Literature DB >> 33409935

A 1.84-Mb region on rice chromosome 2 carrying SPL4, SPL5 and MLO8 genes is associated with higher yield under phosphorus-deficient acidic soil.

Karma Landup Bhutia1,2, Ernieca Lyngdoh Nongbri1, Takhenchangbam Oshin Sharma1, Mayank Rai1, Wricha Tyagi3.   

Abstract

Phosphorus (P) deficiency is one of the major limiting factors for rice productivity with only one locus (PSTOL1) available for field based application. A biparental mapping population (F6) derived from two P deficiency tolerant genotypes (Sahbhagi Dhan (SD) (PSTOL1+) and Chakhao Poreiton (CP) (PSTOL1-)), in which, transcriptome data generated from our lab had previously shown existence of diverse mechanisms was used to identify novel regions for better yield under lowland acidic soils. Phenotyping at F4, F5 and F6 generations revealed significant correlation between traits like tiller number at 30 days (TN 30), tiller number at 60 days (TN 60), filled grains (FG), percent spikelet fertility (SF%), panicle number (PN) and grain yield per panicle (GYPP) and also association with better yield/performance under low P acidic soil conditions. Through selected genotyping on a set of forty superior and inferior lines using SSR, candidate gene-based and SNP polymorphic markers, 5 genomic regions associated with various yield-related traits were identified. Marker trait association studies revealed 13 markers significantly associated with yield attributing traits and PUE under lowland acidic field conditions. Chi-square and regression analyses of markers run on the entire population identified seven and six markers for SF% and GYPP, respectively, and two for biological yield with positive allele derived from SD which constitute a novel 1.847-Mb region on chromosome 2 flanked by two markers RM12550 and PR9-2. Expression analysis of 7 candidate genes lying within this region across SD, CP and two low P susceptible rice genotypes has revealed that expression of four genes including SPL4, SPL5, ACA9 and MLO8 is significantly upregulated only in SD under low P conditions. In CP, there is low expression of MLO8 under low P conditions, whereas SPL4, SPL5 and Os02g08120 are downregulated. In the case of the two susceptible genotypes, there is no expression of Os02g08120 either in optimum or limiting conditions. Sequence data across a panel of 3024 rice genotypes also suggests that there is polymorphism for these differentially expressed genes. The genes and underlying markers identified on chromosome 2 will be key to imparting tolerance to low P in diverse genetic backgrounds and for marker-assisted selection for higher yield under lowland acidic conditions.

Entities:  

Keywords:  Chi-square test; Mapping population; Marker trait association; Markers; Regression test

Year:  2021        PMID: 33409935     DOI: 10.1007/s13353-020-00601-4

Source DB:  PubMed          Journal:  J Appl Genet        ISSN: 1234-1983            Impact factor:   3.240


  35 in total

1.  OsPHF1 regulates the plasma membrane localization of low- and high-affinity inorganic phosphate transporters and determines inorganic phosphate uptake and translocation in rice.

Authors:  Jieyu Chen; Yu Liu; Jun Ni; Yifeng Wang; Youhuang Bai; Jing Shi; Jian Gan; Zhongchang Wu; Ping Wu
Journal:  Plant Physiol       Date:  2011-07-13       Impact factor: 8.340

2.  Marker-trait association for low-light intensity tolerance in rice genotypes from Eastern India.

Authors:  Suvendhu S Dutta; Wricha Tyagi; Gratify Pale; Judith Pohlong; C Aochen; Avinash Pandey; Arunava Pattanayak; Mayank Rai
Journal:  Mol Genet Genomics       Date:  2018-08-07       Impact factor: 3.291

3.  The alternative respiratory pathway mediates carboxylate synthesis in white lupin cluster roots under phosphorus deprivation.

Authors:  Igor Florez-Sarasa; Hans Lambers; Xing Wang; Patrick M Finnegan; Miquel Ribas-Carbo
Journal:  Plant Cell Environ       Date:  2013-10-28       Impact factor: 7.228

4.  Integrative Comparison of the Role of the PHOSPHATE RESPONSE1 Subfamily in Phosphate Signaling and Homeostasis in Rice.

Authors:  Meina Guo; Wenyuan Ruan; Changying Li; Fangliang Huang; Ming Zeng; Yingyao Liu; Yanan Yu; Xiaomeng Ding; Yunrong Wu; Zhongchang Wu; Chuanzao Mao; Keke Yi; Ping Wu; Xiaorong Mo
Journal:  Plant Physiol       Date:  2015-06-16       Impact factor: 8.340

5.  The protein kinase Pstol1 from traditional rice confers tolerance of phosphorus deficiency.

Authors:  Rico Gamuyao; Joong Hyoun Chin; Juan Pariasca-Tanaka; Paolo Pesaresi; Sheryl Catausan; Cheryl Dalid; Inez Slamet-Loedin; Evelyn Mae Tecson-Mendoza; Matthias Wissuwa; Sigrid Heuer
Journal:  Nature       Date:  2012-08-23       Impact factor: 49.962

6.  In silico characterization, and expression analysis of rice golden 2-like (OsGLK) members in response to low phosphorous.

Authors:  Karma Landup Bhutia; Ernieca Lyngdoh Nongbri; Ebenazar Gympad; Mayank Rai; Wricha Tyagi
Journal:  Mol Biol Rep       Date:  2020-02-21       Impact factor: 2.316

7.  Development and application of gene-based markers for the major rice QTL Phosphorus uptake 1.

Authors:  Joong Hyoun Chin; Xiaochun Lu; Stephan M Haefele; Rico Gamuyao; Abdelbagi Ismail; Matthias Wissuwa; Sigrid Heuer
Journal:  Theor Appl Genet       Date:  2009-12-25       Impact factor: 5.699

8.  Physiological Basis and Transcriptional Profiling of Three Salt-Tolerant Mutant Lines of Rice.

Authors:  Concha Domingo; Eric Lalanne; María M Catalá; Eva Pla; Juan L Reig-Valiente; Manuel Talón
Journal:  Front Plant Sci       Date:  2016-09-28       Impact factor: 5.753

9.  Transcriptome analysis of phosphorus stress responsiveness in the seedlings of Dongxiang wild rice (Oryza rufipogon Griff.).

Authors:  Qian-Wen Deng; Xiang-Dong Luo; Ya-Ling Chen; Yi Zhou; Fan-Tao Zhang; Biao-Lin Hu; Jian-Kun Xie
Journal:  Biol Res       Date:  2018-03-15       Impact factor: 5.612

Review 10.  Molecular Genetics and Breeding for Nutrient Use Efficiency in Rice.

Authors:  Jauhar Ali; Zilhas Ahmed Jewel; Anumalla Mahender; Annamalai Anandan; Jose Hernandez; Zhikang Li
Journal:  Int J Mol Sci       Date:  2018-06-14       Impact factor: 5.923

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