Evidence map›Paper›PMID 22724066›Full record

ArticleOpen biology2012

Massively parallel sequencing of the mouse exome to accurately identify rare, induced mutations: an immediate source for thousands of new mouse models.

T D Andrews, B Whittle, M A Field, B Balakishnan, Y Zhang, Y Shao, V Cho, M Kirk, M Singh, Y Xia and 6 more

Open access · goldAbstract read
In one paragraph

Article in Open biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 62 papers.

0numbers the graph read from it
0cells of the map it votes in
62citing papers in PubMed
9.7field-weighted citation impact, top 2% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

62 citing papers in PubMed, 99 citations in OpenAlex.

  1. Article
  2. Article
  3. Germline Saturation Mutagenesis Induces Skeletal Phenotypes in Mice.Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research · 2021
    Article
  4. Article
  5. A Point Mutation in IKAROS ZF1 Causes a B Cell Deficiency in Mice.Journal of immunology (Baltimore, Md. : 1950) · 2021
    Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Genome-Wide Exome Analysis ofG3 (Bethesda, Md.) · 2017
    Article
  20. Article

2 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

16 authors at 3 institutions in 3 countries.

T D AndrewsImmunogenomics Laboratory, Australian National University, GPO Box 334, Canberra City, Australian Capital Territory, 2601 , Australia. dan.andrews@anu.edu.au
B Whittle
M A Field
B Balakishnan
Y Zhang
Y Shao
V Cho
M Kirk
M Singh
Y Xia
J Hager
S Winslade
G Sjollema
B Beutler
A Enders
C C Goodnow
Australian National University · AUThe University of Texas Southwestern Medical Center · USCentre National de Recherche en Génomique Humaine · FR

Funding

Systems Biology CoreU19AI100627 · NIAID · SCRIPPS RESEARCH INSTITUTE, THE · PI ULEVITCH, RICHARD J · 2012 to 2021
$49.1M
Genes for Tolerance and Immunity ConsortiumR01AI052127 · NIAID · AUSTRALIAN NATIONAL UNIVERSITY · PI GOODNOW, CHRISTOPHER CARL · 2002 to 2006
$6.3M
Medical Research CouncilNIAID NIH HHS R01 AI052127NIAID NIH HHS U19 AI100627Wellcome Trust
6 · The paper itself

Abstract

Accurate identification of sparse heterozygous single-nucleotide variants (SNVs) is a critical challenge for identifying the causative mutations in mouse genetic screens, human genetic diseases and cancer. When seeking to identify causal DNA variants that occur at such low rates, they are overwhelmed by false-positive calls that arise from a range of technical and biological sources. We describe a strategy using whole-exome capture, massively parallel DNA sequencing and computational analysis, which identifies with a low false-positive rate the majority of heterozygous and homozygous SNVs arising de novo with a frequency of one nucleotide substitution per megabase in progeny of N-ethyl-N-nitrosourea (ENU)-mutated C57BL/6j mice. We found that by applying a strategy of filtering raw SNV calls against known and platform-specific variants we could call true SNVs with a false-positive rate of 19.4 per cent and an estimated false-negative rate of 21.3 per cent. These error rates are small enough to enable calling a causative mutation from both homozygous and heterozygous candidate mutation lists with little or no further experimental validation. The efficacy of this approach is demonstrated by identifying the causative mutation in the Ptprc gene in a lymphocyte-deficient strain and in 11 other strains with immune disorders or obesity, without the need for meiotic mapping. Exome sequencing of first-generation mutant mice revealed hundreds of unphenotyped protein-changing mutations, 52 per cent of which are predicted to be deleterious, which now become available for breeding and experimental analysis. We show that exome sequencing data alone are sufficient to identify induced mutations. This approach transforms genetic screens in mice, establishes a general strategy for analysing rare DNA variants and opens up a large new source for experimental models of human disease.

Indexed as

Disease Models, AnimalDNA Mutational AnalysisExomePolymorphism, Single NucleotideSequence Analysis, DNAAnimalsCrosses, GeneticEthylnitrosoureaFemaleGenes, RecessiveHeterozygoteHomozygoteInbreedingLeukocyte Common AntigensMaleMiceEthylnitrosoureaLeukocyte Common AntigensPtprc protein, mouseDNA captureexome sequencingmousemutation detectionN-ethyl-N-nitrosourea mutagenesisvariation detection

Identifiers

PMID22724066
PMCPMC3376740
OpenAlexW2119310940

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.