Literature DB >> 23595202

Genetic basis of soybean adaptation to North American vs. Asian mega-environments in two independent populations from Canadian × Chinese crosses.

M Eugenia Rossi1, James H Orf, Li-Jun Liu, Zhimin Dong, Istvan Rajcan.   

Abstract

One of the goals of plant breeding is to increase yield with improved quality characters. Plant introductions (PI) are a rich source of favorable alleles that could improve different characters in modern soybean [Glycine max (L.) Merril] including yield. The objectives of this study were to identify yield QTL underlying the genetic basis for differential adaptation of soybeans to the Canadian, United States or Chinese mega-environments (ME) and to evaluate the relationship and colocalization between yield and agronomic traits QTL. Two crosses between high-yielding Canadian cultivars and elite Chinese cultivars, OAC Millennium × Heinong 38 and Pioneer 9071 × #8902, were used to develop two recombinant inbred line (RIL) populations. Both populations were evaluated at different locations in Ontario, Canada; Minnesota, United States (US), Heilongjiang and Jilin, China, in 2009 and 2010. Significant variation for yield was observed among the RILs of both populations across the three hypothetical ME. Two yield QTL (linked to the interval Satt364-Satt591 and Satt277) and one yield QTL (linked to marker Sat_341) were identified by single-factor ANOVA and interval mapping across all ME in populations 1 and 2, respectively. The most frequent top ten high-yielding lines across all ME carried most of the high-yielding alleles of the QTL that were identified in two and three ME. Both parents contributed favorable alleles, which suggests that not only the adapted parent but also the PI parents are potential sources of beneficial alleles in reciprocal environments. Other QTL were detected also at two and one ME. Most of the yield QTL were co-localized with a QTL associated with an agronomic trait in one, two, or three ME in just one or in both populations. Results suggested that most of the variation observed in seed yield can be explained by the variation of different agronomic traits such a maturity, lodging and height. Novel alleles coming from PI can favorably contribute, directly or indirectly, to seed yield and the utilization of QTL detected across one, two or three ME would facilitate the new allele introgression into breeding populations in both North America and China.

Entities:  

Mesh:

Year:  2013        PMID: 23595202     DOI: 10.1007/s00122-013-2094-9

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


  7 in total

1.  Introgression of a quantitative trait locus for yield from Glycine soja into commercial soybean cultivars.

Authors:  V C Concibido; B La Vallee; P McLaird; N Pineda; J Meyer; L Hummel; J Yang; K Wu; X Delannay
Journal:  Theor Appl Genet       Date:  2002-09-04       Impact factor: 5.699

2.  Validation of mega-environment universal and specific QTL associated with seed yield and agronomic traits in soybeans.

Authors:  Laura Palomeque; Li-Jun Liu; Wenbin Li; Bradley R Hedges; Elroy R Cober; Mathew P Smid; Lewis Lukens; Istvan Rajcan
Journal:  Theor Appl Genet       Date:  2009-12-11       Impact factor: 5.699

3.  Identification of putative QTL that underlie yield in interspecific soybean backcross populations.

Authors:  D Wang; G L Graef; A M Procopiuk; B W Diers
Journal:  Theor Appl Genet       Date:  2003-09-19       Impact factor: 5.699

4.  Seed quality QTL in a prominent soybean population.

Authors:  D L Hyten; V R Pantalone; C E Sams; A M Saxton; D Landau-Ellis; T R Stefaniak; M E Schmidt
Journal:  Theor Appl Genet       Date:  2004-06-24       Impact factor: 5.699

5.  Seed and agronomic QTL in low linolenic acid, lipoxygenase-free soybean (Glycine max (L.) Merrill) germplasm.

Authors:  Yarmilla Reinprecht; Vaino W Poysa; Kangfu Yu; Istvan Rajcan; Gary R Ablett; K Peter Pauls
Journal:  Genome       Date:  2006-12       Impact factor: 2.166

6.  QTL in mega-environments: I. Universal and specific seed yield QTL detected in a population derived from a cross of high-yielding adapted x high-yielding exotic soybean lines.

Authors:  Laura Palomeque; Liu Li-Jun; Wenbin Li; Bradley Hedges; Elroy R Cober; Istvan Rajcan
Journal:  Theor Appl Genet       Date:  2009-05-22       Impact factor: 5.699

7.  QTL in mega-environments: II. Agronomic trait QTL co-localized with seed yield QTL detected in a population derived from a cross of high-yielding adapted x high-yielding exotic soybean lines.

Authors:  Laura Palomeque; Liu Li-Jun; Wenbin Li; Bradley Hedges; Elroy R Cober; Istvan Rajcan
Journal:  Theor Appl Genet       Date:  2009-05-22       Impact factor: 5.699

  7 in total
  18 in total

1.  Genome-wide association study of inflorescence length of cultivated soybean based on the high-throughout single-nucleotide markers.

Authors:  Jinyang Wang; Xue Zhao; Wei Wang; Yingfan Qu; Weili Teng; Lijuan Qiu; Hongkun Zheng; Yingpeng Han; Wenbin Li
Journal:  Mol Genet Genomics       Date:  2019-02-09       Impact factor: 3.291

2.  Fine mapping QTL and mining genes for protein content in soybean by the combination of linkage and association analysis.

Authors:  Xiyu Li; Ping Wang; Kaixin Zhang; Shulin Liu; Zhongying Qi; Yanlong Fang; Yue Wang; Xiaocui Tian; Jie Song; Jiajing Wang; Chang Yang; Xu Sun; Zhixi Tian; Wen-Xia Li; Hailong Ning
Journal:  Theor Appl Genet       Date:  2021-01-09       Impact factor: 5.699

3.  Identification of quantitative trait loci associated with seed quality traits between Canadian and Ukrainian mega-environments using genome-wide association study.

Authors:  Huilin Hong; Mohsen Yoosefzadeh Najafabadi; Davoud Torkamaneh; Istvan Rajcan
Journal:  Theor Appl Genet       Date:  2022-06-18       Impact factor: 5.574

4.  Introgression of novel genetic diversity to improve soybean yield.

Authors:  J M Hegstad; R L Nelson; S Renny-Byfield; L Feng; J M Chaky
Journal:  Theor Appl Genet       Date:  2019-06-17       Impact factor: 5.699

5.  Genome-wide genetic diversity is maintained through decades of soybean breeding in Canada.

Authors:  Robert W Bruce; Davoud Torkamaneh; Christopher Grainger; François Belzile; Milad Eskandari; Istvan Rajcan
Journal:  Theor Appl Genet       Date:  2019-08-05       Impact factor: 5.699

6.  Genetic dissection of yield-related traits via genome-wide association analysis across multiple environments in wild soybean (Glycine soja Sieb. and Zucc.).

Authors:  Dezhou Hu; Huairen Zhang; Qing Du; Zhenbin Hu; Zhongyi Yang; Xiao Li; Jiao Wang; Fang Huang; Deyue Yu; Hui Wang; Guizhen Kan
Journal:  Planta       Date:  2020-01-06       Impact factor: 4.116

7.  Phenotypic Characterization and Genetic Dissection of Growth Period Traits in Soybean (Glycine max) Using Association Mapping.

Authors:  Zhangxiong Liu; Huihui Li; Xuhong Fan; Wen Huang; Jiyu Yang; Candong Li; Zixiang Wen; Yinghui Li; Rongxia Guan; Yong Guo; Ruzhen Chang; Dechun Wang; Shuming Wang; Li-Juan Qiu
Journal:  PLoS One       Date:  2016-07-01       Impact factor: 3.240

8.  SNP-SNP Interaction Analysis on Soybean Oil Content under Multi-Environments.

Authors:  Qingshan Chen; Xinrui Mao; Zhanguo Zhang; Rongsheng Zhu; Zhengong Yin; Yue Leng; Hongxiao Yu; Huiying Jia; Shanshan Jiang; Zhongqiu Ni; Hongwei Jiang; Xue Han; Chunyan Liu; Zhenbang Hu; Xiaoxia Wu; Guohua Hu; Dawei Xin; Zhaoming Qi
Journal:  PLoS One       Date:  2016-09-26       Impact factor: 3.240

9.  Identification of candidate genes and natural allelic variants for QTLs governing plant height in chickpea.

Authors:  Alice Kujur; Hari D Upadhyaya; Deepak Bajaj; C L L Gowda; Shivali Sharma; Akhilesh K Tyagi; Swarup K Parida
Journal:  Sci Rep       Date:  2016-06-20       Impact factor: 4.379

10.  Genome-wide association mapping for flowering and maturity in tropical soybean: implications for breeding strategies.

Authors:  Rodrigo Iván Contreras-Soto; Freddy Mora; Fabiane Lazzari; Marco Antônio Rott de Oliveira; Carlos Alberto Scapim; Ivan Schuster
Journal:  Breed Sci       Date:  2017-11-16       Impact factor: 2.086

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.