Analysis of transcriptome complexity through RNA sequencing in normal and failing murine hearts.
Analysis of transcriptome complexity through RNA sequencing in normal and failing murine hearts.
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通过在正常和失败的鼠心中进行RNA测序分析转录组复杂性。
DOI：
10.1161/circresaha.111.249433
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发表时间：
2011-12-09
影响因子：
20.1
通讯作者：
Xiao X
中科院分区：
文献类型：
--
作者：
Lee JH;Gao C;Peng G;Greer C;Ren S;Wang Y;Xiao X
准确和全面的心脏从头转录组分析是更好地了解心脏生理和疾病的核心问题。虽然已经取得了显着的进展，在心脏基因表达的定量变化的全基因组分析，目前的知识提供了有限的见解，在心脏转录组在单个外显子水平的总复杂性。开发更强大的生物信息学方法来分析高通量RNA测序（RNA-Seq）数据，重点是在单个外显子和转录水平上研究转录组的复杂性。除了总体基因表达分析之外，本研究中开发的方法用于分析关于个体转录物同种型、新剪接外显子、新替代末端外显子、新转录物簇（即，新基因）和长非编码RNA基因。我们将这些方法应用于从经主动脉缩窄诱导的压力超负荷后的小鼠心脏获得的RNA-Seq数据。基于实验验证，分析所识别的外显子/转录本的特征，以及包括先前发表的RNASeq数据的表达分析，我们证明了该方法在检测和定量单个外显子和转录本方面是非常有效的。从心脏转录组的检查方面推断的新见解为进一步的实验研究开辟了道路。我们的工作提供了一套全面的方法来分析小鼠心脏转录组的复杂性在个别外显子和转录水平。这些方法的应用可能会推断出重要的新见解，在正常和疾病的心脏基因调控的外显子利用和潜在的参与心脏转录组的新组件。
Accurate and comprehensive de novo transcriptome profiling in heart is a central issue to better understand cardiac physiology and diseases. Although significant progress has been made in genome-wide profiling for quantitative changes in cardiac gene expression, current knowledge offers limited insights to the total complexity in cardiac transcriptome at individual exon level. To develop more robust bioinformatic approaches to analyze high-throughput RNA sequencing (RNA-Seq) data, with the focus on the investigation of transcriptome complexity at individual exon and transcript levels. In addition to overall gene expression analysis, the methods developed in this study were used to analyze RNA-Seq data with respect to individual transcript isoforms, novel spliced exons, novel alternative terminal exons, novel transcript clusters (i.e., novel genes) and long non-coding RNA genes. We applied these approaches to RNA-Seq data obtained from mouse hearts following pressure-overload induced by trans-aortic constriction. Based on experimental validations, analyses of the features of the identified exons/transcripts, and expression analyses including previously published RNASeq data, we demonstrate that the methods are highly effective in detecting and quantifying individual exons and transcripts. Novel insights inferred from the examined aspects of the cardiac transcriptome open ways to further experimental investigations. Our work provided a comprehensive set of methods to analyze mouse cardiac transcriptome complexity at individual exon and transcript levels. Applications of the methods may infer important new insights to gene regulation in normal and disease hearts in terms of exon utilization and potential involvement of novel components of cardiac transcriptome.