Literature DB >> 23011316

Identification of combining ability loci for five yield-related traits in maize using a set of testcrosses with introgression lines.

Huanhuan Qi1, Juan Huang, Qi Zheng, Yaqun Huang, Renxue Shao, Liying Zhu, Zuxin Zhang, Fazhan Qiu, Guangcheng Zhou, Yonglian Zheng, Bing Yue.   

Abstract

Combining ability is essential for hybrid breeding in crops. However, the genetic basis of combining ability remains unclear and has been seldom investigated. Identifying molecular markers associated with this complex trait would help to understand its genetic basis and provide useful information for hybrid breeding in maize. In this study, we identified genetic loci of general combining ability (GCA) and specific combining ability (SCA) for five yield-related traits under three environments using a set of testcrosses with introgression lines (ILs). GCA or SCA of the five yield-related traits of the ILs was estimated by the performance of testcrosses with four testers from different heterotic groups. Genetic correlations between GCA of the traits and the corresponding traits per se were not significant or not strong, suggesting that the genetic basis between them is different. A total of 56 significant loci for GCA and 21 loci for SCA were commonly identified in at least two environments, and only 5 loci were simultaneously controlling GCA and SCA, indicating that the genetic basis of GCA and SCA is different. For all of the traits investigated, positive and significant correlations between the number of GCA loci in the ILs and the performance of the corresponding GCA of the ILs were detected, implying that pyramiding GCA loci would have positive effect on the performance of GCA. Results in this study would be useful for maize hybrid breeding.

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Year:  2012        PMID: 23011316     DOI: 10.1007/s00122-012-1985-5

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


  9 in total

1.  Use of DNA markers in prediction of hybrid performance and heterosis for a three-line hybrid system in rice.

Authors:  S P Joshi; S G Bhave; K V Chowdari; G S Apte; B L Dhonukshe; K Lalitha; P K Ranjekar; V S Gupta
Journal:  Biochem Genet       Date:  2001-06       Impact factor: 1.890

2.  Chromosomal regions involved in hybrid performance and heterosis: their AFLP(R)-based identification and practical use in prediction models.

Authors:  M Vuylsteke; M Kuiper; P Stam
Journal:  Heredity (Edinb)       Date:  2000-09       Impact factor: 3.821

3.  Prediction of hybrid performance in grain sorghum using RFLP markers.

Authors:  D R Jordan; Y Tao; I D Godwin; R G Henzell; M Cooper; C L McIntyre
Journal:  Theor Appl Genet       Date:  2002-12-19       Impact factor: 5.699

4.  Two-locus theory in recurrent selection for general combining ability in maize.

Authors:  G R Johnson
Journal:  Theor Appl Genet       Date:  1982-09       Impact factor: 5.699

5.  [Correlations between specific combining ability, heterosis and genetic distance in hybrid rice].

Authors:  Xian-Lin Ni; Tao Zhang; Kai-Feng Jiang; Li Yang; Qian-Hua Yang; Ying-Jiang Cao; Chun-Yang Wen; Jia-Kui Zheng
Journal:  Yi Chuan       Date:  2009-08

6.  Prediction of hybrid performance in maize using molecular markers and joint analyses of hybrids and parental inbreds.

Authors:  Tobias A Schrag; Jens Möhring; Albrecht E Melchinger; Barbara Kusterer; Baldev S Dhillon; Hans-Peter Piepho; Matthias Frisch
Journal:  Theor Appl Genet       Date:  2009-11-15       Impact factor: 5.699

7.  Prediction of single-cross hybrid performance for grain yield and grain dry matter content in maize using AFLP markers associated with QTL.

Authors:  T A Schrag; A E Melchinger; A P Sørensen; M Frisch
Journal:  Theor Appl Genet       Date:  2006-08-03       Impact factor: 5.699

8.  Genomic and metabolic prediction of complex heterotic traits in hybrid maize.

Authors:  Christian Riedelsheimer; Angelika Czedik-Eysenberg; Christoph Grieder; Jan Lisec; Frank Technow; Ronan Sulpice; Thomas Altmann; Mark Stitt; Lothar Willmitzer; Albrecht E Melchinger
Journal:  Nat Genet       Date:  2012-01-15       Impact factor: 38.330

9.  QTL mapping of combining ability and heterosis of agronomic traits in rice backcross recombinant inbred lines and hybrid crosses.

Authors:  Zhen Qu; Lanzhi Li; Junyuan Luo; Peng Wang; Sibin Yu; Tongmin Mou; Xingfei Zheng; Zhongli Hu
Journal:  PLoS One       Date:  2012-01-26       Impact factor: 3.240

  9 in total
  24 in total

1.  QTL mapping for combining ability in different population-based NCII designs: a simulation study.

Authors:  Lanzhi Li; Congwei Sun; Yuan Chen; Zhijun Dai; Zhen Qu; Xingfei Zheng; Sibin Yu; Tongmin Mou; Chenwu Xu; Zhongli Hu
Journal:  J Genet       Date:  2013-12       Impact factor: 1.166

2.  General combining ability of most yield-related traits had a genetic basis different from their corresponding traits per se in a set of maize introgression lines.

Authors:  Juan Huang; Huanhuan Qi; Xiaomin Feng; Yaqun Huang; Liying Zhu; Bing Yue
Journal:  Genetica       Date:  2013-10-18       Impact factor: 1.082

3.  Fine mapping of a dominantly inherited powdery mildew resistance major-effect QTL, Pm1.1, in cucumber identifies a 41.1 kb region containing two tandemly arrayed cysteine-rich receptor-like protein kinase genes.

Authors:  Xuewen Xu; Ting Yu; Ruixue Xu; Yang Shi; Xiaojian Lin; Qiang Xu; Xiaohua Qi; Yiqun Weng; Xuehao Chen
Journal:  Theor Appl Genet       Date:  2015-12-11       Impact factor: 5.699

4.  The phenotypic predisposition of the parent in F1 hybrid is correlated with transcriptome preference of the positive general combining ability parent.

Authors:  Gaoyuan Song; Zhibin Guo; Zhenwei Liu; Xuefeng Qu; Daiming Jiang; Wei Wang; Yingguo Zhu; Daichang Yang
Journal:  BMC Genomics       Date:  2014-04-22       Impact factor: 3.969

5.  Interacted QTL mapping in partial NCII design provides evidences for breeding by design.

Authors:  Su Hong Bu; Xinwang Zhao; Zhao Xinwang; Can Yi; Jia Wen; Jinxing Tu; Tu Jinxing; Yuan Ming Zhang
Journal:  PLoS One       Date:  2015-03-30       Impact factor: 3.240

6.  Whole-Genome Resequencing of a Cucumber Chromosome Segment Substitution Line and Its Recurrent Parent to Identify Candidate Genes Governing Powdery Mildew Resistance.

Authors:  Qiang Xu; Yang Shi; Ting Yu; Xuewen Xu; Yali Yan; Xiaohua Qi; Xuehao Chen
Journal:  PLoS One       Date:  2016-10-20       Impact factor: 3.240

7.  Breeding signature of combining ability improvement revealed by a genomic variation map from recurrent selection population in Brassica napus.

Authors:  Xinwang Zhao; Bao Li; Ka Zhang; Kaining Hu; Bin Yi; Jing Wen; Chaozhi Ma; Jinxiong Shen; Tingdong Fu; Jinxing Tu
Journal:  Sci Rep       Date:  2016-07-14       Impact factor: 4.379

8.  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

9.  OsPRR37 and Ghd7 are the major genes for general combining ability of DTH, PH and SPP in rice.

Authors:  Chuan Liu; Gaoyuan Song; Yanhao Zhou; Xuefeng Qu; Zhibin Guo; Zhenwei Liu; Daiming Jiang; Daichang Yang
Journal:  Sci Rep       Date:  2015-08-04       Impact factor: 4.379

10.  Genetic dissection of heterosis using epistatic association mapping in a partial NCII mating design.

Authors:  Jia Wen; Xinwang Zhao; Guorong Wu; Dan Xiang; Qing Liu; Su-Hong Bu; Can Yi; Qijian Song; Jim M Dunwell; Jinxing Tu; Tianzhen Zhang; Yuan-Ming Zhang
Journal:  Sci Rep       Date:  2015-12-17       Impact factor: 4.379

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