Genome-wide association analysis of milk yield traits in Nordic Red Cattle using imputed whole genome sequence variants

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Reliabilities of genomic prediction using combined reference data of the Nordic Red dairy cattle populations

AbstractThis study investigated the possibility of increasing the reliability of direct genomic values (DGV) by combining reference populations. The data were from 3,735 bulls from Danish, Swedish, and Finnish Red dairy cattle populations. Single nucleotide polymorphism markers were fitted as random variables in a Bayesian model, using published estimated breeding values as response variables. In total, 17 index traits were analyzed. Reliabilities were estimated using a 5-fold cross validation, and calculated as the within-year squared correlation between estimated breeding values and DGV. Marker effects were estimated using reference populations from individual countries, as well as using a combined reference population from all 3 countries. Single-country reference populations gave mean reliabilities across 17 traits of 0.19 to 0.23, whereas the combined reference gave mean reliabilities of 0.26 for all populations. Using marker effects from 1 population to predict the other 2 gave a loss in mean reliability of 0.14 to 0.21 when predicting Swedish or Finnish animals with Danish marker effects, or vice versa. Using Swedish or Finnish marker effects to predict each other only showed a loss in mean reliability of 0.03 to 0.05. A combined Swedish-Finnish reference population led to an average reliability as high as that from the 3-country reference population, but somewhat different for individual traits. The results from this study show that it is possible to increase the reliability of DGV by combining reference populations from related populations

The first draft reference genome of the American mink ( Neovison vison )

Abstract The American mink (Neovison vison) is a semiaquatic species of mustelid native to North America. It’s an important animal for the fur industry. Many efforts have been made to locate genes influencing fur quality and color, but this search has been impeded by the lack of a reference genome. Here we present the first draft genome of mink. In our study, two mink individuals were sequenced by Illumina sequencing with 797 Gb sequence generated. Assembly yielded 7,175 scaffolds with an N50 of 6.3 Mb and length of 2.4 Gb including gaps. Repeat sequences constitute around 31% of the genome, which is lower than for dog and cat genomes. The alignments of mink, ferret and dog genomes help to illustrate the chromosomes rearrangement. Gene annotation identified 21,053 protein-coding sequences present in mink genome. The reference genome’s structure is consistent with the microsatellite-based genetic map. Mapping of well-studied genes known to be involved in coat quality and coat color, and previously located fur quality QTL provide new knowledge about putative candidate genes for fur traits. The draft genome shows great potential to facilitate genomic research towards improved breeding for high fur quality animals and strengthen our understanding on evolution of Carnivora

Signatures of selection and environmental adaptation across the goat genome post-domestication

Background: Since goat was domesticated 10,000 years ago, many factors have contributed to the differentiation of goat breeds and these are classified mainly into two types: (i) adaptation to different breeding systems and/or purposes and (ii) adaptation to different environments. As a result, approximately 600 goat breeds have developed worldwide; they differ considerably from one another in terms of phenotypic characteristics and are adapted to a wide range of climatic conditions. In this work, we analyzed the AdaptMap goat dataset, which is composed of data from more than 3000 animals collected worldwide and genotyped with the CaprineSNP50 BeadChip. These animals were partitioned into groups based on geographical area, production uses, available records on solid coat color and environmental variables including the sampling geographical coordinates, to investigate the role of natural and/or artificial selection in shaping the genome of goat breeds. Results: Several signatures of selection on different chromosomal regions were detected across the different breeds, sub-geographical clusters, phenotypic and climatic groups. These regions contain genes that are involved in important biological processes, such as milk-, meat- or fiber-related production, coat color, glucose pathway, oxidative stress response, size, and circadian clock differences. Our results confirm previous findings in other species on adaptation to extreme environments and human purposes and provide new genes that could explain some of the differences between goat breeds according to their geographical distribution and adaptation to different environments. Conclusions: These analyses of signatures of selection provide a comprehensive first picture of the global domestication process and adaptation of goat breeds and highlight possible genes that may have contributed to the differentiation of this species worldwide

Genome-wide SNP profiling of worldwide goat populations reveals strong partitioning of diversity and highlights post-domestication migration routes

Background: Goat populations that are characterized within the AdaptMap project cover a large part of the worldwide distribution of this species and provide the opportunity to assess their diversity at a global scale. We analysed genome-wide 50 K single nucleotide polymorphism (SNP) data from 144 populations to describe the global patterns of molecular variation, compare them to those observed in other livestock species, and identify the drivers that led to the current distribution of goats. Results: A high degree of genetic variability exists among the goat populations studied. Our results highlight a strong partitioning of molecular diversity between and within continents. Three major gene pools correspond to goats from Europe, Africa and West Asia. Dissection of sub-structures disclosed regional gene pools, which reflect the main post-domestication migration routes. We also identified several exchanges, mainly in African populations, and which often involve admixed and cosmopolitan breeds. Extensive gene flow has taken place within specific areas (e.g., south Europe, Morocco and Mali-Burkina Faso-Nigeria), whereas elsewhere isolation due to geographical barriers (e.g., seas or mountains) or human management has decreased local gene flows. Conclusions: After domestication in the Fertile Crescent in the early Neolithic era (ca. 12,000 YBP), domestic goats that already carried differentiated gene pools spread to Europe, Africa and Asia. The spread of these populations determined the major genomic background of the continental populations, which currently have a more marked subdivision than that observed in other ruminant livestock species. Subsequently, further diversification occurred at the regional level due to geographical and reproductive isolation, which was accompanied by additional migrations and/or importations, the traces of which are still detectable today. The effects of breed formation were clearly detected, particularly in Central and North Europe. Overall, our results highlight a remarkable diversity that occurs at the global scale and is locally partitioned and often affected by introgression from cosmopolitan breeds. These findings support the importance of long-term preservation of goat diversity, and provide a useful framework for investigating adaptive introgression, directing genetic improvement and choosing breeding targets

Meta-analysis of genome-wide association studies for cattle stature identifies common genes that regulate body size in mammals

peer-reviewedH.D.D., A.J.C., P.J.B. and B.J.H. would like to acknowledge the Dairy Futures Cooperative Research Centre for funding. H.P. and R.F. acknowledge funding from the German Federal Ministry of Education and Research (BMBF) within the AgroClustEr ‘Synbreed—Synergistic Plant and Animal Breeding’ (grant 0315527B). H.P., R.F., R.E. and K.-U.G. acknowledge the Arbeitsgemeinschaft Süddeutscher Rinderzüchter, the Arbeitsgemeinschaft Österreichischer Fleckviehzüchter and ZuchtData EDV Dienstleistungen for providing genotype data. A. Bagnato acknowledges the European Union (EU) Collaborative Project LowInputBreeds (grant agreement 222623) for providing Brown Swiss genotypes. Braunvieh Schweiz is acknowledged for providing Brown Swiss phenotypes. H.P. and R.F. acknowledge the German Holstein Association (DHV) and the Confederación de Asociaciones de Frisona Española (CONCAFE) for sharing genotype data. H.P. was financially supported by a postdoctoral fellowship from the Deutsche Forschungsgemeinschaft (DFG) (grant PA 2789/1-1). D.B. and D.C.P. acknowledge funding from the Research Stimulus Fund (11/S/112) and Science Foundation Ireland (14/IA/2576). M.S. and F.S.S. acknowledge the Canadian Dairy Network (CDN) for providing the Holstein genotypes. P.S. acknowledges funding from the Genome Canada project entitled ‘Whole Genome Selection through Genome Wide Imputation in Beef Cattle’ and acknowledges WestGrid and Compute/Calcul Canada for providing computing resources. J.F.T. was supported by the National Institute of Food and Agriculture, US Department of Agriculture, under awards 2013-68004-20364 and 2015-67015-23183. A. Bagnato, F.P., M.D. and J.W. acknowledge EU Collaborative Project Quantomics (grant 516 agreement 222664) for providing Brown Swiss and Finnish Ayrshire sequences and genotypes. A.C.B. and R.F.V. acknowledge funding from the public–private partnership ‘Breed4Food’ (code BO-22.04-011- 001-ASG-LR) and EU FP7 IRSES SEQSEL (grant 317697). A.C.B. and R.F.V. acknowledge CRV (Arnhem, the Netherlands) for providing data on Dutch and New Zealand Holstein and Jersey bulls.Stature is affected by many polymorphisms of small effect in humans1. In contrast, variation in dogs, even within breeds, has been suggested to be largely due to variants in a small number of genes2,3. 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 × 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