Biology subjects

Pausch, H.

Publications and source records attributed to Pausch, H..

48 records · Page 3Linked to original sources

bioRxiv2020

A nonsense mutation of bone morphogenetic protein-15 (BMP15) causes both infertility and increased litter size in pigs.

BackgroundAtypical external genitalia are often a sign of reproductive organ pathologies and infertility with both environmental or genetic causes, including karyotypic abnormalities. Genome-wide association studies (GWAS) provide a means for identifying chromosomal regions harboring deleterious DNA-variants causing such phenotypes. We performed a GWAS to unravel the causes of incidental cases of atypically small vulvae in German Landrace gilts. ResultsA case-control GWAS involving Illumina porcine SNP60 BeadChip-called genotypes of 17 gilts with atypically small vulvae and 1,818 control animals (fertile German Landrace sows) identified a significantly associated region on the X-chromosome (P = 8.81 x 10-43). Inspection of whole-genome sequencing data in the critical area allowed us to pinpoint a likely causal variant in the form of a nonsense mutation of bone morphogenetic protein-15 (Sscrofa11.1_X:g.44618787C>T, BMP15:p.R212X). The mutant allele occurs at a frequency of 6.2% in the German Landrace breeding population. Homozygous gilts exhibit underdeveloped, most likely not functional ovaries and are not fertile. Male carriers do not seem to manifest defects. Heterozygous sows produce 0.41{+/-}0.02 (P=4.5 x 10-83) piglets more than wildtype animals. However, the mutant alleles positive effect on litter size accompanies a negative impact on lean meat growth. ConclusionOur results provide an example for the power of GWAS in identifying the genetic causes of a fuzzy phenotype and add to the list of natural deleterious BMP15 mutations that affect fertility in a dosage-dependent manner, the first time in a poly-ovulatory species. We advise eradicating the mutant allele from the German Landrace breeding population since the adverse effects on the lean meat growth outweigh the larger litter size in heterozygous sows.

genomics↗

bioRxiv2020

Investigating the accuracy of imputed genotypes in Nellore cattle using the ARS-UCD1.2 assembly of the bovine genome

BackgroundImputation accuracy among other things depends on the size of the reference panel, the markers minor allele frequency (MAF), and the correct placement of variants on the reference genome assembly. Using high-density genotypes of 3938 Nellore cattle from Brazil, we investigated the accuracy of imputation from 50K to 777K SNP density, using map positions determined according to the bovine genome assemblies UMD3.1 and ARS-UCD1.2. We assessed the effect of reference and target panel sizes on the pre-phasing-based imputation quality using ten-fold cross-validation. Further, we compared the reliability of the model-based imputation quality score (Rsq) from Minimac3 to empirical imputation accuracy. ResultsThe overall accuracy of imputation measured as the squared correlation between true and imputed allele dosages (R2dose) was virtually identical using either the UMD3.1 or ARS-UCD1.2 genome assembly. When the size of the reference panel increased from 250 to 2000, R2dose increased from 0.845 to 0.917, and the number of polymorphic markers in the imputed data set increased from 586,701 to 618,660. Advantages in both accuracy and marker density were also observed when larger target panels were imputed, likely resulting from more accurate haplotype inference. Imputation accuracy and the marker density in the imputed data increased from 0.903 to 0.913 and from 593,239 to 595,570 when haplotypes were inferred in 500 and 2900 target animals, respectively. The model-based imputation quality scores from Minimac3 (Rsq) were highly correlated to but systematically higher than empirically estimated accuracies. The correlation between these metrics increased with the size of the reference panel and MAF of imputed variants. ConclusionsAccurate imputation of BovineHD BeadChip markers is possible in Nellore cattle using the new bovine reference genome assembly ARS-UCD1.2. The use of large reference and target panels improves the accuracy of the imputed genotypes and provides genotypes for more markers segregating at low frequency for downstream genomic analyses. The model-based imputation quality score from Minimac3 (Rsq) can be used to detect poorly imputed variants but its reliability depends on the size of the reference panel used and MAF of the imputed variants.

genomics↗

bioRxiv2020

Deletion of porcine BOLL causes defective acrosomes and subfertility in Yorkshire boars

A recessively inherited sperm defect of Finnish Yorkshire boars was detected more than a decade ago. Affected boars produce ejaculates that contain many spermatozoa with defective acrosomes resulting in low fertility and small litters. The acrosome defect was mapped to porcine chromosome 15 but the causal mutation has not been identified. We re-analyzed microarray-derived genotypes of affected boars and performed a haplotype-based association study. Our results confirmed that the acrosome defect maps to a 12.24 Mb segment of porcine chromosome 15 (P=3.38 x 10-14). In order to detect the mutation causing defective acrosomes, we sequenced the genomes of two affected and three unaffected boars to an average coverage of 11-fold. Read-depth analysis revealed a 55 kb deletion that segregates with the acrosome defect. The deletion encompasses the BOLL gene encoding the boule homolog, RNA binding protein which is an evolutionarily highly conserved member of the DAZ (deleted in azoospermia) gene family. Lack of BOLL expression causes spermatogenic arrest and sperm maturation failure in many species. Our study reveals that absence of BOLL is associated with a sperm defect also in pigs. The acrosomes of boars that carry the deletion in the homozygous state are defective suggesting that lack of porcine BOLL compromises acrosome formation. Our findings warrant further research to investigate the precise function of BOLL during spermatogenesis and sperm maturation in pigs.

genomics↗

bioRxiv2020

A 63-bp insertion in exon 2 of the porcine KIF21A gene is associated with arthrogryposis multiplex congenita

Arthrogryposis multiplex congenita (AMC) is a recessively inherited fatal disease detected almost 20 years ago in the Swiss Large White pig population. A diagnostic marker test enabled the identification of carrier animals, but the underlying causal mutation remains unknown. To identify the mutation underlying AMC, we collected whole-genome genotyping and sequencing data for 11 affected piglets and 23 healthy pigs. Haplotype-based case-control association testing using 47,829 SNPs confirmed that AMC maps to SSC5 (P = 9.4 x10-13). Subsequent autozygosity mapping revealed a common 6.06 Mb region (from 66,757,970 to 72,815,151 bp) of extended homozygosity in 11 piglets affected by AMC. We detected a 63-bp insertion in the second exon of KIF21A gene encoding Kinesin Family Member 21A using whole-genome sequences of a carrier boar, two of its affected and two heterozygous piglets. This insertion was compatible with the recessive inheritance of AMC. The 63-bp insertion likely represents a loss-of-function allele because it is predicted to introduce a premature stop codon in KIF21A gene (p.Val41_Phe42insTer) that truncates 1,614 amino acids ([~] 97%) from the protein. Lack of KIF21A protein is lethal in mice, thus providing additional evidence that a loss-of function allele of KIF21A might cause fatal AMC in pigs. We found that this deleterious allele still segregates at low frequency in the Swiss Large White pig population. The unambiguous detection of carrier animals can now facilitate the eradication of the deleterious allele from the population.

genomics↗

bioRxiv2020

Activation of cryptic splicing in bovine WDR19 is associated with reduced semen quality and male fertility

Cattle are ideally suited to investigate the genetics of male reproduction, because semen quality and fertility are recorded for all ejaculates of artificial insemination bulls. We analysed 26,090 ejaculates of 794 Brown Swiss bulls to assess ejaculate volume, sperm concentration, sperm motility, sperm head and tail anomalies and insemination success. The heritability of the six semen traits was between 0 and 0.26. Genome-wide association testing on 607,511 SNPs revealed a QTL on bovine chromosome 6 that was associated with sperm motility (P = 2.5 x 10-27), head (P = 2.0 x 10-44) and tail anomalies (P = 7.2 x 10-49) and insemination success (P = 9.9 x 10-13). The QTL harbors a recessive allele that compromises semen quality and male fertility. We replicated the effect of the QTL on fertility (P = 7.1 x 10-32) in an independent cohort of 2481 Brown Swiss bulls. The analysis of whole-genome sequencing data revealed that a synonymous variant (BTA6:58373887C>T, rs474302732) in WDR19 encoding WD repeat-containing protein 19 was in linkage disequilibrium with the fertility-associated haplotype. WD repeat-containing protein 19 is a constituent of the intraflagellar transport complex that is essential for the physiological function of motile cilia and flagella. Bioinformatic and transcription analyses revealed that the BTA6:58373887 T-allele activates a cryptic exonic splice site that eliminates three evolutionarily conserved amino acids from WDR19. Western blot analysis demonstrated that the BTA6:58373887 T-allele decreases protein expression. We make the remarkable observation that, in spite of negative effects on semen quality and bull fertility, the BTA6:58373887 T-allele has a frequency of 24 % in the Brown Swiss population. Our findings are the first to uncover a variant that is associated with quantitative variation in semen quality and male fertility in cattle. Author summaryIn cattle farming, artificial insemination is the most commonly used method of breeding. To ensure high fertilization rates, ejaculate quality and insemination success are closely monitored in artificial insemination bulls. We analyse semen quality, insemination success and microarray-called genotypes at more than 600,000 genome-wide SNP markers in 794 bulls to identify a recessive allele that compromises semen quality. We take advantage of whole-genome sequencing to pinpoint a variant in the coding sequence of WDR19 encoding WD repeat-containing protein 19 that activates a novel exonic splice site. Our results indicate that cryptic splicing in WDR19 is associated with reduced male reproductive performance. This is the first report of a variant that contributes to quantitative variation in bovine semen quality.

genomics↗

bioRxiv2019

Sequence read mapping and variant discovery from bovine breed-specific augmented reference graphs

BackgroundThe current bovine genomic reference sequence was assembled from the DNA of a Hereford cow. The resulting linear assembly lacks diversity because it does not contain allelic variation. Lack of diversity is a drawback of linear references that causes reference allele bias. High nucleotide diversity and the separation of individuals by hundreds of breeds make cattle ideally suited to investigate the optimal composition of variation-aware references. ResultsWe augment the bovine linear reference sequence (ARS-UCD1.2) with variants filtered for allele frequency in dairy (Brown Swiss, Holstein) and dual-purpose (Fleckvieh, Original Braunvieh) cattle breeds to construct either breed-specific or pan-genome reference graphs using the vg toolkit. We find that read mapping is more accurate to variation-aware than linear references if pre-selected variants are used to construct the genome graphs. Graphs that contain random variants do not improve read mapping over the linear reference sequence. Breed-specific augmented and pan-genome graphs enable almost similar mapping accuracy improvements over the linear reference. We construct a whole-genome graph that contains the Hereford-based reference sequence and 14 million alleles that have alternate allele frequency greater than 0.03 in the Brown Swiss cattle breed. We show that our novel variation-aware reference facilitates accurate read mapping and unbiased sequence variant genotyping for SNPs and Indels. ConclusionsWe developed the first variation-aware reference graph for an agricultural animal: https://doi.org/10.5281/zenodo.3759712. Our novel reference structure improves sequence read mapping and variant genotyping over the linear reference. Our work is a first step towards the transition from linear to variation-aware reference structures in species with high genetic diversity and many sub-populations.

genomics↗

bioRxiv2019

Assessing genomic diversity and signatures of selection in Original Braunvieh cattle using whole-genome sequencing data

BackgroundAutochthonous cattle breeds represent an important source of genetic variation because they might carry alleles that enable them to adapt to local environment and food conditions. Original Braunvieh (OB) is a local cattle breed of Switzerland used for beef and milk production in alpine areas. Using whole-genome sequencing (WGS) data of 49 key ancestors, we characterize genomic diversity, genomic inbreeding, and signatures of selection in Swiss OB cattle at nucleotide resolution. ResultsWe annotated 15,722,811 million SNPs and 1,580,878 million Indels including 10,738 and 2,763 missense deleterious and high impact variants, respectively, that were discovered in 49 OB key ancestors. Six Mendelian trait-associated variants that were previously detected in breeds other than OB, segregated in the sequenced key ancestors including variants causal for recessive xanthinuria and albinism. The average nucleotide diversity (1.6 x 10-3) was higher in OB than many mainstream European cattle breeds. Accordingly, the average genomic inbreeding quantified using runs of homozygosity (ROH) was relatively low (FROH=0.14) in the 49 OB key ancestor animals. However, genomic inbreeding was higher in more recent generations of OB cattle (FROH=0.16) due to a higher number of long (> 1 Mb) runs of homozygosity. Using two complementary approaches, composite likelihood ratio test and integrated haplotype score, we identified 95 and 162 genomic regions encompassing 136 and 157 protein-coding genes, respectively, that showed evidence (P < 0.005) of past and ongoing selection. These selection signals were enriched for quantitative trait loci related to beef traits including meat quality, feed efficiency and body weight and pathways related to blood coagulation, nervous and sensory stimulus. ConclusionsWe provide a comprehensive overview of sequence variation in Swiss OB cattle genomes. With WGS data, we observe higher genomic diversity and less inbreeding in OB than many European mainstream cattle breeds. Footprints of selection were detected in genomic regions that are possibly relevant for meat quality and adaptation to local environmental conditions. Considering that the population size is low and genomic inbreeding increased in the past generations, the implementation and adoption of optimal mating strategies seems warranted to maintain genetic diversity in the Swiss OB cattle population.

genomics↗

bioRxiv2019

Multi-trait meta-analyses reveal 25 quantitative trait loci for economically important traits in Brown Swiss cattle

BackgroundThe Brown Swiss dual-purpose cattle breed is renowned for high milk and protein yield and long productive lifetime under different production conditions. However, little is known about the genetic architecture of those traits because only few genome-wide association studies (GWAS) have been carried out in this breed. Moreover, most GWAS had been performed for single traits, thus preventing insights into potentially existing pleiotropic effects of trait-associated loci. ResultsTo compile a comprehensive catalogue of large-effect QTL segregating in Brown Swiss cattle, we carried out association tests between partially imputed genotypes at 598,016 SNPs and daughter-derived phenotypes for more than 50 economically important traits, including milk production, growth and carcass quality, body conformation, reproduction and calving traits in 4,578 artificial insemination bulls from two cohorts of Brown Swiss cattle (Austrian-German and Swiss populations). Across-cohort multi-trait meta-analyses of the results from the single-trait GWAS revealed 25 quantitative trait loci (QTL; P < 8.36 x 10-8) for economically relevant traits on 17 Bos taurus autosomes (BTA). Evidence of pleiotropy was detected at five QTL located on BTA5, 6, 17, 21 and 25. Of these, two QTL at BTA6:90,486,780 and BTA25:1,455,150 affect a diverse range of economically important traits, including traits related to body conformation, calving, longevity and milking speed. Furthermore, the QTL at BTA6:90,486,780 seems to be a target of ongoing selection as evidenced by an integrated haplotype score of 2.49 and significant changes in allele frequency over the past 25 years, whereas either no or only weak evidence of selection was detected at all other QTL. ConclusionsOur findings provide a comprehensive overview of QTL segregating in Brown Swiss cattle. Detected QTL explain between 2 and 10% of the variation in the daughter-derived phenotypes and thus may be considered as the most important QTL segregating in the Brown Swiss cattle breed. Multi-trait association testing boosts the power to detect pleiotropic QTL and assesses the full spectrum of phenotypes that are affected by trait-associated variants.

genomics↗

bioRxiv2018

A splice donor variant in CCDC189 is associated with asthenospermia in Nordic Red dairy cattle

BackgroundCattle populations are highly amenable to the genetic mapping of male reproductive traits because longitudinal data on ejaculate quality and dense microarray-derived genotypes are available for many artificial insemination bulls. Two young Nordic Red bulls delivered sperm with low progressive motility (i.e., asthenospermia) during a semen collection period of more than four months. The bulls were related through a common ancestor on both their paternal and maternal ancestry. Thus, a recessive mode of inheritance of asthenospermia was suspected. ResultsBoth bulls were genotyped at 54,001 SNPs using the Illumina BovineSNP50 Bead chip. A scan for autozygosity revealed that they were identical by descent for a 2.98 Mb segment located on bovine chromosome 25. This haplotype was not found in the homozygous state in 8,557 fertile bulls although five homozygous haplotype carriers were expected (P=0.018). Whole genome-sequencing uncovered that both asthenospermic bulls were homozygous for a mutation that disrupts a canonical 5 splice donor site of CCDC189 encoding the coiled-coil domain containing protein 189. Transcription analysis showed that the derived allele activates a cryptic splice site resulting in a frameshift and premature termination of translation. The mutated CCDC189 protein is truncated by more than 40%, thus lacking the flagellar C1a complex subunit C1a-32 that is supposed to modulate the physiological movement of the sperm flagella. The mutant allele occurs at a frequency of 2.5% in Nordic Red cattle. ConclusionsOur study in cattle uncovered that CCDC189 is required for physiological movement of sperm flagella thus enabling active progression of spermatozoa and fertilization. A direct gene test may be implemented to monitor the asthenospermia-associated allele and prevent the birth of homozygous bulls that are infertile. Our results have been integrated in the Online Mendelian Inheritance in Animals (OMIA) database (https://omia.org/OMIA002167/9913/).

genomics↗

bioRxiv2018

Accurate sequence variant genotyping in cattle using variation-aware genome graphs

BackgroundThe genotyping of sequence variants typically involves as a first step the alignment of sequencing reads to a linear reference genome. Because a linear reference genome represents only a small fraction of sequence variation within a species, reference allele bias may occur at highly polymorphic or diverged regions of the genome. Graph-based methods facilitate to compare sequencing reads to a variation-aware genome graph that incorporates non-redundant DNA sequences that segregate within a species. We compared sensitivity and accuracy of graph-based sequence variant genotyping using the Graphtyper software to two widely used methods, i.e., GATK and SAMtools, that rely on linear reference genomes using whole-genomes sequencing data of 49 Original Braunvieh cattle.\n\nResultsWe discovered 21,140,196, 20,262,913 and 20,668,459 polymorphic sites using GATK, Graphtyper, and SAMtools, respectively. Comparisons between sequence variant and microarray-derived genotypes showed that Graphtyper outperformed both GATK and SAMtools in terms of genotype concordance, non-reference sensitivity, and non-reference discrepancy. The sequence variant genotypes that were obtained using Graphtyper had the lowest number of mendelian inconsistencies for both SNPs and indels in nine sire-son pairs with sequence data. Genotype phasing and imputation using the Beagle software improved the quality of the sequence variant genotypes for all tools evaluated particularly for animals that have been sequenced at low coverage. Following imputation, the concordance between sequence- and microarray-derived genotypes was almost identical for the three methods evaluated, i.e., 99.39, 99.29, and 99.52 % for GATK, SAMtools, and Graphtyper, respectively. Graphtyper required considerably more computing resources than SAMtools but it required less than GATK.\n\nConclusionsSequence variant genotyping using Graphtyper is accurate, sensitive and computationally feasible in cattle. Graph-based methods enable sequence variant genotyping from variation-aware reference genomes that may incorporate cohort-specific sequence variants which is not possible with the current implementations of state-of-the-art methods that rely on linear reference genomes.

genomics↗

bioRxiv2017

Meta-Analysis Of Sequence-Based Association Studies Across Three Cattle Breeds Reveals 25 QTL For Fat And Protein Percentages In Milk At Nucleotide Resolution

BackgroundGenotyping and whole-genome sequencing data have been collected in many cattle breeds. The compilation of large reference panels facilitates imputing sequence variant genotypes for animals that have been genotyped using dense genotyping arrays. Association studies with imputed sequence variant genotypes allow characterization of quantitative trait loci (QTL) at nucleotide resolution particularly when individuals from several breeds are included in the mapping populations.\n\nResultsWe imputed genotypes for more than 28 million sequence variants in 17,229 animals of the Braunvieh (BV), Fleckvieh (FV) and Holstein (HOL) cattle breeds in order to generate large mapping populations that are required to identify sequence variants underlying milk production traits. Within-breed association tests between imputed sequence variant genotypes and fat and protein percentages in milk uncovered between six and thirteen QTL (P<1e-8) per breed. Eight of the detected QTL were significant in more than one breed. We combined the association studies across three breeds using meta-analysis and identified 25 QTL including six that were not significant in the within-breed association studies. Closer inspection of the QTL revealed that two well-known causal missense mutations in the ABCG2 (p.Y581S, rs43702337, P=4.3e-34) and GHR (p.F279Y, rs385640152, P=1.6e-74) genes were the top variants at two QTL on chromosomes 6 and 20. Another true causal missense mutation in the DGAT1 gene (p.A232K, rs109326954, P=8.4e-1436) was the second top variant at a QTL on chromosome 14 but its allelic substitution effects were not consistent across three breeds analyzed. It turned out that the conflicting allelic substitution effects resulted from flaws in the imputed genotypes due to the use of a multi-breed reference population for genotype imputation.\n\nConclusionsMany QTL for milk production traits segregate across breeds. Metaanalysis of association studies across breeds has greater power to detect such QTL than within-breed association studies. True causal mutations can be readily detected among the most significantly associated variants at QTL when the accuracy of imputation is high. However, true causal mutations may show conflicting allelic substitution effects across breeds when the imputed sequence variant genotypes contain flaws. Validating the effect of known causal variants is highly recommended in order to assess the ability to detect true causal mutations in association studies with imputed sequence variant genotypes.

genomics↗

bioRxiv2016

Evaluation of the accuracy of imputed sequence variants and their utility for causal variant detection in cattle

BackgroundThe availability of dense genotypes and whole-genome sequence variants from various sources offers the opportunity to compile large data sets consisting of tens of thousands of animals with genotypes for millions of polymorphic sites that may enhance the power of genomic analyses. The imputation of missing genotypes ensures that all individuals have genotypes for a shared set of variants.\n\nResultsWe evaluated the accuracy of imputation from dense genotypes to whole-genome sequence variants in 249 Fleckvieh and 450 Holstein cattle using Minimac and FImpute. The sequence variants of a subset of the animals were reduced to the variants that were included in the Illumina BovineHD genotyping array and subsequently inferred in silico using either within- or multi-breed reference populations. The accuracy of imputation varied considerably across chromosomes and dropped at regions where the bovine genome contains segmental duplications. Depending on the imputation strategy, the correlation between imputed and true genotypes ranged from 0.898 to 0.952. The accuracy of imputation was higher with Minimac than FImpute particularly for rare alleles. Considering a multi-breed reference population increased the accuracy of imputation, particularly when FImpute was used to infer genotypes. When the sequence variants were imputed using Minimac, the true genotypes were more correlated to predicted allele dosages than best-guess genotypes. The computing costs to impute 23,256,743 sequence variants in 6958 animals were 10-fold higher with Minimac than FImpute. Association studies with imputed sequence variants revealed seven quantitative trait loci (QTL) for milk fat percentage. Two known causal mutations in the DGAT1 and GHR genes were the most significantly associated variants at two QTL on chromosomes 14 and 20 when Minimac was used to infer genotypes.\n\nConclusionsThe population-based imputation of millions of sequence variants in large cohorts provides accurate genotypes and is computationally feasible. Using a reference population that includes individuals from many breeds increases the accuracy of imputation particularly at low-frequency variants. Considering allele dosages rather than best-guess genotypes as explanatory variables is advantageous for association studies with imputed sequence variants.

genomics↗