Multiple QTL underlie milk phenotypes at the CSF2RB locus

Abstract

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.

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

“…Multiple protein-coding mutations could be attributed to loci with QTL in both wavenumber and milk composition traits, highlighting genes that appear to be novel to the present study (TGDS and DNAJB13), and genes previously reported in other studies of milk composition traits: GBA [37,65], MTX1 [66], SLC50A1 [36,67], CSF2RB [66,68,69], NCF4 [66,69], TBC1D22A [70], MROH1 [71] and MTARC1 [36]. A number of other QTL that were in strong LD with a PIV were observed in FT-MIR wavenumbers, but not in the FT-MIR predicted milk composition traits.…”

“…Other wavenumber QTL where a co-localized eQTL was identified within FT-MIR wavenumbers, but not the predicted milk composition traits, included effects that highlighted a number of genes that appear novel to the present study: CLDN8, CSTB, TAB2, LAPTM4A, CAPN5, PMP22, HID1 and THRB; and a number of genes previously reported as having an effect on bovine milk composition: SLC37A1 [66,86], NCF4 [66,69], SLC34A2 [87], TENT5A [40], RNF217 [67], MPC1 [85], XDH [88,89], PAEP [60], DGAT1 [56], RGL1 [90], LTF [91,92] and MUS81 [93]. These results underscore the gain in power that is available when using individual FT-MIR wavenumber phenotypes, compared to using predicted milk composition phenotypes which are linear functions of FT-MIR absorbance values.…”

“…Genes corresponding to these effects have previously been published in other studies of bovine milk composition: SH3BP5 [36], SLC50A1 [36,67], USP3 [81,82], IVNS1ABP [36], KCJN2 [36], ANKH [36,71], GPAT4 [83,84] and PICALM [36,71]. Other cases for which the wavenumber QTL was in high LD ( R 2 > 0.9) with the top eQTL variant, highlighted genes previously published in other studies of bovine milk composition: LRRC8C [36], CSF2RB [66,68,69], MGST1 [35,70], CSN3 [65,71], ABO [73,74], GHDC [36,66] and LMAN1 [70,85]; and genes that appear to be novel to the present study: KRTCAP2 and FA2H. Pearson correlations between log-scaled p-values for the trait and expression QTL for the latter two effects were 0.94 and 0.88, respectively, with both displaying very strong LD between the trait QTL and the most highly significant eQTL variant ( R 2 > 0.995).…”