Dent Craig I, Singh Shilpi, Mukherjee Sourav, Mishra Shikhar, Sarwade Rucha D, Shamaya Nawar, Loo Kok Ping, Harrison Paul, Sureshkumar Sridevi, Powell David, Balasubramanian Sureshkumar
School of Biological Sciences, Monash University, VIC 3800, Australia.
Independent Scholar, India.
NAR Genom Bioinform. 2021 May 14;3(2):lqab041. doi: 10.1093/nargab/lqab041. eCollection 2021 Jun.
RNA splicing, and variations in this process referred to as alternative splicing, are critical aspects of gene regulation in eukaryotes. From environmental responses in plants to being a primary link between genetic variation and disease in humans, splicing differences confer extensive phenotypic changes across diverse organisms (1-3). Regulation of splicing occurs through differential selection of splice sites in a splicing reaction, which results in variation in the abundance of isoforms and/or splicing events. However, genomic determinants that influence splice-site selection remain largely unknown. While traditional approaches for analyzing splicing rely on quantifying variant transcripts (i.e. isoforms) or splicing events (i.e. intron retention, exon skipping etc.) (4), recent approaches focus on analyzing complex/mutually exclusive splicing patterns (5-8). However, none of these approaches explicitly measure individual splice-site usage, which can provide valuable information about splice-site choice and its regulation. Here, we present a simple approach to quantify the empirical usage of individual splice sites reflecting their strength, which determines their selection in a splicing reaction. Splice-site strength/usage, as a quantitative phenotype, allows us to directly link genetic variation with usage of individual splice-sites. We demonstrate the power of this approach in defining the genomic determinants of splice-site choice through GWAS. Our pilot analysis with more than a thousand splice sites hints that sequence divergence in rather than is associated with variations in splicing among accessions of . This approach allows deciphering principles of splicing and has broad implications from agriculture to medicine.
RNA剪接以及该过程中被称为可变剪接的变异,是真核生物基因调控的关键方面。从植物对环境的反应到成为人类遗传变异与疾病之间的主要联系,剪接差异在不同生物中带来广泛的表型变化(1 - 3)。剪接的调控通过剪接反应中剪接位点的差异选择来实现,这导致异构体丰度和/或剪接事件的变化。然而,影响剪接位点选择的基因组决定因素在很大程度上仍然未知。虽然传统的剪接分析方法依赖于量化变异转录本(即异构体)或剪接事件(即内含子保留、外显子跳跃等)(4),但最近的方法侧重于分析复杂/相互排斥的剪接模式(5 - 8)。然而,这些方法都没有明确测量单个剪接位点的使用情况,而这可以提供有关剪接位点选择及其调控的有价值信息。在这里,我们提出了一种简单的方法来量化反映单个剪接位点强度的经验使用情况,这种强度决定了它们在剪接反应中的选择。剪接位点强度/使用情况作为一种定量表型,使我们能够直接将遗传变异与单个剪接位点的使用联系起来。我们通过全基因组关联研究(GWAS)证明了这种方法在确定剪接位点选择的基因组决定因素方面的能力。我们对一千多个剪接位点的初步分析表明,[未提及的具体序列]中的序列差异而非[未提及的另一个具体序列]与[未提及的物种名称]不同种质间的剪接变异有关。这种方法有助于解读剪接原理,从农业到医学都有广泛影响。