Suppr超能文献

来自牛组织的变异调用中的 RNA-DNA 差异导致错误的 eQTLs。

RNA-DNA differences in variant calls from cattle tissues result in erroneous eQTLs.

机构信息

Animal Genomics, ETH Zurich, Universitaetstrasse 2, Zurich, 8092, Switzerland.

出版信息

BMC Genomics. 2024 Aug 1;25(1):750. doi: 10.1186/s12864-024-10645-z.

Abstract

BACKGROUND

Association testing between molecular phenotypes and genomic variants can help to understand how genotype affects phenotype. RNA sequencing provides access to molecular phenotypes such as gene expression and alternative splicing while DNA sequencing or microarray genotyping are the prevailing options to obtain genomic variants.

RESULTS

We genotype variants for 74 male Braunvieh cattle from both DNA (~ 13-fold coverage) and deep total RNA sequencing from testis, vas deferens, and epididymis tissue (~ 250 million reads per tissue). We show that RNA sequencing can be used to identify approximately 40% of variants (7-10 million) called from DNA sequencing, with over 80% precision. Within highly expressed coding regions, over 92% of expected variants were called with nearly 98% precision. Allele-specific expression and putative post-transcriptional modifications negatively impact variant genotyping accuracy from RNA sequencing and contribute to RNA-DNA differences. Variants called from RNA sequencing detect roughly 75% of eGenes identified using variants called from DNA sequencing, demonstrating a nearly 2-fold enrichment of eQTL variants. We observe a moderate-to-strong correlation in nominal association p-values (Spearman ρ ~ 0.6), although only 9% of eGenes have the same top associated variant.

CONCLUSIONS

We find hundreds of thousands of RNA-DNA differences in variants called from RNA and DNA sequencing on the same individuals. We identify several highly significant eQTL when using RNA sequencing variant genotypes which are not found with DNA sequencing variant genotypes, suggesting that using RNA sequencing variant genotypes for association testing results in an increased number of false positives. Our findings demonstrate that caution must be exercised beyond filtering for variant quality or imputation accuracy when analysing or imputing variants called from RNA sequencing.

摘要

背景

分子表型与基因组变异之间的关联分析有助于了解基因型如何影响表型。RNA 测序可提供基因表达和选择性剪接等分子表型,而 DNA 测序或微阵列基因分型是获取基因组变异的主要选择。

结果

我们对来自 74 头公牛的 DNA(13 倍覆盖)和睾丸、输精管和附睾组织的深度总 RNA 测序(每个组织约 2.5 亿条读数)中的变体进行了基因分型。我们表明,RNA 测序可用于鉴定约 40%的来自 DNA 测序的变体(700 万至 1000 万),准确率超过 80%。在高表达的编码区中,超过 92%的预期变异具有近 98%的精度。等位基因特异性表达和潜在的转录后修饰会对 RNA 测序的变体基因分型精度产生负面影响,并导致 RNA-DNA 差异。从 RNA 测序中鉴定的变体大致可检测到 75%使用 DNA 测序鉴定的变体所识别的 eGenes,表明 eQTL 变体富集近 2 倍。我们观察到名义关联 p 值(Spearman ρ0.6)具有中度至强相关性,尽管只有 9%的 eGenes具有相同的顶级关联变体。

结论

我们在同一个体的 RNA 和 DNA 测序中鉴定出数十万的 RNA-DNA 差异。我们发现,使用 RNA 测序变体基因型进行关联分析时,有几个高度显著的 eQTL 并未在 DNA 测序变体基因型中发现,这表明使用 RNA 测序变体基因型进行关联分析会导致假阳性数量增加。我们的研究结果表明,在分析或推断 RNA 测序鉴定的变体时,除了过滤变体质量或推断准确性外,还必须谨慎。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验