Next-generation sequencing: impact of exome sequencing in characterizing Mendelian disorders

Next-generation sequencing: impact of exome sequencing in characterizing Mendelian disorders
http://www.nature.com/jhg/journal/v57/n10/full/jhg201291a.html

Traditional approaches for gene mapping from candidate gene studies to positional cloning strategies have been applied for Mendelian disorders. Since 2005, next-generation sequencing (NGS) technologies are improving as rapid, high-throughput and cost-effective approaches to fulfill medical sciences and research demands. Using NGS, the underlying causative genes are directly distinguished via a systematic filtering, in which the identified gene variants are checked for novelty and functionality. During the past 2 years, the role of more than 100 genes has been distinguished in rare Mendelian disorders by means of whole-exome sequencing (WES). Combination of WES with traditional approaches, consistent with linkage analysis, has had the greatest impact on those disorders following autosomal mode of inheritance; in more than 60 identified genes, the causal variants have been transmitted at homozygous or compound heterozygous state. Recent literatures focusing on identified new causal genes in Mendelian disorders using WES are reviewed in the present survey.

Keywords: exome sequencing; mendelian disorder; mutation; next-generation sequencing; NGS; WES

Computational and statistical approaches to analyzing variants identified by exome sequencing

http://genomebiology.com/2011/12/9/227

New sequencing technology has enabled the identification of thousands of single nucleotide polymorphisms in the exome, and many computational and statistical approaches to identify disease-association signals have emerged.

 

Consensus Rules in Variant Detection from Next-Generation Sequencing Data

http://www.plosone.org/article/info:doi/10.1371/journal.pone.0038470#s4
A critical step in detecting variants from next-generation sequencing data ispost hoc filtering of putative variants called or predicted by computational tools. Here, we highlight four critical parameters that could enhance the accuracy of called single nucleotide variants and insertions/deletions: quality and deepness, refinement and improvement of initial mapping, allele/strand balance, and examination of spurious genes. Use of these sequence features appropriately in variant filtering could greatly improve validation rates, thereby saving time and costs in next-generation sequencing projects.