Literature DB >> 18844779

QTL and QTL x environment effects on agronomic and nitrogen acquisition traits in rice.

Senapathy Senthilvel1, Kunnummal Kurungara Vinod, Palaniappan Malarvizhi, Marappa Maheswaran.   

Abstract

Agricultural environments deteriorate due to excess nitrogen application. Breeding for low nitrogen responsive genotypes can reduce soil nitrogen input. Rice genotypes respond variably to soil available nitrogen. The present study attempted quantification of genotype x nitrogen level interaction and mapping of quantitative trait loci (QTLs) associated with nitrogen use efficiency (NUE) and other associated agronomic traits. Twelve parameters were observed across a set of 82 double haploid (DH) lines derived from IR64/Azucena. Three nitrogen regimes namely, native (0 kg/ha; no nitrogen applied), optimum (100 kg/ha) and high (200 kg/ha) replicated thrice were the environments. The parents and DH lines were significantly varying for all traits under different nitrogen regimes. All traits except plant height recorded significant genotype x environment interaction. Individual plant yield was positively correlated with nitrogen use efficiency and nitrogen uptake. Sixteen QTLs were detected by composite interval mapping. Eleven QTLs showed significant QTL x environment interactions. On chromosome 3, seven QTLs were detected associated with nitrogen use, plant yield and associated traits. A QTL region between markers RZ678, RZ574 and RZ284 was associated with nitrogen use and yield. This chromosomal region was enriched with expressed gene sequences of known key nitrogen assimilation genes.

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Year:  2008        PMID: 18844779     DOI: 10.1111/j.1744-7909.2008.00713.x

Source DB:  PubMed          Journal:  J Integr Plant Biol        ISSN: 1672-9072            Impact factor:   7.061


  16 in total

Review 1.  Biochemical and Genetic Approaches Improving Nitrogen Use Efficiency in Cereal Crops: A Review.

Authors:  Nitika Sandhu; Mehak Sethi; Aman Kumar; Devpriya Dang; Jasneet Singh; Parveen Chhuneja
Journal:  Front Plant Sci       Date:  2021-06-04       Impact factor: 5.753

2.  Metabolic and co-expression network-based analyses associated with nitrate response in rice.

Authors:  Viktoriya Coneva; Caitlin Simopoulos; José A Casaretto; Ashraf El-Kereamy; David R Guevara; Jonathan Cohn; Tong Zhu; Lining Guo; Danny C Alexander; Yong-Mei Bi; Paul D McNicholas; Steven J Rothstein
Journal:  BMC Genomics       Date:  2014-12-03       Impact factor: 3.969

3.  Mapping QTLs and association of differentially expressed gene transcripts for multiple agronomic traits under different nitrogen levels in sorghum.

Authors:  Malleswari Gelli; Sharon E Mitchell; Kan Liu; Thomas E Clemente; Donald P Weeks; Chi Zhang; David R Holding; Ismail M Dweikat
Journal:  BMC Plant Biol       Date:  2016-01-13       Impact factor: 4.215

Review 4.  Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches.

Authors:  Perrin H Beatty; Matthias S Klein; Jeffrey J Fischer; Ian A Lewis; Douglas G Muench; Allen G Good
Journal:  Plants (Basel)       Date:  2016-10-10

5.  Identification of QTL Associated with Nitrogen Uptake and Nitrogen Use Efficiency Using High Throughput Genotyped CSSLs in Rice (Oryza sativa L.).

Authors:  Yong Zhou; Yajun Tao; Dongnan Tang; Jun Wang; Jun Zhong; Yi Wang; Qiumei Yuan; Xiaofeng Yu; Yan Zhang; Yulong Wang; Guohua Liang; Guichun Dong
Journal:  Front Plant Sci       Date:  2017-07-11       Impact factor: 5.753

6.  Candidate Gene Analysis for Nitrogen Absorption and Utilization in Japonica Rice at the Seedling Stage Based on a Genome-Wide Association Study.

Authors:  Wei Xin; Jingguo Wang; Jia Li; Hongwei Zhao; Hualong Liu; Hongliang Zheng; Luomiao Yang; Chao Wang; Fan Yang; Jiahui Chen; Detang Zou
Journal:  Front Plant Sci       Date:  2021-06-04       Impact factor: 5.753

7.  Approaches towards nitrogen- and phosphorus-efficient rice.

Authors:  K K Vinod; Sigrid Heuer
Journal:  AoB Plants       Date:  2012-10-31       Impact factor: 3.276

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.  Transcriptome Analysis of Two Rice Varieties Contrasting for Nitrogen Use Efficiency under Chronic N Starvation Reveals Differences in Chloroplast and Starch Metabolism-Related Genes.

Authors:  Subodh Kumar Sinha; Amitha Mithra Sevanthi V; Saurabh Chaudhary; Punit Tyagi; Sureshkumar Venkadesan; Manju Rani; Pranab Kumar Mandal
Journal:  Genes (Basel)       Date:  2018-04-11       Impact factor: 4.096

10.  A follow-up study for biomass yield QTLs in rice.

Authors:  Kazuki Matsubara; Jun-Ichi Yonemaru; Nobuya Kobayashi; Takuro Ishii; Eiji Yamamoto; Ritsuko Mizobuchi; Hiroshi Tsunematsu; Toshio Yamamoto; Hiroshi Kato; Masahiro Yano
Journal:  PLoS One       Date:  2018-10-23       Impact factor: 3.240

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