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基于模型的剪接信号检测。

Model-based detection of alternative splicing signals.

机构信息

Banting and Best Department of Medical Research, University of Toronto, ON, Canada.

出版信息

Bioinformatics. 2010 Jun 15;26(12):i325-33. doi: 10.1093/bioinformatics/btq200.

DOI:10.1093/bioinformatics/btq200
PMID:20529924
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC2881385/
Abstract

MOTIVATION

Transcripts from approximately 95% of human multi-exon genes are subject to alternative splicing (AS). The growing interest in AS is propelled by its prominent contribution to transcriptome and proteome complexity and the role of aberrant AS in numerous diseases. Recent technological advances enable thousands of exons to be simultaneously profiled across diverse cell types and cellular conditions, but require accurate identification of condition-specific splicing changes. It is necessary to accurately identify such splicing changes to elucidate the underlying regulatory programs or link the splicing changes to specific diseases.

RESULTS

We present a probabilistic model tailored for high-throughput AS data, where observed isoform levels are explained as combinations of condition-specific AS signals. According to our formulation, given an AS dataset our tasks are to detect common signals in the data and identify the exons relevant to each signal. Our model can incorporate prior knowledge about underlying AS signals, measurement quality and gene expression level effects. Using a large-scale multi-tissue AS dataset, we demonstrate the advantage of our method over standard alternative approaches. In addition, we describe newly found tissue-specific AS signals which were verified experimentally, and discuss associated regulatory features.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

摘要

动机

约 95%的人类多外显子基因的转录本都受到可变剪接(AS)的影响。AS 越来越受到关注,是因为它对转录组和蛋白质组的复杂性有显著贡献,并且在许多疾病中异常的 AS 也起到了作用。最近的技术进步使我们能够在不同的细胞类型和细胞条件下同时对数千个外显子进行分析,但需要准确识别特定条件下的剪接变化。准确识别这些剪接变化对于阐明潜在的调控程序或将剪接变化与特定疾病联系起来是必要的。

结果

我们提出了一个针对高通量 AS 数据的概率模型,其中观察到的异构体水平被解释为条件特异性 AS 信号的组合。根据我们的公式,给定一个 AS 数据集,我们的任务是检测数据中的常见信号,并识别与每个信号相关的外显子。我们的模型可以结合潜在的 AS 信号、测量质量和基因表达水平效应等先验知识。使用大规模的多组织 AS 数据集,我们证明了我们的方法优于标准的替代方法的优势。此外,我们还描述了新发现的组织特异性 AS 信号,这些信号已通过实验验证,并讨论了相关的调控特征。

补充信息

补充数据可在“Bioinformatics”在线获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/284c/2881385/c347f91d951e/btq200f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/284c/2881385/ce10e078442a/btq200f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/284c/2881385/53bddfc8a80a/btq200f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/284c/2881385/f1d68dd51ee9/btq200f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/284c/2881385/4bcaf21af776/btq200f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/284c/2881385/c347f91d951e/btq200f5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/284c/2881385/ce10e078442a/btq200f1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/284c/2881385/53bddfc8a80a/btq200f2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/284c/2881385/f1d68dd51ee9/btq200f3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/284c/2881385/4bcaf21af776/btq200f4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/284c/2881385/c347f91d951e/btq200f5.jpg

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本文引用的文献

1
Deciphering the splicing code.解读剪接码。
Nature. 2010 May 6;465(7294):53-9. doi: 10.1038/nature09000.
2
Decrypting the genome's alternative messages.解密基因组的其他信息。
Curr Opin Cell Biol. 2009 Jun;21(3):377-86. doi: 10.1016/j.ceb.2009.02.006. Epub 2009 Mar 21.
3
Deep surveying of alternative splicing complexity in the human transcriptome by high-throughput sequencing.通过高通量测序对人类转录组中可变剪接复杂性进行深度研究。
Mol Cell. 2017 Jul 6;67(1):148-161.e5. doi: 10.1016/j.molcel.2017.06.003. Epub 2017 Jun 29.
4
Computational Identification of Tissue-Specific Splicing Regulatory Elements in Human Genes from RNA-Seq Data.从RNA测序数据中对人类基因组织特异性剪接调控元件进行计算识别
PLoS One. 2016 Nov 18;11(11):e0166978. doi: 10.1371/journal.pone.0166978. eCollection 2016.
5
CoSREM: a graph mining algorithm for the discovery of combinatorial splicing regulatory elements.CoSREM:一种用于发现组合剪接调控元件的图挖掘算法。
BMC Bioinformatics. 2015 Sep 4;16:285. doi: 10.1186/s12859-015-0698-6.
6
Identifying splicing regulatory elements with de Bruijn graphs.利用德布鲁因图识别剪接调控元件。
J Comput Biol. 2014 Dec;21(12):880-97. doi: 10.1089/cmb.2014.0183.
7
Identification and characterization of alternative exon usage linked glioblastoma multiforme survival.鉴定和描述与胶质母细胞瘤存活相关的可变外显子使用。
BMC Med Genomics. 2012 Dec 4;5:59. doi: 10.1186/1755-8794-5-59.
8
A generalizable pre-clinical research approach for orphan disease therapy.一种可推广的孤儿病治疗临床前研究方法。
Orphanet J Rare Dis. 2012 Jun 15;7:39. doi: 10.1186/1750-1172-7-39.
9
Deciphering the plant splicing code: experimental and computational approaches for predicting alternative splicing and splicing regulatory elements.破译植物剪接码:预测选择性剪接和剪接调控元件的实验和计算方法。
Front Plant Sci. 2012 Feb 7;3:18. doi: 10.3389/fpls.2012.00018. eCollection 2012.
10
Computational characterization of 3' splice variants in the GFAP isoform family.计算分析 GFAP 同工型家族 3' 剪接变体。
PLoS One. 2012;7(3):e33565. doi: 10.1371/journal.pone.0033565. Epub 2012 Mar 30.
Nat Genet. 2008 Dec;40(12):1413-5. doi: 10.1038/ng.259. Epub 2008 Nov 2.
4
Expression of 24,426 human alternative splicing events and predicted cis regulation in 48 tissues and cell lines.48种组织和细胞系中24,426个人类可变剪接事件的表达及预测的顺式调控
Nat Genet. 2008 Dec;40(12):1416-25. doi: 10.1038/ng.264. Epub 2008 Nov 2.
5
HITS-CLIP yields genome-wide insights into brain alternative RNA processing.HITS-CLIP技术使人们能够在全基因组范围内深入了解大脑中的可变RNA加工过程。
Nature. 2008 Nov 27;456(7221):464-9. doi: 10.1038/nature07488. Epub 2008 Nov 2.
6
Alternative isoform regulation in human tissue transcriptomes.人类组织转录组中的可变亚型调控
Nature. 2008 Nov 27;456(7221):470-6. doi: 10.1038/nature07509.
7
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Genes Dev. 2008 Sep 15;22(18):2550-63. doi: 10.1101/gad.1703108.
8
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Adv Exp Med Biol. 2007;623:175-89. doi: 10.1007/978-0-387-77374-2_11.
9
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10
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