High-throughput annotation of full-length long noncoding RNAs with capture long-read sequencing

生物 计算生物学 注释 基因注释 深度测序 长非编码RNA 基因 遗传学 基因组学 DNA测序 RNA剪接 核糖核酸 基因组
作者
Julien Lagarde,Barbara Uszczyńska-Ratajczak,Silvia Carbonell‐Morote,Sílvia Pérez-Lluch,Amaya Abad,Carrie Davis,T Gingeras,Adam Frankish,Jennifer Harrow,Roderic Guigó,Rory Johnson
出处
期刊:Nature Genetics [Nature Portfolio]
卷期号:49 (12): 1731-1740 被引量:291
标识
DOI:10.1038/ng.3988
摘要

RNA Capture Long Seq (CLS) is a new method for transcript annotation that combines targeted RNA capture with long-read sequencing. CLS reannotates GENCODE lncRNAs and increases the number of validated splice junctions and transcript models for targeted loci. Accurate annotation of genes and their transcripts is a foundation of genomics, but currently no annotation technique combines throughput and accuracy. As a result, reference gene collections remain incomplete—many gene models are fragmentary, and thousands more remain uncataloged, particularly for long noncoding RNAs (lncRNAs). To accelerate lncRNA annotation, the GENCODE consortium has developed RNA Capture Long Seq (CLS), which combines targeted RNA capture with third-generation long-read sequencing. Here we present an experimental reannotation of the GENCODE intergenic lncRNA populations in matched human and mouse tissues that resulted in novel transcript models for 3,574 and 561 gene loci, respectively. CLS approximately doubled the annotated complexity of targeted loci, outperforming existing short-read techniques. Full-length transcript models produced by CLS enabled us to definitively characterize the genomic features of lncRNAs, including promoter and gene structure, and protein-coding potential. Thus, CLS removes a long-standing bottleneck in transcriptome annotation and generates manual-quality full-length transcript models at high-throughput scales.
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