Defining gene and QTL networks

Ritsert C. Jansen; Bruno M. Tesson; Jingyuan Fu; Yajie Yang; Lauren M. McIntyre; L.M. McInttyre

doi:10.1016/j.pbi.2009.01.003

Defining gene and QTL networks

Ritsert C. Jansen, Bruno M. Tesson, Jingyuan Fu, Yajie Yang, Lauren M. McIntyre^*, L.M. McInttyre

^*Corresponding author voor dit werk

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Current technologies for high-throughput molecular profiling of large numbers of genetically different individuals offer great potential for elucidating the genotype-to-phenotype relationship. Variation in molecular and phenotypic traits can be correlated to DNA sequence variation using the methods of quantitative trait locus (QTL) mapping. In addition, the correlation structure in the molecular and phenotypic traits can be informative for inferring the underlying molecular networks. For this, new methods are emerging to distinguish among causality, reactivity, or independence of traits based upon logic involving underlying QTL. These methods are becoming increasingly popular in plant genetic studies as well as in studies on many other organisms.

Originele taal-2	English
Pagina's (van-tot)	241-246
Aantal pagina's	6
Tijdschrift	Current Opinion in Plant Biology
Volume	12
Nummer van het tijdschrift	2
DOI's	https://doi.org/10.1016/j.pbi.2009.01.003
Status	Published - apr.-2009

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@article{03a331e1c7df4ed1b142d30f8e0f86f6,

title = "Defining gene and QTL networks",

abstract = "Current technologies for high-throughput molecular profiling of large numbers of genetically different individuals offer great potential for elucidating the genotype-to-phenotype relationship. Variation in molecular and phenotypic traits can be correlated to DNA sequence variation using the methods of quantitative trait locus (QTL) mapping. In addition, the correlation structure in the molecular and phenotypic traits can be informative for inferring the underlying molecular networks. For this, new methods are emerging to distinguish among causality, reactivity, or independence of traits based upon logic involving underlying QTL. These methods are becoming increasingly popular in plant genetic studies as well as in studies on many other organisms.",

keywords = "QUANTITATIVE TRAIT LOCI, TRANSCRIPT-LEVEL VARIATION, ARABIDOPSIS-THALIANA, COLLABORATIVE CROSS, CANDIDATE GENES, MICROARRAY DATA, EXPRESSION, GENOMICS, IDENTIFICATION, ARCHITECTURE",

author = "Jansen, {Ritsert C.} and Tesson, {Bruno M.} and Jingyuan Fu and Yajie Yang and McIntyre, {Lauren M.} and L.M. McInttyre",

year = "2009",

month = apr,

doi = "10.1016/j.pbi.2009.01.003",

language = "English",

volume = "12",

pages = "241--246",

journal = "Current Opinion in Plant Biology",

issn = "1369-5266",

number = "2",

}

TY - JOUR

T1 - Defining gene and QTL networks

AU - Jansen, Ritsert C.

AU - Tesson, Bruno M.

AU - Fu, Jingyuan

AU - Yang, Yajie

AU - McIntyre, Lauren M.

AU - McInttyre, L.M.

PY - 2009/4

Y1 - 2009/4

N2 - Current technologies for high-throughput molecular profiling of large numbers of genetically different individuals offer great potential for elucidating the genotype-to-phenotype relationship. Variation in molecular and phenotypic traits can be correlated to DNA sequence variation using the methods of quantitative trait locus (QTL) mapping. In addition, the correlation structure in the molecular and phenotypic traits can be informative for inferring the underlying molecular networks. For this, new methods are emerging to distinguish among causality, reactivity, or independence of traits based upon logic involving underlying QTL. These methods are becoming increasingly popular in plant genetic studies as well as in studies on many other organisms.

AB - Current technologies for high-throughput molecular profiling of large numbers of genetically different individuals offer great potential for elucidating the genotype-to-phenotype relationship. Variation in molecular and phenotypic traits can be correlated to DNA sequence variation using the methods of quantitative trait locus (QTL) mapping. In addition, the correlation structure in the molecular and phenotypic traits can be informative for inferring the underlying molecular networks. For this, new methods are emerging to distinguish among causality, reactivity, or independence of traits based upon logic involving underlying QTL. These methods are becoming increasingly popular in plant genetic studies as well as in studies on many other organisms.

KW - QUANTITATIVE TRAIT LOCI

KW - TRANSCRIPT-LEVEL VARIATION

KW - ARABIDOPSIS-THALIANA

KW - COLLABORATIVE CROSS

KW - CANDIDATE GENES

KW - MICROARRAY DATA

KW - EXPRESSION

KW - GENOMICS

KW - IDENTIFICATION

KW - ARCHITECTURE

U2 - 10.1016/j.pbi.2009.01.003

DO - 10.1016/j.pbi.2009.01.003

M3 - Review article

SN - 1369-5266

VL - 12

SP - 241

EP - 246

JO - Current Opinion in Plant Biology

JF - Current Opinion in Plant Biology

IS - 2

ER -

Defining gene and QTL networks

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