de.mpg.escidoc.pubman.appbase.FacesBean
English
 
Help Guide Disclaimer Contact us Login
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
  Single feature polymorphism (SFP)-based selective sweep identification and association mapping of growth-related metabolic traits in Arabidopsis thaliana

Childs, L. H., Witucka-Wall, H., Gunther, T., Sulpice, R., Korff, M. V., Stitt, M., et al. (2010). Single feature polymorphism (SFP)-based selective sweep identification and association mapping of growth-related metabolic traits in Arabidopsis thaliana. BMC Genomics, 11, 188. doi:10.1186/1471-2164-11-188.

Item is

Basic

show hide
Item Permalink: http://hdl.handle.net/11858/00-001M-0000-0014-2438-4 Version Permalink: http://hdl.handle.net/11858/00-001M-0000-0014-2439-2
Genre: Journal Article

Files

show Files
hide Files
:
Childs-2010-Single feature polym.pdf (Any fulltext), 2MB
Description:
-
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
Copyright Date:
-
Copyright Info:
-
License:
-

Locators

show

Creators

show
hide
 Creators:
Childs, L. H.1, Author
Witucka-Wall, H.1, Author
Gunther, T.1, Author
Sulpice, R.2, Author              
Korff, M. V.1, Author
Stitt, M.2, Author              
Walther, D.3, Author              
Schmid, K. J.1, Author
Altmann, T.4, Author              
Affiliations:
1External Organizations, escidoc:persistent22              
2System Regulation, Department Stitt, Max Planck Institute of Molecular Plant Physiology, Max Planck Society, escidoc:1753327              
3BioinformaticsCIG, Infrastructure Groups and Service Units, Max Planck Institute of Molecular Plant Physiology, Max Planck Society, escidoc:1753303              
4Developmental Physiology and Genomics, Cooperative Research Groups, Max Planck Institute of Molecular Plant Physiology, Max Planck Society, escidoc:1753313              

Content

show
hide
Free keywords: positive selection natural variation genetic-variation secondary metabolism population-structure enzyme-activities DNA microarrays flowering time plant-growth human genome
 Abstract: Background: Natural accessions of Arabidopsis thaliana are characterized by a high level of phenotypic variation that can be used to investigate the extent and mode of selection on the primary metabolic traits. A collection of 54 A. thaliana natural accession-derived lines were subjected to deep genotyping through Single Feature Polymorphism (SFP) detection via genomic DNA hybridization to Arabidopsis Tiling 1.0 Arrays for the detection of selective sweeps, and identification of associations between sweep regions and growth-related metabolic traits. Results: A total of 1,072,557 high-quality SFPs were detected and indications for 3,943 deletions and 1,007 duplications were obtained. A significantly lower than expected SFP frequency was observed in protein-, rRNA-, and tRNA-coding regions and in non-repetitive intergenic regions, while pseudogenes, transposons, and non-coding RNA genes are enriched with SFPs. Gene families involved in plant defence or in signalling were identified as highly polymorphic, while several other families including transcription factors are depleted of SFPs. 198 significant associations between metabolic genes and 9 metabolic and growth-related phenotypic traits were detected with annotation hinting at the nature of the relationship. Five significant selective sweep regions were also detected of which one associated significantly with a metabolic trait. Conclusions: We generated a high density polymorphism map for 54 A. thaliana accessions that highlights the variability of resistance genes across geographic ranges and used it to identify selective sweeps and associations between metabolic genes and metabolic phenotypes. Several associations show a clear biological relationship, while many remain requiring further investigation.

Details

show
hide
Language(s): eng - English
 Dates: 2010-03-202010
 Publication Status: Published in print
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Method: -
 Identifiers: ISI: ISI:000276365400001
DOI: 10.1186/1471-2164-11-188
ISSN: 1471-2164 (Electronic) 1471-2164 (Linking)
URI: ://000276365400001 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2850358/pdf/1471-2164-11-188.pdf?tool=pmcentrez
 Degree: -

Event

show

Legal Case

show

Project information

show

Source 1

show
hide
Title: BMC Genomics
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: -
Pages: - Volume / Issue: 11 Sequence Number: - Start / End Page: 188 Identifier: -