Literature DB >> 23183923

Correlations and comparisons of quantitative trait loci with family per se and testcross performance for grain yield and related traits in maize.

Bo Peng1, Yongxiang Li, Yang Wang, Cheng Liu, Zhizhai Liu, Yan Zhang, Weiwei Tan, Di Wang, Yunsu Shi, Baocheng Sun, Yanchun Song, Tianyu Wang, Yu Li.   

Abstract

Simultaneous improvement in grain yield and related traits in maize hybrids and their parents (inbred lines) requires a better knowledge of genotypic correlations between family per se performance (FP) and testcross performance (TP). Thus, to understand the genetic basis of yield-related traits in both inbred lines and their testcrosses, two F (2:3) populations (including 230 and 235 families, respectively) were evaluated for both FP and TP of eight yield-related traits in three diverse environments. Genotypic correlations between FP and TP, [Formula: see text] (FP, TP), were low (0-0.16) for grain yield per plant (GYPP) and kernel number per plant (KNPP) in the two populations, but relatively higher (0.32-0.69) for the other six traits with additive effects as the primary gene action. Similar results were demonstrated by the genotypic correlations between observed and predicted TP values based on quantitative trait loci positions and effects for FP, [Formula: see text] (M (FP), Y (TP)). A total of 88 and 35 QTL were detected with FP and TP, respectively, across all eight traits in the two populations. However, the genotypic variances explained by the QTL detected in the cross-validation analysis were much lower than those in the whole data set for all traits. Several common QTL between FP and TP that accounted for large phenotypic variances were clustered in four genomic regions (bin 1.10, 4.05-4.06, 9.02, and 10.04), which are promising candidate loci for further map-based cloning and improvement in grain yield in maize. Compared with publicly available QTL data, these QTL were also detected in a wide range of genetic backgrounds and environments in maize. These results imply that effective selection based on FP to improve TP could be achieved for traits with prevailing additive effects.

Entities:  

Mesh:

Substances:

Year:  2012        PMID: 23183923     DOI: 10.1007/s00122-012-2017-1

Source DB:  PubMed          Journal:  Theor Appl Genet        ISSN: 0040-5752            Impact factor:   5.699


  23 in total

1.  Identification of quantitative trait loci across recombinant inbred lines and testcross populations for traits of agronomic importance in rice.

Authors:  Aiqing You; Xinggui Lu; Huajun Jin; Xiang Ren; Kai Liu; Guocai Yang; Haiyuan Yang; Lili Zhu; Guangcun He
Journal:  Genetics       Date:  2005-12-01       Impact factor: 4.562

Review 2.  Genetic architecture of complex traits in plants.

Authors:  James B Holland
Journal:  Curr Opin Plant Biol       Date:  2007-02-08       Impact factor: 7.834

Review 3.  Marker-assisted selection: an approach for precision plant breeding in the twenty-first century.

Authors:  Bertrand C Y Collard; David J Mackill
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2008-02-12       Impact factor: 6.237

4.  Population structure and linkage disequilibrium of a mini core set of maize inbred lines in China.

Authors:  Ronghuan Wang; Yongtao Yu; Jiuran Zhao; Yunsu Shi; Yanchun Song; Tianyu Wang; Yu Li
Journal:  Theor Appl Genet       Date:  2008-08-12       Impact factor: 5.699

5.  In an elite cross of maize a major quantitative trait locus controls one-fourth of the genetic variation for grain yield.

Authors:  P Ajnone-Marsan; G Monfredini; W F Ludwig; A E Melchinger; P Franceschini; G Pagnotto; M Motto
Journal:  Theor Appl Genet       Date:  1995-03       Impact factor: 5.699

6.  Drought stress and tropical maize: QTL-by-environment interactions and stability of QTLs across environments for yield components and secondary traits.

Authors:  Rainer Messmer; Yvan Fracheboud; Marianne Bänziger; Mateo Vargas; Peter Stamp; Jean-Marcel Ribaut
Journal:  Theor Appl Genet       Date:  2009-07-12       Impact factor: 5.699

7.  Quantitative trait locus (QTL) mapping using different testers and independent population samples in maize reveals low power of QTL detection and large bias in estimates of QTL effects.

Authors:  A E Melchinger; H F Utz; C C Schön
Journal:  Genetics       Date:  1998-05       Impact factor: 4.562

8.  Quantitative trait loci underlying gene product variation: a novel perspective for analyzing regulation of genome expression.

Authors:  C Damerval; A Maurice; J M Josse; D de Vienne
Journal:  Genetics       Date:  1994-05       Impact factor: 4.562

9.  Mapping of QTL for resistance to the Mediterranean corn borer attack using the intermated B73 x Mo17 (IBM) population of maize.

Authors:  Bernardo Ordas; Rosa A Malvar; Rogelio Santiago; German Sandoya; Maria C Romay; Ana Butron
Journal:  Theor Appl Genet       Date:  2009-09-16       Impact factor: 5.699

10.  MAPMAKER: an interactive computer package for constructing primary genetic linkage maps of experimental and natural populations.

Authors:  E S Lander; P Green; J Abrahamson; A Barlow; M J Daly; S E Lincoln; L A Newberg; L Newburg
Journal:  Genomics       Date:  1987-10       Impact factor: 5.736

View more
  4 in total

1.  QTL mapping of agronomic waterlogging tolerance using recombinant inbred lines derived from tropical maize (Zea mays L) germplasm.

Authors:  Pervez Haider Zaidi; Zerka Rashid; Madhumal Thayil Vinayan; Gustavo Dias Almeida; Ramesh Kumar Phagna; Raman Babu
Journal:  PLoS One       Date:  2015-04-17       Impact factor: 3.240

2.  Dissecting the Genetic Basis Underlying Combining Ability of Plant Height Related Traits in Maize.

Authors:  Zhiqiang Zhou; Chaoshu Zhang; Xiaohuan Lu; Liwei Wang; Zhuanfang Hao; Mingshun Li; Degui Zhang; Hongjun Yong; Hanyong Zhu; Jianfeng Weng; Xinhai Li
Journal:  Front Plant Sci       Date:  2018-08-02       Impact factor: 5.753

3.  Analysis of heterosis and quantitative trait loci for kernel shape related traits using triple testcross population in maize.

Authors:  Lu Jiang; Min Ge; Han Zhao; Tifu Zhang
Journal:  PLoS One       Date:  2015-04-28       Impact factor: 3.240

4.  Heterotic loci identified for maize kernel traits in two chromosome segment substitution line test populations.

Authors:  Yafei Wang; Xiangge Zhang; Xia Shi; Canran Sun; Jiao Jin; Runmiao Tian; Xiaoyi Wei; Huiling Xie; Zhanyong Guo; Jihua Tang
Journal:  Sci Rep       Date:  2018-07-23       Impact factor: 4.379

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.