Allele-specific binding variants causing ChIP-seq peak height of histone modification are not enriched in expression QTL annotations.

BACKGROUND: Genome sequence variants affecting complex traits (quantitative trait loci, QTL) are enriched in functional regions of the genome, such as those marked by certain histone modifications. These variants are believed to influence gene expression. However, due to the linkage disequilibrium among nearby variants, pinpointing the precise location of QTL is challenging. We aimed to identify allele-specific binding (ASB) QTL (asbQTL) that cause variation in the level of histone modification, as measured by the height of peaks assayed by ChIP-seq (chromatin immunoprecipitation sequencing). We identified DNA sequences that predict the difference between alleles in ChIP-seq peak height in H3K4me3 and H3K27ac histone modifications in the mammary glands of cows. RESULTS: We used a gapped k-mer support vector machine, a novel best linear unbiased prediction model, and a multiple linear regression model that combines the other two approaches to predict variant impacts on peak height. For each method, a subset of 1000 sites with the highest magnitude of predicted ASB was considered as candidate asbQTL. The accuracy of this prediction was measured by the proportion where the predicted direction matched the observed direction. Prediction accuracy ranged between 0.59 and 0.74, suggesting that these 1000 sites are enriched for asbQTL. Using independent data, we investigated functional enrichment in the candidate asbQTL set and three control groups, including non-causal ASB sites, non-ASB variants under a peak, and SNPs (single nucleotide polymorphisms) not under a peak. For H3K4me3, a higher proportion of the candidate asbQTL were confirmed as ASB when compared to the non-causal ASB sites (P < 0.01). However, these candidate asbQTL did not enrich for the other annotations, including expression QTL (eQTL), allele-specific expression QTL (aseQTL) and sites conserved across mammals (P > 0.05). CONCLUSIONS: We identified putatively causal sites for asbQTL using the DNA sequence surrounding these sites. Our results suggest that many sites influencing histone modifications may not directly affect gene expression. However, it is important to acknowledge that distinguishing between putative causal ASB sites and other non-causal ASB sites in high linkage disequilibrium with the causal sites regarding their impact on gene expression may be challenging due to limitations in statistical power.

A common regulatory haplotype doubles lactoferrin concentration in milk.

BACKGROUND: Bovine lactoferrin (Lf) is an iron absorbing whey protein with antibacterial, antiviral, and antifungal activity. Lactoferrin is economically valuable and has an extremely variable concentration in milk, partly driven by environmental influences such as milking frequency, involution, or mastitis. A significant genetic influence has also been previously observed to regulate lactoferrin content in milk. Here, we conducted genetic mapping of lactoferrin protein concentration in conjunction with RNA-seq, ChIP-seq, and ATAC-seq data to pinpoint candidate causative variants that regulate lactoferrin concentrations in milk. RESULTS: We identified a highly-significant lactoferrin protein quantitative trait locus (pQTL), as well as a cis lactotransferrin (LTF) expression QTL (cis-eQTL) mapping to the LTF locus. Using ChIP-seq and ATAC-seq datasets representing lactating mammary tissue samples, we also report a number of regions where the openness of chromatin is under genetic influence. Several of these also show highly significant QTL with genetic signatures similar to those highlighted through pQTL and eQTL analysis. By performing correlation analysis between these QTL, we revealed an ATAC-seq peak in the putative promotor region of LTF, that highlights a set of 115 high-frequency variants that are potentially responsible for these effects. One of the 115 variants (rs110000337), which maps within the ATAC-seq peak, was predicted to alter binding sites of transcription factors known to be involved in lactation-related pathways. CONCLUSIONS: Here, we report a regulatory haplotype of 115 variants with conspicuously large impacts on milk lactoferrin concentration. These findings could enable the selection of animals for high-producing specialist herds.

Genetic variation in histone modifications and gene expression identifies regulatory variants in the mammary gland of cattle.

BACKGROUND: Causal variants for complex traits, such as eQTL are often found in non-coding regions of the genome, where they are hypothesised to influence phenotypes by regulating gene expression. Many regulatory regions are marked by histone modifications, which can be assayed by chromatin immunoprecipitation followed by sequencing (ChIP-seq). Sequence reads from ChIP-seq form peaks at putative regulatory regions, which may reflect the amount of regulatory activity at this region. Therefore, eQTL which are also associated with differences in histone modifications are excellent candidate causal variants. RESULTS: We assayed the histone modifications H3K4Me3, H3K4Me1 and H3K27ac and mRNA in the mammary gland of up to 400 animals. We identified QTL for peak height (histone QTL), exon expression (eeQTL), allele specific expression (aseQTL) and allele specific binding (asbQTL). By intersecting these results, we identify variants which may influence gene expression by altering regulatory regions of the genome, and may be causal variants for other traits. Lastly, we find that these variants are found in putative transcription factor binding sites, identifying a mechanism for the effect of many eQTL. CONCLUSIONS: We find that allele specific and traditional QTL analysis often identify the same genetic variants and provide evidence that many eQTL are regulatory variants which alter activity at regulatory regions of the bovine genome. Our work provides methodological and biological updates on how regulatory mechanisms interplay at multi-omics levels.

Screening for phenotypic outliers identifies an unusually low concentration of a ß-lactoglobulin B protein isoform in bovine milk caused by a synonymous SNP.

BACKGROUND: Milk samples from 10,641 dairy cattle were screened by a mass spectrometry method for extreme concentrations of the A or B isoforms of the whey protein, ß-lactoglobulin (BLG), to identify causative genetic variation driving changes in BLG concentration. RESULTS: A cohort of cows, from a single sire family, was identified that produced milk containing a low concentration of the BLG B protein isoform. A genome-wide association study (GWAS) of BLG B protein isoform concentration in milk from AB heterozygous cows, detected a group of highly significant single nucleotide polymorphisms (SNPs) within or close to the BLG gene. Among these was a synonymous G/A variation at position + 78 bp in exon 1 of the BLG gene (chr11:103256256G > A). The effect of the A allele of this SNP (which we named B') on BLG expression was evaluated in a luciferase reporter assay in transfected CHO-K1 and MCF-7 cells. In both cell types, the presence of the B' allele in a plasmid containing the bovine BLG gene from -922 to + 898 bp (relative to the transcription initiation site) resulted in a 60% relative reduction in mRNA expression, compared to the plasmid containing the wild-type B sequence allele. Examination of a mammary RNAseq dataset (n = 391) identified 14 heterozygous carriers of the B' allele which were homozygous for the BLG B protein isoform (BB'). The level of expression of the BLG B' allele was 41.9 ± 1.0% of that of the wild-type BLG B allele. Milk samples from three cows, homozygous for the A allele at chr11:103,256,256 (B'B'), were analysed (HPLC) and showed BLG concentrations of 1.04, 1.26 and 1.83 g/L relative to a mean of 4.84 g/L in milk from 16 herd contemporaries of mixed (A and B) BLG genotypes. The mechanism by which B' downregulates milk BLG concentration remains to be determined. CONCLUSIONS: High-throughput screening and identification of outliers, enabled the discovery of a synonymous G > A mutation in exon 1 of the B allele of the BLG gene (B'), which reduced the milk concentration of ß-lactoglobulin B protein isoform, by more than 50%. Milk from cows carrying the B' allele is expected to have improved processing characteristics, particularly for cheese-making.

Comparison of the genetic characteristics of directly measured and Fourier-transform mid-infrared-predicted bovine milk fatty acids and proteins.

Fourier-transform mid-infrared (FT-MIR) spectroscopy is a high-throughput and inexpensive methodology used to evaluate concentrations of fat and protein in dairy cattle milk samples. The objective of this study was to compare the genetic characteristics of FT-MIR predicted fatty acids and individual milk proteins with those that had been measured directly using gas and liquid chromatography methods. The data used in this study was based on 2,005 milk samples collected from 706 Holstein-Friesian × Jersey animals that were managed in a seasonal, pasture-based dairy system, with milk samples collected across 2 consecutive seasons. Concentrations of fatty acids and protein fractions in milk samples were directly determined by gas chromatography and high-performance liquid chromatography, respectively. Models to predict each directly measured trait based on FT-MIR spectra were developed using partial least squares regression, with spectra from a random selection of half the cows used to train the models, and predictions for the remaining cows used as validation. Variance parameters for each trait and genetic correlations for each pair of measured/predicted traits were estimated from pedigree-based bivariate models using REML procedures. A genome-wide association study was undertaken using imputed whole-genome sequence, and quantitative trait loci (QTL) from directly measured traits were compared with QTL from the corresponding FT-MIR predicted traits. Cross-validation prediction accuracies based on partial least squares for individual and grouped fatty acids ranged from 0.18 to 0.65. Trait prediction accuracies in cross-validation for protein fractions were 0.53, 0.19, and 0.48 for α-casein, ß-casein, and κ-casein, 0.31 for α-lactalbumin, 0.68 for ß-lactoglobulin, and 0.36 for lactoferrin. Heritability estimates for directly measured traits ranged from 0.07 to 0.55 for fatty acids; and from 0.14 to 0.63 for individual milk proteins. For FT-MIR predicted traits, heritability estimates were mostly higher than for the corresponding measured traits, ranging from 0.14 to 0.46 for fatty acids, and from 0.30 to 0.70 for individual proteins. Genetic correlations between directly measured and FT-MIR predicted protein fractions were consistently above 0.75, with the exceptions of C18:0 and C18:3 cis-3, which had genetic correlations of 0.72 and 0.74, respectively. The GWAS identified trait QTL for fatty acids with likely candidates in the DGAT1, CCDC57, SCD, and GPAT4 genes. Notably, QTL for SCD were largely absent in the FT-MIR predicted traits, and QTL for GPAT4 were absent in directly measured traits. Similarly, for directly measured individual proteins, we identified QTL with likely candidates in the CSN1S1, CSN3, PAEP, and LTF genes, but the QTL for CSN3 and LTF were absent in the FT-MIR predicted traits. Our study indicates that genetic correlations between directly measured and FT-MIR predicted fatty acid and protein fractions are typically high, but that phenotypic variation in these traits may be underpinned by differing genetic architecture.

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, characterize, and conduct genetic mapping studies of novel transcript edits. Using a discovery population of nine deeply sequenced cows, we identify 2413 edit sites in the mammary transcriptome, the majority of which are adenosine to inosine edits (98.6%). Most sites are predicted to reside in double-stranded secondary structures (85.1%), 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 highlight 152 cis-regulated edQTL, of which 15 appear to cosegregate with expression QTL effects. Trait association analyses in a separate population of 9989 lactating cows also shows 12 of the cis-edQTL coincide with at least one cosegregating 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.

Sequence-based genome-wide association study of individual milk mid-infrared wavenumbers in mixed-breed dairy cattle.

BACKGROUND: Fourier-transform mid-infrared (FT-MIR) spectroscopy provides a high-throughput and inexpensive method for predicting milk composition and other novel traits from milk samples. While there have been many genome-wide association studies (GWAS) conducted on FT-MIR predicted traits, there have been few GWAS for individual FT-MIR wavenumbers. Using imputed whole-genome sequence for 38,085 mixed-breed New Zealand dairy cattle, we conducted GWAS on 895 individual FT-MIR wavenumber phenotypes, and assessed the value of these direct phenotypes for identifying candidate causal genes and variants, and improving our understanding of the physico-chemical properties of milk. RESULTS: Separate GWAS conducted for each of 895 individual FT-MIR wavenumber phenotypes, identified 450 1-Mbp genomic regions with significant FT-MIR wavenumber QTL, compared to 246 1-Mbp genomic regions with QTL identified for FT-MIR predicted milk composition traits. Use of mammary RNA-seq data and gene annotation information identified 38 co-localized and co-segregating expression QTL (eQTL), and 31 protein-sequence mutations for FT-MIR wavenumber phenotypes, the latter including a null mutation in the ABO gene that has a potential role in changing milk oligosaccharide profiles. For the candidate causative genes implicated in these analyses, we examined the strength of association between relevant loci and each wavenumber across the mid-infrared spectrum. This revealed shared association patterns for groups of genomically-distant loci, highlighting clusters of loci linked through their biological roles in lactation and their presumed impacts on the chemical composition of milk. CONCLUSIONS: This study demonstrates the utility of FT-MIR wavenumber phenotypes for improving our understanding of milk composition, presenting a larger number of QTL and putative causative genes and variants than found from FT-MIR predicted composition traits. Examining patterns of significance across the mid-infrared spectrum for loci of interest further highlighted commonalities of association, which likely reflects the physico-chemical properties of milk constituents.

A new mechanism for a familiar mutation - bovine DGAT1 K232A modulates gene expression through multi-junction exon splice enhancement.

BACKGROUND: The DGAT1 gene encodes an enzyme responsible for catalysing the terminal reaction in mammary triglyceride synthesis, and underpins a well-known pleiotropic quantitative trait locus (QTL) with a large influence on milk composition phenotypes. Since first described over 15 years ago, a protein-coding variant K232A has been assumed as the causative variant underlying these effects, following in-vitro studies that demonstrated differing levels of triglyceride synthesis between the two protein isoforms. RESULTS: We used a large RNAseq dataset to re-examine the underlying mechanisms of this large milk production QTL, and hereby report novel expression-based functions of the chr14 g.1802265AA > GC variant that encodes the DGAT1 K232A substitution. Using expression QTL (eQTL) mapping, we demonstrate a highly-significant mammary eQTL for DGAT1, where the K232A mutation appears as one of the top associated variants for this effect. By conducting in vitro expression and splicing experiments in bovine mammary cell culture, we further show modulation of splicing efficiency by this mutation, likely through disruption of an exon splice enhancer as a consequence of the allele encoding the 232A variant. CONCLUSIONS: The relative contributions of the enzymatic and transcription-based mechanisms now attributed to K232A remain unclear; however, these results suggest that transcriptional impacts contribute to the diversity of lactation effects observed at the DGAT1 locus.

Multiple QTL underlie milk phenotypes at the CSF2RB locus.

BACKGROUND: Over many years, artificial selection has substantially improved milk production by cows. However, the genes that underlie milk production quantitative trait loci (QTL) remain relatively poorly characterised. Here, we investigate a previously reported QTL located at the CSF2RB locus on chromosome 5, for several milk production phenotypes, to better understand its underlying genetic and molecular causes. RESULTS: Using a population of 29,350 taurine dairy cows, 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 11 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 responsible for 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 that involves the CSF2RB gene. CONCLUSIONS: This 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.

Genome-wide association analysis reveals QTL and candidate mutations involved in white spotting in cattle.

BACKGROUND: White spotting of the coat is a characteristic trait of various domestic species including cattle and other mammals. It is a hallmark of Holstein-Friesian cattle, and several previous studies have detected genetic loci with major effects for white spotting in animals with Holstein-Friesian ancestry. Here, our aim was to better understand the underlying genetic and molecular mechanisms of white spotting, by conducting the largest mapping study for this trait in cattle, to date. RESULTS: Using imputed whole-genome sequence data, we conducted a genome-wide association analysis in 2973 mixed-breed cows and bulls. Highly significant quantitative trait loci (QTL) were found on chromosomes 6 and 22, highlighting the well-established coat color genes KIT and MITF as likely responsible for these effects. These results are in broad agreement with previous studies, although we also report a third significant QTL on chromosome 2 that appears to be novel. This signal maps immediately adjacent to the PAX3 gene, which encodes a known transcription factor that controls MITF expression and is the causal locus for white spotting in horses. More detailed examination of these loci revealed a candidate causal mutation in PAX3 (p.Thr424Met), and another candidate mutation (rs209784468) within a conserved element in intron 2 of MITF transcripts expressed in the skin. These analyses also revealed a mechanistic ambiguity at the chromosome 6 locus, where highly dispersed association signals suggested multiple or multiallelic QTL involving KIT and/or other genes in this region. CONCLUSIONS: Our findings extend those of previous studies that reported KIT as a likely causal gene for white spotting, and report novel associations between candidate causal mutations in both the MITF and PAX3 genes. The sizes of the effects of these QTL are substantial, and could be used to select animals with darker, or conversely whiter, coats depending on the desired characteristics.

DNA and RNA-sequence based GWAS highlights membrane-transport genes as key modulators of milk lactose content.

BACKGROUND: Lactose provides an easily-digested energy source for neonates, and is the primary carbohydrate in milk in most species. Bovine lactose is also a key component of many human food products. However, compared to analyses of other milk components, the genetic control of lactose has been little studied. Here we present the first GWAS focussed on analysis of milk lactose traits. RESULTS: Using a discovery population of 12,000 taurine dairy cattle, we detail 27 QTL for lactose concentration and yield, and subsequently validate the effects of 26 of these loci in a distinct population of 18,000 cows. We next present data implicating causative genes and variants for these QTL. Fine mapping of these regions using imputed, whole genome sequence-resolution genotypes reveals protein-coding candidate causative variants affecting the ABCG2, DGAT1, STAT5B, KCNH4, NPFFR2 and RNF214 genes. Eleven of the remaining QTL appear to be driven by regulatory effects, suggested by the presence of co-locating, co-segregating eQTL discovered using mammary RNA sequence data from a population of 357 lactating cows. Pathway analysis of genes representing all lactose-associated loci shows significant enrichment of genes located in the endoplasmic reticulum, with functions related to ion channel activity mediated through the LRRC8C, P2RX4, KCNJ2 and ANKH genes. A number of the validated QTL are also found to be associated with additional milk volume, fat and protein phenotypes. CONCLUSIONS: Overall, these findings highlight novel candidate genes and variants involved in milk lactose regulation, whose impacts on membrane transport mechanisms reinforce the key osmo-regulatory roles of lactose in milk.

HandyCNV: Standardized Summary, Annotation, Comparison, and Visualization of Copy Number Variant, Copy Number Variation Region, and Runs of Homozygosity.

Detection of CNVs (copy number variants) and ROH (runs of homozygosity) from SNP (single nucleotide polymorphism) genotyping data is often required in genomic studies. The post-analysis of CNV and ROH generally involves many steps, potentially across multiple computing platforms, which requires the researchers to be familiar with many different tools. In order to get around this problem and improve research efficiency, we present an R package that integrates the summarization, annotation, map conversion, comparison and visualization functions involved in studies of CNV and ROH. This one-stop post-analysis system is standardized, comprehensive, reproducible, timesaving, and user-friendly for researchers in humans and most diploid livestock species.

Non-additive association analysis using proxy phenotypes identifies novel cattle syndromes.

Mammalian species carry ~100 loss-of-function variants per individual1,2, where ~1-5 of these impact essential genes and cause embryonic lethality or severe disease when homozygous3. The functions of the remainder are more difficult to resolve, although the assumption is that these variants impact fitness in less manifest ways. Here we report one of the largest sequence-resolution screens of cattle to date, targeting discovery and validation of non-additive effects in 130,725 animals. We highlight six novel recessive loci with impacts generally exceeding the largest-effect variants identified from additive genome-wide association studies, presenting analogs of human diseases and hitherto-unrecognized disorders. These loci present compelling missense (PLCD4, MTRF1 and DPF2), premature stop (MUS81) and splice-disrupting (GALNT2 and FGD4) mutations, together explaining substantial proportions of inbreeding depression. These results demonstrate that the frequency distribution of deleterious alleles segregating in selected species can afford sufficient power to directly map novel disorders, presenting selection opportunities to minimize the incidence of genetic disease.