Connected populations for detecting quantitative trait loci and testing for epistasis: an application in maize

被引:0
|
作者
G. Blanc
A. Charcosset
B. Mangin
A. Gallais
L. Moreau
机构
[1] INRA/INA-PG/UPS/CNRS,
[2] UMR de Génétique Végétale,undefined
[3] INRA,undefined
[4] Unité de Biométrie et Intelligence Artificielle,undefined
来源
关键词
Quantitative Trait Locus; Epistatic Interaction; Epistatic Effect; Quantitative Trait Locus Effect; Allelic Effect;
D O I
暂无
中图分类号
学科分类号
摘要
Quantitative trait loci (QTL) detection experiments have often been restricted to large biallelic populations. Use of connected multiparental crosses has been proposed to increase the genetic variability addressed and to test for epistatic interactions between QTL and the genetic background. We present here the results of a QTL detection performed on six connected F2 populations of 150 F2:3 families each, derived from four maize inbreds and evaluated for three traits of agronomic interest. The QTL detection was carried out by composite interval mapping on each population separately, then on the global design either by taking into account the connections between populations or not. Epistatic interactions between loci and with the genetic background were tested. Taking into account the connections between populations increased the number of QTL detected and the accuracy of QTL position estimates. We detected many epistatic interactions, particularly for grain yield QTL (R2 increase of 9.6%). Use of connections for the QTL detection also allowed a global ranking of alleles at each QTL. Allelic relationships and epistasis both contribute to the lack of consistency for QTL positions observed among populations, in addition to the limited power of the tests. The potential benefit of assembling favorable alleles by marker-assisted selection are discussed.
引用
收藏
页码:206 / 224
页数:18
相关论文
共 50 条
  • [21] Congruency of quantitative trait loci detected for agronomic traits in testcrosses of five populations of European maize
    Mihaljevic, R
    Utz, HF
    Melchinger, AE
    CROP SCIENCE, 2004, 44 (01) : 114 - 124
  • [22] Quantitative trait loci for metal accumulation in maize leaf
    Soric, Roberta
    Ledencan, Tatjana
    Zdunic, Zvonimir
    Jambrovic, Antun
    Brkic, Ivan
    Loncaric, Zdenko
    Kovacevic, Vlado
    Simic, Domagoj
    MAYDICA, 2011, 56 (04): : 323 - 329
  • [23] Identification of the quantitative trait loci for grain rate in maize
    Liu, Xiaohong
    He, Sulan
    Zheng, Zuping
    Tan, Zhenbo
    Liu, Daihui
    AFRICAN JOURNAL OF BIOTECHNOLOGY, 2010, 9 (47): : 8007 - 8012
  • [24] Quantitative Trait Loci for Biofortification Traits in Maize Grain
    Simic, Domagoj
    Drinic, Snezana Mladenovic
    Zdunic, Zvonimir
    Jambrovic, Antun
    Ledencan, Tatjana
    Brkic, Josip
    Brkic, Andrija
    Brkic, Ivan
    JOURNAL OF HEREDITY, 2012, 103 (01) : 47 - 54
  • [25] The use of selection experiments for detecting quantitative trait loci
    Ollivier, L
    Messer, LA
    Rothschild, MF
    Legault, C
    GENETICAL RESEARCH, 1997, 69 (03) : 227 - 232
  • [26] Grammatical Evolution of Neural Networks for Discovering Epistasis among Quantitative Trait Loci
    Turner, Stephen D.
    Dudek, Scott M.
    Ritchie, Marylyn D.
    EVOLUTIONARY COMPUTATION, MACHINE LEARNING AND DATA MINING IN BIOINFORMATICS, PROCEEDINGS, 2010, 6023 : 86 - 97
  • [27] Quantitative Trait Loci and Epistasis for Oat Winter-Hardiness Component Traits
    Wooten, D. R.
    Livingston, D. P., III
    Lyerly, H. J.
    Holland, J. B.
    Jellen, E. N.
    Marshall, D. S.
    Murphy, J. P.
    CROP SCIENCE, 2009, 49 (06) : 1989 - 1998
  • [28] Mapping and analysis of quantitative trait loci in experimental populations
    Rebecca W. Doerge
    Nature Reviews Genetics, 2002, 3 : 43 - 52
  • [29] Mapping and analysis of quantitative trait loci in experimental populations
    Doerge, RW
    NATURE REVIEWS GENETICS, 2002, 3 (01) : 43 - 52