Identification of structural variation in mouse genomes.

Binnaz Yalcin,David J. Adams,Alexandre Reymond,Jonathan Flint,Kim Wong,Thomas M. Keane

doi:10.3389/fgene.2014.00192

Abstract

Structural variation is variation in structure of DNA regions affecting DNA sequence length and/or orientation. It generally includes deletions, insertions, copy-number gains, inversions, and transposable elements. Traditionally, the identification of structural variation in genomes has been challenging. However, with the recent advances in high-throughput DNA sequencing and paired-end mapping (PEM) methods, the ability to identify structural variation and their respective association to human diseases has improved considerably. In this review, we describe our current knowledge of structural variation in the mouse, one of the prime model systems for studying human diseases and mammalian biology. We further present the evolutionary implications of structural variation on transposable elements. We conclude with future directions on the study of structural variation in mouse genomes that will increase our understanding of molecular architecture and functional consequences of structural variation.

Highlights

Structural variation (SV) is generally considered as rearrangements of DNA regions affecting DNA sequence length and/or orientation in the genome of one species, and includes deletions, insertions, copy-number gains, inversions, and transposable elements
Results presented in this review suggest that, given the abundance of structural variants in mouse genomes, SVs make less of a contribution to individual phenotypic variation than single-nucleotide polymorphisms (SNPs)
FUTURE WORK AND CONCLUDING REMARKS The current approaches for cataloging mutations are primarily based on aligning sequencing reads to the appropriate reference genome to identify SNPs, indels, and structural variations

Summary

Introduction

INTRODUCTION Structural variation (SV) is generally considered as rearrangements of DNA regions affecting DNA sequence length and/or orientation in the genome of one species, and includes deletions, insertions, copy-number gains, inversions, and transposable elements. DETECTION OF STRUCTURAL VARIANTS USING PAIRED-END MAPPING METHODS While most deep-sequencing applications focus on the identification of single-nucleotide polymorphisms (SNPs) or small insertion deletion polymorphisms, structural variation can be identified from the same data.

Results

Conclusion