Female fertility is an important trait in dairy cattle. Identifying putative causal variants associated with fertility may help to improve the accuracy of genomic prediction of fertility. Combining expression data (eQTL) of genes, exons, gene splicing and allele specific expression is a promising approach to fine map QTL to get closer to the causal mutations. Another approach is to identify genomic differences between cows selected for high and low fertility and a selection experiment in New Zealand has created exactly this resource. Our objective was to combine multiple types of expression data, fertility traits and allele frequency in high- (POS) and low-fertility (NEG) cows with a genome-wide association study (GWAS) on calving interval in Australian cows to fine-map QTL associated with fertility in both Australia and New Zealand dairy cattle populations. Variants that were significantly associated with calving interval (CI) were strongly enriched for variants associated with gene, exon, gene splicing and allele-specific expression, indicating that there is substantial overlap between QTL associated with CI and eQTL. We identified 671 genes with significant differential expression between POS and NEG cows, with the largest fold change detected for the CCDC196 gene on chromosome 10. Our results provide numerous candidate genes associated with female fertility in dairy cattle, including GYS2 and TIGAR on chromosome 5 and SYT3 and HSD17B14 on chromosome 18. Multiple QTL regions were located in regions with large numbers of copy number variants (CNV). To identify the causal mutations for these variants, long read sequencing may be useful. Variants that were significantly associated with CI were highly enriched for eQTL. We detected 671 genes that were differentially expressed between POS and NEG cows. Several QTL detected for CI overlapped with eQTL, providing candidate genes for fertility in dairy cattle.

中文翻译：

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使用表达数据精细绘制与奶牛生育力相关的 QTL


雌性生育力是奶牛的一个重要性状。识别与生育力相关的假定因果变异可能有助于提高生育力基因组预测的准确性。结合基因、外显子、基因剪接和等位基因特异性表达的表达数据 (eQTL) 是精细绘制 QTL 图谱以更接近因果突变的有前途的方法。另一种方法是确定高生育力和低生育力奶牛之间的基因组差异，新西兰的一项选择实验恰恰创造了这种资源。我们的目标是将高生育力 (POS) 和低生育力 (NEG) 奶牛的多种类型的表达数据、生育性状和等位基因频率与澳大利亚奶牛产犊间隔的全基因组关联研究 (GWAS) 相结合，以绘制精细图谱QTL 与澳大利亚和新西兰奶牛种群的生育力相关。与产犊间隔（CI）显着相关的变异在与基因、外显子、基因剪接和等位基因特异性表达相关的变异中强烈富集，表明与CI相关的QTL和eQTL之间存在实质性重叠。我们鉴定了 671 个在 POS 和 NEG 奶牛之间具有显着表达差异的基因，其中在 10 号染色体上的 CCDC196 基因检测到最大的倍数变化。我们的结果提供了许多与奶牛雌性生育力相关的候选基因，包括 5 号染色体上的 GYS2 和 TIGAR 以及SYT3和HSD17B14位于18号染色体上。多个QTL区域位于具有大量拷贝数变异(CNV)的区域。为了确定这些变异的因果突变，长读长测序可能有用。与 CI 显着相关的变异体的 eQTL 高度富集。 我们检测到 671 个基因在 POS 和 NEG 奶牛之间存在差异表达。 CI 检测到的几个 QTL 与 eQTL 重叠，为奶牛的生育能力提供了候选基因。