites. Genomic profiles were obtained from 4993 Single Nucleotide Polymorphisms (SNPs) representative of as many gene loci distributed among the 12 linkage groups common to spruce. GS models were obtained for four growth and wood traits. Validation using independent sets of trees showed that GS model accuracy was high, related to trait heritability and equivalent to that of conventional pedigree-based models. In forward selection, gains per unit of time were three times higher with the GS approach than with conventional selection. In addition, models were also accurate across sites, indicating little genotype-by-environment interaction in the area investigated. Using information from half-sibs instead of full-sibs led to a significant reduction in model accuracy, indicating that the inclusion of relatedness in the model contributed to its higher accuracies. About 500 to 1000 markers were sufficient to obtain GS model accuracy almost equivalent to that obtained with all markers, whether they were well spread across the genome or from a single linkage group, further confirming the implication of relatedness and potential long-range linkage disequilibrium (LD) in the high accuracy estimates obtained. Only slightly higher model accuracy was obtained when using marker subsets that were

Toward integration of genomic selection with crop modelling: the development of an integrated approach to predicting rice heading dates.

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Onogi, Akio; Watanabe, Maya; Mochizuki, Toshihiro; Hayashi, Takeshi; Nakagawa, Hiroshi; Hasegawa, Toshihiro; Iwata, Hiroyoshi

2016-04-01

It is suggested that accuracy in predicting plant phenotypes can be improved by integrating genomic prediction with crop modelling in a single hierarchical model. Accurate prediction of phenotypes is important for plant breeding and management. Although genomic prediction/selection aims to predict phenotypes on the basis of whole-genome marker information, it is often difficult to predict phenotypes of complex traits in diverse environments, because plant phenotypes are often influenced by genotype-environment interaction. A possible remedy is to integrate genomic prediction with crop/ecophysiological modelling, which enables us to predict plant phenotypes using environmental and management information. To this end, in the present study, we developed a novel method for integrating genomic prediction with phenological modelling of Asian rice (Oryza sativa, L.), allowing the heading date of untested genotypes in untested environments to be predicted. The method simultaneously infers the phenological model parameters and whole-genome marker effects on the parameters in a Bayesian framework. By cultivating backcross inbred lines of Koshihikari × Kasalath in nine environments, we evaluated the potential of the proposed method in comparison with conventional genomic prediction, phenological modelling, and two-step methods that applied genomic prediction to phenological model parameters inferred from Nelder-Mead or Markov chain Monte Carlo algorithms. In predicting heading dates of untested lines in untested environments, the proposed and two-step methods tended to provide more accurate predictions than the conventional genomic prediction methods, particularly in environments where phenotypes from environments similar to the target environment were unavailable for training genomic prediction. The proposed method showed greater accuracy in prediction than the two-step methods in all cross-validation schemes tested, suggesting the potential of the integrated approach in

Genomic selection for crossbred performance accounting for breed-specific effects.

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Lopes, Marcos S; Bovenhuis, Henk; Hidalgo, André M; van Arendonk, Johan A M; Knol, Egbert F; Bastiaansen, John W M

2017-06-26

Breed-specific effects are observed when the same allele of a given genetic marker has a different effect depending on its breed origin, which results in different allele substitution effects across breeds. In such a case, single-breed breeding values may not be the most accurate predictors of crossbred performance. Our aim was to estimate the contribution of alleles from each parental breed to the genetic variance of traits that are measured in crossbred offspring, and to compare the prediction accuracies of estimated direct genomic values (DGV) from a traditional genomic selection model (GS) that are trained on purebred or crossbred data, with accuracies of DGV from a model that accounts for breed-specific effects (BS), trained on purebred or crossbred data. The final dataset was composed of 924 Large White, 924 Landrace and 924 two-way cross (F1) genotyped and phenotyped animals. The traits evaluated were litter size (LS) and gestation length (GL) in pigs. The genetic correlation between purebred and crossbred performance was higher than 0.88 for both LS and GL. For both traits, the additive genetic variance was larger for alleles inherited from the Large White breed compared to alleles inherited from the Landrace breed (0.74 and 0.56 for LS, and 0.42 and 0.40 for GL, respectively). The highest prediction accuracies of crossbred performance were obtained when training was done on crossbred data. For LS, prediction accuracies were the same for GS and BS DGV (0.23), while for GL, prediction accuracy for BS DGV was similar to the accuracy of GS DGV (0.53 and 0.52, respectively). In this study, training on crossbred data resulted in higher prediction accuracy than training on purebred data and evidence of breed-specific effects for LS and GL was demonstrated. However, when training was done on crossbred data, both GS and BS models resulted in similar prediction accuracies. In future studies, traits with a lower genetic correlation between purebred and crossbred

Genomic Selection in the Era of Next Generation Sequencing for Complex Traits in Plant Breeding.

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Bhat, Javaid A; Ali, Sajad; Salgotra, Romesh K; Mir, Zahoor A; Dutta, Sutapa; Jadon, Vasudha; Tyagi, Anshika; Mushtaq, Muntazir; Jain, Neelu; Singh, Pradeep K; Singh, Gyanendra P; Prabhu, K V

2016-01-01

Genomic selection (GS) is a promising approach exploiting molecular genetic markers to design novel breeding programs and to develop new markers-based models for genetic evaluation. In plant breeding, it provides opportunities to increase genetic gain of complex traits per unit time and cost. The cost-benefit balance was an important consideration for GS to work in crop plants. Availability of genome-wide high-throughput, cost-effective and flexible markers, having low ascertainment bias, suitable for large population size as well for both model and non-model crop species with or without the reference genome sequence was the most important factor for its successful and effective implementation in crop species. These factors were the major limitations to earlier marker systems viz., SSR and array-based, and was unimaginable before the availability of next-generation sequencing (NGS) technologies which have provided novel SNP genotyping platforms especially the genotyping by sequencing. These marker technologies have changed the entire scenario of marker applications and made the use of GS a routine work for crop improvement in both model and non-model crop species. The NGS-based genotyping have increased genomic-estimated breeding value prediction accuracies over other established marker platform in cereals and other crop species, and made the dream of GS true in crop breeding. But to harness the true benefits from GS, these marker technologies will be combined with high-throughput phenotyping for achieving the valuable genetic gain from complex traits. Moreover, the continuous decline in sequencing cost will make the WGS feasible and cost effective for GS in near future. Till that time matures the targeted sequencing seems to be more cost-effective option for large scale marker discovery and GS, particularly in case of large and un-decoded genomes.

Characterizing neutral genomic diversity and selection signatures in indigenous populations of Moroccan goats (Capra hircus using WGS data

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Badr eBenjelloun

2015-04-01

Full Text Available Since the time of their domestication, goats (Capra hircus have evolved in a large variety of locally adapted populations in response to different human and environmental pressures. In the present era, many indigenous populations are threatened with extinction due to their substitution by cosmopolitan breeds, while they might represent highly valuable genomic resources. It is thus crucial to characterize the neutral and adaptive genetic diversity of indigenous populations. A fine characterization of whole genome variation in farm animals is now possible by using new sequencing technologies. We sequenced the complete genome at 12X coverage of 44 goats geographically representative of the three phenotypically distinct indigenous populations in Morocco. The study of mitochondrial genomes showed a high diversity exclusively restricted to the haplogroup A. The 44 nuclear genomes showed a very high diversity (24 million variants associated with low linkage disequilibrium. The overall genetic diversity was weakly structured according to geography and phenotypes. When looking for signals of positive selection in each population we identified many candidate genes, several of which gave insights into the metabolic pathways or biological processes involved in the adaptation to local conditions (e.g. panting in warm/desert conditions. This study highlights the interest of WGS data to characterize livestock genomic diversity. It illustrates the valuable genetic richness present in indigenous populations that have to be sustainably managed and may represent valuable genetic resources for the long-term preservation of the species.

Genome-wide analysis of signatures of selection in populations of African honey bees (Apis mellifera) using new web-based tools.

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Fuller, Zachary L; Niño, Elina L; Patch, Harland M; Bedoya-Reina, Oscar C; Baumgarten, Tracey; Muli, Elliud; Mumoki, Fiona; Ratan, Aakrosh; McGraw, John; Frazier, Maryann; Masiga, Daniel; Schuster, Stephen; Grozinger, Christina M; Miller, Webb

2015-07-10

With the development of inexpensive, high-throughput sequencing technologies, it has become feasible to examine questions related to population genetics and molecular evolution of non-model species in their ecological contexts on a genome-wide scale. Here, we employed a newly developed suite of integrated, web-based programs to examine population dynamics and signatures of selection across the genome using several well-established tests, including F ST, pN/pS, and McDonald-Kreitman. We applied these techniques to study populations of honey bees (Apis mellifera) in East Africa. In Kenya, there are several described A. mellifera subspecies, which are thought to be localized to distinct ecological regions. We performed whole genome sequencing of 11 worker honey bees from apiaries distributed throughout Kenya and identified 3.6 million putative single-nucleotide polymorphisms. The dense coverage allowed us to apply several computational procedures to study population structure and the evolutionary relationships among the populations, and to detect signs of adaptive evolution across the genome. While there is considerable gene flow among the sampled populations, there are clear distinctions between populations from the northern desert region and those from the temperate, savannah region. We identified several genes showing population genetic patterns consistent with positive selection within African bee populations, and between these populations and European A. mellifera or Asian Apis florea. These results lay the groundwork for future studies of adaptive ecological evolution in honey bees, and demonstrate the use of new, freely available web-based tools and workflows ( http://usegalaxy.org/r/kenyanbee ) that can be applied to any model system with genomic information.

Comparative genomics of Ceriporiopsis subvermispora and Phanerochaete chrysosporium provide insight into selective ligninolysis

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Fernandez-Fueyo, Elena; Ruiz-Duenas, Francisco J.; Ferreira, Patrica; Floudas, Dimitrios; HIbbett, David S.; Canessa, Paulo; Larrondo, Luis F.; James, Tim Y.; Seelenfreund, Daniela; Lobos, Sergio; Polanco, Ruben; Tello, Mario; Honda, Yoichi; Watanabe, Takahito; Watanabe, Takashi; Ryu, Jae San; Kubicek, Christian P.; Schmoll, Monika; Gaskell, Jill; Hammel, Kenneth E.; John, Franz J.; Vanden Wymelenberg, Amber; Sabat, Grzegorz; Splinter BonDurant, Sandra; Syed, Khajamohiddin; Yadav, Jagjit S.; Doddapaneni, Harshavardhan; Subramanian, Venkataramanan; Lavin, Jose L.; Oguiza, Jose A.; Perez, Gumer; Pisabarro, Antonio G.; Ramirez, Lucia; Santoyo, Francisco; Master, Emma; Coutinho, Pedro M.; Henrissat, Bernard; Lombard, Vincent; Magnuson, Jon Karl; Kues, Ursula; Hori, Chiaki; Igarashi, Kiyohiko; Samejima, Masahiro; Held, Benjamin W.; Barry, Kerrie W.; LaButti, Kurt M.; Lapidus, Alla; Lindquist, Erika A.; Lucas, Susan M.; Riley, Robert; Salamov, Asaf A.; Hoffmeister, Dirk; Schwenk, Daniel; Hadar, Yitzhak; Yarden, Oded; de Vries, Ronald P.; Wiebenga, Ad; Stenlid, Jan; Eastwood, Daniel; Grigoriev, Igor V.; Berka, Randy M.; Blanchette, Robert A.; Kersten, Phil; Martinez, Angel T.; Vicuna, Rafael; Cullen, Dan

2011-12-06

Efficient lignin depolymerization is unique to the wood decay basidiomycetes, collectively referred to as white rot fungi. Phanerochaete chrysosporium simultaneously degrades lignin and cellulose, whereas the closely related species, Ceriporiopsis subvermispora, also depolymerizes lignin but may do so with relatively little cellulose degradation. To investigate the basis for selective ligninolysis, we conducted comparative genome analysis of C. subvermispora and P. chrysosporium. Genes encoding manganese peroxidase numbered 13 and five in C. subvermispora and P. chrysosporium, respectively. In addition, the C. subvermispora genome contains at least seven genes predicted to encode laccases, whereas the P. chrysosporium genome contains none. We also observed expansion of the number of C. subvermispora desaturase-encoding genes putatively involved in lipid metabolism. Microarray-based transcriptome analysis showed substantial up-regulation of several desaturase and MnP genes in wood-containing medium. MS identified MnP proteins in C. subvermispora culture filtrates, but none in P. chrysosporium cultures. These results support the importance of MnP and a lignin degradation mechanism whereby cleavage of the dominant nonphenolic structures is mediated by lipid peroxidation products. Two C. subvermispora genes were predicted to encode peroxidases structurally similar to P. chrysosporium lignin peroxidase and, following heterologous expression in Escherichia coli, the enzymes were shown to oxidize high redox potential substrates, but not Mn2. Apart from oxidative lignin degradation, we also examined cellulolytic and hemicellulolytic systems in both fungi. In summary, the C. subvermispora genetic inventory and expression patterns exhibit increased oxidoreductase potential and diminished cellulolytic capability relative to P. chrysosporium.

An evolutionary analysis of genome expansion and pathogenicity in Escherichia coli.

Science.gov (United States)

Bohlin, Jon; Brynildsrud, Ola B; Sekse, Camilla; Snipen, Lars

2014-10-09

There are several studies describing loss of genes through reductive evolution in microbes, but how selective forces are associated with genome expansion due to horizontal gene transfer (HGT) has not received similar attention. The aim of this study was therefore to examine how selective pressures influence genome expansion in 53 fully sequenced and assembled Escherichia coli strains. We also explored potential connections between genome expansion and the attainment of virulence factors. This was performed using estimations of several genomic parameters such as AT content, genomic drift (measured using relative entropy), genome size and estimated HGT size, which were subsequently compared to analogous parameters computed from the core genome consisting of 1729 genes common to the 53 E. coli strains. Moreover, we analyzed how selective pressures (quantified using relative entropy and dN/dS), acting on the E. coli core genome, influenced lineage and phylogroup formation. Hierarchical clustering of dS and dN estimations from the E. coli core genome resulted in phylogenetic trees with topologies in agreement with known E. coli taxonomy and phylogroups. High values of dS, compared to dN, indicate that the E. coli core genome has been subjected to substantial purifying selection over time; significantly more than the non-core part of the genome (pcoli genome size correlated with estimated HGT size (pcoli are largely attained through HGT. No associations were found between selective pressures operating on the E. coli core genome, as estimated using relative entropy, and genome size (p~0.98). On a larger time frame, genome expansion in E. coli, which is significantly associated with the acquisition of virulence factors, appears to be independent of selective forces operating on the core genome.

Evolution of small prokaryotic genomes

Directory of Open Access Journals (Sweden)

David José Martínez-Cano

2015-01-01

Full Text Available As revealed by genome sequencing, the biology of prokaryotes with reduced genomes is strikingly diverse. These include free-living prokaryotes with ~800 genes as well as endosymbiotic bacteria with as few as ~140 genes. Comparative genomics is revealing the evolutionary mechanisms that led to these small genomes. In the case of free-living prokaryotes, natural selection directly favored genome reduction, while in the case of endosymbiotic prokaryotes neutral processes played a more prominent role. However, new experimental data suggest that selective processes may be at operation as well for endosymbiotic prokaryotes at least during the first stages of genome reduction. Endosymbiotic prokaryotes have evolved diverse strategies for living with reduced gene sets inside a host-defined medium. These include utilization of host-encoded functions (some of them coded by genes acquired by gene transfer from the endosymbiont and/or other bacteria; metabolic complementation between co-symbionts; and forming consortiums with other bacteria within the host. Recent genome sequencing projects of intracellular mutualistic bacteria showed that previously believed universal evolutionary trends like reduced G+C content and conservation of genome synteny are not always present in highly reduced genomes. Finally, the simplified molecular machinery of some of these organisms with small genomes may be used to aid in the design of artificial minimal cells. Here we review recent genomic discoveries of the biology of prokaryotes endowed with small gene sets and discuss the evolutionary mechanisms that have been proposed to explain their peculiar nature.

Detecting loci under recent positive selection in dairy and beef cattle by combining different genome-wide scan methods.

Directory of Open Access Journals (Sweden)

Yuri Tani Utsunomiya

Full Text Available As the methodologies available for the detection of positive selection from genomic data vary in terms of assumptions and execution, weak correlations are expected among them. However, if there is any given signal that is consistently supported across different methodologies, it is strong evidence that the locus has been under past selection. In this paper, a straightforward frequentist approach based on the Stouffer Method to combine P-values across different tests for evidence of recent positive selection in common variations, as well as strategies for extracting biological information from the detected signals, were described and applied to high density single nucleotide polymorphism (SNP data generated from dairy and beef cattle (taurine and indicine. The ancestral Bovinae allele state of over 440,000 SNP is also reported. Using this combination of methods, highly significant (P<3.17×10(-7 population-specific sweeps pointing out to candidate genes and pathways that may be involved in beef and dairy production were identified. The most significant signal was found in the Cornichon homolog 3 gene (CNIH3 in Brown Swiss (P = 3.82×10(-12, and may be involved in the regulation of pre-ovulatory luteinizing hormone surge. Other putative pathways under selection are the glucolysis/gluconeogenesis, transcription machinery and chemokine/cytokine activity in Angus; calpain-calpastatin system and ribosome biogenesis in Brown Swiss; and gangliosides deposition in milk fat globules in Gyr. The composite method, combined with the strategies applied to retrieve functional information, may be a useful tool for surveying genome-wide selective sweeps and providing insights in to the source of selection.

Genomic selection in small dairy cattle populations

DEFF Research Database (Denmark)

Thomasen, Jørn Rind

on optimization of genomc selction for a small dairy cattle breed such as Danish Jersey. Implementing genetic superior breeding schemes thus requires more accurate genomc predictions. Besides international collaboration, genotyping of cows is an efficient way to obtain more accurate genomic predictions...

Long- and short-term selective forces on malaria parasite genomes

DEFF Research Database (Denmark)

Nygaard, Sanne; Braunstein, Alexander; Malsen, Gareth

2010-01-01

Plasmodium parasites, the causal agents of malaria, result in more than 1 million deaths annually. Plasmodium are unicellular eukaryotes with small ~23 Mb genomes encoding ~5200 protein-coding genes. The protein-coding genes comprise about half of these genomes. Although evolutionary processes ha...

GWA study data mining and independent replication identify cardiomyopathy-associated 5 (CMYA5) as a risk gene for schizophrenia

NARCIS (Netherlands)

Chen, X.; Lee, G.; Maher, B. S.; Fanous, A. H.; Chen, J.; Zhao, Z.; Guo, A.; van den Oord, E.; Sullivan, P. F.; Shi, J.; Levinson, D. F.; Gejman, P. V.; Sanders, A.; Duan, J.; Owen, M. J.; Craddock, N. J.; O'Donovan, M. C.; Blackman, J.; Lewis, D.; Kirov, G. K.; Qin, W.; Schwab, S.; Wildenauer, D.; Chowdari, K.; Nimgaonkar, V.; Straub, R. E.; Weinberger, D. R.; O'Neill, F. A.; Walsh, D.; Bronstein, M.; Darvasi, A.; Lencz, T.; Malhotra, A. K.; Rujescu, D.; Giegling, I.; Werge, T.; Hansen, T.; Ingason, A.; Nöethen, M. M.; Rietschel, M.; Cichon, S.; Djurovic, S.; Andreassen, O. A.; Cantor, R. M.; Ophoff, R.; Corvin, A.; Morris, D. W.; Gill, M.; Pato, C. N.; Pato, M. T.; Macedo, A.; Gurling, H. M. D.; McQuillin, A.; Pimm, J.; Hultman, C.; Lichtenstein, P.; Sklar, P.; Purcell, S. M.; Scolnick, E.; St Clair, D.; Blackwood, D. H. R.; Kendler, K. S.; Kahn, René S.; Linszen, Don H.; van Os, Jim; Wiersma, Durk; Bruggeman, Richard; Cahn, Wiepke; de Haan, Lieuwe; Krabbendam, Lydia; Myin-Germeys, Inez; O'Donovan, Michael C.; Kirov, George K.; Craddock, Nick J.; Holmans, Peter A.; Williams, Nigel M.; Georgieva, Lyudmila; Nikolov, Ivan; Norton, N.; Williams, H.; Toncheva, Draga; Milanova, Vihra; Owen, Michael J.; Hultman, Christina M.; Lichtenstein, Paul; Thelander, Emma F.; Sullivan, Patrick; Morris, Derek W.; O'Dushlaine, Colm T.; Kenny, Elaine; Quinn, Emma M.; Gill, Michael; Corvin, Aiden; McQuillin, Andrew; Choudhury, Khalid; Datta, Susmita; Pimm, Jonathan; Thirumalai, Srinivasa; Puri, Vinay; Krasucki, Robert; Lawrence, Jacob; Quested, Digby; Bass, Nicholas; Gurling, Hugh; Crombie, Caroline; Fraser, Gillian; Kuan, Soh Leh; Walker, Nicholas; St Clair, David; Blackwood, Douglas H. R.; Muir, Walter J.; McGhee, Kevin A.; Pickard, Ben; Malloy, Pat; Maclean, Alan W.; van Beck, Margaret; Wray, Naomi R.; Macgregor, Stuart; Visscher, Peter M.; Pato, Michele T.; Medeiros, Helena; Middleton, Frank; Carvalho, Celia; Morley, Christopher; Fanous, Ayman; Conti, David; Knowles, James A.; Ferreira, Carlos Paz; Macedo, Antonio; Azevedo, M. Helena; Pato, Carlos N.; Stone, Jennifer L.; Ruderfer, Douglas M.; Kirby, Andrew N.; Ferreira, Manuel A. R.; Daly, Mark J.; Purcell, Shaun M.; Sklar, Pamela; Chambert, Kimberly; Kuruvilla, Finny; Gabriel, Stacey B.; Ardlie, Kristin; Moran, Jennifer L.; Scolnick, Edward M.

2011-01-01

We conducted data-mining analyses using the Clinical Antipsychotic Trials of Intervention Effectiveness (CATIE) and molecular genetics of schizophrenia genome-wide association study supported by the genetic association information network (MGS-GAIN) schizophrenia data sets and performed

Functional conservation of nucleosome formation selectively biases presumably neutral molecular variation in yeast genomes.

Science.gov (United States)

Babbitt, Gregory A; Cotter, C R

2011-01-01

One prominent pattern of mutational frequency, long appreciated in comparative genomics, is the bias of purine/pyrimidine conserving substitutions (transitions) over purine/pyrimidine altering substitutions (transversions). Traditionally, this transitional bias has been thought to be driven by the underlying rates of DNA mutation and/or repair. However, recent sequencing studies of mutation accumulation lines in model organisms demonstrate that substitutions generally do not accumulate at rates that would indicate a transitional bias. These observations have called into question a very basic assumption of molecular evolution; that naturally occurring patterns of molecular variation in noncoding regions accurately reflect the underlying processes of randomly accumulating neutral mutation in nuclear genomes. Here, in Saccharomyces yeasts, we report a very strong inverse association (r = -0.951, P < 0.004) between the genome-wide frequency of substitutions and their average energetic effect on nucleosome formation, as predicted by a structurally based energy model of DNA deformation around the nucleosome core. We find that transitions occurring at sites positioned nearest the nucleosome surface, which are believed to function most importantly in nucleosome formation, alter the deformation energy of DNA to the nucleosome core by only a fraction of the energy changes typical of most transversions. When we examined the same substitutions set against random background sequences as well as an existing study reporting substitutions arising in mutation accumulation lines of Saccharomyces cerevisiae, we failed to find a similar relationship. These results support the idea that natural selection acting to functionally conserve chromatin organization may contribute significantly to genome-wide transitional bias, even in noncoding regions. Because nucleosome core structure is highly conserved across eukaryotes, our observations may also help to further explain locally elevated

Herbarium genomics

DEFF Research Database (Denmark)

Bakker, Freek T.; Lei, Di; Yu, Jiaying

2016-01-01

Herbarium genomics is proving promising as next-generation sequencing approaches are well suited to deal with the usually fragmented nature of archival DNA. We show that routine assembly of partial plastome sequences from herbarium specimens is feasible, from total DNA extracts and with specimens...... up to 146 years old. We use genome skimming and an automated assembly pipeline, Iterative Organelle Genome Assembly, that assembles paired-end reads into a series of candidate assemblies, the best one of which is selected based on likelihood estimation. We used 93 specimens from 12 different...... correlation between plastome coverage and nuclear genome size (C value) in our samples, but the range of C values included is limited. Finally, we conclude that routine plastome sequencing from herbarium specimens is feasible and cost-effective (compared with Sanger sequencing or plastome...

The value of cows in reference populations for genomic selection of new functional traits

DEFF Research Database (Denmark)

Buch, Line Hjortø; Kargo, Morten; Berg, Peer

2012-01-01

Today, almost all reference populations consist of progeny tested bulls. However, older progeny tested bulls do not have reliable estimated breeding values (EBV) for new traits. Thus, to be able to select for these new traits, it is necessary to build a reference population. We used a deterministic...... of the direct genomic values (DGV) for a new functional trait, regardless of its heritability. For small-scale recording, we compared two scenarios where the reference population consisted of the 2000 cows with phenotypic records or the 30 sires of these cows in the first year with measurements of the new...... to achieve accuracies of the DGV that enable selection for new functional traits recorded on a large scale within 3 years from commencement of recording; and (iv) a higher heritability benefits a reference population of cows more than a reference population of bulls....

Using Partial Genomic Fosmid Libraries for Sequencing CompleteOrganellar Genomes

Energy Technology Data Exchange (ETDEWEB)

McNeal, Joel R.; Leebens-Mack, James H.; Arumuganathan, K.; Kuehl, Jennifer V.; Boore, Jeffrey L.; dePamphilis, Claude W.

2005-08-26

Organellar genome sequences provide numerous phylogenetic markers and yield insight into organellar function and molecular evolution. These genomes are much smaller in size than their nuclear counterparts; thus, their complete sequencing is much less expensive than total nuclear genome sequencing, making broader phylogenetic sampling feasible. However, for some organisms it is challenging to isolate plastid DNA for sequencing using standard methods. To overcome these difficulties, we constructed partial genomic libraries from total DNA preparations of two heterotrophic and two autotrophic angiosperm species using fosmid vectors. We then used macroarray screening to isolate clones containing large fragments of plastid DNA. A minimum tiling path of clones comprising the entire genome sequence of each plastid was selected, and these clones were shotgun-sequenced and assembled into complete genomes. Although this method worked well for both heterotrophic and autotrophic plants, nuclear genome size had a dramatic effect on the proportion of screened clones containing plastid DNA and, consequently, the overall number of clones that must be screened to ensure full plastid genome coverage. This technique makes it possible to determine complete plastid genome sequences for organisms that defy other available organellar genome sequencing methods, especially those for which limited amounts of tissue are available.

The impact of genome editing on the introduction of monogenic traits in livestock.

Science.gov (United States)

Bastiaansen, John W M; Bovenhuis, Henk; Groenen, Martien A M; Megens, Hendrik-Jan; Mulder, Han A

2018-04-16

Genome editing technologies provide new tools for genetic improvement and have the potential to become the next game changer in animal and plant breeding. The aim of this study was to investigate how genome editing in combination with genomic selection can accelerate the introduction of a monogenic trait in a livestock population as compared to genomic selection alone. A breeding population was simulated under genomic selection for a polygenic trait. After reaching Bulmer equilibrium, the selection objective was to increase the allele frequency of a monogenic trait, with or without genome editing, in addition to improving the polygenic trait. Scenarios were compared for time to fixation of the desired allele, selection response for the polygenic trait, and level of inbreeding. The costs, in terms of number of editing procedures, were compared to the benefits of having more animals with the desired phenotype of the monogenic trait. Effects of reduced editing efficiency were investigated. In a population of 20,000 selection candidates per generation, the total number of edited zygotes needed to reach fixation of the desired allele was 22,118, 7072, or 3912 with, no, moderate, or high selection emphasis on the monogenic trait, respectively. Genome editing resulted in up to four-fold faster fixation of the desired allele when efficiency was 100%, while the loss in long-term selection response for the polygenic trait was up to seven-fold less compared to genomic selection alone. With moderate selection emphasis on the monogenic trait, introduction of genome editing led to a four-fold reduction in the total number of animals showing the undesired phenotype before fixation. However, with a currently realistic editing efficiency of 4%, the number of required editing procedures increased by 72% and loss in selection response increased eight-fold compared to 100% efficiency. With low efficiency, loss in selection response was 29% more compared to genomic selection alone

Applied Genetics and Genomics in Alfalfa Breeding

Directory of Open Access Journals (Sweden)

E. Charles Brummer

2012-03-01

Full Text Available Alfalfa (Medicago sativa L., a perennial and outcrossing species, is a widely planted forage legume for hay, pasture and silage throughout the world. Currently, alfalfa breeding relies on recurrent phenotypic selection, but alternatives incorporating molecular marker assisted breeding could enhance genetic gain per unit time and per unit cost, and accelerate alfalfa improvement. Many major quantitative trait loci (QTL related to agronomic traits have been identified by family-based QTL mapping, but in relatively large genomic regions. Candidate genes elucidated from model species have helped to identify some potential causal loci in alfalfa mapping and breeding population for specific traits. Recently, high throughput sequencing technologies, coupled with advanced bioinformatics tools, have been used to identify large numbers of single nucleotide polymorphisms (SNP in alfalfa, which are being developed into markers. These markers will facilitate fine mapping of quantitative traits and genome wide association mapping of agronomic traits and further advanced breeding strategies for alfalfa, such as marker-assisted selection and genomic selection. Based on ideas from the literature, we suggest several ways to improve selection in alfalfa including (1 diversity selection and paternity testing, (2 introgression of QTL and (3 genomic selection.

Comparing Patterns of Natural Selection across Species Using Selective Signatures

Energy Technology Data Exchange (ETDEWEB)

Shapiro, Jesse; Alm, Eric J.

2007-12-01

Comparing gene expression profiles over many different conditions has led to insights that were not obvious from single experiments. In the same way, comparing patterns of natural selection across a set of ecologically distinct species may extend what can be learned from individual genome-wide surveys. Toward this end, we show how variation in protein evolutionary rates, after correcting for genome-wide effects such as mutation rate and demographic factors, can be used to estimate the level and types of natural selection acting on genes across different species. We identify unusually rapidly and slowly evolving genes, relative to empirically derived genome-wide and gene family-specific background rates for 744 core protein families in 30 c-proteobacterial species. We describe the pattern of fast or slow evolution across species as the"selective signature" of a gene. Selective signatures represent aprofile of selection across species that is predictive of gene function: pairs of genes with correlated selective signatures are more likely to share the same cellular function, and genes in the same pathway can evolve in concert. For example,glycolysis and phenylalanine metabolism genes evolve rapidly in Idiomarina loihiensis, mirroring an ecological shift in carbon source from sugars to amino acids. In a broader context, our results suggest that the genomic landscape is organized into functional modules even at the level of natural selection, and thus it may be easier than expected to understand the complex evolutionary pressures on a cell.

Comparing Patterns of Natural Selection Across Species Using Selective Signatures

Energy Technology Data Exchange (ETDEWEB)

Alm, Eric J.; Shapiro, B. Jesse; Alm, Eric J.

2007-12-18

Comparing gene expression profiles over many different conditions has led to insights that were not obvious from single experiments. In the same way, comparing patterns of natural selection across a set of ecologically distinct species may extend what can be learned from individual genome-wide surveys. Toward this end, we show how variation in protein evolutionary rates, after correcting for genome-wide effects such as mutation rate and demographic factors, can be used to estimate the level and types of natural selection acting on genes across different species. We identify unusually rapidly and slowly evolving genes, relative to empirically derived genome-wide and gene family-specific background rates for 744 core protein families in 30 gamma-proteobacterial species. We describe the pattern of fast or slow evolution across species as the 'selective signature' of a gene. Selective signatures represent a profile of selection across species that is predictive of gene function: pairs of genes with correlated selective signatures are more likely to share the same cellular function, and genes in the same pathway can evolve in concert. For example, glycolysis and phenylalanine metabolism genes evolve rapidly in Idiomarina loihiensis, mirroring an ecological shift in carbon source from sugars to amino acids. In a broader context, our results suggest that the genomic landscape is organized into functional modules even at the level of natural selection, and thus it may be easier than expected to understand the complex evolutionary pressures on a cell.

The Global Invertebrate Genomics Alliance (GIGA): Developing Community Resources to Study Diverse Invertebrate Genomes

KAUST Repository

Bracken-Grissom, Heather

2013-12-12

Over 95% of all metazoan (animal) species comprise the invertebrates, but very few genomes from these organisms have been sequenced. We have, therefore, formed a Global Invertebrate Genomics Alliance (GIGA). Our intent is to build a collaborative network of diverse scientists to tackle major challenges (e.g., species selection, sample collection and storage, sequence assembly, annotation, analytical tools) associated with genome/transcriptome sequencing across a large taxonomic spectrum. We aim to promote standards that will facilitate comparative approaches to invertebrate genomics and collaborations across the international scientific community. Candidate study taxa include species from Porifera, Ctenophora, Cnidaria, Placozoa, Mollusca, Arthropoda, Echinodermata, Annelida, Bryozoa, and Platyhelminthes, among others. GIGA will target 7000 noninsect/nonnematode species, with an emphasis on marine taxa because of the unrivaled phyletic diversity in the oceans. Priorities for selecting invertebrates for sequencing will include, but are not restricted to, their phylogenetic placement; relevance to organismal, ecological, and conservation research; and their importance to fisheries and human health. We highlight benefits of sequencing both whole genomes (DNA) and transcriptomes and also suggest policies for genomic-level data access and sharing based on transparency and inclusiveness. The GIGA Web site () has been launched to facilitate this collaborative venture.

Applied Genomics of Foodborne Pathogens

DEFF Research Database (Denmark)

and customized source of information designed for and accessible to microbiologists interested in applying cutting-edge genomics in food safety and public health research. This book fills this void with a well-selected collection of topics, case studies, and bioinformatics tools contributed by experts......This book provides a timely and thorough snapshot into the emerging and fast evolving area of applied genomics of foodborne pathogens. Driven by the drastic advance of whole genome shot gun sequencing (WGS) technologies, genomics applications are becoming increasingly valuable and even essential...... at the forefront of foodborne pathogen genomics research....

Relaxation of Selective Constraints Causes Independent Selenoprotein Extinction in Insect Genomes

OpenAIRE

Chapple, Charles E.; Guigó, Roderic

2008-01-01

BACKGROUND: Selenoproteins are a diverse family of proteins notable for the presence of the 21st amino acid, selenocysteine. Until very recently, all metazoan genomes investigated encoded selenoproteins, and these proteins had therefore been believed to be essential for animal life. Challenging this assumption, recent comparative analyses of insect genomes have revealed that some insect genomes appear to have lost selenoprotein genes. METHODOLOGY/PRINCIPAL FINDINGS: In this paper we investiga...

Are there laws of genome evolution?

Directory of Open Access Journals (Sweden)

Eugene V Koonin

2011-08-01

Full Text Available Research in quantitative evolutionary genomics and systems biology led to the discovery of several universal regularities connecting genomic and molecular phenomic variables. These universals include the log-normal distribution of the evolutionary rates of orthologous genes; the power law-like distributions of paralogous family size and node degree in various biological networks; the negative correlation between a gene's sequence evolution rate and expression level; and differential scaling of functional classes of genes with genome size. The universals of genome evolution can be accounted for by simple mathematical models similar to those used in statistical physics, such as the birth-death-innovation model. These models do not explicitly incorporate selection; therefore, the observed universal regularities do not appear to be shaped by selection but rather are emergent properties of gene ensembles. Although a complete physical theory of evolutionary biology is inconceivable, the universals of genome evolution might qualify as "laws of evolutionary genomics" in the same sense "law" is understood in modern physics.

Human genome I

International Nuclear Information System (INIS)

Anon.

1989-01-01

An international conference, Human Genome I, was held Oct. 2-4, 1989 in San Diego, Calif. Selected speakers discussed: Current Status of the Genome Project; Technique Innovations; Interesting regions; Applications; and Organization - Different Views of Current and Future Science and Procedures. Posters, consisting of 119 presentations, were displayed during the sessions. 119 were indexed for inclusion to the Energy Data Base

The accuracy of prediction of genomic selection in elite hybrid rye populations surpasses the accuracy of marker-assisted selection and is equally augmented by multiple field evaluation locations and test years.

Science.gov (United States)

Wang, Yu; Mette, Michael Florian; Miedaner, Thomas; Gottwald, Marlen; Wilde, Peer; Reif, Jochen C; Zhao, Yusheng

2014-07-04

Marker-assisted selection (MAS) and genomic selection (GS) based on genome-wide marker data provide powerful tools to predict the genotypic value of selection material in plant breeding. However, case-to-case optimization of these approaches is required to achieve maximum accuracy of prediction with reasonable input. Based on extended field evaluation data for grain yield, plant height, starch content and total pentosan content of elite hybrid rye derived from testcrosses involving two bi-parental populations that were genotyped with 1048 molecular markers, we compared the accuracy of prediction of MAS and GS in a cross-validation approach. MAS delivered generally lower and in addition potentially over-estimated accuracies of prediction than GS by ridge regression best linear unbiased prediction (RR-BLUP). The grade of relatedness of the plant material included in the estimation and test sets clearly affected the accuracy of prediction of GS. Within each of the two bi-parental populations, accuracies differed depending on the relatedness of the respective parental lines. Across populations, accuracy increased when both populations contributed to estimation and test set. In contrast, accuracy of prediction based on an estimation set from one population to a test set from the other population was low despite that the two bi-parental segregating populations under scrutiny shared one parental line. Limiting the number of locations or years in field testing reduced the accuracy of prediction of GS equally, supporting the view that to establish robust GS calibration models a sufficient number of test locations is of similar importance as extended testing for more than one year. In hybrid rye, genomic selection is superior to marker-assisted selection. However, it achieves high accuracies of prediction only for selection candidates closely related to the plant material evaluated in field trials, resulting in a rather pessimistic prognosis for distantly related material

Genomic breeding value prediction:methods and procedures

NARCIS (Netherlands)

Calus, M.P.L.

2010-01-01

Animal breeding faces one of the most significant changes of the past decades – the implementation of genomic selection. Genomic selection uses dense marker maps to predict the breeding value of animals with reported accuracies that are up to 0.31 higher than those of pedigree indexes, without the

Experimental Induction of Genome Chaos.

Science.gov (United States)

Ye, Christine J; Liu, Guo; Heng, Henry H

2018-01-01

Genome chaos, or karyotype chaos, represents a powerful survival strategy for somatic cells under high levels of stress/selection. Since the genome context, not the gene content, encodes the genomic blueprint of the cell, stress-induced rapid and massive reorganization of genome topology functions as a very important mechanism for genome (karyotype) evolution. In recent years, the phenomenon of genome chaos has been confirmed by various sequencing efforts, and many different terms have been coined to describe different subtypes of the chaotic genome including "chromothripsis," "chromoplexy," and "structural mutations." To advance this exciting field, we need an effective experimental system to induce and characterize the karyotype reorganization process. In this chapter, an experimental protocol to induce chaotic genomes is described, following a brief discussion of the mechanism and implication of genome chaos in cancer evolution.

Wrapper-based selection of genetic features in genome-wide association studies through fast matrix operations

Science.gov (United States)

2012-01-01

Background Through the wealth of information contained within them, genome-wide association studies (GWAS) have the potential to provide researchers with a systematic means of associating genetic variants with a wide variety of disease phenotypes. Due to the limitations of approaches that have analyzed single variants one at a time, it has been proposed that the genetic basis of these disorders could be determined through detailed analysis of the genetic variants themselves and in conjunction with one another. The construction of models that account for these subsets of variants requires methodologies that generate predictions based on the total risk of a particular group of polymorphisms. However, due to the excessive number of variants, constructing these types of models has so far been computationally infeasible. Results We have implemented an algorithm, known as greedy RLS, that we use to perform the first known wrapper-based feature selection on the genome-wide level. The running time of greedy RLS grows linearly in the number of training examples, the number of features in the original data set, and the number of selected features. This speed is achieved through computational short-cuts based on matrix calculus. Since the memory consumption in present-day computers can form an even tighter bottleneck than running time, we also developed a space efficient variation of greedy RLS which trades running time for memory. These approaches are then compared to traditional wrapper-based feature selection implementations based on support vector machines (SVM) to reveal the relative speed-up and to assess the feasibility of the new algorithm. As a proof of concept, we apply greedy RLS to the Hypertension – UK National Blood Service WTCCC dataset and select the most predictive variants using 3-fold external cross-validation in less than 26 minutes on a high-end desktop. On this dataset, we also show that greedy RLS has a better classification performance on independent

Genomic characterization of Burkholderia pseudomallei isolates selected for medical countermeasures testing: comparative genomics associated with differential virulence.

Directory of Open Access Journals (Sweden)

Jason W Sahl

Full Text Available Burkholderia pseudomallei is the causative agent of melioidosis and a potential bioterrorism agent. In the development of medical countermeasures against B. pseudomallei infection, the US Food and Drug Administration (FDA animal Rule recommends using well-characterized strains in animal challenge studies. In this study, whole genome sequence data were generated for 6 B. pseudomallei isolates previously identified as candidates for animal challenge studies; an additional 5 isolates were sequenced that were associated with human inhalational melioidosis. A core genome single nucleotide polymorphism (SNP phylogeny inferred from a concatenated SNP alignment from the 11 isolates sequenced in this study and a diverse global collection of isolates demonstrated the diversity of the proposed Animal Rule isolates. To understand the genomic composition of each isolate, a large-scale blast score ratio (LS-BSR analysis was performed on the entire pan-genome; this demonstrated the variable composition of genes across the panel and also helped to identify genes unique to individual isolates. In addition, a set of ~550 genes associated with pathogenesis in B. pseudomallei were screened against the 11 sequenced genomes with LS-BSR. Differential gene distribution for 54 virulence-associated genes was observed between genomes and three of these genes were correlated with differential virulence observed in animal challenge studies using BALB/c mice. Differentially conserved genes and SNPs associated with disease severity were identified and could be the basis for future studies investigating the pathogenesis of B. pseudomallei. Overall, the genetic characterization of the 11 proposed Animal Rule isolates provides context for future studies involving B. pseudomallei pathogenesis, differential virulence, and efficacy to therapeutics.

Which individuals to choose to update the reference population? Minimizing the loss of genetic diversity in animal genomic selection programs

NARCIS (Netherlands)

Eynard, Sonia E.; Croiseau, Pascal; Laloë, Denis; Fritz, Sebastien; Calus, Mario P.L.; Restoux, Gwendal

2018-01-01

Genomic selection (GS) is commonly used in livestock and increasingly in plant breeding. Relying on phenotypes and genotypes of a reference population, GS allows performance prediction for young individuals having only genotypes. This is expected to achieve fast high genetic gain but with a

Public attitudes to the promotion of genomic crop studies in Japan: correlations between genomic literacy, trust, and favourable attitude.

Science.gov (United States)

Ishiyama, Izumi; Tanzawa, Tetsuro; Watanabe, Maiko; Maeda, Tadahiko; Muto, Kaori; Tamakoshi, Akiko; Nagai, Akiko; Yamagata, Zentaro

2012-05-01

This study aimed to assess public attitudes in Japan to the promotion of genomic selection in crop studies and to examine associated factors. We analysed data from a nationwide opinion survey. A total of 4,000 people were selected from the Japanese general population by a stratified two-phase sampling method, and 2,171 people participated by post; this survey asked about the pros and cons of crop-related genomic studies promotion, examined people's scientific literacy in genomics, and investigated factors thought to be related to genomic literacy and attitude. The relationships were examined using logistic regression models stratified by gender. Survey results showed that 50.0% of respondents approved of the promotion of crop-related genomic studies, while 6.7% disapproved. No correlation was found between literacy and attitude towards promotion. Trust in experts, belief in science, an interest in genomic studies and willingness to purchase new products correlated with a positive attitude towards crop-related genomic studies.

Genomic and chromatin signals underlying transcription start-site selection

DEFF Research Database (Denmark)

Valen, Eivind; Sandelin, Albin Gustav

2011-01-01

A central question in cellular biology is how the cell regulates transcription and discerns when and where to initiate it. Locating transcription start sites (TSSs), the signals that specify them, and ultimately elucidating the mechanisms of regulated initiation has therefore been a recurrent theme....... In recent years substantial progress has been made towards this goal, spurred by the possibility of applying genome-wide, sequencing-based analysis. We now have a large collection of high-resolution datasets identifying locations of TSSs, protein-DNA interactions, and chromatin features over whole genomes...

Single-Molecule FISH Reveals Non-selective Packaging of Rift Valley Fever Virus Genome Segments

NARCIS (Netherlands)

Wichgers Schreur, Paul J.; Kortekaas, Jeroen

2016-01-01

The bunyavirus genome comprises a small (S), medium (M), and large (L) RNA segment of negative polarity. Although genome segmentation confers evolutionary advantages by enabling genome reassortment events with related viruses, genome segmentation also complicates genome replication and packaging.

Accounting for genotype–by-environment interactions and non-additive genetic variation in genomic selection for water-soluble carbohydrate concentration in wheat

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Abiotic stress tolerance traits are often complex and recalcitrant targets for conventional breeding improvement in many crop species. This study evaluated the potential of genomic selection to predict water-soluble carbohydrate concentration (WSCC), an important drought tolerance trait, in wheat un...

A MITE-based genotyping method to reveal hundreds of DNA polymorphisms in an animal genome after a few generations of artificial selection

Directory of Open Access Journals (Sweden)

Tetreau Guillaume

2008-10-01

Full Text Available Abstract Background For most organisms, developing hundreds of genetic markers spanning the whole genome still requires excessive if not unrealistic efforts. In this context, there is an obvious need for methodologies allowing the low-cost, fast and high-throughput genotyping of virtually any species, such as the Diversity Arrays Technology (DArT. One of the crucial steps of the DArT technique is the genome complexity reduction, which allows obtaining a genomic representation characteristic of the studied DNA sample and necessary for subsequent genotyping. In this article, using the mosquito Aedes aegypti as a study model, we describe a new genome complexity reduction method taking advantage of the abundance of miniature inverted repeat transposable elements (MITEs in the genome of this species. Results Ae. aegypti genomic representations were produced following a two-step procedure: (1 restriction digestion of the genomic DNA and simultaneous ligation of a specific adaptor to compatible ends, and (2 amplification of restriction fragments containing a particular MITE element called Pony using two primers, one annealing to the adaptor sequence and one annealing to a conserved sequence motif of the Pony element. Using this protocol, we constructed a library comprising more than 6,000 DArT clones, of which at least 5.70% were highly reliable polymorphic markers for two closely related mosquito strains separated by only a few generations of artificial selection. Within this dataset, linkage disequilibrium was low, and marker redundancy was evaluated at 2.86% only. Most of the detected genetic variability was observed between the two studied mosquito strains, but individuals of the same strain could still be clearly distinguished. Conclusion The new complexity reduction method was particularly efficient to reveal genetic polymorphisms in Ae. egypti. Overall, our results testify of the flexibility of the DArT genotyping technique and open new

Comparative genomics of Mycoplasma: analysis of conserved essential genes and diversity of the pan-genome.

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Wei Liu

Full Text Available Mycoplasma, the smallest self-replicating organism with a minimal metabolism and little genomic redundancy, is expected to be a close approximation to the minimal set of genes needed to sustain bacterial life. This study employs comparative evolutionary analysis of twenty Mycoplasma genomes to gain an improved understanding of essential genes. By analyzing the core genome of mycoplasmas, we finally revealed the conserved essential genes set for mycoplasma survival. Further analysis showed that the core genome set has many characteristics in common with experimentally identified essential genes. Several key genes, which are related to DNA replication and repair and can be disrupted in transposon mutagenesis studies, may be critical for bacteria survival especially over long period natural selection. Phylogenomic reconstructions based on 3,355 homologous groups allowed robust estimation of phylogenetic relatedness among mycoplasma strains. To obtain deeper insight into the relative roles of molecular evolution in pathogen adaptation to their hosts, we also analyzed the positive selection pressures on particular sites and lineages. There appears to be an approximate correlation between the divergence of species and the level of positive selection detected in corresponding lineages.

Genomic architecture of habitat-related divergence and signature of directional selection in the body shapes of Gnathopogon fishes.

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Kakioka, Ryo; Kokita, Tomoyuki; Kumada, Hiroki; Watanabe, Katsutoshi; Okuda, Noboru

2015-08-01

Evolution of ecomorphologically relevant traits such as body shapes is important to colonize and persist in a novel environment. Habitat-related adaptive divergence of these traits is therefore common among animals. We studied the genomic architecture of habitat-related divergence in the body shape of Gnathopogon fishes, a novel example of lake-stream ecomorphological divergence, and tested for the action of directional selection on body shape differentiation. Compared to stream-dwelling Gnathopogon elongatus, the sister species Gnathopogon caerulescens, exclusively inhabiting a large ancient lake, had an elongated body, increased proportion of the caudal region and small head, which would be advantageous in the limnetic environment. Using an F2 interspecific cross between the two Gnathopogon species (195 individuals), quantitative trait locus (QTL) analysis with geometric morphometric quantification of body shape and restriction-site associated DNA sequencing-derived markers (1622 loci) identified 26 significant QTLs associated with the interspecific differences of body shape-related traits. These QTLs had small to moderate effects, supporting polygenic inheritance of the body shape-related traits. Each QTL was mostly located on different genomic regions, while colocalized QTLs were detected for some ecomorphologically relevant traits that are proxy of body and caudal peduncle depths, suggesting different degree of modularity among traits. The directions of the body shape QTLs were mostly consistent with the interspecific difference, and QTL sign test suggested a genetic signature of directional selection in the body shape divergence. Thus, we successfully elucidated the genomic architecture underlying the adaptive changes of the quantitative and complex morphological trait in a novel system. © 2015 John Wiley & Sons Ltd.

Genome-enabled prediction models for yield related traits in chickpea

Science.gov (United States)

Genomic selection (GS) unlike marker-assisted backcrossing (MABC) predicts breeding values of lines using genome-wide marker profiling and allows selection of lines prior to field-phenotyping, thereby shortening the breeding cycle. A collection of 320 elite breeding lines was selected and phenotyped...

Genomic analysis of codon usage shows influence of mutation pressure, natural selection, and host features on Marburg virus evolution.

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Nasrullah, Izza; Butt, Azeem M; Tahir, Shifa; Idrees, Muhammad; Tong, Yigang

2015-08-26

The Marburg virus (MARV) has a negative-sense single-stranded RNA genome, belongs to the family Filoviridae, and is responsible for several outbreaks of highly fatal hemorrhagic fever. Codon usage patterns of viruses reflect a series of evolutionary changes that enable viruses to shape their survival rates and fitness toward the external environment and, most importantly, their hosts. To understand the evolution of MARV at the codon level, we report a comprehensive analysis of synonymous codon usage patterns in MARV genomes. Multiple codon analysis approaches and statistical methods were performed to determine overall codon usage patterns, biases in codon usage, and influence of various factors, including mutation pressure, natural selection, and its two hosts, Homo sapiens and Rousettus aegyptiacus. Nucleotide composition and relative synonymous codon usage (RSCU) analysis revealed that MARV shows mutation bias and prefers U- and A-ended codons to code amino acids. Effective number of codons analysis indicated that overall codon usage among MARV genomes is slightly biased. The Parity Rule 2 plot analysis showed that GC and AU nucleotides were not used proportionally which accounts for the presence of natural selection. Codon usage patterns of MARV were also found to be influenced by its hosts. This indicates that MARV have evolved codon usage patterns that are specific to both of its hosts. Moreover, selection pressure from R. aegyptiacus on the MARV RSCU patterns was found to be dominant compared with that from H. sapiens. Overall, mutation pressure was found to be the most important and dominant force that shapes codon usage patterns in MARV. To our knowledge, this is the first detailed codon usage analysis of MARV and extends our understanding of the mechanisms that contribute to codon usage and evolution of MARV.

Genomic heritabilities and genomic estimated breeding values for methane traits in Angus cattle.

Science.gov (United States)

Hayes, B J; Donoghue, K A; Reich, C M; Mason, B A; Bird-Gardiner, T; Herd, R M; Arthur, P F

2016-03-01

Enteric methane emissions from beef cattle are a significant component of total greenhouse gas emissions from agriculture. The variation between beef cattle in methane emissions is partly genetic, whether measured as methane production, methane yield (methane production/DMI), or residual methane production (observed methane production - expected methane production), with heritabilities ranging from 0.19 to 0.29. This suggests methane emissions could be reduced by selection. Given the high cost of measuring methane production from individual beef cattle, genomic selection is the most feasible approach to achieve this reduction in emissions. We derived genomic EBV (GEBV) for methane traits from a reference set of 747 Angus animals phenotyped for methane traits and genotyped for 630,000 SNP. The accuracy of GEBV was tested in a validation set of 273 Angus animals phenotyped for the same traits. Accuracies of GEBV ranged from 0.29 ± 0.06 for methane yield and 0.35 ± 0.06 for residual methane production. Selection on GEBV using the genomic prediction equations derived here could reduce emissions for Angus cattle by roughly 5% over 10 yr.

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.

GAPIT: genome association and prediction integrated tool.

Science.gov (United States)

Lipka, Alexander E; Tian, Feng; Wang, Qishan; Peiffer, Jason; Li, Meng; Bradbury, Peter J; Gore, Michael A; Buckler, Edward S; Zhang, Zhiwu

2012-09-15

Software programs that conduct genome-wide association studies and genomic prediction and selection need to use methodologies that maximize statistical power, provide high prediction accuracy and run in a computationally efficient manner. We developed an R package called Genome Association and Prediction Integrated Tool (GAPIT) that implements advanced statistical methods including the compressed mixed linear model (CMLM) and CMLM-based genomic prediction and selection. The GAPIT package can handle large datasets in excess of 10 000 individuals and 1 million single-nucleotide polymorphisms with minimal computational time, while providing user-friendly access and concise tables and graphs to interpret results. http://www.maizegenetics.net/GAPIT. zhiwu.zhang@cornell.edu Supplementary data are available at Bioinformatics online.

Specific and selective target detection of supra-genome 21 Mers Salmonella via silicon nanowires biosensor

Science.gov (United States)

Mustafa, Mohammad Razif Bin; Dhahi, Th S.; Ehfaed, Nuri. A. K. H.; Adam, Tijjani; Hashim, U.; Azizah, N.; Mohammed, Mohammed; Noriman, N. Z.

2017-09-01

The nano structure based on silicon can be surface modified to be used as label-free biosensors that allow real-time measurements. The silicon nanowire surface was functionalized using 3-aminopropyltrimethoxysilane (APTES), which functions as a facilitator to immobilize biomolecules on the silicon nanowire surface. The process is simple, economical; this will pave the way for point-of-care applications. However, the surface modification and subsequent detection mechanism still not clear. Thus, study proposed step by step process of silicon nano surface modification and its possible in specific and selective target detection of Supra-genome 21 Mers Salmonella. The device captured the molecule with precisely; the approach took the advantages of strong binding chemistry created between APTES and biomolecule. The results indicated how modifications of the nanowires provide sensing capability with strong surface chemistries that can lead to specific and selective target detection.

Quantitation of Murine Stroma and Selective Purification of the Human Tumor Component of Patient-Derived Xenografts for Genomic Analysis.

Directory of Open Access Journals (Sweden)

Valentina E Schneeberger

Full Text Available Patient-derived xenograft (PDX mouse models are increasingly used for preclinical therapeutic testing of human cancer. A limitation in molecular and genetic characterization of PDX tumors is the presence of integral murine stroma. This is particularly problematic for genomic sequencing of PDX models. Rapid and dependable approaches for quantitating stromal content and purifying the malignant human component of these tumors are needed. We used a recently developed technique exploiting species-specific polymerase chain reaction (PCR amplicon length (ssPAL differences to define the fractional composition of murine and human DNA, which was proportional to the fractional composition of cells in a series of lung cancer PDX lines. We compared four methods of human cancer cell isolation: fluorescence-activated cell sorting (FACS, an immunomagnetic mouse cell depletion (MCD approach, and two distinct EpCAM-based immunomagnetic positive selection methods. We further analyzed DNA extracted from the resulting enriched human cancer cells by targeted sequencing using a clinically validated multi-gene panel. Stromal content varied widely among tumors of similar histology, but appeared stable over multiple serial tumor passages of an individual model. FACS and MCD were superior to either positive selection approach, especially in cases of high stromal content, and consistently allowed high quality human-specific genomic profiling. ssPAL is a dependable approach to quantitation of murine stromal content, and MCD is a simple, efficient, and high yield approach to human cancer cell isolation for genomic analysis of PDX tumors.

Meier-Gorlin syndrome Clinical genetics and genomics

OpenAIRE

Munnik, Sonja; Hoefsloot, Lies; Roukema, Jolt; Schoots, Jeroen; Knoers, Nine; Brunner, H.G.; Jackson, Andrew; Bongers, Ernie

2015-01-01

textabstractMeier-Gorlin syndrome (MGS) is a rare autosomal recessive primordial dwarfism disorder, characterized by microtia, patellar applasia/hypoplasia, and a proportionate short stature. Associated clinical features encompass feeding problems, congenital pulmonary emphysema, mammary hypoplasia in females and urogenital anomalies, such as cryptorchidism and hypoplastic labia minora and majora. Typical facial characteristics during childhood comprise a small mouth with full lips and micro-...

Genetic diversity, molecular phylogeny and selection evidence of the silkworm mitochondria implicated by complete resequencing of 41 genomes

Directory of Open Access Journals (Sweden)

Tellier Laurent C

2010-03-01

Full Text Available Abstract Background Mitochondria are a valuable resource for studying the evolutionary process and deducing phylogeny. A few mitochondria genomes have been sequenced, but a comprehensive picture of the domestication event for silkworm mitochondria remains to be established. In this study, we integrate the extant data, and perform a whole genome resequencing of Japanese wild silkworm to obtain breakthrough results in silkworm mitochondrial (mt population, and finally use these to deduce a more comprehensive phylogeny of the Bombycidae. Results We identified 347 single nucleotide polymorphisms (SNPs in the mt genome, but found no past recombination event to have occurred in the silkworm progenitor. A phylogeny inferred from these whole genome SNPs resulted in a well-classified tree, confirming that the domesticated silkworm, Bombyx mori, most recently diverged from the Chinese wild silkworm, rather than from the Japanese wild silkworm. We showed that the population sizes of the domesticated and Chinese wild silkworms both experience neither expansion nor contraction. We also discovered that one mt gene, named cytochrome b, shows a strong signal of positive selection in the domesticated clade. This gene is related to energy metabolism, and may have played an important role during silkworm domestication. Conclusions We present a comparative analysis on 41 mt genomes of B. mori and B. mandarina from China and Japan. With these, we obtain a much clearer picture of the evolution history of the silkworm. The data and analyses presented here aid our understanding of the silkworm in general, and provide a crucial insight into silkworm phylogeny.

Discordance in selected designee for return of genomic findings in the event of participant death and estate executor.

Science.gov (United States)

Goodman, Jessie L; Amendola, Laura M; Horike-Pyne, Martha; Trinidad, Susan B; Fullerton, Stephanie M; Burke, Wylie; Jarvik, Gail P

2017-03-01

Legal and ethical questions arise regarding disseminating genetic research results to family members in the event of a research participant's death; failure to return or return to legal next of kin or estate executor may not reflect participant desires. We sought to determine participant preferences for whether and to whom they would like their data released in the case of their death prior to receiving genomic results, focusing on whether the person selected was also their estate executor. The University of Washington NEXT Medicine Study of the Clinical Sequencing Exploratory Research program previously reported participant preferences regarding designating an individual to receive genomic results in the event of death, including whether they want results shared, and if so, with what person. Participants were also asked whether this designee is executor of their will or estate. To date, 61 individuals were asked about the concordance of their study designee and legal representative: 42 (69%) reported having a will or estate plan and of these, 14 (33%) chose someone other than their executor to receive their results. For the 14 who chose someone other than their estate executor to receive genetic results, 12 (86%) chose a family member, typically a biological relative, as their designee. Those with a different genomic designee than their executor were less likely to be partnered ( P  = 0.0024). For those partnered participants without an estate plan, spouses were not always chosen for return of genomic results. For one-third of our participants, the individual deemed most appropriate by the participant to receive their genomic results was not the executor. In the absence of an explicit designation, HIPAA may prohibit access to genomic results to persons other than the executor; hence asking for designation at the time of study enrollment (or initiation of clinical testing) is important.

Population genomics of the inbred Scandinavian wolf.

Science.gov (United States)

Hagenblad, Jenny; Olsson, Maria; Parker, Heidi G; Ostrander, Elaine A; Ellegren, Hans

2009-04-01

The Scandinavian wolf population represents one of the genetically most well-characterized examples of a severely bottlenecked natural population (with only two founders), and of how the addition of new genetic material (one immigrant) can at least temporarily provide a 'genetic rescue'. However, inbreeding depression has been observed in this population and in the absence of additional immigrants, its long-term viability is questioned. To study the effects of inbreeding and selection on genomic diversity, we performed a genomic scan with approximately 250 microsatellite markers distributed across all autosomes and the X chromosome. We found linkage disequilibrium (LD) that extended up to distances of 50 Mb, exceeding that of most outbreeding species studied thus far. LD was particularly pronounced on the X chromosome. Overall levels of observed genomic heterozygosity did not deviate significantly from simulations based on known population history, giving no support for a general selection for heterozygotes. However, we found evidence supporting balancing selection at a number of loci and also evidence suggesting directional selection at other loci. For markers on chromosome 23, the signal of selection was particularly strong, indicating that purifying selection against deleterious alleles may have occurred even in this very small population. These data suggest that population genomics allows the exploration of the effects of neutral and non-neutral evolution on a finer scale than what has previously been possible.

The Arabidopsis lyrata genome sequence and the basis of rapid genome size change

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