Next generation sequencing technology and genomewide data analysis: Perspectives for retinal research

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• 作者：Vijender Chaitankar¹ ; ² ; Gö ; khan Karakü ; lah¹ ; ² ; Rinki Ratnapriya¹ ; ² ; Felipe O. Giuste² ; Matthew J. Brooks² ; Anand Swaroop ; ² ; ^{swaroopa@nei.nih.gov" class="auth_mail" title="E-mail the corresponding author}
• 关键词：ChIP-seq ; Chromatin ; Epigenetics ; Gene regulatory network ; Genomics ; High throughput data ; Network analysis ; Photoreceptor ; Retina ; Retinal disease ; RNA-Seq ; Systems biology ; Transcriptome ; Vision ; Whole exome sequencing ; Whole genome sequencing ; NGS data integration
• 刊名：Progress in Retinal and Eye Research
• 出版年：2016
• 出版时间：November 2016
• 年：2016
• 卷：55
• 期：Complete
• 页码：1-31
• 全文大小：2515 K

文摘

The advent of high throughput next generation sequencing (NGS) has accelerated the pace of discovery of disease-associated genetic variants and genomewide profiling of expressed sequences and epigenetic marks, thereby permitting systems-based analyses of ocular development and disease. Rapid evolution of NGS and associated methodologies presents significant challenges in acquisition, management, and analysis of large data sets and for extracting biologically or clinically relevant information. Here we illustrate the basic design of commonly used NGS-based methods, specifically whole exome sequencing, transcriptome, and epigenome profiling, and provide recommendations for data analyses. We briefly discuss systems biology approaches for integrating multiple data sets to elucidate gene regulatory or disease networks. While we provide examples from the retina, the NGS guidelines reviewed here are applicable to other tissues/cell types as well.