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Genome-wide association study reveals significant genomic regions for improving yield, adaptability of rice under dry direct seeded cultivation condition.
Friday, 2019/06/14 | 07:54:26

Subedi SR1,2,3, Sandhu N1,4, Singh VK5, Sinha P6, Kumar S7, Singh SP8, Ghimire SK2, Pandey M2, Yadaw RB3, Varshney RK6, Kumar A9.

BMC Genomics. 2019 Jun 10;20(1):471. doi: 10.1186/s12864-019-5840-9.

 

Abstract

BACKGROUND:

 

Puddled transplanted system of rice cultivation despite having several benefits, is a highly labor, water and energy intensive system. In the face of changing climatic conditions, a successful transition from puddled to dry direct seeded rice (DDSR) cultivation system looks must in future. Genome-wide association study was performed for traits including, roots and nutrient uptake (14 traits), plant-morphological (5 traits), lodging-resistance (4 traits) and yield and yield attributing traits (7 traits) with the aim to identify significant marker-trait associations (MTAs) for traits enhancing rice adaptability to dry direct-seeded rice (DDSR) system.

 

RESULTS:

 

Study identified a total of 37 highly significant MTAs for 20 traits. The false discovery rate (FDR) ranged from 0.264 to 3.69×10- 4, 0.0330 to 1.25×10- 4, and 0.0534 to 4.60×10-6 in 2015WS, 2016DS and combined analysis, respectively. The percent phenotypic variance (PV) explained by SNPs ranged from 9 to 92%. Among the identified significant MTAs, 15 MTAs associated with the traits including nodal root, root hair length, root length density, stem and culm diameter, plant height and grain yield were reported to be located in the proximity of earlier identified candidate gene. The significant positive correlation of grain-yield with seedling establishment traits, root morphological and nutrient-uptake related traits and grain yield attributing traits pointing towards combining target traits to increase rice yield and adaptability under DDSR. Seven promising progenies with better root morphology, nutrient-uptake and higher grain yield were identified that can further be used in genomics assisted breeding for DDSR varietal development.

 

CONCLUSIONS:

 

Once validated, the identified MTAs and the SNPs linked with trait of interest could be of direct use in genomic assisted breeding (GAB) to improve grain yield and adaptability of rice under DDSR.

 

See: https://www.ncbi.nlm.nih.gov/pubmed/31182016

Fig. 2

Phenotype-Phenotype correlation plot of different seedling establishment, root, grain and grain yield contributing traits considering whole population; a in 2015WS. bin 2016DS. c in combined seasons. d different seedling establishment, root, nutrient uptake, grain and grain yield contributing traits considering 60 progenies (30 high yielding and 30 low grain yielding used for nutrient uptake analysis). The blue color indicates the significant positive correlation and red color indicates the significant negative correlation among different traits. RGR1: relative growth rate from 22 to 15 DAS, RGR2: relative growth rate from 29 to 22 DAS, RGR3: relative growth rate from 29 to 22 DAS, NR1: number of nodal roots at 15 DAS, NR2: number of nodal roots at 22 DAS, NR3: number of nodal roots at 29 DAS, RL1: maximum root length (cm) at 15 DAS, RL2: maximum root length (cm) at 22 DAS, RL3: maximum root length (cm) at 29 DAS, RHL: root hair length, RHD: root hair density, LCC: leaf color chart, SPAD: cholorophyll content, FLL: flag leaf length, FLW: flag leaf width, FLA: flag leaf area, FLAngle: Flag leaf Angle, DTFirst: days to first emergence, DTFull: days to full emergence, SD: stem diameter, CD: culm diameter, BS: bending strength (kg cm), BM: bending moment (kg cm2), PHT: plant height (cm), DTF: days to 50% flowering (days), BMF: biomass at 50% flowering (g), VVG: vegetative vigor score, NPT: number of productive tillers per plant, PL: panicle length (cm), NFG/P: number of filled grains/panicle, 1000GW: 1000 grain weight (g), SY: straw yield (kg ha− 1), GY: grain yield (kg ha− 1), N: nitrogen, P: phosphorus, Fe: iron, Zn: zinc

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