Analysis of differential gene expression and alternative splicing is significantly influenced by choice of reference genome
Analysis of differential gene expression and alternative splicing is significantly influenced by choice of reference genome
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DOI：
10.1261/rna.070227.118
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发表时间：
2019-03
期刊：
影响因子：
4.5
通讯作者：
Erin Slabaugh;Jigar S. Desai;Ryan C. Sartor;L. M. F. Lawas;S. K. Jagadish;Colleen J. Doherty
中科院分区：
文献类型：
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作者：
Erin Slabaugh;Jigar S. Desai;Ryan C. Sartor;L. M. F. Lawas;S. K. Jagadish;Colleen J. Doherty
RNA-seq 分析已经能够评估包括非模式生物在内的许多物种的转录变化。然而，在大多数物种中，只有一个参考基因组可用，并且来自高度差异品种的 RNA-seq 读数通常与该参考基因组对齐。在这里，我们量化了水稻基因组作图选择的影响，其中可以获得三个高质量的参考基因组。我们将一种流行的高产水稻品种的 RNA-seq 数据与三个不同的参考基因组进行比对，发现差异表达基因的识别因用于作图的参考基因组而异。此外，检测差异使用转录亚型的能力受到参考基因组选择的深刻影响：当读数映射到更常用但相关性更远的参考基因组时，只有 30% 的差异使用剪接特征被检测到。这表明基因表达和剪接分析根据作图参考基因组的不同而有很大差异，并且可以通过获取新的基因组参考材料来改进对与可用参考基因组关系较远的个体的分析。我们观察到转录组分析中的这些差异部分是由于测序个体和每个参考基因组之间存在单核苷酸多态性，以及参考基因组之间甚至存在同线性直向同源物之间的注释差异。我们的结论是，即使在质量相似的两个密切相关的基因组之间，使用与采样物种最密切相关的参考基因组也可以显着改善转录组分析。
RNA-seq analysis has enabled the evaluation of transcriptional changes in many species including nonmodel organisms. However, in most species only a single reference genome is available and RNA-seq reads from highly divergent varieties are typically aligned to this reference. Here, we quantify the impacts of the choice of mapping genome in rice where three high-quality reference genomes are available. We aligned RNA-seq data from a popular productive rice variety to three different reference genomes and found that the identification of differentially expressed genes differed depending on which reference genome was used for mapping. Furthermore, the ability to detect differentially used transcript isoforms was profoundly affected by the choice of reference genome: Only 30% of the differentially used splicing features were detected when reads were mapped to the more commonly used, but more distantly related reference genome. This demonstrated that gene expression and splicing analysis varies considerably depending on the mapping reference genome, and that analysis of individuals that are distantly related to an available reference genome may be improved by acquisition of new genomic reference material. We observed that these differences in transcriptome analysis are, in part, due to the presence of single nucleotide polymorphisms between the sequenced individual and each respective reference genome, as well as annotation differences between the reference genomes that exist even between syntenic orthologs. We conclude that even between two closely related genomes of similar quality, using the reference genome that is most closely related to the species being sampled significantly improves transcriptome analysis.