A COL11A2 Mutation in Labrador Retrievers with Mild Disproportionate Dwarfism

Peer reviewe

Genome-wide association studies of fertility and calving traits in Brown Swiss cattle using imputed whole-genome sequences

BACKGROUND: The detection of quantitative trait loci has accelerated with recent developments in genomics. The introduction of genomic selection in combination with sequencing efforts has made a large amount of genotypic data available. Functional traits such as fertility and calving traits have been included in routine genomic estimation of breeding values making large quantities of phenotypic data available for these traits. This data was used to investigate the genetics underlying fertility and calving traits and to identify potentially causative genomic regions and variants. We performed genome-wide association studies for 13 functional traits related to female fertility as well as for direct and maternal calving ease based on imputed whole-genome sequences. Deregressed breeding values from ~1000-5000 bulls per trait were used to test for associations with approximately 10 million imputed sequence SNPs. RESULTS: We identified a QTL on BTA17 associated with non-return rate at 56 days and with interval from first to last insemination. We found two significantly associated non-synonymous SNPs within this QTL region. Two more QTL for fertility traits were identified on BTA25 and 29. A single QTL was identified for maternal calving traits on BTA13 whereas three QTL on BTA19, 21 and 25 were identified for direct calving traits. The QTL on BTA19 co-localizes with the reported BH2 haplotype. The QTL on BTA25 is concordant for fertility and calving traits and co-localizes with a QTL previously reported to influence stature and related traits in Brown Swiss dairy cattle. CONCLUSION: The detection of QTL and their causative variants remains challenging. Combining comprehensive phenotypic data with imputed whole genome sequences seems promising. We present a QTL on BTA17 for female fertility in dairy cattle with two significantly associated non-synonymous SNPs, along with five additional QTL for fertility traits and calving traits. For all of these we fine mapped the regions and suggest candidate genes and candidate variants

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

A first update on mapping the human genetic architecture of COVID-19

peer reviewe

Selection signatures in Shetland ponies.

Shetland ponies were selected for numerous traits including small stature, strength, hardiness and longevity. Despite the different selection criteria, Shetland ponies are well known for their small stature. We performed a selection signature analysis including genome-wide SNPs of 75 Shetland ponies and 76 large-sized horses. Based upon this dataset, we identified a selection signature on equine chromosome (ECA) 1 between 103.8 Mb and 108.5 Mb. A total of 33 annotated genes are located within this interval including the IGF1R gene at 104.2 Mb and the ADAMTS17 gene at 105.4 Mb. These two genes are well known to have a major impact on body height in numerous species including humans. Homozygosity mapping in the Shetland ponies identified a region with increased homozygosity between 107.4 Mb and 108.5 Mb. None of the annotated genes in this region have so far been associated with height. Thus, we cannot exclude the possibility that the identified selection signature on ECA1 is associated with some trait other than height, for which Shetland ponies were selected

Genome-wide association studies based on sequence-derived genotypes reveal new QTL associated with conformation and performance traits in the Franches-Montagnes horse breed

To identify novel quantitative trait loci (QTL) within horses, we performed genome-wide association studies (GWAS) based on sequence-level genotypes for conformation and performance traits in the Franches-Montagnes (FM) horse breed. Sequence-level genotypes of FM horses were derived by re-sequencing 30 key founders and imputing 50K data of genotyped horses. In total, we included 1077 FM horses genotyped for ~4 million SNPs and their respective de-regressed breeding values of the traits in the analysis. Based on this dataset, we identified a total of 14 QTL associated with 18 conformation traits and one performance trait. Therefore, our results suggest that the application of sequence-derived genotypes increases the power to identify novel QTL which were not identified previously based on 50K SNP chip data

Imputation of sequence level genotypes in the Franches-Montagnes horse breed

BACKGROUND A cost-effective strategy to increase the density of available markers within a population is to sequence a small proportion of the population and impute whole-genome sequence data for the remaining population. Increased densities of typed markers are advantageous for genome-wide association studies (GWAS) and genomic predictions. METHODS We obtained genotypes for 54 602 SNPs (single nucleotide polymorphisms) in 1077 Franches-Montagnes (FM) horses and Illumina paired-end whole-genome sequencing data for 30 FM horses and 14 Warmblood horses. After variant calling, the sequence-derived SNP genotypes (~13 million SNPs) were used for genotype imputation with the software programs Beagle, Impute2 and FImpute. RESULTS The mean imputation accuracy of FM horses using Impute2 was 92.0%. Imputation accuracy using Beagle and FImpute was 74.3% and 77.2%, respectively. In addition, for Impute2 we determined the imputation accuracy of all individual horses in the validation population, which ranged from 85.7% to 99.8%. The subsequent inclusion of Warmblood sequence data further increased the correlation between true and imputed genotypes for most horses, especially for horses with a high level of admixture. The final imputation accuracy of the horses ranged from 91.2% to 99.5%. CONCLUSIONS Using Impute2, the imputation accuracy was higher than 91% for all horses in the validation population, which indicates that direct imputation of 50k SNP-chip data to sequence level genotypes is feasible in the FM population. The individual imputation accuracy depended mainly on the applied software and the level of admixture

Data from: Genetic diversity analyses reveal first insights into breed-specific selection signatures within Swiss goat breeds

We used genotype data from the caprine 50k Illumina BeadChip for the assessment of genetic diversity within and between 10 local Swiss goat breeds. Three different cluster methods allowed the goat samples to be assigned to the respective breed groups, whilst the samples of Nera Verzasca and Tessin Grey goats could not be differentiated from each other. The results of the different genetic diversity measures show that Appenzell, Toggenburg, Valais and Booted goats should be prioritized in future conservation activities. Furthermore, we examined runs of homozygosity (ROH) and compared genomic inbreeding coefficients based on ROH (FROH) with pedigree-based inbreeding coefficients (FPED). The linear relationship between FROH and FPED was confirmed for goats by including samples from the three main breeds (Saanen, Chamois and Toggenburg goats). FROH appears to be a suitable measure for describing levels of inbreeding in goat breeds with missing pedigree information. Finally, we derived selection signatures between the breeds. We report a total of 384 putative selection signals. The 25 most significant windows contained genes known for traits such as: coat color variation (MITF, KIT, ASIP), growth (IGF2, IGF2R, HRAS, FGFR3) and milk composition (PITX2). Several other putative genes involved in the formation of populations, which might have been selected for adaptation to the alpine environment, are highlighted. The results provide a contemporary background for the management of genetic diversity in local Swiss goat breeds

Genetic diversity analyses reveal first insights into breed-specific selection signatures within Swiss goat breeds

We used genotype data from the caprine 50k Illumina BeadChip for the assessment of genetic diversity within and between 10 local Swiss goat breeds. Three different cluster methods allowed the goat samples to be assigned to the respective breed groups, whilst the samples of Nera Verzasca and Tessin Grey goats could not be differentiated from each other. The results of the different genetic diversity measures show that Appenzell, Toggenburg, Valais and Booted goats should be prioritized in future conservation activities. Furthermore, we examined runs of homozygosity (ROH) and compared genomic inbreeding coefficients based on ROH (FROH ) with pedigree-based inbreeding coefficients (FPED ). The linear relationship between FROH and FPED was confirmed for goats by including samples from the three main breeds (Saanen, Chamois and Toggenburg goats). FROH appears to be a suitable measure for describing levels of inbreeding in goat breeds with missing pedigree information. Finally, we derived selection signatures between the breeds. We report a total of 384 putative selection signals. The 25 most significant windows contained genes known for traits such as: coat color variation (MITF, KIT, ASIP), growth (IGF2, IGF2R, HRAS, FGFR3) and milk composition (PITX2). Several other putative genes involved in the formation of populations, which might have been selected for adaptation to the alpine environment, are highlighted. The results provide a contemporary background for the management of genetic diversity in local Swiss goat breeds