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Discovery of candidate disease genes in ENU-induced mouse mutants by large-scale sequencing, including a splice-site mutation in nucleoredoxin.

Authors :
Melissa K Boles
Bonney M Wilkinson
Laurens G Wilming
Bin Liu
Frank J Probst
Jennifer Harrow
Darren Grafham
Kathryn E Hentges
Lanette P Woodward
Andrea Maxwell
Karen Mitchell
Michael D Risley
Randy Johnson
Karen Hirschi
James R Lupski
Yosuke Funato
Hiroaki Miki
Pablo Marin-Garcia
Lucy Matthews
Alison J Coffey
Anne Parker
Tim J Hubbard
Jane Rogers
Allan Bradley
David J Adams
Monica J Justice
Source :
PLoS Genetics, Vol 5, Iss 12, p e1000759 (2009)
Publication Year :
2009
Publisher :
Public Library of Science (PLoS), 2009.

Abstract

An accurate and precisely annotated genome assembly is a fundamental requirement for functional genomic analysis. Here, the complete DNA sequence and gene annotation of mouse Chromosome 11 was used to test the efficacy of large-scale sequencing for mutation identification. We re-sequenced the 14,000 annotated exons and boundaries from over 900 genes in 41 recessive mutant mouse lines that were isolated in an N-ethyl-N-nitrosourea (ENU) mutation screen targeted to mouse Chromosome 11. Fifty-nine sequence variants were identified in 55 genes from 31 mutant lines. 39% of the lesions lie in coding sequences and create primarily missense mutations. The other 61% lie in noncoding regions, many of them in highly conserved sequences. A lesion in the perinatal lethal line l11Jus13 alters a consensus splice site of nucleoredoxin (Nxn), inserting 10 amino acids into the resulting protein. We conclude that point mutations can be accurately and sensitively recovered by large-scale sequencing, and that conserved noncoding regions should be included for disease mutation identification. Only seven of the candidate genes we report have been previously targeted by mutation in mice or rats, showing that despite ongoing efforts to functionally annotate genes in the mammalian genome, an enormous gap remains between phenotype and function. Our data show that the classical positional mapping approach of disease mutation identification can be extended to large target regions using high-throughput sequencing.

Subjects

Subjects :
Genetics
QH426-470

Details

Language :
English
ISSN :
15537390 and 15537404
Volume :
5
Issue :
12
Database :
Directory of Open Access Journals
Journal :
PLoS Genetics
Publication Type :
Academic Journal
Accession number :
edsdoj.1a22b98f229e441bb8fc377e6991707a
Document Type :
article
Full Text :
https://doi.org/10.1371/journal.pgen.1000759