Bevin Harris

Variants modulating the expression of a chromosome domain encompassing PLAG1 influence bovine stature

We report mapping of a quantitative trait locus (QTL) with a major effect on bovine stature to a ∼780-kb interval using a Hidden Markov Model–based approach that simultaneously exploits linkage and linkage disequilibrium. We re-sequenced the interval in six sires with known QTL genotype and identified 13 clustered candidate quantitative trait nucleotides (QTNs) out of >9,572 discovered variants. We eliminated five candidate QTNs by studying the phenotypic effect of a recombinant haplotype identified in a breed diversity panel. We show that the QTL influences fetal expression of seven of the nine genes mapping to the ∼780-kb interval. We further show that two of the eight candidate QTNs, mapping to the PLAG1-CHCHD7 intergenic region, influence bidirectional promoter strength and affect binding of nuclear factors. By performing expression QTL analyses, we identified a splice site variant in CHCHD7 and exploited this naturally occurring null allele to exclude CHCHD7 as single causative gene.

Genomic predictions for New Zealand dairy bulls and integration with national genetic evaluation.

A method is described for the prediction of breeding values incorporating genomic information. The first stage involves the prediction of genomic breeding values for genotyped individuals. A novel component of this is the estimation of the genomic relationship matrix in the context of a multi-breed population. Because not all ancestors of genotyped animals are genotyped, a selection index procedure is used to blend genomic predictions with traditional ancestral information that is lost between the process of deregression of the national breeding values and subsequent re-estimation using the genomic relationship matrix. Finally, the genomically enhanced predictions are filtered through to nongenotyped descendants using a regression procedure.

Genome scan for the degree of white spotting in dairy cattle

White spotting is one of the most distinguishing visual characters in dairy cattle. There is considerable variation within and between breeds of cattle. The objective of this study was to map quantitative trait loci (QTL) affecting the degree of white spotting in dairy cattle based on an F(2) experimental design using Holstein-Friesian and Jersey crossbred cows. The genome scan was implemented using half-sib and line-of-descent approaches with high density markers. Significant QTL were found on chromosomes 6, 18 and 22. The mapped region on BTA6 confirmed the widely conserved KIT locus affecting mammalian pigmentation. Haplotype information linked the highly significant QTL on BTA22 to the Microphthalmia-associated transcription factor (MITF) gene, which has been reported to be associated with pigmentation traits in some other mammals.

Genome scan of pigmentation traits in Friesian-Jersey crossbred cattle.

Pigmentation traits expressed in animals are visual characteristics that allow us to distinguish between breeds and between strains within breed. The objective of this study was to map quantitative trait loci (QTLs) affecting the pigmentation traits in approximately 800 F(2) grand daughter dairy cattle from a Holstein-Friesian and Jersey cross breed cattle. Traits analyzed included pigmentation phenotypes on the body, teat and hoop. The phenoypes were collected from digital photos or visual inspection of live animals. QTL mapping was implemented using half-sib and line-of-descent inheritance models. Our analysis initially detected a number of significant QTLs on chromosomes: 2, 6, 13, 15, 18 and 22. The significant QTLs were divided into two groups: one group influencing the pigmentation color and the other group affecting the absence or level of pigmentation. The most significant QTL peaks were observed on Bovine taurus autosome 18 (BTA18) close to melanocortin 1 receptor (MC1R) for the color traits, on BTA6 close to the receptor tyrosine kinase (KIT) and BTA22 close to microphthalmia-associated transcription factor (MITF) gene for the spotting traits. Association studies were conducted for candidate regions or genes known to affect pigmentation in dairy cattle.

Estimation of test-day model (co)variance components across breeds using New Zealand dairy cattle data

In New Zealand, a large proportion of cows are currently crossbreds, mostly Holstein-Friesians (HF) x Jersey (JE). The genetic evaluation system for milk yields is considering the same additive genetic effects for all breeds. The objective was to model different additive effects according to parental breeds to obtain first estimates of correlations among breed-specific effects and to study the usefulness of this type of random regression test-day model. Estimates of (co)variance components for purebred HF and JE cattle in purebred herds were computed by using a single-breed model. This analysis showed differences between the 2 breeds, with a greater variability in the HF breed. (Co)variance components for purebred HF and JE and crossbred HF x JE cattle were then estimated by using a complete multibreed model in which computations of complete across-breed (co)variances were simplified by correlating only eigenvectors for HF and JE random regressions of the same order as obtained from the single-breed analysis. Parameter estimates differed more strongly than expected between the single-breed and multibreed analyses, especially for JE. This could be due to differences between animals and management in purebred and non-purebred herds. In addition, the model used only partially accounted for heterosis. The multibreed analysis showed additive genetic differences between the HF and JE breeds, expressed as genetic correlations of additive effects in both breeds, especially in linear and quadratic Legendre polynomials (respectively, 0.807 and 0.604). The differences were small for overall milk production (0.926). Results showed that permanent environmental lactation curves were highly correlated across breeds; however, intraherd lactation curves were also affected by the breed-environment interaction. This result may indicate the existence of breed-specific competition effects that vary through the different lactation stages. In conclusion, a multibreed model similar to the one presented could optimally use the environmental and genetic parameters and provide breed-dependent additive breeding values. This model could also be a useful tool to evaluate crossbred dairy cattle populations like those in New Zealand. However, a routine evaluation would still require the development of an improved methodology. It would also be computationally very challenging because of the simultaneous presence of a large number of breeds.

Widespread cis-regulation of RNA-editing in a large mammal

Post-transcriptional RNA editing may regulate transcript expression and diversity in cells, with potential impacts on various aspects of physiology and environmental adaptation. A small number of recent genome-wide studies in Drosophila, mouse, and human have shown that RNA editing can be genetically modulated, highlighting loci that quantitatively impact editing of transcripts. The potential gene expression and physiological consequences of these RNA editing quantitative trait loci (edQTL), however, are almost entirely unknown. Here, we present analyses of RNA editing in a large domestic mammal (Bos taurus), where we use whole genome and high depth RNA sequencing to discover, characterise, and conduct genetic mapping studies of novel transcript edits. Using a discovery population of nine deeply-sequenced cows, we identify 2,001 edit sites in the mammary transcriptome, the majority of which are adenosine to inosine edits (97.4%). Most sites are predicted to reside in double-stranded secondary structures (85.7%), and quantification of the rates of editing in an additional 355 cows reveals editing is negatively correlated with gene expression in the majority of cases. Genetic analyses of RNA editing and gene expression highlights 67 cis-regulated edQTL, of which seven appear to co-segregate with expression QTL effects. Trait association analyses in a separate population of 9,988 lactating cows also shows nine of the cis-edQTL coincide with at least one co-segregating lactation QTL. Together, these results enhance our understanding of RNA editing dynamics in mammals, and suggest mechanistic links by which loci may impact phenotype through RNA-editing mediated processes.

Multiple QTL underlie milk phenotypes at the CSF2RB locus

Background Bovine milk provides an important source of nutrition in much of the Western world, forming components of many food products. Over many years, artificial selection has substantially improved milk production by cows. However, the genes underlying milk production quantitative trait loci (QTL) remain relatively poorly characterised. Here, we investigate a previously-reported QTL located at the CSF2RB locus, for several milk production phenotypes, to better understand its underlying genetic and molecular causes. Results Using a population of 29,350 taurine dairy cattle, we conducted association analyses for milk yield and composition traits, and identified highly significant QTL for milk yield, milk fat concentration, and milk protein concentration. Strikingly, protein concentration and milk yield appear to show co-located yet genetically distinct QTL. To attempt to understand the molecular mechanisms that might be mediating these effects, gene expression data were used to investigate eQTL for eleven genes in the broader interval. This analysis highlighted genetic impacts on CSF2RB and NCF4 expression that share similar association signatures to those observed for lactation QTL, strongly implicating one or both of these genes as the cause of these effects. Using the same gene expression dataset representing 357 lactating cows, we also identified 38 novel RNA editing sites in the 3′ UTR of CSF2RB transcripts. The extent to which two of these sites were edited also appears to be genetically co-regulated with lactation QTL, highlighting a further layer of regulatory complexity implicating the CSF2RB gene. Conclusions This chromosome 5 locus presents a diversity of molecular and lactation QTL, likely representing multiple overlapping effects that, at a minimum, highlight the CSF2RB gene as having a causal role in these processes.