A reverse genetic approach identifies an ancestral frameshift mutation in RP1 causing recessive progressive retinal degeneration in European cattle breeds

A recessive CLN3 variant is responsible for delayed-onset retinal degeneration in Hereford cattle

Thirteen American Hereford cattle were reported blind with presumed onset when ~12-mo-old. All blind cattle shared a common ancestor through both the maternal and paternal pedigrees, suggesting a recessive genetic origin. Given the pedigree relationships and novel phenotype, we characterized the ophthalmo-pathologic changes associated with blindness and identified the responsible gene variant. Ophthalmologic examinations of 5 blind cattle revealed retinal degeneration. Histologically, 2 blind cattle had loss of the retinal photoreceptor layer. Whole-genome sequencing (WGS) of 7 blind cattle and 9 unaffected relatives revealed a 1-bp frameshift deletion in ceroid lipofuscinosis neuronal 3 (CLN3; chr25 g.26043843del) for which the blind cattle were homozygous and their parents heterozygous. The identified variant in exon 16 of 17 is predicted to truncate the encoded protein (p. Pro369Argfs*8) battenin, which is involved in lysosomal function necessary for photoreceptor layer maintenance. Of 462 cattle genotyped, only blind cattle were homozygous for the deletion. A query of WGS data of > 5,800 animals further revealed that the variant was only observed in related Hereford cattle. Mutations in CLN3 are associated with human juvenile neuronal ceroid lipofuscinosis (JNCL), or Batten disease, which results in early-onset retinal degeneration and lesions similar to those observed in our cases. Our data support the frameshift variant of CLN3 as causative of blindness in these Hereford cattle, and provide additional evidence of the role of this gene in retinal lesions, possibly as a model for human non-syndromic JNCL.

Genome-Wide Association Study to Identify QTL for Carcass Traits in Korean Hanwoo Cattle

This study aimed to identify genetic associations with carcass traits in Hanwoo cattle using a genome-wide association study. A total of 9302 phenotypes were analyzed, and all animals were genotyped using the Illumina Bovine 50K v.3 SNP chip. Heritabilities for carcass weight (CWT), eye muscle area (EMA), backfat thickness (BF), and marbling score (MS) were estimated as 0.42, 0.36, 0.36, and 0.47, respectively, using the GBLUP model, and 0.47, 0.37, 0.36, and 0.42, respectively, using the Bayes B model. We identified 129 common SNPs using DGEBV and 118 common SNPs using GEBV on BTA6, BTA13, and BTA14, suggesting their potential association with the traits of interest. No common SNPs were found between the GBLUP and Bayes B methods when using residuals as a response variable in GWAS. The most promising candidate genes for CWT included SLIT2, PACRGL, KCNIP4, RP1, XKR4, LYN, RPS20, MOS, FAM110B, UBXN2B, CYP7A1, SDCBP, NSMAF, TOX, CA8, LAP3, FAM184B, and NCAPG. For EMA, the genes IBSP, LAP3, FAM184B, LCORL, NCAPG, SLC30A9, and BEND4 demonstrated significance. Similarly, CYP7B1, ARMC1, PDE7A, and CRH were associated with BF, while CTSZ, GNAS, VAPB, and RAB22A were associated with MS. This finding offers valuable insights into genomic regions and molecular mechanisms influencing Hanwoo carcass traits, aiding efficient breeding strategies.

Invited review: Good practices in genome-wide association studies to identify candidate sequence variants in dairy cattle

Genotype data from dairy cattle selection programs have greatly facilitated GWAS to identify variants related to economic traits. Results can enhance the accuracy of genomic prediction, analyze more complex models that go beyond additive effects, elucidate the genetic architecture of a trait, and finally, decipher the underlying biology of traits. The entire process, comprising data generation, quality control, statistical analyses, interpretation of association results, and linking results to biology should be designed and executed to minimize the generation of false-positive and false-negative associations and misleading links to biological processes. This review aims to provide general guidelines for data analysis that address data quality control, association tests, adjustment for population stratification, and significance evaluation to improve the reliability of conclusions. We also provide guidance on post-GWAS strategy and the interpretation of results. These guidelines are tailored to dairy cattle, which are characterized by long-range linkage disequilibrium, large half-sib families, and routinely collected phenotypes, requiring different approaches than those applied in human GWAS. We discuss common limitations and challenges that have been overlooked in the analysis and interpretation of GWAS to identify candidate sequence variants in dairy cattle.

Integrative QTL mapping and selection signatures in Groningen White Headed cattle inferred from whole-genome sequences

Here, we aimed to identify and characterize genomic regions that differ between Groningen White Headed (GWH) breed and other cattle, and in particular to identify candidate genes associated with coat color and/or eye-protective phenotypes. Firstly, whole genome sequences of 170 animals from eight breeds were used to evaluate the genetic structure of the GWH in relation to other cattle breeds by carrying out principal components and model-based clustering analyses. Secondly, the candidate genomic regions were identified by integrating the findings from: a) a genome-wide association study using GWH, other white headed breeds (Hereford and Simmental), and breeds with a non-white headed phenotype (Dutch Friesian, Deep Red, Meuse-Rhine-Yssel, Dutch Belted, and Holstein Friesian); b) scans for specific signatures of selection in GWH cattle by comparison with four other Dutch traditional breeds (Dutch Friesian, Deep Red, Meuse-Rhine-Yssel and Dutch Belted) and the commercial Holstein Friesian; and c) detection of candidate genes identified via these approaches. The alignment of the filtered reads to the reference genome (ARS-UCD1.2) resulted in a mean depth of coverage of 8.7X. After variant calling, the lowest number of breed-specific variants was detected in Holstein Friesian (148,213), and the largest in Deep Red (558,909). By integrating the results, we identified five genomic regions under selection on BTA4 (70.2-71.3 Mb), BTA5 (10.0-19.7 Mb), BTA20 (10.0-19.9 and 20.0-22.7 Mb), and BTA25 (0.5-9.2 Mb). These regions contain positional and functional candidate genes associated with retinal degeneration (e.g., CWC27 and CLUAP1), ultraviolet protection (e.g., ERCC8), and pigmentation (e.g. PDE4D) which are probably associated with the GWH specific pigmentation and/or eye-protective phenotypes, e.g. Ambilateral Circumocular Pigmentation (ACOP). Our results will assist in characterizing the molecular basis of GWH phenotypes and the biological implications of its adaptation.

Non-additive QTL mapping of lactation traits in 124,000 cattle reveals novel recessive loci

BACKGROUND

Deleterious recessive conditions have been primarily studied in the context of Mendelian diseases. Recently, several deleterious recessive mutations with large effects were discovered via non-additive genome-wide association studies (GWAS) of quantitative growth and developmental traits in cattle, which showed that quantitative traits can be used as proxies of genetic disorders when such traits are indicative of whole-animal health status. We reasoned that lactation traits in cattle might also reflect genetic disorders, given the increased energy demands of lactation and the substantial stresses imposed on the animal. In this study, we screened more than 124,000 cows for recessive effects based on lactation traits.

RESULTS

We discovered five novel quantitative trait loci (QTL) that are associated with large recessive impacts on three milk yield traits, with these loci presenting missense variants in the DOCK8, IL4R, KIAA0556, and SLC25A4 genes or premature stop variants in the ITGAL, LRCH4, and RBM34 genes, as candidate causal mutations. For two milk composition traits, we identified several previously reported additive QTL that display small dominance effects. By contrasting results from milk yield and milk composition phenotypes, we note differing genetic architectures. Compared to milk composition phenotypes, milk yield phenotypes had lower heritabilities and were associated with fewer additive QTL but had a higher non-additive genetic variance and were associated with a higher proportion of loci exhibiting dominance.

CONCLUSIONS

We identified large-effect recessive QTL which are segregating at surprisingly high frequencies in cattle. We speculate that the differences in genetic architecture between milk yield and milk composition phenotypes derive from underlying dissimilarities in the cellular and molecular representation of these traits, with yield phenotypes acting as a better proxy of underlying biological disorders through presentation of a larger number of major recessive impacts.

Deleterious protein-coding variants in diverse cattle breeds of the world

The domestication of wild animals has resulted in a reduction in effective population sizes, which can affect the deleterious mutation load of domesticated breeds. In addition, artificial selection contributes to the accumulation of deleterious mutations because of an increased rate of inbreeding among domesticated animals. Since founder population sizes and artificial selection differ between cattle breeds, their deleterious mutation load can vary. We investigated this question by using whole-genome data from 432 animals belonging to 54 worldwide cattle breeds. Our analysis revealed a negative correlation between genomic heterozygosity and nonsynonymous-to-silent diversity ratio, which suggests a higher proportion of single nucleotide variants (SNVs) affecting proteins in low-diversity breeds. Our results also showed that low-diversity breeds had a larger number of high-frequency (derived allele frequency (DAF) > 0.51) deleterious SNVs than high-diversity breeds. An opposite trend was observed for the low-frequency (DAF ≤ 0.51) deleterious SNVs. Overall, the number of high-frequency deleterious SNVs was larger in the genomes of taurine cattle breeds than of indicine breeds, whereas the number of low-frequency deleterious SNVs was larger in the genomes of indicine cattle than in those of taurine cattle. Furthermore, we observed significant variation in the counts of deleterious SNVs within taurine breeds. The variations in deleterious mutation load between taurine and indicine breeds could be attributed to the population sizes of the wild progenitors before domestication, whereas the variations observed within taurine breeds could be due to differences in inbreeding level, strength of artificial selection, and/or founding population size. Our findings imply that the incidence of genetic diseases can vary between cattle breeds.

Analysis of pedigree data and whole-genome sequences in 12 cattle breeds reveals extremely low within-breed Y-chromosome diversity

In this article, we analyzed pedigree information on males from 12 bovine breeds born in France between 2015 and 2019. We report an overall small number of paternal lineages with, for example, a minimal number of ancestors accounting for 95% of the Y‐chromosome pool of their breed ranging from only 2 to 15 individuals. Then, we mined whole‐genome sequence data from 811 sires (2 ≤ n ≤ 510 per breed) and built a median‐joining network using 1411 SNPs. Most branches were breed‐specific and in agreement with the geographic and genetic relatedness of these populations. The within‐breed haplotype diversity was lower than expected based on genealogical information, which supports the existence of major male founder effects predating pedigree recording. In addition, we observed de novo mutation events among the descendants of the same ancestors, which are of interest to define paternal sub‐lineages. Our results pave the way to future studies on the estimation of the effects of Y‐chromosome haplotypes on male reproductive performances and on the conservation of Y‐chromosome diversity.

Genome-wide association study for buffalo mammary gland morphology

This research communication describes a genome-wide association study for Italian buffalo mammary gland morphology. Three single nucleotide polymorphisms (AX-85117983, AX-8509475 and AX-85117518) were identified to be significantly associated with buffalo anterior teat length, posterior teat length and distance between anterior and posterior teat, respectively. Two significant signals for buffalo mammary gland morphology were observed in two genomic regions on the chromosome 10, and chromosome 20. One of the regions located on the chromosome 10 has the most likely candidate genes ACTC1 and GJD2, both of which have putative roles in the regulation of mammary gland development. This study provides new insights into the genetic variants of buffalo mammary gland morphology and may be beneficial for understanding of the genetic regulation of mammary growth.

Weighted single-step genomic best linear unbiased prediction integrating variants selected from sequencing data by association and bioinformatics analyses

Background

Sequencing data enable the detection of causal loci or single nucleotide polymorphisms (SNPs) highly linked to causal loci to improve genomic prediction. However, until now, studies on integrating such SNPs using a single-step genomic best linear unbiased prediction (ssGBLUP) model are scarce. We investigated the integration of sequencing SNPs selected by association (1262 SNPs) and bioinformatics (2359 SNPs) analyses into the currently used 54K-SNP chip, using three ssGBLUP models which make different assumptions on the distribution of SNP effects: a basic ssGBLUP model, a so-called featured ssGBLUP (ssFGBLUP) model that considered selected sequencing SNPs as a feature genetic component, and a weighted ssGBLUP (ssWGBLUP) model in which the genomic relationship matrix was weighted by the SNP variances estimated from a Bayesian whole-genome regression model, with every 1, 30, or 100 adjacent SNPs within a chromosome region sharing the same variance. We used data on milk production and female fertility in Danish Jersey. In total, 15,823 genotyped and 528,981‬ non-genotyped females born between 1990 and 2013 were used as reference population and 7415 genotyped females and 33,040 non-genotyped females born between 2014 and 2016 were used as validation population.

Results

With basic ssGBLUP, integrating SNPs selected from sequencing data improved prediction reliabilities for milk and protein yields, but resulted in limited or no improvement for fat yield and female fertility. Model performances depended on the SNP set used. When using ssWGBLUP with the 54K SNPs, reliabilities for milk and protein yields improved by 0.028 for genotyped animals and by 0.006 for non-genotyped animals compared with ssGBLUP. However, with the SNP set that included SNPs selected from sequencing data, no statistically significant difference in prediction reliability was observed between the three ssGBLUP models.

Conclusions

In summary, when using 54K SNPs, a ssWGBLUP model with a common weight on the SNPs in a given region is a feasible approach for single-trait genetic evaluation. Integrating relevant SNPs selected from sequencing data into the standard SNP chip can improve the reliability of genomic prediction. Based on such SNP data, a basic ssGBLUP model was suggested since no significant improvement was observed from using alternative models such as ssWGBLUP and ssFGBLUP.

Imputation for sequencing variants preselected to a customized low-density chip

The sequencing variants preselected from association analyses and bioinformatics analyses could improve genomic prediction. In this study, the imputation of sequencing SNPs preselected from major dairy breeds in Denmark-Finland-Sweden (DFS) and France (FRA) was investigated for both contemporary animals and old bulls in Danish Jersey. For contemporary animals, a two-step imputation which first imputed to 54 K and then to 54 K + DFS + FRA SNPs achieved highest accuracy. Correlations between observed and imputed genotypes were 91.6% for DFS SNPs and 87.6% for FRA SNPs, while concordance rates were 96.6% for DFS SNPs and 93.5% for FRA SNPs. The SNPs with lower minor allele frequency (MAF) tended to have lower correlations but higher concordance rates. For old bulls, imputation for DFS and FRA SNPs were relatively accurate even for bulls without progenies (correlations higher than 97.2% and concordance rates higher than 98.4%). For contemporary animals, given limited imputation accuracy of preselected sequencing SNPs especially for SNPs with low MAF, it would be a good strategy to directly genotype preselected sequencing SNPs with a customized SNP chip. For old bulls, given high imputation accuracy for preselected sequencing SNPs with all MAF ranges, it would be unnecessary to re-genotype preselected sequencing SNPs.

Genome-wide association and genotype by environment interactions for growth traits in U.S. Gelbvieh cattle

BACKGROUND

Single nucleotide polymorphism (SNP) arrays have facilitated discovery of genetic markers associated with complex traits in domestic cattle; thereby enabling modern breeding and selection programs. Genome-wide association analyses (GWAA) for growth traits were conducted on 10,837 geographically diverse U.S. Gelbvieh cattle using a union set of 856,527 imputed SNPs. Birth weight (BW), weaning weight (WW), and yearling weight (YW) were analyzed using GEMMA and EMMAX (via imputed genotypes). Genotype-by-environment (GxE) interactions were also investigated.

RESULTS

GEMMA and EMMAX produced moderate marker-based heritability estimates that were similar for BW (0.36-0.37, SE = 0.02-0.06), WW (0.27-0.29, SE = 0.01), and YW (0.39-0.41, SE = 0.01-0.02). GWAA using 856K imputed SNPs (GEMMA; EMMAX) revealed common positional candidate genes underlying pleiotropic QTL for Gelbvieh growth traits on BTA6, BTA7, BTA14, and BTA20. The estimated proportion of phenotypic variance explained (PVE) by the lead SNP defining these QTL (EMMAX) was larger and most similar for BW and YW, and smaller for WW. Collectively, GWAAs (GEMMA; EMMAX) produced a highly concordant set of BW, WW, and YW QTL that met a nominal significance level (P ≤ 1e-05), with prioritization of common positional candidate genes; including genes previously associated with stature, feed efficiency, and growth traits (i.e., PLAG1, NCAPG, LCORL, ARRDC3, STC2). Genotype-by-environment QTL were not consistent among traits at the nominal significance threshold (P ≤ 1e-05); although some shared QTL were apparent at less stringent significance thresholds (i.e., P ≤ 2e-05).

CONCLUSIONS

Pleiotropic QTL for growth traits were detected on BTA6, BTA7, BTA14, and BTA20 for U.S. Gelbvieh beef cattle. Seven QTL detected for Gelbvieh growth traits were also recently detected for feed efficiency and growth traits in U.S. Angus, SimAngus, and Hereford cattle. Marker-based heritability estimates and the detection of pleiotropic QTL segregating in multiple breeds support the implementation of multiple-breed genomic selection.

1000 Bull Genomes Project to Map Simple and Complex Genetic Traits in Cattle: Applications and Outcomes

The 1000 Bull Genomes Project is a collection of whole-genome sequences from 2,703 individuals capturing a significant proportion of the world's cattle diversity. So far, 84 million single-nucleotide polymorphisms (SNPs) and 2.5 million small insertion deletions have been identified in the collection, a very high level of genetic diversity. The project has greatly accelerated the identification of deleterious mutations for a range of genetic diseases, as well as for embryonic lethals. The rate of identification of causal mutations for complex traits has been slower, reflecting the typically small effect size of these mutations and the fact that many are likely in as-yet-unannotated regulatory regions. Both the deleterious mutations that have been identified and the mutations associated with complex trait variation have been included in low-cost SNP array designs, and these arrays are being genotyped in tens of thousands of dairy and beef cattle, enabling management of deleterious mutations in these populations as well as genomic selection.

Short communication: A splice site mutation in CENPU is associated with recessive embryonic lethality in Holstein cattle

A genome scan for homozygous haplotype deficiency coupled with whole-genome sequence data analysis is a very effective method to identify embryonic lethal mutations in cattle. Among other factors, the power of the approach depends on the availability of a greater amount of genotyping and sequencing data. In the present study, we analyzed the largest known panel of Illumina BovineSNP50 (Illumina Inc., San Diego, CA) genotypes, comprising 401,896 Holstein animals, and we report the mapping of a new embryonic lethal haplotype on chromosome 27, called HH7. We fine mapped the locus in a 2.0-Mb interval using an identical-by-descent approach and analyzed genome sequence data from 4 carrier and 143 noncarrier Holstein bulls to identify the causative mutation. We detected a strong candidate variant in the gene encoding centromere protein U (CENPU), a centromere component essential for proper chromosome segregation during mitosis. The mutant allele is a deletion of 4 nucleotides located at position +3 to +6 bp after the splicing donor site of exon 11. Cross-species nucleotide alignment revealed that the nucleotide at position +3 is entirely conserved among vertebrates, suggesting that it plays an important role in the regulation of CENPU splicing. For verification, we genotyped the candidate variant in 232,775 Holstein individuals and did not observe any homozygotes, whereas 16 were expected (Poisson P-value = 1.1 × 10^-7; allele frequency = 0.8%). In addition, genotyping of 250,602 animals from 19 additional breeds revealed that the mutant allele is restricted to animals of Holstein descent. Finally, we estimated the effect of the candidate variant on 2 fertility traits in at-risk mating (i.e., between carrier bulls and daughters of carrier bulls) versus non-risk mating. In agreement with a recessive lethal inheritance pattern, we observed a marked reduction in both conception rate and 56-d nonreturn rate in heifers and cows. The effect on 56-d nonreturn rate suggests that a substantial proportion of homozygous mutants die before 35 d after insemination, which is consistent with the early embryonic death previously reported in CENPU^-/- mouse embryos. In conclusion, we demonstrate that with more than 400,000 genotypes, we can map very rare recessive lethal mutations segregating at a frequency below 1% in the population. We recommend performing new analyses regularly as data are accumulating.

Improvement of genomic prediction by integrating additional single nucleotide polymorphisms selected from imputed whole genome sequencing data

The availability of whole genome sequencing (WGS) data enables the discovery of causative single nucleotide polymorphisms (SNPs) or SNPs in high linkage disequilibrium with causative SNPs. This study investigated effects of integrating SNPs selected from imputed WGS data into the data of 54K chip on genomic prediction in Danish Jersey. The WGS SNPs, mainly including peaks of quantitative trait loci, structure variants, regulatory regions of genes, and SNPs within genes with strong effects predicted with variant effect predictor, were selected in previous analyses for dairy breeds in Denmark–Finland–Sweden (DFS) and France (FRA). Animals genotyped with 54K chip, standard LD chip, and customized LD chip which covered selected WGS SNPs and SNPs in the standard LD chip, were imputed to 54K together with DFS and FRA SNPs. Genomic best linear unbiased prediction (GBLUP) and Bayesian four-distribution mixture models considering 54K and selected WGS SNPs as one (a one-component model) or two separate genetic components (a two-component model) were used to predict breeding values. For milk production traits and mastitis, both DFS (0.025) and FRA (0.029) sets of additional WGS SNPs improved reliabilities, and inclusions of all selected WGS SNPs generally achieved highest improvements of reliabilities (0.034). A Bayesian four-distribution model yielded higher reliabilities than a GBLUP model for milk and protein, but extra gains in reliabilities from using selected WGS SNPs were smaller for a Bayesian four-distribution model than a GBLUP model. Generally, no significant difference was observed between one-component and two-component models, except for using GBLUP models for milk.

Association of udder traits with single nucleotide polymorphisms in crossbred Bos indicus-Bos taurus cows

The size, support, and health of udders limit the productive life of beef cows, especially those with background, because, in general, such cows have a reputation for problems with udders. Genomic association studies of bovine udder traits have been conducted in dairy cattle and recently in Continental European beef breeds but not in cows with background. The objective of this study was to determine associations of SNP and udder support scores, teat length, and teat diameter in half (Nellore), half (Angus) cows. Udders of cows ( = 295) born from 2003 to 2007 were evaluated for udder support and teat length and diameter ( = 1,746 records) from 2005 through 2014. These included a subjective score representing udder support (values of 1 indicated poorly supported, pendulous udders and values of 9 indicated very well-supported udders) and lengths and diameters of individual teats in the 4 udder quarters as well as the average. Cows were in full-sibling or half-sibling families. Residuals for each trait were produced from repeated records models with cow age category nested within birth year of cows. Those residuals were averaged to become the dependent variables for genomewide association analyses. Regression analyses of those dependent variables included genotypic values as explanatory variables for 34,980 SNP from a commercially available array and included the genomic relationship matrix. Fifteen SNP loci on BTA 5 were associated (false discovery rate controlled at 0.05) with udder support score. One of those was also detected as associated with average teat diameter. Three of those 15 SNP were located within genes, including one each in (), (), and (). These are notable for their functional role in some aspect of mammary gland formation or health. Other candidate genes for these traits in the vicinity of the SNP loci include () and (). Because these were detected in Nellore-Angus crossbred cows, which typically have very well-formed udders with excellent support across their productive lives, similar efforts in other breeds should be completed, because that may facilitate further refinement of genomic regions responsible for variation in udder traits important in multiple breeds.

Genotype disclosure in the genomics era: roles and responsibilities

Disclosure of affected breed without disclosure of major progenitors has been the usual practice in scientific papers reporting recessive heritable disorders of cattle. Before molecular genetics, carrier identity could not be used by breeders to control causal mutations because phenotypically normal heterozygotes among genetically related animals could not be detected other than by test mating. Accurate, low-cost DNA tests fundamentally changed this situation. Genomics can provide relief from the old problem of emerging recessive disorders in cattle breeding, but greater transparency of genotype data between breeders is necessary to fully exploit the opportunities for cost-efficient genetic disease control. Effective control of several recessive disorders has been demonstrated in Angus cattle, based entirely on voluntary DNA testing by breeders but mandatory public disclosure of test results and genotype probabilities for all registered animals. When a DNA test is available, major progenitors (particularly bulls from which semen has been distributed) should be identified and disclosed concurrently with the affected breed. As a minimum, whenever possible the closest common ancestors in the pedigrees of the parents of homozygous mutants should be disclosed after confirmation of carrier status. Progenitor disclosure in scientific publications should occur in cooperation with breed societies, which should have the opportunity to advise breeders and initiate management programs before scientific publication. Unless properly managed, genomic enhancement of animal selection using SNP markers may increase inbreeding, co-ancestry and emergence of recessive disorders. The information systems and genotype disclosure policies of some breed societies will be increasingly challenged, particularly with accelerating mutation discovery using next-generation sequencing.