Literature DB >> 29274071

Genome-wide association analysis of lead accumulation in maize.

Xiongwei Zhao1, Yajuan Liu1, Wenmei Wu1, Yuhua Li1, Longxin Luo1, Yuzhou Lan1, Yanhua Cao1, Zhiming Zhang1, Shibin Gao1, Guangsheng Yuan1, Li Liu1, Yaou Shen1, Guangtang Pan1, Haijian Lin2.   

Abstract

Large phenotypic variations in the lead (Pb) concentration were observed in grains and leaves of maize plants. A further understanding of inheritance of Pb accumulation may facilitate improvement of low-Pb-accumulating cultivars in maize. A genome-wide association study was conducted in a population of 269 maize accessions with 43,737 single-nucleotide polymorphisms (SNPs). The Pb concentrations in leaves and kernels of 269 accessions were collected in pot-culture and field experiments in years of 2015 and 2016. Significant differences in Pb accumulation were found among individuals under different environments. Using the structure and kinship model, a total of 21 SNPs significantly associated with the Pb accumulation were identified with P < 2.28 × 10-5 and FDR < 0.05 in the pot-culture and field experiments across 2 years. Three SNPs on chromosome 4 had significant associations simultaneously with the Pb concentrations of kernels and leaves and were co-localized with the previously detected quantitative trait loci. Through ridge regression best linear unbiased prediction Pb accumulation in the association population, the prediction accuracies by cross validation were 0.18-0.59 and 0.17-0.64, depending on the k-fold and the size of the training population. The results are helpful for genetic improvement and genomic prediction of Pb accumulation in maize.

Entities:  

Keywords:  Association analysis; Genome prediction; Lead accumulation; Maize

Mesh:

Substances:

Year:  2017        PMID: 29274071     DOI: 10.1007/s00438-017-1411-4

Source DB:  PubMed          Journal:  Mol Genet Genomics        ISSN: 1617-4623            Impact factor:   3.291


  26 in total

1.  Genomic prediction of hybrid performance in maize with models incorporating dominance and population specific marker effects.

Authors:  Frank Technow; Christian Riedelsheimer; Tobias A Schrag; Albrecht E Melchinger
Journal:  Theor Appl Genet       Date:  2012-06-26       Impact factor: 5.699

2.  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

3.  AtHMA3, a P1B-ATPase allowing Cd/Zn/Co/Pb vacuolar storage in Arabidopsis.

Authors:  Mélanie Morel; Jérôme Crouzet; Antoine Gravot; Pascaline Auroy; Nathalie Leonhardt; Alain Vavasseur; Pierre Richaud
Journal:  Plant Physiol       Date:  2008-11-26       Impact factor: 8.340

4.  Identification of QTLs for arsenic accumulation in maize (Zea mays L.) using a RIL population.

Authors:  Dong Ding; Weihua Li; Guiliang Song; Hongyuan Qi; Jingbao Liu; Jihua Tang
Journal:  PLoS One       Date:  2011-10-18       Impact factor: 3.240

5.  Genome-wide association study reveals a set of genes associated with resistance to the Mediterranean corn borer (Sesamia nonagrioides L.) in a maize diversity panel.

Authors:  Luis Fernando Samayoa; Rosa Ana Malvar; Bode A Olukolu; James B Holland; Ana Butrón
Journal:  BMC Plant Biol       Date:  2015-02-05       Impact factor: 4.215

Review 6.  Cadmium transport and tolerance in rice: perspectives for reducing grain cadmium accumulation.

Authors:  Shimpei Uraguchi; Toru Fujiwara
Journal:  Rice (N Y)       Date:  2012-02-27       Impact factor: 4.783

7.  Comparative mapping combined with homology-based cloning of the rice genome reveals candidate genes for grain zinc and iron concentration in maize.

Authors:  Tiantian Jin; Jingtang Chen; Liying Zhu; Yongfeng Zhao; Jinjie Guo; Yaqun Huang
Journal:  BMC Genet       Date:  2015-02-14       Impact factor: 2.797

8.  Genome-wide association study, genomic prediction and marker-assisted selection for seed weight in soybean (Glycine max).

Authors:  Jiaoping Zhang; Qijian Song; Perry B Cregan; Guo-Liang Jiang
Journal:  Theor Appl Genet       Date:  2015-10-30       Impact factor: 5.699

9.  Genome-wide association study (GWAS) reveals the genetic architecture of four husk traits in maize.

Authors:  Zhenhai Cui; Jinhong Luo; Chuangye Qi; Yanye Ruan; Jing Li; Ao Zhang; Xiaohong Yang; Yan He
Journal:  BMC Genomics       Date:  2016-11-21       Impact factor: 3.969

10.  Genome wide association studies using a new nonparametric model reveal the genetic architecture of 17 agronomic traits in an enlarged maize association panel.

Authors:  Ning Yang; Yanli Lu; Xiaohong Yang; Juan Huang; Yang Zhou; Farhan Ali; Weiwei Wen; Jie Liu; Jiansheng Li; Jianbing Yan
Journal:  PLoS Genet       Date:  2014-09-11       Impact factor: 5.917

View more
  4 in total

Review 1.  Genome-wide association mapping in maize: status and prospects.

Authors:  Kumari Shikha; J P Shahi; M T Vinayan; P H Zaidi; A K Singh; B Sinha
Journal:  3 Biotech       Date:  2021-04-29       Impact factor: 2.406

Review 2.  Lead and Zinc Uptake and Toxicity in Maize and Their Management.

Authors:  Tayebeh Abedi; Shahin Gavanji; Amin Mojiri
Journal:  Plants (Basel)       Date:  2022-07-25

3.  Association mapping uncovers maize ZmbZIP107 regulating root system architecture and lead absorption under lead stress.

Authors:  Fengxia Hou; Kai Liu; Na Zhang; Chaoying Zou; Guangsheng Yuan; Shibin Gao; Minyan Zhang; Guangtang Pan; Langlang Ma; Yaou Shen
Journal:  Front Plant Sci       Date:  2022-09-26       Impact factor: 6.627

4.  Genome-wide association study (GWAS) reveals genetic loci of lead (Pb) tolerance during seedling establishment in rapeseed (Brassica napus L.).

Authors:  Fugui Zhang; Xin Xiao; Kun Xu; Xi Cheng; Ting Xie; Jihong Hu; Xiaoming Wu
Journal:  BMC Genomics       Date:  2020-02-10       Impact factor: 3.969

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.