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"ANIMAL BREEDING"
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Meta-analysis of genome-wide association studies for cattle stature identifies common genes that regulate body size in mammals
Stature is affected by many polymorphisms of small effect in humans(1). In contrast, variation in dogs, even within breeds, has been suggested to be largely due to variants in a small number of genes(2,3). Here we use data from cattle to compare the genetic architecture of stature to those in humans and dogs. We conducted a meta-analysis for stature using 58,265 cattle from 17 populations with 25.4 million imputed whole-genome sequence variants. Results showed that the genetic architecture of stature in cattle is similar to that in humans, as the lead variants in 163 significantly associated genomic regions (P < 5 x 10(-8)) explained at most 13.8% of the phenotypic variance. Most of these variants were noncoding, including variants that were also expression quantitative trait loci (eQTLs) and in ChIP-seq peaks. There was significant overlap in loci for stature with humans and dogs, suggesting that a set of common genes regulates body size in mammals
Journal Article
Trends in genome-wide and region-specific genetic diversity in the Dutch-Flemish Holstein–Friesian breeding program from 1986 to 2015
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; 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.
Methods
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.
Results
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.
Conclusions
Genome-wide and region-specific diversity trends reflect major changes in the Dutch-Flemish HF breeding program. Introduction of OCS and the shift in breeding goal were followed by a drop in inbreeding and kinship and a shift in the direction of changes in allele frequency. After introduction of GS, rates of inbreeding and kinship increased substantially while allele frequencies continued to change in the same direction as before GS. These results provide insight in the effect of breeding practices on genomic diversity and emphasize the need for efficient management of genetic diversity in GS schemes.
Journal Article
The effects of recent changes in breeding preferences on maintaining traditional Dutch chicken genomic diversity
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 the neo-bantams homozygosity, genetic exchange between breeders may increase their genetic diversity. We use the 60 K SNP array to characterise the genetic diversity, demographic history, and level of inbreeding of Dutch heritage breeds, and particularly of neo-bantams. Commercial white layers are used to contrast the impact of management strategy on genetic diversity and demography. A high proportion of alleles was found to be shared between large fowls and neo-bantams, suggesting gene flow during neo-bantams development. Population admixture analysis supports these findings, in addition to revealing introgression from neo-bantams of the same breed and of phenotypically similar breeds. The prevalence of long runs of homozygosity (ROH) confirms the importance of recent inbreeding. A high diversity in management, carried out in small breeding units explains the high heterogeneity in diversity and ROH profile displayed by traditional breeds compared to commercial lines. Population bottlenecks may explain the long ROHs in large fowls, while repetitive backcrossing for phenotype selection may account for them in neo-bantams. Our results highlight the importance of using markers to inform breeding programmes on potentially harmful homozygosity to prevent loss of genetic diversity. We conclude that bantamisation has generated unique and identifiable genetic diversity. However, this diversity can only be preserved in the near future through structured breeding programmes.
Journal Article
Genomic prediction unifies animal and plant breeding programs to form platforms for biological discovery
Wayne Powell and colleagues compare the different tools and approaches used by the plant breeding community versus the animal breeding community for crop and livestock improvement. They argue that the two disciplines can be united via adoption of genomic selection along with the exchange of resources and techniques between the two areas.
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.
Journal Article
Genomic analysis on pygmy hog reveals extensive interbreeding during wild boar expansion
Wild boar (
Sus scrofa
) drastically colonized mainland Eurasia and North Africa, most likely from East Asia during the Plio-Pleistocene (2–1Mya). In recent studies, based on genome-wide information, it was hypothesized that wild boar did not replace the species it encountered, but instead exchanged genetic materials with them through admixture. The highly endangered pygmy hog (
Porcula salvania)
is the only suid species in mainland Eurasia known to have outlived this expansion, and therefore provides a unique opportunity to test this hybridization hypothesis. Analyses of pygmy hog genomes indicate that despite large phylogenetic divergence (~2 My), wild boar and pygmy hog did indeed interbreed as the former expanded across Eurasia. In addition, we also assess the taxonomic placement of the donor of another introgression, pertaining to a now-extinct species with a deep phylogenetic placement in the
Suidae
tree. Altogether, our analyses indicate that the rapid spread of wild boar was facilitated by inter-specific/inter-generic admixtures.
The pygmy hog (
Porcula salvania
), now highly endangered and restricted in a small region at the southern foothills of the Himalaya, is the only suid species in mainland Eurasia that outlived the expansion of wild boar (
Sus scrofa
). Here, the authors analyze genomes of pygmy hog and related suid species, and identify signals of introgression among these species.
Journal Article
Genomic prediction for crossbred performance using metafounders
Future genomic evaluation models to be used routinely in breeding programs for pigs and poultry need to be able to optimally use information of crossbred (CB) animals to predict breeding values for CB performance of purebred (PB) selection candidates. Important challenges in the commonly used single-step genomic best linear unbiased prediction (ssGBLUP) model are the definition of relationships between the different line compositions and the definition of the base generation per line. The use of metafounders (MFs) in ssGBLUP has been proposed to overcome these issues. When relationships between lines are known to be different from 0, the use of MFs generalizes the concept of genetic groups relying on the genotype data. Our objective was to investigate the effect of using MFs in genomic prediction for CB performance on estimated variance components, and accuracy and bias of GEBV. This was studied using stochastic simulation to generate data representing a three-way crossbreeding scheme in pigs, with the parental lines being either closely related or unrelated. Results show that using MFs, the variance components should be scaled appropriately, especially when basing them on estimates obtained with, for example a pedigree-based model. The accuracies of GEBV that were obtained using MFs were similar to accuracies without using MFs, regardless whether the lines involved in the CB were closely related or unrelated. The use of MFs resulted in a model that had similar or somewhat better convergence properties compared to other models. We recommend the use of MFs in ssGBLUP for genomic evaluations in crossbreeding schemes.
Journal Article
Genomic evaluation for a three-way crossbreeding system considering breed-of-origin of alleles
Background
Genomic prediction of purebred animals for crossbred performance can be based on a model that estimates effects of single nucleotide polymorphisms (SNPs) in purebreds on crossbred performance. For crossbred performance, SNP effects might be breed-specific due to differences between breeds in allele frequencies and linkage disequilibrium patterns between SNPs and quantitative trait loci. Accurately tracing the breed-of-origin of alleles (BOA) in three-way crosses is possible with a recently developed procedure called BOA. A model that accounts for breed-specific SNP effects (BOA model), has never been tested empirically on a three-way crossbreeding scheme. Therefore, the objectives of this study were to evaluate the estimates of variance components and the predictive accuracy of the BOA model compared to models in which SNP effects for crossbred performance were assumed to be the same across breeds, using either breed-specific allele frequencies (
G
A
model) or allele frequencies averaged across breeds (
G
B
model). In this study, we used data from purebred and three-way crossbred pigs on average daily gain (ADG), back fat thickness (BF), and loin depth (LD).
Results
Estimates of variance components for crossbred performance from the BOA model were mostly similar to estimates from models
G
A
and
G
B
. Heritabilities for crossbred performance ranged from 0.24 to 0.46 between traits. Genetic correlations between purebred and crossbred performance (
r
pc
) across breeds ranged from 0.30 to 0.62 for ADG and from 0.53 to 0.74 for BF and LD. For ADG, prediction accuracies of the BOA model were higher than those of the
G
A
and
G
B
models, with significantly higher accuracies only for one maternal breed. For BF and LD, prediction accuracies of models
G
A
and
G
B
were higher than those of the BOA model, with no significant differences. Across all traits, models
G
A
and
G
B
yielded similar predictions.
Conclusions
The BOA model yielded a higher prediction accuracy for ADG in one maternal breed, which had the lowest
r
pc
(0.30). Using the BOA model was especially relevant for traits with a low
r
pc
. In all other cases, the use of crossbred information in models
G
A
and
G
B
, does not jeopardize predictions and these models are more easily implemented than the BOA model.
Journal Article