Thomasen, Jørn Rind; Guldbrandtsen, Bernt; Su, Guosheng
In order to optimize the use of genomic selection in breeding plans, it is essential to have reliable estimates of the genomic breeding values. This study investigated reliabilities of direct genomic values (DGVs) in the Jersey population estimated by three different methods. The validation methods...... were (i) fivefold cross-validation and (ii) validation on the most recent 3 years of bulls. The reliability of DGV was assessed using squared correlations between DGV and deregressed proofs (DRPs). In the recent 3-year validation model, estimated reliabilities were also used to assess the reliabilities...... of DGV. The data set consisted of 1003 Danish Jersey bulls with conventional estimated breeding values (EBVs) for 14 different traits included in the Nordic selection index. The bulls were genotyped for Single-nucleotide polymorphism (SNP) markers using the Illumina 54 K chip. A Bayesian method was used...
Full Text Available Abstract Genomic selection refers to the use of genomewide dense markers for breeding value estimation and subsequently for selection. The main challenge of genomic breeding value estimation is the estimation of many effects from a limited number of observations. Bayesian methods have been proposed to successfully cope with these challenges. As an alternative class of models, non- and semiparametric models were recently introduced. The present study investigated the ability of nonparametric additive regression models to predict genomic breeding values. The genotypes were modelled for each marker or pair of flanking markers (i.e. the predictors separately. The nonparametric functions for the predictors were estimated simultaneously using additive model theory, applying a binomial kernel. The optimal degree of smoothing was determined by bootstrapping. A mutation-drift-balance simulation was carried out. The breeding values of the last generation (genotyped was predicted using data from the next last generation (genotyped and phenotyped. The results show moderate to high accuracies of the predicted breeding values. A determination of predictor specific degree of smoothing increased the accuracy.
Přibyl, J; Bauer, J; Čermák, V; Pešek, P; Přibylová, J; Šplíchal, J; Vostrá-Vydrová, H; Vostrý, L; Zavadilová, L
Estimated breeding values (EBVs) and genomic enhanced breeding values (GEBVs) for milk production of young genotyped Holstein bulls were predicted using a conventional BLUP - Animal Model, a method fitting regression coefficients for loci (RRBLUP), a method utilizing the realized genomic relationship matrix (GBLUP), by a single-step procedure (ssGBLUP) and by a one-step blending procedure. Information sources for prediction were the nation-wide database of domestic Czech production records in the first lactation combined with deregressed proofs (DRP) from Interbull files (August 2013) and domestic test-day (TD) records for the first three lactations. Data from 2627 genotyped bulls were used, of which 2189 were already proven under domestic conditions. Analyses were run that used Interbull values for genotyped bulls only or that used Interbull values for all available sires. Resultant predictions were compared with GEBV of 96 young foreign bulls evaluated abroad and whose proofs were from Interbull method GMACE (August 2013) on the Czech scale. Correlations of predictions with GMACE values of foreign bulls ranged from 0.33 to 0.75. Combining domestic data with Interbull EBVs improved prediction of both EBV and GEBV. Predictions by Animal Model (traditional EBV) using only domestic first lactation records and GMACE values were correlated by only 0.33. Combining the nation-wide domestic database with all available DRP for genotyped and un-genotyped sires from Interbull resulted in an EBV correlation of 0.60, compared with 0.47 when only Interbull data were used. In all cases, GEBVs had higher correlations than traditional EBVs, and the highest correlations were for predictions from the ssGBLUP procedure using combined data (0.75), or with all available DRP from Interbull records only (one-step blending approach, 0.69). The ssGBLUP predictions using the first three domestic lactation records in the TD model were correlated with GMACE predictions by 0.69, 0.64 and 0
Full Text Available Objective Holsteins are known as the world’s highest-milk producing dairy cattle. The purpose of this study was to identify genetic regions strongly associated with milk traits (milk production, fat, and protein using Korean Holstein data. Methods This study was performed using single nucleotide polymorphism (SNP chip data (Illumina BovineSNP50 Beadchip of 911 Korean Holstein individuals. We inferred each genomic estimated breeding values based on best linear unbiased prediction (BLUP and ridge regression using BLUPF90 and R. We then performed a genome-wide association study and identified genetic regions related to milk traits. Results We identified 9, 6, and 17 significant genetic regions related to milk production, fat and protein, respectively. These genes are newly reported in the genetic association with milk traits of Holstein. Conclusion This study complements a recent Holstein genome-wide association studies that identified other SNPs and genes as the most significant variants. These results will help to expand the knowledge of the polygenic nature of milk production in Holsteins.
Full Text Available Abstract Background The predictive ability of genomic estimated breeding values (GEBV originates both from associations between high-density markers and QTL (Quantitative Trait Loci and from pedigree information. Thus, GEBV are expected to provide more persistent accuracy over successive generations than breeding values estimated using pedigree-based methods. The objective of this study was to evaluate the accuracy of GEBV in a closed population of layer chickens and to quantify their persistence over five successive generations using marker or pedigree information. Methods The training data consisted of 16 traits and 777 genotyped animals from two generations of a brown-egg layer breeding line, 295 of which had individual phenotype records, while others had phenotypes on 2,738 non-genotyped relatives, or similar data accumulated over up to five generations. Validation data included phenotyped and genotyped birds from five subsequent generations (on average 306 birds/generation. Birds were genotyped for 23,356 segregating SNP. Animal models using genomic or pedigree relationship matrices and Bayesian model averaging methods were used for training analyses. Accuracy was evaluated as the correlation between EBV and phenotype in validation divided by the square root of trait heritability. Results Pedigree relationships in outbred populations are reduced by 50% at each meiosis, therefore accuracy is expected to decrease by the square root of 0.5 every generation, as observed for pedigree-based EBV (Estimated Breeding Values. In contrast the GEBV accuracy was more persistent, although the drop in accuracy was substantial in the first generation. Traits that were considered to be influenced by fewer QTL and to have a higher heritability maintained a higher GEBV accuracy over generations. In conclusion, GEBV capture information beyond pedigree relationships, but retraining every generation is recommended for genomic selection in closed breeding
Akdemir, Deniz; Sánchez, Julio I
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.
Su, G; Guldbrandtsen, B; Gregersen, V R
or no effects, and a single prior distribution common for all SNP. It was found that, in general, the model with a common prior distribution of scaling factors had better predictive ability than any mixture prior models. Therefore, a common prior model was used to estimate SNP effects and breeding values......Abstract This study investigated the reliability of genomic estimated breeding values (GEBV) in the Danish Holstein population. The data in the analysis included 3,330 bulls with both published conventional EBV and single nucleotide polymorphism (SNP) markers. After data editing, 38,134 SNP markers...... were available. In the analysis, all SNP were fitted simultaneously as random effects in a Bayesian variable selection model, which allows heterogeneous variances for different SNP markers. The response variables were the official EBV. Direct GEBV were calculated as the sum of individual SNP effects...
Ould Estaghvirou, Sidi Boubacar; Ogutu, Joseph O; Schulz-Streeck, Torben; Knaak, Carsten; Ouzunova, Milena; Gordillo, Andres; Piepho, Hans-Peter
In genomic prediction, an important measure of accuracy is the correlation between the predicted and the true breeding values. Direct computation of this quantity for real datasets is not possible, because the true breeding value is unknown. Instead, the correlation between the predicted breeding values and the observed phenotypic values, called predictive ability, is often computed. In order to indirectly estimate predictive accuracy, this latter correlation is usually divided by an estimate of the square root of heritability. In this study we use simulation to evaluate estimates of predictive accuracy for seven methods, four (1 to 4) of which use an estimate of heritability to divide predictive ability computed by cross-validation. Between them the seven methods cover balanced and unbalanced datasets as well as correlated and uncorrelated genotypes. We propose one new indirect method (4) and two direct methods (5 and 6) for estimating predictive accuracy and compare their performances and those of four other existing approaches (three indirect (1 to 3) and one direct (7)) with simulated true predictive accuracy as the benchmark and with each other. The size of the estimated genetic variance and hence heritability exerted the strongest influence on the variation in the estimated predictive accuracy. Increasing the number of genotypes considerably increases the time required to compute predictive accuracy by all the seven methods, most notably for the five methods that require cross-validation (Methods 1, 2, 3, 4 and 6). A new method that we propose (Method 5) and an existing method (Method 7) used in animal breeding programs were the fastest and gave the least biased, most precise and stable estimates of predictive accuracy. Of the methods that use cross-validation Methods 4 and 6 were often the best. The estimated genetic variance and the number of genotypes had the greatest influence on predictive accuracy. Methods 5 and 7 were the fastest and produced the least
Full Text Available Abstract Background The QTLMAS XVth dataset consisted of pedigree, marker genotypes and quantitative trait performances of animals with a sib family structure. Pedigree and genotypes concerned 3,000 progenies among those 2,000 were phenotyped. The trait was regulated by 8 QTLs which displayed additive, imprinting or epistatic effects. The 1,000 unphenotyped progenies were considered as candidates to selection and their Genomic Estimated Breeding Values (GEBV were evaluated by participants of the XVth QTLMAS workshop. This paper aims at comparing the GEBV estimation results obtained by seven participants to the workshop. Methods From the known QTL genotypes of each candidate, two "true" genomic values (TV were estimated by organizers: the genotypic value of the candidate (TGV and the expectation of its progeny genotypic values (TBV. GEBV were computed by the participants following different statistical methods: random linear models (including BLUP and Ridge Regression, selection variable techniques (LASSO, Elastic Net and Bayesian methods. Accuracy was evaluated by the correlation between TV (TGV or TBV and GEBV presented by participants. Rank correlation of the best 10% of individuals and error in predictions were also evaluated. Bias was tested by regression of TV on GEBV. Results Large differences between methods were found for all criteria and type of genetic values (TGV, TBV. In general, the criteria ranked consistently methods belonging to the same family. Conclusions Bayesian methods - A
Newell, Mark A; Jannink, Jean-Luc
Genomic selection (GS) is a method to predict the genetic value of selection candidates based on the genomic estimated breeding value (GEBV) predicted from high-density markers positioned throughout the genome. Unlike marker-assisted selection, the GEBV is based on all markers including both minor and major marker effects. Thus, the GEBV may capture more of the genetic variation for the particular trait under selection.
Mark, Thomas; Sandøe, Peter
the thoughts of breeders and other stakeholders on how to best make use of genomic breeding in the future. Intensive breeding has played a major role in securing dramatic increases in milk yield since the Second World War. Until recently, the main focus in dairy cattle breeding was on production traits...... it less accountable to the concern of private farmers for the welfare of their animals. It is argued that there is a need to mobilise a wide range of stakeholders to monitor developments and maintain pressure on breeding companies so that they are aware of the need to take precautionary measures to avoid...
Full Text Available More than 80% of the 19 million ha of maize ( L. in tropical Asia is rainfed and prone to drought. The breeding methods for improving drought tolerance (DT, including genomic selection (GS, are geared to increase the frequency of favorable alleles. Two biparental populations (CIMMYT-Asia Population 1 [CAP1] and CAP2 were generated by crossing elite Asian-adapted yellow inbreds (CML470 and VL1012767 with an African white drought-tolerant line, CML444. Marker effects of polymorphic single-nucleotide polymorphisms (SNPs were determined from testcross (TC performance of F families under drought and optimal conditions. Cycle 1 (C1 was formed by recombining the top 10% of the F families based on TC data. Subsequently, (i C2[PerSe_PS] was derived by recombining those C1 plants that exhibited superior per se phenotypes (phenotype-only selection, and (ii C2[TC-GS] was derived by recombining a second set of C1 plants with high genomic estimated breeding values (GEBVs derived from TC phenotypes of F families (marker-only selection. All the generations and their top crosses to testers were evaluated under drought and optimal conditions. Per se grain yields (GYs of C2[PerSe_PS] and that of C2[TC-GS] were 23 to 39 and 31 to 53% better, respectively, than that of the corresponding F population. The C2[TC-GS] populations showed superiority of 10 to 20% over C2[PerSe-PS] of respective populations. Top crosses of C2[TC-GS] showed 4 to 43% superiority of GY over that of C2[PerSe_PS] of respective populations. Thus, GEBV-enabled selection of superior phenotypes (without the target stress resulted in rapid genetic gains for DT.
Boerner, V; Johnston, D; Wu, X-L; Bauck, S
Genomically estimated breeding values (GEBV) for Angus beef cattle are available from at least 2 commercial suppliers (Igenity [http://www.igenity.com] and Zoetis [http://www.zoetis.com]). The utility of these GEBV for improving genetic evaluation depends on their accuracies, which can be estimated by the genetic correlation with phenotypic target traits. Genomically estimated breeding values of 1,032 Angus bulls calculated from prediction equations (PE) derived by 2 different procedures in the U.S. Angus population were supplied by Igenity. Both procedures were based on Illuminia BovineSNP50 BeadChip genotypes. In procedure sg, GEBV were calculated from PE that used subsets of only 392 SNP, where these subsets were individually selected for each trait by BayesCπ. In procedure rg GEBV were calculated from PE derived in a ridge regression approach using all available SNP. Because the total set of 1,032 bulls with GEBV contained 732 individuals used in the Igenity training population, GEBV subsets were formed characterized by a decreasing average relationship between individuals in the subsets and individuals in the training population. Accuracies of GEBV were estimated as genetic correlations between GEBV and their phenotypic target traits modeling GEBV as trait observations in a bivariate REML approach, in which phenotypic observations were those recorded in the commercial Australian Angus seed stock sector. Using results from the GEBV subset excluding all training individuals as a reference, estimated accuracies were generally in agreement with those already published, with both types of GEBV (sg and rg) yielding similar results. Accuracies for growth traits ranged from 0.29 to 0.45, for reproductive traits from 0.11 to 0.53, and for carcass traits from 0.3 to 0.75. Accuracies generally decreased with an increasing genetic distance between the training and the validation population. However, for some carcass traits characterized by a low number of phenotypic
Yu, Xijiang; Meuwissen, Theo H E
Genome-wide breeding value (GWEBV) estimation methods can be classified based on the prior distribution assumptions of marker effects. Genome-wide BLUP methods assume a normal prior distribution for all markers with a constant variance, and are computationally fast. In Bayesian methods, more flexible prior distributions of SNP effects are applied that allow for very large SNP effects although most are small or even zero, but these prior distributions are often also computationally demanding as they rely on Monte Carlo Markov chain sampling. In this study, we adopted the Pareto principle to weight available marker loci, i.e., we consider that x% of the loci explain (100 - x)% of the total genetic variance. Assuming this principle, it is also possible to define the variances of the prior distribution of the 'big' and 'small' SNP. The relatively few large SNP explain a large proportion of the genetic variance and the majority of the SNP show small effects and explain a minor proportion of the genetic variance. We name this method MixP, where the prior distribution is a mixture of two normal distributions, i.e. one with a big variance and one with a small variance. Simulation results, using a real Norwegian Red cattle pedigree, show that MixP is at least as accurate as the other methods in all studied cases. This method also reduces the hyper-parameters of the prior distribution from 2 (proportion and variance of SNP with big effects) to 1 (proportion of SNP with big effects), assuming the overall genetic variance is known. The mixture of normal distribution prior made it possible to solve the equations iteratively, which greatly reduced computation loads by two orders of magnitude. In the era of marker density reaching million(s) and whole-genome sequence data, MixP provides a computationally feasible Bayesian method of analysis.
Hayes, B J; Donoghue, K A; Reich, C M; Mason, B A; Bird-Gardiner, T; Herd, R M; Arthur, P F
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.
Full Text Available Genomic selection has become a useful tool for animal and plant breeding. Currently, genomic evaluation is usually carried out using a single-trait model. However, a multi-trait model has the advantage of using information on the correlated traits, leading to more accurate genomic prediction. To date, joint genomic prediction for a continuous and a threshold trait using a multi-trait model is scarce and needs more attention. Based on the previously proposed methods BayesCπ for single continuous trait and BayesTCπ for single threshold trait, we developed a novel method based on a linear-threshold model, i.e., LT-BayesCπ, for joint genomic prediction of a continuous trait and a threshold trait. Computing procedures of LT-BayesCπ using Markov Chain Monte Carlo algorithm were derived. A simulation study was performed to investigate the advantages of LT-BayesCπ over BayesCπ and BayesTCπ with regard to the accuracy of genomic prediction on both traits. Factors affecting the performance of LT-BayesCπ were addressed. The results showed that, in all scenarios, the accuracy of genomic prediction obtained from LT-BayesCπ was significantly increased for the threshold trait compared to that from single trait prediction using BayesTCπ, while the accuracy for the continuous trait was comparable with that from single trait prediction using BayesCπ. The proposed LT-BayesCπ could be a method of choice for joint genomic prediction of one continuous and one threshold trait.
Wang, Quanchao; Yu, Yang; Li, Fuhua; Zhang, Xiaojun; Xiang, Jianhai
Genomic selection (GS) can be used to accelerate genetic improvement by shortening the selection interval. The successful application of GS depends largely on the accuracy of the prediction of genomic estimated breeding value (GEBV). This study is a first attempt to understand the practicality of GS in Litopenaeus vannamei and aims to evaluate models for GS on growth traits. The performance of GS models in L. vannamei was evaluated in a population consisting of 205 individuals, which were genotyped for 6 359 single nucleotide polymorphism (SNP) markers by specific length amplified fragment sequencing (SLAF-seq) and phenotyped for body length and body weight. Three GS models (RR-BLUP, BayesA, and Bayesian LASSO) were used to obtain the GEBV, and their predictive ability was assessed by the reliability of the GEBV and the bias of the predicted phenotypes. The mean reliability of the GEBVs for body length and body weight predicted by the different models was 0.296 and 0.411, respectively. For each trait, the performances of the three models were very similar to each other with respect to predictability. The regression coefficients estimated by the three models were close to one, suggesting near to zero bias for the predictions. Therefore, when GS was applied in a L. vannamei population for the studied scenarios, all three models appeared practicable. Further analyses suggested that improved estimation of the genomic prediction could be realized by increasing the size of the training population as well as the density of SNPs.
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...
Iwata, Hiroyoshi; Minamikawa, Mai F.; Kajiya-Kanegae, Hiromi; Ishimori, Motoyuki; Hayashi, Takeshi
Recent advancements in genomic analysis technologies have opened up new avenues to promote the efficiency of plant breeding. Novel genomics-based approaches for plant breeding and genetics research, such as genome-wide association studies (GWAS) and genomic selection (GS), are useful, especially in fruit tree breeding. The breeding of fruit trees is hindered by their long generation time, large plant size, long juvenile phase, and the necessity to wait for the physiological maturity of the pl...
Nakaya, Akihiro; Isobe, Sachiko N.
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...
Iwata, Hiroyoshi; Minamikawa, Mai F; Kajiya-Kanegae, Hiromi; Ishimori, Motoyuki; Hayashi, Takeshi
Recent advancements in genomic analysis technologies have opened up new avenues to promote the efficiency of plant breeding. Novel genomics-based approaches for plant breeding and genetics research, such as genome-wide association studies (GWAS) and genomic selection (GS), are useful, especially in fruit tree breeding. The breeding of fruit trees is hindered by their long generation time, large plant size, long juvenile phase, and the necessity to wait for the physiological maturity of the plant to assess the marketable product (fruit). In this article, we describe the potential of genomics-assisted breeding, which uses these novel genomics-based approaches, to break through these barriers in conventional fruit tree breeding. We first introduce the molecular marker systems and whole-genome sequence data that are available for fruit tree breeding. Next we introduce the statistical methods for biparental linkage and quantitative trait locus (QTL) mapping as well as GWAS and GS. We then review QTL mapping, GWAS, and GS studies conducted on fruit trees. We also review novel technologies for rapid generation advancement. Finally, we note the future prospects of genomics-assisted fruit tree breeding and problems that need to be overcome in the breeding.
Egger-Danner, C; Schwarzenbacher, H; Willam, A
The aim of this study was to quantify the impact of genotyping cows with reliable phenotypes for direct health traits on annual monetary genetic gain (AMGG) and discounted profit. The calculations were based on a deterministic approach using ZPLAN software (University of Hohenheim, Stuttgart, Germany). It was assumed that increases in reliability of the total merit index (TMI) of 5, 15, and 25 percentage points were achieved through genotyping 5,000, 25,000, and 50,000 cows, respectively. Costs for phenotyping, genotyping, and genomic estimated breeding values vary between €150 and €20 per cow. The gain in genotyping cows for traits with medium to high heritability is more than for direct health traits with low heritability. The AMGG is increased by 1.5% if the reliability of TMI is 5 percentage points higher (i.e., 5,000 cows genotyped) and 6.53% higher AMGG can be expected when the reliability of TMI is increased by 25 percentage points (i.e., 50,000 cows genotyped). The discounted profit depends not only on the costs of genotyping but also on the population size. This study indicates that genotyping cows with reliable phenotypes is feasible to speed up the availability of genomic estimated breeding values for direct health traits. But, because of the huge amount of valid phenotypes and genotypes needed to establish an efficient genomic evaluation, it is likely that financial constraints will be the main limiting factor for implementation into breeding program such as Fleckvieh Austria. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
Pérez-de-Castro, A.M.; Vilanova, S.; Cañizares, J.; Pascual, L.; Blanca, J.M.; Díez, M.J.; Prohens, J.; Picó, B.
Plant breeding has been very successful in developing improved varieties using conventional tools and methodologies. Nowadays, the availability of genomic tools and resources is leading to a new revolution of plant breeding, as they facilitate the study of the genotype and its relationship with the phenotype, in particular for complex traits. Next Generation Sequencing (NGS) technologies are allowing the mass sequencing of genomes and transcriptomes, which is producing a vast array of genomic...
Nakaya, Akihiro; Isobe, Sachiko N
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.
Parker, Heidi G
A rose may be a rose by any other name, but when you call a dog a poodle it becomes a very different animal than if you call it a bulldog. Both the poodle and the bulldog are examples of dog breeds of which there are >400 recognized worldwide. Breed creation has played a significant role in shaping the modern dog from the length of his leg to the cadence of his bark. The selection and line-breeding required to maintain a breed has also reshaped the genome of the dog, resulting in a unique genetic pattern for each breed. The breed-based population structure combined with extensive morphologic variation and shared human environments have made the dog a popular model for mapping both simple and complex traits and diseases. In order to obtain the most benefit from the dog as a genetic system, it is necessary to understand the effect structured breeding has had on the genome of the species. That is best achieved by looking at genomic analyses of the breeds, their histories, and their relationships to each other.
Browett, Sam; McHugo, Gillian; Richardson, Ian W.; Magee, David A.; Park, Stephen D. E.; Fahey, Alan G.; Kearney, John F.; Correia, Carolina N.; Randhawa, Imtiaz A. S.; MacHugh, David E.
Kerry cattle are an endangered landrace heritage breed of cultural importance to Ireland. In the present study we have used genome-wide SNP array data to evaluate genomic diversity within the Kerry population and between Kerry cattle and other European breeds. Patterns of genetic differentiation and gene flow among breeds using phylogenetic trees with ancestry graphs highlighted historical gene flow from the British Shorthorn breed into the ancestral population of modern Kerry cattle. Principal component analysis (PCA) and genetic clustering emphasised the genetic distinctiveness of Kerry cattle relative to comparator British and European cattle breeds. Modelling of genetic effective population size (Ne) revealed a demographic trend of diminishing Ne over time and that recent estimated Ne values for the Kerry breed may be less than the threshold for sustainable genetic conservation. In addition, analysis of genome-wide autozygosity (FROH) showed that genomic inbreeding has increased significantly during the 20 years between 1992 and 2012. Finally, signatures of selection revealed genomic regions subject to natural and artificial selection as Kerry cattle adapted to the climate, physical geography and agro-ecology of southwest Ireland. PMID:29520297
Full Text Available Kerry cattle are an endangered landrace heritage breed of cultural importance to Ireland. In the present study we have used genome-wide SNP array data to evaluate genomic diversity within the Kerry population and between Kerry cattle and other European breeds. Patterns of genetic differentiation and gene flow among breeds using phylogenetic trees with ancestry graphs highlighted historical gene flow from the British Shorthorn breed into the ancestral population of modern Kerry cattle. Principal component analysis (PCA and genetic clustering emphasised the genetic distinctiveness of Kerry cattle relative to comparator British and European cattle breeds. Modelling of genetic effective population size (Ne revealed a demographic trend of diminishing Ne over time and that recent estimated Ne values for the Kerry breed may be less than the threshold for sustainable genetic conservation. In addition, analysis of genome-wide autozygosity (FROH showed that genomic inbreeding has increased significantly during the 20 years between 1992 and 2012. Finally, signatures of selection revealed genomic regions subject to natural and artificial selection as Kerry cattle adapted to the climate, physical geography and agro-ecology of southwest Ireland.
Pérez-de-Castro, A M; Vilanova, S; Cañizares, J; Pascual, L; Blanca, J M; Díez, M J; Prohens, J; Picó, B
Plant breeding has been very successful in developing improved varieties using conventional tools and methodologies. Nowadays, the availability of genomic tools and resources is leading to a new revolution of plant breeding, as they facilitate the study of the genotype and its relationship with the phenotype, in particular for complex traits. Next Generation Sequencing (NGS) technologies are allowing the mass sequencing of genomes and transcriptomes, which is producing a vast array of genomic information. The analysis of NGS data by means of bioinformatics developments allows discovering new genes and regulatory sequences and their positions, and makes available large collections of molecular markers. Genome-wide expression studies provide breeders with an understanding of the molecular basis of complex traits. Genomic approaches include TILLING and EcoTILLING, which make possible to screen mutant and germplasm collections for allelic variants in target genes. Re-sequencing of genomes is very useful for the genome-wide discovery of markers amenable for high-throughput genotyping platforms, like SSRs and SNPs, or the construction of high density genetic maps. All these tools and resources facilitate studying the genetic diversity, which is important for germplasm management, enhancement and use. Also, they allow the identification of markers linked to genes and QTLs, using a diversity of techniques like bulked segregant analysis (BSA), fine genetic mapping, or association mapping. These new markers are used for marker assisted selection, including marker assisted backcross selection, 'breeding by design', or new strategies, like genomic selection. In conclusion, advances in genomics are providing breeders with new tools and methodologies that allow a great leap forward in plant breeding, including the 'superdomestication' of crops and the genetic dissection and breeding for complex traits.
E. Charles Brummer
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.
Gois, I B; Borém, A; Cristofani-Yaly, M; de Resende, M D V; Azevedo, C F; Bastianel, M; Novelli, V M; Machado, M A
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.
Genomic prediction is successful in single breed genetic evaluation. However, there is no achievement in acoress breed prediction until now. This thesis investigated genomic prediction across populations and breeds using Chinese Holsterin, Nordic Holstein, Norwgian Red, and Nordic Red. Nordic Red...
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
Jonas, Elisabeth; de Koning, Dirk-Jan
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.
van den Berg, Irene; Guldbrandtsen, Bernt; Hozé, C
Our objective was to investigate the potential benefits of using sequence data to improve across breed genomic prediction, using data from five French and Danish dairy cattle breeds. First, QTL for protein yield were detected using high density genotypes. Part of the QTL detected within breed was...
Semenova, S K; Illarionova, N A; Vasil'ev, V A; Shubkina, A V; Ryskov, A P
The method of polymerase chain reaction with a set of arbitrary primers (RAPD-PCR) was used to describe genetic variation and to estimate genetic diversity in East-European swift hounds, Russian Psovyi and Hortyi Borzois. For comparison, swift hounds of two West-European breeds (Whippet and Greyhound) and single dogs of other breed groups (shepherd, terriers, mastiffs, and bird dogs) were examined. For all dog groups, their closest related species, the wolf Canis lupus, was used as an outgroup. Variation of RAPD markers was studied at several hierarchic levels: intra- and interfamily (for individual families of Russian Psovyi and Hortyi Borzois), intra- and interbreed (for ten dog breeds), and interspecific (C. familiaris-C. lupus). In total, 57 dogs and 4 wolfs were studied. Using RAPD-PCR with three primers, 93 DNA fragments with a length of 150-1500 bp were detected in several Borzoi families with known filiation. These fragments were found to be inherited as dominant markers and to be applicable for estimation of genetic differences between parents and their offspring and for comparison of individuals and families with different level of inbreeding. A high level of intra- and interbreed variation was found in Russian Psovyi and Hortyi Borzois. In these dog groups, genetic similarity indices varied in a range of 72.2 to 93.4% (parents-offspring) and 68.0 to 94.5 (sibs). Based on the patterns of RAPD markers obtained using six primers, a dendrogram of genetic similarity between the wolf and different dog breeds was constructed, and indices of intragroup diversity were calculated. All studied breeds were found to fall into two clusters, swift hounds (Borzoi-like dogs) and other dogs. Russian Borzois represent a very heterogeneous group, in which the Russian Psovyi Borzoi is closer to Greyhound than the Russian Hortyi Borzoi. All studied wolfs constituted a separate cluster. Significant differences were found between the wolf and dogs by the number of RAPD markers
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
Nastasiya F Grinberg
Full Text Available Perennial ryegrass (Lolium perenne L. is one of the most widely grown forage grasses in temperate agriculture. In order to maintain and increase its usage as forage in livestock agriculture, there is a continued need for improvement in biomass yield, quality, disease resistance and seed yield. Genetic gain for traits such as biomass yield has been relatively modest. This has been attributed to its long breeding cycle, and the necessity to use population based breeding methods. Thanks to recent advances in genotyping techniques there is increasing interest in genomic selection from which genomically estimated breeding values (GEBV are derived. In this paper we compare the classical RRBLUP model with state-of-the-art machine learning (ML techniques that should yield themselves easily to use in GS and demonstrate their application to predicting quantitative traits in a breeding population of L. perenne. Prediction accuracies varied from 0 to 0.59 depending on trait, prediction model and composition of the training population. The BLUP model produced the highest prediction accuracies for most traits and training populations. Forage quality traits had the highest accuracies compared to yield related traits. There appeared to be no clear pattern to the effect of the training population composition on the prediction accuracies. The heritability of the forage quality traits was generally higher than for the yield related traits, and could partly explain the difference in accuracy. Some population structure was evident in the breeding populations, and probably contributed to the varying effects of training population on the predictions. The average linkage disequilibrium (LD between adjacent markers ranged from 0.121 to 0.215. Higher marker density and larger training population closely related with the test population are likely to improve the prediction accuracy.
Fé, Dario; Ashraf, Bilal; Greve-Pedersen, Morten
We present a genomic selection study performed on 1918 rye grass families (Lolium perenne L.), which were derived from a commercial breeding program at DLF-Trifolium, Denmark. Phenotypes were recorded on standard plots, across 13 years and in 6 different countries. Variants were identified...... this set. Estimated Breeding Value and prediction accuracies were calculated trough two different cross-validation schemes: (i) k-fold (k=10); (ii) leaving out one parent combination at the time, in order to test for accuracy of predicting new families. Accuracies ranged between 0.56 and 0.97 for scheme (i....... A larger set of 1791 F2s were used as training set to predict EBVs of 127 synthetic families (originated from poly-crosses between 5-11 single plants) for heading date and crown rust resistance. Prediction accuracies were 0.93 and 0.57 respectively. Results clearly demonstrate considerable potential...
Breeding value estimation for somatic cell score in South African dairy cattle. ... are not unity, the RM-model estimates more competitive variances and requires ... are therefore recommended for breeding value estimation on a national basis.
Zanella, Ricardo; Peixoto, Jane O; Cardoso, Fernando F; Cardoso, Leandro L; Biegelmeyer, Patrícia; Cantão, Maurício E; Otaviano, Antonio; Freitas, Marcelo S; Caetano, Alexandre R; Ledur, Mônica C
Genetic improvement in livestock populations can be achieved without significantly affecting genetic diversity if mating systems and selection decisions take genetic relationships among individuals into consideration. The objective of this study was to examine the genetic diversity of two commercial breeds of pigs. Genotypes from 1168 Landrace (LA) and 1094 Large White (LW) animals from a commercial breeding program in Brazil were obtained using the Illumina PorcineSNP60 Beadchip. Inbreeding estimates based on pedigree (F x) and genomic information using runs of homozygosity (F ROH) and the single nucleotide polymorphisms (SNP) by SNP inbreeding coefficient (F SNP) were obtained. Linkage disequilibrium (LD), correlation of linkage phase (r) and effective population size (N e ) were also estimated. Estimates of inbreeding obtained with pedigree information were lower than those obtained with genomic data in both breeds. We observed that the extent of LD was slightly larger at shorter distances between SNPs in the LW population than in the LA population, which indicates that the LW population was derived from a smaller N e . Estimates of N e based on genomic data were equal to 53 and 40 for the current populations of LA and LW, respectively. The correlation of linkage phase between the two breeds was equal to 0.77 at distances up to 50 kb, which suggests that genome-wide association and selection should be performed within breed. Although selection intensities have been stronger in the LA breed than in the LW breed, levels of genomic and pedigree inbreeding were lower for the LA than for the LW breed. The use of genomic data to evaluate population diversity in livestock animals can provide new and more precise insights about the effects of intense selection for production traits. Resulting information and knowledge can be used to effectively increase response to selection by appropriately managing the rate of inbreeding, minimizing negative effects of inbreeding
Zhao, Yusheng; Gowda, Manje; Liu, Wenxin; Würschum, Tobias; Maurer, Hans P; Longin, Friedrich H; Ranc, Nicolas; Reif, Jochen C
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.
Bouquet, A; Juga, J
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
Jonas, Elisabeth; de Koning, Dirk-Jan
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.
Gobena, Mesfin; Elzo, Mauricio A; Mateescu, Raluca G
Crossbreeding is a common strategy used in tropical and subtropical regions to enhance beef production, and having accurate knowledge of breed composition is essential for the success of a crossbreeding program. Although pedigree records have been traditionally used to obtain the breed composition of crossbred cattle, the accuracy of pedigree-based breed composition can be reduced by inaccurate and/or incomplete records and Mendelian sampling. Breed composition estimation from genomic data has multiple advantages including higher accuracy without being affected by missing, incomplete, or inaccurate records and the ability to be used as independent authentication of breed in breed-labeled beef products. The present study was conducted with 676 Angus-Brahman crossbred cattle with genotype and pedigree information to evaluate the feasibility and accuracy of using genomic data to determine breed composition. We used genomic data in parametric and non-parametric methods to detect population structure due to differences in breed composition while accounting for the confounding effect of close familial relationships. By applying principal component analysis (PCA) and the maximum likelihood method of ADMIXTURE to genomic data, it was possible to successfully characterize population structure resulting from heterogeneous breed ancestry, while accounting for close familial relationships. PCA results offered additional insight into the different hierarchies of genetic variation structuring. The first principal component was strongly correlated with Angus-Brahman proportions, and the second represented variation within animals that have a relatively more extended Brangus lineage-indicating the presence of a distinct pattern of genetic variation in these cattle. Although there was strong agreement between breed proportions estimated from pedigree and genetic information, there were significant discrepancies between these two methods for certain animals. This was most likely due
Full Text Available Crossbreeding is a common strategy used in tropical and subtropical regions to enhance beef production, and having accurate knowledge of breed composition is essential for the success of a crossbreeding program. Although pedigree records have been traditionally used to obtain the breed composition of crossbred cattle, the accuracy of pedigree-based breed composition can be reduced by inaccurate and/or incomplete records and Mendelian sampling. Breed composition estimation from genomic data has multiple advantages including higher accuracy without being affected by missing, incomplete, or inaccurate records and the ability to be used as independent authentication of breed in breed-labeled beef products. The present study was conducted with 676 Angus–Brahman crossbred cattle with genotype and pedigree information to evaluate the feasibility and accuracy of using genomic data to determine breed composition. We used genomic data in parametric and non-parametric methods to detect population structure due to differences in breed composition while accounting for the confounding effect of close familial relationships. By applying principal component analysis (PCA and the maximum likelihood method of ADMIXTURE to genomic data, it was possible to successfully characterize population structure resulting from heterogeneous breed ancestry, while accounting for close familial relationships. PCA results offered additional insight into the different hierarchies of genetic variation structuring. The first principal component was strongly correlated with Angus–Brahman proportions, and the second represented variation within animals that have a relatively more extended Brangus lineage—indicating the presence of a distinct pattern of genetic variation in these cattle. Although there was strong agreement between breed proportions estimated from pedigree and genetic information, there were significant discrepancies between these two methods for certain animals
Haberland, A M; König von Borstel, U; Simianer, H; König, S
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.
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
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.
Clark, Samuel A; Hickey, John M; Daetwyler, Hans D; van der Werf, Julius H J
The theory of genomic selection is based on the prediction of the effects of genetic markers in linkage disequilibrium with quantitative trait loci. However, genomic selection also relies on relationships between individuals to accurately predict genetic value. This study aimed to examine the importance of information on relatives versus that of unrelated or more distantly related individuals on the estimation of genomic breeding values. Simulated and real data were used to examine the effects of various degrees of relationship on the accuracy of genomic selection. Genomic Best Linear Unbiased Prediction (gBLUP) was compared to two pedigree based BLUP methods, one with a shallow one generation pedigree and the other with a deep ten generation pedigree. The accuracy of estimated breeding values for different groups of selection candidates that had varying degrees of relationships to a reference data set of 1750 animals was investigated. The gBLUP method predicted breeding values more accurately than BLUP. The most accurate breeding values were estimated using gBLUP for closely related animals. Similarly, the pedigree based BLUP methods were also accurate for closely related animals, however when the pedigree based BLUP methods were used to predict unrelated animals, the accuracy was close to zero. In contrast, gBLUP breeding values, for animals that had no pedigree relationship with animals in the reference data set, allowed substantial accuracy. An animal's relationship to the reference data set is an important factor for the accuracy of genomic predictions. Animals that share a close relationship to the reference data set had the highest accuracy from genomic predictions. However a baseline accuracy that is driven by the reference data set size and the overall population effective population size enables gBLUP to estimate a breeding value for unrelated animals within a population (breed), using information previously ignored by pedigree based BLUP methods.
Shakil Ahmad Bhat
Full Text Available Since centuries, the traits for production and disease resistance are being targeted while improving the genetic merit of domestic animals, using conventional breeding programs such as inbreeding, outbreeding, or introduction of marker-assisted selection. The arrival of new scientific concepts, such as cloning and genome engineering, has added a new and promising research dimension to the existing animal breeding programs. Development of genome editing technologies such as transcription activator-like effector nuclease, zinc finger nuclease, and clustered regularly interspaced short palindromic repeats systems begun a fresh era of genome editing, through which any change in the genome, including specific DNA sequence or indels, can be made with unprecedented precision and specificity. Furthermore, it offers an opportunity of intensification in the frequency of desirable alleles in an animal population through gene-edited individuals more rapidly than conventional breeding. The specific research is evolving swiftly with a focus on improvement of economically important animal species or their traits all of which form an important subject of this review. It also discusses the hurdles to commercialization of these techniques despite several patent applications owing to the ambiguous legal status of genome-editing methods on account of their disputed classification. Nonetheless, barring ethical concerns gene-editing entailing economically important genes offers a tremendous potential for breeding animals with desirable traits.
Rajeev K. Varshney
Full Text Available The major abiotic and biotic stresses that adversely affect yield of chickpea (Cicer arietinum L. include drought, heat, fusarium wilt, ascochyta blight and pod borer. Excellent progress has been made in developing short-duration varieties with high resistance to fusarium wilt. The early maturity helps in escaping terminal drought and heat stresses and the adaptation of chickpea to short-season environments. Ascochyta blight continues to be a major challenge to chickpea productivity in areas where chickpea is exposed to cool and wet conditions. Limited variability for pod borer resistance has been a major bottleneck in the development of pod borer resistant cultivars. The use of genomics technologies in chickpea breeding programs has been limited, since available genomic resources were not adequate and limited polymorphism was observed in the cultivated chickpea for the available molecular markers. Remarkable progress has been made in the development of genetic and genomic resources in recent years and integration of genomic technologies in chickpea breeding has now started. Marker-assisted breeding is currently being used for improving drought tolerance and combining resistance to diseases. The integration of genomic technologies is expected to improve the precision and efficiency of chickpea breeding in the development of improved cultivars with enhanced resistance to abiotic and biotic stresses, better adaptation to existing and evolving agro-ecologies and traits preferred by farmers, industries and consumers.
Maurice-Van Eijndhoven, M H T; Bovenhuis, H; Veerkamp, R F; Calus, M P L
The aim of this study was to identify if genomic variations associated with fatty acid (FA) composition are similar between the Holstein-Friesian (HF) and native dual-purpose breeds used in the Dutch dairy industry. Phenotypic and genotypic information were available for the breeds Meuse-Rhine-Yssel (MRY), Dutch Friesian (DF), Groningen White Headed (GWH), and HF. First, the reliability of genomic breeding values of the native Dutch dual-purpose cattle breeds MRY, DF, and GWH was evaluated using single nucleotide polymorphism (SNP) effects estimated in HF, including all SNP or subsets with stronger associations in HF. Second, the genomic variation of the regions associated with FA composition in HF (regions on Bos taurus autosome 5, 14, and 26), were studied in the different breeds. Finally, similarities in genotype and allele frequencies between MRY, DF, GWH, and HF breeds were assessed for specific regions associated with FA composition. On average across the traits, the highest reliabilities of genomic prediction were estimated for GWH (0.158) and DF (0.116) when the 8 to 22 SNP with the strongest association in HF were included. With the same set of SNP, GEBV for MRY were the least reliable (0.022). This indicates that on average only 2 (MRY) to 16% (GWH) of the genomic variation in HF is shared with the native Dutch dual-purpose breeds. The comparison of predicted variances of different regions associated with milk and milk fat composition showed that breeds clearly differed in genomic variation within these regions. Finally, the correlations of allele frequencies between breeds across the 8 to 22 SNP with the strongest association in HF were around 0.8 between the Dutch native dual-purpose breeds, whereas the correlations between the native breeds and HF were clearly lower and around 0.5. There was no consistent relationship between the reliabilities of genomic prediction for a specific breed and the correlation between the allele frequencies of this breed
Choi, Taejeong; Lim, Dajeong; Park, Byoungho; Sharma, Aditi; Kim, Jong-Joo; Kim, Sidong; Lee, Seung Hwan
Intramuscular fat is one of the meat quality traits that is considered in the selection strategies for Hanwoo (Korean cattle). Different methods are used to estimate the breeding value of selection candidates. In the present work we focused on accuracy of different genotype relationship matrices as described by forni and pedigree based relationship matrix. The data set included a total of 778 animals that were genotyped for BovineSNP50 BeadChip. Among these 778 animals, 72 animals were sires for 706 reference animals and were used as a validation dataset. Single trait animal model (best linear unbiased prediction and genomic best linear unbiased prediction) was used to estimate the breeding values from genomic and pedigree information. The diagonal elements for the pedigree based coefficients were slightly higher for the genomic relationship matrices (GRM) based coefficients while off diagonal elements were considerably low for GRM based coefficients. The accuracy of breeding value for the pedigree based relationship matrix (A) was 13% while for GRM (GOF, G05, and Yang) it was 0.37, 0.45, and 0.38, respectively. Accuracy of GRM was 1.5 times higher than A in this study. Therefore, genomic information will be more beneficial than pedigree information in the Hanwoo breeding program.
Tayeh, Nadim; Aubert, Grégoire; Pilet-Nayel, Marie-Laure; Lejeune-Hénaut, Isabelle; Warkentin, Thomas D.; Burstin, Judith
Pea (Pisum sativum L.) is an annual cool-season legume and one of the oldest domesticated crops. Dry pea seeds contain 22–25% protein, complex starch and fiber constituents, and a rich array of vitamins, minerals, and phytochemicals which make them a valuable source for human consumption and livestock feed. Dry pea ranks third to common bean and chickpea as the most widely grown pulse in the world with more than 11 million tons produced in 2013. Pea breeding has achieved great success since the time of Mendel's experiments in the mid-1800s. However, several traits still require significant improvement for better yield stability in a larger growing area. Key breeding objectives in pea include improving biotic and abiotic stress resistance and enhancing yield components and seed quality. Taking advantage of the diversity present in the pea genepool, many mapping populations have been constructed in the last decades and efforts have been deployed to identify loci involved in the control of target traits and further introgress them into elite breeding materials. Pea now benefits from next-generation sequencing and high-throughput genotyping technologies that are paving the way for genome-wide association studies and genomic selection approaches. This review covers the significant development and deployment of genomic tools for pea breeding in recent years. Future prospects are discussed especially in light of current progress toward deciphering the pea genome. PMID:26640470
Full Text Available Pea (Pisum sativum L. is an annual cool-season legume and one of the oldest domesticated crops. Dry pea seeds contain 22-25 percent protein, complex starch and fibre constituents and a rich array of vitamins, minerals, and phytochemicals which make them a valuable source for human consumption and livestock feed. Dry pea ranks third to common bean and chickpea as the most widely grown pulse in the world with more than 11 million tonnes produced in 2013. Pea breeding has achieved great success since the time of Mendel’s experiments in the mid-1800s. However, several traits still require significant improvement for better yield stability in a larger growing area. Key breeding objectives in pea include improving biotic and abiotic stress resistance and enhancing yield components and seed quality. Taking advantage of the diversity present in the pea genepool, many mapping populations have been constructed in the last decades and efforts have been deployed to identify loci involved in the control of target traits and further introgress them into elite breeding materials. Pea now benefits from next-generation sequencing and high-throughput genotyping technologies that are paving the way for genome-wide association studies and genomic selection approaches. This review covers the significant development and deployment of genomic tools for pea breeding in recent years. Future prospects are discussed especially in light of current progress towards deciphering the pea genome.
Chakradhar, Thammineni; Hindu, Vemuri; Reddy, Palakolanu Sudhakar
Maize has traditionally been the main staple diet in the Southern Asia and Sub-Saharan Africa and widely grown by millions of resource poor small scale farmers. Approximately, 35.4 million hectares are sown to tropical maize, constituting around 59% of the developing worlds. Tropical maize encounters tremendous challenges besides poor agro-climatic situations with average yields recorded <3 tones/hectare that is far less than the average of developed countries. On the contrary to poor yields, the demand for maize as food, feed, and fuel is continuously increasing in these regions. Heterosis breeding introduced in early 90 s improved maize yields significantly, but genetic gains is still a mirage, particularly for crop growing under marginal environments. Application of molecular markers has accelerated the pace of maize breeding to some extent. The availability of array of sequencing and genotyping technologies offers unrivalled service to improve precision in maize-breeding programs through modern approaches such as genomic selection, genome-wide association studies, bulk segregant analysis-based sequencing approaches, etc. Superior alleles underlying complex traits can easily be identified and introgressed efficiently using these sequence-based approaches. Integration of genomic tools and techniques with advanced genetic resources such as nested association mapping and backcross nested association mapping could certainly address the genetic issues in maize improvement programs in developing countries. Huge diversity in tropical maize and its inherent capacity for doubled haploid technology offers advantage to apply the next generation genomic tools for accelerating production in marginal environments of tropical and subtropical world. Precision in phenotyping is the key for success of any molecular-breeding approach. This article reviews genomic technologies and their application to improve agronomic traits in tropical maize breeding has been reviewed in
Marcos A. Machado
Full Text Available Although the citriculture is one of the most important economic activities in Brazil, it is based on a small number of varieties. This fact has contributed for the vulnerability of the culture regarding the phytosanitary problems. A higher number of varieties/genotypes with potential for commercial growing, either for the industry or fresh market, has been one of the main objectives of citrus breeding programs. The genetic breeding of citrus has improved, in the last decades, due to the possibility of an association between biotechnological tools and classical methods of breeding. The use of molecular markers for early selection of zygotic seedlings from controlled crosses resulted in the possibility of selection of a high number of new combination and, as a consequence, the establishment of a great number of hybrids in field experiments. The faster new tools are incorporated in the program, the faster is possibility to reach new genotypes that can be tested as a new variety. Good traits should be kept or incorporate, whereas bad traits have to be excluded or minimized in the new genotype. Scion and rootstock can not be considered separately, and graft compatibility, fruit quality and productivity are essential traits to be evaluated in the last stages of the program. The mapping of QTLs has favored breeding programs of several perennial species and in citrus it was possible to map several characteristics with qualitative and quantitative inheritance. The existence of linkage maps and QTLs already mapped, the development of EST and BAC library and the sequencing of the Citrus complete genome altogether make very demanding and urgent the exploration of such data to launch a wider genetic study of citrus. The rising of information on genome of several organisms has opened new approaches looking for integration between breeding, genetic and genome. Genome assisted selection (GAS involves more than gene or complete genome sequencing and is becoming
Dimitrijevic, Aleksandra; Horn, Renate
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
Dimitrijevic, Aleksandra; Horn, Renate
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
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
Dnyaneshwar C. Kadam
Full Text Available Prediction of single-cross performance has been a major goal of plant breeders since the beginning of hybrid breeding. Recently, genomic prediction has shown to be a promising approach, but only limited studies have examined the accuracy of predicting single-cross performance. Moreover, no studies have examined the potential of predicting single crosses among random inbreds derived from a series of biparental families, which resembles the structure of germplasm comprising the initial stages of a hybrid maize breeding pipeline. The main objectives of this study were to evaluate the potential of genomic prediction for identifying superior single crosses early in the hybrid breeding pipeline and optimize its application. To accomplish these objectives, we designed and analyzed a novel population of single crosses representing the Iowa Stiff Stalk synthetic/non-Stiff Stalk heterotic pattern commonly used in the development of North American commercial maize hybrids. The performance of single crosses was predicted using parental combining ability and covariance among single crosses. Prediction accuracies were estimated using cross-validation and ranged from 0.28 to 0.77 for grain yield, 0.53 to 0.91 for plant height, and 0.49 to 0.94 for staygreen, depending on the number of tested parents of the single cross and genomic prediction method used. The genomic estimated general and specific combining abilities showed an advantage over genomic covariances among single crosses when one or both parents of the single cross were untested. Overall, our results suggest that genomic prediction of single crosses in the early stages of a hybrid breeding pipeline holds great potential to redesign hybrid breeding and increase its efficiency.
Boukar, Ousmane; Fatokun, Christian A.; Huynh, Bao-Lam; Roberts, Philip A.; Close, Timothy J.
Cowpea is one of the most important grain legumes in sub-Saharan Africa (SSA). It provides strong support to the livelihood of small-scale farmers through its contributions to their nutritional security, income generation and soil fertility enhancement. Worldwide about 6.5 million metric tons of cowpea are produced annually on about 14.5 million hectares. The low productivity of cowpea is attributable to numerous abiotic and biotic constraints. The abiotic stress factors comprise drought, low soil fertility, and heat while biotic constraints include insects, diseases, parasitic weeds, and nematodes. Cowpea farmers also have limited access to quality seeds of improved varieties for planting. Some progress has been made through conventional breeding at international and national research institutions in the last three decades. Cowpea improvement could also benefit from modern breeding methods based on molecular genetic tools. A number of advances in cowpea genetic linkage maps, and quantitative trait loci associated with some desirable traits such as resistance to Striga, Macrophomina, Fusarium wilt, bacterial blight, root-knot nematodes, aphids, and foliar thrips have been reported. An improved consensus genetic linkage map has been developed and used to identify QTLs of additional traits. In order to take advantage of these developments single nucleotide polymorphism (SNP) genotyping is being streamlined to establish an efficient workflow supported by genotyping support service (GSS)-client interactions. About 1100 SNPs mapped on the cowpea genome were converted by LGC Genomics to KASP assays. Several cowpea breeding programs have been exploiting these resources to implement molecular breeding, especially for MARS and MABC, to accelerate cowpea variety improvement. The combination of conventional breeding and molecular breeding strategies, with workflow managed through the CGIAR breeding management system (BMS), promises an increase in the number of improved
Full Text Available Cowpea is one of the most important grain legumes in sub-Saharan Africa (SSA. It provides strong support to the livelihood of small-scale farmers through its contributions to their nutritional security, income generation and soil fertility enhancement. Worldwide about 6.5 million metric tons of cowpea are produced annually on about 14.5 million hectares. The low productivity of cowpea is attributable to numerous abiotic and biotic constraints. The abiotic stress factors comprise drought, low soil fertility, and heat while biotic constraints include insects, diseases, parasitic weeds and nematodes. Cowpea farmers also have limited access to quality seeds of improved varieties for planting. Some progress has been made through conventional breeding at international and national research institutions in the last three decades. Cowpea improvement could also benefit from modern breeding methods based on molecular genetic tools. A number of advances in cowpea genetic linkage maps, and quantitative trait loci associated with some desirable traits such as resistance to Striga, Macrophomina, Fusarium wilt, bacterial blight, root-knot nematodes, aphids and foliar thrips have been reported. An improved consensus genetic linkage map has been developed and used to identify QTLs of additional traits. In order to take advantage of these developments single nucleotide polymorphism (SNP genotyping is being streamlined to establish an efficient workflow supported by genotyping support service (GSS-client interactions. About 1100 SNPs mapped on the cowpea genome were converted by LGC Genomics to KASP assays. Several cowpea breeding programs have been exploiting these resources to implement molecular breeding, especially for MARS and MABC, to accelerate cowpea variety improvement. The combination of conventional breeding and molecular breeding strategies, with workflow managed through the CGIAR breeding management system (BMS, promises an increase in the number of
Full Text Available International programs aim at developing knowledge and tools in the model species Medicago truncatula. Genetic resources, DNA sequences, markers, genetic and physical maps are now publicly available. These efforts contribute to improve breeding schemes of crop species such as alfalfa. However, transfer of information from M. truncatula to alfalfa is not straightforward. The article reviews the gain given by the model species to better analyze genetic determinism of breeding traits in alfalfa. It also shows that investments in alfalfa genomics (DNA sequences, SNP development are needed to benefit from the model species.
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.
Wang, Huihua; Zhang, Li; Cao, Jiaxve; Wu, Mingming; Ma, Xiaomeng; Liu, Zhen; Liu, Ruizao; Zhao, Fuping; Wei, Caihong; Du, Lixin
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.
Rachit K Saxena
Full Text Available Cytoplasmic genic male sterility based hybrid technology has demonstrated its immense potential in increasing the productivity of various crops, including pigeonpea. This technology has shown promise for breaking the long-standing yield stagnation in pigeonpea. There are difficulties in commercial hybrid seed production due to non-availability of field-oriented technologies such as time-bound assessment of genetic purity of hybrid seeds. Besides this, there are other routine breeding activities which are labour oriented and need more resources. These include breeding and maintenance of new fertility restorers and maintainer lines, diversification of cytoplasm, and incorporation of biotic and abiotic stress resistances. The recent progress in genomics research could accelerate the existing traditional efforts to strengthen the hybrid breeding technology. Marker based seed purity assessment, identification of heterotic groups; selection of new fertility restorers are few areas which have already been initiated. In this paper efforts have been made to identify critical areas and opportunities where genomics can play a leading role and assist breeders in accelerating various activities related to breeding and commercialization of pigeonpea hybrids.
Sue K Kim
Full Text Available Among the legume family, mungbean (Vigna radiata has become one of the important crops in Asia, showing a steady increase in global production. It provides a good source of protein and contains most notably folate and iron. Beyond the nutritional value of mungbean, certain features make it a well-suited model organism among legume plants because of its small genome size, short life-cycle, self-pollinating, and close genetic relationship to other legumes. In the past, there have been several efforts to develop molecular markers and linkage maps associated with agronomic traits for the genetic improvement of mungbean and, ultimately, breeding for cultivar development to increase the average yields of mungbean. The recent release of a reference genome of the cultivated mungbean (V. radiata var. radiata VC1973A and an additional de novo sequencing of a wild relative mungbean (V. radiata var. sublobata has provided a framework for mungbean genetic and genome research, that can further be used for genome-wide association and functional studies to identify genes related to specific agronomic traits. Moreover, the diverse gene pool of wild mungbean comprises valuable genetic resources of beneficial genes that may be helpful in widening the genetic diversity of cultivated mungbean. This review paper covers the research progress on molecular and genomics approaches and the current status of breeding programs that have developed to move toward the ultimate goal of mungbean improvement.
Estimation of genetic diversity between three Saudi sheep breeds using DNA markers. AAG Adam, NB Hamza, MAW Salim, KS Khalil. Abstract. The genetic variation of Najdi, Harri and Awassi breeds of Saudi sheep prevailing in Raniah province of Makka district were assessed and compared to Sudanese Desert sheep ...
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.
Lin, Zibei; Cogan, Noel O I; Pembleton, Luke W; Spangenberg, German C; Forster, John W; Hayes, Ben J; Daetwyler, Hans D
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.
Lopes, Marcos S; Bovenhuis, Henk; Hidalgo, André M; van Arendonk, Johan A M; Knol, Egbert F; Bastiaansen, John W M
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
Badenes, Maria L; Fernández I Martí, Angel; Ríos, Gabino; Rubio-Cabetas, María J
The recent introduction of next generation sequencing (NGS) technologies represents a major revolution in providing new tools for identifying the genes and/or genomic intervals controlling important traits for selection in breeding programs. In perennial fruit trees with long generation times and large sizes of adult plants, the impact of these techniques is even more important. High-throughput DNA sequencing technologies have provided complete annotated sequences in many important tree species. Most of the high-throughput genotyping platforms described are being used for studies of genetic diversity and population structure. Dissection of complex traits became possible through the availability of genome sequences along with phenotypic variation data, which allow to elucidate the causative genetic differences that give rise to observed phenotypic variation. Association mapping facilitates the association between genetic markers and phenotype in unstructured and complex populations, identifying molecular markers for assisted selection and breeding. Also, genomic data provide in silico identification and characterization of genes and gene families related to important traits, enabling new tools for molecular marker assisted selection in tree breeding. Deep sequencing of transcriptomes is also a powerful tool for the analysis of precise expression levels of each gene in a sample. It consists in quantifying short cDNA reads, obtained by NGS technologies, in order to compare the entire transcriptomes between genotypes and environmental conditions. The miRNAs are non-coding short RNAs involved in the regulation of different physiological processes, which can be identified by high-throughput sequencing of RNA libraries obtained by reverse transcription of purified short RNAs, and by in silico comparison with known miRNAs from other species. All together, NGS techniques and their applications have increased the resources for plant breeding in tree species, closing the
Bassi, Filippo M; Bentley, Alison R; Charmet, Gilles; Ortiz, Rodomiro; Crossa, Jose
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.
Li, Chun-Hong; Shi, Wei; Shi, Wan-Yu
The Egyptian swift Rock Pigeon is a breed of fancy pigeon developed over many years of selective breeding. In this work, we report the complete mitochondrial genome sequence of Egyptian swift Rock Pigeon. The total length of the mitogenome was 17,239 bp and its overall base composition was estimated to be 30.2% for A, 24.0% for T, 31.9% for C and 13.9% for G, indicating an A-T (54.2%)-rich feature in the mitogenome. It contained the typical structure of 13 protein-coding genes, 2 ribosomal RNA genes, 22 transfer RNA genes and a non-coding control region (D-loop region). The complete mitochondrial genome sequence of Egyptian swift Rock Pigeon would serve as an important data set of the germplasm resources for further study.
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
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.
Elliot L. Heffner
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.
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...
Brascamp, E.W.; Bijma, P.
Background Efficient methodologies based on animal models are widely used to estimate breeding values in farm animals. These methods are not applicable in honey bees because of their mode of reproduction. Observations are recorded on colonies, which consist of a single queen and thousands of workers
Xu, Yao; Jiang, Yu; Shi, Tao; Cai, Hanfang; Lan, Xianyong; Zhao, Xin; Plath, Martin; Chen, Hong
Whole-genome sequencing provides a powerful tool to obtain more genetic variability that could produce a range of benefits for cattle breeding industry. Nanyang (Bos indicus) and Qinchuan (Bos taurus) are two important Chinese indigenous cattle breeds with distinct phenotypes. To identify the genetic characteristics responsible for variation in phenotypes between the two breeds, in the present study, we for the first time sequenced the genomes of four Nanyang and four Qinchuan cattle with 10 ...
Bouwman, Aniek C.; Hayes, Ben J.; Calus, Mario P.L.
Background: Genomic evaluation is used to predict direct genomic values (DGV) for selection candidates in breeding programs, but also to estimate allele substitution effects (ASE) of single nucleotide polymorphisms (SNPs). Scaling of allele counts influences the estimated ASE, because scaling of
Kadlec, J.A.; Drury, W.H.
Counts on photographs and visual estimates of the numbers of territorial gulls are usually reliable indicators of the number of gull nests, but single visual estimates are not adequate to measure the number of nests in individual colonies. To properly interpret gull counts requires that several islands with known numbers of nests be photographed to establish the ratio of gulls to nests applicable for a given local census. Visual estimates are adequate to determine total breeding gull numbers by regions. Neither visual estimates nor photography will reliably detect annual changes of less than about 2.5 percent.
Heidi G. Parker
Full Text Available There are nearly 400 modern domestic dog breeds with a unique histories and genetic profiles. To track the genetic signatures of breed development, we have assembled the most diverse dataset of dog breeds, reflecting their extensive phenotypic variation and heritage. Combining genetic distance, migration, and genome-wide haplotype sharing analyses, we uncover geographic patterns of development and independent origins of common traits. Our analyses reveal the hybrid history of breeds and elucidate the effects of immigration, revealing for the first time a suggestion of New World dog within some modern breeds. Finally, we used cladistics and haplotype sharing to show that some common traits have arisen more than once in the history of the dog. These analyses characterize the complexities of breed development, resolving longstanding questions regarding individual breed origination, the effect of migration on geographically distinct breeds, and, by inference, transfer of trait and disease alleles among dog breeds.
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.
Grenier, Cécile; Cao, Tuong-Vi; Ospina, Yolima; Quintero, Constanza; Châtel, Marc Henri; Tohme, Joe; Courtois, Brigitte; Ahmadi, Nourollah
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.
Adriana L. Somavilla
Full Text Available Nelore is the most economically important cattle breed in Brazil, and the use of genetically improved animals has contributed to increased beef production efficiency. The Brazilian beef feedlot industry has grown considerably in the last decade, so the selection of animals with higher growth rates on feedlot has become quite important. Genomic selection (GS could be used to reduce generation intervals and improve the rate of genetic gains. The aim of this study was to evaluate the prediction of genomic-estimated breeding values (GEBV for average daily weight gain (ADG in 718 feedlot-finished Nelore steers. Analyses of three Bayesian model specifications [Bayesian GBLUP (BGBLUP, BayesA, and BayesCπ] were performed with four genotype panels [Illumina BovineHD BeadChip, TagSNPs, and GeneSeek High- and Low-density indicus (HDi and LDi, respectively]. Estimates of Pearson correlations, regression coefficients, and mean squared errors were used to assess accuracy and bias of predictions. Overall, the BayesCπ model resulted in less biased predictions. Accuracies ranged from 0.18 to 0.27, which are reasonable values given the heritability estimates (from 0.40 to 0.44 and sample size (568 animals in the training population. Furthermore, results from Bos taurus indicus panels were as informative as those from Illumina BovineHD, indicating that they could be used to implement GS at lower costs.
Xiong, Jin-Song; Ding, Jing; Li, Yi
Plant breeding, one of the oldest agricultural activities, parallels human civilization. Many crops have been domesticated to satisfy human's food and aesthetical needs, including numerous specialty horticultural crops such as fruits, vegetables, ornamental flowers, shrubs, and trees. Crop varieties originated through selection during early human civilization. Other technologies, such as various forms of hybridization, mutation, and transgenics, have also been invented and applied to crop breeding over the past centuries. The progress made in these breeding technologies, especially the modern biotechnology-based breeding technologies, has had a great impact on crop breeding as well as on our lives. Here, we first review the developmental process and applications of these technologies in horticultural crop breeding. Then, we mainly describe the principles of the latest genome-editing technologies and discuss their potential applications in the genetic improvement of horticultural crops. The advantages and challenges of genome-editing technologies in horticultural crop breeding are also discussed. PMID:26504570
Full Text Available Abstract Background Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction. Methods Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values. Results Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied. Conclusions These results suggest that genomic estimates
Saatchi, Mahdi; McClure, Mathew C; McKay, Stephanie D; Rolf, Megan M; Kim, JaeWoo; Decker, Jared E; Taxis, Tasia M; Chapple, Richard H; Ramey, Holly R; Northcutt, Sally L; Bauck, Stewart; Woodward, Brent; Dekkers, Jack C M; Fernando, Rohan L; Schnabel, Robert D; Garrick, Dorian J; Taylor, Jeremy F
Genomic selection is a recently developed technology that is beginning to revolutionize animal breeding. The objective of this study was to estimate marker effects to derive prediction equations for direct genomic values for 16 routinely recorded traits of American Angus beef cattle and quantify corresponding accuracies of prediction. Deregressed estimated breeding values were used as observations in a weighted analysis to derive direct genomic values for 3570 sires genotyped using the Illumina BovineSNP50 BeadChip. These bulls were clustered into five groups using K-means clustering on pedigree estimates of additive genetic relationships between animals, with the aim of increasing within-group and decreasing between-group relationships. All five combinations of four groups were used for model training, with cross-validation performed in the group not used in training. Bivariate animal models were used for each trait to estimate the genetic correlation between deregressed estimated breeding values and direct genomic values. Accuracies of direct genomic values ranged from 0.22 to 0.69 for the studied traits, with an average of 0.44. Predictions were more accurate when animals within the validation group were more closely related to animals in the training set. When training and validation sets were formed by random allocation, the accuracies of direct genomic values ranged from 0.38 to 0.85, with an average of 0.65, reflecting the greater relationship between animals in training and validation. The accuracies of direct genomic values obtained from training on older animals and validating in younger animals were intermediate to the accuracies obtained from K-means clustering and random clustering for most traits. The genetic correlation between deregressed estimated breeding values and direct genomic values ranged from 0.15 to 0.80 for the traits studied. These results suggest that genomic estimates of genetic merit can be produced in beef cattle at a young age but
Azevedo Peixoto, Leonardo de; Laviola, Bruno Galvêas; Alves, Alexandre Alonso; Rosado, Tatiana Barbosa; Bhering, Leonardo Lopes
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.
Full Text Available Prediction accuracies of estimated breeding values for economically important traits are expected to benefit from genomic information. Single nucleotide polymorphism (SNP panels used in genomic prediction are increasing in density, but the Markov Chain Monte Carlo (MCMC estimation of SNP effects can be quite time consuming or slow to converge when a large number of SNPs are fitted simultaneously in a linear mixed model. Here we present an EM algorithm (termed "fastBayesA" without MCMC. This fastBayesA approach treats the variances of SNP effects as missing data and uses a joint posterior mode of effects compared to the commonly used BayesA which bases predictions on posterior means of effects. In each EM iteration, SNP effects are predicted as a linear combination of best linear unbiased predictions of breeding values from a mixed linear animal model that incorporates a weighted marker-based realized relationship matrix. Method fastBayesA converges after a few iterations to a joint posterior mode of SNP effects under the BayesA model. When applied to simulated quantitative traits with a range of genetic architectures, fastBayesA is shown to predict GEBV as accurately as BayesA but with less computing effort per SNP than BayesA. Method fastBayesA can be used as a computationally efficient substitute for BayesA, especially when an increasing number of markers bring unreasonable computational burden or slow convergence to MCMC approaches.
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.
Jannink, Jean-Luc; Lorenz, Aaron J; Iwata, Hiroyoshi
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.
Dreger, Dayna L.; Rimbault, Maud; Davis, Brian W.; Bhatnagar, Adrienne; Parker, Heidi G.
ABSTRACT In the decade following publication of the draft genome sequence of the domestic dog, extraordinary advances with application to several fields have been credited to the canine genetic system. Taking advantage of closed breeding populations and the subsequent selection for aesthetic and behavioral characteristics, researchers have leveraged the dog as an effective natural model for the study of complex traits, such as disease susceptibility, behavior and morphology, generating unique contributions to human health and biology. When designing genetic studies using purebred dogs, it is essential to consider the unique demography of each population, including estimation of effective population size and timing of population bottlenecks. The analytical design approach for genome-wide association studies (GWAS) and analysis of whole-genome sequence (WGS) experiments are inextricable from demographic data. We have performed a comprehensive study of genomic homozygosity, using high-depth WGS data for 90 individuals, and Illumina HD SNP data from 800 individuals representing 80 breeds. These data were coupled with extensive pedigree data analyses for 11 breeds that, together, allowed us to compute breed structure, demography, and molecular measures of genome diversity. Our comparative analyses characterize the extent, formation and implication of breed-specific diversity as it relates to population structure. These data demonstrate the relationship between breed-specific genome dynamics and population architecture, and provide important considerations influencing the technological and cohort design of association and other genomic studies. PMID:27874836
Elferink, Martin G.; Megens, Hendrik-Jan; Vereijken, Addie; Hu, Xiaoxiang; Crooijmans, Richard P. M. A.; Groenen, Martien A. M.
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
Northcutt Sally L
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.
Williams, K.A.; Frederick, P.C.; Nichols, J.D.
Many populations of animals are fluid in both space and time, making estimation of numbers difficult. Much attention has been devoted to estimation of bias in detection of animals that are present at the time of survey. However, an equally important problem is estimation of population size when all animals are not present on all survey occasions. Here, we showcase use of the superpopulation approach to capture-recapture modeling for estimating populations where group membership is asynchronous, and where considerable overlap in group membership among sampling occasions may occur. We estimate total population size of long-legged wading bird (Great Egret and White Ibis) breeding colonies from aerial observations of individually identifiable nests at various times in the nesting season. Initiation and termination of nests were analogous to entry and departure from a population. Estimates using the superpopulation approach were 47-382% larger than peak aerial counts of the same colonies. Our results indicate that the use of the superpopulation approach to model nesting asynchrony provides a considerably less biased and more efficient estimate of nesting activity than traditional methods. We suggest that this approach may also be used to derive population estimates in a variety of situations where group membership is fluid. ?? 2011 by the Ecological Society of America.
This is because the SNPs on BovineSNP50 and GGP-80K assays were ascertained as being common in European taurine breeds. Lower MAF and SNP informativeness observed in this study limits the application of these assays in breed assignment, and could have other implications for genome-wide studies in South ...
Full Text Available Abstract Background Genomic selection is an effective tool for animal and plant breeding, allowing effective individual selection without phenotypic records through the prediction of genomic breeding value (GBV. To date, genomic selection has focused on a single trait. However, actual breeding often targets multiple correlated traits, and, therefore, joint analysis taking into consideration the correlation between traits, which might result in more accurate GBV prediction than analyzing each trait separately, is suitable for multi-trait genomic selection. This would require an extension of the prediction model for single-trait GBV to multi-trait case. As the computational burden of multi-trait analysis is even higher than that of single-trait analysis, an effective computational method for constructing a multi-trait prediction model is also needed. Results We described a Bayesian regression model incorporating variable selection for jointly predicting GBVs of multiple traits and devised both an MCMC iteration and variational approximation for Bayesian estimation of parameters in this multi-trait model. The proposed Bayesian procedures with MCMC iteration and variational approximation were referred to as MCBayes and varBayes, respectively. Using simulated datasets of SNP genotypes and phenotypes for three traits with high and low heritabilities, we compared the accuracy in predicting GBVs between multi-trait and single-trait analyses as well as between MCBayes and varBayes. The results showed that, compared to single-trait analysis, multi-trait analysis enabled much more accurate GBV prediction for low-heritability traits correlated with high-heritability traits, by utilizing the correlation structure between traits, while the prediction accuracy for uncorrelated low-heritability traits was comparable or less with multi-trait analysis in comparison with single-trait analysis depending on the setting for prior probability that a SNP has zero
Morton, Richard; Howarth, Jordan M
Fish bred in tanks or ponds cannot be easily tagged individually. The parentage of any individual may be determined by DNA fingerprinting, but is sufficiently expensive that large numbers cannot be so finger-printed. The measurement of the objective trait can be made on a much larger sample relatively cheaply. This article deals with experimental designs for selecting individuals to be finger-printed and for the estimation of the individual and family breeding values. The general setup provides estimates for both genetic effects regarded as fixed or random and for fixed effects due to known regressors. The family effects can be well estimated when even very small numbers are finger-printed, provided that they are the individuals with the most extreme phenotypes.
Lin, Zibei; Shi, Fan; Hayes, Ben J; Daetwyler, Hans D
Heuristic genomic inbreeding controls reduce inbreeding in genomic breeding schemes without reducing genetic gain. Genomic selection is increasingly being implemented in plant breeding programs to accelerate genetic gain of economically important traits. However, it may cause significant loss of genetic diversity when compared with traditional schemes using phenotypic selection. We propose heuristic strategies to control the rate of inbreeding in outbred plants, which can be categorised into three types: controls during mate allocation, during selection, and simultaneous selection and mate allocation. The proposed mate allocation measure GminF allocates two or more parents for mating in mating groups that minimise coancestry using a genomic relationship matrix. Two types of relationship-adjusted genomic breeding values for parent selection candidates ([Formula: see text]) and potential offspring ([Formula: see text]) are devised to control inbreeding during selection and even enabling simultaneous selection and mate allocation. These strategies were tested in a case study using a simulated perennial ryegrass breeding scheme. As compared to the genomic selection scheme without controls, all proposed strategies could significantly decrease inbreeding while achieving comparable genetic gain. In particular, the scenario using [Formula: see text] in simultaneous selection and mate allocation reduced inbreeding to one-third of the original genomic selection scheme. The proposed strategies are readily applicable in any outbred plant breeding program.
Marcio P. Arruda
Full Text Available Genomic selection (GS is a breeding method that uses marker–trait models to predict unobserved phenotypes. This study developed GS models for predicting traits associated with resistance to head blight (FHB in wheat ( L.. We used genotyping-by-sequencing (GBS to identify 5054 single-nucleotide polymorphisms (SNPs, which were then treated as predictor variables in GS analysis. We compared how the prediction accuracy of the genomic-estimated breeding values (GEBVs was affected by (i five genotypic imputation methods (random forest imputation [RFI], expectation maximization imputation [EMI], -nearest neighbor imputation [kNNI], singular value decomposition imputation [SVDI], and the mean imputation [MNI]; (ii three statistical models (ridge-regression best linear unbiased predictor [RR-BLUP], least absolute shrinkage and operator selector [LASSO], and elastic net; (iii marker density ( = 500, 1500, 3000, and 4500 SNPs; (iv training population (TP size ( = 96, 144, 192, and 218; (v marker-based and pedigree-based relationship matrices; and (vi control for relatedness in TPs and validation populations (VPs. No discernable differences in prediction accuracy were observed among imputation methods. The RR-BLUP outperformed other models in nearly all scenarios. Accuracies decreased substantially when marker number decreased to 3000 or 1500 SNPs, depending on the trait; when sample size of the training set was less than 192; when using pedigree-based instead of marker-based matrix; or when no control for relatedness was implemented. Overall, moderate to high prediction accuracies were observed in this study, suggesting that GS is a very promising breeding strategy for FHB resistance in wheat.
Schiavo, G; Galimberti, G; Calò, D G; Samorè, A B; Bertolini, F; Russo, V; Gallo, M; Buttazzoni, L; Fontanesi, L
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.
Thomasen, Jørn Rind; Sørensen, Anders Christian
A simulation study was performed for testing the effect of using reproductive technologies in a genomic dairy cattle young bull breeding scheme. The breeding scheme parameters: 1) number of donors, 2) number of progeny per donor, 3) age of the donor, 4) number of sires, and 5) reliability...... of genomic breeding values. The breeding schemes were evaluated according to genetic gain and rate of inbreeding. The relative gain by use of reproductive technologies is 11 to 84 percent points depending on the choice of other breeding scheme parameters. A large donor program with high selection intensity...... of sires provides the highest genetic gain. A relatively higher genetic gain is obtained for higher reliability of GEBV. Extending the donor program and number of selected bulls has a major effect of reducing the rate of inbreeding without compromising genetic gain....
Vincze, Éva; Bowra, Steve
) is the ‘umbrella' term used to describe a suite of tools now being applied to plant breeding. In the context of genomic-assisted breeding, we will briefly discuss in the second section of this chapter the molecular genetic-based tools underpinning GAB (understanding gene expression, candidate gene selection......In the struggle to achieve global food security, crop breeding retains an important role in crop production. A current trend is the diversification of the aims of crop production, to include an increased awareness of aspects and consequences of food quality. The added emphasis on food and feed...... quality made crop breeding more challenging and required a combination of new tools. We illustrate these concepts by taking examples from barley, one of the most ancient of domesticated grains with a diverse profile of utilisation (feed, brewing, new nutritional uses). Genomic-assisted breeding (GAB...
Hudson, Nicholas J; Porto-Neto, Laercio; Kijas, James W; Reverter, Antonio
Genetic relatedness is currently estimated by a combination of traditional pedigree-based approaches (i.e. numerator relationship matrices, NRM) and, given the recent availability of molecular information, using marker genotypes (via genomic relationship matrices, GRM). To date, GRM are computed by genome-wide pair-wise SNP (single nucleotide polymorphism) correlations. We describe a new estimate of genetic relatedness using the concept of normalised compression distance (NCD) that is borrowed from Information Theory. Analogous to GRM, the resultant compression relationship matrix (CRM) exploits numerical patterns in genome-wide allele order and proportion, which are known to vary systematically with relatedness. We explored properties of the CRM in two industry cattle datasets by analysing the genetic basis of yearling weight, a phenotype of moderate heritability. In both Brahman (Bos indicus) and Tropical Composite (Bos taurus by Bos indicus) populations, the clustering inferred by NCD was comparable to that based on SNP correlations using standard principal component analysis approaches. One of the versions of the CRM modestly increased the amount of explained genetic variance, slightly reduced the 'missing heritability' and tended to improve the prediction accuracy of breeding values in both populations when compared to both NRM and GRM. Finally, a sliding window-based application of the compression approach on these populations identified genomic regions influenced by introgression of taurine haplotypes. For these two bovine populations, CRM reduced the missing heritability and increased the amount of explained genetic variation for a moderately heritable complex trait. Given that NCD can sensitively discriminate closely related individuals, we foresee CRM having possible value for estimating breeding values in highly inbred populations.
Hickey, John M.; Chiurugwi, Tinashe; Mackay, Ian
The rate of annual yield increases for major staple crops must more than double relative to current levels in order to feed a predicted global population of 9 billion by 2050. Controlled hybridization and selective breeding have been used for centuries to adapt plant and animal species for human...... that unifies breeding approaches, biological discovery, and tools and methods. Here we compare and contrast some animal and plant breeding approaches to make a case for bringing the two together through the application of genomic selection. We propose a strategy for the use of genomic selection as a unifying...... use. However, achieving higher, sustainable rates of improvement in yields in various species will require renewed genetic interventions and dramatic improvement of agricultural practices. Genomic prediction of breeding values has the potential to improve selection, reduce costs and provide a platform...
Hickey, John M; Chiurugwi, Tinashe; Mackay, Ian; Powell, Wayne
The rate of annual yield increases for major staple crops must more than double relative to current levels in order to feed a predicted global population of 9 billion by 2050. Controlled hybridization and selective breeding have been used for centuries to adapt plant and animal species for human use. However, achieving higher, sustainable rates of improvement in yields in various species will require renewed genetic interventions and dramatic improvement of agricultural practices. Genomic prediction of breeding values has the potential to improve selection, reduce costs and provide a platform that unifies breeding approaches, biological discovery, and tools and methods. Here we compare and contrast some animal and plant breeding approaches to make a case for bringing the two together through the application of genomic selection. We propose a strategy for the use of genomic selection as a unifying approach to deliver innovative 'step changes' in the rate of genetic gain at scale.
Camilla Garcia Moreira
Full Text Available ABSTRACT: The equations available in the literature to estimate the body weight (BW of Pêga breed donkeys were evaluated using 25 animals aged 0-6 months and it was proposed an equation for BW prediction. For the measurement of the thoracic perimeter (TP and for weighing the animals using the weighing tape, the animals were positioned in a forced station on a steep slope. An electronic scale was used for the determination of the BW. Accuracy of linear and nonlinear equations described in the literature was tested for BW prediction based on the animals’ TP, followed by the comparison of these equations with the equation developed in the present study for BW prediction of Pêga breed donkeys. A difference was noted (P<0.001 between the weights obtained on the electronic scale and the weighing tape. Linear and nonlinear equations available in the literature did not present favorable results with the data of the present study. The equation developed for the estimation of donkeys’ BW allowed the development of a weighing tape exclusive for young animals. Further evaluations are required for other Pêga donkey populations to confirm the efficacy of the proposed equation.
Los Campos, De G.; Hickey, J.M.; Pong-Wong, R.; Daetwyler, H.D.; Calus, M.P.L.
Genomic-enabled prediction is becoming increasingly important in animal and plant breeding, and is also receiving attention in human genetics. Deriving accurate predictions of complex traits requires implementing whole-genome regression (WGR) models where phenotypes are regressed on thousands of
Filipe Inácio Matias
Full Text Available Be-Breeder is an application directed toward genetic breeding of plants, developed through the Shiny package of the R software, which allows different phenotype and molecular (marker analysis to be undertaken. The section for analysis of molecular data of the Be-Breeder application makes it possible to achieve quality control of genotyping data, to obtain genomic kinship matrices, and to analyze genomic selection, genome association, and genetic diversity in a simple manner on line. This application is available for use in a network through the site of the Allogamous Plant Breeding Laboratory of ESALQ-USP (http://www.genetica.esalq.usp.br/alogamas/R.html.
Two methods to efficiently approximate theoretical genomic reliabilities are presented. The first method is based on the direct inverse of the left hand side (LHS) of mixed model equations. It uses the genomic relationship matrix for a small subset of individuals with the highest genomic relationshi...
Matias,Filipe Inácio; Granato,Italo Stefanine Correa; Dequigiovanni,Gabriel; Fritsche-Neto,Roberto
Abstract Be-Breeder is an application directed toward genetic breeding of plants, developed through the Shiny package of the R software, which allows different phenotype and molecular (marker) analysis to be undertaken. The section for analysis of molecular data of the Be-Breeder application makes it possible to achieve quality control of genotyping data, to obtain genomic kinship matrices, and to analyze genome selection, genome association, and genetic diversity in a simple manner on line. ...
Full Text Available Pigeonpea is an important pulse crop grown predominantly in the tropical and sub-tropical regions of the world. Although pigeonpea growing area has considerably increased, yield has remained stagnant for the last six decades mainly due to the exposure of the crop to various biotic and abiotic constraints. In addition, low level of genetic variability and limited genomic resources have been serious impediments to pigeonpea crop improvement through modern breeding approaches. In recent years, however, due to the availability of next generation sequencing and high-throughput genotyping technologies, the scenario has changed tremendously. The reduced sequencing costs resulting in the decoding of the pigeonpea genome has led to the development of various genomic resources including molecular markers, transcript sequences and comprehensive genetic maps. Mapping of some important traits including resistance to Fusarium wilt and sterility mosaic disease, fertility restoration, determinacy with other agronomically important traits have paved the way for applying genomics-assisted breeding (GAB through marker assisted selection as well as genomic selection. This would lead to accelerate the development and improvement of both varieties and hybrids in pigeonpea. Particularly for hybrid breeding programme, mitochondrial genomes of cytoplasmic male sterile lines, maintainers and hybrids have also been sequenced to identify genes responsible for cytoplasmic male sterility. Furthermore, several diagnostic molecular markers have been developed to assess the purity of commercial hybrids. In summary, pigeonpea has become a genomic resources-rich crop and efforts have already been initiated to integrate these resources in pigeonpea breeding.
Forage quality depends on the digestibility of fodder, and can be directly measured by the intake and metabolic conversion in animal trials. However, animal trials are time-consuming, laborious, and thus expensive. It is not possible to study thousands of plant genotypes, as required in breeding...... studied in detail and sequence motifs with likely effect on forage quality have been identified by association studies. Moreover, transgenic approaches substantiated the effect of several of these genes on forage quality. Perspectives and limitations of these findings for forage crop breeding...
Anik Budhi Dharmayanthi
Full Text Available Like Chinese Silkie, Indonesian Ayam Cemani exhibits fibromelanosis or dermal hyperpigmentation and possesses complex segmental duplications on chromosome 20 that involve the endothelin 3 gene, EDN3. A genomic region, DR1 of 127 kb, together with another region, DR2 of 171 kb, was duplicated by unequal crossing over, accompanied by inversion of one DR2. Quantitative PCR and copy number variation analyses on the Cemani genome sequence confirmed the duplication of EDN3. These genetic arrangements are identical in Cemani and Silkie, indicating a single origin of the genetic cause of Fm. The two DR1s harbor two distinct EDN3 haplotypes in a form of permanent heterozygosity, although they remain allelic in the ancestral Red Jungle Fowl population and some domesticated chicken breeds, with their allelic divergence time being as recent as 0.3 million years ago. In Cemani and Silkie breeds, artificial selection favoring the Fm phenotype has left an unambiguous record for selective sweep that extends in both directions from tandemly duplicated EDN3 loci. This highly homozygous tract is different in length between Cemani and Silkie, reflecting their distinct breeding histories. It is estimated that the Fm phenotype came into existence at least 6600-9100 years ago, prior to domestication of Cemani and Silkie, and that throughout domestication there has been intense artificial selection with strength s > 50% in each breed.
Pandey, Manish K.; Roorkiwal, Manish; Singh, Vikas K.; Ramalingam, Abirami; Kudapa, Himabindu; Thudi, Mahendar; Chitikineni, Anu; Rathore, Abhishek; Varshney, Rajeev K.
Legumes play a vital role in ensuring global nutritional food security and improving soil quality through nitrogen fixation. Accelerated higher genetic gains is required to meet the demand of ever increasing global population. In recent years, speedy developments have been witnessed in legume genomics due to advancements in next-generation sequencing (NGS) and high-throughput genotyping technologies. Reference genome sequences for many legume crops have been reported in the last 5 years. The availability of the draft genome sequences and re-sequencing of elite genotypes for several important legume crops have made it possible to identify structural variations at large scale. Availability of large-scale genomic resources and low-cost and high-throughput genotyping technologies are enhancing the efficiency and resolution of genetic mapping and marker-trait association studies. Most importantly, deployment of molecular breeding approaches has resulted in development of improved lines in some legume crops such as chickpea and groundnut. In order to support genomics-driven crop improvement at a fast pace, the deployment of breeder-friendly genomics and decision support tools seems appear to be critical in breeding programs in developing countries. This review provides an overview of emerging genomics and informatics tools/approaches that will be the key driving force for accelerating genomics-assisted breeding and ultimately ensuring nutritional and food security in developing countries. PMID:27199998
Bauchet, Guillaume; Grenier, Stéphane; Samson, Nicolas; Bonnet, Julien; Grivet, Laurent; Causse, Mathilde
A panel of 300 tomato accessions including breeding materials was built and characterized with >11,000 SNP. A population structure in six subgroups was identified. Strong heterogeneity in linkage disequilibrium and recombination landscape among groups and chromosomes was shown. GWAS identified several associations for fruit weight, earliness and plant growth. Genome-wide association studies (GWAS) have become a method of choice in quantitative trait dissection. First limited to highly polymorphic and outcrossing species, it is now applied in horticultural crops, notably in tomato. Until now GWAS in tomato has been performed on panels of heirloom and wild accessions. Using modern breeding materials would be of direct interest for breeding purpose. To implement GWAS on a large panel of 300 tomato accessions including 168 breeding lines, this study assessed the genetic diversity and linkage disequilibrium decay and revealed the population structure and performed GWA experiment. Genetic diversity and population structure analyses were based on molecular markers (>11,000 SNP) covering the whole genome. Six genetic subgroups were revealed and associated to traits of agronomical interest, such as fruit weight and disease resistance. Estimates of linkage disequilibrium highlighted the heterogeneity of its decay among genetic subgroups. Haplotype definition allowed a fine characterization of the groups and their recombination landscape revealing the patterns of admixture along the genome. Selection footprints showed results in congruence with introgressions. Taken together, all these elements refined our knowledge of the genetic material included in this panel and allowed the identification of several associations for fruit weight, plant growth and earliness, deciphering the genetic architecture of these complex traits and identifying several new loci useful for tomato breeding.
Zhang, Rui-Hua; He, Wen-Xiao; Xu, Tong
The king pigeon is a breed of pigeon developed over many years of selective breeding primarily as a utility breed. In the present work, we report the complete mitochondrial genome sequence of king pigeon for the first time. The total length of the mitogenome was 17,221 bp with the base composition of 30.14% for A, 24.05% for T, 31.82% for C, and 13.99% for G and an A-T (54.22 %)-rich feature was detected. It harbored 13 protein-coding genes, two ribosomal RNA genes, 22 transfer RNA genes, and one non-coding control region (D-loop region). The arrangement of all genes was identical to the typical mitochondrial genomes of pigeon. The complete mitochondrial genome sequence of king pigeon would serve as an important data set of the germplasm resources for further study.
An understanding of the structures and characteristics of the chloroplast, mitochondrial, and nuclear genomes have played significant roles in the genetic improvement of Allium crops. In this chapter I reflect upon the practical use of this genomic information for genetic improvement of the Alliums....
Shariati, Mohammad M; Sørensen, Peter; Janss, Luc
In genomic models that assign an individual variance to each marker, the contribution of one marker to the posterior distribution of the marker variance is only one degree of freedom (df), which introduces many variance parameters with only little information per variance parameter. A better alternative could be to form clusters of markers with similar effects where markers in a cluster have a common variance. Therefore, the influence of each marker group of size p on the posterior distribution of the marker variances will be p df. The simulated data from the 15th QTL-MAS workshop were analyzed such that SNP markers were ranked based on their effects and markers with similar estimated effects were grouped together. In step 1, all markers with minor allele frequency more than 0.01 were included in a SNP-BLUP prediction model. In step 2, markers were ranked based on their estimated variance on the trait in step 1 and each 150 markers were assigned to one group with a common variance. In further analyses, subsets of 1500 and 450 markers with largest effects in step 2 were kept in the prediction model. Grouping markers outperformed SNP-BLUP model in terms of accuracy of predicted breeding values. However, the accuracies of predicted breeding values were lower than Bayesian methods with marker specific variances. Grouping markers is less flexible than allowing each marker to have a specific marker variance but, by grouping, the power to estimate marker variances increases. A prior knowledge of the genetic architecture of the trait is necessary for clustering markers and appropriate prior parameterization.
Sahana, Goutam; Guldbrandtsen, Bernt; Lund, Mogens Sandø
Genome-wide association study was carried out in Nordic Holsteins, Nordic Red and Jersey breeds for functional traits using BovineHD Genotyping BreadChip (Illumina, San Diego, CA). The association analyses were carried out using both linear mixed model approach and a Bayesian variable selection...... method. Principal components were used to account for population structure. The QTL segregating in all three breeds were selected and a few of the most significant ones were followed in further analyses. The polymorphisms in the identified QTL regions were imputed using 90 whole genome sequences...
Talukder, Shyamal K.; Saha, Malay C.
Most important food and feed crops in the world belong to the C3 grass family. The future of food security is highly reliant on achieving genetic gains of those grasses. Conventional breeding methods have already reached a plateau for improving major crops. Genomics tools and resources have opened an avenue to explore genome-wide variability and make use of the variation for enhancing genetic gains in breeding programs. Major C3 annual cereal breeding programs are well equipped with genomic tools; however, genomic research of C3 cool-season perennial grasses is lagging behind. In this review, we discuss the currently available genomics tools and approaches useful for C3 cool-season perennial grass breeding. Along with a general review, we emphasize the discussion focusing on forage grasses that were considered orphan and have little or no genetic information available. Transcriptome sequencing and genotype-by-sequencing technology for genome-wide marker detection using next-generation sequencing (NGS) are very promising as genomics tools. Most C3 cool-season perennial grass members have no prior genetic information; thus NGS technology will enhance collinear study with other C3 model grasses like Brachypodium and rice. Transcriptomics data can be used for identification of functional genes and molecular markers, i.e., polymorphism markers and simple sequence repeats (SSRs). Genome-wide association study with NGS-based markers will facilitate marker identification for marker-assisted selection. With limited genetic information, genomic selection holds great promise to breeders for attaining maximum genetic gain of the cool-season C3 perennial grasses. Application of all these tools can ensure better genetic gains, reduce length of selection cycles, and facilitate cultivar development to meet the future demand for food and fodder. PMID:28798766
Shyamal K. Talukder
Full Text Available Most important food and feed crops in the world belong to the C3 grass family. The future of food security is highly reliant on achieving genetic gains of those grasses. Conventional breeding methods have already reached a plateau for improving major crops. Genomics tools and resources have opened an avenue to explore genome-wide variability and make use of the variation for enhancing genetic gains in breeding programs. Major C3 annual cereal breeding programs are well equipped with genomic tools; however, genomic research of C3 cool-season perennial grasses is lagging behind. In this review, we discuss the currently available genomics tools and approaches useful for C3 cool-season perennial grass breeding. Along with a general review, we emphasize the discussion focusing on forage grasses that were considered orphan and have little or no genetic information available. Transcriptome sequencing and genotype-by-sequencing technology for genome-wide marker detection using next-generation sequencing (NGS are very promising as genomics tools. Most C3 cool-season perennial grass members have no prior genetic information; thus NGS technology will enhance collinear study with other C3 model grasses like Brachypodium and rice. Transcriptomics data can be used for identification of functional genes and molecular markers, i.e., polymorphism markers and simple sequence repeats (SSRs. Genome-wide association study with NGS-based markers will facilitate marker identification for marker-assisted selection. With limited genetic information, genomic selection holds great promise to breeders for attaining maximum genetic gain of the cool-season C3 perennial grasses. Application of all these tools can ensure better genetic gains, reduce length of selection cycles, and facilitate cultivar development to meet the future demand for food and fodder.
Ibanez-Escriche, N.; Gonzalez-Recio, O.
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.
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.
Rius-Vilarrasa, E; Strandberg, E; Fikse, W F
Using a combined multi-breed reference population, this study explored the influence of model specification and the effect of including a polygenic effect on the reliability of genomic breeding values (DGV and GEBV). The combined reference population consisted of 2986 Swedish Red Breed (SRB) and ...
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.
Nielsen, Nanna Hellum; Jahoor, Ahmed; Jensen, Jens Due; Orabi, Jihad; Cericola, Fabio; Edriss, Vahid; Jensen, Just
Genomic selection was recently introduced in plant breeding. The objective of this study was to develop genomic prediction for important seed quality parameters in spring barley. The aim was to predict breeding values without expensive phenotyping of large sets of lines. A total number of 309 advanced spring barley lines tested at two locations each with three replicates were phenotyped and each line was genotyped by Illumina iSelect 9Kbarley chip. The population originated from two different breeding sets, which were phenotyped in two different years. Phenotypic measurements considered were: seed size, protein content, protein yield, test weight and ergosterol content. A leave-one-out cross-validation strategy revealed high prediction accuracies ranging between 0.40 and 0.83. Prediction across breeding sets resulted in reduced accuracies compared to the leave-one-out strategy. Furthermore, predicting across full and half-sib-families resulted in reduced prediction accuracies. Additionally, predictions were performed using reduced marker sets and reduced training population sets. In conclusion, using less than 200 lines in the training set can result in low prediction accuracy, and the accuracy will then be highly dependent on the family structure of the selected training set. However, the results also indicate that relatively small training sets (200 lines) are sufficient for genomic prediction in commercial barley breeding. In addition, our results indicate a minimum marker set of 1,000 to decrease the risk of low prediction accuracy for some traits or some families. PMID:27783639
Nanna Hellum Nielsen
Full Text Available Genomic selection was recently introduced in plant breeding. The objective of this study was to develop genomic prediction for important seed quality parameters in spring barley. The aim was to predict breeding values without expensive phenotyping of large sets of lines. A total number of 309 advanced spring barley lines tested at two locations each with three replicates were phenotyped and each line was genotyped by Illumina iSelect 9Kbarley chip. The population originated from two different breeding sets, which were phenotyped in two different years. Phenotypic measurements considered were: seed size, protein content, protein yield, test weight and ergosterol content. A leave-one-out cross-validation strategy revealed high prediction accuracies ranging between 0.40 and 0.83. Prediction across breeding sets resulted in reduced accuracies compared to the leave-one-out strategy. Furthermore, predicting across full and half-sib-families resulted in reduced prediction accuracies. Additionally, predictions were performed using reduced marker sets and reduced training population sets. In conclusion, using less than 200 lines in the training set can result in low prediction accuracy, and the accuracy will then be highly dependent on the family structure of the selected training set. However, the results also indicate that relatively small training sets (200 lines are sufficient for genomic prediction in commercial barley breeding. In addition, our results indicate a minimum marker set of 1,000 to decrease the risk of low prediction accuracy for some traits or some families.
Desalegn Debelo Serba
Full Text Available Pearl millet (Penisetum glaucum (L R. Br. is a hardy cereal crop grown in the arid and semiarid tropics where other cereals are likely to fail to produce economic yields due to drought and heat stresses. Adaptive evolution, a form of natural selection shaped the crop to grow and yield satisfactorily with limited moisture supply or under periodic water deficits in the soil. Drought tolerance is a complex polygenic trait that various morphological and physiological responses are controlled by hundreds of genes and significantly influenced by the environment. The development of genomic tools will have enormous potential to improve the efficiency and precision of conventional breeding. The apparent independent domestication events, highly outcrossing nature and traditional cultivation in stressful environments maintained tremendous amount of polymorphism in pearl millet. This high polymorphism of the crop has been revealed by genome mapping that in turn stimulated the mapping and tagging of genomic regions controlling important traits such as drought tolerance. Mapping of a major QTL for terminal drought tolerance in independent populations envisaged the prospect for the development of molecular breeding in pearl millet. To accelerate genetic gains for drought tolerance targeted novel approaches such as establishment of marker-trait associations, genomic selection tools, genome sequence and genotyping-by-sequencing are still limited. Development and application of high throughput genomic tools need to be intensified to improve the breeding efficiency of pearl millet to minimize the impact of climate change on its production.
Lipka, Alexander E.; Lu, Fei; Cherney, Jerome H.; Buckler, Edward S.; Casler, Michael D.; Costich, Denise E.
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
Dayaram, Anisha; Piasecki, Tomasz; Chrząstek, Klaudia; White, Robyn; Julian, Laurel; van Bysterveldt, Katherine; Varsani, Arvind
Eight genomes of avian polyomaviruses (APVs) were recovered and sequenced from deceased Psittacula eupatria, Psittacula krameri, and Melopsittacus undulatus from various breeding facilities in Poland. Of these APV-positive samples, six had previously tested positive for beak and feather disease virus (BFDV) and/or parrot hepatitis B virus (PHBV). Copyright © 2015 Dayaram et al.
Dayaram, Anisha; Piasecki, Tomasz; Chrząstek, Klaudia; White, Robyn; Julian, Laurel; van Bysterveldt, Katherine; Varsani, Arvind
Eight genomes of avian polyomaviruses (APVs) were recovered and sequenced from deceased Psittacula eupatria, Psittacula krameri, and Melopsittacus undulatus from various breeding facilities in Poland. Of these APV-positive samples, six had previously tested positive for beak and feather disease virus (BFDV) and/or parrot hepatitis B virus (PHBV).
Heuvel, van den T.
Innovative developments in technology, such as the emergence of genomics as a plant breeding practice, hold the potential to change the supply side of the market. The success of these practices not only depends on the improved efficiency and effectiveness it brings, but also on how well they are
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.
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
Oct 14, 2015 ... The cluster analysis shows that Najdi breed is genetically different from both Harri and Awassi and .... Genetic distance value of 0.0 reflects very high similarity between ..... The State of the Worlds Animal Genetic Resources for.
de los Campos, Gustavo; Hickey, John M.; Pong-Wong, Ricardo; Daetwyler, Hans D.; Calus, Mario P. L.
Genomic-enabled prediction is becoming increasingly important in animal and plant breeding and is also receiving attention in human genetics. Deriving accurate predictions of complex traits requires implementing whole-genome regression (WGR) models where phenotypes are regressed on thousands of markers concurrently. Methods exist that allow implementing these large-p with small-n regressions, and genome-enabled selection (GS) is being implemented in several plant and animal breeding programs. The list of available methods is long, and the relationships between them have not been fully addressed. In this article we provide an overview of available methods for implementing parametric WGR models, discuss selected topics that emerge in applications, and present a general discussion of lessons learned from simulation and empirical data analysis in the last decade. PMID:22745228
Zhang, Rui-Hua; He, Wen-Xiao
The ice pigeon is a breed of fancy pigeon developed over many years of selective breeding. In the present work, we report the complete mitochondrial genome sequence of ice pigeon for the first time. The total length of the mitogenome was 17,236 bp with the base composition of 30.2% for A, 24.0% for T, 31.9% for C, and 13.9% for G and an A-T (54.2 %)-rich feature was detected. It harbored 13 protein-coding genes, 2 ribosomal RNA genes, 22 transfer RNA genes and 1 non-coding control region (D-loop region). The arrangement of all genes was identical to the typical mitochondrial genomes of pigeon. The complete mitochondrial genome sequence of ice pigeon would serve as an important data set of the germplasm resources for further study.
He, Wen-Xiao; Jia, Jin-Feng
The Jacobin is a breed of fancy pigeon developed over many years of selective breeding that originated in Asia. In the present work, we report the complete mitochondrial genome sequence of Jacobin pigeon for the first time. The total length of the mitogenome was 17,245 bp with the base composition of 30.18% for A, 23.98% for T, 31.88% for C, and 13.96% for G and an A-T (54.17 %)-rich feature was detected. It harbored 13 protein-coding genes, 2 ribosomal RNA genes, 22 transfer RNA genes and 1 non-coding control region. The arrangement of all genes was identical to the typical mitochondrial genomes of pigeon. The complete mitochondrial genome sequence of Jacobin pigeon would serve as an important data set of the germplasm resources for further study.
Stothard, Paul; Chung, Won-Hyong; Jeon, Heoyn-Jeong; Miller, Stephen P.; Choi, So-Young; Lee, Jeong-Koo; Yang, Bokyoung; Lee, Kyung-Tai; Han, Kwang-Jin; Kim, Hyeong-Cheol; Jeong, Dongkee; Oh, Jae-Don; Kim, Namshin; Kim, Tae-Hun; Lee, Hak-Kyo; Lee, Sung-Jin
A main goal of cattle genomics is to identify DNA differences that account for variations in economically important traits. In this study, we performed whole-genome analyses of three important cattle breeds in Korea—Hanwoo, Jeju Heugu, and Korean Holstein—using the Illumina HiSeq 2000 sequencing platform. We achieved 25.5-, 29.6-, and 29.5-fold coverage of the Hanwoo, Jeju Heugu, and Korean Holstein genomes, respectively, and identified a total of 10.4 million single nucleotide polymorphisms (SNPs), of which 54.12% were found to be novel. We also detected 1,063,267 insertions–deletions (InDels) across the genomes (78.92% novel). Annotations of the datasets identified a total of 31,503 nonsynonymous SNPs and 859 frameshift InDels that could affect phenotypic variations in traits of interest. Furthermore, genome-wide copy number variation regions (CNVRs) were detected by comparing the Hanwoo, Jeju Heugu, and previously published Chikso genomes against that of Korean Holstein. A total of 992, 284, and 1881 CNVRs, respectively, were detected throughout the genome. Moreover, 53, 65, 45, and 82 putative regions of homozygosity (ROH) were identified in Hanwoo, Jeju Heugu, Chikso, and Korean Holstein respectively. The results of this study provide a valuable foundation for further investigations to dissect the molecular mechanisms underlying variation in economically important traits in cattle and to develop genetic markers for use in cattle breeding. PMID:24992012
Peter S. Kristensen
Full Text Available The aim of the this study was to identify SNP markers associated with five important wheat quality traits (grain protein content, Zeleny sedimentation, test weight, thousand-kernel weight, and falling number, and to investigate the predictive abilities of GBLUP and Bayesian Power Lasso models for genomic prediction of these traits. In total, 635 winter wheat lines from two breeding cycles in the Danish plant breeding company Nordic Seed A/S were phenotyped for the quality traits and genotyped for 10,802 SNPs. GWAS were performed using single marker regression and Bayesian Power Lasso models. SNPs with large effects on Zeleny sedimentation were found on chromosome 1B, 1D, and 5D. However, GWAS failed to identify single SNPs with significant effects on the other traits, indicating that these traits were controlled by many QTL with small effects. The predictive abilities of the models for genomic prediction were studied using different cross-validation strategies. Leave-One-Out cross-validations resulted in correlations between observed phenotypes corrected for fixed effects and genomic estimated breeding values of 0.50 for grain protein content, 0.66 for thousand-kernel weight, 0.70 for falling number, 0.71 for test weight, and 0.79 for Zeleny sedimentation. Alternative cross-validations showed that the genetic relationship between lines in training and validation sets had a bigger impact on predictive abilities than the number of lines included in the training set. Using Bayesian Power Lasso instead of GBLUP models, gave similar or slightly higher predictive abilities. Genomic prediction based on all SNPs was more effective than prediction based on few associated SNPs.
James W Kijas
Full Text Available The genetic structure of sheep reflects their domestication and subsequent formation into discrete breeds. Understanding genetic structure is essential for achieving genetic improvement through genome-wide association studies, genomic selection and the dissection of quantitative traits. After identifying the first genome-wide set of SNP for sheep, we report on levels of genetic variability both within and between a diverse sample of ovine populations. Then, using cluster analysis and the partitioning of genetic variation, we demonstrate sheep are characterised by weak phylogeographic structure, overlapping genetic similarity and generally low differentiation which is consistent with their short evolutionary history. The degree of population substructure was, however, sufficient to cluster individuals based on geographic origin and known breed history. Specifically, African and Asian populations clustered separately from breeds of European origin sampled from Australia, New Zealand, Europe and North America. Furthermore, we demonstrate the presence of stratification within some, but not all, ovine breeds. The results emphasize that careful documentation of genetic structure will be an essential prerequisite when mapping the genetic basis of complex traits. Furthermore, the identification of a subset of SNP able to assign individuals into broad groupings demonstrates even a small panel of markers may be suitable for applications such as traceability.
Eriksson, S; Jonas, E; Rydhmer, L; Röcklinsberg, H
The hot topic of genetic modification and genome editing is sometimes presented as a rapid solution to various problems in the field of animal breeding and genetics. These technologies hold potential for future use in agriculture but we need to be aware of difficulties in large-scale application and integration in breeding schemes. In this review, we discuss applications of both classical genetic modifications (GM) using vectors and genome editing in dairy cattle breeding. We use an interdisciplinary approach considering both ethical and animal breeding perspectives. Decisions on how to make use of these techniques need to be made based not only on what is possible, but on what is reasonable to do. Principles of animal integrity, naturalness, risk perception, and animal welfare issues are examples of ethically relevant factors to consider. These factors also influence public perception and decisions about regulations by authorities. We need to acknowledge that we lack complete understanding of the genetic background of complex traits. It may be difficult, therefore, to predict the full effect of certain modifications in large-scale breeding programs. We present 2 potential applications: genome editing to dispense with dehorning, and insertion of human genes in bovine genomes to improve udder health as an example of classical GM. Both of these cases could be seen as beneficial for animal welfare but they differ in other aspects. In the former case, a genetic variant already present within the species is introduced, whereas in the latter case, transgenic animals are generated-this difference may influence how society regards the applications. We underline that the use of GM, as well as genome editing, of farm animals such as cattle is not independent of the context, and should be considered as part of an entire process, including, for example, the assisted reproduction technology that needs to be used. We propose that breeding organizations and breeding companies
Full Text Available Rice is one of the major cereal food crops whose production has to be doubled to achieve the projected demand  and current yield trends are not sufficient to meet the projected growth in production. Increasing the rice production by 30% during 2030 needs overcoming challenges viz., yield plateau, declining land, water and labor resources and predicted effects of global climate change. Development of high performance rice genotypes with enhanced yield potential and resilience to climate change will help in sustained increase in rice production. Deployment of genomic technologies can accelerate development and delivery of improved germplasm with enhanced resilience and adaptability [2, 3]. In this context, the present study was undertaken with an aim of developing rice genotypes pyramided with QTLs/genes controlling tolerance against various biotic and abiotic stresses viz., bacterial leaf blight (xa13, Xa21, blast (Pi9, Gall midge (Gm4, drought (qDTY1.1 qDTY2.1, submergence (Sub1 and salinity (Saltol. CBMAS14065 an elite culture harboring QTLs controlling tolerance against drought, salinity and submergence was crossed with a donor harboring BLB, Blast and Gall midge resistant genes. True F1s were backcrossed with CBMAS14065 and BC1F1 progenies were subjected to foreground selection using markers linked to the target traits. Superior plants (18 of BC1F1 generation were subjected to background selection which revealed 71.42 - 86.90% recurrent parent (CBMAS14065 genome recovery. Selected BC1F1 plants were advanced to BC2F1 generation backcrossing with CBMAS14065. In BC2F1 generation, through foreground selection 6-8 QTL/gene positive plants have been selected and advanced for further evaluation. The superior lines with desired QTLs/genes will be subjected to rigorous phenotypic evaluation against target stresses and advanced further.
Bernal-Vasquez, Angela-Maria; Gordillo, Andres; Schmidt, Malthe; Piepho, Hans-Peter
The use of multiple genetic backgrounds across years is appealing for genomic prediction (GP) because past years' data provide valuable information on marker effects. Nonetheless, single-year GP models are less complex and computationally less demanding than multi-year GP models. In devising a suitable analysis strategy for multi-year data, we may exploit the fact that even if there is no replication of genotypes across years, there is plenty of replication at the level of marker loci. Our principal aim was to evaluate different GP approaches to simultaneously model genotype-by-year (GY) effects and breeding values using multi-year data in terms of predictive ability. The models were evaluated under different scenarios reflecting common practice in plant breeding programs, such as different degrees of relatedness between training and validation sets, and using a selected fraction of genotypes in the training set. We used empirical grain yield data of a rye hybrid breeding program. A detailed description of the prediction approaches highlighting the use of kinship for modeling GY is presented. Using the kinship to model GY was advantageous in particular for datasets disconnected across years. On average, predictive abilities were 5% higher for models using kinship to model GY over models without kinship. We confirmed that using data from multiple selection stages provides valuable GY information and helps increasing predictive ability. This increase is on average 30% higher when the predicted genotypes are closely related with the genotypes in the training set. A selection of top-yielding genotypes together with the use of kinship to model GY improves the predictive ability in datasets composed of single years of several selection cycles. Our results clearly demonstrate that the use of multi-year data and appropriate modeling is beneficial for GP because it allows dissecting GY effects from genomic estimated breeding values. The model choice, as well as ensuring
Jensen, Per; Andersson, Leif
Animal behavior is a central part of animal welfare, a keystone in sustainable animal breeding. During domestication, animals have adapted with respect to behavior and an array of other traits. We compared the behavior of junglefowl and White Leghorn layers, selected for egg production (and indirectly for growth). Jungle-fowl had a more active behavior in social, exploratory, anti-predatory, and feeding tests. A genome scan for Quantitative Trait Loci (QTLs) in a junglefowl x White Leghorn intercross revealed several significant or suggestive QTLs for different traits. Some production QTLs coincided with QTLs for behavior, suggesting that pleiotropic effects may be important for the development of domestication phenotypes. One gene has been located, which has a strong effect on the risk of being a victim of feather pecking, a detrimental behavior disorder. Modern genomics paired with analysis of behavior may help in designing more sustainable and robust breeding in the future.
Thomasen, Jørn Rind; Sørensen, Anders Christian; Lund, Mogens Sandø
We hypothesized that adding cows to the reference population in a breed with a small number of reference bulls would increase reliabilities of genomic breeding values and genetic gain. We tested this premise by comparing two strategies for maintaining the reference population for genetic gain......, inbreeding and reliabilities of genomic predictions: 1) Adding 60 progeny tested bulls each year (B), and 2) in addition to 60 progeny tested bulls, adding 2,000 genotyped cows per year (C). Two breeding schemes were tested: 1) A turbo scheme (T) with only genotyped young bulls used intensively, and 2...... compared to the H-B, at the same level of ∆F. T-C yielded 15% higher ∆G compared t o T-B. Changing the breeding scheme from H-B to H-C increased ∆G by 5.5%. The lowest ∆F was observed with genotyping of cows. Reliabilities of GEBV in the C schemes showed a steep increase in reliability during the first...
Full Text Available The implementation of genomic selection (GS in plant breeding, so far, has been mainly evaluated in crops farmed as homogeneous varieties, and the results have been generally positive. Fewer results are available for species, such as forage grasses, that are grown as heterogenous families (developed from multiparent crosses in which the control of the genetic variation is far more complex. Here we test the potential for implementing GS in the breeding of perennial ryegrass ( L. using empirical data from a commercial forage breeding program. Biparental F and multiparental synthetic (SYN families of diploid perennial ryegrass were genotyped using genotyping-by-sequencing, and phenotypes for five different traits were analyzed. Genotypes were expressed as family allele frequencies, and phenotypes were recorded as family means. Different models for genomic prediction were compared by using practically relevant cross-validation strategies. All traits showed a highly significant level of genetic variance, which could be traced using the genotyping assay. While there was significant genotype × environment (G × E interaction for some traits, accuracies were high among F families and between biparental F and multiparental SYN families. We have demonstrated that the implementation of GS in grass breeding is now possible and presents an opportunity to make significant gains for various traits.
O'Hagan, Steve; Knowles, Joshua; Kell, Douglas B.
Comparatively few studies have addressed directly the question of quantifying the benefits to be had from using molecular genetic markers in experimental breeding programmes (e.g. for improved crops and livestock), nor the question of which organisms should be mated with each other to best effect. We argue that this requires in silico modelling, an approach for which there is a large literature in the field of evolutionary computation (EC), but which has not really been applied in this way to experimental breeding programmes. EC seeks to optimise measurable outcomes (phenotypic fitnesses) by optimising in silico the mutation, recombination and selection regimes that are used. We review some of the approaches from EC, and compare experimentally, using a biologically relevant in silico landscape, some algorithms that have knowledge of where they are in the (genotypic) search space (G-algorithms) with some (albeit well-tuned ones) that do not (F-algorithms). For the present kinds of landscapes, F- and G-algorithms were broadly comparable in quality and effectiveness, although we recognise that the G-algorithms were not equipped with any ‘prior knowledge’ of epistatic pathway interactions. This use of algorithms based on machine learning has important implications for the optimisation of experimental breeding programmes in the post-genomic era when we shall potentially have access to the full genome sequence of every organism in a breeding population. The non-proprietary code that we have used is made freely available (via Supplementary information). PMID:23185279
Auinger, Hans-Jürgen; Schönleben, Manfred; Lehermeier, Christina; Schmidt, Malthe; Korzun, Viktor; Geiger, Hartwig H; Piepho, Hans-Peter; Gordillo, Andres; Wilde, Peer; Bauer, Eva; Schön, Chris-Carolin
Genomic prediction accuracy can be significantly increased by model calibration across multiple breeding cycles as long as selection cycles are connected by common ancestors. In hybrid rye breeding, application of genome-based prediction is expected to increase selection gain because of long selection cycles in population improvement and development of hybrid components. Essentially two prediction scenarios arise: (1) prediction of the genetic value of lines from the same breeding cycle in which model training is performed and (2) prediction of lines from subsequent cycles. It is the latter from which a reduction in cycle length and consequently the strongest impact on selection gain is expected. We empirically investigated genome-based prediction of grain yield, plant height and thousand kernel weight within and across four selection cycles of a hybrid rye breeding program. Prediction performance was assessed using genomic and pedigree-based best linear unbiased prediction (GBLUP and PBLUP). A total of 1040 S 2 lines were genotyped with 16 k SNPs and each year testcrosses of 260 S 2 lines were phenotyped in seven or eight locations. The performance gap between GBLUP and PBLUP increased significantly for all traits when model calibration was performed on aggregated data from several cycles. Prediction accuracies obtained from cross-validation were in the order of 0.70 for all traits when data from all cycles (N CS = 832) were used for model training and exceeded within-cycle accuracies in all cases. As long as selection cycles are connected by a sufficient number of common ancestors and prediction accuracy has not reached a plateau when increasing sample size, aggregating data from several preceding cycles is recommended for predicting genetic values in subsequent cycles despite decreasing relatedness over time.
Hickey, John M; Chiurugwi, Tinashe; Mackay, Ian; Powell, Wayne; Implementing Genomic Selection in CGIAR Breeding Programs Workshop Participants
The rate of annual yield increases for major staple crops must more than double relative to current levels in order to feed a predicted global population of 9 billion by 2050. Controlled hybridization and selective breeding have been used for centuries to adapt plant and animal species for human use. However, achieving higher, sustainable rates of improvement in yields in various species will require renewed genetic interventions and dramatic improvement of agricultural practices. Genomic pre...
Cabrera-Bosquet, Llorenç; Crossa, José; von Zitzewitz, Jarislav; Serret, María Dolors; Araus, José Luis
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.
Hill, William G
Although animal breeding was practiced long before the science of genetics and the relevant disciplines of population and quantitative genetics were known, breeding programs have mainly relied on simply selecting and mating the best individuals on their own or relatives' performance. This is based on sound quantitative genetic principles, developed and expounded by Lush, who attributed much of his understanding to Wright, and formalized in Fisher's infinitesimal model. Analysis at the level of individual loci and gene frequency distributions has had relatively little impact. Now with access to genomic data, a revolution in which molecular information is being used to enhance response with "genomic selection" is occurring. The predictions of breeding value still utilize multiple loci throughout the genome and, indeed, are largely compatible with additive and specifically infinitesimal model assumptions. I discuss some of the history and genetic issues as applied to the science of livestock improvement, which has had and continues to have major spin-offs into ideas and applications in other areas.
Full Text Available This review is an overview of traditional and modern breeding methodologies being used to develop new Prunus cultivars (stone fruits with major emphasis on peach, sweet cherry and Japanese plum. To this end, common breeding tools used to produce seedlings, including in vitro culture tools, are discussed. Additionally, the mechanisms of inheritance of many important agronomical traits are described. Recent advances in stone fruit transcriptomics and genomic resources are providing an understanding of the molecular basis of phenotypic variability as well as the identification of allelic variants and molecular markers. These have potential applications for understanding the genetic diversity of the Prunus species, molecular marker-assisted selection and transgenesis. Simple Sequence Repeat (SSR and Single Nucleotide Polymorphism (SNPs molecular markers are described as useful tools to describe genetic diversity in peach, sweet cherry and Japanese plum. Additionally, the recently sequenced peach genome and the public release of the sweet cherry genome are discussed in terms of their applicability to breeding programs
Mathewson, Heather A.; Groce, Julie E.; Mcfarland, Tiffany M.; Morrison, Michael L.; Newnam, J. Cal; Snelgrove, R. Todd; Collier, Bret A.; Wilkins, R. Neal
relied on localized population studies on public lands and qualitative-based methods. Our goal was to estimate breeding population size of male warblers using a predictive model based on metrics for patches of woodland habitat throughout the species
Advancing the production efficiency and profitability of aquaculture is dependent upon the ability to utilize a diverse array of genetic resources. The ultimate goals of aquaculture genomics, genetics and breeding research are to enhance aquaculture production efficiency, sustainability, product qua...
Maurice - Van Eijndhoven, M.H.T.; Bovenhuis, H.; Veerkamp, R.F.; Calus, M.P.L.
The aim of this study was to identify if genomic variations associated with fatty acid (FA) composition are similar between the Holstein-Friesian (HF) and native dual-purpose breeds used in the Dutch dairy industry. Phenotypic and genotypic information were available for the breeds Meuse-Rhine-Yssel
Reiner-Benaim, A; Ezra, E; Weller, J I
Although it now standard practice to genotype thousands of female calves, genotyping of bull calves is generally limited to progeny of elite cows. In addition to genotyping costs, increasing the pool of candidate sires requires purchase, isolation, and identification of calves until selection decisions are made. We economically optimized via simulation a genomic breeding program for a population of approximately 120,000 milk-recorded cows, corresponding to the Israeli Holstein population. All 30,000 heifers and 60,000 older cows of parities 1 to 3 were potential bull dams. Animals were assumed to have genetic evaluations for a trait with heritability of 0.25 derived by an animal model evaluation of the population. Only bull calves were assumed to be genotyped. A pseudo-phenotype corresponding to each animal's genetic evaluation was generated, consisting of the animal's genetic value plus a residual with variance set to obtain the assumed reliability for each group of animals. Between 4 and 15 bulls and between 200 and 27,000 cows with the highest pseudo-phenotypes were selected as candidate bull parents. For all progeny of the founder animals, genetic values were simulated as the mean of the parental values plus a Mendelian sampling effect with variance of 0.5. A probability of 0.3 for a healthy bull calf per mating, and a genomic reliability of 0.43 were assumed. The 40 bull calves with the highest genomic evaluations were selected for general service for 1 yr. Costs included genotyping of candidate bulls and their dams, purchase of the calves from the farmers, and identification. Costs of raising culled calves were partially recovered by resale for beef. Annual costs were estimated as $10,922 + $305 × candidate bulls. Nominal profit per cow per genetic standard deviation was $106. Economic optimum with a discount rate of 5%, first returns after 4 yr, and a profit horizon of 15 yr were obtained with genotyping 1,620 to 1,750 calves for all numbers of bull sires
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.
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
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.
Álvarez-Borrego, Josué; Gallardo-Escárate, Crisitian; Kober, Vitaly; López-Bonilla, Oscar
Recently, within the cytogenetic analysis, the evolutionary relations implied in the content of nuclear DNA in plants and animals have received a great attention. The first detailed measurements of the nuclear DNA content were made in the early 40's, several years before Watson and Crick proposed the molecular structure of the DNA. In the following years Hewson Swift developed the concept of "C-value" in reference to the haploid phase of DNA in plants. Later Mirsky and Ris carried out the first systematic study of genomic size in animals, including representatives of the five super classes of vertebrates as well as of some invertebrates. From these preliminary results it became evident that the DNA content varies enormously between the species and that this variation does not bear relation to the intuitive notion from the complexity of the organism. Later, this observation was reaffirmed in the following years as the studies increased on genomic size, thus denominating to this characteristic of the organisms like the "Paradox of the C-value". Few years later along with the no-codification discovery of DNA the paradox was solved, nevertheless, numerous questions remain until nowadays unfinished, taking to denominate this type of studies like the "C-value enigma". In this study, we reported a new method for genome size estimation by quantification of fluorescence fading. We measured the fluorescence intensity each 1600 milliseconds in DAPI-stained nuclei. The estimation of the area under the graph (integral fading) during fading period was related with the genome size.
Full Text Available Recent studies have found that copy number variations (CNVs are widespread in human and animal genomes. CNVs are a significant source of genetic variation, and have been shown to be associated with phenotypic diversity. However, the effect of CNVs on genetic variation in horses is not well understood. In the present study, CNVs in 6 different breeds of mare horses, Mongolia horse, Abaga horse, Hequ horse and Kazakh horse (all plateau breeds and Debao pony and Thoroughbred, were determined using aCGH. In total, seven hundred CNVs were identified ranging in size from 6.1 Kb to 0.57 Mb across all autosomes, with an average size of 43.08 Kb and a median size of 15.11 Kb. By merging overlapping CNVs, we found a total of three hundred and fifty-three CNV regions (CNVRs. The length of the CNVRs ranged from 6.1 Kb to 1.45 Mb with average and median sizes of 38.49 Kb and 13.1 Kb. Collectively, 13.59 Mb of copy number variation was identified among the horses investigated and accounted for approximately 0.61% of the horse genome sequence. Five hundred and eighteen annotated genes were affected by CNVs, which corresponded to about 2.26% of all horse genes. Through the gene ontology (GO, genetic pathway analysis and comparison of CNV genes among different breeds, we found evidence that CNVs involving 7 genes may be related to the adaptation to severe environment of these plateau horses. This study is the first report of copy number variations in Chinese horses, which indicates that CNVs are ubiquitous in the horse genome and influence many biological processes of the horse. These results will be helpful not only in mapping the horse whole-genome CNVs, but also to further research for the adaption to the high altitude severe environment for plateau horses.
Full Text Available Climate change affects agricultural productivity worldwide. Increased prices of food commodities are the initial indication of drastic edible yield loss, which is expected to surge further due to global warming. This situation has compelled plant scientists to develop climate change-resilient crops, which can withstand broad-spectrum stresses such as drought, heat, cold, salinity, flood and submergence, and pests along with increased productivity. Genomics appears to be a promising tool for deciphering the stress responsiveness of crop species with adaptation traits or in wild relatives towards identifying underlying genes, alleles or quantitative trait loci. Molecular breeding approaches have been proven helpful in enhancing the stress adaptation of crop plants, and recent advancement in next-generation sequencing along with high-throughput sequencing and phenotyping platforms have transformed molecular breeding to genomics-assisted breeding (GAB. In view of this, the present review elaborates the progress and prospects of GAB in improving climate change resilience in crop plants towards circumventing global food insecurity.
Fang, Lingzhao; Sahana, Goutam; Ma, Peipei; Su, Guosheng; Yu, Ying; Zhang, Shengli; Lund, Mogens Sandø; Sørensen, Peter
A better understanding of the genetic architecture underlying complex traits (e.g., the distribution of causal variants and their effects) may aid in the genomic prediction. Here, we hypothesized that the genomic variants of complex traits might be enriched in a subset of genomic regions defined by genes grouped on the basis of "Gene Ontology" (GO), and that incorporating this independent biological information into genomic prediction models might improve their predictive ability. Four complex traits (i.e., milk, fat and protein yields, and mastitis) together with imputed sequence variants in Holstein (HOL) and Jersey (JER) cattle were analysed. We first carried out a post-GWAS analysis in a HOL training population to assess the degree of enrichment of the association signals in the gene regions defined by each GO term. We then extended the genomic best linear unbiased prediction model (GBLUP) to a genomic feature BLUP (GFBLUP) model, including an additional genomic effect quantifying the joint effect of a group of variants located in a genomic feature. The GBLUP model using a single random effect assumes that all genomic variants contribute to the genomic relationship equally, whereas GFBLUP attributes different weights to the individual genomic relationships in the prediction equation based on the estimated genomic parameters. Our results demonstrate that the immune-relevant GO terms were more associated with mastitis than milk production, and several biologically meaningful GO terms improved the prediction accuracy with GFBLUP for the four traits, as compared with GBLUP. The improvement of the genomic prediction between breeds (the average increase across the four traits was 0.161) was more apparent than that it was within the HOL (the average increase across the four traits was 0.020). Our genomic feature modelling approaches provide a framework to simultaneously explore the genetic architecture and genomic prediction of complex traits by taking advantage of
Full Text Available Whole-genome sequencing provides a powerful tool to obtain more genetic variability that could produce a range of benefits for cattle breeding industry. Nanyang (Bos indicus and Qinchuan (Bos taurus are two important Chinese indigenous cattle breeds with distinct phenotypes. To identify the genetic characteristics responsible for variation in phenotypes between the two breeds, in the present study, we for the first time sequenced the genomes of four Nanyang and four Qinchuan cattle with 10 to 12 fold on average of 97.86% and 98.98% coverage of genomes, respectively. Comparison with the Bos_taurus_UMD_3.1 reference assembly yielded 9,010,096 SNPs for Nanyang, and 6,965,062 for Qinchuan cattle, 51% and 29% of which were novel SNPs, respectively. A total of 154,934 and 115,032 small indels (1 to 3 bp were found in the Nanyang and Qinchuan genomes, respectively. The SNP and indel distribution revealed that Nanyang showed a genetically high diversity as compared to Qinchuan cattle. Furthermore, a total of 2,907 putative cases of copy number variation (CNV were identified by aligning Nanyang to Qinchuan genome, 783 of which (27% encompassed the coding regions of 495 functional genes. The gene ontology (GO analysis revealed that many CNV genes were enriched in the immune system and environment adaptability. Among several CNV genes related to lipid transport and fat metabolism, Lepin receptor gene (LEPR overlapping with CNV_1815 showed remarkably higher copy number in Qinchuan than Nanyang (log2 (ratio = -2.34988; P value = 1.53E-102. Further qPCR and association analysis investigated that the copy number of the LEPR gene presented positive correlations with transcriptional expression and phenotypic traits, suggesting the LEPR CNV may contribute to the higher fat deposition in muscles of Qinchuan cattle. Our findings provide evidence that the distinct phenotypes of Nanyang and Qinchuan breeds may be due to the different genetic variations including SNPs
Nirea Kahsay G
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
The Cool Season Food Legume Genome database (CSFL, www.coolseasonfoodlegume.org) is an online resource for genomics, genetics, and breeding research for chickpea, lentil,pea, and faba bean. The user-friendly and curated website allows for all publicly available map,marker,trait, gene,transcript, ger...
Mdladla, K; Dzomba, E F; Huson, H J; Muchadeyi, F C
The sustainability of goat farming in marginal areas of southern Africa depends on local breeds that are adapted to specific agro-ecological conditions. Unimproved non-descript goats are the main genetic resources used for the development of commercial meat-type breeds of South Africa. Little is known about genetic diversity and the genetics of adaptation of these indigenous goat populations. This study investigated the genetic diversity, population structure and breed relations, linkage disequilibrium, effective population size and persistence of gametic phase in goat populations of South Africa. Three locally developed meat-type breeds of the Boer (n = 33), Savanna (n = 31), Kalahari Red (n = 40), a feral breed of Tankwa (n = 25) and unimproved non-descript village ecotypes (n = 110) from four goat-producing provinces of the Eastern Cape, KwaZulu-Natal, Limpopo and North West were assessed using the Illumina Goat 50K SNP Bead Chip assay. The proportion of SNPs with minor allele frequencies >0.05 ranged from 84.22% in the Tankwa to 97.58% in the Xhosa ecotype, with a mean of 0.32 ± 0.13 across populations. Principal components analysis, admixture and pairwise FST identified Tankwa as a genetically distinct population and supported clustering of the populations according to their historical origins. Genome-wide FST identified 101 markers potentially under positive selection in the Tankwa. Average linkage disequilibrium was highest in the Tankwa (r(2) = 0.25 ± 0.26) and lowest in the village ecotypes (r(2) range = 0.09 ± 0.12 to 0.11 ± 0.14). We observed an effective population size of 100 kb with the exception of those in Savanna and Tswana populations. This study highlights the high level of genetic diversity in South African indigenous goats as well as the utility of the genome-wide SNP marker panels in genetic studies of these populations. © 2016 Stichting International Foundation for Animal Genetics.
Full Text Available The domestication of Asian rice (Oryza sativa was a complex process punctuated by episodes of introgressive hybridization among and between subpopulations. Deep genetic divergence between the two main varietal groups (Indica and Japonica suggests domestication from at least two distinct wild populations. However, genetic uniformity surrounding key domestication genes across divergent subpopulations suggests cultural exchange of genetic material among ancient farmers.In this study, we utilize a novel 1,536 SNP panel genotyped across 395 diverse accessions of O. sativa to study genome-wide patterns of polymorphism, to characterize population structure, and to infer the introgression history of domesticated Asian rice. Our population structure analyses support the existence of five major subpopulations (indica, aus, tropical japonica, temperate japonica and GroupV consistent with previous analyses. Our introgression analysis shows that most accessions exhibit some degree of admixture, with many individuals within a population sharing the same introgressed segment due to artificial selection. Admixture mapping and association analysis of amylose content and grain length illustrate the potential for dissecting the genetic basis of complex traits in domesticated plant populations.Genes in these regions control a myriad of traits including plant stature, blast resistance, and amylose content. These analyses highlight the power of population genomics in agricultural systems to identify functionally important regions of the genome and to decipher the role of human-directed breeding in refashioning the genomes of a domesticated species.
Doekes, Harmen P; Veerkamp, Roel F; Bijma, Piter; Hiemstra, Sipke J; Windig, Jack J
In recent decades, Holstein-Friesian (HF) selection schemes have undergone profound changes, including the introduction of optimal contribution selection (OCS; around 2000), a major shift in breeding goal composition (around 2000) and the implementation of genomic selection (GS; around 2010). These changes are expected to have influenced genetic diversity trends. Our aim was to evaluate genome-wide and region-specific diversity in HF artificial insemination (AI) bulls in the Dutch-Flemish breeding program from 1986 to 2015. Pedigree and genotype data (~ 75.5 k) of 6280 AI-bulls were used to estimate rates of genome-wide inbreeding and kinship and corresponding effective population sizes. Region-specific inbreeding trends were evaluated using regions of homozygosity (ROH). Changes in observed allele frequencies were compared to those expected under pure drift to identify putative regions under selection. We also investigated the direction of changes in allele frequency over time. Effective population size estimates for the 1986-2015 period ranged from 69 to 102. Two major breakpoints were observed in genome-wide inbreeding and kinship trends. Around 2000, inbreeding and kinship levels temporarily dropped. From 2010 onwards, they steeply increased, with pedigree-based, ROH-based and marker-based inbreeding rates as high as 1.8, 2.1 and 2.8% per generation, respectively. Accumulation of inbreeding varied substantially across the genome. A considerable fraction of markers showed changes in allele frequency that were greater than expected under pure drift. Putative selected regions harboured many quantitative trait loci (QTL) associated to a wide range of traits. In consecutive 5-year periods, allele frequencies changed more often in the same direction than in opposite directions, except when comparing the 1996-2000 and 2001-2005 periods. Genome-wide and region-specific diversity trends reflect major changes in the Dutch-Flemish HF breeding program. Introduction of
Shirasawa, Kenta; Isobe, Sachiko; Tabata, Satoshi; Hirakawa, Hideki
In order to provide useful genomic information for agronomical plants, we have established a database, the Kazusa Marker DataBase (http://marker.kazusa.or.jp). This database includes information on DNA markers, e.g., SSR and SNP markers, genetic linkage maps, and physical maps, that were developed at the Kazusa DNA Research Institute. Keyword searches for the markers, sequence data used for marker development, and experimental conditions are also available through this database. Currently, 10 plant species have been targeted: tomato (Solanum lycopersicum), pepper (Capsicum annuum), strawberry (Fragaria × ananassa), radish (Raphanus sativus), Lotus japonicus, soybean (Glycine max), peanut (Arachis hypogaea), red clover (Trifolium pratense), white clover (Trifolium repens), and eucalyptus (Eucalyptus camaldulensis). In addition, the number of plant species registered in this database will be increased as our research progresses. The Kazusa Marker DataBase will be a useful tool for both basic and applied sciences, such as genomics, genetics, and molecular breeding in crops. PMID:25320561
Full Text Available The paper purpose was to apply a simplified mixed model BLUP for estimating bulls' breeding value for meat production in terms of weight daily gain and establish their hierarchy, Also, it aimed to compare the bulls' ranging obtained by a simplified BLUP mixed model with their hierarchy set up by contemporary comparison. A sample of 1,705 half sibs steers, offspring of 106 Friesian bulls were used as biological material. Bulls' breeding value varied between + 244.5 g for the best bull and -204.7 g for the bull with the weakest records. A number of 57 bulls ( 53.77% registered positive breeding values. The accuracy of the breeding value estimation varied between 80, the highest precision, in case of the bull number 21 and 53, the lowest precision, in case of the bull number 38. A number of 7 bulls of the total of 57 with a positive breeding value were situated aproximately on the same positions at a difference of 0 to 1 points on the both lists established by BLUP and contemporary comparison. As a conclusion, BLUP could be largely and easily applied in bull evaluation for meat production traits in term of weight daily gain, considered the key parameter during the fattening period and its precision is very high, a guarantee that the bulls' hierarchy is a correct one. If a farmer would chose a high breeding value bull from a catalogue, he could be sure of the improvement of beef production by genetic gain.
Full Text Available Abstract Background The domestic cat has offered enormous genomic potential in the veterinary description of over 250 hereditary disease models as well as the occurrence of several deadly feline viruses (feline leukemia virus -- FeLV, feline coronavirus -- FECV, feline immunodeficiency virus - FIV that are homologues to human scourges (cancer, SARS, and AIDS respectively. However, to realize this bio-medical potential, a high density single nucleotide polymorphism (SNP map is required in order to accomplish disease and phenotype association discovery. Description To remedy this, we generated 3,178,297 paired fosmid-end Sanger sequence reads from seven cats, and combined these data with the publicly available 2X cat whole genome sequence. All sequence reads were assembled together to form a 3X whole genome assembly allowing the discovery of over three million SNPs. To reduce potential false positive SNPs due to the low coverage assembly, a low upper-limit was placed on sequence coverage and a high lower-limit on the quality of the discrepant bases at a potential variant site. In all domestic cats of different breeds: female Abyssinian, female American shorthair, male Cornish Rex, female European Burmese, female Persian, female Siamese, a male Ragdoll and a female African wildcat were sequenced lightly. We report a total of 964 k common SNPs suitable for a domestic cat SNP genotyping array and an additional 900 k SNPs detected between African wildcat and domestic cats breeds. An empirical sampling of 94 discovered SNPs were tested in the sequenced cats resulting in a SNP validation rate of 99%. Conclusions These data provide a large collection of mapped feline SNPs across the cat genome that will allow for the development of SNP genotyping platforms for mapping feline diseases.
Lenz, Patrick R N; Beaulieu, Jean; Mansfield, Shawn D; Clément, Sébastien; Desponts, Mireille; Bousquet, Jean
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
Lado, Bettina; Battenfield, Sarah; Guzmán, Carlos; Quincke, Martín; Singh, Ravi P; Dreisigacker, Susanne; Peña, R Javier; Fritz, Allan; Silva, Paula; Poland, Jesse; Gutiérrez, Lucía
The single most important decision in plant breeding programs is the selection of appropriate crosses. The ideal cross would provide superior predicted progeny performance and enough diversity to maintain genetic gain. The aim of this study was to compare the best crosses predicted using combinations of mid-parent value and variance prediction accounting for linkage disequilibrium (V) or assuming linkage equilibrium (V). After predicting the mean and the variance of each cross, we selected crosses based on mid-parent value, the top 10% of the progeny, and weighted mean and variance within progenies for grain yield, grain protein content, mixing time, and loaf volume in two applied wheat ( L.) breeding programs: Instituto Nacional de Investigación Agropecuaria (INIA) Uruguay and CIMMYT Mexico. Although the variance of the progeny is important to increase the chances of finding superior individuals from transgressive segregation, we observed that the mid-parent values of the crosses drove the genetic gain but the variance of the progeny had a small impact on genetic gain for grain yield. However, the relative importance of the variance of the progeny was larger for quality traits. Overall, the genomic resources and the statistical models are now available to plant breeders to predict both the performance of breeding lines per se as well as the value of progeny from any potential crosses. Copyright © 2017 Crop Science Society of America.
Fernández, Jesús; Toro, Miguel Á; Sonesson, Anna K; Villanueva, Beatriz
The success of an aquaculture breeding program critically depends on the way in which the base population of breeders is constructed since all the genetic variability for the traits included originally in the breeding goal as well as those to be included in the future is contained in the initial founders. Traditionally, base populations were created from a number of wild strains by sampling equal numbers from each strain. However, for some aquaculture species improved strains are already available and, therefore, mean phenotypic values for economically important traits can be used as a criterion to optimize the sampling when creating base populations. Also, the increasing availability of genome-wide genotype information in aquaculture species could help to refine the estimation of relationships within and between candidate strains and, thus, to optimize the percentage of individuals to be sampled from each strain. This study explores the advantages of using phenotypic and genome-wide information when constructing base populations for aquaculture breeding programs in terms of initial and subsequent trait performance and genetic diversity level. Results show that a compromise solution between diversity and performance can be found when creating base populations. Up to 6% higher levels of phenotypic performance can be achieved at the same level of global diversity in the base population by optimizing the selection of breeders instead of sampling equal numbers from each strain. The higher performance observed in the base population persisted during 10 generations of phenotypic selection applied in the subsequent breeding program.
Dassonneville, R; Brøndum, Rasmus Froberg; Druet, T
The purpose of this study was to investigate the imputation error and loss of reliability of direct genomic values (DGV) or genomically enhanced breeding values (GEBV) when using genotypes imputed from a 3,000-marker single nucleotide polymorphism (SNP) panel to a 50,000-marker SNP panel. Data...... of missing markers and prediction of breeding values were performed using 2 different reference populations in each country: either a national reference population or a combined EuroGenomics reference population. Validation for accuracy of imputation and genomic prediction was done based on national test...... with a national reference data set gave an absolute loss of 0.05 in mean reliability of GEBV in the French study, whereas a loss of 0.03 was obtained for reliability of DGV in the Nordic study. When genotypes were imputed using the EuroGenomics reference, a loss of 0.02 in mean reliability of GEBV was detected...
A. H. Sallam
Full Text Available Prediction accuracy of genomic selection (GS has been previously evaluated through simulation and cross-validation; however, validation based on progeny performance in a plant breeding program has not been investigated thoroughly. We evaluated several prediction models in a dynamic barley breeding population comprised of 647 six-row lines using four traits differing in genetic architecture and 1536 single nucleotide polymorphism (SNP markers. The breeding lines were divided into six sets designated as one parent set and five consecutive progeny sets comprised of representative samples of breeding lines over a 5-yr period. We used these data sets to investigate the effect of model and training population composition on prediction accuracy over time. We found little difference in prediction accuracy among the models confirming prior studies that found the simplest model, random regression best linear unbiased prediction (RR-BLUP, to be accurate across a range of situations. In general, we found that using the parent set was sufficient to predict progeny sets with little to no gain in accuracy from generating larger training populations by combining the parent set with subsequent progeny sets. The prediction accuracy ranged from 0.03 to 0.99 across the four traits and five progeny sets. We explored characteristics of the training and validation populations (marker allele frequency, population structure, and linkage disequilibrium, LD as well as characteristics of the trait (genetic architecture and heritability, . Fixation of markers associated with a trait over time was most clearly associated with reduced prediction accuracy for the mycotoxin trait DON. Higher trait in the training population and simpler trait architecture were associated with greater prediction accuracy.
Morton, John M; Auldist, Martin J; Douglas, Meaghan L; Macmillan, Keith L
Milk protein concentration in dairy cows has been positively associated with a range of measures of reproductive performance, and genetic factors affecting both milk protein concentration and reproductive performance may contribute to the observed phenotypic associations. It was of interest to assess whether these beneficial phenotypic associations are accounted for or interact with the effects of estimated breeding values for fertility. The effects of a multitrait estimated breeding value for fertility [the Australian breeding value for daughter fertility (ABV fertility)] on reproductive performance were also of interest. Interactions of milk protein concentration and ABV fertility with the interval from calving date to the start of the herd's seasonally concentrated breeding period were also assessed. A retrospective single cohort study was conducted using data collected from 74 Australian seasonally and split calving dairy herds. Associations between milk protein concentration, ABV fertility, and reproductive performance in Holstein cows were assessed using random effects logistic regression. Between 52,438 and 61,939 lactations were used for analyses of 4 reproductive performance measures. Milk protein concentration was strongly and positively associated with reproductive performance in dairy cows, and this effect was not accounted for by the effects of ABV fertility. Increases in ABV fertility had important additional beneficial effects on the probability of pregnancy by wk 6 and 21 of the herd's breeding period. For cows calved before the start of the breeding period, the effects of increases in both milk protein concentration and ABV fertility were beneficial regardless of their interval from calving to the start of the breeding period. These findings demonstrate the potential for increasing reproductive performance through identifying the causes of the association between milk protein concentration and reproductive performance and then devising management
Full Text Available Domesticated species are often composed of distinct populations differing in the character and strength of artificial and natural selection pressures, providing a valuable model to study adaptation. In contrast to pure-breed dogs that constitute artificially maintained inbred lines, free-ranging dogs are typically free-breeding, i.e., unrestrained in mate choice. Many traits in free-breeding dogs (FBDs may be under similar natural and sexual selection conditions to wild canids, while relaxation of sexual selection is expected in pure-breed dogs. We used a Bayesian approach with strict false-positive control criteria to identify FST-outlier SNPs between FBDs and either European or East Asian breeds, based on 167,989 autosomal SNPs. By identifying outlier SNPs located within coding genes, we found four candidate genes under diversifying selection shared by these two comparisons. Three of them are associated with the Hedgehog (HH signaling pathway regulating vertebrate morphogenesis. A comparison between FBDs and East Asian breeds also revealed diversifying selection on the BBS6 gene, which was earlier shown to cause snout shortening and dental crowding via disrupted HH signaling. Our results suggest that relaxation of natural and sexual selection in pure-breed dogs as opposed to FBDs could have led to mild changes in regulation of the HH signaling pathway. HH inhibits adhesion and the migration of neural crest cells from the neural tube, and minor deficits of these cells during embryonic development have been proposed as the underlying cause of “domestication syndrome.” This suggests that the process of breed formation involved the same genetic and developmental pathways as the process of domestication.
Vandenplas, J.; Colinet, F.G.; Glorieux, G.; Bertozzi, C.; Gengler, N.
Based on a Bayesian view of linear mixed models, several studies showed the possibilities to integrate estimated breeding values (EBV) and associated reliabilities (REL) provided by genetic evaluations performed outside a given evaluation system into this genetic evaluation. Hereafter, the term
Full Text Available Genomic selection (GS procedures have proven useful in estimating breeding value and predicting phenotype with genome-wide molecular marker information. However, issues of high dimensionality, multicollinearity, and the inability to deal effectively with epistasis can jeopardize accuracy and predictive ability. We, therefore, propose a new nonparametric method, pRKHS, which combines the features of supervised principal component analysis (SPCA and reproducing kernel Hilbert spaces (RKHS regression, with versions for traits with no/low epistasis, pRKHS-NE, to high epistasis, pRKHS-E. Instead of assigning a specific relationship to represent the underlying epistasis, the method maps genotype to phenotype in a nonparametric way, thus requiring fewer genetic assumptions. SPCA decreases the number of markers needed for prediction by filtering out low-signal markers with the optimal marker set determined by cross-validation. Principal components are computed from reduced marker matrix (called supervised principal components, SPC and included in the smoothing spline ANOVA model as independent variables to fit the data. The new method was evaluated in comparison with current popular methods for practicing GS, specifically RR-BLUP, BayesA, BayesB, as well as a newer method by Crossa et al., RKHS-M, using both simulated and real data. Results demonstrate that pRKHS generally delivers greater predictive ability, particularly when epistasis impacts trait expression. Beyond prediction, the new method also facilitates inferences about the extent to which epistasis influences trait expression.
Sun, Xiaochun; Ma, Ping; Mumm, Rita H
Genomic selection (GS) procedures have proven useful in estimating breeding value and predicting phenotype with genome-wide molecular marker information. However, issues of high dimensionality, multicollinearity, and the inability to deal effectively with epistasis can jeopardize accuracy and predictive ability. We, therefore, propose a new nonparametric method, pRKHS, which combines the features of supervised principal component analysis (SPCA) and reproducing kernel Hilbert spaces (RKHS) regression, with versions for traits with no/low epistasis, pRKHS-NE, to high epistasis, pRKHS-E. Instead of assigning a specific relationship to represent the underlying epistasis, the method maps genotype to phenotype in a nonparametric way, thus requiring fewer genetic assumptions. SPCA decreases the number of markers needed for prediction by filtering out low-signal markers with the optimal marker set determined by cross-validation. Principal components are computed from reduced marker matrix (called supervised principal components, SPC) and included in the smoothing spline ANOVA model as independent variables to fit the data. The new method was evaluated in comparison with current popular methods for practicing GS, specifically RR-BLUP, BayesA, BayesB, as well as a newer method by Crossa et al., RKHS-M, using both simulated and real data. Results demonstrate that pRKHS generally delivers greater predictive ability, particularly when epistasis impacts trait expression. Beyond prediction, the new method also facilitates inferences about the extent to which epistasis influences trait expression.
Dreger, Dayna L.; Davis, Brian W.; Cocco, Raffaella; Sechi, Sara; Di Cerbo, Alessandro; Parker, Heidi G.; Polli, Michele; Marelli, Stefano P.; Crepaldi, Paola; Ostrander, Elaine A.
The island inhabitants of Sardinia have long been a focus for studies of complex human traits due to their unique ancestral background and population isolation reflecting geographic and cultural restriction. Population isolates share decreased genomic diversity, increased linkage disequilibrium, and increased inbreeding coefficients. In many regions, dogs and humans have been exposed to the same natural and artificial forces of environment, growth, and migration. Distinct dog breeds have arisen through human-driven selection of characteristics to meet an ideal standard of appearance and function. The Fonni’s Dog, an endemic dog population on Sardinia, has not been subjected to an intensive system of artificial selection, but rather has developed alongside the human population of Sardinia, influenced by geographic isolation and unregulated selection based on its environmental adaptation and aptitude for owner-desired behaviors. Through analysis of 28 dog breeds, represented with whole-genome sequences from 13 dogs and ∼170,000 genome-wide single nucleotide variants from 155 dogs, we have produced a genomic illustration of the Fonni’s Dog. Genomic patterns confirm within-breed similarity, while population and demographic analyses provide spatial identity of Fonni’s Dog to other Mediterranean breeds. Investigation of admixture and fixation indices reveals insights into the involvement of Fonni’s Dogs in breed development throughout the Mediterranean. We describe how characteristics of population isolates are reflected in dog breeds that have undergone artificial selection, and are mirrored in the Fonni’s Dog through traditional isolating factors that affect human populations. Lastly, we show that the genetic history of Fonni’s Dog parallels demographic events in local human populations. PMID:27519604
Zhang, Xiao; Zhang, Hua; Li, Lujiang; Lan, Hai; Ren, Zhiyong; Liu, Dan; Wu, Ling; Liu, Hailan; Jaqueth, Jennifer; Li, Bailin; Pan, Guangtang; Gao, Shibin
Maize breeding germplasm used in Southwest China has high complexity because of the diverse ecological features of this area. In this study, the population structure, genetic diversity, and linkage disequilibrium decay distance of 362 important inbred lines collected from the breeding program of Southwest China were characterized using the MaizeSNP50 BeadChip with 56,110 single nucleotide polymorphisms (SNPs). With respect to population structure, two (Tropical and Temperate), three (Tropical, Stiff Stalk and non-Stiff Stalk), four [Tropical, group A germplasm derived from modern U.S. hybrids (PA), group B germplasm derived from modern U.S. hybrids (PB) and Reid] and six (Tropical, PB, Reid, Iowa Stiff Stalk Synthetic, PA and North) subgroups were identified. With increasing K value, the Temperate group showed pronounced hierarchical structure with division into further subgroups. The Genetic Diversity of each group was also estimated, and the Tropical group was more diverse than the Temperate group. Seven low-genetic-diversity and one high-genetic-diversity regions were collectively identified in the Temperate, Tropical groups, and the entire panel. SNPs with significant variation in allele frequency between the Tropical and Temperate groups were also evaluated. Among them, a region located at 130 Mb on Chromosome 2 showed the highest genetic diversity, including both number of SNPs with significant variation and the ratio of significant SNPs to total SNPs. Linkage disequilibrium decay distance in the Temperate group was greater (2.5-3 Mb) than that in the entire panel (0.5-0.75 Mb) and the Tropical group (0.25-0.5 Mb). A large region at 30-120 Mb of Chromosome 7 was concluded to be a region conserved during the breeding process by comparison between S37, which was considered a representative tropical line in Southwest China, and its 30 most similar derived lines. For the panel covered most of widely used inbred lines in Southwest China, this work
Full Text Available With the availability of high density whole-genome single nucleotide polymorphism chips, genomic selection has become a promising method to estimate genetic merit with potentially high accuracy for animal, plant and aquaculture species of economic importance. With markers covering the entire genome, genetic merit of genotyped individuals can be predicted directly within the framework of mixed model equations, by using a matrix of relationships among individuals that is derived from the markers. Here we extend that approach by deriving a marker-based relationship matrix specifically for the trait of interest.In the framework of mixed model equations, a new best linear unbiased prediction (BLUP method including a trait-specific relationship matrix (TA was presented and termed TABLUP. The TA matrix was constructed on the basis of marker genotypes and their weights in relation to the trait of interest. A simulation study with 1,000 individuals as the training population and five successive generations as candidate population was carried out to validate the proposed method. The proposed TABLUP method outperformed the ridge regression BLUP (RRBLUP and BLUP with realized relationship matrix (GBLUP. It performed slightly worse than BayesB with an accuracy of 0.79 in the standard scenario.The proposed TABLUP method is an improvement of the RRBLUP and GBLUP method. It might be equivalent to the BayesB method but it has additional benefits like the calculation of accuracies for individual breeding values. The results also showed that the TA-matrix performs better in predicting ability than the classical numerator relationship matrix and the realized relationship matrix which are derived solely from pedigree or markers without regard to the trait. This is because the TA-matrix not only accounts for the Mendelian sampling term, but also puts the greater emphasis on those markers that explain more of the genetic variance in the trait.
Bortoluzzi, Chiara; Crooijmans, Richard P.M.A.; Bosse, Mirte; Hiemstra, Sipke Joost; Groenen, Martien A.M.; Megens, Hendrik Jan
Traditional Dutch chicken breeds are marginalised breeds of ornamental and cultural-historical importance. In the last decades, miniaturising of existing breeds (so called neo-bantam) has become popular and resulted in alternatives to original large breeds. However, while backcrossing is increasing
Sauer, J.R.; Dolton, D.D.; Droege, S.
The mourning dove (Zenaida macroura) Callcount Survey and the North American Breeding Bird Survey provide information on population trends of mourning doves throughout the continental United States. Because surveys are an integral part of the development of hunting regulations, a need exists to determine which survey provides precise information. We estimated population trends from 1966 to 1988 by state and dove management unit, and assessed the relative efficiency of each survey. Estimates of population trend differ (P lt 0.05) between surveys in 11 of 48 states; 9 of 11 states with divergent results occur in the Eastern Management Unit. Differences were probably a consequence of smaller sample sizes in the Callcount Survey. The Breeding Bird Survey generally provided trend estimates with smaller variances than did the Callcount Survey. Although the Callcount Survey probably provides more withinroute accuracy because of survey methods and timing, the Breeding Bird Survey has a larger sample size of survey routes and greater consistency of coverage in the Eastern Unit.
Müller, Bárbara S F; Neves, Leandro G; de Almeida Filho, Janeo E; Resende, Márcio F R; Muñoz, Patricio R; Dos Santos, Paulo E T; Filho, Estefano Paludzyszyn; Kirst, Matias; Grattapaglia, Dario
The advent of high-throughput genotyping technologies coupled to genomic prediction methods established a new paradigm to integrate genomics and breeding. We carried out whole-genome prediction and contrasted it to a genome-wide association study (GWAS) for growth traits in breeding populations of Eucalyptus benthamii (n =505) and Eucalyptus pellita (n =732). Both species are of increasing commercial interest for the development of germplasm adapted to environmental stresses. Predictive ability reached 0.16 in E. benthamii and 0.44 in E. pellita for diameter growth. Predictive abilities using either Genomic BLUP or different Bayesian methods were similar, suggesting that growth adequately fits the infinitesimal model. Genomic prediction models using ~5000-10,000 SNPs provided predictive abilities equivalent to using all 13,787 and 19,506 SNPs genotyped in the E. benthamii and E. pellita populations, respectively. No difference was detected in predictive ability when different sets of SNPs were utilized, based on position (equidistantly genome-wide, inside genes, linkage disequilibrium pruned or on single chromosomes), as long as the total number of SNPs used was above ~5000. Predictive abilities obtained by removing relatedness between training and validation sets fell near zero for E. benthamii and were halved for E. pellita. These results corroborate the current view that relatedness is the main driver of genomic prediction, although some short-range historical linkage disequilibrium (LD) was likely captured for E. pellita. A GWAS identified only one significant association for volume growth in E. pellita, illustrating the fact that while genome-wide regression is able to account for large proportions of the heritability, very little or none of it is captured into significant associations using GWAS in breeding populations of the size evaluated in this study. This study provides further experimental data supporting positive prospects of using genome-wide data to
Zhe Zhang, Z.; Liu, J.F.; Ding, Z.; Bijma, P.; Koning, de D.J.
With the availability of high density whole-genome single nucleotide polymorphism chips, genomic selection has become a promising method to estimate genetic merit with potentially high accuracy for animal, plant and aquaculture species of economic importance. With markers covering the entire genome,
Morgan, M.R.; Norment, C.; Runge, M.C.
Declining populations of grassland breeding birds have led to increased efforts to assess habitat quality, typically by estimating density or relative abundance. Because some grassland habitats may function as ecological traps, a more appropriate metric for determining quality is breeding success, which is challenging to determine for many cryptic-nesting grassland birds. This difficulty led Vickery et al. (1992) to propose a reproductive index based on behavioral observations rather than nest fate. We rigorously evaluated the index for 2 years using a Savannah Sparrow (Passerculus sandwichensis) population in western New York and found a weak correlation in classification of the breeding stages of monitored territories among multiple observers (r = 0.398). We also discovered a large difference between overall territory and nest success rates independently estimated with the index (9.8% over the entire breeding cycle) and with nest searching and monitoring (41.7% of nests successfully fledged young). Most importantly, we made territory-level comparisons of index estimates with actual nest fate and found that the index correctly predicted fates for only 43% of the monitored nests. A Mayfield logistic regression analysis demonstrated that only index rank 4 (eggs hatched, but young failed to fledge) showed a strong positive correlation with nest success. Although the reproductive index may function as a coarse indicator of habitat suitability (e.g., documenting production in potential ecological traps), in our study the index exhibited neither internal consistency nor the ability to predict nest fate at the plot or territory level and functioned poorly as a substitute for nest searching and monitoring. ?? 2010 The American Ornithologists' Union.
S Hong Lee
Full Text Available Genomic prediction is emerging in a wide range of fields including animal and plant breeding, risk prediction in human precision medicine and forensic. It is desirable to establish a theoretical framework for genomic prediction accuracy when the reference data consists of information sources with varying degrees of relationship to the target individuals. A reference set can contain both close and distant relatives as well as 'unrelated' individuals from the wider population in the genomic prediction. The various sources of information were modeled as different populations with different effective population sizes (Ne. Both the effective number of chromosome segments (Me and Ne are considered to be a function of the data used for prediction. We validate our theory with analyses of simulated as well as real data, and illustrate that the variation in genomic relationships with the target is a predictor of the information content of the reference set. With a similar amount of data available for each source, we show that close relatives can have a substantially larger effect on genomic prediction accuracy than lesser related individuals. We also illustrate that when prediction relies on closer relatives, there is less improvement in prediction accuracy with an increase in training data or marker panel density. We release software that can estimate the expected prediction accuracy and power when combining different reference sources with various degrees of relationship to the target, which is useful when planning genomic prediction (before or after collecting data in animal, plant and human genetics.
For many of the new breeding techniques, sequence information is of the utmost importance. In addition to current breeding techniques, such as marker-assisted selection (MAS) and genetic modification (GM), new breeding techniques such as zinc finger nucleases, oligonucleotide-mediated mutagenesis, R...
Riedelsheimer, Christian; Melchinger, Albrecht E
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
Buch, Line Hjortø; Sørensen, Morten Kargo; Berg, Peer
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...
Kijas, James W.; Lenstra, Johannes A.; Hayes, Ben; Boitard, Simon; Porto Neto, Laercio R.; San Cristobal, Magali; Servin, Bertrand; McCulloch, Russell; Whan, Vicki; Gietzen, Kimberly; Paiva, Samuel; Barendse, William; Ciani, Elena; Raadsma, Herman; McEwan, John; Dalrymple, Brian
Through their domestication and subsequent selection, sheep have been adapted to thrive in a diverse range of environments. To characterise the genetic consequence of both domestication and selection, we genotyped 49,034 SNP in 2,819 animals from a diverse collection of 74 sheep breeds. We find the majority of sheep populations contain high SNP diversity and have retained an effective population size much higher than most cattle or dog breeds, suggesting domestication occurred from a broad genetic base. Extensive haplotype sharing and generally low divergence time between breeds reveal frequent genetic exchange has occurred during the development of modern breeds. A scan of the genome for selection signals revealed 31 regions containing genes for coat pigmentation, skeletal morphology, body size, growth, and reproduction. We demonstrate the strongest selection signal has occurred in response to breeding for the absence of horns. The high density map of genetic variability provides an in-depth view of the genetic history for this important livestock species. PMID:22346734
James W Kijas
Full Text Available Through their domestication and subsequent selection, sheep have been adapted to thrive in a diverse range of environments. To characterise the genetic consequence of both domestication and selection, we genotyped 49,034 SNP in 2,819 animals from a diverse collection of 74 sheep breeds. We find the majority of sheep populations contain high SNP diversity and have retained an effective population size much higher than most cattle or dog breeds, suggesting domestication occurred from a broad genetic base. Extensive haplotype sharing and generally low divergence time between breeds reveal frequent genetic exchange has occurred during the development of modern breeds. A scan of the genome for selection signals revealed 31 regions containing genes for coat pigmentation, skeletal morphology, body size, growth, and reproduction. We demonstrate the strongest selection signal has occurred in response to breeding for the absence of horns. The high density map of genetic variability provides an in-depth view of the genetic history for this important livestock species.
Nagl, Nevena; Taski-Ajdukovic, Ksenija; Barac, Goran; Baburski, Aleksandar; Seccareccia, Ivana; Milic, Dragan; Katic, Slobodan
Alfalfa is an autotetraploid, allogamous and heterozygous forage legume, whose varieties are synthetic populations. Due to the complex nature of the species, information about genetic diversity of germplasm used in any alfalfa breeding program is most beneficial. The genetic diversity of five alfalfa varieties, involved in progeny tests at Institute of Field and Vegetable Crops, was characterized based on RAPD markers. A total of 60 primers were screened, out of which 17 were selected for the analysis of genetic diversity. A total of 156 polymorphic bands were generated, with 10.6 bands per primer. Number and percentage of polymorphic loci, effective number of alleles, expected heterozygosity and Shannon's information index were used to estimate genetic variation. Variety Zuzana had the highest values for all tested parameters, exhibiting the highest level of variation, whereas variety RSI 20 exhibited the lowest. Analysis of molecular variance (AMOVA) showed that 88.39% of the total genetic variation was attributed to intra-varietal variance. The cluster analysis for individual samples and varieties revealed differences in their population structures: variety Zuzana showed a very high level of genetic variation, Banat and Ghareh were divided in subpopulations, while Pecy and RSI 20 were relatively uniform. Ways of exploiting the investigated germplasm in the breeding programs are suggested in this paper, depending on their population structure and diversity. The RAPD analysis shows potential to be applied in analysis of parental populations in semi-hybrid alfalfa breeding program in both, development of new homogenous germplasm, and identification of promising, complementary germplasm.
Wiens, J. David; Kolar, Patrick S.; Fuller, Mark R.; Hunt, W. Grainger; Hunt, Teresa
We used a multistate occupancy sampling design to estimate occupancy, breeding success, and abundance of territorial pairs of golden eagles (Aquila chrysaetos) in the Diablo Range, California, in 2014. This method uses the spatial pattern of detections and non-detections over repeated visits to survey sites to estimate probabilities of occupancy and successful reproduction while accounting for imperfect detection of golden eagles and their young during surveys. The estimated probability of detecting territorial pairs of golden eagles and their young was less than 1 and varied with time of the breeding season, as did the probability of correctly classifying a pair’s breeding status. Imperfect detection and breeding classification led to a sizeable difference between the uncorrected, naïve estimate of the proportion of occupied sites where successful reproduction was observed (0.20) and the model-based estimate (0.30). The analysis further indicated a relatively high overall probability of landscape occupancy by pairs of golden eagles (0.67, standard error = 0.06), but that areas with the greatest occupancy and reproductive potential were patchily distributed. We documented a total of 138 territorial pairs of golden eagles during surveys completed in the 2014 breeding season, which represented about one-half of the 280 pairs we estimated to occur in the broader 5,169-square kilometer region sampled. The study results emphasize the importance of accounting for imperfect detection and spatial heterogeneity in studies of site occupancy, breeding success, and abundance of golden eagles.
Mathewson, Heather A.
Population abundance estimates using predictive models are important for describing habitat use and responses to population-level impacts, evaluating conservation status of a species, and for establishing monitoring programs. The golden-cheeked warbler (Setophaga chrysoparia) is a neotropical migratory bird that was listed as federally endangered in 1990 because of threats related to loss and fragmentation of its woodland habitat. Since listing, abundance estimates for the species have mainly relied on localized population studies on public lands and qualitative-based methods. Our goal was to estimate breeding population size of male warblers using a predictive model based on metrics for patches of woodland habitat throughout the species\\' breeding range. We first conducted occupancy surveys to determine range-wide distribution. We then conducted standard point-count surveys on a subset of the initial sampling locations to estimate density of males. Mean observed patch-specific density was 0.23 males/ha (95% CI = 0.197-0.252, n = 301). We modeled the relationship between patch-specific density of males and woodland patch characteristics (size and landscape composition) and predicted patch occupancy. The probability of patch occupancy, derived from a model that used patch size and landscape composition as predictor variables while addressing effects of spatial relatedness, best predicted patch-specific density. We predicted patch-specific densities as a function of occupancy probability and estimated abundance of male warblers across 63,616 woodland patches accounting for 1.678 million ha of potential warbler habitat. Using a Monte Carlo simulation, our approach yielded a range-wide male warbler population estimate of 263,339 (95% CI: 223,927-302,620). Our results provide the first abundance estimate using habitat and count data from a sampling design focused on range-wide inference. Managers can use the resulting model as a tool to support conservation planning
Begum, Hasina; Spindel, Jennifer E; Lalusin, Antonio; Borromeo, Teresita; Gregorio, Glenn; Hernandez, Jose; Virk, Parminder; Collard, Bertrand; McCouch, Susan R
Genome-wide association mapping studies (GWAS) are frequently used to detect QTL in diverse collections of crop germplasm, based on historic recombination events and linkage disequilibrium across the genome. Generally, diversity panels genotyped with high density SNP panels are utilized in order to assay a wide range of alleles and haplotypes and to monitor recombination breakpoints across the genome. By contrast, GWAS have not generally been performed in breeding populations. In this study we performed association mapping for 19 agronomic traits including yield and yield components in a breeding population of elite irrigated tropical rice breeding lines so that the results would be more directly applicable to breeding than those from a diversity panel. The population was genotyped with 71,710 SNPs using genotyping-by-sequencing (GBS), and GWAS performed with the explicit goal of expediting selection in the breeding program. Using this breeding panel we identified 52 QTL for 11 agronomic traits, including large effect QTLs for flowering time and grain length/grain width/grain-length-breadth ratio. We also identified haplotypes that can be used to select plants in our population for short stature (plant height), early flowering time, and high yield, and thus demonstrate the utility of association mapping in breeding populations for informing breeding decisions. We conclude by exploring how the newly identified significant SNPs and insights into the genetic architecture of these quantitative traits can be leveraged to build genomic-assisted selection models.
Lamb, Jennifer Y.; Waddle, J. Hardin; Qualls, Carl P.
Large gaps exist in our knowledge of the ecology of stream-breeding plethodontid salamanders in the Gulf Coastal Plain. Data describing where these salamanders are likely to occur along environmental gradients, as well as their likelihood of detection, are important for the prevention and management of amphibian declines. We used presence/absence data from leaf litter bag surveys and a hierarchical Bayesian multispecies single-season occupancy model to estimate the occurrence of five species of plethodontids across reaches in headwater streams in the Gulf Coastal Plain. Average detection probabilities were high (range = 0.432–0.942) and unaffected by sampling covariates specific to the use of litter bags (i.e., bag submergence, sampling season, in-stream cover). Estimates of occurrence probabilities differed substantially between species (range = 0.092–0.703) and were influenced by the size of the upstream drainage area and by the maximum proportion of the reach that dried. The effects of these two factors were not equivalent across species. Our results demonstrate that hierarchical multispecies models successfully estimate occurrence parameters for both rare and common stream-breeding plethodontids. The resulting models clarify how species are distributed within stream networks, and they provide baseline values that will be useful in evaluating the conservation statuses of plethodontid species within lotic systems in the Gulf Coastal Plain.
Full Text Available The sequencing of the full nuclear genome of sesame (Sesamum indicum L. provides the platform for functional analyses of genome components and their application in breeding programs. Although the importance of microsatellites markers or simple sequence repeats (SSR in crop genotyping, genetics, and breeding applications is well established, only a little information exist concerning SSRs at the whole genome level in sesame. In addition, SSRs represent a suitable marker type for sesame molecular breeding in developing countries where it is mainly grown. In this study, we identified 138,194 genome-wide SSRs of which 76.5% were physically mapped onto the 13 pseudo-chromosomes. Among these SSRs, up to three primers pairs were supplied for 101,930 SSRs and used to in silico amplify the reference genome together with two newly sequenced sesame accessions. A total of 79,957 SSRs (78% were polymorphic between the three genomes thereby suggesting their promising use in different genomics-assisted breeding applications. From these polymorphic SSRs, 23 were selected and validated to have high polymorphic potential in 48 sesame accessions from different growing areas of Africa. Furthermore, we have developed an online user-friendly database, SisatBase (http://www.sesame-bioinfo.org/SisatBase/, which provides free access to SSRs data as well as an integrated platform for functional analyses. Altogether, the reference SSR and SisatBase would serve as useful resources for genetic assessment, genomic studies, and breeding advancement in sesame, especially in developing countries.
Kendall, W.L.; Nichols, J.D.; Hines, J.E.
Statistical inference for capture-recapture studies of open animal populations typically relies on the assumption that all emigration from the studied population is permanent. However, there are many instances in which this assumption is unlikely to be met. We define two general models for the process of temporary emigration, completely random and Markovian. We then consider effects of these two types of temporary emigration on Jolly-Seber (Seber 1982) estimators and on estimators arising from the full-likelihood approach of Kendall et al. (1995) to robust design data. Capture-recapture data arising from Pollock's (1982) robust design provide the basis for obtaining unbiased estimates of demographic parameters in the presence of temporary emigration and for estimating the probability of temporary emigration. We present a likelihood-based approach to dealing with temporary emigration that permits estimation under different models of temporary emigration and yields tests for completely random and Markovian emigration. In addition, we use the relationship between capture probability estimates based on closed and open models under completely random temporary emigration to derive three ad hoc estimators for the probability of temporary emigration, two of which should be especially useful in situations where capture probabilities are heterogeneous among individual animals. Ad hoc and full-likelihood estimators are illustrated for small mammal capture-recapture data sets. We believe that these models and estimators will be useful for testing hypotheses about the process of temporary emigration, for estimating demographic parameters in the presence of temporary emigration, and for estimating probabilities of temporary emigration. These latter estimates are frequently of ecological interest as indicators of animal movement and, in some sampling situations, as direct estimates of breeding probabilities and proportions.
Full Text Available Carcass and price traits of 72,969 Hanwoo cows, bulls and steers aged 16 to 80 months at slaughter collected from 2002 to 2013 at 75 beef packing plants in Korea were analyzed to determine heritability, correlation and breeding value using the Multi-Trait restricted maximum likelihood (REML animal model procedure. The traits included carcass measurements, scores and grades at 24 h postmortem and bid prices at auction. Relatively high heritability was found for maturity (0.41±0.031, while moderate heritability estimates were obtained for backfat thickness (0.20±0.018, longissimus muscle (LM area (0.23±0.020, carcass weight (0.28±0.019, yield index (0.20±0.018, yield grade (0.16±0.017, marbling (0.28±0.021, texture (0.14±0.016, quality grade (0.26±0.016 and price/kg (0.24±0.025. Relatively low heritability estimates were observed for meat color (0.06±0.013 and fat color (0.06±0.012. Heritability estimates for most traits were lower than those in the literature. Genetic correlations of carcass measurements with characteristic scores or quality grade of carcass ranged from −0.27 to +0.21. Genetic correlations of yield grade with backfat thickness, LM area and carcass weight were 0.91, −0.43, and −0.09, respectively. Genetic correlations of quality grade with scores of marbling, meat color, fat color and texture were −0.99, 0.48, 0.47, and 0.98, respectively. Genetic correlations of price/kg with LM area, carcass weight, marbling, meat color, texture and maturity were 0.57, 0.64, 0.76, −0.41, −0.79, and −0.42, respectively. Genetic correlations of carcass price with LM area, carcass weight, marbling and texture were 0.61, 0.57, 0.64, and −0.73, respectively, with standard errors ranging from ±0.047 to ±0.058. The mean carcass weight breeding values increased by more than 8 kg, whereas the mean marbling scores decreased by approximately 0.2 from 2000 through 2009. Overall, the results suggest that genetic improvement of
Onzima, R B; Upadhyay, M R; Mukiibi, R; Kanis, E; Groenen, M A M; Crooijmans, R P M A
Uganda has a large population of goats, predominantly from indigenous breeds reared in diverse production systems, whose existence is threatened by crossbreeding with exotic Boer goats. Knowledge about the genetic characteristics and relationships among these Ugandan goat breeds and the potential admixture with Boer goats is still limited. Using a medium-density single nucleotide polymorphism (SNP) panel, we assessed the genetic diversity, population structure and admixture in six goat breeds in Uganda: Boer, Karamojong, Kigezi, Mubende, Small East African and Sebei. All the animals had genotypes for about 46 105 SNPs after quality control. We found high proportions of polymorphic SNPs ranging from 0.885 (Kigezi) to 0.928 (Sebei). The overall mean observed (H O ) and expected (H E ) heterozygosity across breeds was 0.355 ± 0.147 and 0.384 ± 0.143 respectively. Principal components, genetic distances and admixture analyses revealed weak population sub-structuring among the breeds. Principal components separated Kigezi and weakly Small East African from other indigenous goats. Sebei and Karamojong were tightly entangled together, whereas Mubende occupied a more central position with high admixture from all other local breeds. The Boer breed showed a unique cluster from the Ugandan indigenous goat breeds. The results reflect common ancestry but also some level of geographical differentiation. admixture and f 4 statistics revealed gene flow from Boer and varying levels of genetic admixture among the breeds. Generally, moderate to high levels of genetic variability were observed. Our findings provide useful insights into maintaining genetic diversity and designing appropriate breeding programs to exploit within-breed diversity and heterozygote advantage in crossbreeding schemes. © 2018 The Authors. Animal Genetics published by John Wiley & Sons Ltd on behalf of Stichting International Foundation for Animal Genetics.
Dehnavi, E; Mahyari, S Ansari; Schenkel, F S; Sargolzaei, M
Using cow data in the training population is attractive as a way to mitigate bias due to highly selected training bulls and to implement genomic selection for countries with no or limited proven bull data. However, one potential issue with cow data is a bias due to the preferential treatment. The objectives of this study were to (1) investigate the effect of including cow genotype and phenotype data into the training population on accuracy and bias of genomic predictions and (2) assess the effect of preferential treatment for different proportions of elite cows. First, a 4-pathway Holstein dairy cattle population was simulated for 2 traits with low (0.05) and moderate (0.3) heritability. Then different numbers of cows (0, 2,500, 5,000, 10,000, 15,000, or 20,000) were randomly selected and added to the training group composed of different numbers of top bulls (0, 2,500, 5,000, 10,000, or 15,000). Reliability levels of de-regressed estimated breeding values for training cows and bulls were 30 and 75% for traits with low heritability and were 60 and 90% for traits with moderate heritability, respectively. Preferential treatment was simulated by introducing upward bias equal to 35% of phenotypic variance to 5, 10, and 20% of elite bull dams in each scenario. Two different validation data sets were considered: (1) all animals in the last generation of both elite and commercial tiers (n = 42,000) and (2) only animals in the last generation of the elite tier (n = 12,000). Adding cow data into the training population led to an increase in accuracy (r) and decrease in bias of genomic predictions in all considered scenarios without preferential treatment. The gain in r was higher for the low heritable trait (from 0.004 to 0.166 r points) compared with the moderate heritable trait (from 0.004 to 0.116 r points). The gain in accuracy in scenarios with a lower number of training bulls was relatively higher (from 0.093 to 0.166 r points) than with a higher number of training
Sun, Yaqi; Wang, Hongyang; Wang, Chao; Yu, Shaobo; Liu, Jing; Zhang, Yu; Fan, Bin; Li, Kui; Liu, Bang
Copy number variations (CNVs) represent a substantial source of structural variants in mammals and contribute to both normal phenotypic variability and disease susceptibility. Although low-resolution CNV maps are produced in many domestic animals, and several reports have been published about the CNVs of porcine genome, the differences between Chinese and western pigs still remain to be elucidated. In this study, we used Porcine SNP60 BeadChip and PennCNV algorithm to perform a genome-wide CNV detection in 302 individuals from six Chinese indigenous breeds (Tongcheng, Laiwu, Luchuan, Bama, Wuzhishan and Ningxiang pigs), three western breeds (Yorkshire, Landrace and Duroc) and one hybrid (Tongcheng×Duroc). A total of 348 CNV Regions (CNVRs) across genome were identified, covering 150.49 Mb of the pig genome or 6.14% of the autosomal genome sequence. In these CNVRs, 213 CNVRs were found to exist only in the six Chinese indigenous breeds, and 60 CNVRs only in the three western breeds. The characters of CNVs in four Chinese normal size breeds (Luchuan, Tongcheng and Laiwu pigs) and two minipig breeds (Bama and Wuzhishan pigs) were also analyzed in this study. Functional annotation suggested that these CNVRs possess a great variety of molecular function and may play important roles in phenotypic and production traits between Chinese and western breeds. Our results are important complementary to the CNV map in pig genome, which provide new information about the diversity of Chinese and western pig breeds, and facilitate further research on porcine genome CNVs. PMID:25198154
Onzima, R.B.; Upadhyay, M.R.; Mukiibi, R.; Kanis, E.; Groenen, M.A.M.; Crooijmans, R.P.M.A.
Uganda has a large population of goats, predominantly from indigenous breeds reared in diverse production systems, whose existence is threatened by crossbreeding with exotic Boer goats. Knowledge about the genetic characteristics and relationships among these Ugandan goat breeds and the potential
Full Text Available Clovers (genus Trifolium are a large and widespread genus of legumes. A number of clovers are of agricultural importance as forage crops in grassland agriculture, particularly temperate areas. White clover (Trifolium repens L. is used in grazed pasture and red clover (T. pratense L. is widely cut and conserved as a winter feed. For the diploid red clover, genetic and genomic tools and resources have developed rapidly over the last five years including genetic and physical maps, BAC (bacterial artificial chromosome end sequence and transcriptome sequence information. This has paved the way for the use of genome wide selection and high throughput phenotyping in germplasm development. For the allotetraploid white clover progress has been slower although marker assisted selection is in use and relatively robust genetic maps and QTL (quantitative trait locus information now exist. For both species the sequencing of the model legume Medicago truncatula gene space is an important development to aid genomic, biological and evolutionary studies. The first genetic maps of another species, subterranean clover (Trifolium subterraneum L. have also been published and its comparative genomics with red clover and M. truncatula conducted. Next generation sequencing brings the potential to revolutionize clover genomics, but international consortia and effective use of germplasm, novel population structures and phenomics will be required to carry out effective translation into breeding. Another avenue for clover genomic and genetic improvement is interspecific hybridization. This approach has considerable potential with regard to crop improvement but also opens windows of opportunity for studies of biological and evolutionary processes.
Xu, Song-Song; Gao, Lei; Xie, Xing-Long; Ren, Yan-Ling; Shen, Zhi-Qiang; Wang, Feng; Shen, Min; Eyϸórsdóttir, Emma; Hallsson, Jón H.; Kiseleva, Tatyana; Kantanen, Juha; Li, Meng-Hua
Reproduction is an important trait in sheep breeding as well as in other livestock. However, despite its importance the genetic mechanisms of litter size in domestic sheep (Ovis aries) are still poorly understood. To explore genetic mechanisms underlying the variation in litter size, we conducted multiple independent genome-wide association studies in five sheep breeds of high prolificacy (Wadi, Hu, Icelandic, Finnsheep, and Romanov) and one low prolificacy (Texel) using the Ovine Infinium HD BeadChip, respectively. We identified different sets of candidate genes associated with litter size in different breeds: BMPR1B, FBN1, and MMP2 in Wadi; GRIA2, SMAD1, and CTNNB1 in Hu; NCOA1 in Icelandic; INHBB, NF1, FLT1, PTGS2, and PLCB3 in Finnsheep; ESR2 in Romanov and ESR1, GHR, ETS1, MMP15, FLI1, and SPP1 in Texel. Further annotation of genes and bioinformatics analyses revealed that different biological pathways could be involved in the variation in litter size of females: hormone secretion (FSH and LH) in Wadi and Hu, placenta and embryonic lethality in Icelandic, folliculogenesis and LH signaling in Finnsheep, ovulation and preovulatory follicle maturation in Romanov, and estrogen and follicular growth in Texel. Taken together, our results provide new insights into the genetic mechanisms underlying the prolificacy trait in sheep and other mammals, suggesting targets for selection where the aim is to increase prolificacy in breeding projects.
Full Text Available Alfalfa is an autotetraploid, allogamous and heterozygous forage legume, whose varieties are synthetic populations. Due to the complex nature of the species, information about genetic diversity of germplasm used in any alfalfa breeding program is most beneficial. The genetic diversity of five alfalfa varieties, involved in progeny tests at Institute of Field and Vegetable Crops, was characterized based on RAPD markers. A total of 60 primers were screened, out of which 17 were selected for the analysis of genetic diversity. A total of 156 polymorphic bands were generated, with 10.6 bands per primer. Number and percentage of polymorphic loci, effective number of alleles, expected heterozygosity and Shannon’s information index were used to estimate genetic variation. Variety Zuzana had the highest values for all tested parameters, exhibiting the highest level of variation, whereas variety RSI 20 exhibited the lowest. Analysis of molecular variance (AMOVA showed that 88.39% of the total genetic variation was attributed to intra-varietal variance. The cluster analysis for individual samples and varieties revealed differences in their population structures: variety Zuzana showed a very high level of genetic variation, Banat and Ghareh were divided in subpopulations, while Pecy and RSI 20 were relatively uniform. Ways of exploiting the investigated germplasm in the breeding programs are suggested in this paper, depending on their population structure and diversity. The RAPD analysis shows potential to be applied in analysis of parental populations in semi-hybrid alfalfa breeding program in both, development of new homogenous germplasm, and identification of promising, complementary germplasm.
Mahdi Shariati, Mohammad; Sørensen, Peter; Janss, Luc
. A better alternative could be to form clusters of markers with similar effects where markers in a cluster have a common variance. Therefore, the influence of each marker group of size p on the posterior distribution of the marker variances will be p df. Methods: The simulated data from the 15th QTL......Background: In genomic models that assign an individual variance to each marker, the contribution of one marker to the posterior distribution of the marker variance is only one degree of freedom (df), which introduces many variance parameters with only little information per variance parameter......-MAS workshop were analyzed such that SNP markers were ranked based on their effects and markers with similar estimated effects were grouped together. In step 1, all markers with minor allele frequency more than 0.01 were included in a SNP-BLUP prediction model. In step 2, markers were ranked based...
Navas González, Francisco Javier; Jordana Vidal, Jordi; León Jurado, José Manuel; Arando Arbulu, Ander; McLean, Amy Katherine; Delgado Bermejo, Juan Vicente
Donkeys are recognized therapy or leisure-riding animals. Anecdotal evidence has suggested that more reactive donkeys or those more easily engaging flight mechanisms tend to be easier to train compared to those displaying the natural donkey behaviour of fight. This context brings together the need to quantify such traits and to genetically select donkeys displaying a neutral reaction during training, because of its implication with handler/rider safety and trainability. We analysed the scores for coping style traits from 300 Andalusian donkeys from 2013 to 2015. Three scales were applied to describe donkeys' response to 12 stimuli. Genetic parameters were estimated using multivariate models with year, sex, husbandry system and stimulus as fixed effects and age as a linear and quadratic covariable. Heritabilities were moderate, 0.18 ± 0.020 to 0.21 ± 0.021. Phenotypic correlations between intensity and mood/emotion or response type were negative and moderate (-0.21 and -0.25, respectively). Genetic correlations between the same variables were negative and moderately high (-0.46 and -0.53, respectively). Phenotypic and genetic correlations between mood/emotion and response type were positive and high (0.92 and 0.95, respectively). Breeding values enable selection methods that could lead to endangered breed preservation and genetically selecting donkeys for the uses that they may be most suitable. Copyright © 2018 Elsevier B.V. All rights reserved.
Dario, C; Carnicella, D; Dario, M; Bufano, G
A data set concerning 1,816 subjects entered in the Italian Horse Registry from 1925 to 2002 was analyzed to investigate the morphological evolution of the Murgese horse and to obtain useful elements to enhance breeding practices. Three basic body measurements (height at withers, chest girth, and cannon bone circumference) were considered for each subject. Heritabilities were calculated for each parameter to infer the growth and development traits of this breed. Over the past 20 years the Murgese horse has undergone considerable changes, passing from a typical mesomorphic structure (height at withers: 156.30 and 151.04 cm; chest girth: 185.80 and 176.11 cm; cannon bone: 21.10 and 19.82 cm for males and females, respectively) to a mesodolichomorphic structure (height at withers: 160.31 and 156.44 cm; chest girth: 187.89 and 182.48 cm; cannon bone: 21.07 and 20.37 cm, for males and females, respectively). Due to these changes and to its characteristic strength and power, the Murgese, which was once used in agriculture and for meat production (at the end of its life), is now involved in sports, mainly in trekking and equestrian tourism. The heritability estimates for the three body measurements were found to be 0.24, 0.39 and 0.44.
He, Jianbo; Meng, Shan; Zhao, Tuanjie; Xing, Guangnan; Yang, Shouping; Li, Yan; Guan, Rongzhan; Lu, Jiangjie; Wang, Yufeng; Xia, Qiuju; Yang, Bing; Gai, Junyi
The innovative RTM-GWAS procedure provides a relatively thorough detection of QTL and their multiple alleles for germplasm population characterization, gene network identification, and genomic selection strategy innovation in plant breeding. The previous genome-wide association studies (GWAS) have been concentrated on finding a handful of major quantitative trait loci (QTL), but plant breeders are interested in revealing the whole-genome QTL-allele constitution in breeding materials/germplasm (in which tremendous historical allelic variation has been accumulated) for genome-wide improvement. To match this requirement, two innovations were suggested for GWAS: first grouping tightly linked sequential SNPs into linkage disequilibrium blocks (SNPLDBs) to form markers with multi-allelic haplotypes, and second utilizing two-stage association analysis for QTL identification, where the markers were preselected by single-locus model followed by multi-locus multi-allele model stepwise regression. Our proposed GWAS procedure is characterized as a novel restricted two-stage multi-locus multi-allele GWAS (RTM-GWAS, https://github.com/njau-sri/rtm-gwas ). The Chinese soybean germplasm population (CSGP) composed of 1024 accessions with 36,952 SNPLDBs (generated from 145,558 SNPs, with reduced linkage disequilibrium decay distance) was used to demonstrate the power and efficiency of RTM-GWAS. Using the CSGP marker information, simulation studies demonstrated that RTM-GWAS achieved the highest QTL detection power and efficiency compared with the previous procedures, especially under large sample size and high trait heritability conditions. A relatively thorough detection of QTL with their multiple alleles was achieved by RTM-GWAS compared with the linear mixed model method on 100-seed weight in CSGP. A QTL-allele matrix (402 alleles of 139 QTL × 1024 accessions) was established as a compact form of the population genetic constitution. The 100-seed weight QTL-allele matrix was
Avhashoni AA. Zwane
Sep 20, 2016 ... ... high temperatures and low-quality grass and for their resistance to ... growth rate, early marketability, grazing performance and good ... development of the Bonsmara breed (Scholtz, 2010). ..... transferability to water buffalo.
Full Text Available Some mammals breed throughout the year, while others breed only at certain times of year. These differences in reproductive behavior can be explained by evolution. We identified positively-selected genes in two sets of species with different degrees of relatedness including seasonal and non-seasonal breeding species, using branch-site models. After stringent filtering by sum of pairs scoring, we revealed that more genes underwent positive selection in seasonal compared with non-seasonal breeding species. Positively-selected genes were verified by cDNA mapping of the positive sites with the corresponding cDNA sequences. The design of the evolutionary analysis can effectively lower the false-positive rate and thus identify valid positive genes. Validated, positively-selected genes, including CGA, DNAH1, INVS, and CD151, were related to reproductive behaviors such as spermatogenesis and cell proliferation in non-seasonal breeding species. Genes in seasonal breeding species, including THRAP3, TH1L, and CMTM6, may be related to the evolution of sperm and the circadian rhythm system. Identification of these positively-selected genes might help to identify the molecular mechanisms underlying seasonal and non-seasonal reproductive behaviors.
Hu, G; Gu, W; Bai, Q L; Wang, B Q
Genetic parameters and breeding values for growth traits were estimated in the first and, currently, the only family selective breeding program for rainbow trout (Oncorhynchus mykiss) in China. Genetic and phenotypic data were collected for growth traits from 75 full-sibling families with a 2-generation pedigree. Genetic parameters and breeding values for growth traits of rainbow trout were estimated using the derivative-free restricted maximum likelihood method. The goodness-of-fit of the models was tested using Akaike and Bayesian information criteria. Genetic parameters and breeding values were estimated using the best-fit model for each trait. The values for heritability estimating body weight and length ranged from 0.20 to 0.45 and from 0.27 to 0.60, respectively, and the heritability of condition factor was 0.34. Our results showed a moderate degree of heritability for growth traits in this breeding program and suggested that the genetic and phenotypic tendency of body length, body weight, and condition factor were similar. Therefore, the selection of phenotypic values based on pedigree information was also suitable in this research population.
Jeong, Hyeonsoo; Kim, Kwondo; Caetano-Anollés, Kelsey; Kim, Heebal; Kim, Byung-Ki; Yi, Jun-Koo; Ha, Jae-Jung; Cho, Seoae; Oh, Dong Yep
Chicken, Gallus gallus, is a valuable species both as a food source and as a model organism for scientific research. Here, we sequenced the genome of Gyeongbuk Araucana, a rare chicken breed with unique phenotypic characteristics including flight ability, large body size, and laying blue-shelled eggs, to identify its genomic features. We generated genomes of Gyeongbuk Araucana, Leghorn, and Korean Native Chicken at a total of 33.5, 35.82, and 33.23 coverage depth, respectively. Along with the genomes of 12 Chinese breeds, we identified genomic variants of 16.3 million SNVs and 2.3 million InDels in mapped regions. Additionally, through assembly of unmapped reads and selective sweep, we identified candidate genes that fall into heart, vasculature and muscle development and body growth categories, which provided insight into Gyeongbuk Araucana's phenotypic traits. Finally, genetic variation based on the transposable element insertion pattern was investigated to elucidate the features of transposable elements related to blue egg shell formation. This study presents results of the first genomic study on the Gyeongbuk Araucana breed; it has potential to serve as an invaluable resource for future research on the genomic characteristics of this chicken breed as well as others.
Significant advances in the establishment of the methodologies required for the molecular breeding of temperate forage grasses (Lolium and Festuca species) and legumes (Trifolium and Medicago species) are reviewed. Examples of current products and approaches for the application of these methodologies to forage grass and legume improvement are outlined. The plethora of new technologies and tools now available for high-throughput gene discovery and genome-wide expression analysis have opened up opportunities for innovative applications in the identification, functional characterization and use of genes of value in forage production systems and beyond. Selected examples of current work in pasture plant genomics, xenogenomics, symbiogenomics and micro-array-based molecular phenotyping are discussed. (author)
Bastiaansen, John W M; Coster, Albart; Calus, Mario P L; van Arendonk, Johan A M; Bovenhuis, Henk
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
Full Text Available Objective. Estimate the genetic parameters for milk traits in a Romanian local sheep population Teleorman Black Head. Material and methods. Records of 262 sheep belonging to 17 rams and 139 ewes were used in the study. The following traits were investigated: milk yield, fat yield, protein yield, fat percentage and protein percentage. The genetic parameters were estimated using the Restricted Maximum Likelihood method, with a model including maternal effects. Results. The results from our study revealed that direct heritability estimates were moderate for milk yield (0.449, fat yield (0.442, protein yield (0.386 while for protein percentage (0.708 and fat percentage (0.924 were high. The high direct and maternal genetic correlation was between milk yield and protein yield (0.979, 0.973 and between protein yield and fat yield (0.952, 0.913 while the phenotypic correlation between the milk yield and fat yield (0.968, the milk yield and protein yield (0.967, fat yield and protein yield (0.936 was high and positive. Conclusions. The genetic parameters are important in selection program on this breed for genetic improvement.
Zhang, Ao; Wang, Hongwu; Beyene, Yoseph; Semagn, Kassa; Liu, Yubo; Cao, Shiliang; Cui, Zhenhai; Ruan, Yanye; Burgueño, Juan; San Vicente, Felix; Olsen, Michael; Prasanna, Boddupalli M; Crossa, José; Yu, Haiqiu; Zhang, Xuecai
Genomic selection is being used increasingly in plant breeding to accelerate genetic gain per unit time. One of the most important applications of genomic selection in maize breeding is to predict and select the best un-phenotyped lines in bi-parental populations based on genomic estimated breeding values. In the present study, 22 bi-parental tropical maize populations genotyped with low density SNPs were used to evaluate the genomic prediction accuracy ( r MG ) of the six trait-environment combinations under various levels of training population size (TPS) and marker density (MD), and assess the effect of trait heritability ( h 2 ), TPS and MD on r MG estimation. Our results showed that: (1) moderate r MG values were obtained for different trait-environment combinations, when 50% of the total genotypes was used as training population and ~200 SNPs were used for prediction; (2) r MG increased with an increase in h 2 , TPS and MD, both correlation and variance analyses showed that h 2 is the most important factor and MD is the least important factor on r MG estimation for most of the trait-environment combinations; (3) predictions between pairwise half-sib populations showed that the r MG values for all the six trait-environment combinations were centered around zero, 49% predictions had r MG values above zero; (4) the trend observed in r MG differed with the trend observed in r MG / h , and h is the square root of heritability of the predicted trait, it indicated that both r MG and r MG / h values should be presented in GS study to show the accuracy of genomic selection and the relative accuracy of genomic selection compared with phenotypic selection, respectively. This study provides useful information to maize breeders to design genomic selection workflow in their breeding programs.
Full Text Available Genomic selection is being used increasingly in plant breeding to accelerate genetic gain per unit time. One of the most important applications of genomic selection in maize breeding is to predict and select the best un-phenotyped lines in bi-parental populations based on genomic estimated breeding values. In the present study, 22 bi-parental tropical maize populations genotyped with low density SNPs were used to evaluate the genomic prediction accuracy (rMG of the six trait-environment combinations under various levels of training population size (TPS and marker density (MD, and assess the effect of trait heritability (h2, TPS and MD on rMG estimation. Our results showed that: (1 moderate rMG values were obtained for different trait-environment combinations, when 50% of the total genotypes was used as training population and ~200 SNPs were used for prediction; (2 rMG increased with an increase in h2, TPS and MD, both correlation and variance analyses showed that h2 is the most important factor and MD is the least important factor on rMG estimation for most of the trait-environment combinations; (3 predictions between pairwise half-sib populations showed that the rMG values for all the six trait-environment combinations were centered around zero, 49% predictions had rMG values above zero; (4 the trend observed in rMG differed with the trend observed in rMG/h, and h is the square root of heritability of the predicted trait, it indicated that both rMG and rMG/h values should be presented in GS study to show the accuracy of genomic selection and the relative accuracy of genomic selection compared with phenotypic selection, respectively. This study provides useful information to maize breeders to design genomic selection workflow in their breeding programs.
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.
Spindel, Jennifer; Begum, Hasina; Akdemir, Deniz; Virk, Parminder; Collard, Bertrand; Redoña, Edilberto; Atlin, Gary; Jannink, Jean-Luc; McCouch, Susan R
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.
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
Spindel, Jennifer; Begum, Hasina; Akdemir, Deniz; Virk, Parminder; Collard, Bertrand; Redoña, Edilberto; Atlin, Gary; Jannink, Jean-Luc; McCouch, Susan R.
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
Ben J Hayes
Full Text Available Continued production of food in areas predicted to be most affected by climate change, such as dairy farming regions of Australia, will be a major challenge in coming decades. Along with rising temperatures and water shortages, scarcity of inputs such as high energy feeds is predicted. With the motivation of selecting cattle adapted to these changing environments, we conducted a genome wide association study to detect DNA markers (single nucleotide polymorphisms associated with the sensitivity of milk production to environmental conditions. To do this we combined historical milk production and weather records with dense marker genotypes on dairy sires with many daughters milking across a wide range of production environments in Australia. Markers associated with sensitivity of milk production to feeding level and sensitivity of milk production to temperature humidity index on chromosome nine and twenty nine respectively were validated in two independent populations, one a different breed of cattle. As the extent of linkage disequilibrium across cattle breeds is limited, the underlying causative mutations have been mapped to a small genomic interval containing two promising candidate genes. The validated marker panels we have reported here will aid selection for high milk production under anticipated climate change scenarios, for example selection of sires whose daughters will be most productive at low levels of feeding.
van der Westhuizen, R R; van der Westhuizen, J
It is generally accepted that feed intake and growth (gain) are the most important economic components when calculating profitability in a growth test or feedlot. We developed a single post-weaning growth (feedlot) index based on the economic values of different components. Variance components, heritabilities and genetic correlations for and between initial weight (IW), final weight (FW), feed intake (FI), and shoulder height (SHD) were estimated by multitrait restricted maximum likelihood procedures. The estimated breeding values (EBVs) and the economic values for IW, FW and FI were used in a selection index to estimate a post-weaning or feedlot profitability value. Heritabilities for IW, FW, FI, and SHD were 0.41, 0.40, 0.33, and 0.51, respectively. The highest genetic correlations were 0.78 (between IW and FW) and 0.70 (between FI and FW). EBVs were used in a selection index to calculate a single economical value for each animal. This economic value is an indication of the gross profitability value or the gross test value (GTV) of the animal in a post-weaning growth test. GTVs varied between -R192.17 and R231.38 with an average of R9.31 and a standard deviation of R39.96. The Pearson correlations between EBVs (for production and efficiency traits) and GTV ranged from -0.51 to 0.68. The lowest correlation (closest to zero) was 0.26 between the Kleiber ratio and GTV. Correlations of 0.68 and -0.51 were estimated between average daily gain and GTV and feed conversion ratio and GTV, respectively. These results showed that it is possible to select for GTV. The selection index can benefit feedlotting in selecting offspring of bulls with high GTVs to maximize profitability.
Vaysse, Amaury; Ratnakumar, Abhirami; Derrien, Thomas
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 br...
Full Text Available Linear mixed model (LMM analysis has been recently used extensively for estimating additive genetic variances and narrow-sense heritability in many genomic studies. While the LMM analysis is computationally less intensive than the Bayesian algorithms, it remains infeasible for large-scale genomic data sets. In this paper, we advocate the use of a statistical procedure known as symmetric differences squared (SDS as it may serve as a viable alternative when the LMM methods have difficulty or fail to work with large datasets. The SDS procedure is a general and computationally simple method based only on the least squares regression analysis. We carry out computer simulations and empirical analyses to compare the SDS procedure with two commonly used LMM-based procedures. Our results show that the SDS method is not as good as the LMM methods for small data sets, but it becomes progressively better and can match well with the precision of estimation by the LMM methods for data sets with large sample sizes. Its major advantage is that with larger and larger samples, it continues to work with the increasing precision of estimation while the commonly used LMM methods are no longer able to work under our current typical computing capacity. Thus, these results suggest that the SDS method can serve as a viable alternative particularly when analyzing 'big' genomic data sets.
Since both the number of SNPs (single nucleotide polymorphisms) used in genomic prediction and the number of individuals used in training datasets are rapidly increasing, there is an increasing need to improve the efficiency of genomic prediction models in terms of computing time and memory (RAM)
Gordo, D G M; Espigolan, R; Tonussi, R L; Júnior, G A F; Bresolin, T; Magalhães, A F Braga; Feitosa, F L; Baldi, F; Carvalheiro, R; Tonhati, H; de Oliveira, H N; Chardulo, L A L; de Albuquerque, L G
The objective of this study was to determine whether visual scores used as selection criteria in Nellore breeding programs are effective indicators of carcass traits measured after slaughter. Additionally, this study evaluated the effect of different structures of the relationship matrix ( and ) on the estimation of genetic parameters and on the prediction accuracy of breeding values. There were 13,524 animals for visual scores of conformation (CS), finishing precocity (FP), and muscling (MS) and 1,753, 1,747, and 1,564 for LM area (LMA), backfat thickness (BF), and HCW, respectively. Of these, 1,566 animals were genotyped using a high-density panel containing 777,962 SNP. Six analyses were performed using multitrait animal models, each including the 3 visual scores and 1 carcass trait. For the visual scores, the model included direct additive genetic and residual random effects and the fixed effects of contemporary group (defined by year of birth, management group at yearling, and farm) and the linear effect of age of animal at yearling. The same model was used for the carcass traits, replacing the effect of age of animal at yearling with the linear effect of age of animal at slaughter. The variance and covariance components were estimated by the REML method in analyses using the numerator relationship matrix () or combining the genomic and the numerator relationship matrices (). The heritability estimates for the visual scores obtained with the 2 methods were similar and of moderate magnitude (0.23-0.34), indicating that these traits should response to direct selection. The heritabilities for LMA, BF, and HCW were 0.13, 0.07, and 0.17, respectively, using matrix and 0.29, 0.16, and 0.23, respectively, using matrix . The genetic correlations between the visual scores and carcass traits were positive, and higher correlations were generally obtained when matrix was used. Considering the difficulties and cost of measuring carcass traits postmortem, visual scores of
Shade Larry L
Full Text Available Abstract Background Approximately 11 Mb of finished high quality genomic sequences were sampled from cattle, dog and human to estimate genomic divergences and their regional variation among these lineages. Results Optimal three-way multi-species global sequence alignments for 84 cattle clones or loci (each >50 kb of genomic sequence were constructed using the human and dog genome assemblies as references. Genomic divergences and substitution rates were examined for each clone and for various sequence classes under different functional constraints. Analysis of these alignments revealed that the overall genomic divergences are relatively constant (0.32–0.37 change/site for pairwise comparisons among cattle, dog and human; however substitution rates vary across genomic regions and among different sequence classes. A neutral mutation rate (2.0–2.2 × 10(-9 change/site/year was derived from ancestral repetitive sequences, whereas the substitution rate in coding sequences (1.1 × 10(-9 change/site/year was approximately half of the overall rate (1.9–2.0 × 10(-9 change/site/year. Relative rate tests also indicated that cattle have a significantly faster rate of substitution as compared to dog and that this difference is about 6%. Conclusion This analysis provides a large-scale and unbiased assessment of genomic divergences and regional variation of substitution rates among cattle, dog and human. It is expected that these data will serve as a baseline for future mammalian molecular evolution studies.
Li, L; Feng, D X; Wu, J
It is a difficult problem of forensic medicine to accurately estimate the post-mortem interval. Entomological approach has been regarded as an effective way to estimate the post-mortem interval. The developmental biology of carrion-breeding flies has an important position at the post-mortem interval estimation. Phorid flies are tiny and occur as the main or even the only insect evidence in relatively enclosed environments. This paper reviews the research progress of carrion-breeding phorid flies for estimating post-mortem interval in forensic medicine which includes their roles, species identification and age determination of immatures. Copyright© by the Editorial Department of Journal of Forensic Medicine.
Standen, Ismo; Christensen, Ole Fredslund
Genomic data are used in animal breeding to assist genetic evaluation. Several models to estimate genomic breeding values have been studied. In general, two approaches have been used. One approach estimates the marker effects first and then, genomic breeding values are obtained by summing marker...... effects. In the second approach, genomic breeding values are estimated directly using an equivalent model with a genomic relationship matrix. Allele coding is the method chosen to assign values to the regression coefficients in the statistical model. A common allele coding is zero for the homozygous...... genotype of the first allele, one for the heterozygote, and two for the homozygous genotype for the other allele. Another common allele coding changes these regression coefficients by subtracting a value from each marker such that the mean of regression coefficients is zero within each marker. We call...
Ruttink, Tom; Roldán-Ruiz, Isabel; Asp, Torben
To advance the application of molecular breeding in Lolium perenne, we have generated a sequence resource to facilitate gene discovery and SNP marker development. Illumina GAII transcriptome sequencing was performed on meristem-enriched samples of 14 Lolium genotypes. De novo assemblies for indiv......To advance the application of molecular breeding in Lolium perenne, we have generated a sequence resource to facilitate gene discovery and SNP marker development. Illumina GAII transcriptome sequencing was performed on meristem-enriched samples of 14 Lolium genotypes. De novo assemblies...... of SNP markers in selected candidate genes. In parallel, a germplasm collection of 602 Lolium genotypes was established and is being phenotyped for plant architecture, reproductive characteristics, flowering time, and forage quality traits. We will test through association genetics whether phenotypic...
Kevin C. Fraser
Full Text Available The global decline in many species of migratory birds has focused attention on the extent of migratory connectivity between breeding and wintering populations. Stable-hydrogen isotope (Î´D analysis of feathers is a useful technique for measuring connectivity, but is constrained by features of molt location and timing. Claws are metabolically inert, keratinous tissues that grow continuously and can be sampled at any point in the annual cycle, thus providing potentially useful clues about an individual's previous movements. However, variation in the rate at which claws incorporate local Î´D values is not well described. We measured Î´D values in claws of two species of Neotropical-Nearctic migrant wood-warblers (Golden-winged Warbler and Cerulean Warbler breeding in eastern Ontario, Canada to investigate the rate of Î´D change through the breeding season and the utility of claw Î´D values for estimating migratory origins. Î´D values of claw tips from 66 different individuals, each sampled once during the breeding season, showed an average change of -0.3 to -0.4 per day in the direction of the expected local Ontario value. There were no significant sex or species differences in the rate of change. These results suggest Î´D values of claw tips in Parulids may reflect those of the non-breeding area for 3-7 weeks after arrival on the breeding grounds, and are useful estimators of non-breeding migratory origin. Our results also suggest that these species may leave the breeding ground before claw tips fully incorporate a local Î´D signature, as claws sampled at the end of the breeding season did not match locally grown feather and claw Î´D values. This is the first study to examine the seasonal rate of the change in Î´D values of claws in long-distance, insectivorous, migratory birds.
Edwards, J D; Baldo, A M; Mueller, L A
Ricebase (http://ricebase.org) is an integrative genomic database for rice (Oryza sativa) with an emphasis on combining datasets in a way that maintains the key links between past and current genetic studies. Ricebase includes DNA sequence data, gene annotations, nucleotide variation data and molecular marker fragment size data. Rice research has benefited from early adoption and extensive use of simple sequence repeat (SSR) markers; however, the majority of rice SSR markers were developed prior to the latest rice pseudomolecule assembly. Interpretation of new research using SNPs in the context of literature citing SSRs requires a common coordinate system. A new pipeline, using a stepwise relaxation of stringency, was used to map SSR primers onto the latest rice pseudomolecule assembly. The SSR markers and experimentally assayed amplicon sizes are presented in a relational database with a web-based front end, and are available as a track loaded in a genome browser with links connecting the browser and database. The combined capabilities of Ricebase link genetic markers, genome context, allele states across rice germplasm and potentially user curated phenotypic interpretations as a community resource for genetic discovery and breeding in rice. Published by Oxford University Press 2016. This work is written by US Government employees and is in the public domain in the United States.
Kim, Tae-Sung; He, Qiang; Kim, Kyu-Won; Yoon, Min-Young; Ra, Won-Hee; Li, Feng Peng; Tong, Wei; Yu, Jie; Oo, Win Htet; Choi, Buung; Heo, Eun-Beom; Yun, Byoung-Kook; Kwon, Soon-Jae; Kwon, Soon-Wook; Cho, Yoo-Hyun; Lee, Chang-Yong; Park, Beom-Seok; Park, Yong-Jin
Rice germplasm collections continue to grow in number and size around the world. Since maintaining and screening such massive resources remains challenging, it is important to establish practical methods to manage them. A core collection, by definition, refers to a subset of the entire population that preserves the majority of genetic diversity, enhancing the efficiency of germplasm utilization. Here, we report whole-genome resequencing of the 137 rice mini core collection or Korean rice core set (KRICE_CORE) that represents 25,604 rice germplasms deposited in the Korean genebank of the Rural Development Administration (RDA). We implemented the Illumina HiSeq 2000 and 2500 platform to produce short reads and then assembled those with 9.8 depths using Nipponbare as a reference. Comparisons of the sequences with the reference genome yielded more than 15 million (M) single nucleotide polymorphisms (SNPs) and 1.3 M INDELs. Phylogenetic and population analyses using 2,046,529 high-quality SNPs successfully assigned rice accessions to the relevant rice subgroups, suggesting that these SNPs capture evolutionary signatures that have accumulated in rice subpopulations. Furthermore, genome-wide association studies (GWAS) for four exemplary agronomic traits in the KRIC_CORE manifest the utility of KRICE_CORE; that is, identifying previously defined genes or novel genetic factors that potentially regulate important phenotypes. This study provides strong evidence that the size of KRICE_CORE is small but contains high genetic and functional diversity across the genome. Thus, our resequencing results will be useful for future breeding, as well as functional and evolutionary studies, in the post-genomic era.
Sørensen, Lars P; Janss, Luc; Madsen, Per
was used. There was a clear difference in the region-wise patterns of genomic correlation among combinations of traits, with distinctive peaks indicating the presence of pleiotropic QTL. CONCLUSIONS: The results show that it is possible to estimate, genome-wide and region-wise genomic (co)variances......BACKGROUND: Multi-trait genomic models in a Bayesian context can be used to estimate genomic (co)variances, either for a complete genome or for genomic regions (e.g. per chromosome) for the purpose of multi-trait genomic selection or to gain further insight into the genomic architecture of related...... with a common prior distribution for the marker allele substitution effects and estimation of the hyperparameters in this prior distribution from the progeny means data. From the Markov chain Monte Carlo samples of the allele substitution effects, genomic (co)variances were calculated on a whole-genome level...
Fernando Henrique Biase
Full Text Available We sampled 119 Nelore cattle (Bos indicus, 69 harboring B. indicus mtDNA plus 50 carrying Bos taurus mtDNA, to estimate the frequencies of putative mtDNA single nucleotide polymorphisms (SNPs and investigate their association with Nelore weight and scrotal circumference estimated breeding values (EBVs. The PCR restriction fragment length polymorphism (PCR-RFLP method was used to detect polymorphisms in the mitochondrial asparagine, cysteine, glycine, leucine and proline transporter RNA (tRNA genes (tRNAasn, tRNAcys, tRNAgly, tRNAleu and tRNApro. The 50 cattle carrying B. taurus mtDNA were monomorphic for all the tRNA gene SNPs analyzed, suggesting that they are specific to mtDNA from B. indicus cattle. No tRNAcys or tRNAgly polymorphisms were detected in any of the cattle but we did detect polymorphic SNPs in the tRNAasn, tRNAleu and tRNApro genes in the cattle harboring B. indicus mtDNA, with the same allele observed in the B. taurus sequence being present in the following percentage of cattle harboring B. indicus mtDNA: 72.46% for tRNAasn, 95.23% for tRNAleu and 90.62% for tRNApro. Analyses of variance using the tRNAasn SNP as the independent variable and EBVs as the dependent variable showed that the G -> T SNP was significantly associated (p < 0.05 with maternal EBVs for weight at 120 and 210 days (p < 0.05 and animal's EBVs for weight at 210, 365 and 455 days. There was no association of the tRNAasn SNP with the scrotal circumference EBVs. These results confirm that mtDNA can affect weight and that mtDNA polymorphisms can be a source of genetic variation for quantitative traits.
Schneider, J F; Rempel, L A; Rohrer, G A
The primary objective of this study was to determine genetic and genomic parameters among swine (Sus scrofa) farrowing traits. Genetic parameters were obtained using MTDFREML. Genomic parameters were obtained using GENSEL. Genetic and residual variances obtained from MTDFREML were used as priors for the Bayes C analysis of GENSEL. Farrowing traits included total number born (TNB), number born alive (NBA), number born dead (NBD), number stillborn (NSB), number of mummies (MUM), litter birth weight (LBW), and average piglet birth weight (ABW). Statistically significant heritabilities included TNB (0.09, P = 0.048), NBA (0.09, P = 0.041), LBW (0.20, P = 0.002), and ABW (0.26, P NBA (0.97, P NBA-LBW (0.56, P NBA (0.06), NBD (0.00), NSB (0.01), MUM (0.00), LBW (0.11), and ABW (0.31). Limited information is available in the literature about genomic parameters. Only the GP estimate for NSB is significantly lower than what has been published. The GP estimate for ABW is greater than the estimate for heritability found in this study. Other traits with significant heritability had GP estimates half the value of heritability. This research indicates that significant genetic markers will be found for TNB, NBA, LBW, and ABW that will have either immediate use in industry or provide a roadmap to further research with fine mapping or sequencing of areas of significance. Furthermore, these results indicate that genomic selection implemented at an early age would have similar annual progress as traditional selection, and could be incorporated along with traditional selection procedures to improve genetic progress of litter traits.
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.
Kumar, Anil; Waiz, Syma Ashraf; Sridhar Goud, T; Tonk, R K; Grewal, Anita; Singh, S V; Yadav, B R; Upadhyay, R C
The aim of this study was to evaluate the genome integrity so as to assess the adaptability of three breeds of indigenous cattle reared under arid and semi-arid regions of Rajasthan (Bikaner) and Haryana (Karnal) India. The cattle were of homogenous group (same age and sex) of indigenous breeds viz. Sahiwal, Tharparkar and Kankrej. A total of 100 animals were selected for this study from both climatic conditions. The sister chromatid exchanges (SCE's), chromosomal gaps and chromatid breaks were observed in metaphase plates of chromosome preparations obtained from in vitro culture of peripheral blood lymphocytes. The mean number of breaks and gaps in Sahiwal and Tharparkar of semi-arid zone were 8.56 ± 3.16, 6.4 ± 3.39 and 8.72 ± 2.04, 3.52 ± 6.29, respectively. Similarly, the mean number of breaks and gaps in Tharparkar and Kankrej cattle of arid zone were 5.26 ± 1.76, 2.74 ± 1.76 and 5.24 ± 1.84, 2.5 ± 1.26, respectively. The frequency of SCEs in chromosomes was found significantly higher (P 0.05) was observed in the same zone. The analysis of frequency of CAs and SCEs revealed significant effects of environmental conditions on the genome integrity of animals, thereby indicating an association with their adaptability.
Li, Chun-Hong; Liu, Fang; Wang, Li
Abstract In the present work, we report the complete mitochondrial genome sequence of feral rock pigeon for the first time. The total length of the mitogenome was 17,239 bp with the base composition of 30.3% for A, 24.0% for T, 31.9% for C, and 13.8% for G and an A-T (54.3 %)-rich feature was detected. It harbored 13 protein-coding genes, 2 ribosomal RNA genes, 22 transfer RNA genes and 1 non-coding control region (D-loop region). The arrangement of all genes was identical to the typical mitochondrial genomes of pigeon. The complete mitochondrial genome sequence of feral rock pigeon would serve as an important data set of the germplasm resources for further study.
We conducted a genome-wide scan for visceral leishmaniasis in mixed-breed dogs from a highly endemic area in Brazil using 149,648 single nucleotide polymorphism (SNP) markers genotyped in 20 cases and 28 controls. Using a mixed model approach, we found two candidate loci on canine autosomes 1 and 2....
Calus, M.P.L.; Meuwissen, T.H.E.; Windig, J.J.; Knol, E.F.; Schrooten, C.; Vereijken, A.L.J.; Veerkamp, R.F.
The aim of this paper was to compare the effect of haplotype definition on the precision of QTL-mapping and on the accuracy of predicted genomic breeding values. In a multiple QTL model using identity-by-descent (IBD) probabilities between haplotypes, various haplotype definitions were tested i.e.
Doekes, Harmen P.; Veerkamp, Roel F.; Bijma, Piter; Hiemstra, Sipke J.; Windig, Jack J.
Background: In recent decades, Holstein-Friesian (HF) selection schemes have undergone profound changes, including the introduction of optimal contribution selection (OCS; around 2000), a major shift in breeding goal composition (around 2000) and the implementation of genomic selection (GS;
Nedenia Bonvino Stafuzza
Full Text Available Whole-genome re-sequencing, alignment and annotation analyses were undertaken for 12 sires representing four important cattle breeds in Brazil: Guzerat (multi-purpose, Gyr, Girolando and Holstein (dairy production. A total of approximately 4.3 billion reads from an Illumina HiSeq 2000 sequencer generated for each animal 10.7 to 16.4-fold genome coverage. A total of 27,441,279 single nucleotide variations (SNVs and 3,828,041 insertions/deletions (InDels were detected in the samples, of which 2,557,670 SNVs and 883,219 InDels were novel. The submission of these genetic variants to the dbSNP database significantly increased the number of known variants, particularly for the indicine genome. The concordance rate between genotypes obtained using the Bovine HD BeadChip array and the same variants identified by sequencing was about 99.05%. The annotation of variants identified numerous non-synonymous SNVs and frameshift InDels which could affect phenotypic variation. Functional enrichment analysis was performed and revealed that variants in the olfactory transduction pathway was over represented in all four cattle breeds, while the ECM-receptor interaction pathway was over represented in Girolando and Guzerat breeds, the ABC transporters pathway was over represented only in Holstein breed, and the metabolic pathways was over represented only in Gyr breed. The genetic variants discovered here provide a rich resource to help identify potential genomic markers and their associated molecular mechanisms that impact economically important traits for Gyr, Girolando, Guzerat and Holstein breeding programs.
Foucher, F.; Hilbrand-Saint Oyant, L.; Hamama, L.; Sakr, S.; Baudino, S.; Caissard, J.P.; Smulders, M.J.M.; Debener, T.; Riek, de J.; Torres, A.F.; Desnoyé, B.
Rose is one of the most economically important ornamental crops worldwide. Rosa sp. can become a model for woody ornamentals. Its genome size is relatively small (560 Mb), its genetic history with ploïdy events is well documented, and rose has a short life for a woody plant. Furthermore, different
Vandenplas, J; Colinet, F G; Glorieux, G; Bertozzi, C; Gengler, N
Based on a Bayesian view of linear mixed models, several studies showed the possibilities to integrate estimated breeding values (EBV) and associated reliabilities (REL) provided by genetic evaluations performed outside a given evaluation system into this genetic evaluation. Hereafter, the term "internal" refers to this given genetic evaluation system, and the term "external" refers to all other genetic evaluations performed outside the internal evaluation system. Bayesian approaches integrate external information (i.e., external EBV and associated REL) by altering both the mean and (co)variance of the prior distributions of the additive genetic effects based on the knowledge of this external information. Extensions of the Bayesian approaches to multivariate settings are interesting because external information expressed on other scales, measurement units, or trait definitions, or associated with different heritabilities and genetic parameters than the internal traits, could be integrated into a multivariate genetic evaluation without the need to convert external information to the internal traits. Therefore, the aim of this study was to test the integration of external EBV and associated REL, expressed on a 305-d basis and genetically correlated with a trait of interest, into a multivariate genetic evaluation using a random regression test-day model for the trait of interest. The approach we used was a multivariate Bayesian approach. Results showed that the integration of external information led to a genetic evaluation for the trait of interest for, at least, animals associated with external information, as accurate as a bivariate evaluation including all available phenotypic information. In conclusion, the multivariate Bayesian approaches have the potential to integrate external information correlated with the internal phenotypic traits, and potentially to the different random regressions, into a multivariate genetic evaluation. This allows the use of different
Ebensperger, Luis A; Rivera, Daniela S; Hayes, Loren D
1. Understanding how variation in fitness relates to variation in group living remains critical to determine whether this major aspect of social behaviour is currently adaptive. 2. Available evidence in social mammals aimed to examine this issue remains controversial. Studies show positive (i.e. potentially adaptive), neutral or even negative fitness effects of group living. 3. Attempts to explain this variation rely on intrinsic and extrinsic factors to social groups. Thus, relatively more positive fitness effects are predicted in singularly breeding as opposed to plural breeding species. Fitness effects of sociality in turn may depend on ecological conditions (i.e. extrinsic factors) that influence associated benefits and costs. 4. We used meta-analytic tools to review how breeding strategy or ecological conditions influence the effect size associated with direct fitness-sociality relationships reported in the mammalian literature. Additionally, we determined how taxonomic affiliation of species studied, different fitness and sociality measures used, and major climatic conditions of study sites explained any variation in direct fitness effect size. 5. We found group living had modest, yet positive effects on direct fitness. This generally adaptive scenario was contingent not only upon breeding strategy and climate of study sites, but also on fitness measures examined. Thus, positive and significant effects characterized singular as opposed to plural breeding strategies. 6. We found more positive fitness effects on studies conducted in tropical as opposed to temperate or arid climates. More positive and significant effects were noted on studies that relied on group fecundity, male fecundity and offspring survival as measures of fitness. 7. To conclude, direct fitness consequences of mammalian group living are driven by interspecific differences in breeding strategy and climate conditions. Other factors not examined in this study, namely individual variation in
Felleki, M; Lee, D; Lee, Y; Gilmour, A R; Rönnegård, L
The possibility of breeding for uniform individuals by selecting animals expressing a small response to environment has been studied extensively in animal breeding. Bayesian methods for fitting models with genetic components in the residual variance have been developed for this purpose, but have limitations due to the computational demands. We use the hierarchical (h)-likelihood from the theory of double hierarchical generalized linear models (DHGLM) to derive an estimation algorithm that is computationally feasible for large datasets. Random effects for both the mean and residual variance parts of the model are estimated together with their variance/covariance components. An important feature of the algorithm is that it can fit a correlation between the random effects for mean and variance. An h-likelihood estimator is implemented in the R software and an iterative reweighted least square (IRWLS) approximation of the h-likelihood is implemented using ASReml. The difference in variance component estimates between the two implementations is investigated, as well as the potential bias of the methods, using simulations. IRWLS gives the same results as h-likelihood in simple cases with no severe indication of bias. For more complex cases, only IRWLS could be used, and bias did appear. The IRWLS is applied on the pig litter size data previously analysed by Sorensen & Waagepetersen (2003) using Bayesian methodology. The estimates we obtained by using IRWLS are similar to theirs, with the estimated correlation between the random genetic effects being -0·52 for IRWLS and -0·62 in Sorensen & Waagepetersen (2003).
Lopez-Cruz, Marco; Crossa, Jose; Bonnett, David; Dreisigacker, Susanne; Poland, Jesse; Jannink, Jean-Luc; Singh, Ravi P; Autrique, Enrique; de los Campos, Gustavo
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
Hayes, Benjamin J; MacLeod, Iona M; Daetwyler, Hans D
Advantages of using whole genome sequence data to predict genomic estimated breeding values (GEBV) include better persistence of accuracy of GEBV across generations and more accurate GEBV across breeds. The 1000 Bull Genomes Project provides a database of whole genome sequenced key ancestor bulls....... In a dairy data set, predictions using BayesRC and imputed sequence data from 1000 Bull Genomes were 2% more accurate than with 800k data. We could demonstrate the method identified causal mutations in some cases. Further improvements will come from more accurate imputation of sequence variant genotypes...
Tauson, A H; Chwalibog, André; Jakobsen, K
Protein and energy metabolism in boars of different breeds, 10 each of Hampshire, Duroc and Danish Landrace was measured in balance and respiration experiments by means of indirect calorimetry in an open-air circulation system. Measurements were performed in four periods (Period I-IV) covering th...
Paaijmans, K.P.; Jacobs, A.F.G.; Takken, W.; Heusinkveld, B.G.; Githeko, A.K.; Dicke, M.; Holtslag, A.A.M.
Water temperature is an important determinant of the growth and development of malaria mosquito immatures. To gain a better understanding of the daily temperature dynamics of malaria mosquito breeding sites and of the relationships between meteorological variables and water temperature, three clear
Bhering, L L; Junqueira, V S; Peixoto, L A; Cruz, C D; Laviola, B G
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.
Sithembile Olga Makina
Full Text Available Information about genetic diversity and population structure among cattle breeds is essential for genetic improvement, understanding of environmental adaptation as well as utilization and conservation of cattle breeds. This study investigated genetic diversity and the population structure among six cattle breeds in South African (SA including Afrikaner (n=44, Nguni (n=54, Drakensberger (n=47, Bonsmara (n=44, Angus (n=31 and Holstein (n=29. Genetic diversity within cattle breeds was analyzed using three measures of genetic diversity namely allelic richness (AR, expected heterozygosity (He and inbreeding coefficient (f. Genetic distances between breed pairs were evaluated using Nei’s genetic distance. Population structure was assessed using model-based clustering (ADMIXTURE. Results of this study revealed that the allelic richness ranged from 1.88 (Afrikaner to 1.73 (Nguni. Afrikaner cattle had the lowest level of genetic diversity (He=0.24 and the Drakensberger cattle (He=0.30 had the highest level of genetic variation among indigenous and locally-developed cattle breeds. The level of inbreeding was lower across the studied cattle breeds. As expected the average genetic distance was the greatest between indigenous cattle breeds and Bos taurus cattle breeds but the lowest among indigenous and locally-developed breeds. Model-based clustering revealed some level of admixture among indigenous and locally-developed breeds and supported the clustering of the breeds according to their history of origin. The results of this study provided useful insight regarding genetic structure of South African cattle breeds.
Eun, M.Y.; Cho, Y.G.; Hahn, J.H.; Yoon, U.H.; Yi, B.Y.; Chung, T.Y.
An 'MG' recombinant inbred population which consists of 164 F 13 lines has been developed from a cross between a Tongil type variety Milyang 23 and a Japonica type Gihobyeo by single seed descent. A Restriction Fragment Length Polymorphism (RFLP) framework map using this population has been constructed. Morphological markers, isozyme loci, microsatellites, Amplified Fragment Length Polymorphisms (AFLP), and new complementary DNA (cDNA) markers are being integrated in the framework map for a highly saturated comprehensive map. So far, 207 RFLPs, 89 microsatellites, 5 isozymes, 232 AFLPs, and 2 morphological markers have been mapped through international collaboration. The map contains 1,826 cM with an average interval size of 4.5 cM on the framework map and 3.4 cM overall (as of 29 October 1996). The framework map is being used for analyzing, quantitative trait loci (QTL) of agronomic characters and some physico-chemical properties relating to rice quality. The number of significant QTLs affecting each trait ranged from one to five, and 38 QTLs were detected for 17 traits. The percentage of variance explained by each QTL ranged from 5.6 to 66.9%. The isozyme marker, EstI-2, and two RFLP markers, RG109 and RG220, were linked most tightly at a distance less than 1 cM with the semidwarf (sd-1) gene on chromosome 1. These markers could be used for precise in vitro selection of individuals carrying the semidwarf gene using single seeds or very young leaf tissue, before this character is fully expressed. Appropriate application of marker-assisted selection, using EstI-2 and RFLP markers for the semidwarf character, in combination with other markers linked to genes of agronomic importance in rice, holds promise for improving, the efficiency of breeding, and the high-resolution genetic and physical mapping near sd-1, aimed at ultimately cloning this valuable gene
Full Text Available Genome size diversity in angiosperms varies roughly 2400-fold, although approximately 45% of angiosperm families lack a single genome size estimation, and therefore, this range could be enlarged. To contribute completing family and genera representation, DNA C-Values are here provided for 19 species from 16 eudicot families, including first values for 6 families, 14 genera and 17 species. The sample of species studied is very diverse, including herbs, weeds, vines, shrubs and trees. Data are discussed regarding previous genome size estimates of closely related species or genera, if any, their chromosome number, growth form or invasive behaviour. The present research contributes approximately 1.5% new values for previously unreported angiosperm families, being the current coverage around 55% of angiosperm families, according to the Plant DNA C-Values Database.
La diversidad del tamaño del genoma en angiospermas es muy amplia, siendo el valor más elevado aproximadamente unas 2400 veces superior al más pequeño. Sin embargo, cerca del 45% de las familias no presentan ni una sola estimación, por lo que el rango real podría ser ampliado. Para contribuir a completar la representación de familias y géneros de angiospermas, este estudio contribuye con valores C para 19 especies de 16 familias de eudicoticotiledóneas, incluyendo los primeros valores para 6 familias, 14 géneros y 17 especies. La muestra estudiada es muy diversa, e incluye hierbas, malezas, enredaderas, arbustos y árboles. Se discuten los resultados en función de estimaciones previas del tamaño del genoma de especies o géneros estrechamente relacionados, del número de cromosomas, la forma de crecimiento o el comportamiento invasor de las especies analizadas. El presente estudio contribuye aproximadamente en un 1,5% de nuevos valores para familias de angiospermas no estudiadas previamente, de las que actualmente existe información para el 55%, según la base de datos
Marshall, M. R.
Full Text Available Many species of bird exhibit varying degrees of site–fidelity to the previous year’s territory or breeding area, a phenomenon we refer to as incomplete breeding site–fidelity. If the territory they occupy is located beyond the bounds of the study area or search area (i.e., they have emigrated from the study area, the bird will go undetected and is therefore indistinguishable from dead individuals in capture–mark–recapture studies. Differential emigration rates confound inferences regarding differences in survival between sexes and among species if apparent survival rates are used as estimates of true survival. Moreover, the bias introduced by using apparent survival rates for true survival rates can have profound effects on the predictions of population persistence through time, source/sink dynamics, and other aspects of life–history theory. We investigated four study design and analysis approaches that result in apparent survival estimates that are closer to true survival estimates. Our motivation for this research stemmed from a multi–year capture–recapture study of Prothonotary Warblers (Protonotaria citrea on multiple study plots within a larger landscape of suitable breeding habitat where substantial inter–annual movements of marked individuals among neighboring study plots was documented. We wished to quantify the effects of this type of movement on annual survival estimation. The first two study designs we investigated involved marking birds in a core area and resighting them in the core as well as an area surrounding the core. For the first of these two designs, we demonstrated that as the resighting area surrounding the core gets progressively larger, and more “emigrants” are resighted, apparent survival estimates begin to approximate true survival rates (bias < 0.01. However, given observed inter–annual movements of birds, it is likely to be logistically impractical to resight birds on sufficiently large
Genomic Selection (GS) is a relatively new technology, which has already revolutionized animal breeding and which is expected to have a high impact on plant breeding. In contrast to traditional marker assisted breeding, which only focuses on specific genes. GS estimates the genetic value...
Strathe, Anders B; Mark, Thomas; Nielsen, Bjarne
Random regression models were used to estimate covariance functions between cumulated feed intake (CFI) and body weight (BW) in 8424 Danish Duroc pigs. Random regressions on second order Legendre polynomials of age were used to describe genetic and permanent environmental curves in BW and CFI...
Lorenz, Aaron J
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
Veronika Ruslanovna Kharzinova
Full Text Available Three semi-domesticated reindeer breeds inhabiting the Republic of Sakha – Yakutia have been characterized using nine microsatellite markers. Genomic DNA was isolated from tissue samples of 123 individuals of the Chukotka (Khargin (CHU, n=47, the Evenk (EVK, n=32 and the Even (EVN, n=44 breeds, collected from different regions of Yakutia. Fragment analysis and sizing were run on ABI 3131xl genetic analyzer. Allele frequencies were calculated and used for the characterization of reindeer breeds and the evaluation of their genetic biodiversity. Nei’s standard genetic distance was calculated and used for the construction of a neighbor-joining tree. Statistical analysis was conducted with GenAIEx 6.5.1, PAST2.15 and STRUCTURE2.3.4 software. The highest number of alleles, such as informative (with a frequency more than 5%, effective (Ne and private (Pr, was detected in the CHU breed: Na≥5%=5.333±0.441, Ne=4.517±0393 and Pr =1.111±0.389, while the EVN breed had the lowest number: 4.778±0.324, 4.315±0.488 and 0.444±0.242, respectively. The EVN breed occupied an intermediate position (5.000±0.373, 4.408±0.315 and 0.889±0.261. Among reindeer breeds, observed heterozygosity ranged from 0.729 ± 0.026 to 0.608±0.050 with the lowest value found in CHU reindeer and the highest in EVK reindeer. A heterozygotes’ deficiency was observed in all reindeer breeds. At K=3, STRUCTURE analysis matches with the data of Nei's genetic distance dimension results, indicating the presence of a common consistent pattern. CHU and EVK reindeer breeds are characterized by a closer genetic relationship in comparison with the EVN breed, which formed a separate cluster.
Wientjes, Yvonne C J; Bijma, Piter; Vandenplas, Jérémie; Calus, Mario P L
Different methods are available to calculate multi-population genomic relationship matrices. Since those matrices differ in base population, it is anticipated that the method used to calculate genomic relationships affects the estimate of genetic variances, covariances, and correlations. The aim of this article is to define the multi-population genomic relationship matrix to estimate current genetic variances within and genetic correlations between populations. The genomic relationship matrix containing two populations consists of four blocks, one block for population 1, one block for population 2, and two blocks for relationships between the populations. It is known, based on literature, that by using current allele frequencies to calculate genomic relationships within a population, current genetic variances are estimated. In this article, we theoretically derived the properties of the genomic relationship matrix to estimate genetic correlations between populations and validated it using simulations. When the scaling factor of across-population genomic relationships is equal to the product of the square roots of the scaling factors for within-population genomic relationships, the genetic correlation is estimated unbiasedly even though estimated genetic variances do not necessarily refer to the current population. When this property is not met, the correlation based on estimated variances should be multiplied by a correction factor based on the scaling factors. In this study, we present a genomic relationship matrix which directly estimates current genetic variances as well as genetic correlations between populations. Copyright © 2017 by the Genetics Society of America.
Full Text Available Abstract The aim of this paper was to compare the effect of haplotype definition on the precision of QTL-mapping and on the accuracy of predicted genomic breeding values. In a multiple QTL model using identity-by-descent (IBD probabilities between haplotypes, various haplotype definitions were tested i.e. including 2, 6, 12 or 20 marker alleles and clustering base haplotypes related with an IBD probability of > 0.55, 0.75 or 0.95. Simulated data contained 1100 animals with known genotypes and phenotypes and 1000 animals with known genotypes and unknown phenotypes. Genomes comprising 3 Morgan were simulated and contained 74 polymorphic QTL and 383 polymorphic SNP markers with an average r2 value of 0.14 between adjacent markers. The total number of haplotypes decreased up to 50% when the window size was increased from two to 20 markers and decreased by at least 50% when haplotypes related with an IBD probability of > 0.55 instead of > 0.95 were clustered. An intermediate window size led to more precise QTL mapping. Window size and clustering had a limited effect on the accuracy of predicted total breeding values, ranging from 0.79 to 0.81. Our conclusion is that different optimal window sizes should be used in QTL-mapping versus genome-wide breeding value prediction.
Full Text Available Hypothyroidism is a complex clinical condition found in both humans and dogs, thought to be caused by a combination of genetic and environmental factors. In this study we present a multi-breed analysis of predisposing genetic risk factors for hypothyroidism in dogs using three high-risk breeds--the Gordon Setter, Hovawart and the Rhodesian Ridgeback. Using a genome-wide association approach and meta-analysis, we identified a major hypothyroidism risk locus shared by these breeds on chromosome 12 (p = 2.1x10(-11. Further characterisation of the candidate region revealed a shared ~167 kb risk haplotype (4,915,018-5,081,823 bp, tagged by two SNPs in almost complete linkage disequilibrium. This breed-shared risk haplotype includes three genes (LHFPL5, SRPK1 and SLC26A8 and does not extend to the dog leukocyte antigen (DLA class II gene cluster located in the vicinity. These three genes have not been identified as candidate genes for hypothyroid disease previously, but have functions that could potentially contribute to the development of the disease. Our results implicate the potential involvement of novel genes and pathways for the development of canine hypothyroidism, raising new possibilities for screening, breeding programmes and treatments in dogs. This study may also contribute to our understanding of the genetic etiology of human hypothyroid disease, which is one of the most common endocrine disorders in humans.
Guo, Gang; Lund, Mogens Sandø; Zhang, Y
genotype. Moreover, the results showed that the correlation between GEBV and conventional parent average (PA) was lower (corresponding to a relatively larger gain by including PA) when using the DYD approach than when using the EBV approach. Consequently, the two approaches led to similar reliability...
Iezzoni, A.F.; Weebadde, C.; Luby, J.; Yue, C.; Weg, van de W.E.; Fazio, G.; Main, D.; Peace, C.P.; Bassil, N.V.; McFerson, J.
Genomics research has not yet been translated into routine practical application in breeding Rosaceae fruit crops (peach, apple, strawberry, cherry, apricot, pear, raspberry, etc.). Through dedicated efforts of many researchers worldwide, a wealth of genomics resources has accumulated, including EST
Lund Mogens S
Full Text Available Abstract Background The use of genomic selection in breeding programs may increase the rate of genetic improvement, reduce the generation time, and provide higher accuracy of estimated breeding values (EBVs. A number of different methods have been developed for genomic prediction of breeding values, but many of them assume that all animals have been genotyped. In practice, not all animals are genotyped, and the methods have to be adapted to this situation. Results In this paper we provide an extension of a linear mixed model method for genomic prediction to the situation with non-genotyped animals. The model specifies that a breeding value is the sum of a genomic and a polygenic genetic random effect, where genomic genetic random effects are correlated with a genomic relationship matrix constructed from markers and the polygenic genetic random effects are correlated with the usual relationship matrix. The extension of the model to non-genotyped animals is made by using the pedigree to derive an extension of the genomic relationship matrix to non-genotyped animals. As a result, in the extended model the estimated breeding values are obtained by blending the information used to compute traditional EBVs and the information used to compute purely genomic EBVs. Parameters in the model are estimated using average information REML and estimated breeding values are best linear unbiased predictions (BLUPs. The method is illustrated using a simulated data set. Conclusions The extension of the method to non-genotyped animals presented in this paper makes it possible to integrate all the genomic, pedigree and phenotype information into a one-step procedure for genomic prediction. Such a one-step procedure results in more accurate estimated breeding values and has the potential to become the standard tool for genomic prediction of breeding values in future practical evaluations in pig and cattle breeding.
Muths, Erin L.; Scherer, Rick D.; Lambert, Brad A.
1. Estimates of demographic parameters for females, in many organisms, are sparse. This is particularly worrisome as more and more species are faced with high extinction probabilities and conservation increasingly depends on actions dictated by complex predictive models that require accurate estimates of demographic parameters for each sex and species.
Doll, Andrew C.; Lanctot, Richard B.; Stricker, Craig A.; Yezerinac, Stephen M.; Wunder, Michael B.
The use of stable isotopes in animal ecology depends on accurate descriptions of isotope dynamics within individuals. The prevailing assumption that laboratory-derived isotopic parameters apply to free-living animals is largely untested. We used stable carbon isotopes (δ13C) in whole blood from migratory Dunlin (Calidris alpina arcticola) to estimate an in situ turnover rate and individual diet-switch dates. Our in situ results indicated that turnover rates were higher in free-living birds, in comparison to the results of an experimental study on captive Dunlin and estimates derived from a theoretical allometric model. Diet-switch dates from all 3 methods were then used to estimate arrival dates to the Arctic; arrival dates calculated with the in situ turnover rate were later than those with the other turnover-rate estimates, substantially so in some cases. These later arrival dates matched dates when local snow conditions would have allowed Dunlin to settle, and agreed with anticipated arrival dates of Dunlin tracked with light-level geolocators. Our study presents a novel method for accurately estimating arrival dates for individuals of migratory species in which return dates are difficult to document. This may be particularly appropriate for species in which extrinsic tracking devices cannot easily be employed because of cost, body size, or behavioral constraints, and in habitats that do not allow individuals to be detected easily upon first arrival. Thus, this isotopic method offers an exciting alternative approach to better understand how species may be altering their arrival dates in response to changing climatic conditions.
Campos, G S; Reimann, F A; Cardoso, L L; Ferreira, C E R; Junqueira, V S; Schmidt, P I; Braccini Neto, J; Yokoo, M J I; Sollero, B P; Boligon, A A; Cardoso, F F
The objective of the present study was to evaluate the accuracy and bias of direct and blended genomic predictions using different methods and cross-validation techniques for growth traits (weight and weight gains) and visual scores (conformation, precocity, muscling and size) obtained at weaning and at yearling in Hereford and Braford breeds. Phenotypic data contained 126,290 animals belonging to the Delta G Connection genetic improvement program, and a set of 3,545 animals genotyped with the 50K chip and 131 sires with the 777K. After quality control, 41,045 markers remained for all animals. An animal model was used to estimate (co)variances components and to predict breeding values, which were later used to calculate the deregressed estimated breeding values (DEBV). Animals with genotype and phenotype for the traits studied were divided into four or five groups by random and k-means clustering cross-validation strategies. The values of accuracy of the direct genomic values (DGV) were moderate to high magnitude for at weaning and at yearling traits, ranging from 0.19 to 0.45 for the k-means and 0.23 to 0.78 for random clustering among all traits. The greatest gain in relation to the pedigree BLUP (PBLUP) was 9.5% with the BayesB method with both the k-means and the random clustering. Blended genomic value accuracies ranged from 0.19 to 0.56 for k-means and from 0.21 to 0.82 for random clustering. The analyzes using the historical pedigree and phenotypes contributed additional information to calculate the GEBV and in general, the largest gains were for the single-step (ssGBLUP) method in bivariate analyses with a mean increase of 43.00% among all traits measured at weaning and of 46.27% for those evaluated at yearling. The accuracy values for the marker effects estimation methods were lower for k-means clustering, indicating that the training set relationship to the selection candidates is a major factor affecting accuracy of genomic predictions. The gains in
Full Text Available Non-additive genetic variation is usually ignored when genome-wide markers are used to study the genetic architecture and genomic prediction of complex traits in human, wild life, model organisms or farm animals. However, non-additive genetic effects may have an important contribution to total genetic variation of complex traits. This study presented a genomic BLUP model including additive and non-additive genetic effects, in which additive and non-additive genetic relation matrices were constructed from information of genome-wide dense single nucleotide polymorphism (SNP markers. In addition, this study for the first time proposed a method to construct dominance relationship matrix using SNP markers and demonstrated it in detail. The proposed model was implemented to investigate the amounts of additive genetic, dominance and epistatic variations, and assessed the accuracy and unbiasedness of genomic predictions for daily gain in pigs. In the analysis of daily gain, four linear models were used: 1 a simple additive genetic model (MA, 2 a model including both additive and additive by additive epistatic genetic effects (MAE, 3 a model including both additive and dominance genetic effects (MAD, and 4 a full model including all three genetic components (MAED. Estimates of narrow-sense heritability were 0.397, 0.373, 0.379 and 0.357 for models MA, MAE, MAD and MAED, respectively. Estimated dominance variance and additive by additive epistatic variance accounted for 5.6% and 9.5% of the total phenotypic variance, respectively. Based on model MAED, the estimate of broad-sense heritability was 0.506. Reliabilities of genomic predicted breeding values for the animals without performance records were 28.5%, 28.8%, 29.2% and 29.5% for models MA, MAE, MAD and MAED, respectively. In addition, models including non-additive genetic effects improved unbiasedness of genomic predictions.
Wei, Zhong; Jousset, Alexandre
Plant breeding has traditionally improved traits encoded in the plant genome. Here we propose an alternative framework reaching novel phenotypes by modifying together genomic information and plant-associated microbiota. This concept is made possible by a novel technology that enables the
Full Text Available In Romania, the Transylvanian Naked Neck hen breed is considered to be an“endangered” population, reason for which we consider that a special attentionshould have been given until now. Plymouth Rock breed was imported for the firsttime to Romania from the Studler Company, France in 1969. This paper is aimingto perform a profound analysis of the development patterns of the neural tube inthe two breeds, by measurements carried out at 30, 40, 50, and 60 hours ofincubation. Observations show that the closure of the neural canal and itstransformation into a tube follows an undulatory pattern, of which positive andnegative curls are diametrically opposed in the two breeds, while the developmentspeed during the whole studied period have a relative similar value between thetwo breeds. We estimate that the two breeds have a good combinative capacity,which recommend the utilization of these genetic materials to obtain hybrids forproducing “peasant-type” chicken meat, very well-appreciated by the Europeansbetween the two World Wars.
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.
Heslot, Nicolas; Rutkoski, Jessica; Poland, Jesse; Jannink, Jean-Luc; Sorrells, Mark E.
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
Bastiaansen, J.W.M.; Bink, M.C.A.M.; Coster, A.; Maliepaard, C.A.; Calus, M.P.L.
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
Full Text Available Maize is one of the most important economic crops and the best studied and most tractable genetic system among monocots. The development of biotechnology has led to a great increase in our knowledge of maize genetics and understanding of the structure and behaviour of maize genomes. Conventional breeding practices can now be complemented by a number of new and powerful techniques. Some of these often referred to as molecular methods, enable scientists to see the layout of the entire genome of any organism and to select plants with preferred characteristics by "reading" at the molecular level, saving precious time and resources. DNA markers have provided valuable tools in various analyses ranging from phylogenetic analysis to the positional cloning of genes. Application of molecular markers for genetic studies of maize include: assessment of genetic variability and characterization of germ plasm, identification and fingerprinting of genotypes, estimation of genetic distance, detection of monogamic and quantitative trait loci, marker assisted selection, identification of sequence of useful candidate genes, etc. The development of high-density molecular maps which has been facilitated by PCR-based markers, have made the mapping and tagging of almost any trait possible and serve as bases for marker assisted selection. Sequencing of maize genomes would help to elucidate gene function, gene regulation and their expression. Modern biotechnology also includes an array of tools for introducing or deieting a particular gene or genes to produce plants with novel traits. Development of informatics and biotechnology are resulted in bioinformatic as well as in expansion of microarrey technique. Modern biotechnologies could complement and improve the efficiency of traditional selection and breeding techniques to enhance agricultural productivity.
Full Text Available The ability to predict gene content is highly desirable for characterization of not-yet sequenced genomes like those of dinoflagellates. Using data from completely sequenced and annotated genomes from phylogenetically diverse lineages, we investigated the relationship between gene content and genome size using regression analyses. Distinct relationships between log(10-transformed protein-coding gene number (Y' versus log(10-transformed genome size (X', genome size in kbp were found for eukaryotes and non-eukaryotes. Eukaryotes best fit a logarithmic model, Y' = ln(-46.200+22.678X', whereas non-eukaryotes a linear model, Y' = 0.045+0.977X', both with high significance (p0.91. Total gene number shows similar trends in both groups to their respective protein coding regressions. The distinct correlations reflect lower and decreasing gene-coding percentages as genome size increases in eukaryotes (82%-1% compared to higher and relatively stable percentages in prokaryotes and viruses (97%-47%. The eukaryotic regression models project that the smallest dinoflagellate genome (3x10(6 kbp contains 38,188 protein-coding (40,086 total genes and the largest (245x10(6 kbp 87,688 protein-coding (92,013 total genes, corresponding to 1.8% and 0.05% gene-coding percentages. These estimates do not likely represent extraordinarily high functional diversity of the encoded proteome but rather highly redundant genomes as evidenced by high gene copy numbers documented for various dinoflagellate species.
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.
Yabe, Shiori; Hara, Takashi; Ueno, Mariko; Enoki, Hiroyuki; Kimura, Tatsuro; Nishimura, Satoru; Yasui, Yasuo; Ohsawa, Ryo; Iwata, Hiroyoshi
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.
Kentie, Rosemarie; Senner, Nathan R.; Hooijmeijer, Jos C.E.W.; Márquez-Ferrando, Rocío; Figuerola, Jordi; Masero, José A.; Verhoeven, Mo A.; Piersma, Theunis
Over the past 50 years, the population of Continental Black-tailed Godwits Limosa limosa limosa breeding of the East Atlantic Flyway has been in steep decline. This decline has previously been documented in trend analyses and six Netherlands-wide count-based population estimates, the last of which
Genomic prediction accounting for genotype by environment interaction offers an effective framework for breeding simultaneously for adaptation to an abiotic stress and performance under normal cropping conditions in rice
Ahmadi, Nourollah; Cao, Tuong-Vi; Valé, Giampiero; Bartholomé, Jérôme; Hassen, Manel
Developing rice varieties adapted to alternate wetting and drying water management is crucial for the sustainability of irrigated rice cropping systems. Here we report the first study exploring the feasibility of breeding rice for adaptation to alternate wetting and drying using genomic prediction methods that account for genotype by environment interactions. Two breeding populations (a reference panel of 284 accessions and a progeny population of 97 advanced lines) were evaluated under alter...
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
Background: Access to sheep genome sequences significantly improves the chances of identifying genes that may influence the health, welfare, and productivity of these animals. Methods: A public, searchable DNA sequence resource for U.S. sheep was created with whole genome sequence (WGS) of 96 rams. ...
Coopman, F.; Smet, S.; Gengler, N.; Haegeman, A.; Jacobs, K.; Poucke, van M.; Laevens, H.; Zeveren, van A.; Groen, A.F.
In the double-muscled (DM) Belgian Blue beef (BBB) breed, caesarean section (CS) is being applied systematically as a management tool to prevent dystocia. As a matter of fact, CS is the only possible way of calving in the breed. High birth weight and a relatively small pelvic area are the main
Liu, Liang; Xi, Zhenxiang; Wu, Shaoyuan; Davis, Charles C; Edwards, Scott V
The heterogeneity of signals in the genomes of diverse organisms poses challenges for traditional phylogenetic analysis. Phylogenetic methods known as "species tree" methods have been proposed to directly address one important source of gene tree heterogeneity, namely the incomplete lineage sorting that occurs when evolving lineages radiate rapidly, resulting in a diversity of gene trees from a single underlying species tree. Here we review theory and empirical examples that help clarify conflicts between species tree and concatenation methods, and misconceptions in the literature about the performance of species tree methods. Considering concatenation as a special case of the multispecies coalescent model helps explain differences in the behavior of the two methods on phylogenomic data sets. Recent work suggests that species tree methods are more robust than concatenation approaches to some of the classic challenges of phylogenetic analysis, including rapidly evolving sites in DNA sequences and long-branch attraction. We show that approaches, such as binning, designed to augment the signal in species tree analyses can distort the distribution of gene trees and are inconsistent. Computationally efficient species tree methods incorporating biological realism are a key to phylogenetic analysis of whole-genome data. © 2015 New York Academy of Sciences.
Stavrovskaya, Elena D; Niranjan, Tejasvi; Fertig, Elana J; Wheelan, Sarah J; Favorov, Alexander V; Mironov, Andrey A
Genomics features with similar genome-wide distributions are generally hypothesized to be functionally related, for example, colocalization of histones and transcription start sites indicate chromatin regulation of transcription factor activity. Therefore, statistical algorithms to perform spatial, genome-wide correlation among genomic features are required. Here, we propose a method, StereoGene, that rapidly estimates genome-wide correlation among pairs of genomic features. These features may represent high-throughput data mapped to reference genome or sets of genomic annotations in that reference genome. StereoGene enables correlation of continuous data directly, avoiding the data binarization and subsequent data loss. Correlations are computed among neighboring genomic positions using kernel correlation. Representing the correlation as a function of the genome position, StereoGene outputs the local correlation track as part of the analysis. StereoGene also accounts for confounders such as input DNA by partial correlation. We apply our method to numerous comparisons of ChIP-Seq datasets from the Human Epigenome Atlas and FANTOM CAGE to demonstrate its wide applicability. We observe the changes in the correlation between epigenomic features across developmental trajectories of several tissue types consistent with known biology and find a novel spatial correlation of CAGE clusters with donor splice sites and with poly(A) sites. These analyses provide examples for the broad applicability of StereoGene for regulatory genomics. The StereoGene C ++ source code, program documentation, Galaxy integration scripts and examples are available from the project homepage http://stereogene.bioinf.fbb.msu.ru/. firstname.lastname@example.org. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: email@example.com
Vandenplas, Jérémie; Calus, Mario P L; Sevillano, Claudia A; Windig, Jack J; Bastiaansen, John W M
For some species, animal production systems are based on the use of crossbreeding to take advantage of the increased performance of crossbred compared to purebred animals. Effects of single nucleotide polymorphisms (SNPs) may differ between purebred and crossbred animals for several reasons: (1) differences in linkage disequilibrium between SNP alleles and a quantitative trait locus; (2) differences in genetic backgrounds (e.g., dominance and epistatic interactions); and (3) differences in environmental conditions, which result in genotype-by-environment interactions. Thus, SNP effects may be breed-specific, which has led to the development of genomic evaluations for crossbred performance that take such effects into account. However, to estimate breed-specific effects, it is necessary to know breed origin of alleles in crossbred animals. Therefore, our aim was to develop an approach for assigning breed origin to alleles of crossbred animals (termed BOA) without information on pedigree and to study its accuracy by considering various factors, including distance between breeds. The BOA approach consists of: (1) phasing genotypes of purebred and crossbred animals; (2) assigning breed origin to phased haplotypes; and (3) assigning breed origin to alleles of crossbred animals based on a library of assigned haplotypes, the breed composition of crossbred animals, and their SNP genotypes. The accuracy of allele assignments was determined for simulated datasets that include crosses between closely-related, distantly-related and unrelated breeds. Across these scenarios, the percentage of alleles of a crossbred animal that were correctly assigned to their breed origin was greater than 90 %, and increased with increasing distance between breeds, while the percentage of incorrectly assigned alleles was always less than 2 %. For the remaining alleles, i.e. 0 to 10 % of all alleles of a crossbred animal, breed origin could not be assigned. The BOA approach accurately assigns
Gillentine, Madelyn A; Lupo, Philip J; Stankiewicz, Pawel; Schaaf, Christian P
Multiple genomic disorders result from recurrent deletions or duplications between low copy repeat (LCR) clusters, mediated by nonallelic homologous recombination. These copy number variants (CNVs) often exhibit variable expressivity and/or incomplete penetrance. However, the population prevalence of many genomic disorders has not been estimated accurately. A subset of genomic disorders similarly characterized by CNVs between LCRs have been studied epidemiologically, including Williams-Beuren syndrome (7q11.23), Smith-Magenis syndrome (17p11.2), velocardiofacial syndrome (22q11.21), Prader-Willi/Angelman syndromes (15q11.2q12), 17q12 deletion syndrome, and Charcot-Marie-Tooth neuropathy type 1/hereditary neuropathy with liability to pressure palsy (PMP22, 17q11.2). We have generated a method to estimate prevalence of highly penetrant genomic disorders by (1) leveraging epidemiological data for genomic disorders with previously reported prevalence estimates, (2) obtaining chromosomal microarray data on genomic disorders from a large medical genetics clinic; and (3) utilizing these in a linear regression model to determine the prevalence of this syndromic copy number change among the general population. Using our algorithm, the prevalence for five clinically relevant recurrent genomic disorders: 1q21.1 microdeletion (1/6882 live births) and microduplication syndromes (1/6309), 15q13.3 microdeletion syndrome (1/5525), and 16p11.2 microdeletion (1/3021) and microduplication syndromes (1/4216), were determined. These findings will inform epidemiological strategies for evaluating those conditions, and our method may be useful to evaluate the prevalence of other highly penetrant genomic disorders.
Christensen Ole F
Full Text Available Abstract Background Genomic data are used in animal breeding to assist genetic evaluation. Several models to estimate genomic breeding values have been studied. In general, two approaches have been used. One approach estimates the marker effects first and then, genomic breeding values are obtained by summing marker effects. In the second approach, genomic breeding values are estimated directly using an equivalent model with a genomic relationship matrix. Allele coding is the method chosen to assign values to the regression coefficients in the statistical model. A common allele coding is zero for the homozygous genotype of the first allele, one for the heterozygote, and two for the homozygous genotype for the other allele. Another common allele coding changes these regression coefficients by subtracting a value from each marker such that the mean of regression coefficients is zero within each marker. We call this centered allele coding. This study considered effects of different allele coding methods on inference. Both marker-based and equivalent models were considered, and restricted maximum likelihood and Bayesian methods were used in inference. Results Theoretical derivations showed that parameter estimates and estimated marker effects in marker-based models are the same irrespective of the allele coding, provided that the model has a fixed general mean. For the equivalent models, the same results hold, even though different allele coding methods lead to different genomic relationship matrices. Calculated genomic breeding values are independent of allele coding when the estimate of the general mean is included into the values. Reliabilities of estimated genomic breeding values calculated using elements of the inverse of the coefficient matrix depend on the allele coding because different allele coding methods imply different models. Finally, allele coding affects the mixing of Markov chain Monte Carlo algorithms, with the centered coding being
Barabaschi, Delfina; Tondelli, Alessandro; Desiderio, Francesca; Volante, Andrea; Vaccino, Patrizia; Valè, Giampiero; Cattivelli, Luigi
The genomic revolution of the past decade has greatly improved our understanding of the genetic make-up of living organisms. The sequencing of crop genomes has completely changed our vision and interpretation of genome organization and evolution. Re-sequencing allows the identification of an unlimited number of markers as well as the analysis of germplasm allelic diversity based on allele mining approaches. High throughput marker technologies coupled with advanced phenotyping platforms provide new opportunities for discovering marker-trait associations which can sustain genomic-assisted breeding. The availability of genome sequencing information is enabling genome editing (site-specific mutagenesis), to obtain gene sequences desired by breeders. This review illustrates how next generation sequencing-derived information can be used to tailor genomic tools for different breeders' needs to revolutionize crop improvement. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Full Text Available Abstract Background In this study we compare outlier loci detected using a FST based method with those identified by a recently described method based on spatial analysis (SAM. We tested a panel of single nucleotide polymorphisms (SNPs previously genotyped in individuals of goat breeds of southern areas of the Mediterranean basin (Italy, Greece and Albania. We evaluate how the SAM method performs with SNPs, which are increasingly employed due to their high number, low cost and easy of scoring. Results The combined use of the two outlier detection approaches, never tested before using SNP polymorphisms, resulted in the identification of the same three loci involved in milk and meat quality data by using the two methods, while the FST based method identified 3 more loci as under selection sweep in the breeds examined. Conclusion Data appear congruent by using the two methods for FST values exceeding the 99% confidence limits. The methods of FST and SAM can independently detect signatures of selection and therefore can reduce the probability of finding false positives if employed together. The outlier loci identified in this study could indicate adaptive variation in the analysed species, characterized by a large range of climatic conditions in the rearing areas and by a history of intense trade, that implies plasticity in adapting to new environments.
Full Text Available Two methods of SNPs pre-selection based on single marker regression for the estimation of genomic breeding values (G-EBVs were compared using simulated data provided by the XII QTL-MAS workshop: i Bonferroni correction of the significance threshold and ii Permutation test to obtain the reference distribution of the null hypothesis and identify significant markers at P<0.01 and P<0.001 significance thresholds. From the set of markers significant at P<0.001, random subsets of 50% and 25% markers were extracted, to evaluate the effect of further reducing the number of significant SNPs on G-EBV predictions. The Bonferroni correction method allowed the identification of 595 significant SNPs that gave the best G-EBV accuracies in prediction generations (82.80%. The permutation methods gave slightly lower G-EBV accuracies even if a larger number of SNPs resulted significant (2,053 and 1,352 for 0.01 and 0.001 significance thresholds, respectively. Interestingly, halving or dividing by four the number of SNPs significant at P<0.001 resulted in an only slightly decrease of G-EBV accuracies. The genetic structure of the simulated population with few QTL carrying large effects, might have favoured the Bonferroni method.
Oldenbroek, Kor; Waaij, van der Liesbeth
This textbook contains teaching material on animal breeding and genetics for BSc students. The text book started as an initiative of the Dutch Universities for Applied (Agricultural) Sciences. The textbook is made available by the Animal Breeding and Genomics Centre (ABGC) of Wageningen UR
Jia, Qiang; Koyama, Kazuo; Choi, Chang-Yong
For the first time, we estimated the population sizes of two swan species and four goose species from observations during the non-breeding period in East Asia. Based on combined counts from South Korea, Japan and China, we estimated the total abundance of these species as follows: 42,000–47,000 W......For the first time, we estimated the population sizes of two swan species and four goose species from observations during the non-breeding period in East Asia. Based on combined counts from South Korea, Japan and China, we estimated the total abundance of these species as follows: 42......,000–47,000 Whooper Swans Cygnus cygnus ; 99,000–141,000 Tundra Swans C. columbianus bewickii ; 56,000–98,000 Swan Geese Anser cygnoides ; 157,000–194,000 Bean Geese A. fabalis ; 231,000–283,000 Greater White-fronted Geese A. albifrons ; and 14,000–19,000 Lesser White-fronted Geese A. erythropus. While the count data...... from Korea and Japan provide a good reflection of numbers present, there remain gaps in the coverage in China, which particularly affect the precision of the estimates for Bean, Greater and Lesser White-fronted Geese as well as Tundra Swans. Lack of subspecies distinction of Bean Geese in China until...
Li, Heng-De; Bao, Zhen-Min; Sun, Xiao-Wen
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.
Full Text Available Prunus rootstock is an important choice in optimizing productivity of grafted cultivars. Nevertheless, many Prunus rootstocks are notoriously intolerant to hypoxia which is caused by waterlogging and/or heavy soils. There is no available information to help select Prunus rootstocks that are tolerant to stress conditions such as root hypoxia caused by excess moisture. Information from genetic maps has demonstrated a high level of synteny among Prunus species, and this suggests that they all share a similar genomic structure. It should be possible to identify the genetic determinants involved in tolerance to hypoxia and other traits in Prunus rootstocks by applying methods to identify regions of the genome involved in the expression of important traits; these have been developed mainly in peach which is the model species for the genus. Molecular markers that are tightly linked to major genes would be useful in marker-assisted selection (MAS to optimize new rootstock selection. This article provides insight on the advances in the development of molecular markers, genetic maps, and gene identification in Prunus, mainly in peach; the aim is to provide a general approach for identifying the genetic determinants of hypoxia stress in rootstocks.
Full Text Available Maintaining genetic variation and controlling the increase in inbreeding are crucial requirements in animal conservation programs. The most widely accepted strategy for achieving these objectives is to maximize the effective population size by minimizing the global coancestry obtained from a particular pedigree. However, for most natural or captive populations genealogical information is absent. In this situation, microsatellites have been traditionally the markers of choice to characterize genetic variation, and several estimators of genealogical coefficients have been developed using marker data, with unsatisfactory results. The development of high-throughput genotyping techniques states the necessity of reviewing the paradigm that genealogical coancestry is the best parameter for measuring genetic diversity. In this study, the Illumina PorcineSNP60 BeadChip was used to obtain genome-wide estimates of rates of coancestry and inbreeding and effective population size for an ancient strain of Iberian pigs that is now in serious danger of extinction and for which very accurate genealogical information is available (the Guadyerbas strain. Genome-wide estimates were compared with those obtained from microsatellite and from pedigree data. Estimates of coancestry and inbreeding computed from the SNP chip were strongly correlated with genealogical estimates and these correlations were substantially higher than those between microsatellite and genealogical coefficients. Also, molecular coancestry computed from SNP information was a better predictor of genealogical coancestry than coancestry computed from microsatellites. Rates of change in coancestry and inbreeding and effective population size estimated from molecular data were very similar to those estimated from genealogical data. However, estimates of effective population size obtained from changes in coancestry or inbreeding differed. Our results indicate that genome-wide information represents a
Srivastava, Rishi; Bajaj, Deepak; Sayal, Yogesh K; Meher, Prabina K; Upadhyaya, Hari D; Kumar, Rajendra; Tripathi, Shailesh; Bharadwaj, Chellapilla; Rao, Atmakuri R; Parida, Swarup K
The discovery and large-scale genotyping of informative gene-based markers is essential for rapid delineation of genes/QTLs governing stress tolerance and yield component traits in order to drive genetic enhancement in chickpea. A genome-wide 119169 and 110491 ISM (intron-spanning markers) from 23129 desi and 20386 kabuli protein-coding genes and 7454 in silico InDel (insertion-deletion) (1-45-bp)-based ILP (intron-length polymorphism) markers from 3283 genes were developed that were structurally and functionally annotated on eight chromosomes and unanchored scaffolds of chickpea. A much higher amplification efficiency (83%) and intra-specific polymorphic potential (86%) detected by these markers than that of other sequence-based genetic markers among desi and kabuli chickpea accessions was apparent even by a cost-effective agarose gel-based assay. The genome-wide physically mapped 1718 ILP markers assayed a wider level of functional genetic diversity (19-81%) and well-defined phylogenetics among domesticated chickpea accessions. The gene-derived 1424 ILP markers were anchored on a high-density (inter-marker distance: 0.65cM) desi intra-specific genetic linkage map/functional transcript map (ICC 4958×ICC 2263) of chickpea. This reference genetic map identified six major genomic regions harbouring six robust QTLs mapped on five chromosomes, which explained 11-23% seed weight trait variation (7.6-10.5 LOD) in chickpea. The integration of high-resolution QTL mapping with differential expression profiling detected six including one potential serine carboxypeptidase gene with ILP markers (linked tightly to the major seed weight QTLs) exhibiting seed-specific expression as well as pronounced up-regulation especially in seeds of high (ICC 4958) as compared to low (ICC 2263) seed weight mapping parental accessions. The marker information generated in the present study was made publicly accessible through a user-friendly web-resource, "Chickpea ISM-ILP Marker Database
Full Text Available The research was carried out on 4,030 Polish Merino ewes born in the years 1991- 2001, kept in 15 flocks from the Pomorze and Kujawy region. Fertility of ewes in subsequent reproduction seasons was analysed with the use of multiple logistic regression. The research showed that there is a statistical influence of the flock, year of birth, age of dam, flock year interaction of birth on the ewes fertility. In order to estimate the genetic parameters, the Gibbs sampling method was applied, using the univariate animal models, both linear as well as threshold. Estimates of fertility depending on the model equalled 0.067 to 0.104, whereas the estimates of repeatability equalled respectively: 0.076 and 0.139. The obtained genetic parameters were then used to estimate the breeding values of the animals in terms of controlled trait (Best Linear Unbiased Prediction method using linear and threshold models. The obtained animal breeding values rankings in respect of the same trait with the use of linear and threshold models were strongly correlated with each other (rs = 0.972. Negative genetic trends of fertility (0.01-0.08% per year were found.
Full Text Available Domestic cats have a unique breeding history and can be used as models for human hereditary and infectious diseases. In the current era of genome-wide association studies, insights regarding linkage disequilibrium (LD are essential for efficient association studies. The objective of this study is to investigate the extent of LD in the domestic cat, Felis silvestris catus, particularly within its breeds. A custom illumina GoldenGate Assay consisting of 1536 single nucleotide polymorphisms (SNPs equally divided over ten 1 Mb chromosomal regions was developed, and genotyped across 18 globally recognized cat breeds and two distinct random bred populations. The pair-wise LD descriptive measure (r(2 was calculated between the SNPs in each region and within each population independently. LD decay was estimated by determining the non-linear least-squares of all pair-wise estimates as a function of distance using established models. The point of 50% decay of r(2 was used to compare the extent of LD between breeds. The longest extent of LD was observed in the Burmese breed, where the distance at which r(2 ≈ 0.25 was ∼380 kb, comparable to several horse and dog breeds. The shortest extent of LD was found in the Siberian breed, with an r(2 ≈ 0.25 at approximately 17 kb, comparable to random bred cats and human populations. A comprehensive haplotype analysis was also conducted. The haplotype structure of each region within each breed mirrored the LD estimates. The LD of cat breeds largely reflects the breeds' population history and breeding strategies. Understanding LD in diverse populations will contribute to an efficient use of the newly developed SNP array for the cat in the design of genome-wide association studies, as well as to the interpretation of results for the fine mapping of disease and phenotypic traits.
Full Text Available The paper goal was to set up a simplified BLUP model in order to estimate the bulls' breeding value for milk production characters and establish their hierarchy, Also, it aimed to compare the bulls' hierarchy set up by means of the simplified BLUP model with their hierarchy established by using the traditional contemporary comparison method. In this purpose, a number of 51 Romanian Friesian bulls were used for evaluating their breeding value for milk production characters: milk yield, fat percentage and fat yield during the 305 days of the 1st lactation of a number of 1,989 daughters in various dairy herds. The simplified BLUP model set up in this research work has demonstrated its high precision of breeding value, which varied between 55 and 92, and more than this it proved that in some cases, the position occupied by bulls could be similar with the one registered by using the contemporary comparison. The higher precision assured by the simplified BLUP model is the guarantee that the bulls' hierarchy in catalogues is a correct one. In this way, farmers could chose the best bulls for improving milk yield in their dairy herds.
Magretha D. Pierce
Full Text Available Copy number variations (CNVs comprise deletions, duplications, and insertions found within the genome larger than 50 bp in size. CNVs are thought to be primary role-players in breed formation and adaptation. South Africa boasts a diverse ecology with harsh environmental conditions and a broad spectrum of parasites and diseases that pose challenges to livestock production. This has led to the development of composite cattle breeds which combine the hardiness of Sanga breeds and the production potential of the Taurine breeds. The prevalence of CNVs within these respective breeds of cattle and the prevalence of CNV regions (CNVRs in their diversity, adaptation and production is however not understood. This study therefore aimed to ascertain the prevalence, diversity, and correlations of CNVRs within cattle breeds used in South Africa. Illumina Bovine SNP50 data and PennCNV were utilized to identify CNVRs within the genome of 287 animals from seven cattle breeds representing Sanga, Taurine, Composite, and cross breeds. Three hundred and fifty six CNVRs of between 36 kb to 4.1 Mb in size were identified. The null hypothesis that one CNVR loci is independent of another was tested using the GENEPOP software. One hunded and two and seven of the CNVRs in the Taurine and Sanga/Composite cattle breeds demonstrated a significant (p ≤ 0.05 association. PANTHER overrepresentation analyses of correlated CNVRs demonstrated significant enrichment of a number of biological processes, molecular functions, cellular components, and protein classes. CNVR genetic variation between and within breed group was measured using phiPT which allows intra-individual variation to be suppressed and hence proved suitable for measuring binary CNVR presence/absence data. Estimate PhiPT within and between breed variance was 2.722 and 0.518 respectively. Pairwise population PhiPT values corresponded with breed type, with Taurine Holstein and Angus breeds demonstrating no between
Desta, Zeratsion Abera; Ortiz, Rodomiro
Association analysis is used to measure relations between markers and quantitative trait loci (QTL). Their estimation ignores genes with small effects that trigger underpinning quantitative traits. By contrast, genome-wide selection estimates marker effects across the whole genome on the target population based on a prediction model developed in the training population (TP). Whole-genome prediction models estimate all marker effects in all loci and capture small QTL effects. Here, we review several genomic selection (GS) models with respect to both the prediction accuracy and genetic gain from selection. Phenotypic selection or marker-assisted breeding protocols can be replaced by selection, based on whole-genome predictions in which phenotyping updates the model to build up the prediction accuracy. Copyright © 2014 Elsevier Ltd. All rights reserved.
Friggens, N C; Badsberg, J H
The objectives of this study were to see if the body condition score curve during lactation could be described using a model amenable to biological interpretation, a non-linear function assuming exponential rates of change in body condition with time, and to quantify the effect of breed and parity on curves of body condition during lactation. Three breeds were represented: Danish Holstein (n = 112), Danish Red (n = 97) and Jerseys (n = 8). Cows entered the experiment at the start of first lactation and were studied during consecutive lactations (average number of lactations 2, minimum 1, maximum 3). They remained on the same dietary treatment throughout. Body condition was scored to the nearest half unit on the Danish scale (see Kristensen (1986); derived from the Lowman et al. (1976) system) from 1 to 5 on days: 2, 14, 28, 42, 56, 84, 112, 168, 224 after calving. Additionally, condition score was recorded on the day of drying off the cow, 35, 21, and 7 days before expected calving and finally on the day of calving. All condition scores were made by the trained personal on the research farm, where the same person made 92% of the scores. The temporal patterns in condition score were modelled as consisting of two underlying processes, one related to days from calving, referred to as lactation only, the other to days from (subsequent) conception, referred to as pregnancy. Both processes were assumed to be exponential functions of time. Each process was modelled separately using exponential functions, i.e. one model for lactation only and one for pregnancy, and then a combined model for both lactation only and pregnancy was fitted. The data set contained 467 lactation periods and 378 pregnancy periods. The temporal patterns in condition score of cows kept under stable and sufficient nutritional conditions were successfully described using a two component non-linear function. First lactation cows had shallower curves, they had greater condition scores at the nadir
Full Text Available Abstract Background Extensive computational and database tools are available to mine genomic and genetic databases for model organisms, but little genomic data is available for many species of ecological or agricultural significance, especially those with large genomes. Genome surveys using conventional sequencing techniques are powerful, particularly for detecting sequences present in many copies per genome. However these methods are time-consuming and have potential drawbacks. High throughput 454 sequencing provides an alternative method by which much information can be gained quickly and cheaply from high-coverage surveys of genomic DNA. Results We sequenced 78 million base-pairs of randomly sheared soybean DNA which passed our quality criteria. Computational analysis of the survey sequences provided global information on the abundant repetitive sequences in soybean. The sequence was used to determine the copy number across regions of large genomic clones or contigs and discover higher-order structures within satellite repeats. We have created an annotated, online database of sequences present in multiple copies in the soybean genome. The low bias of pyrosequencing against repeat sequences is demonstrated by the overall composition of the survey data, which matches well with past estimates of repetitive DNA content obtained by DNA re-association kinetics (Cot analysis. Conclusion This approach provides a potential aid to conventional or shotgun genome assembly, by allowing rapid assessment of copy number in any clone or clone-end sequence. In addition, we show that partial sequencing can provide access to partial protein-coding sequences.
This paper reviews the historical work on slave breeding in the ante-bellum United States. Slave breeding consisted of interference in the sexual life of slaves by their owners with the intent and result of increasing the number of slave children born. The weight of evidence suggests that slave breeding occurred in sufficient force to raise the rate of growth of the American slave population despite evidence that only a minority of slave-owners engaged in such practices.
Gregory, T Ryan; Nathwani, Paula; Bonnett, Tiffany R; Huber, Dezene P W
A study was undertaken to evaluate both a pre-existing method and a newly proposed approach for the estimation of nuclear genome sizes in arthropods. First, concerns regarding the reliability of the well-established method of flow cytometry relating to impacts of rearing conditions on genome size estimates were examined. Contrary to previous reports, a more carefully controlled test found negligible environmental effects on genome size estimates in the fly Drosophila melanogaster. Second, a more recently touted method based on quantitative real-time PCR (qPCR) was examined in terms of ease of use, efficiency, and (most importantly) accuracy using four test species: the flies Drosophila melanogaster and Musca domestica and the beetles Tribolium castaneum and Dendroctonus ponderosa. The results of this analysis demonstrated that qPCR has the tendency to produce substantially different genome size estimates from other established techniques while also being far less efficient than existing methods.
Soliman, Essam S; Moawed, Sherif A; Hassan, Rania A
Birds litter contains unutilized nitrogen in the form of uric acid that is converted into ammonia; a fact that does not only affect poultry performance but also has a negative effect on people's health around the farm and contributes in the environmental degradation. The influence of microclimatic ammonia emissions on Ross and Hubbard broilers reared in different housing systems at two consecutive seasons (fall and winter) was evaluated using a discriminant function analysis to differentiate between Ross and Hubbard breeds. A total number of 400 air samples were collected and analyzed for ammonia levels during the experimental period. Data were analyzed using univariate and multivariate statistical methods. Ammonia levels were significantly higher (p0.05) were found between the two farms in body weight, body weight gain, feed intake, feed conversion ratio, and performance index (PI) of broilers. Body weight; weight gain and PI had increased values (pbroiler breed. Ammonia emissions were positively (although weekly) correlated with the ambient relative humidity (r=0.383; p0.05). Test of significance of discriminant function analysis did not show a classification based on the studied traits suggesting that they cannot been used as predictor variables. The percentage of correct classification was 52% and it was improved after deletion of highly correlated traits to 57%. The study revealed that broiler's growth was negatively affected by increased microclimatic ammonia concentrations and recommended the analysis of broilers' growth performance parameters data using multivariate discriminant function analysis.
Background Discerning the traits evolving under neutral conditions from those traits evolving rapidly because of various selection pressures is a great challenge. We propose a new method, composite selection signals (CSS), which unifies the multiple pieces of selection evidence from the rank distribution of its diverse constituent tests. The extreme CSS scores capture highly differentiated loci and underlying common variants hauling excess haplotype homozygosity in the samples of a target population. Results The data on high-density genotypes were analyzed for evidence of an association with either polledness or double muscling in various cohorts of cattle and sheep. In cattle, extreme CSS scores were found in the candidate regions on autosome BTA-1 and BTA-2, flanking the POLL locus and MSTN gene, for polledness and double muscling, respectively. In sheep, the regions with extreme scores were localized on autosome OAR-2 harbouring the MSTN gene for double muscling and on OAR-10 harbouring the RXFP2 gene for polledness. In comparison to the constituent tests, there was a partial agreement between the signals at the four candidate loci; however, they consistently identified additional genomic regions harbouring no known genes. Persuasively, our list of all the additional significant CSS regions contains genes that have been successfully implicated to secondary phenotypic diversity among several subpopulations in our data. For example, the method identified a strong selection signature for stature in cattle capturing selective sweeps harbouring UQCC-GDF5 and PLAG1-CHCHD7 gene regions on BTA-13 and BTA-14, respectively. Both gene pairs have been previously associated with height in humans, while PLAG1-CHCHD7 has also been reported for stature in cattle. In the additional analysis, CSS identified significant regions harbouring multiple genes for various traits under selection in European cattle including polledness, adaptation, metabolism, growth rate, stature
Ito, Tetsuya; Fukawa, Kazuo; Kamikawa, Mai; Nikaidou, Satoshi; Taniguchi, Masaaki; Arakawa, Aisaku; Tanaka, Genki; Mikawa, Satoshi; Furukawa, Tsutomu; Hirose, Kensuke
Daily feed intake (DFI) is an important consideration for improving feed efficiency, but measurements using electronic feeder systems contain many missing and incorrect values. Therefore, we evaluated three methods for correcting missing DFI data (quadratic, orthogonal polynomial, and locally weighted (Loess) regression equations) and assessed the effects of these missing values on the genetic parameters and the estimated breeding values (EBV) for feeding traits. DFI records were obtained from 1622 Duroc pigs, comprising 902 individuals without missing DFI and 720 individuals with missing DFI. The Loess equation was the most suitable method for correcting the missing DFI values in 5-50% randomly deleted datasets among the three equations. Both variance components and heritability for the average DFI (ADFI) did not change because of the missing DFI proportion and Loess correction. In terms of rank correlation and information criteria, Loess correction improved the accuracy of EBV for ADFI compared to randomly deleted cases. These findings indicate that the Loess equation is useful for correcting missing DFI values for individual pigs and that the correction of missing DFI values could be effective for the estimation of breeding values and genetic improvement using EBV for feeding traits. © 2017 The Authors. Animal Science Journal published by John Wiley & Sons Australia, Ltd on behalf of Japanese Society of Animal Science.
Ghosh, Debashis; Chinnaiyan, Arul M
In most analyses of large-scale genomic data sets, differential expression analysis is typically assessed by testing for differences in the mean of the distributions between 2 groups. A recent finding by Tomlins and others (2005) is of a different type of pattern of differential expression in which a fraction of samples in one group have overexpression relative to samples in the other group. In this work, we describe a general mixture model framework for the assessment of this type of expression, called outlier profile analysis. We start by considering the single-gene situation and establishing results on identifiability. We propose 2 nonparametric estimation procedures that have natural links to familiar multiple testing procedures. We then develop multivariate extensions of this methodology to handle genome-wide measurements. The proposed methodologies are compared using simulation studies as well as data from a prostate cancer gene expression study.
Lee, S Hong; Ripke, Stephan; Neale, Benjamin M
Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases...... and controls in schizophrenia, bipolar disorder, major depressive disorder, autism spectrum disorders (ASD) and attention-deficit/hyperactivity disorder (ADHD). We apply univariate and bivariate methods for the estimation of genetic variation within and covariation between disorders. SNPs explained 17......-29% of the variance in liability. The genetic correlation calculated using common SNPs was high between schizophrenia and bipolar disorder (0.68 ± 0.04 s.e.), moderate between schizophrenia and major depressive disorder (0.43 ± 0.06 s.e.), bipolar disorder and major depressive disorder (0.47 ± 0.06 s.e.), and ADHD...
Castel, Guillaume; Tordo, Noël; Plyusnin, Alexander
Because of the great variability of their reservoir hosts, hantaviruses are excellent models to evaluate the dynamics of virus-host co-evolution. Intriguing questions remain about the timescale of the diversification events that influenced this evolution. In this paper we attempted to estimate the first ever timing of hantavirus diversification based on thirty five available complete genomes representing five major groups of hantaviruses and the assumption of co-speciation of hantaviruses with their respective mammal hosts. Phylogenetic analyses were used to estimate the main diversification points during hantavirus evolution in mammals while host diversification was mostly estimated from independent calibrators taken from fossil records. Our results support an earlier developed hypothesis of co-speciation of known hantaviruses with their respective mammal hosts and hence a common ancestor for all hantaviruses carried by placental mammals. Copyright © 2017 Elsevier B.V. All rights reserved.
Soliman, Essam S.; Moawed, Sherif A.; Hassan, Rania A.
Background and Aim: Birds litter contains unutilized nitrogen in the form of uric acid that is converted into ammonia; a fact that does not only affect poultry performance but also has a negative effect on people’s health around the farm and contributes in the environmental degradation. The influence of microclimatic ammonia emissions on Ross and Hubbard broilers reared in different housing systems at two consecutive seasons (fall and winter) was evaluated using a discriminant function analysis to differentiate between Ross and Hubbard breeds. Materials and Methods: A total number of 400 air samples were collected and analyzed for ammonia levels during the experimental period. Data were analyzed using univariate and multivariate statistical methods. Results: Ammonia levels were significantly higher (p0.05) were found between the two farms in body weight, body weight gain, feed intake, feed conversion ratio, and performance index (PI) of broilers. Body weight; weight gain and PI had increased values (pbroiler breed. Ammonia emissions were positively (although weekly) correlated with the ambient relative humidity (r=0.383; p0.05). Test of significance of discriminant function analysis did not show a classification based on the studied traits suggesting that they cannot been used as predictor variables. The percentage of correct classification was 52% and it was improved after deletion of highly correlated traits to 57%. Conclusion: The study revealed that broiler’s growth was negatively affected by increased microclimatic ammonia concentrations and recommended the analysis of broilers’ growth performance parameters data using multivariate discriminant function analysis. PMID:28919677
Full Text Available BACKGROUND: Aspen naturally grows in large, single-species, even-aged stands that regenerate clonally after fire disturbance. This offers an opportunity for an intensive clonal forestry system that closely emulates the natural life history of the species. In this paper, we assess the potential of genetic tree improvement and clonal deployment to enhance the productivity of aspen forests in Alberta. We further investigate geographic patterns of genetic variation in aspen and infer forest management strategies under uncertain future climates. METHODOLOGY/PRINCIPAL FINDINGS: Genetic variation among 242 clones from Alberta was evaluated in 13 common garden trials after 5-8 growing seasons in the field. Broad-sense heritabilities for height and diameter at breast height (DBH ranged from 0.36 to 0.64, allowing 5-15% genetic gains in height and 9-34% genetic gains in DBH. Geographic partitioning of genetic variance revealed predominant latitudinal genetic differentiation. We further observed that northward movement of clones almost always resulted in increased growth relative to local planting material, while southward movement had a strong opposite effect. CONCLUSION/SIGNIFICANCE: Aspen forests are an important natural resource in western Canada that is used for pulp and oriented strandboard production, accounting for ~40% of the total forest harvest. Moderate to high broad-sense heritabilities in growth traits suggest good potential for a genetic tree improvement program with aspen. Significant productivity gains appear possible through clonal selection from existing trials. We propose two breeding regions for Alberta, and suggest that well-tested southern clones may be used in the northern breeding region, accounting for a general warming trend observed over the last several decades in Alberta.
Gylander, Tim; Hamann, Andreas; Brouard, Jean S.; Thomas, Barb R.
Background Aspen naturally grows in large, single-species, even-aged stands that regenerate clonally after fire disturbance. This offers an opportunity for an intensive clonal forestry system that closely emulates the natural life history of the species. In this paper, we assess the potential of genetic tree improvement and clonal deployment to enhance the productivity of aspen forests in Alberta. We further investigate geographic patterns of genetic variation in aspen and infer forest management strategies under uncertain future climates. Methodology/Principal Findings Genetic variation among 242 clones from Alberta was evaluated in 13 common garden trials after 5–8 growing seasons in the field. Broad-sense heritabilities for height and diameter at breast height (DBH) ranged from 0.36 to 0.64, allowing 5–15% genetic gains in height and 9–34% genetic gains in DBH. Geographic partitioning of genetic variance revealed predominant latitudinal genetic differentiation. We further observed that northward movement of clones almost always resulted in increased growth relative to local planting material, while southward movement had a strong opposite effect. Conclusion/Significance Aspen forests are an important natural resource in western Canada that is used for pulp and oriented strandboard production, accounting for ∼40% of the total forest harvest. Moderate to high broad-sense heritabilities in growth traits suggest good potential for a genetic tree improvement program with aspen. Significant productivity gains appear possible through clonal selection from existing trials. We propose two breeding regions for Alberta, and suggest that well-tested southern clones may be used in the northern breeding region, accounting for a general warming trend observed over the last several decades in Alberta. PMID:22957006
Stella, Judith L; Bauer, Amy E; Croney, Candace C
The objectives of this cross-sectional study were: 1) to estimate the prevalence and characterize the severity of periodontal disease in a population of dogs housed in commercial breeding facilities; 2) to characterize PD preventive care utilized by facility owners; and 3) to assess inter-rater reliability of a visual scoring assessment tool. Adult dogs (N = 445) representing 42 breeds at 24 CB facilities in Indiana and Illinois were assessed. Periodontal disease was scored visually using the American Veterinary Dental Collage 0-IV scale. Inter-rater reliability was assessed on 198 dogs and facility owners were asked to provide information about the preventive care utilized. The overall prevalence of periodontal disease (Grades I-IV) was 86.3% (95% CI: 82.9, 89.3). An ordered logistic regression analysis found age (OR = 1.4; 95% CI 1.24, 1.54; Pperiodontal disease increased with increasing age. Additionally, a trend toward decreasing risk with increasing weight was also found, although it was not statistically significant. The trends identified agree with studies that have evaluated periodontal disease in the companion dog population and do not support the assumption that the dental health of dogs in commercial breeding facilities is worse than that of the population as a whole. Although there were few cases of severe periodontal disease and all facilities employed some type of preventive care in this sample, the large number of dogs with some degree of disease (Grades I-IV) suggests that further investigation of preventive care is warranted.
Summary: READSCAN is a highly scalable parallel program to identify non-host sequences (of potential pathogen origin) and estimate their genome relative abundance in high-throughput sequence datasets. READSCAN accurately classified human and viral sequences on a 20.1 million reads simulated dataset in <27 min using a small Beowulf compute cluster with 16 nodes (Supplementary Material). Availability: http://cbrc.kaust.edu.sa/readscan Contact: or firstname.lastname@example.org Supplementary information: Supplementary data are available at Bioinformatics online. 2012 The Author(s).
Naeem, Raeece; Rashid, Mamoon; Pain, Arnab
Summary: READSCAN is a highly scalable parallel program to identify non-host sequences (of potential pathogen origin) and estimate their genome relative abundance in high-throughput sequence datasets. READSCAN accurately classified human and viral sequences on a 20.1 million reads simulated dataset in <27 min using a small Beowulf compute cluster with 16 nodes (Supplementary Material). Availability: http://cbrc.kaust.edu.sa/readscan Contact: or email@example.com Supplementary information: Supplementary data are available at Bioinformatics online. 2012 The Author(s).
McPherson, Andrew W; Roth, Andrew; Ha, Gavin; Chauve, Cedric; Steif, Adi; de Souza, Camila P E; Eirew, Peter; Bouchard-Côté, Alexandre; Aparicio, Sam; Sahinalp, S Cenk; Shah, Sohrab P
Somatic evolution of malignant cells produces tumors composed of multiple clonal populations, distinguished in part by rearrangements and copy number changes affecting chromosomal segments. Whole genome sequencing mixes the signals of sampled populations, diluting the signals of clone-specific aberrations, and complicating estimation of clone-specific genotypes. We introduce ReMixT, a method to unmix tumor and contaminating normal signals and jointly predict mixture proportions, clone-specific segment copy number, and clone specificity of breakpoints. ReMixT is free, open-source software and is available at http://bitbucket.org/dranew/remixt .
Zhao, Yusheng; Gowda, Manje; Longin, Friedrich H; Würschum, Tobias; Ranc, Nicolas; Reif, Jochen C
Estimating marker effects based on routinely generated phenotypic data of breeding programs is a cost-effective strategy to implement genomic selection. Truncation selection in breeding populations, however, could have a strong impact on the accuracy to predict genomic breeding values. The main objective of our study was to investigate the influence of phenotypic selection on the accuracy and bias of genomic selection. We used experimental data of 788 testcross progenies from an elite maize breeding program. The testcross progenies were evaluated in unreplicated field trials in ten environments and fingerprinted with 857 SNP markers. Random regression best linear unbiased prediction method was used in combination with fivefold cross-validation based on genotypic sampling. We observed a substantial loss in the accuracy to predict genomic breeding values in unidirectional selected populations. In contrast, estimating marker effects based on bidirectional selected populations led to only a marginal decrease in the prediction accuracy of genomic breeding values. We concluded that bidirectional selection is a valuable approach to efficiently implement genomic selection in applied plant breeding programs.
Adrion, Jeffrey R.; Song, Michael J.; Schrider, Daniel R.; Hahn, Matthew W.
Abstract Knowing the rate at which transposable elements (TEs) insert and delete is critical for understanding their role in genome evolution. We estimated spontaneous rates of insertion and deletion for all known, active TE superfamilies present in a set of Drosophila melanogaster mutation-accumulation (MA) lines using whole genome sequence data. Our results demonstrate that TE insertions far outpace TE deletions in D. melanogaster. We found a significant effect of background genotype on TE activity, with higher rates of insertions in one MA line. We also found significant rate heterogeneity between the chromosomes, with both insertion and deletion rates elevated on the X relative to the autosomes. Further, we identified significant associations between TE activity and chromatin state, and tested for associations between TE activity and other features of the local genomic environment such as TE content, exon content, GC content, and recombination rate. Our results provide the most detailed assessment of TE mobility in any organism to date, and provide a useful benchmark for both addressing theoretical predictions of TE dynamics and for exploring large-scale patterns of TE movement in D. melanogaster and other species. PMID:28338986
Xu, Yunbi; Li, Ping; Zou, Cheng; Lu, Yanli; Xie, Chuanxiao; Zhang, Xuecai; Prasanna, Boddupalli M; Olsen, Michael S
As one of the important concepts in conventional quantitative genetics and breeding, genetic gain can be defined as the amount of increase in performance that is achieved annually through artificial selection. To develop pro ducts that meet the increasing demand of mankind, especially for food and feed, in addition to various industrial uses, breeders are challenged to enhance the potential of genetic gain continuously, at ever higher rates, while they close the gaps that remain between the yield potential in breeders' demonstration trials and the actual yield in farmers' fields. Factors affecting genetic gain include genetic variation available in breeding materials, heritability for traits of interest, selection intensity, and the time required to complete a breeding cycle. Genetic gain can be improved through enhancing the potential and closing the gaps, which has been evolving and complemented with modern breeding techniques and platforms, mainly driven by molecular and genomic tools, combined with improved agronomic practice. Several key strategies are reviewed in this article. Favorable genetic variation can be unlocked and created through molecular and genomic approaches including mutation, gene mapping and discovery, and transgene and genome editing. Estimation of heritability can be improved by refining field experiments through well-controlled and precisely assayed environmental factors or envirotyping, particularly for understanding and controlling spatial heterogeneity at the field level. Selection intensity can be significantly heightened through improvements in the scale and precision of genotyping and phenotyping. The breeding cycle time can be shortened by accelerating breeding procedures through integrated breeding approaches such as marker-assisted selection and doubled haploid development. All the strategies can be integrated with other widely used conventional approaches in breeding programs to enhance genetic gain. More transdisciplinary
Genomic Prediction Accounting for Genotype by Environment Interaction Offers an Effective Framework for Breeding Simultaneously for Adaptation to an Abiotic Stress and Performance Under Normal Cropping Conditions in Rice.
Ben Hassen, Manel; Bartholomé, Jérôme; Valè, Giampiero; Cao, Tuong-Vi; Ahmadi, Nourollah
Developing rice varieties adapted to alternate wetting and drying water management is crucial for the sustainability of irrigated rice cropping systems. Here we report the first study exploring the feasibility of breeding rice for adaptation to alternate wetting and drying using genomic prediction methods that account for genotype by environment interactions. Two breeding populations (a reference panel of 284 accessions and a progeny population of 97 advanced lines) were evaluated under alternate wetting and drying and continuous flooding management systems. The predictive ability of genomic prediction for response variables (index of relative performance and the slope of the joint regression) and for multi-environment genomic prediction models were compared. For the three traits considered (days to flowering, panicle weight and nitrogen-balance index), significant genotype by environment interactions were observed in both populations. In cross validation, predictive ability for the index was on average lower (0.31) than that of the slope of the joint regression (0.64) whatever the trait considered. Similar results were found for progeny validation. Both cross-validation and progeny validation experiments showed that the performance of multi-environment models predicting unobserved phenotypes of untested entrees was similar to the performance of single environment models with differences in predictive ability ranging from -6% to 4% depending on the trait and on the statistical model concerned. The predictive ability of multi-environment models predicting unobserved phenotypes of entrees evaluated under both water management systems outperformed single environment models by an average of 30%. Practical implications for breeding rice for adaptation to alternate wetting and drying system are discussed. Copyright © 2018, G3: Genes, Genomes, Genetics.
Navas González, Francisco Javier; Jordana Vidal, Jordi; Camacho Vallejo, María Esperanza; León Jurado, Jose Manuel; de la Haba Giraldo, Manuel Rafael; Barba Capote, Cecilio; Delgado Bermejo, Juan Vicente
Cutaneous habronematidosis (CH) is a highly prevalent seasonally recurrent skin disease that affects donkeys as a result from the action of spirurid stomach worm larvae. Carrier flies mistakenly deposit these larvae on previous skin lesions or on the moisture of natural orifices, causing distress and inflicting relapsing wounds to the animals. First, we carried out a meta-analysis of the predisposing factors that could condition the development of CH in Andalusian donkeys. Second, basing on the empirical existence of an inter and intrafamilial variation previously addressed by owners, we isolated the genetic background behind the hypersensibility to this parasitological disease. To this aim, we designed a Bayesian linear model (BLM) to estimate the breeding values and genetic parameters for the hypersensibility to CH as a way to infer the potential selection suitability of this trait, seeking the improvement of donkey conservation programs. We studied the historical record of the cases of CH of 765 donkeys from 1984 to 2017. Fixed effects included birth year, birth season, sex, farm/owner, and husbandry system. Age was included as a linear and quadratic covariate. Although the effects of birth season and birth year were statistically non-significant (P > 0.05), their respective interactions with sex and farm/owner were statistically significant (P < 0.01), what translated into an increase of 40.5% in the specificity and of 0.6% of the sensibility of the model designed, when such interactions were included. Our BLM reported highly accurate genetic parameters as suggested by the low error of around 0.005, and the 95% credible interval for the heritability of ±0.0012. The CH hypersensibility heritability was 0.0346. The value of 0.1232 for additive genetic variance addresses a relatively low genetic variation in the Andalusian donkey breed. Our results suggest that farms managed under extensive husbandry conditions are the most protective ones against
Li, Hong-wei; Wang, Rui-jun; Wang, Zhi-ying; Li, Xue-wu; Wang, Zhen-yu; Yanjun, Zhang; Rui, Su; Zhihong, Liu; Jinquan, Li
With the development of gene chip and breeding technology, genomic selection in plants and animals has become research hotspots in recent years. Genomic selection has been extensively applied to all kinds of economic livestock, due to its high accuracy, short generation intervals and low breeding costs. In this review, we summarize genotyping technology and the methods for genomic breeding value estimation, the latter including the least square method, RR-BLUP, GBLUP, ssGBLUP, BayesA and BayesB. We also cover basic principles of genomic selection and compare their genetic marker ranges, genomic selection accuracy and operational speed. In addition, we list common indicators, methods and influencing factors that are related to genomic selection accuracy. Lastly, we discuss latest applications and the current problems of genomic selection at home and abroad. Importantly, we envision future status of genomic selection research, including multi-trait and multi-population genomic selection, as well as impact of whole genome sequencing and dominant effects on genomic selection. This review will provide some venues for other breeders to further understand genome selection.
Full Text Available Abstract Background The Approximate Bayesian Computation (ABC approach has been used to infer demographic parameters for numerous species, including humans. However, most applications of ABC still use limited amounts of data, from a small number of loci, compared to the large amount of genome-wide population-genetic data which have become available in the last few years. Results We evaluated the performance of the ABC approach for three 'population divergence' models - similar to the 'isolation with migration' model - when the data consists of several hundred thousand SNPs typed for multiple individuals by simulating data from known demographic models. The ABC approach was used to infer demographic parameters of interest and we compared the inferred values to the true parameter values that was used to generate hypothetical "observed" data. For all three case models, the ABC approach inferred most demographic parameters quite well with narrow credible intervals, for example, population divergence times and past population sizes, but some parameters were more difficult to infer, such as population sizes at present and migration rates. We compared the ability of different summary statistics to infer demographic parameters, including haplotype and LD based statistics, and found that the accuracy of the parameter estimates can be improved by combining summary statistics that capture different parts of information in the data. Furthermore, our results suggest that poor choices of prior distributions can in some circumstances be detected using ABC. Finally, increasing the amount of data beyond some hundred loci will substantially improve the accuracy of many parameter estimates using ABC. Conclusions We conclude that the ABC approach can accommodate realistic genome-wide population genetic data, which may be difficult to analyze with full likelihood approaches, and that the ABC can provide accurate and precise inference of demographic parameters from
Flávia Barbosa Silva Botelho
Full Text Available World’s ornamental plant market, including domestic market of several countries and its exports, is currently evaluated in 107 billion dollars yearly. Such estimate highlights the importance of the sector in the economy of the countries, as well as its important social role, as it represents one of the main activities, which contributes to income and employment. Therefore a well-structured plant breeding program, which is connected with consumers’ demands, is required in order to fulfill these market needs globally. Activities related to pre-breeding, conventional breeding, and breeding by biotechnological techniques constitute the basis for the successful development of new ornamental plant cultivars. Techniques that involve tissue culture, protoplast fusion and genetic engineering greatly aid conventional breeding (germplasm introduction, plant selection and hybridization, aiming the obtention of superior genotypes. Therefore it makes evident, in the literature, the successful employment of genetic breeding, since it aims to develop plants with commercial value that are also competitive with the ones available in the market.
Julio Andre, Benavides; Cross, Paul C.; Luikart, Gordon; Scott, Creel
Cross-species transmission (CST) of bacterial pathogens has major implications for human health, livestock, and wildlife management because it determines whether control actions in one species may have subsequent effects on other potential host species. The study of bacterial transmission has benefitted from methods measuring two types of genetic variation: variable number of tandem repeats (VNTRs) and single nucleotide polymorphisms (SNPs). However, it is unclear whether these data can distinguish between different epidemiological scenarios. We used a simulation model with two host species and known transmission rates (within and between species) to evaluate the utility of these markers for inferring CST. We found that CST estimates are biased for a wide range of parameters when based on VNTRs and a most parsimonious reconstructed phylogeny. However, estimations of CST rates lower than 5% can be achieved with relatively low bias using as low as 250 SNPs. CST estimates are sensitive to several parameters, including the number of mutations accumulated since introduction, stochasticity, the genetic difference of strains introduced, and the sampling effort. Our results suggest that, even with whole-genome sequences, unbiased estimates of CST will be difficult when sampling is limited, mutation rates are low, or for pathogens that were recently introduced.
Brown, T. A. (Terence A.)
... of genome expression and replication processes, and transcriptomics and proteomics. This text is richly illustrated with clear, easy-to-follow, full color diagrams, which are downloadable from the book's website...
Judith L Stella
Full Text Available The objectives of this cross-sectional study were: 1 to estimate the prevalence and characterize the severity of periodontal disease in a population of dogs housed in commercial breeding facilities; 2 to characterize PD preventive care utilized by facility owners; and 3 to assess inter-rater reliability of a visual scoring assessment tool. Adult dogs (N = 445 representing 42 breeds at 24 CB facilities in Indiana and Illinois were assessed. Periodontal disease was scored visually using the American Veterinary Dental Collage 0-IV scale. Inter-rater reliability was assessed on 198 dogs and facility owners were asked to provide information about the preventive care utilized. The overall prevalence of periodontal disease (Grades I-IV was 86.3% (95% CI: 82.9, 89.3. An ordered logistic regression analysis found age (OR = 1.4; 95% CI 1.24, 1.54; P<0.0001, facility (OR = 1.13; 95% CI 1.09, 1.18; P<0.0001, sex (OR = 1.7; 95% CI 1.12, 2.65; P = 0.013, and non-professional dental scaling (OR = 2.82; 95% CI 1.34, 5.91; P = 0.006 to be statistically significant. Inter-rater reliability analysis found agreement to be 86.2%, with a weighted kappa of 0.4731 (95% CI 0.3847, 0.5615 indicating moderate agreement. Risk of periodontal disease increased with increasing age. Additionally, a trend toward decreasing risk with increasing weight was also found, although it was not statistically significant. The trends identified agree with studies that have evaluated periodontal disease in the companion dog population and do not support the assumption that the dental health of dogs in commercial breeding facilities is worse than that of the population as a whole. Although there were few cases of severe periodontal disease and all facilities employed some type of preventive care in this sample, the large number of dogs with some degree of disease (Grades I-IV suggests that further investigation of preventive care is warranted.
Full Text Available Toxicogenomics promises to aid in predicting adverse effects, understanding the mechanisms of drug action or toxicity, and uncovering unexpected or secondary pharmacology. However, modeling adverse effects using high dimensional and high noise genomic data is prone to over-fitting. Models constructed from such data sets often consist of a large number of genes with no obvious functional relevance to the biological effect the model intends to predict that can make it challenging to interpret the modeling results. To address these issues, we developed a novel algorithm, Predictive Power Estimation Algorithm (PPEA, which estimates the predictive power of each individual transcript through an iterative two-way bootstrapping procedure. By repeatedly enforcing that the sample number is larger than the transcript number, in each iteration of modeling and testing, PPEA reduces the potential risk of overfitting. We show with three different cases studies that: (1 PPEA can quickly derive a reliable rank order of predictive power of individual transcripts in a relatively small number of iterations, (2 the top ranked transcripts tend to be functionally related to the phenotype they are intended to predict, (3 using only the most predictive top ranked transcripts greatly facilitates development of multiplex assay such as qRT-PCR as a biomarker, and (4 more importantly, we were able to demonstrate that a small number of genes identified from the top-ranked transcripts are highly predictive of phenotype as their expression changes distinguished adverse from nonadverse effects of compounds in completely independent tests. Thus, we believe that the PPEA model effectively addresses the over-fitting problem and can be used to facilitate genomic biomarker discovery for predictive toxicology and drug responses.
Anthony T. Slater
Full Text Available Potato ( L. breeders consider a large number of traits during cultivar development and progress in conventional breeding can be slow. There is accumulating evidence that some of these traits, such as yield, are affected by a large number of genes with small individual effects. Recently, significant efforts have been applied to the development of genomic resources to improve potato breeding, culminating in a draft genome sequence and the identification of a large number of single nucleotide polymorphisms (SNPs. The availability of these genome-wide SNPs is a prerequisite for implementing genomic selection for improvement of polygenic traits such as yield. In this review, we investigate opportunities for the application of genomic selection to potato, including novel breeding program designs. We have considered a number of factors that will influence this process, including the autotetraploid and heterozygous genetic nature of potato, the rate of decay of linkage disequilibrium, the number of required markers, the design of a reference population, and trait heritability. Based on estimates of the effective population size derived from a potato breeding program, we have calculated the expected accuracy of genomic selection for four key traits of varying heritability and propose that it will be reasonably accurate. We compared the expected genetic gain from genomic selection with the expected gain from phenotypic and pedigree selection, and found that genetic gain can be substantially improved by using genomic selection.
Annotated Draft Genome Assemblies for the Northern Bobwhite (Colinus virginianus and the Scaled Quail (Callipepla squamata Reveal Disparate Estimates of Modern Genome Diversity and Historic Effective Population Size
David L. Oldeschulte
Full Text Available Northern bobwhite (Colinus virginianus; hereafter bobwhite and scaled quail (Callipepla squamata populations have suffered precipitous declines across most of their US ranges. Illumina-based first- (v1.0 and second- (v2.0 generation draft genome assemblies for the scaled quail and the bobwhite produced N50 scaffold sizes of 1.035 and 2.042 Mb, thereby producing a 45-fold improvement in contiguity over the existing bobwhite assembly, and ≥90% of the assembled genomes were captured within 1313 and 8990 scaffolds, respectively. The scaled quail assembly (v1.0 = 1.045 Gb was ∼20% smaller than the bobwhite (v2.0 = 1.254 Gb, which was supported by kmer-based estimates of genome size. Nevertheless, estimates of GC content (41.72%; 42.66%, genome-wide repetitive content (10.40%; 10.43%, and MAKER-predicted protein coding genes (17,131; 17,165 were similar for the scaled quail (v1.0 and bobwhite (v2.0 assemblies, respectively. BUSCO analyses utilizing 3023 single-copy orthologs revealed a high level of assembly completeness for the scaled quail (v1.0; 84.8% and the bobwhite (v2.0; 82.5%, as verified by comparison with well-established avian genomes. We also detected 273 putative segmental duplications in the scaled quail genome (v1.0, and 711 in the bobwhite genome (v2.0, including some that were shared among both species. Autosomal variant prediction revealed ∼2.48 and 4.17 heterozygous variants per kilobase within the scaled quail (v1.0 and bobwhite (v2.0 genomes, respectively, and estimates of historic effective population size were uniformly higher for the bobwhite across all time points in a coalescent model. However, large-scale declines were predicted for both species beginning ∼15–20 KYA.
Annotated Draft Genome Assemblies for the Northern Bobwhite (Colinus virginianus) and the Scaled Quail (Callipepla squamata) Reveal Disparate Estimates of Modern Genome Diversity and Historic Effective Population Size.
Oldeschulte, David L; Halley, Yvette A; Wilson, Miranda L; Bhattarai, Eric K; Brashear, Wesley; Hill, Joshua; Metz, Richard P; Johnson, Charles D; Rollins, Dale; Peterson, Markus J; Bickhart, Derek M; Decker, Jared E; Sewell, John F; Seabury, Christopher M
Northern bobwhite ( Colinus virginianus ; hereafter bobwhite) and scaled quail ( Callipepla squamata ) populations have suffered precipitous declines across most of their US ranges. Illumina-based first- (v1.0) and second- (v2.0) generation draft genome assemblies for the scaled quail and the bobwhite produced N50 scaffold sizes of 1.035 and 2.042 Mb, thereby producing a 45-fold improvement in contiguity over the existing bobwhite assembly, and ≥90% of the assembled genomes were captured within 1313 and 8990 scaffolds, respectively. The scaled quail assembly (v1.0 = 1.045 Gb) was ∼20% smaller than the bobwhite (v2.0 = 1.254 Gb), which was supported by kmer-based estimates of genome size. Nevertheless, estimates of GC content (41.72%; 42.66%), genome-wide repetitive content (10.40%; 10.43%), and MAKER-predicted protein coding genes (17,131; 17,165) were similar for the scaled quail (v1.0) and bobwhite (v2.0) assemblies, respectively. BUSCO analyses utilizing 3023 single-copy orthologs revealed a high level of assembly completeness for the scaled quail (v1.0; 84.8%) and the bobwhite (v2.0; 82.5%), as verified by comparison with well-established avian genomes. We also detected 273 putative segmental duplications in the scaled quail genome (v1.0), and 711 in the bobwhite genome (v2.0), including some that were shared among both species. Autosomal variant prediction revealed ∼2.48 and 4.17 heterozygous variants per kilobase within the scaled quail (v1.0) and bobwhite (v2.0) genomes, respectively, and estimates of historic effective population size were uniformly higher for the bobwhite across all time points in a coalescent model. However, large-scale declines were predicted for both species beginning ∼15-20 KYA. Copyright © 2017 Oldeschulte et al.
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...
Full Text Available Recently genome-wide association studies (GWAS have identified numerous susceptibility variants for complex diseases. In this study we proposed several approaches to estimate the total number of variants underlying these diseases. We assume that the variance explained by genetic markers (Vg follow an exponential distribution, which is justified by previous studies on theories of adaptation. Our aim is to fit the observed distribution of Vg from GWAS to its theoretical distribution. The number of variants is obtained by the heritability divided by the estimated mean of the exponential distribution. In practice, due to limited sample sizes, there is insufficient power to detect variants with small effects. Therefore the power was taken into account in fitting. Besides considering the most significant variants, we also tried to relax the significance threshold, allowing more markers to be fitted. The effects of false positive variants were removed by considering the local false discovery rates. In addition, we developed an alternative approach by directly fitting the z-statistics from GWAS to its theoretical distribution. In all cases, the "winner's curse" effect was corrected analytically. Confidence intervals were also derived. Simulations were performed to compare and verify the performance of different estimators (which incorporates various means of winner's curse correction and the coverage of the proposed analytic confidence intervals. Our methodology only requires summary statistics and is able to handle both binary and continuous traits. Finally we applied the methods to a few real disease examples (lipid traits, type 2 diabetes and Crohn's disease and estimated that hundreds to nearly a thousand variants underlie these traits.
Lin, Y; Rajan, V; Moret, B M E
The rapid accumulation of whole-genome data has renewed interest in the study of genomic rearrangements. Comparative genomics, evolutionary biology, and cancer research all require models and algorithms to elucidate the mechanisms, history, and consequences of these rearrangements. However, even simple models lead to NP-hard problems, particularly in the area of phylogenetic analysis. Current approaches are limited to small collections of genomes and low-resolution data (typically a few hundred syntenic blocks). Moreover, whereas phylogenetic analyses from sequence data are deemed incomplete unless bootstrapping scores (a measure of confidence) are given for each tree edge, no equivalent to bootstrapping exists for rearrangement-based phylogenetic analysis. We describe a fast and accurate algorithm for rearrangement analysis that scales up, in both time and accuracy, to modern high-resolution genomic data. We also describe a novel approach to estimate the robustness of results-an equivalent to the bootstrapping analysis used in sequence-based phylogenetic reconstruction. We present the results of extensive testing on both simulated and real data showing that our algorithm returns very accurate results, while scaling linearly with the size of the genomes and cubically with their number. We also present extensive experimental results showing that our approach to robustness testing provides excellent estimates of confidence, which, moreover, can be tuned to trade off thresholds between false positives and false negatives. Together, these two novel approaches enable us to attack heretofore intractable problems, such as phylogenetic inference for high-resolution vertebrate genomes, as we demonstrate on a set of six vertebrate genomes with 8,380 syntenic blocks. A copy of the software is available on demand.
Fang, Lingzhao; Sahana, Goutam; Ma, Peipei
sequence variants in Holstein (HOL) and Jersey (JER) cattle were analysed. We first carried out a post-GWAS analysis in a HOL training population to assess the degree of enrichment of the association signals in the gene regions defined by each GO term. We then extended the genomic best linear unbiased......BACKGROUND: A better understanding of the genetic architecture underlying complex traits (e.g., the distribution of causal variants and their effects) may aid in the genomic prediction. Here, we hypothesized that the genomic variants of complex traits might be enriched in a subset of genomic...
Xiao, Yong; Xu, Pengwei; Fan, Haikuo; Baudouin, Luc; Xia, Wei; Bocs, Stéphanie; Xu, Junyang; Li, Qiong; Guo, Anping; Zhou, Lixia; Li, Jing; Wu, Yi; Ma, Zilong; Armero, Alix; Issali, Auguste Emmanuel; Liu, Na; Peng, Ming; Yang, Yaodong
Coconut palm (Cocos nucifera,2n = 32), a member of genus Cocos and family Arecaceae (Palmaceae), is an important tropical fruit and oil crop. Currently, coconut palm is cultivated in 93 countries, including Central and South America, East and West Africa, Southeast Asia and the Pacific Islands, with a total growth area of more than 12 million hectares . Coconut palm is generally classified into 2 main categories: "Tall" (flowering 8-10 years after planting) and "Dwarf" (flowering 4-6 years after planting), based on morphological characteristics and breeding habits. This Palmae species has a long growth period before reproductive years, which hinders conventional breeding progress. In spite of initial successes, improvements made by conventional breeding have been very slow. In the present study, we obtained de novo sequences of the Cocos nucifera genome: a major genomic resource that could be used to facilitate molecular breeding in Cocos nucifera and accelerate the breeding process in this important crop. A total of 419.67 gigabases (Gb) of raw reads were generated by the Illumina HiSeq 2000 platform using a series of paired-end and mate-pair libraries, covering the predicted Cocos nucifera genome length (2.42 Gb, variety "Hainan Tall") to an estimated ×173.32 read depth. A total scaffold length of 2.20 Gb was generated (N50 = 418 Kb), representing 90.91% of the genome. The coconut genome was predicted to harbor 28 039 protein-coding genes, which is less than in Phoenix dactylifera (PDK30: 28 889), Phoenix dactylifera (DPV01: 41 660), and Elaeis guineensis (EG5: 34 802). BUSCO evaluation demonstrated that the obtained scaffold sequences covered 90.8% of the coconut genome and that the genome annotation was 74.1% complete. Genome annotation results revealed that 72.75% of the coconut genome consisted of transposable elements, of which long-terminal repeat retrotransposons elements (LTRs) accounted for the largest proportion (92.23%). Comparative analysis of the
Henryon, Mark; Berg, Peer; Sørensen, Anders Christian
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...
Angly, Florent E.; Willner, Dana; Prieto-Dav?, Alejandra; Edwards, Robert A.; Schmieder, Robert; Vega-Thurber, Rebecca; Antonopoulos, Dionysios A.; Barott, Katie; Cottrell, Matthew T.; Desnues, Christelle; Dinsdale, Elizabeth A.; Furlan, Mike; Haynes, Matthew; Henn, Matthew R.; Hu, Yongfei
Metagenomic studies characterize both the composition and diversity of uncultured viral and microbial communities. BLAST-based comparisons have typically been used for such analyses; however, sampling biases, high percentages of unknown sequences, and the use of arbitrary thresholds to find significant similarities can decrease the accuracy and validity of estimates. Here, we present Genome relative Abundance and Average Size (GAAS), a complete software package that provides improved estimate...
Pryce, J E; Gonzalez-Recio, O; Nieuwhof, G; Wales, W J; Coffey, M P; Hayes, B J; Goddard, M E
A new breeding value that combines the amount of feed saved through improved metabolic efficiency with predicted maintenance requirements is described. The breeding value includes a genomic component for residual feed intake (RFI) combined with maintenance requirements calculated from either a genomic or pedigree estimated breeding value (EBV) for body weight (BW) predicted using conformation traits. Residual feed intake is only available for genotyped Holsteins; however, BW is available for all breeds. The RFI component of the "feed saved" EBV has 2 parts: Australian calf RFI and Australian lactating cow RFI. Genomic breeding values for RFI were estimated from a reference population of 2,036 individuals in a multi-trait analysis including Australian calf RFI (n=843), Australian lactating cow RFI (n=234), and UK and Dutch lactating cow RFI (n=958). In all cases, the RFI phenotypes were deviations from a mean of 0, calculated by correcting dry matter intake for BW, growth, and milk yield (in the case of lactating cows). Single nucleotide polymorphism effects were calculated from the output of genomic BLUP and used to predict breeding values of 4,106 Holstein sires that were genotyped but did not have RFI phenotypes themselves. These bulls already had BW breeding values calculated from type traits, from which maintenance requirements in kilograms of feed per year were inferred. Finally, RFI and the feed required for maintenance (through BW) were used to calculate a feed saved breeding value and expressed as the predicted amount of feed saved per year. Animals that were 1 standard deviation above the mean were predicted to eat 66 kg dry matter less per year at the same level of milk production. In a data set of genotyped Holstein sires, the mean reliability of the feed saved breeding value was 0.37. For Holsteins that are not genotyped and for breeds other than Holsteins, feed saved is calculated using BW only. From April 2015, feed saved has been included as part of
Parthiban, S; Govindaraj, P; Senthilkumar, S
Twenty-five primer pairs developed from genomic simple sequence repeats (SSR) were compared with 25 expressed sequence tags (EST) SSRs to evaluate the efficiency of these two sets of primers using 59 sugarcane genetic stocks. The mean polymorphism information content (PIC) of genomic SSR was higher (0.72) compared to the PIC value recorded by EST-SSR marker (0.62). The relatively low level of polymorphism in EST-SSR markers may be due to the location of these markers in more conserved and expressed sequences compared to genomic sequences which are spread throughout the genome. Dendrogram based on the genomic SSR and EST-SSR marker data showed differences in grouping of genotypes. A total of 59 sugarcane accessions were grouped into 6 and 4 clusters using genomic SSR and EST-SSR, respectively. The highly efficient genomic SSR could subcluster the genotypes of some of the clusters formed by EST-SSR markers. The difference in dendrogram observed was probably due to the variation in number of markers produced by genomic SSR and EST-SSR and different portion of genome amplified by both the markers. The combined dendrogram (genomic SSR and EST-SSR) more clearly showed the genetic relationship among the sugarcane genotypes by forming four clusters. The mean genetic similarity (GS) value obtained using EST-SSR among 59 sugarcane accessions was 0.70, whereas the mean GS obtained using genomic SSR was 0.63. Although relatively lower level of polymorphism was displayed by the EST-SSR markers, genetic diversity shown by the EST-SSR was found to be promising as they were functional marker. High level of PIC and low genetic similarity values of genomic SSR may be more useful in DNA fingerprinting, selection of true hybrids, identification of variety specific markers and genetic diversity analysis. Identification of diverse parents based on cluster analysis can be effectively done with EST-SSR as the genetic similarity estimates are based on functional attributes related to
Angly, Florent E; Willner, Dana; Prieto-Davó, Alejandra; Edwards, Robert A; Schmieder, Robert; Vega-Thurber, Rebecca; Antonopoulos, Dionysios A; Barott, Katie; Cottrell, Matthew T; Desnues, Christelle; Dinsdale, Elizabeth A; Furlan, Mike; Haynes, Matthew; Henn, Matthew R; Hu, Yongfei; Kirchman, David L; McDole, Tracey; McPherson, John D; Meyer, Folker; Miller, R Michael; Mundt, Egbert; Naviaux, Robert K; Rodriguez-Mueller, Beltran; Stevens, Rick; Wegley, Linda; Zhang, Lixin; Zhu, Baoli; Rohwer, Forest
Metagenomic studies characterize both the composition and diversity of uncultured viral and microbial communities. BLAST-based comparisons have typically been used for such analyses; however, sampling biases, high percentages of unknown sequences, and the use of arbitrary thresholds to find significant similarities can decrease the accuracy and validity of estimates. Here, we present Genome relative Abundance and Average Size (GAAS), a complete software package that provides improved estimates of community composition and average genome length for metagenomes in both textual and graphical formats. GAAS implements a novel methodology to control for sampling bias via length normalization, to adjust for multiple BLAST similarities by similarity weighting, and to select significant similarities using relative alignment lengths. In benchmark tests, the GAAS method was robust to both high percentages of unknown sequences and to variations in metagenomic sequence read lengths. Re-analysis of the Sargasso Sea virome using GAAS indicated that standard methodologies for metagenomic analysis may dramatically underestimate the abundance and importance of organisms with small genomes in environmental systems. Using GAAS, we conducted a meta-analysis of microbial and viral average genome lengths in over 150 metagenomes from four biomes to determine whether genome lengths vary consistently between and within biomes, and between microbial and viral communities from the same environment. Significant differences between biomes and within aquatic sub-biomes (oceans, hypersaline systems, freshwater, and microbialites) suggested that average genome length is a fundamental property of environments driven by factors at the sub-biome level. The behavior of paired viral and microbial metagenomes from the same environment indicated that microbial and viral average genome sizes are independent of each other, but indicative of community responses to stressors and environmental conditions.
Florent E Angly
Full Text Available Metagenomic studies characterize both the composition and diversity of uncultured viral and microbial communities. BLAST-based comparisons have typically been used for such analyses; however, sampling biases, high percentages of unknown sequences, and the use of arbitrary thresholds to find significant similarities can decrease the accuracy and validity of estimates. Here, we present Genome relative Abundance and Average Size (GAAS, a complete software package that provides improved estimates of community composition and average genome length for metagenomes in both textual and graphical formats. GAAS implements a novel methodology to control for sampling bias via length normalization, to adjust for multiple BLAST similarities by similarity weighting, and to select significant similarities using relative alignment lengths. In benchmark tests, the GAAS method was robust to both high percentages of unknown sequences and to variations in metagenomic sequence read lengths. Re-analysis of the Sargasso Sea virome using GAAS indicated that standard methodologies for metagenomic analysis may dramatically underestimate the abundance and importance of organisms with small genomes in environmental systems. Using GAAS, we conducted a meta-analysis of microbial and viral average genome lengths in over 150 metagenomes from four biomes to determine whether genome lengths vary consistently between and within biomes, and between microbial and viral communities from the same environment. Significant differences between biomes and within aquatic sub-biomes (oceans, hypersaline systems, freshwater, and microbialites suggested that average genome length is a fundamental property of environments driven by factors at the sub-biome level. The behavior of paired viral and microbial metagenomes from the same environment indicated that microbial and viral average genome sizes are independent of each other, but indicative of community responses to stressors and
Eduardo da Cruz Gouveia Pimentel
Full Text Available The aim of this study was to compare iterative and direct solvers for estimation of marker effects in genomic selection. One iterative and two direct methods were used: Gauss-Seidel with Residual Update, Cholesky Decomposition and Gentleman-Givens rotations. For resembling different scenarios with respect to number of markers and of genotyped animals, a simulated data set divided into 25 subsets was used. Number of markers ranged from 1,200 to 5,925 and number of animals ranged from 1,200 to 5,865. Methods were also applied to real data comprising 3081 individuals genotyped for 45181 SNPs. Results from simulated data showed that the iterative solver was substantially faster than direct methods for larger numbers of markers. Use of a direct solver may allow for computing (covariances of SNP effects. When applied to real data, performance of the iterative method varied substantially, depending on the level of ill-conditioning of the coefficient matrix. From results with real data, Gentleman-Givens rotations would be the method of choice in this particular application as it provided an exact solution within a fairly reasonable time frame (less than two hours. It would indeed be the preferred method whenever computer resources allow its use.
Kaas, Rolf Sommer; Rundsten, Carsten Friis; Ussery, David
Background Escherichia coli exists in commensal and pathogenic forms. By measuring the variation of individual genes across more than a hundred sequenced genomes, gene variation can be studied in detail, including the number of mutations found for any given gene. This knowledge will be useful...... for creating better phylogenies, for determination of molecular clocks and for improved typing techniques. Results We find 3,051 gene clusters/families present in at least 95% of the genomes and 1,702 gene clusters present in 100% of the genomes. The former 'soft core' of about 3,000 gene families is perhaps...... more biologically relevant, especially considering that many of these genome sequences are draft quality. The E. coli pan-genome for this set of isolates contains 16,373 gene clusters. A core-gene tree, based on alignment and a pan-genome tree based on gene presence/absence, maps the relatedness...
Hirsch, Candice N; Hirsch, Cory D; Felcher, Kimberly; Coombs, Joseph; Zarka, Dan; Van Deynze, Allen; De Jong, Walter; Veilleux, Richard E; Jansky, Shelley; Bethke, Paul; Douches, David S; Buell, C Robin
Cultivated potato (Solanum tuberosum L.), a vegetatively propagated autotetraploid, has been bred for distinct market classes, including fresh market, pigmented, and processing varieties. Breeding efforts have relied on phenotypic selection of populations developed from intra- and intermarket class crosses and introgressions of wild and cultivated Solanum relatives. To retrospectively explore the effects of potato breeding at the genome level, we used 8303 single-nucleotide polymorphism markers to genotype a 250-line diversity panel composed of wild species, genetic stocks, and cultivated potato lines with release dates ranging from 1857 to 2011. Population structure analysis revealed four subpopulations within the panel, with cultivated potato lines grouping together and separate from wild species and genetic stocks. With pairwise kinship estimates clear separation between potato market classes was observed. Modern breeding efforts have scarcely changed the percentage of heterozygous loci or the frequency of homozygous, single-dose, and duplex loci on a genome level, despite concerted efforts by breeders. In contrast, clear selection in less than 50 years of breeding was observed for alleles in biosynthetic pathways important for market class-specific traits such as pigmentation and carbohydrate composition. Although improvement and diversification for distinct market classes was observed through whole-genome analysis of historic and current potato lines, an increased rate of gain from selection will be required to meet growing global food demands and challenges due to climate change. Understanding the genetic basis of diversification and trait improvement will allow for more rapid genome-guided improvement of potato in future breeding efforts.
Villumsen, Trine Michelle; Janss, Luc
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 ...
Lee, S.H.; Ripke, S.; Neale, B.; Faraone, S.V.; Purcell, S.M.; Perlis, R.H.; Mowry, B. J.; Thapar, A.; Goddard, M.E.; Witte, J.S.; Absher, D.; Agartz, I.; Akil, H.; Amin, F.; Andreassen, O.A.; Anjorin, A.; Anney, R.; Anttila, V.; Arking, D.E.; Asherson, P.; Azevedo, M.H.; Backlund, L.; Badner, J.A.; Bailey, A.J.; Banaschewski, T.; Barchas, J.D.; Barnes, M.R.; Barrett, T.B.; Bass, N.; Battaglia, A.; Bauer, M.; Bayés, M.; Bellivier, F.; Bergen, S.E.; Berrettini, W.; Betancur, C.; Bettecken, T.; Biederman, J; Binder, E.B.; Black, D.W.; Blackwood, D.H.; Bloss, C.S.; Boehnke, M.; Boomsma, D.I.; Breen, G.; Breuer, R.; Bruggeman, R.; Cormican, P.; Buccola, N.G.; Buitelaar, J.K.; Bunney, W.E.; Buxbaum, J.D.; Byerley, W. F.; Byrne, E.M.; Caesar, S.; Cahn, W.; Cantor, R.M.; Casas, M.; Chakravarti, A.; Chambert, K.; Choudhury, K.; Cichon, S.; Cloninger, C. R.; Collier, D.A.; Cook, E.H.; Coon, H.; Corman, B.; Corvin, A.; Coryell, W.H.; Craig, D.W.; Craig, I.W.; Crosbie, J.; Cuccaro, M.L.; Curtis, D.; Czamara, D.; Datta, S.; Dawson, G.; Day, R.; de Geus, E.J.C.; Degenhardt, F.; Djurovic, S.; Donohoe, G.; Doyle, A.E.; Duan, J.; Dudbridge, F.; Duketis, E.; Ebstein, R.P.; Edenberg, H.J.; Elia, J.; Ennis, S.; Etain, B.; Fanous, A.; Farmer, A.E.; Ferrier, I.N.; Flickinger, M.; Fombonne, E.; Foroud, T.; Frank, J.; Franke, B.; Fraser, C.; Freedman, R.; Freimer, N.B.; Freitag, C.; Friedl, M.; Frisén, L.; Gallagher, L.; Gejman, P.V.; Georgieva, L.; Gershon, E.S.; Geschwind, D.H.; Giegling, I.; Gill, M.; Gordon, S.D.; Gordon-Smith, K.; Green, E.K.; Greenwood, T.A.; Grice, D.E.; Gross, M.; Grozeva, D.; Guan, W.; Gurling, H.; de Haan, L.; Haines, J.L.; Hakonarson, H.; Hallmayer, J.; Hamilton, S.P.; Hamshere, M.L.; Hansen, T.F.; Hartmann, A.M.; Hautzinger, M.; Heath, A.C.; Henders, A.K.; Herms, S.; Hickie, I.B.; Hipolito, M.; Hoefels, S.; Holmans, P.A.; Holsboer, F.; Hoogendijk, W.J.G.; Hottenga, J.J.; Hultman, C. M.; Hus, V.; Ingason, A.; Ising, M.; Jamain, S.; Jones, E.G.; Jones, I.; Jones, L.; Tzeng, J.Y.; Kähler, A.K.; Kahn, R.S.; Kandaswamy, R.; Keller, M.C.; Kennedy, J.L.; Kenny, E.; Kent, L.; Kim, Y.; Kirov, G. K.; Klauck, S.M.; Klei, L.; Knowles, J.A.; Kohli, M.A.; Koller, D.L.; Konte, B.; Korszun, A.; Krabbendam, L.; Krasucki, R.; Kuntsi, J.; Kwan, P.; Landén, M.; Langstrom, N.; Lathrop, M.; Lawrence, J.; Lawson, W.B.; Leboyer, M.; Ledbetter, D.H.; Lee, P.H.; Lencz, T.; Lesch, K.P.; Levinson, D.F.; Lewis, C.M.; Li, J.; Lichtenstein, P.; Lieberman, J. A.; Lin, D.Y.; Linszen, D.H.; Liu, C.; Lohoff, F.W.; Loo, S.K.; Lord, C.; Lowe, J.K.; Lucae, S.; MacIntyre, D.J.; Madden, P.A.F.; Maestrini, E.; Magnusson, P.K.E.; Mahon, P.B.; Maier, W.; Malhotra, A.K.; Mane, S.M.; Martin, C.L.; Martin, N.G.; Mattheisen, M.; Matthews, K.; Mattingsdal, M.; McCarroll, S.A.; McGhee, K.A.; McGough, J.J.; McGrath, P.J.; McGuffin, P.; McInnis, M.G.; McIntosh, A.; McKinney, R.; McLean, A.W.; McMahon, F.J.; McMahon, W.M.; McQuillin, A.; Medeiros, H.; Medland, S.E.; Meier, S.; Melle, I.; Meng, F.; Meyer, J.; Middeldorp, C.M.; Middleton, L.; Milanova, V.; Miranda, A.; Monaco, A.P.; Montgomery, G.W.; Moran, J.L.; Moreno-De Luca, D.; Morken, G.; Morris, D.W.; Morrow, E.M.; Moskvina, V.; Muglia, P.; Mühleisen, T.W.; Muir, W.J.; Müller-Myhsok, B.; Murtha, M.; Myers, R.M.; Myin-Germeys, I.; Neale, M.C.; Nelson, S.F.; Nievergelt, C.M.; Nikolov, I.; Nimgaonkar, V.L.; Nolen, W.A.; Nöthen, M.M.; Nurnberger, J.I.; Nwulia, E.A.; Nyholt, DR; O'Dushlaine, C.; Oades, R.D.; Olincy, A.; Oliveira, G.; Olsen, L.; Ophoff, R.A.; Osby, U.; Owen, M.J.; Palotie, A.; Parr, J.R.; Paterson, A.D.; Pato, C.N.; Pato, M.T.; Penninx, B.W.J.H.; Pergadia, M.L.; Pericak-Vance, M.A.; Pickard, B.S.; Pimm, J.; Piven, J.; Posthuma, D.; Potash, J.B.; Poustka, F.; Propping, P.; Puri, V.; Quested, D.; Quinn, E.M.; Ramos-Quiroga, J.A.; Rasmussen, H.B.; Raychaudhuri, S.; Rehnström, K.; Reif, A.; Ribasés, M.; Rice, J.P.; Rietschel, M.; Roeder, K.; Roeyers, H.; Rossin, L.; Rothenberger, A.; Rouleau, G.; Ruderfer, D.; Rujescu, D.; Sanders, A.R.; Sanders, S.J.; Santangelo, S.; Sergeant, J.A.; Schachar, R.; Schalling, M.; Schatzberg, A.F.; Scheftner, W.A.; Schellenberg, G.D.; Scherer, S.W.; Schork, N.J.; Schulze, T.G.; Schumacher, J.; Schwarz, M.; Scolnick, E.; Scott, L.J.; Shi, J.; Shilling, P.D.; Shyn, S.I.; Silverman, J.M.; Slager, S.L.; Smalley, S.L.; Smit, J.H.; Smith, E.N.; Sonuga-Barke, E.J.; St Clair, D.; State, M.; Steffens, M; Steinhausen, H.C.; Strauss, J.; Strohmaier, J.; Stroup, T.S.; Sutcliffe, J.; Szatmari, P.; Szelinger, S.; Thirumalai, S.; Thompson, R.C.; Todorov, A.A.; Tozzi, F.; Treutlein, J.; Uhr, M.; van den Oord, E.J.C.G.; Grootheest, G.; van Os, J.; Vicente, A.; Vieland, V.; Vincent, J.B.; Visscher, P.M.; Walsh, C.A.; Wassink, T.H.; Watson, S.J.; Weissman, M.M.; Werge, T.; Wienker, T.F.; Wijsman, E.M.; Willemsen, G.; Williams, N.; Willsey, A.J.; Witt, S.H.; Xu, W.; Young, A.H.; Yu, T.W.; Zammit, S.; Zandi, P.P.; Zhang, P.; Zitman, F.G.; Zöllner, S.; Devlin, B.; Kelsoe, J.; Sklar, P.; Daly, M.J.; O'Donovan, M.C.; Craddock, N.; Sullivan, P.F.; Smoller, J.W.; Kendler, K.S.; Wray, N.R.
Most psychiatric disorders are moderately to highly heritable. The degree to which genetic variation is unique to individual disorders or shared across disorders is unclear. To examine shared genetic etiology, we use genome-wide genotype data from the Psychiatric Genomics Consortium (PGC) for cases
Carolina L. A. Da Silva
Full Text Available We investigated (1 the relationship between the estimated breeding values (EBVs for litter traits at birth and ovulation rate (OR, average corpora luteal weight, uterine length and embryonic survival and development traits in gilts at 35 days of pregnancy by linear regression, (2 the genetic variance of OR, average corpora lutea (CL weight, uterine length and embryonic survival and development traits at 35 days of pregnancy, and (3 the genetic correlations between these traits. Landrace (n = 86 and Yorkshire × Landrace (n = 304 gilts were inseminated and slaughtered at 35 days of pregnancy. OR was assessed by dissection of the CL on both ovaries. Individual CL was weighed and the average CL weight calculated. The number of embryos (total and vital were counted and the vital embryos were individually weighed for calculation of within litter average and standard deviation (SD of the embryo weight. Length of the uterine implantation site of the vital embryos was measured and the average per gilt calculated. Results suggests that increasing the EBV for total number of piglets born would proportionally increase OR and number of embryos, while decreasing the average CL weight. On the contrary, increasing the EBV for average piglet birth weight and for within litter birth weight standard deviation would increase the average CL weight. There was no relationship between the EBVs for BW and for BWSD and vital embryonic weight at 35 days of pregnancy. OR, average CL weight, number of embryos, average weight and implantation length of the vital embryos had all moderate to high heritabilities, ranging from 0.36 (±0.18 to 0.70 (±0.17. Thus, results indicate that there is ample genetic variation in OR, average CL weight and embryonic development traits. This knowledge could be used to optimize the balance between selection for litter size, average piglets birth weight and within litter birth weight uniformity.
Go, Yun Young; Bailey, Ernest; Cook, Deborah G.; Coleman, Stephen J.; MacLeod, James N.; Chen, Kuey-Chu; Timoney, Peter J.; Balasuriya, Udeni B. R.
Previously, we have shown that horses could be divided into susceptible and resistant groups based on an in vitro assay using dual-color flow cytometric analysis of CD3+ T cells infected with equine arteritis virus (EAV). Here, we demonstrate that the differences in in vitro susceptibility of equine CD3+ T lymphocytes to EAV infection have a genetic basis. To investigate the possible hereditary basis for this trait, we conducted a genome-wide association study (GWAS) to compare susceptible and resistant phenotypes. Testing of 267 DNA samples from four horse breeds that had a susceptible or a resistant CD3+ T lymphocyte phenotype using both Illumina Equine SNP50 BeadChip and Sequenom's MassARRAY system identified a common, genetically dominant haplotype associated with the susceptible phenotype in a region of equine chromosome 11 (ECA11), positions 49572804 to 49643932. The presence of a common haplotype indicates that the trait occurred in a common ancestor of all four breeds, suggesting that it may be segregated among other modern horse breeds. Biological pathway analysis revealed several cellular genes within this region of ECA11 encoding proteins associated with virus attachment and entry, cytoskeletal organization, and NF-κB pathways that may be associated with the trait responsible for the in vitro susceptibility/resistance of CD3+ T lymphocytes to EAV infection. The data presented in this study demonstrated a strong association of genetic markers with the trait, representing de facto proof that the trait is under genetic control. To our knowledge, this is the first GWAS of an equine infectious disease and the first GWAS of equine viral arteritis. PMID:21994447
Fé, Dario; Greve-Pedersen, Morten; Jensen, Christian Sig
In the joint project “FORAGESELECT”, we aim to implement Genome Wide Selection (GWS) in breeding of perennial ryegrass (Lolium perenne L.), in order to increase genetic response in important agronomic traits such as yield, seed production, stress tolerance and disease resistance, while decreasing...... of this study was to estimate the genetic and environmental variance in the training set composed of F2 families selected from a ten year breeding period. Variance components were estimated on 1193 of those families, sown in 2001, 2003 and 2005 in five locations around Europe. Families were tested together...
Schulmann, Nina F; Sahana, Goutam; Iso-Touru, T
A whole-genome scan using single marker association was used to detect chromosome regions associated with seven female fertility traits in Finnish Ayrshire dairy cattle. The phenotypic data consisted of de-regressed estimated breeding values for 340 bulls which were estimated using a single trait...
Jiang, Yue; Turinsky, Andrei L.; Brudno, Michael
With the development of High-Throughput Sequencing (HTS) thousands of human genomes have now been sequenced. Whenever different studies analyze the same genome they usually agree on the amount of single-nucleotide polymorphisms, but differ dramatically on the number of insertion and deletion variants (indels). Furthermore, there is evidence that indels are often severely under-reported. In this manuscript we derive the total number of indel variants in a human genome by combining data from different sequencing technologies, while assessing the indel detection accuracy. Our estimate of approximately 1 million indels in a Yoruban genome is much higher than the results reported in several recent HTS studies. We identify two key sources of difficulties in indel detection: the insufficient coverage, read length or alignment quality; and the presence of repeats, including short interspersed elements and homopolymers/dimers. We quantify the effect of these factors on indel detection. The quality of sequencing data plays a major role in improving indel detection by HTS methods. However, many indels exist in long homopolymers and repeats, where their detection is severely impeded. The true number of indel events is likely even higher than our current estimates, and new techniques and technologies will be required to detect them. PMID:26130710
Han, Mira V; Thomas, Gregg W C; Lugo-Martinez, Jose; Hahn, Matthew W
Current sequencing methods produce large amounts of data, but genome assemblies constructed from these data are often fragmented and incomplete. Incomplete and error-filled assemblies result in many annotation errors, especially in the number of genes present in a genome. This means that methods attempting to estimate rates of gene duplication and loss often will be misled by such errors and that rates of gene family evolution will be consistently overestimated. Here, we present a method that takes these errors into account, allowing one to accurately infer rates of gene gain and loss among genomes even with low assembly and annotation quality. The method is implemented in the newest version of the software package CAFE, along with several other novel features. We demonstrate the accuracy of the method with extensive simulations and reanalyze several previously published data sets. Our results show that errors in genome annotation do lead to higher inferred rates of gene gain and loss but that CAFE 3 sufficiently accounts for these errors to provide accurate estimates of important evolutionary parameters.
Full Text Available Abstract Background Comparison of recent patterns of recombination derived from linkage maps to historical patterns of recombination from linkage disequilibrium (LD could help identify genomic regions affected by strong artificial selection, appearing as reduced recent recombination. Norwegian Red cattle (NRF make an interesting case study for investigating these patterns as it is an admixed breed with an extensively recorded pedigree. NRF have been under strong artificial selection for traits such as milk and meat production, fertility and health. While measures of LD is also crucial for determining the number of markers required for association mapping studies, estimates of recombination rate can be used to assess quality of genomic assemblies. Results A dataset containing more than 17,000 genome-wide distributed SNPs and 2600 animals was used to assess recombination rates and LD in NRF. Although low LD measured by r2 was observed in NRF relative to some of the breeds from which this breed originates, reports from breeds other than those assessed in this study have described more rapid decline in r2 at short distances than what was found in NRF. Rate of decline in r2 for NRF suggested that to obtain an expected r2 between markers and a causal polymorphism of at least 0.5 for genome-wide association studies, approximately one SNP every 15 kb or a total of 200,000 SNPs would be required. For well known quantitative trait loci (QTLs for milk production traits on Bos Taurus chromosomes 1, 6 and 20, map length based on historic recombination was greater than map length based on recent recombination in NRF. Further, positions for 130 previously unpositioned contigs from assembly of the bovine genome sequence (Btau_4.0 found using comparative sequence analysis were validated by linkage analysis, and 28% of these positions corresponded to extreme values of population recombination rate. Conclusion While LD is reduced in NRF compared to some of the
Su, Hailin; Li, Hengde; Wang, Shi; Wang, Yangfan; Bao, Zhenmin
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.
Dijk, van T.; Pagliarani, G.; Pikunova, A.; Noordijk, Y.; Yilmaz-Temel, H.; Meulenbroek, B.; Visser, R.G.F.; Weg, van de W.E.
Background Breeders in the allo-octoploid strawberry currently make little use of molecular marker tools. As a first step of a QTL discovery project on fruit quality traits and resistance to soil-borne pathogens such as Phytophthora cactorum and Verticillium we built a genome-wide SSR linkage map
Isik, Fikret; Bartholomé, Jérôme; Farjat, Alfredo; Chancerel, Emilie; Raffin, Annie; Sanchez, Leopoldo; Plomion, Christophe; Bouffier, Laurent
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.
Full Text Available The term epistasis refers to interactions between multiple genetic loci. Genetic epistasis is important in regulating biological function and is considered to explain part of the 'missing heritability,' which involves marginal genetic effects that cannot be accounted for in genome-wide association studies. Thus, the study of epistasis is of great interest to geneticists. However, estimating epistatic effects for quantitative traits is challenging due to the large number of interaction effects that must be estimated, thus significantly increasing computing demands. Here, we present a new web server-based tool, the Pipeline for estimating EPIStatic genetic effects (PEPIS, for analyzing polygenic epistatic effects. The PEPIS software package is based on a new linear mixed model that has been used to predict the performance of hybrid rice. The PEPIS includes two main sub-pipelines: the first for kinship matrix calculation, and the second for polygenic component analyses and genome scanning for main and epistatic effects. To accommodate the demand for high-performance computation, the PEPIS utilizes C/C++ for mathematical matrix computing. In addition, the modules for kinship matrix calculations and main and epistatic-effect genome scanning employ parallel computing technology that effectively utilizes multiple computer nodes across our networked cluster, thus significantly improving the computational speed. For example, when analyzing the same immortalized F2 rice population genotypic data examined in a previous study, the PEPIS returned identical results at each analysis step with the original prototype R code, but the computational time was reduced from more than one month to about five minutes. These advances will help overcome the bottleneck frequently encountered in genome wide epistatic genetic effect analysis and enable accommodation of the high computational demand. The PEPIS is publically available at http://bioinfo.noble.org/PolyGenic_QTL/.
Zhang, Wenchao; Dai, Xinbin; Wang, Qishan; Xu, Shizhong; Zhao, Patrick X
The term epistasis refers to interactions between multiple genetic loci. Genetic epistasis is important in regulating biological function and is considered to explain part of the 'missing heritability,' which involves marginal genetic effects that cannot be accounted for in genome-wide association studies. Thus, the study of epistasis is of great interest to geneticists. However, estimating epistatic effects for quantitative traits is challenging due to the large number of interaction effects that must be estimated, thus significantly increasing computing demands. Here, we present a new web server-based tool, the Pipeline for estimating EPIStatic genetic effects (PEPIS), for analyzing polygenic epistatic effects. The PEPIS software package is based on a new linear mixed model that has been used to predict the performance of hybrid rice. The PEPIS includes two main sub-pipelines: the first for kinship matrix calculation, and the second for polygenic component analyses and genome scanning for main and epistatic effects. To accommodate the demand for high-performance computation, the PEPIS utilizes C/C++ for mathematical matrix computing. In addition, the modules for kinship matrix calculations and main and epistatic-effect genome scanning employ parallel computing technology that effectively utilizes multiple computer nodes across our networked cluster, thus significantly improving the computational speed. For example, when analyzing the same immortalized F2 rice population genotypic data examined in a previous study, the PEPIS returned identical results at each analysis step with the original prototype R code, but the computational time was reduced from more than one month to about five minutes. These advances will help overcome the bottleneck frequently encountered in genome wide epistatic genetic effect analysis and enable accommodation of the high computational demand. The PEPIS is publically available at http://bioinfo.noble.org/PolyGenic_QTL/.
Full Text Available Runs of homozygosity (ROH, uninterrupted stretches of homozygous genotypes resulting from parents transmitting identical haplotypes to their offspring, have emerged as informative genome-wide estimates of autozygosity (inbreeding. We used genomic profiles based on 698 K single nucleotide polymorphisms (SNPs from nine breeds of domestic cattle (Bos taurus and the European bison (Bison bonasus to investigate how ROH distributions can be compared within and among species. We focused on two length classes: 0.5–15 Mb to investigate ancient events and >15 Mb to address recent events (approximately three generations. For each length class, we chose a few chromosomes with a high number of ROH, calculated the percentage of times a SNP appeared in a ROH, and plotted the results. We selected areas with distinct patterns including regions where (1 all groups revealed an increase or decrease of ROH, (2 bison differed from cattle, (3 one cattle breed or groups of breeds differed (e.g., dairy versus meat cattle. Examination of these regions in the cattle genome showed genes potentially important for natural and human-induced selection, concerning, for example, meat and milk quality, metabolism, growth, and immune function. The comparative methodology presented here permits visual identification of regions of interest for selection, breeding programs, and conservation.
Reinartz, S; Distl, O
Non-syndromic congenital cleft lip and jaw (CLJ) is a condition reported in Vorderwald × Montbéliarde cattle. The objective of the present study was to perform a genome-wide association study (GWAS) for 10 CLJ-affected and 50 unaffected Vorderwald × Montbéliarde cattle using the bovine Illumina high density bead chip to identify loci for this condition. Phenotypic classification of CLJ was based on a detailed recording of orofacial structures using computed tomography. A breeding experiment among CLJ-affected Vorderwald × Montbéliarde cattle and CLJ-affected Vorderwald × Montbéliarde cattle with unaffected Holsteins confirmed recessive inheritance and different loci for bilateral or left-sided versus right-sided CLJ. The GWAS for the five cases with right-sided CLJ gave a genome-wide signal on bovine chromosome (BTA) 29 at 16 Mb. For the four left-sided and one bilateral CLJ case, a genome-wide significant association was identified on BTA4 at 32 Mb. Two different loci are very likely to be involved in CLJ in Vorderwald × Montbéliarde cattle because experimental matings among affected cows and bulls with different types of CLJ did not result in CLJ-affected progeny, and in addition, two different loci were also found through GWAS and mapped on two different bovine chromosomes. Validation in 346 Vorderwald × Montbéliarde cattle for the highly associated SNPs on BTA4 and 29 gave ratios of 33/346 (0.095, BTA4) and 6/346 (0.017, BTA29) homozygous mutant genotypes. Further studies should elucidate the responsible mutations underlying the different types of CLJ in Vorderwald × Montbéliarde cattle. © 2017 Stichting International Foundation for Animal Genetics.
Krapohl, E; Plomin, R
One of the best predictors of children's educational achievement is their family's socioeconomic status (SES), but the degree to which this association is genetically mediated remains unclear. For 3000 UK-representative unrelated children we found that genome-wide single-nucleotide polymorphisms could explain a third of the variance of scores on an age-16 UK national examination of educational achievement and half of the correlation between their scores and family SES. Moreover, genome-wide polygenic scores based on a previously published genome-wide association meta-analysis of total number of years in education accounted for ~3.0% variance in educational achievement and ~2.5% in family SES. This study provides the first molecular evidence for substantial genetic influence on differences in children's educational achievement and its association with family SES.
Full Text Available The study of continuously varying, quantitative traits is important in evolutionary biology, agriculture, and medicine. Variation in such traits is attributable to many, possibly interacting, genes whose expression may be sensitive to the environment, which makes their dissection into underlying causative factors difficult. An important population parameter for quantitative traits is heritability, the proportion of total variance that is due to genetic factors. Response to artificial and natural selection and the degree of resemblance between relatives are all a function of this parameter. Following the classic paper by R. A. Fisher in 1918, the estimation of additive and dominance genetic variance and heritability in populations is based upon the expected proportion of genes shared between different types of relatives, and explicit, often controversial and untestable models of genetic and non-genetic causes of family resemblance. With genome-wide coverage of genetic markers it is now possible to estimate such parameters solely within families using the actual degree of identity-by-descent sharing between relatives. Using genome scans on 4,401 quasi-independent sib pairs of which 3,375 pairs had phenotypes, we estimated the heritability of height from empirical genome-wide identity-by-descent sharing, which varied from 0.374 to 0.617 (mean 0.498, standard deviation 0.036. The variance in identity-by-descent sharing per chromosome and per genome was consistent with theory. The maximum likelihood estimate of the heritability for height was 0.80 with no evidence for non-genetic causes of sib resemblance, consistent with results from independent twin and family studies but using an entirely separate source of information. Our application shows that it is feasible to estimate genetic variance solely from within-family segregation and provides an independent validation of previously untestable assumptions. Given sufficient data, our new paradigm will
Smith, Stephen A; Brown, Joseph W; Walker, Joseph F
Phylogenomic datasets have been successfully used to address questions involving evolutionary relationships, patterns of genome structure, signatures of selection, and gene and genome duplications. However, despite the recent explosion in genomic and transcriptomic data, the utility of these data sources for efficient divergence-time inference remains unexamined. Phylogenomic datasets pose two distinct problems for divergence-time estimation: (i) the volume of data makes inference of the entire dataset intractable, and (ii) the extent of underlying topological and rate heterogeneity across genes makes model mis-specification a real concern. "Gene shopping", wherein a phylogenomic dataset is winnowed to a set of genes with desirable properties, represents an alternative approach that holds promise in alleviating these issues. We implemented an approach for phylogenomic datasets (available in SortaDate) that filters genes by three criteria: (i) clock-likeness, (ii) reasonable tree length (i.e., discernible information content), and (iii) least topological conflict with a focal species tree (presumed to have already been inferred). Such a winnowing procedure ensures that errors associated with model (both clock and topology) mis-specification are minimized, therefore reducing error in divergence-time estimation. We demonstrated the efficacy of this approach through simulation and applied it to published animal (Aves, Diplopoda, and Hymenoptera) and plant (carnivorous Caryophyllales, broad Caryophyllales, and Vitales) phylogenomic datasets. By quantifying rate heterogeneity across both genes and lineages we found that every empirical dataset examined included genes with clock-like, or nearly clock-like, behavior. Moreover, many datasets had genes that were clock-like, exhibited reasonable evolutionary rates, and were mostly compatible with the species tree. We identified overlap in age estimates when analyzing these filtered genes under strict clock and uncorrelated
Conclusions: Adjusting only for clinical variables led to substantial precision gains (at least 5% in three of the four data sets, with a 1% precision loss in the remaining data set. These gains were unchanged or increased when sample sizes were doubled in our simulations. The precision gains due to incorporating genomic information, beyond the gains from adjusting for clinical variables, were not substantial.
Roberts, K S; Lamberson, W R
Extinction of rare breeds of livestock threatens to reduce the total genetic variation available for selection in the face of the changing environment and new diseases. Swine breeds facing extinction typically share characteristics such as small size, slow growth rate, and high fat percentage, which limit them from contributing to commercial production. Compounding the risk of loss of variation is the lack of pedigree information for many rare breeds due to inadequate herd books, which increases the chance that producers are breeding closely related individuals. By making genetic data available, producers can make more educated breeding decisions to preserve genetic diversity in future generations, and conservation organizations can prioritize investments in breed preservation. The objective of this study was to characterize genetic variation within and among breeds of swine and prioritize heritage breeds for preservation. Genotypes from the Illumina PorcineSNP60 BeadChip (GeneSeek, Lincoln, NE) were obtained for Guinea, Ossabaw Island, Red Wattle, American Saddleback, Mulefoot, British Saddleback, Duroc, Landrace, Large White, Pietrain, and Tamworth pigs. A whole-genome analysis toolset was used to construct a genomic relationship matrix and to calculate inbreeding coefficients for the animals within each breed. Relatedness and average inbreeding coefficient differed among breeds, and pigs from rare breeds were generally more closely related and more inbred ( Guinea pigs. Tamworth, Duroc, and Mulefoot tended to not cluster with the other 7 breeds.
Buchanan, David S.; Lenstra, Johannes A.
This chapter gives an overview on the different breeds of cattle (Bos taurus and B. indicus). Cattle breeds are presented and categorized according to utility and mode of origin. Classification and phylogeny of breeds are also discussed. Furthermore, a description of cattle breeds is provided.
Janssen, K.; Chavanne, H.; Berentsen, P.; Komen, H.
Objectives of this study were to determine the combined market share of breeding companies in aquaculture production in Europe, to describe the main characteristics of breeding companies and their programs, and to provide per species estimates on cumulative genetic gain in growth performance.
Full Text Available Flow cytometry (FCM is a commonly used method for estimating genome size in many organisms. The use of flow cytometry in plants is influenced by endogenous fluorescence inhibitors and may cause an inaccurate estimation of genome size; thus, falsifying the relationship between genome size and phenotypic traits/ecological performance. Quantitative optimization of FCM methodology minimizes such errors, yet there are few studies detailing this methodology. We selected the genus Primulina, one of the most representative and diverse genera of the Old World Gesneriaceae, to evaluate the methodology effect on determining genome size. Our results showed that buffer choice significantly affected genome size estimation in six out of the eight species examined and altered the 2C-value (DNA content by as much as 21.4%. The staining duration and propidium iodide (PI concentration slightly affected the 2C-value. Our experiments showed better histogram quality when the samples were stained for 40 minutes at a PI concentration of 100 µg ml-1. The quality of the estimates was not improved by one-day incubation in the dark at 4 °C or by centrifugation. Thus, our study determined an optimum protocol for genome size measurement in Primulina: LB01 buffer supplemented with 100 µg ml-1 PI and stained for 40 minutes. This protocol also demonstrated a high universality in other Gesneriaceae genera. We report the genome size of nine Gesneriaceae species for the first time. The results showed substantial genome size variation both within and among the species, with the 2C-value ranging between 1.62 and 2.71 pg. Our study highlights the necessity of optimizing the FCM methodology prior to obtaining reliable genome size estimates in a given taxon.
Vouraki, Sotiria; Gelasakis, Athanasios I; Alexandri, Panoraia; Boukouvala, Evridiki; Ekateriniadou, Loukia V; Banos, Georgios; Arsenos, Georgios
Polymorphisms at PRNP gene locus have been associated with resistance against classical scrapie in goats. Genetic selection on this gene within appropriate breeding programs may contribute to the control of the disease. The present study characterized the genetic profile of codons 146, 211 and 222 in three dairy goat breeds in Greece. A total of 766 dairy goats from seven farms were used. Animals belonged to two indigenous Greek, Eghoria (n = 264) and Skopelos (n = 287) and a foreign breed, Damascus (n = 215). Genomic DNA was extracted from blood samples from individual animals. Polymorphisms were detected in these codons using Real-Time PCR analysis and four different Custom TaqMan® SNP Genotyping Assays. Genotypic, allelic and haplotypic frequencies were calculated based on individual animal genotypes. Chi-square tests were used to examine Hardy-Weinberg equilibrium state and compare genotypic distribution across breeds. Genetic distances among the three breeds, and between these and 30 breeds reared in other countries were estimated based on haplotypic frequencies using fixation index FST with Arlequin v3.1 software; a Neighbor-Joining tree was created using PHYLIP package v3.695. Level of statistical significance was set at P = 0.01. All scrapie resistance-associated alleles (146S, 146D, 211Q and 222K) were detected in the studied population. Significant frequency differences were observed between the indigenous Greek and Damascus breeds. Alleles 222K and 146S had the highest frequency in the two indigenous and the Damascus breed, respectively (ca. 6.0%). The studied breeds shared similar haplotypic frequencies with most South Italian and Turkish breeds but differed significantly from North-Western European, Far East and some USA goat breeds. Results suggest there is adequate variation in the PRNP gene locus to support breeding programs for enhanced scrapie resistance in goats reared in Greece. Genetic comparisons among goat breeds indicate that separate
P. Stephen Baenziger
Full Text Available Our long-term goal is to develop wheat cultivars that will improve the profitability and competitiveness of organic producers in Nebraska and the Northern Great Plains. Our approach is to select in early generations for highly heritable traits that are needed for both organic and conventional production (another breeding goal, followed by a targeted organic breeding effort with testing at two organic locations (each in a different ecological region beginning with the F6 generation. Yield analyses from replicated trials at two organic breeding sites and 7 conventional breeding sites from F6 through F12 nurseries revealed, using analyses of variance, biplots, and comparisons of selected lines that it is inappropriate to use data from conventional testing for making germplasm selections for organic production. Selecting and testing lines under organic production practices in different ecological regions was also needed and cultivar selections for organic production were different than those for conventional production. Modifications to this breeding protocol may include growing early generation bulks in an organic cropping system. In the future, our selection efforts should also focus on using state-of-the-art, non-transgenic breeding technologies (genomic selection, marker-assisted breeding, and high throughput phenotyping to synergistically improve organic and conventional wheat breeding.
Sadhu, Abhishek; Bhadra, Sreetama; Bandyopadhyay, Maumita
Cytological parameters such as chromosome numbers and genome sizes of plants are used routinely for studying evolutionary aspects of polyploid plants. Members of Zingiberaceae show a wide range of inter- and intrageneric variation in their reproductive habits and ploidy levels. Conventional cytological study in this group of plants is severely hampered by the presence of diverse secondary metabolites, which also affect their genome size estimation using flow cytometry. None of the several nuclei isolation buffers used in flow cytometry could be used very successfully for members of Zingiberaceae to isolate good quality nuclei from both shoot and root tissues. The competency of eight nuclei isolation buffers was compared with a newly formulated buffer, MB01, in six different genera of Zingiberaceae based on the fluorescence intensity of propidium iodide-stained nuclei using flow cytometric parameters, namely coefficient of variation of the G 0 /G 1 peak, debris factor and nuclei yield factor. Isolated nuclei were studied using fluorescence microscopy and bio-scanning electron microscopy to analyse stain-nuclei interaction and nuclei topology, respectively. Genome contents of 21 species belonging to these six genera were determined using MB01. Flow cytometric parameters showed significant differences among the analysed buffers. MB01 exhibited the best combination of analysed parameters; photomicrographs obtained from fluorescence and electron microscopy supported the superiority of MB01 buffer over other buffers. Among the 21 species studied, nuclear DNA contents of 14 species are reported for the first time. Results of the present study substantiate the enhanced efficacy of MB01, compared to other buffers tested, in the generation of acceptable cytograms from all species of Zingiberaceae studied. Our study facilitates new ways of sample preparation for further flow cytometric analysis of genome size of other members belonging to this highly complex polyploid family
Full Text Available In the last decade, genomic selection has become a standard in the genetic evaluation of livestock populations. However, most procedures for the implementation of genomic selection only consider the additive effects associated with SNP (Single Nucleotide Polymorphism markers used to calculate the prediction of the breeding values of candidates for selection. Nevertheless, the availability of estimates of non-additive effects is of interest because: (i they contribute to an increase in the accuracy of the prediction of breeding values and the genetic response; (ii they allow the definition of mate allocation procedures between candidates for selection; and (iii they can be used to enhance non-additive genetic variation through the definition of appropriate crossbreeding or purebred breeding schemes. This study presents a review of methods for the incorporation of non-additive genetic effects into genomic selection procedures and their potential applications in the prediction of future performance, mate allocation, crossbreeding, and purebred selection. The work concludes with a brief outline of some ideas for future lines of that may help the standard inclusion of non-additive effects in genomic selection.
Norrild, Bodil; Guldberg, Per; Ralfkiær, Elisabeth Methner
Almost all cells in the human body contain a complete copy of the genome with an estimated number of 25,000 genes. The sequences of these genes make up about three percent of the genome and comprise the inherited set of genetic information. The genome also contains information that determines whe...
Liu, Z; Goddard, M E; Hayes, B J; Reinhardt, F; Reents, R
Routine genomic evaluations in animal breeding are usually based on either a BLUP with genomic relationship matrix (GBLUP) or single nucleotide polymorphism (SNP) BLUP model. For a multi-step genomic evaluation, these 2 alternative genomic models were proven to give equivalent predictions for genomic reference animals. The model equivalence was verified also for young genotyped animals without phenotypes. Due to incomplete linkage disequilibrium of SNP markers to genes or causal mutations responsible for genetic inheritance of quantitative traits, SNP markers cannot explain all the genetic variance. A residual polygenic effect is normally fitted in the genomic model to account for the incomplete linkage disequilibrium. In this study, we start by showing the proof that the multi-step GBLUP and SNP BLUP models are equivalent for the reference animals, when they have a residual polygenic effect included. Second, the equivalence of both multi-step genomic models with a residual polygenic effect was also verified for young genotyped animals without phenotypes. Additionally, we derived formulas to convert genomic estimated breeding values of the GBLUP model to its components, direct genomic values and residual polygenic effect. Third, we made a proof that the equivalence of these 2 genomic models with a residual polygenic effect holds also for single-step genomic evaluation. Both the single-step GBLUP and SNP BLUP models lead to equal prediction for genotyped animals with phenotypes (e.g., reference animals), as well as for (young) genotyped animals without phenotypes. Finally, these 2 single-step genomic models with a residual polygenic effect were proven to be equivalent for estimation of SNP effects, too. Copyright © 2016 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
Laghari, Muhammad Younis; Lashari, Punhal; Xu, Peng; Zhao, Zixia; Jiang, Li; Narejo, Naeem Tariq; Xin, Baoping; Sun, Xiaowen; Zhang, Yan
Complete mitochondrial genome of fresh water giant catfish, Wallago attu, was isolated by LA PCR (TakaRa LAtaq, Dalian, China); and sequenced by Sanger's method to obtain the complete mitochondrial genome. The complete mitogenome was 15,639 bp in length and contains 13 typical vertebrate protein-coding genes, 2 rRNA and 22 tRNA genes. The whole genome base composition was estimated to be 31.17% A, 28.15% C, 15.55% G and 25.12% T. The complete mitochondrial genome of catfish, W. attu, provides the fundamental tools for genetic breeding.
Lashari, Punhal; Laghari, Muhammad Younis; Xu, Peng; Zhao, Zixia; Jiang, Li; Narejo, Naeem Tariq; Deng, Yulin; Sun, Xiaowen; Zhang, Yan
The complete mitochondrial genome of Catfish, Rita rita, was isolated by LA PCR (TakaRa LAtaq, Dalian, China); and sequenced by Sanger's method to obtain the complete mitochondrial genome, which is listed Critically Endangered and Red Listed species. The complete mitogenome was 16,449 bp in length and contains 13 typical vertebrate protein-coding genes, 2 rRNA and 22 tRNA genes. The whole genome base composition was estimated to be 33.40% A, 27.43% C, 14.26% G and 24.89% T. The complete mitochondrial genome of catfish, Rita rita provides the basis for genetic breeding and conservation studies.
Full Text Available Organic breeding is a new trend in plant breeding aimed at breeding of organic cultivars adapted to conditions and expectations of organic plant production. The best proof for the need of organic cultivars is the existence of interaction between the performances of genotypes with the kind of production (conventional or organic (graph. 1. The adaptation to low-input conditions of organic production by more eddicient uptake and utilization of plant nutrients is especially important for organic cultivars. One of the basic mechanism of weed control in organic production is the competition of organic cultivars and weeds i.e. the enhanced ability of organic cultivars to suppress the weeds. Resistance/tolerance to diseases and pests is among the most important expectations toward the organic cultivars. In comparison with the methods of conventional plant breeding, in case of organic plant breeding limitations exist in choice of methods for creation of variability and selection classified as permitted, conditionally permitted and banned. The use of genetically modified organisms and their derivated along with induced mutations is not permitted in organic production. The use of molecular markers in organic plant breeding is the only permitted modern method of biotechnology. It is not permitted to patent the breeding material of organic plant breeding or the organic cultivars. .
Sørensen, Anders Christian; Norberg, Elise
In Denmark there are small populations of five Nordic sheep breeds, two of which are Danish in origin. The purpose of this study was to estimate trends in inbreeding for these breeds. All five breeds have been recording pedigrees for decades, so pedigree completeness is adequate. The rate of inbr...
to fledging was unknown owing to the rapid drying of the pan in late March 1999. No Greater Flamingo breeding was seen that season. Exceptional flooding during 1999–2000 produced highly favourable breeding conditions, with numbers of Greater and Lesser Flamingos breeding estimated to be 23 869 and 64 287 pairs, ...
Full Text Available Genetic recombination is a very important evolutionary mechanism that mixes parental haplotypes and produces new raw material for organismal evolution. As a result, information on recombination rates is critical for biological research. In this paper, we introduce a new extremely fast open-source software package (FastEPRR that uses machine learning to estimate recombination rate ρ (=4Ner from intraspecific DNA polymorphism data. When ρ>10 and the number of sampled diploid individuals is large enough (≥50, the variance of ρFastEPRR remains slightly smaller than that of ρLDhat. The new estimate ρcomb (calculated by averaging ρFastEPRR and ρLDhat has the smallest variance of all cases. When estimating ρFastEPRR, the finite-site model was employed to analyze cases with a high rate of recurrent mutations, and an additional method is proposed to consider the effect of variable recombination rates within windows. Simulations encompassing a wide range of parameters demonstrate that different evolutionary factors, such as demography and selection, may not increase the false positive rate of recombination hotspots. Overall, accuracy of FastEPRR is similar to the well-known method, LDhat, but requires far less computation time. Genetic maps for each human population (YRI, CEU, and CHB extracted from the 1000 Genomes OMNI data set were obtained in less than 3 d using just a single CPU core. The Pearson Pairwise correlation coefficient between the ρFastEPRR and ρLDhat maps is very high, ranging between 0.929 and 0.987 at a 5-Mb scale. Considering that sample sizes for these kinds of data are increasing dramatically with advances in next-generation sequencing technologies, FastEPRR (freely available at http://www.picb.ac.cn/evolgen/ is expected to become a widely used tool for establishing genetic maps and studying recombination hotspots in the population genomic era.
Joksic, G.; Nikolic, M.; Vuckovic, M.
The individual variability in response to radiation was examined in a group of 77 healthy individuals, 35-45 years aged, employing Cytochalasin-blocking micronucleus test. Blood samples were irradiated by the most explored therapeutical gamma dose of 2 Gy ( 60 Co) in vitro. The results of our examination demonstrated statistically significant difference in the yield of spontaneously occurring micronuclei between genders of the same age group, while in the yields of induced micronuclei no statistical significance was observed. Out of 77 persons, 4% showed extreme radiosensitivity, while 2% showed extreme radioresistance. Since both extremes are genetically controlled, such genomes could easily be recognized employing CB micronuclei test. It would be useful to perform this type of analysis instead of 'null control' chromosomal aberration analysis for all professionals working in ionizing radiation zone. Persons with such genetic predisposition should be advised to work out of ionizing radiation zone. (author)
Ruffalo, Matthew; Koyutürk, Mehmet; Ray, Soumya; LaFramboise, Thomas
Motivation: Several software tools specialize in the alignment of short next-generation sequencing reads to a reference sequence. Some of these tools report a mapping quality score for each alignment—in principle, this quality score tells researchers the likelihood that the alignment is correct. However, the reported mapping quality often correlates weakly with actual accuracy and the qualities of many mappings are underestimated, encouraging the researchers to discard correct mappings. Further, these low-quality mappings tend to correlate with variations in the genome (both single nucleotide and structural), and such mappings are important in accurately identifying genomic variants. Approach: We develop a machine learning tool, LoQuM (LOgistic regression tool for calibrating the Quality of short read mappings, to assign reliable mapping quality scores to mappings of Illumina reads returned by any alignment tool. LoQuM uses statistics on the read (base quality scores reported by the sequencer) and the alignment (number of matches, mismatches and deletions, mapping quality score returned by the alignment tool, if available, and number of mappings) as features for classification and uses simulated reads to learn a logistic regression model that relates these features to actual mapping quality. Results: We test the predictions of LoQuM on an independent dataset generated by the ART short read simulation software and observe that LoQuM can ‘resurrect’ many mappings that are assigned zero quality scores by the alignment tools and are therefore likely to be discarded by researchers. We also observe that the recalibration of mapping quality scores greatly enhances the precision of called single nucleotide polymorphisms. Availability: LoQuM is available as open source at http://compbio.case.edu/loqum/. Contact: firstname.lastname@example.org. PMID:22962451
The manual is a compilation of work done on the use of induced mutations in plant breeding, and presents general methods and techniques in this field. The use of chemical mutagens and ionizing radiations (X-rays, gamma rays, α- and β-particles, protons, neutrons) are described as well as the effects of these mutagens. The different types of mutations achieved can be divided into genome mutations, chromosome mutations and extra nuclear mutations. Separate chapters deal with mutation techniques in breeding seed-propagated species and asexually propagated plants (examples of development of cultivars given). Plant characters which can be improved by mutation breeding include yield, ripening time, growth habit, disease resistance and tolerance to environmental factors (temperature, salinity etc.). The use of mutagens for some specific plant breeding problems is discussed and attention is also paid to somatic cell genetics in connection with induced mutations. The manual contains a comprehensive bibliography (60 p. references) and a subject index
Sverrisdóttir, Elsa; Janss, Luc; Byrne, Stephen
Breeding for more space and resource efficient crops is important to feed the world’s increasing population. Potatoes produce approximately twice the amount of calories per hectare compared to cereals. The traditional “mate and phenotype” breeding approach is costly and time-consuming; however......, the completion of the genome sequence of potato has enabled the application of genomics-assisted breeding technologies. Genomic selection using genome-wide molecular markers is becoming increasingly applicable to crops as the genotyping costs continue to reduce and it is thus an attractive breeding alternative...... selection, can be obtained with good prediction accuracies in tetraploid potato....
Ashraf, Bilal; Fé, Dario; Jensen, Just
at each SNP in family pools or polyploids. There are, however, several statistical challenges associated with this method, including low sequencing depth and missing values. Low sequencing depth results in inaccuracies in estimates of allele frequencies for each SNP. In this work we have focused...
Full Text Available Tumour cellularity, the relative proportion of tumour and normal cells in a sample, affects the sensitivity of mutation detection, copy number analysis, cancer gene expression and methylation profiling. Tumour cellularity is traditionally estimated by pathological review of sectioned specimens; however this method is both subjective and prone to error due to heterogeneity within lesions and cellularity differences between the sample viewed during pathological review and tissue used for research purposes. In this paper we describe a statistical model to estimate tumour cellularity from SNP array profiles of paired tumour and normal samples using shifts in SNP allele frequency at regions of loss of heterozygosity (LOH in the tumour. We also provide qpure, a software implementation of the method. Our experiments showed that there is a medium correlation 0.42 ([Formula: see text]-value=0.0001 between tumor cellularity estimated by qpure and pathology review. Interestingly there is a high correlation 0.87 ([Formula: see text]-value [Formula: see text] 2.2e-16 between cellularity estimates by qpure and deep Ion Torrent sequencing of known somatic KRAS mutations; and a weaker correlation 0.32 ([Formula: see text]-value=0.004 between IonTorrent sequencing and pathology review. This suggests that qpure may be a more accurate predictor of tumour cellularity than pathology review. qpure can be downloaded from https://sourceforge.net/projects/qpure/.
Schlebusch, Carina M; Malmström, Helena; Günther, Torsten; Sjödin, Per; Coutinho, Alexandra; Edlund, Hanna; Munters, Arielle R; Vicente, Mário; Steyn, Maryna; Soodyall, Himla; Lombard, Marlize; Jakobsson, Mattias
Southern Africa is consistently placed as a potential region for the evolution of Homo sapiens We present genome sequences, up to 13x coverage, from seven ancient individuals from KwaZulu-Natal, South Africa. The remains of three Stone Age hunter-gatherers (about 2000 years old) were genetically similar to current-day southern San groups, and those of four Iron Age farmers (300 to 500 years old) were genetically similar to present-day Bantu-language speakers. We estimate that all modern-day Khoe-San groups have been influenced by 9 to 30% genetic admixture from East Africans/Eurasians. Using traditional and new approaches, we estimate the first modern human population divergence time to between 350,000 and 260,000 years ago. This estimate increases the deepest divergence among modern humans, coinciding with anatomical developments of archaic humans into modern humans, as represented in the local fossil record. Copyright © 2017 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works.
Full Text Available The genus Vitis (the grapevine is a group of highly diverse, diploid woody perennial vines consisting of approximately 60 species from across the northern hemisphere. It is the world's most valuable horticultural crop with ~8 million hectares planted, most of which is processed into wine. To gain insights into the use of wild Vitis species during the past century of interspecific grape breeding and to provide a foundation for marker-assisted breeding programmes, we present a principal components analysis (PCA based ancestry estimation method to calculate admixture proportions of hybrid grapes in the United States Department of Agriculture grape germplasm collection using genome-wide polymorphism data. We find that grape breeders have backcrossed to both the domesticated V. vinifera and wild Vitis species and that reasonably accurate genome-wide ancestry estimation can be performed on interspecific Vitis hybrids using a panel of fewer than 50 ancestry informative markers (AIMs. We compare measures of ancestry informativeness used in selecting SNP panels for two-way admixture estimation, and verify the accuracy of our method on simulated populations of admixed offspring. Our method of ancestry deconvolution provides a first step towards selection at the seed or seedling stage for desirable admixture profiles, which will facilitate marker-assisted breeding that aims to introgress traits from wild Vitis species while retaining the desirable characteristics of elite V. vinifera cultivars.
Sawler, Jason; Reisch, Bruce; Aradhya, Mallikarjuna K.; Prins, Bernard; Zhong, Gan-Yuan; Schwaninger, Heidi; Simon, Charles; Buckler, Edward; Myles, Sean
The genus Vitis (the grapevine) is a group of highly diverse, diploid woody perennial vines consisting of approximately 60 species from across the northern hemisphere. It is the world’s most valuable horticultural crop with ~8 million hectares planted, most of which is processed into wine. To gain insights into the use of wild Vitis species during the past century of interspecific grape breeding and to provide a foundation for marker-assisted breeding programmes, we present a principal components analysis (PCA) based ancestry estimation method to calculate admixture proportions of hybrid grapes in the United States Department of Agriculture grape germplasm collection using genome-wide polymorphism data. We find that grape breeders have backcrossed to both the domesticated V. vinifera and wild Vitis species and that reasonably accurate genome-wide ancestry estimation can be performed on interspecific Vitis hybrids using a panel of fewer than 50 ancestry informative markers (AIMs). We compare measures of ancestry informativeness used in selecting SNP panels for two-way admixture estimation, and verify the accuracy of our method on simulated populations of admixed offspring. Our method of ancestry deconvolution provides a first step towards selection at the seed or seedling stage for desirable admixture profiles, which will facilitate marker-assisted breeding that aims to introgress traits from wild Vitis species while retaining the desirable characteristics of elite V. vinifera cultivars. PMID:24244717
The aim of this study was the estimation of the cross-breeding influence of Zlotnicka spotted sows with boars of polish large white and Duroc breeds on carcass traits of fatteners. 50 pigs were divided into four groups: Zlotnicka spotted (ZS), Zlotnicka spotted x polish large white (ZS x PLW), Zlotnicka spotted x Duroc (ZS x D) ...
Fleischmann, Andreas; Michael, Todd P.; Rivadavia, Fernando; Sousa, Aretuza; Wang, Wenqin; Temsch, Eva M.; Greilhuber, Johann; Müller, Kai F.; Heubl, Günther
Background and Aims Some species of Genlisea possess ultrasmall nuclear genomes, the smallest known among angiosperms, and some have been found to have chromosomes of diminutive size, which may explain why chromosome numbers and karyotypes are not known for the majority of species of the genus. However, other members of the genus do not possess ultrasmall genomes, nor do most taxa studied in related genera of the family or order. This study therefore examined the evolution of genome sizes and chromosome numbers in Genlisea in a phylogenetic context. The correlations of genome size with chromosome number and size, with the phylogeny of the group and with growth forms and habitats were also examined. Methods Nuclear genome sizes were measured from cultivated plant material for a comprehensive sampling of taxa, including nearly half of all species of Genlisea and representing all major lineages. Flow cytometric measurements were conducted in parallel in two laboratories in order to compare the consistency of different methods and controls. Chromosome counts were performed for the majority of taxa, comparing different staining techniques for the ultrasmall chromosomes. Key Results Genome sizes of 15 taxa of Genlisea are presented and interpreted in a phylogenetic context. A high degree of congruence was found between genome size distribution and the major phylogenetic lineages. Ultrasmall genomes with 1C values of sections of the genus. The smallest known plant genomes were not found in G. margaretae, as previously reported, but in G. tuberosa (1C ≈ 61 Mbp) and some strains of G. aurea (1C ≈ 64 Mbp). Conclusions Genlisea is an ideal candidate model organism for the understanding of genome reduction as the genus includes species with both relatively large (∼1700 Mbp) and ultrasmall (∼61 Mbp) genomes. This comparative, phylogeny-based analysis of genome sizes and karyotypes in Genlisea provides essential data for selection of suitable species for comparative
Colwell, F. S.; Crawford, R. L.; Sorenson, K.
Dissolved dense nonaqueous-phase liquid plumes are persistent, widespread problems in the DOE complex. While perceived as being difficult to degrade, at the Idaho National Engineering and Environmental Laboratory, dissolved trichloroethylene (TCE) is disappearing from the Snake River Plain aquifer (SRPA) by natural attenuation, a finding that saves significant site restoration costs. Acceptance of monitored natural attenuation as a preferred treatment technology requires direct proof of the process and rate of the degradation. Our proposal aims to provide that proof for one such site by testing two hypotheses. First, we believe that realistic values for in situ rates of TCE cometabolism can be obtained by sustaining the putative microorganisms at the low catabolic activities consistent with aquifer conditions. Second, the patterns of functional gene expression evident in these communities under starvation conditions while carrying out TCE cometabolism can be used to diagnose the cometabolic activity in the aquifer itself. Using the cometabolism rate parameters derived in low-growth bioreactors, we will complete the models that predict the time until background levels of TCE are attained at this location and validate the long term stewardship of this plume. Realistic terms for cometabolism of TCE will provide marked improvements in DOE's ability to predict and monitor natural attenuation of chlorinated organics at other sites, increase the acceptability of this solution, and provide significant economic and health benefits through this noninvasive remediation strategy. Finally, this project will derive valuable genomic information about the functional attributes of subsurface microbial communities upon which DOE must depend to resolve some of its most difficult contamination issues.
Xu, Peng; Zhang, Xiaofeng; Wang, Xumin; Li, Jiongtang; Liu, Guiming; Kuang, Youyi; Xu, Jian; Zheng, Xianhu; Ren, Lufeng; Wang, Guoliang; Zhang, Yan; Huo, Linhe; Zhao, Zixia; Cao, Dingchen; Lu, Cuiyun; Li, Chao; Zhou, Yi; Liu, Zhanjiang; Fan, Zhonghua; Shan, Guangle; Li, Xingang; Wu, Shuangxiu; Song, Lipu; Hou, Guangyuan; Jiang, Yanliang; Jeney, Zsigmond; Yu, Dan; Wang, Li; Shao, Changjun; Song, Lai; Sun, Jing; Ji, Peifeng; Wang, Jian; Li, Qiang; Xu, Liming; Sun, Fanyue; Feng, Jianxin; Wang, Chenghui; Wang, Shaolin; Wang, Baosen; Li, Yan; Zhu, Yaping; Xue, Wei; Zhao, Lan; Wang, Jintu; Gu, Ying; Lv, Weihua; Wu, Kejing; Xiao, Jingfa; Wu, Jiayan; Zhang, Zhang; Yu, Jun; Sun, Xiaowen
The common carp, Cyprinus carpio, is one of the most important cyprinid species and globally accounts for 10% of freshwater aquaculture production. Here we present a draft genome of domesticated C. carpio (strain Songpu), whose current assembly contains 52,610 protein-coding genes and approximately 92.3% coverage of its paleotetraploidized genome (2n = 100). The latest round of whole-genome duplication has been estimated to have occurred approximately 8.2 million years ago. Genome resequencing of 33 representative individuals from worldwide populations demonstrates a single origin for C. carpio in 2 subspecies (C. carpio Haematopterus and C. carpio carpio). Integrative genomic and transcriptomic analyses were used to identify loci potentially associated with traits including scaling patterns and skin color. In combination with the high-resolution genetic map, the draft genome paves the way for better molecular studies and improved genome-assisted breeding of C. carpio and other closely related species.
Serra, Angela; Coretto, Pietro; Fratello, Michele; Tagliaferri, Roberto; Stegle, Oliver
Microarray technology can be used to study the expression of thousands of genes across a number of different experimental conditions, usually hundreds. The underlying principle is that genes sharing similar expression patterns, across different samples, can be part of the same co-expression system, or they may share the same biological functions. Groups of genes are usually identified based on cluster analysis. Clustering methods rely on the similarity matrix between genes. A common choice to measure similarity is to compute the sample correlation matrix. Dimensionality reduction is another popular data analysis task which is also based on covariance/correlation matrix estimates. Unfortunately, covariance/correlation matrix estimation suffers from the intrinsic noise present in high-dimensional data. Sources of noise are: sampling variations, presents of outlying sample units, and the fact that in most cases the number of units is much larger than the number of genes. In this paper, we propose a robust correlation matrix estimator that is regularized based on adaptive thresholding. The resulting method jointly tames the effects of the high-dimensionality, and data contamination. Computations are easy to implement and do not require hand tunings. Both simulated and real data are analyzed. A Monte Carlo experiment shows that the proposed method is capable of remarkable performances. Our correlation metric is more robust to outliers compared with the existing alternatives in two gene expression datasets. It is also shown how the regularization allows to automatically detect and filter spurious correlations. The same regularization is also extended to other less robust correlation measures. Finally, we apply the ARACNE algorithm on the SyNTreN gene expression data. Sensitivity and specificity of the reconstructed network is compared with the gold standard. We show that ARACNE performs better when it takes the proposed correlation matrix estimator as input. The R
Igarashi, Megumi; Hatsuyama, Yoshimichi; Harada, Takeo; Fukasawa-Akada, Tomoko
Apple is a fruit crop of significant economic importance, and breeders world wide continue to develop novel cultivars with improved characteristics. The lengthy juvenile period and the large field space required to grow apple populations have imposed major limitations on breeding. Various molecular biological techniques have been employed to make apple breeding easier. Transgenic technology has facilitated the development of apples with resistance to fungal or bacterial diseases, improved fruit quality, or root stocks with better rooting or dwarfing ability. DNA markers for disease resistance (scab, powdery mildew, fire-blight, Alternaria blotch) and fruit skin color have also been developed, and marker-assisted selection (MAS) has been employed in breeding programs. In the last decade, genomic sequences and chromosome maps of various cultivars have become available, allowing the development of large SNP arrays, enabling efficient QTL mapping and genomic selection (GS). In recent years, new technologies for genetic improvement, such as trans-grafting, virus vectors, and genome-editing, have emerged. Using these techniques, no foreign genes are present in the final product, and some of them show considerable promise for application to apple breeding. PMID:27069388
Marcos Eli Buzanskas
Full Text Available The aim of this study was to evaluate the level of introgression of breeds in the Canchim (CA: 62.5% Charolais-37.5% Zebu and MA genetic group (MA: 65.6% Charolais-34.4% Zebu cattle using genomic information on Charolais (CH, Nelore (NE, and Indubrasil (IB breeds. The number of animals used was 395 (CA and MA, 763 (NE, 338 (CH, and 37 (IB. The Bovine50SNP BeadChip from Illumina panel was used to estimate the levels of introgression of breeds considering the Maximum likelihood, Bayesian, and Single Regression method. After genotype quality control, 32,308 SNPs were considered in the analysis. Furthermore, three thresholds to prune out SNPs in linkage disequilibrium higher than 0.10, 0.05, and 0.01 were considered, resulting in 15,286, 7,652, and 1,582 SNPs, respectively. For k = 2, the proportion of taurine and indicine varied from the expected proportion based on pedigree for all methods studied. For k = 3, the Regression method was able to differentiate the animals in three main clusters assigned to each purebred breed, showing more reasonable according to its biological viewpoint. Analyzing the data considering k = 2 seems to be more appropriate for Canchim-MA animals due to its biological interpretation. The usage of 32,308 SNPs in the analyses resulted in similar findings between the estimated and expected breed proportions. Using the Regression approach, a contribution of Indubrasil was observed in Canchim-MA when k = 3 was considered. Genetic parameter estimation could account for this breed composition information as a source of variation in order to improve the accuracy of genetic models. Our findings may help assemble appropriate reference populations for genomic prediction for Canchim-MA in order to improve prediction accuracy. Using the information on the level of introgression in each individual could also be useful in breeding or crossing design to improve individual heterosis in crossbred cattle.
kantanen, J; Olsaker, Ingrid; Holm, Lars-Erik
Blood samples were collected from 743 animals from 15 indigenous, 2 old imported, and 3 commercial North European cattle breeds. The samples were analyzed for 11 erythrocyte antigen systems, 8 proteins, and 10 microsatellites, and used to assess inter- and intrabreed genetic variation and genetic......, allelic diversity has been reduced in several breeds, which was explained by limited effective population sizes over the course of man-directed breed development and demographic bottlenecks of indigenous breeds. A tree showing genetic relationships between breeds was constructed from a matrix of random...... drift-based genetic distance estimates. The breeds were classified on the basis of the tree topology into four major breed groups, defined as Northern indigenous breeds, Southern breeds, Ayrshire and Friesian breeds, and Jersey. Grouping of Nordic breeds was supported by documented breed history...
Thuy, N T.D. [Department of Animal Breeding and Biotechnology, University of Hohenheim, Stuttgart (Germany); Institute of Biotechnology (IBT), National Center for Natural Science and Technology, Hanoi (Viet Nam); Melchinger, E; Kuss, A W; Peischl, T; Bartenschlager, H; Geldermann, H [Department of Animal Breeding and Biotechnology, University of Hohenheim, Stuttgart (Germany); Cuong, N V [Institute of Biotechnology (IBT), National Center for Natural Science and Technology, Hanoi (Viet Nam)
Indigenous resources of the Asian pig population are less defined and only rarely compared with European breeds. In this study, five indigenous pig breeds from Viet Nam (Mong Cai, Muong Khuong, Co, Meo, Tap Na), two exotic breeds kept in Viet Nam (Large White, Landrace), three European commercial breeds (Pietrain, Landrace, Large White), and European Wild Boar were chosen for evaluation and comparison of genetic diversity. Samples and data from 317 animals were collected and ten polymorphic microsatellite loci were selected according to the recommendations of the FAO Domestic Animal Diversity Information System (DAD-IS; http://www.fao.org/dad-is/). Effective number of alleles, Polymorphism Information Content (PIC), within-breed diversity, estimated heterozygosities and tests for Hardy-Weinberg equilibrium were determined. Breed differentiation was evaluated using the fixation indices of Wright (1951). Genetic distances between breeds were estimated according to Nei (1972) and used for the construction of UPGMA dendrograms which were evaluated by bootstrapping. Heterozygosity was higher in indigenous Vietnamese breeds than in the other breeds. The Vietnamese indigenous breeds also showed higher genetic diversity than the European breeds and all genetic distances had a strong bootstrap support. The European commercial breeds, in contrast, were closely related and bootstrapping values for genetic distances among them were below 60%. European Wild Boar displayed closer relation with commercial breeds of European origin than with the native breeds from Viet Nam. This study is one of the first to contribute to a genetic characterization of autochthonous Vietnamese pig breeds and it clearly demonstrates that these breeds harbour a rich reservoir of genetic diversity. (author)
Thuy, N.T.D.; Melchinger, E.; Kuss, A.W.; Peischl, T.; Bartenschlager, H.; Geldermann, H.; Cuong, N.V.
Indigenous resources of the Asian pig population are less defined and only rarely compared with European breeds. In this study, five indigenous pig breeds from Viet Nam (Mong Cai, Muong Khuong, Co, Meo, Tap Na), two exotic breeds kept in Viet Nam (Large White, Landrace), three European commercial breeds (Pietrain, Landrace, Large White), and European Wild Boar were chosen for evaluation and comparison of genetic diversity. Samples and data from 317 animals were collected and ten polymorphic microsatellite loci were selected according to the recommendations of the FAO Domestic Animal Diversity Information System (DAD-IS; http://www.fao.org/dad-is/). Effective number of alleles, Polymorphism Information Content (PIC), within-breed diversity, estimated heterozygosities and tests for Hardy-Weinberg equilibrium were determined. Breed differentiation was evaluated using the fixation indices of Wright (1951). Genetic distances between breeds were estimated according to Nei (1972) and used for the construction of UPGMA dendrograms which were evaluated by bootstrapping. Heterozygosity was higher in indigenous Vietnamese breeds than in the other breeds. The Vietnamese indigenous breeds also showed higher genetic diversity than the European breeds and all genetic distances had a strong bootstrap support. The European commercial breeds, in contrast, were closely related and bootstrapping values for genetic distances among them were below 60%. European Wild Boar displayed closer relation with commercial breeds of European origin than with the native breeds from Viet Nam. This study is one of the first to contribute to a genetic characterization of autochthonous Vietnamese pig breeds and it clearly demonstrates that these breeds harbour a rich reservoir of genetic diversity. (author)
Molecular markers are the most powerful genomic tools to increase the efficiency and precision of breeding practices for crop improvement. Progress in the development of genomic resources in the leading legume crops of the semi-arid tropics (SAT), namely, chickpea (Cicer arietinum), pigeonpea (Cajanus cajan) and ...
The enormous population growth, climate change and global warming are now considered major threats to agriculture and world's food security. To improve the productivity and sustainability of agriculture, the development of high-yielding and durable abiotic and biotic stress-tolerant cultivars and/climate resilient crops is ...
Full Text Available The aim of this study was to obtain unbiased estimates of the diversity parameters, the population history, and the degree of admixture in Cika cattle which represents the local admixed breeds at risk of extinction undergoing challenging conservation programs. Genetic analyses were performed on the genome-wide Single Nucleotide Polymorphism (SNP Illumina Bovine SNP50 array data of 76 Cika animals and 531 animals from 14 reference populations. To obtain unbiased estimates we used short haplotypes spanning four markers instead of single SNPs to avoid an ascertainment bias of the BovineSNP50 array. Genome-wide haplotypes combined with partial pedigree and type trait classification show the potential to improve identification of purebred animals with a low degree of admixture. Phylogenetic analyses demonstrated unique genetic identity of Cika animals. Genetic distance matrix presented by rooted Neighbour-Net suggested long and broad phylogenetic connection between Cika and Pinzgauer. Unsupervised clustering performed by the admixture analysis and two-dimensional presentation of the genetic distances between individuals also suggest Cika is a distinct breed despite being similar in appearance to Pinzgauer. Animals identified as the most purebred could be used as a nucleus for a recovery of the native genetic background in the current admixed population. The results show that local well-adapted strains, which have never been intensively managed and differentiated into specific breeds, exhibit large haplotype diversity. They suggest a conservation and recovery approach that does not rely exclusively on the search for the original native genetic background but rather on the identification and removal of common introgressed haplotypes would be more powerful. Successful implementation of such an approach should be based on combining phenotype, pedigree, and genome-wide haplotype data of the breed of interest and a spectrum of reference breeds which
Liu, Shenglin; Hansen, Michael M; Jacobsen, Magnus W
We analysed 81 whole genome sequences of threespine sticklebacks from Pacific North America, Greenland and Northern Europe, representing 16 populations. Principal component analysis of nuclear SNPs grouped populations according to geographical location, with Pacific populations being more divergent from each other relative to European and Greenlandic populations. Analysis of mitogenome sequences showed Northern European populations to represent a single phylogeographical lineage, whereas Greenlandic and particularly Pacific populations showed admixture between lineages. We estimated demographic history using a genomewide coalescence with recombination approach. The Pacific populations showed gradual population expansion starting >100 Kya, possibly reflecting persistence in cryptic refuges near the present distributional range, although we do not rule out possible influence of ancient admixture. Sharp population declines ca. 14-15 Kya were suggested to reflect founding of freshwater populations by marine ancestors. In Greenland and Northern Europe, demographic expansion started ca. 20-25 Kya coinciding with the end of the Last Glacial Maximum. In both regions, marine and freshwater populations started to show different demographic trajectories ca. 8-9 Kya, suggesting that this was the time of recolonization. In Northern Europe, this estimate was surprisingly late, but found support in subfossil evidence for presence of several freshwater fish species but not sticklebacks 12 Kya. The results demonstrate distinctly different demographic histories across geographical regions with potential consequences for adaptive processes. They also provide empirical support for previous assumptions about freshwater populations being founded independently from large, coherent marine populations, a key element in the Transporter Hypothesis invoked to explain the widespread occurrence of parallel evolution across freshwater stickleback populations. © 2016 John Wiley & Sons Ltd.
Pasaniuc, Bogdan; Sankararaman, Sriram; Torgerson, Dara G.; Gignoux, Christopher; Zaitlen, Noah; Eng, Celeste; Rodriguez-Cintron, William; Chapela, Rocio; Ford, Jean G.; Avila, Pedro C.; Rodriguez-Santana, Jose; Chen, Gary K.; Le Marchand, Loic; Henderson, Brian; Reich, David; Haiman, Christopher A.; Gonzàlez Burchard, Esteban; Halperin, Eran
Motivation: Local ancestry analysis of genotype data from recently admixed populations (e.g. Latinos, African Americans) provides key insights into population history and disease genetics. Although methods for local ancestry inference have been extensively validated in simulations (under many unrealistic assumptions), no empirical study of local ancestry accuracy in Latinos exists to date. Hence, interpreting findings that rely on local ancestry in Latinos is challenging. Results: Here, we use 489 nuclear families from the mainland USA, Puerto Rico and Mexico in conjunction with 3204 unrelated Latinos from the Multiethnic Cohort study to provide the first empirical characterization of local ancestry inference accuracy in Latinos. Our approach for identifying errors does not rely on simulations but on the observation that local ancestry in families follows Mendelian inheritance. We measure the rate of local ancestry assignments that lead to Mendelian inconsistencies in local ancestry in trios (MILANC), which provides a lower bound on errors in the local ancestry estimates. We show that MILANC rates observed in simulations underestimate the rate observed in real data, and that MILANC varies substantially across the genome. Second, across a wide range of methods, we observe that loci with large deviations in local ancestry also show enrichment in MILANC rates. Therefore, local ancestry estimates at such loci should be interpreted with caution. Finally, we reconstruct ancestral haplotype panels to be used as reference panels in local ancestry inference and show that ancestry inference is significantly improved by incoroprating these reference panels. Availability and implementation: We provide the reconstructed reference panels together with the maps of MILANC rates as a public resource for researchers analyzing local ancestry in Latinos at http://bogdanlab.pathology.ucla.edu. Contact: email@example.com Supplementary information: Supplementary data are
Key technological problems that influence tritium breeding in fusion blankets are reviewed. The breeding potential of candidate materials is evaluated and compared to the tritium breeding requirements. The sensitivity of tritium breeding to design and nuclear data parameters is reviewed. A framework for an integrated approach to improve tritium breeding prediction is discussed with emphasis on nuclear data requirements
Full Text Available About 950,000 goats, farmed mostly in hilly and mountainous areas of Albania, contribute about 8% of the country’s total milk production. In order to increase milk production, farmers are currently using crosses of the local goat breed with exotic breeds, mainly the Alpine breed from France. This study examines milk production data of first lactation from 45 goats of the local breed, 82 goats of the Alpine breed and 58 F1 crosses (♂Alpine breed x ♀local breed. The goats were kept on small-scale farms according to the traditional Albanian system. Milking was carried out in the morning and evening. Kids were weaned at 65 days of age after which milking started. Milk yield was recorded twice with a 15-day interval between the two readings. Total milk yield was calculated using the Fleischmann method. The F1 goats produced 37.8 kg more milk than local breed goats although the lactation length (P<0.05 of F1 goats was six days shorter compared to that of local breed goats (P<0.05. Analysis of variance showed a highly significant effect (P<0.01 of the genotype factor on milk production. The average Cappio-Borlino curves of three genotypes indicated that the lactation curves of local breed and F1 crosses were similar. Although the F1 cross goats had 50% of their genomes from a genetically improved breed they were still able to deal with the difficult conditions that characterize the traditional extensive farming systems in Albania. Breeding pure Alpine breed or its crosses with the local goat breed improved milk production in an extensive traditional system.
Full Text Available The domestic dog, Canis familiaris, exhibits profound phenotypic diversity and is an ideal model organism for the genetic dissection of simple and complex traits. However, some of the most interesting phenotypes are fixed in particular breeds and are therefore less tractable to genetic analysis using classical segregation-based mapping approaches. We implemented an across breed mapping approach using a moderately dense SNP array, a low number of animals and breeds carefully selected for the phenotypes of interest to identify genetic variants responsible for breed-defining characteristics. Using a modest number of affected (10-30 and control (20-60 samples from multiple breeds, the correct chromosomal assignment was identified in a proof of concept experiment using three previously defined loci; hyperuricosuria, white spotting and chondrodysplasia. Genome-wide association was performed in a similar manner for one of the most striking morphological traits in dogs: brachycephalic head type. Although candidate gene approaches based on comparable phenotypes in mice and humans have been utilized for this trait, the causative gene has remained elusive using this method. Samples from nine affected breeds and thirteen control breeds identified strong genome-wide associations for brachycephalic head type on Cfa 1. Two independent datasets identified the same genomic region. Levels of relative heterozygosity in the associated region indicate that it has been subjected to a selective sweep, consistent with it being a breed defining morphological characteristic. Genotyping additional dogs in the region confirmed the association. To date, the genetic structure of dog breeds has primarily been exploited for genome wide association for segregating traits. These results demonstrate that non-segregating traits under strong selection are equally tractable to genetic analysis using small sample numbers.
Hollenberg, G.W.; Johnson, C.E.; Abdou, M.
Tritium breeding materials are essential to the operation of D-T fusion facilities. Both of the present options - solid ceramic breeding materials and liquid metal materials are reviewed with emphasis not only on their attractive features but also on critical materials issues which must be resolved
Hollenberg, G.W.; Johnson, C.E.; Abdou, M.A.
Tritium breeding materials are essential to the operation of D-T fusion facilities. Both of the present options - solid ceramic breeding materials and liquid metal materials are reviewed with emphasis not only on their attractive features but also on critical materials issues which must be resolved
Received 31 August 1996; accepted 20 March /998. Mitochondrial DNA cleavage patterns from representative animals of the Afrikaner and Nguni sanga cattle breeds, indigenous to Southern Africa, were compared to the mitochondrial DNA cleavage patterns of the Brahman (zebu) and the Jersey. (taurine) cattle breeds.
Graml, R; Ohmayer, G; Pirchner, F; Erhard, L; Buchberger, J; Mostageer, A
Gene frequencies were estimated in a sample of Baladi cattle for milk proteins, blood proteins and blood groups. Gene frequency estimates of Bos taurus, Bos indicus and Sanga breeds were assembled from the literature. The gene frequencies were utilized for estimating the genetic distance between the breeds and breed groups. The Egyptian Baladi cattle appeared to be closer to Bos taurus breeds than to the Sanga. They are far removed from Zebus.
Probabilistic quantitative microbial risk assessment model of norovirus from wastewater irrigated vegetables in Ghana using genome copies and fecal indicator ratio conversion for estimating exposure dose.
Owusu-Ansah, Emmanuel de-Graft Johnson; Sampson, Angelina; Amponsah, Samuel K; Abaidoo, Robert C; Dalsgaard, Anders; Hald, Tine
The need to replace the commonly applied fecal indicator conversions ratio (an assumption of 1:10 -5 virus to fecal indicator organism) in Quantitative Microbial Risk Assessment (QMRA) with models based on quantitative data on the virus of interest has gained prominence due to the different physical and environmental factors that might influence the reliability of using indicator organisms in microbial risk assessment. The challenges facing analytical studies on virus enumeration (genome copies or particles) have contributed to the already existing lack of data in QMRA modelling. This study attempts to fit a QMRA model to genome copies of norovirus data. The model estimates the risk of norovirus infection from the intake of vegetables irrigated with wastewater from different sources. The results were compared to the results of a corresponding model using the fecal indicator conversion ratio to estimate the norovirus count. In all scenarios of using different water sources, the application of the fecal indicator conversion ratio underestimated the norovirus disease burden, measured by the Disability Adjusted Life Years (DALYs), when compared to results using the genome copies norovirus data. In some cases the difference was >2 orders of magnitude. All scenarios using genome copies met the 10 -4 DALY per person per year for consumption of vegetables irrigated with wastewater, although these results are considered to be highly conservative risk estimates. The fecal indicator conversion ratio model of stream-water and drain-water sources of wastewater achieved the 10 -6 DALY per person per year threshold, which tends to indicate an underestimation of health risk when compared to using genome copies for estimating the dose. Copyright © 2017 Elsevier B.V. All rights reserved.
Full Text Available Alfalfa ( L., an important forage crop that is also a potential biofuel crop, has advantages of high yield, high lignocellulose concentration in stems, and has low input costs. In this study, we investigated population structure and linkage disequilibrium (LD patterns in a tetraploid alfalfa breeding population using genome-wide simple sequence repeat (SSR markers and identified markers related to yield and cell wall composition by association mapping. No obvious population structure was found in our alfalfa breeding population, which could be due to the relatively narrow genetic base of the founders and/or due to two generations of random mating. We found significant LD ( 10% alleles across the 71 SSR markers, 15 showed strong association ( < 0.005 with yield in at least one of five environments, and most of the 15 alleles were identified in multiple environments. Only one allele showed strong association with acid detergent fiber (ADF and one allele with acid detergent lignin (ADL. Alleles associated with traits could be directly applied in a breeding program using marker-assisted selection. However, based on our estimated LD level, we would need about 1000 markers to explore the whole alfalfa genome for association between markers and traits.
Smith, D.; Billone, M.; Gohar, Y.; Baker, C.; Mori, S.; Kuroda, T.; Maki, K.; Takatsu, H.; Yoshida, H.; Raffray, A.; Sviatoslavsky, I.; Simbolotti, G.; Shatalov, G.
The terms of reference for ITER provide for incorporation of a tritium breeding blanket with a breeding ratio as close to unity as practical. A breeding blanket is required to assure an adequate supply of tritium to meet the program objectives. Based on specified design criteria, a ceramic breeder concept with water coolant and an austenitic steel structure has been selected as the first option and lithium-lead blanket concept has been chosen as an alternate option. The first wall, blanket, and shield are integrated into a single unit with separate cooling systems. The design makes extensive use of beryllium to enhance the tritium breeding ratio. The design goals with a tritium breeding ratio of 0.8--0.9 have been achieved and the R ampersand D requirements to qualify the design have been identified. 4 refs., 8 figs., 2 tabs
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.
Gu, Feng; Gao, Caixia
Genome editing technology, as an innovative biotechnology, has been widely used for editing the genome from model organisms, animals, plants and microbes. CRISPR/Cas9-based genome editing technology shows its great value and potential in the dissection of functional genomics, improved breeding and genetic disease treatment. In the present special issue, the principle and application of genome editing techniques has been summarized. The advantages and disadvantages of the current genome editing technology and future prospects would also be highlighted.
Tian, Yang; Zeng, Yan; Zhang, Jing; Yang, ChengGuang; Yan, Liang; Wang, XuanJun; Shi, ChongYing; Xie, Jing; Dai, TianYi; Peng, Lei; Zeng Huan, Yu; Xu, AnNi; Huang, YeWei; Zhang, JiaJin; Ma, Xiao; Dong, Yang; Hao, ShuMei; Sheng, Jun
The drumstick tree (Moringa oleifera Lam.) is a perennial crop that has gained popularity in certain developing countries for its high-nutrition content and adaptability to arid and semi-arid environments. Here we report a high-quality draft genome sequence of M. oleifera. This assembly represents 91.78% of the estimated genome size and contains 19,465 protein-coding genes. Comparative genomic analysis between M. oleifera and related woody plant genomes helps clarify the general evolution of this species, while the identification of several species-specific gene families and positively selected genes in M. oleifera may help identify genes related to M. oleifera's high protein content, fast-growth, heat and stress tolerance. This reference genome greatly extends the basic research on M. oleifera, and may further promote applying genomics to enhanced breeding and improvement of M. oleifera.
Kang, Si Yong; Kim, Dong Sub; Lee, Geung Joo
A mutation breeding is to use physical or chemical mutagens to induce mutagenesis, followed by individual selections with favorable traits. The mutation breeding has many advantages over other breeding methods, which include the usefulness for improving one or two inferior characteristics, applications to broad species with different reproductive systems or to diverse plant materials, native or plant introduction with narrow genetic background, time and cost-effectiveness, and valuable mutant resources for genomic researches. Recent applications of the radiation breeding techniques to developments of flowering plants or food crops with improved functional constituents heightened the public's interests in agriculture and in our genetic resources and seed industries. The goals of this project, therefore, include achieving advances in domestic seed industries and agricultural productivities by developing and using new radiation mutants with favored traits, protecting an intellectual property right of domestic seeds or germplasm, and sharing the valuable mutants and mutated gene information for the genomic and biotech researches that eventually leads to economic benefits
Kang, Si Yong; Kim, Dong Sub; Lee, Geung Joo (and others)
A mutation breeding is to use physical or chemical mutagens to induce mutagenesis, followed by individual selections with favorable traits. The mutation breeding has many advantages over other breeding methods, which include the usefulness for improving one or two inferior characteristics, applications to broad species with different reproductive systems or to diverse plant materials, native or plant introduction with narrow genetic background, time and cost-effectiveness, and valuable mutant resources for genomic researches. Recent applications of the radiation breeding techniques to developments of flowering plants or food crops with improved functional constituents heightened the public's interests in agriculture and in our genetic resources and seed industries. The goals of this project, therefore, include achieving advances in domestic seed industries and agricultural productivities by developing and using new radiation mutants with favored traits, protecting an intellectual property right of domestic seeds or germplasm, and sharing the valuable mutants and mutated gene information for the genomic and biotech researches that eventually leads to economic benefits.
Bolger, Marie; Gundlach, Heidrun; Scholz, Uwe; Mayer, Klaus; Usadel, Björn; Schwacke, Rainer; Schmutzer, Thomas; Chen, Jinbo; Arend, Daniel; Oppermann, Markus; Weise, Stephan; Lange, Matthias; Fiorani, Fabio; Spannagl, Manuel
Recent advances in sequencing technologies have greatly accelerated the rate of plant genome and applied breeding research. Despite this advancing trend, plant genomes continue to present numerous difficulties to the standard tools and pipelines not only for genome assembly but also gene annotation and downstream analysis.Here we give a perspective on tools, resources and services necessary to assemble and analyze plant genomes and link them to plant phenotypes.
Peter T Fretwell
Full Text Available We describe a new breeding behaviour discovered in emperor penguins; utilizing satellite and aerial-survey observations four emperor penguin breeding colonies have been recorded as existing on ice-shelves. Emperors have previously been considered as a sea-ice obligate species, with 44 of the 46 colonies located on sea-ice (the other two small colonies are on land. Of the colonies found on ice-shelves, two are newly discovered, and these have been recorded on shelves every season that they have been observed, the other two have been recorded both on ice-shelves and sea-ice in different breeding seasons. We conduct two analyses; the first using synthetic aperture radar data to assess why the largest of the four colonies, for which we have most data, locates sometimes on the shelf and sometimes on the sea-ice, and find that in years where the sea-ice forms late, the colony relocates onto the ice-shelf. The second analysis uses a number of environmental variables to test the habitat marginality of all emperor penguin breeding sites. We find that three of the four colonies reported in this study are in the most northerly, warmest conditions where sea-ice is often sub-optimal. The emperor penguin's reliance on sea-ice as a breeding platform coupled with recent concerns over changed sea-ice patterns consequent on regional warming, has led to their designation as "near threatened" in the IUCN red list. Current climate models predict that future loss of sea-ice around the Antarctic coastline will negatively impact emperor numbers; recent estimates suggest a halving of the population by 2052. The discovery of this new breeding behaviour at marginal sites could mitigate some of the consequences of sea-ice loss; potential benefits and whether these are permanent or temporary need to be considered and understood before further attempts are made to predict the population trajectory of this iconic species.
Wiggans, G R; VanRaden, P M; Cooper, T A
A method was developed to calculate preliminary genomic evaluations daily or weekly before the release of official monthly evaluations by processing only newly genotyped animals using estimates of single nucleotide polymorphism effects from the previous official evaluation. To minimize computing time, reliabilities and genomic inbreeding are not calculated, and fixed weights are used to combine genomic and traditional information. Correlations of preliminary and September official monthly evaluations for animals with genotypes that became usable after the extraction of genotypes for August 2014 evaluations were >0.99 for most Holstein traits. Correlations were lower for breeds with smaller population size. Earlier access to genomic evaluations benefits producers by enabling earlier culling decisions and genotyping laboratories by making workloads more uniform across the month. Copyright © 2015 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.
Dobson, Jane M.
Cancer is a common problem in dogs and although all breeds of dog and crossbred dogs may be affected, it is notable that some breeds of pedigree dogs appear to be at increased risk of certain types of cancer suggesting underlying genetic predisposition to cancer susceptibility. Although the aetiology of most cancers is likely to be multifactorial, the limited genetic diversity seen in purebred dogs facilitates genetic linkage or association studies on relatively small populations as compared to humans, and by using newly developed resources, genome-wide association studies in dog breeds are proving to be a powerful tool for unravelling complex disorders. This paper will review the literature on canine breed susceptibility to histiocytic sarcoma, osteosarcoma, haemangiosarcoma, mast cell tumours, lymphoma, melanoma, and mammary tumours including the recent advances in knowledge through molecular genetic, cytogenetic, and genome wide association studies. PMID:23738139
Jia, Jing; Wei, Yi-Liang; Qin, Cui-Jiao; Hu, Lan; Wan, Li-Hua; Li, Cai-Xia
Inferring the ancestral origin of DNA samples can be helpful in correcting population stratification in disease association studies or guiding crime investigations. Populations throughout the world vary in appearance features and biological characteristics. Based on this idea, we performed a genome-wide scan for SNPs within genes that are related to physical and biological traits. Using the HapMap database, we screened 52 genes and their flanking regions. Thirty-five SNPs that displayed highly contrasting allele frequencies (F(st)>0.3, linkage disequilibrium r(2)0.001) among Africans, Europeans, and East Asians were selected and validated. A multiplexed assay was developed to genotype these 35 SNPs in 357 individuals from 10 populations worldwide. This panel provided accurate estimates of individual ancestry proportions with balanced discriminatory power among the three continental ancestries: Africans, Europeans, and East Asians. It also proved very effective in evaluating admixed populations living in joint regions of continents (e.g., Uyghurs and Indians) and discriminating some subpopulations within each of the three continents. Structure analysis was performed to establish and evaluate the panel of ancestry-informative markers, and the components of each population were also described to indicate the structural composition. The 21 population structures in our study are consistent with geographic patterns, and individuals were properly assigned to their original ancestral populations with proportion analyses and random match probability calculations. Thus, the panel and its population information will be useful resources to minimize the effects of population stratification in association analyses and to assign the most likely origin of an unknown DNA contributor in forensic investigations. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Campbell, M.L.H.; Sandøe, Peter
and identifies areas in which data is lacking. We suggest that all methods of horse breeding are associated with potential welfare problems, but also that the judicious use of ARTs can sometimes help to address those problems. We discuss how negative welfare effects could be identified and limited and how...... positive welfare effects associated with breeding might be maximised. Further studies are needed to establish an evidence base about how stressful or painful various breeding procedures are for the animals involved, and what the lifetime welfare implications of ARTs are for future animal generations....
Smaragdov, M G
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.
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
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.
Zheng, S.J.; Kamenetsky, R.; Féréol, L.; Barandiaran, X.; Rabinowitch, H.D.; Chovelon, V.; Kik, C.
This review outlines innovative methods for garlic breeding improvement and discusses the techniques used to increase variation like mutagenesis and in vitro techniques, as well as the current developments in florogenesis, sexual hybridization, genetic transformation and mass propagation. Sexual
California Natural Resource Agency — This data set provides access to information gathered on annual breeding bird surveys in California using a map layer developed by the Department. This data layer...
Full Text Available This article discusses changes in sunflower breeding objectives since the introduction of hybrid varieties 50 years ago. After a reminder of the importance of some early programmes, Canadian in particular, the present situation for each breeding objective is compared with those encountered earlier. Breeding for yield has changed from maximum possible yield under intensive agriculture to yield with resistance to abiotic stresses, moderate droughts and shallow soils in particular, helped by collaboration with agronomists to produce crop models. Breeding for oil has changed from quantity to quality and the value of seed meal is again becoming economically important. Necessary disease resistances vary with agronomic practises and selection pressure on pathogens according to varietal genetics. The possibilities of new types of sunflower are also discussed. Advances in genomics will change breeding procedures, but with rapidly changing molecular techniques, international collaboration is particularly important.
Walter D Koenig
Full Text Available Cooperative breeding, in which more than a pair of conspecifics cooperate to raise young at a single nest or brood, is widespread among vertebrates but highly variable in its geographic distribution. Particularly vexing has been identifying the ecological correlates of this phenomenon, which has been suggested to be favored in populations inhabiting both relatively stable, productive environments and in populations living under highly variable and unpredictable conditions. Griesser et al. provide a novel approach to this problem, performing a phylogenetic analysis indicating that family living is an intermediate step between nonsocial and cooperative breeding birds. They then examine the ecological and climatic conditions associated with these different social systems, concluding that cooperative breeding emerges when family living is favored in highly productive environments, followed secondarily by selection for cooperative breeding when environmental conditions deteriorate and within-year variability increases. Combined with recent work addressing the fitness consequences of cooperative breeding, Griesser et al.'s contribution stands to move the field forward by demonstrating that the evolution of complex adaptations such as cooperative breeding may only be understood when each of the steps leading to it are identified and carefully integrated.
Full Text Available Cisgenesis is genetic modification to transfer beneficial alleles from crossable species into a recipient plant. The donor genes transferred by cisgenesis are the same as those used in traditional breeding. It can avoid linkage drag, enhance the use of existing gene alleles. This approach combines traditional breeding techniques with modern biotechnology and dramatically speeds up the breeding process. This allows plant genomes to be modified while remaining plants within the gene pool. Therefore, cisgenic plants should not be assessed as transgenics for environmental impacts.
Lin, Qiang; Qiu, Ying; Gu, Ruobo; Xu, Meng; Li, Jia; Bian, Chao; Zhang, Huixian; Qin, Geng; Zhang, Yanhong; Luo, Wei; Chen, Jieming; You, Xinxin; Fan, Mingjun; Sun, Min; Xu, Pao; Venkatesh, Byrappa; Xu, Junming; Fu, Hongtuo; Shi, Qiong
The lined seahorse, Hippocampus erectus , is an Atlantic species and mainly inhabits shallow sea beds or coral reefs. It has become very popular in China for its wide use in traditional Chinese medicine. In order to improve the aquaculture yield of this valuable fish species, we are trying to develop genomic resources for assistant selection in genetic breeding. Here, we provide whole genome sequencing, assembly, and gene annotation of the lined seahorse, which can enrich genome resource and further application for its molecular breeding. A total of 174.6 Gb (Gigabase) raw DNA sequences were generated by the Illumina Hiseq2500 platform. The final assembly of the lined seahorse genome is around 458 Mb, representing 94% of the estimated genome size (489 Mb by k-mer analysis). The contig N50 and scaffold N50 reached 14.57 kb and 1.97 Mb, respectively. Quality of the assembled genome was assessed by BUSCO with prediction of 85% of the known vertebrate genes and evaluated using the de novo assembled RNA-seq transcripts to prove a high mapping ratio (more than 99% transcripts could be mapped to the assembly). Using homology-based, de novo and transcriptome-based prediction methods, we predicted 20 788 protein-coding genes in the generated assembly, which is less than our previously reported gene number (23 458) of the tiger tail seahorse ( H. comes ). We report a draft genome of the lined seahorse. These generated genomic data are going to enrich genome resource of this economically important fish, and also provide insights into the genetic mechanisms of its iconic morphology and male pregnancy behavior. © The Authors 2017. Published by Oxford University Press.
Results of an online questionnaire to survey calf management practices on dairy cattle breeding farms in Austria and to estimate differences in disease incidences depending on farm structure and management practices.
Klein-Jöbstl, Daniela; Arnholdt, Tim; Sturmlechner, Franz; Iwersen, Michael; Drillich, Marc
Calf disease may result in great economic losses. To implement prevention strategies it is important to gain information on management and to point out risk factors. The objective of this internet based survey was to describe calf management practices on registered dairy breeding farms in Austria and to estimate differences in calf disease incidences depending on farm structure and management practices. A total of 1287 questionnaires were finally analysed (response rate 12.2 %). Herd characteristics and regional distribution of farms indicated that this survey gives a good overview on calf management practices on registered dairy farms in Austria. The median number of cows per farm was 20 (interquartile range 13-30). Significant differences regarding farm characteristics and calf management between small and large farms (≤20 vs >20 cows) were present. Only 2.8 % of farmers tested first colostrum quality by use of a hydrometer. Storing frozen colostrum was more prevalent on large farms (80.8 vs 64.2 %). On 85.1 % of the farms, whole milk, including waste milk, was fed to the calves. Milk replacer and waste milk were more often used on large farms. In accordance with similar studies from other countries, calf diarrhoea was indicated as the most prevalent disease. Multivariable logistic regression analysis revealed that herd size was associated with calf diarrhoea and calf respiratory tract disease, with higher risk of disease on large farms. Furthermore, feeding waste milk to the calves was associated with increasing calf diarrhoea incidence on farm. In the final model with calf respiratory tract disease as outcome, respondents from organic farms reported less often a respiratory tract disease incidence of over 10 % compared with conventional farms [odds ratio (OR) 0.40, 95 % confidence interval (CI) 0.21-0.75] and farmers that housed calves individually or in groups after birth significantly reported more often to have an incidence of respiratory tract
Poland, Jesse; Rutkoski, Jessica
Breeding for disease resistance is a central focus of plant breeding programs, as any successful variety must have the complete package of high yield, disease resistance, agronomic performance, and end-use quality. With the need to accelerate the development of improved varieties, genomics-assisted breeding is becoming an important tool in breeding programs. With marker-assisted selection, there has been success in breeding for disease resistance; however, much of this work and research has focused on identifying, mapping, and selecting for major resistance genes that tend to be highly effective but vulnerable to breakdown with rapid changes in pathogen races. In contrast, breeding for minor-gene quantitative resistance tends to produce more durable varieties but is a more challenging breeding objective. As the genetic architecture of resistance shifts from single major R genes to a diffused architecture of many minor genes, the best approach for molecular breeding will shift from marker-assisted selection to genomic selection. Genomics-assisted breeding for quantitative resistance will therefore necessitate whole-genome prediction models and selection methodology as implemented for classical complex traits such as yield. Here, we examine multiple case studies testing whole-genome prediction models and genomic selection for disease resistance. In general, whole-genome models for disease resistance can produce prediction accuracy suitable for application in breeding. These models also largely outperform multiple linear regression as would be applied in marker-assisted selection. With the implementation of genomic selection for yield and other agronomic traits, whole-genome marker profiles will be available for the entire set of breeding lines, enabling genomic selection for disease at no additional direct cost. In this context, the scope of implementing genomics selection for disease resistance, and specifically for quantitative resistance and quarantined pathogens
Cruz, Fernando; Julca, Irene; Gómez-Garrido, Jèssica; Loska, Damian; Marcet-Houben, Marina; Cano, Emilio; Galán, Beatriz; Frias, Leonor; Ribeca, Paolo; Derdak, Sophia; Gut, Marta; Sánchez-Fernández, Manuel; García, Jose Luis; Gut, Ivo G; Vargas, Pablo; Alioto, Tyler S; Gabaldón, Toni
The Mediterranean olive tree (Olea europaea subsp. europaea) was one of the first trees to be domesticated and is currently of major agricultural importance in the Mediterranean region as the source of olive oil. The molecular bases underlying the phenotypic differences among domesticated cultivars, or between domesticated olive trees and their wild relatives, remain poorly understood. Both wild and cultivated olive trees have 46 chromosomes (2n). A total of 543 Gb of raw DNA sequence from whole genome shotgun sequencing, and a fosmid library containing 155,000 clones from a 1,000+ year-old olive tree (cv. Farga) were generated by Illumina sequencing using different combinations of mate-pair and pair-end libraries. Assembly gave a final genome with a scaffold N50 of 443 kb, and a total length of 1.31 Gb, which represents 95 % of the estimated genome length (1.38 Gb). In addition, the associated fungus Aureobasidium pullulans was partially sequenced. Genome annotation, assisted by RNA sequencing from leaf, root, and fruit tissues at various stages, resulted in 56,349 unique protein coding genes, suggesting recent genomic expansion. Genome completeness, as estimated using the CEGMA pipeline, reached 98.79 %. The assembled draft genome of O. europaea will provide a valuable resource for the study of the evolution and domestication processes of this important tree, and allow determination of the genetic bases of key phenotypic traits. Moreover, it will enhance breeding programs and the formation of new varieties.
Domesticated species form a treasure-trove for molecular characterization of Mendelian traits by exploiting the specific genetic structure of these species in across-breed genome wide association studies
Megens, H.J.W.C.; Groenen, M.A.M.
Domesticated species have been important models for understanding phenotypic consequences of selection and genetics in the past 150 years. Among the most famous examples, is the work by Charles Darwin on the breeding of fancy pigeons that formed one of the pillars of his theory of evolution. Unknown
, which can be comparable to, or even surpass those from, eyewitness reports. This mini-review puts recent developments in age estimation via (epi)genetic methods in the context of the requirements and goals of forensic genetics and highlights paths to follow in the future of forensic genomics. © 2018 S. Karger AG, Basel.