School of Veterinary Science, The University of Queensland, Gatton Campus, QLD 4343, Australia.
J Anim Sci. 2012 Sep;90(9):2894-906. doi: 10.2527/jas.2011-4601. Epub 2012 Jun 27.
Measures of heifer fertility are economically relevant traits for beef production systems and knowledge of candidate genes could be incorporated into future genomic selection strategies. Ten traits related to growth and fertility were measured in 890 Brangus heifers (3/8 Brahman × 5/8 Angus, from 67 sires). These traits were: BW and hip height adjusted to 205 and 365 d of age, postweaning ADG, yearling assessment of carcass traits (i.e., back fat thickness, intramuscular fat, and LM area), as well as heifer pregnancy and first service conception (FSC). These fertility traits were collected from controlled breeding seasons initiated with estrous synchronization and AI targeting heifers to calve by 24 mo of age. The BovineSNP50 BeadChip was used to ascertain 53,692 SNP genotypes for ∼802 heifers. Associations of genotypes and phenotypes were performed and SNP effects were estimated for each trait. Minimally associated SNP (P < 0.05) and their effects across the 10 traits formed the basis for an association weight matrix and its derived gene network related to FSC (57.3% success and heritability = 0.06 ± 0.05). These analyses yielded 1,555 important SNP, which inferred genes linked by 113,873 correlations within a network. Specifically, 1,386 SNP were nodes and the 5,132 strongest correlations (|r| ≥ 0.90) were edges. The network was filtered with genes queried from a transcriptome resource created from deep sequencing of RNA (i.e., RNA-Seq) from the hypothalamus of a prepubertal and a postpubertal Brangus heifer. The remaining hypothalamic-influenced network contained 978 genes connected by 2,560 edges or predicted gene interactions. This hypothalamic gene network was enriched with genes involved in axon guidance, which is a pathway known to influence pulsatile release of LHRH. There were 5 transcription factors with 21 or more connections: ZMAT3, STAT6, RFX4, PLAGL1, and NR6A1 for FSC. The SNP that identified these genes were intragenic and were on chromosomes 1, 5, 9, and 11. Chromosome 5 harbored both STAT6 and RFX4. The large number of interactions and genes observed with network analyses of multiple sources of genomic data (i.e., GWAS and RNA-Seq) support the concept of FSC being a polygenic trait.
奶牛繁殖力是肉牛生产系统中具有经济意义的重要特征，了解候选基因可为未来的基因组选择策略提供信息。本研究在 890 头布郎格斯小母牛（3/8 婆罗门牛×5/8 安格斯牛，来自 67 头公牛）中测量了与生长和繁殖力相关的 10 个性状。这些性状包括：调整至 205 和 365 日龄的体重和臀部高度、断奶后日增重、育成牛体躯性状评估（即背膘厚、肌间脂肪和 LM 面积）以及小母牛妊娠和首次输精受胎率（FSC）。这些繁殖力性状是在发情同步和人工授精控制配种季节中收集的，目标是使小母牛在 24 月龄前产犊。利用 BovineSNP50 BeadChip 对大约 802 头小母牛的 53692 个 SNP 基因型进行了测定。对基因型和表型进行了关联分析，并估计了每个性状的 SNP 效应。最小关联 SNP（P<0.05）及其在 10 个性状上的效应构成了关联权重矩阵及其与 FSC 相关的基因网络的基础（成功率为 57.3%，遗传力=0.06±0.05）。这些分析得到了 1555 个重要 SNP，这些 SNP 推断出的基因通过网络内的 113873 个相关性连接。具体来说，有 1386 个 SNP 是节点，5132 个最强的相关性（|r|≥0.90）是边缘。利用来自青春期前和青春期后布郎格斯小母牛下丘脑深度测序的 RNA 转录组资源（即 RNA-Seq）查询基因，对网络进行了过滤。剩余的受下丘脑影响的网络包含 978 个基因，由 2560 个边缘或预测的基因相互作用连接。该下丘脑基因网络富含参与轴突导向的基因，这是已知影响 LHRL 脉冲释放的途径。有 5 个转录因子有 21 个或更多的连接：FSC 中的 ZMAT3、STAT6、RFX4、PLAGL1 和 NR6A1。确定这些基因的 SNP 是基因内 SNP，位于 1、5、9 和 11 号染色体上。5 号染色体上同时存在 STAT6 和 RFX4。大量的相互作用和基因观察到的网络分析多个来源的基因组数据（即 GWAS 和 RNA-Seq）支持 FSC 是一个多基因性状的概念。
