SLIDR and SLOPPR: flexible identification of spliced leader trans-splicing and prediction of eukaryotic operons from RNA-Seq data.
SLIDR and SLOPPR: flexible identification of spliced leader trans-splicing and prediction of eukaryotic operons from RNA-Seq data.
复制标题
DOI：
10.1186/s12859-021-04009-7
复制
发表时间：
2021-03-22
影响因子：
3
通讯作者：
Pettitt J
中科院分区：
文献类型：
--
作者：
Wenzel MA;Müller B;Pettitt J
剪接前导序列（SL）反式剪接用剪接前导序列取代前体mRNA的5′端，剪接前导序列是源自基因组其他地方的专门非编码RNA的外显子。该过程对于将由真核操纵子产生的多顺反子前mRNA解析成单顺反子转录物是必需的。SL反式剪接和操纵子可能在整个真核生物中独立进化了多次，但我们对这些现象的理解仅限于少数几个特征明确的生物体，最值得注意的是C。线虫和锥虫。SL反式剪接和操纵子的系统发现和表征的主要障碍是缺乏用于利用广泛的真核生物的转录组和基因组资源激增的计算工具。在这里，我们提出了两个新的管道，自动发现SL和预测操纵子在真核基因组中的RNA-Seq数据。SLIDR从与参考基因组或转录组进行读段比对后存在的5′读段尾组装推定的SL，然后通过询问相应的SL RNA基因以获得真正SL RNA分子中预期的序列基序来验证。SLOPPR识别包含给定5′ SL序列的RNA-Seq读段，量化全基因组SL反式剪接事件，并通过相邻基因间SL反式剪接事件的不同模式预测操纵子。我们用已知进行SL反式剪接并将其基因组织成操纵子的生物体测试了这两种管道，并证明（1）SLIDR正确检测预期的SL并经常发现新的SL变体;（2）SLOPPR正确识别功能专门化的SL，正确预测已知的操纵子并检测可能的新操纵子。SLIDR和SLOPPR是灵活的工具，将加速研究整个真核生物的SL反式剪接和操纵子的进化动力学，并改善基因发现和注释的广泛的真核生物基因组。这两个管道都是在Bash和R中实现的，并且构建在大多数生物信息学服务器上通常安装的现成软件上。甚至可以从稀疏、低覆盖率的数据集中收集生物学见解，这意味着可以从现有的RNA-Seq数据集以及新的全亚型测序方案中检索到大量未开发的信息，因为它们变得更广泛可用。在线版本包含补充材料，可通过10.1186/s12859-021-04009-7获得。
Spliced leader (SL) trans-splicing replaces the 5′ end of pre-mRNAs with the spliced leader, an exon derived from a specialised non-coding RNA originating from elsewhere in the genome. This process is essential for resolving polycistronic pre-mRNAs produced by eukaryotic operons into monocistronic transcripts. SL trans-splicing and operons may have independently evolved multiple times throughout Eukarya, yet our understanding of these phenomena is limited to only a few well-characterised organisms, most notably C. elegans and trypanosomes. The primary barrier to systematic discovery and characterisation of SL trans-splicing and operons is the lack of computational tools for exploiting the surge of transcriptomic and genomic resources for a wide range of eukaryotes. Here we present two novel pipelines that automate the discovery of SLs and the prediction of operons in eukaryotic genomes from RNA-Seq data. SLIDR assembles putative SLs from 5′ read tails present after read alignment to a reference genome or transcriptome, which are then verified by interrogating corresponding SL RNA genes for sequence motifs expected in bona fide SL RNA molecules. SLOPPR identifies RNA-Seq reads that contain a given 5′ SL sequence, quantifies genome-wide SL trans-splicing events and predicts operons via distinct patterns of SL trans-splicing events across adjacent genes. We tested both pipelines with organisms known to carry out SL trans-splicing and organise their genes into operons, and demonstrate that (1) SLIDR correctly detects expected SLs and often discovers novel SL variants; (2) SLOPPR correctly identifies functionally specialised SLs, correctly predicts known operons and detects plausible novel operons. SLIDR and SLOPPR are flexible tools that will accelerate research into the evolutionary dynamics of SL trans-splicing and operons throughout Eukarya and improve gene discovery and annotation for a wide range of eukaryotic genomes. Both pipelines are implemented in Bash and R and are built upon readily available software commonly installed on most bioinformatics servers. Biological insight can be gleaned even from sparse, low-coverage datasets, implying that an untapped wealth of information can be retrieved from existing RNA-Seq datasets as well as from novel full-isoform sequencing protocols as they become more widely available. The online version contains supplementary material available at 10.1186/s12859-021-04009-7.
登录
查看更多内容
影响因子：
10.7
作者：
Danks, Gemma B.;Raasholm, Martina;Thompson, Eric M.
通讯作者：
Thompson, Eric M.
影响因子：
14.9
作者：
Hansen KD;Brenner SE;Dudoit S
通讯作者：
Dudoit S
DOI：
10.1093/bioinformatics/bts565
发表时间：
2012-12-01
期刊：
Bioinformatics (Oxford, England)
影响因子：
--
作者：
Fu L;Niu B;Zhu Z;Wu S;Li W
通讯作者：
Li W
影响因子：
4.5
作者：
Guiliano DB;Blaxter ML
通讯作者：
Blaxter ML
影响因子：
4.3
作者：
Dahlgren AR;Scott EY;Mansour T;Hales EN;Ross PJ;Kalbfleisch TS;MacLeod JN;Petersen JL;Bellone RR;Finno CJ
通讯作者：
Finno CJ