导致组蛋白修饰 ChIP-seq 峰高的等位基因特异性结合变体在表达 QTL 注释中并不富集

IF 3.6 1区 农林科学 Q1 AGRICULTURE, DAIRY & ANIMAL SCIENCE
Mohammad Ghoreishifar, Amanda J. Chamberlain, Ruidong Xiang, Claire P. Prowse-Wilkins, Thomas J. Lopdell, Mathew D. Littlejohn, Jennie E. Pryce, Michael E. Goddard
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引用次数: 0

摘要

影响复杂性状(数量性状位点,QTL)的基因组序列变异富集在基因组的功能区域,如那些以某些组蛋白修饰为标志的区域。这些变异被认为会影响基因表达。然而,由于附近变体之间存在连锁不平衡,精确定位 QTL 具有挑战性。我们的目标是鉴定导致组蛋白修饰水平变异的等位基因特异性结合(ASB)QTL(asbQTL),组蛋白修饰水平是通过 ChIP-seq(染色质免疫沉淀测序)测定的峰高来衡量的。我们确定了能预测奶牛乳腺中 H3K4me3 和 H3K27ac 组蛋白修饰 ChIP-seq 峰高等位基因差异的 DNA 序列。我们使用了间隙 k-mer 支持向量机、新型最佳线性无偏预测模型以及结合了其他两种方法的多元线性回归模型来预测变异对峰高的影响。每种方法都将预测 ASB 值最高的 1000 个位点子集视为候选 asbQTL。这种预测的准确性是通过预测方向与观测方向相吻合的比例来衡量的。预测准确率介于 0.59 和 0.74 之间,表明这 1000 个位点富含 asbQTL。利用独立数据,我们调查了候选asbQTL集和三个对照组的功能富集情况,包括非因果关系的ASB位点、峰值下的非ASB变异和非峰值下的SNP(单核苷酸多态性)。就 H3K4me3 而言,与非因果关系的 ASB 位点相比,候选 asbQTL 被确认为 ASB 的比例更高(P 0.05)。我们利用这些位点周围的 DNA 序列确定了 asbQTL 的假定因果位点。我们的结果表明,许多影响组蛋白修饰的位点可能不会直接影响基因表达。然而,必须承认的是,由于统计能力的限制,区分假定的因果ASB位点和与因果位点高度连锁不平衡的其他非因果ASB位点对基因表达的影响可能具有挑战性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Allele-specific binding variants causing ChIP-seq peak height of histone modification are not enriched in expression QTL annotations
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. 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). 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.
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来源期刊
Genetics Selection Evolution
Genetics Selection Evolution 生物-奶制品与动物科学
CiteScore
6.50
自引率
9.80%
发文量
74
审稿时长
1 months
期刊介绍: Genetics Selection Evolution invites basic, applied and methodological content that will aid the current understanding and the utilization of genetic variability in domestic animal species. Although the focus is on domestic animal species, research on other species is invited if it contributes to the understanding of the use of genetic variability in domestic animals. Genetics Selection Evolution publishes results from all levels of study, from the gene to the quantitative trait, from the individual to the population, the breed or the species. Contributions concerning both the biological approach, from molecular genetics to quantitative genetics, as well as the mathematical approach, from population genetics to statistics, are welcome. Specific areas of interest include but are not limited to: gene and QTL identification, mapping and characterization, analysis of new phenotypes, high-throughput SNP data analysis, functional genomics, cytogenetics, genetic diversity of populations and breeds, genetic evaluation, applied and experimental selection, genomic selection, selection efficiency, and statistical methodology for the genetic analysis of phenotypes with quantitative and mixed inheritance.
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