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Genome-wide association studies using 50 K rice genic SNP chip unveil genetic architecture for anaerobic germination of deep-water rice population of Assam, India

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Abstract

North Eastern part of India such as Assam is inundated by flood every year where the farmers are forced to grow the traditional tall deep-water rice. Genetic improvement of this type of rice is slow because of insufficient knowledge about their genetic architecture and population structure. In the present investigation, the genetic diversity architecture of 94 deep-water rice genotypes of Assam and association mapping strategy was, for the first time, applied to determine the significant SNPs and genes for deep-water rice. These genotypes are known for their unique elongation ability under deep-water condition. The anaerobic germination (AG) related trait-associated genes identified here can provide affluent resources for rice breeding especially in flood-prone areas. We investigated the genome-wide association studies (GWAS) using 50 K rice genic SNP chip across 94 deep-water rice genotypes collected from different flood-prone districts/villages of Assam. Population structure and diversity analysis revealed that these genotypes were stratified into four sub-populations. Using GWAS approach, 20 significant genes were identified and found to be associated with AG-related traits. Of them, two most relevant genes (OsXDH1and SSXT) have been identified which explain phenotypic variability (R2 > 20%) in the population. These genes were located in Chr 3 (LOC_Os03g31550) which encodes for enzyme xanthine dehydrogenase 1(OsXDH1) and in Chr 12 (LOC_Os12g31350) which encodes for SSXT family protein. Both of these genes were found to be associated with anaerobic response index (increase in the coleoptile length under water in anaerobic condition with respect to control), respectively. Interestingly, OsXDH1is involved in purine catabolism pathway and acts as a scavenger of reactive oxygen species in plants, whereas SSXT is GRF1-interacting factor 3. These two candidate genes associated with AG of deep-water rice have been found to be reported for the first time. Thus, this study provides a greater resource for breeders not only for improvement of deep-water rice, but also for AG tolerant variety useful for direct-seeded rice in flood-affected areas.

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Acknowledgements

The authors are grateful to Department of Biotechnology, New Delhi for financial assistance through DBT-TWIN mode project. The authors are also grateful to Director, ICAR-National Institute for Plant Biotechnology, New Delhi, for providing the facility and. Mr. Mahammed Saba Rahim to provide valuable suggestions for some part of the statistical analysis

Funding

The work was funded by Department of Biotechnology, Govt of India, New Delhi, through a competitive grant number: BT/PR16907/NER/95/345/2015.

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  1. Megha Rohilla and Nisha Singh have contributed equally to this work.

Authors and Affiliations

  1. ICAR-National Institute for Plant Biotechnology, Pusa, New Delhi, 110012, India

    Megha Rohilla, Nisha Singh, Abhishek Mazumder, Nagendra Kumar Singh & Tapan Kumar Mondal

  2. Department of Agricultural Biotechnology, Assam Agricultural University, Jorhat, Assam, India

    Priyabrata Sen & Priyanka Roy

  3. Regional Agricultural Research Station, Assam Agricultural University, North Lakhimpur, Assam, India

    Dhiren Chowdhury

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  1. Megha Rohilla
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Contributions

MR did most of the wet lab experiment, NS did most of the statistical analysis, AM did part of the wet lab experiment and part of statistical analysis, DC did most of the experiment, supplied the seeds of all the genotypes, PS did part of the wet lab experiment, NKS guided the work, and TKM conceived the experiment, wrote majority of the manuscript which was assisted by MR, NS, and AM.

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Correspondence to Tapan Kumar Mondal.

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438_2020_1690_MOESM1_ESM.pptx

Suppl.Fig.S1:Diversity analysis in deep-water rice collections: a) Estimation of rate of heterozygosity using 50K SNP markers, x-axis=Heterozygosity rate, y-axis= number of SNPs, b) Estimation of minor allele frequency (MAF): x-axis=MAF Value, y-axis=number of SNPs (PPTX 56 kb)

438_2020_1690_MOESM2_ESM.pptx

Suppl.Fig.S2: Frequency distribution of SNPs variation in duplicated names of deep-water rice genotypes used in the present study (PPTX 71 kb)

438_2020_1690_MOESM3_ESM.pptx

Suppl.Fig.S3: Genome wide Manhattan plots and Q/Q plots of association mapping for AG using GLM: a) Q/Q plots for germination percentage b) Manhattan plots for germination percentage c) Q/Q plots for survival percentage d) Manhattan plots for survival percentage e) Q/Q plots for anaerobic response index f) Manhattan plots for anaerobic response index. (PPTX 1351 kb)

438_2020_1690_MOESM4_ESM.pptx

Suppl.Fig.S4: Genome wide Manhattan plots and Q/Q plots of association mapping for AG using MLMM: a) Q/Q plots for germination percentage b) Manhattan plots for germination percentage c) Q/Q plots for survival percentage d) Manhattan plots for survival percentage e) Q/Q plots for anaerobic response index f) Manhattan plots for anaerobic response index. (PPTX 1336 kb)

438_2020_1690_MOESM5_ESM.pptx

Suppl.Fig.S5: Genome wide Manhattan plots and Q/Q plots of association mapping for AG using FarmCPU: a) Q/Q plots for germination percentage b) Manhattan plots for germination percentage c) Q/Q plots for survival percentage d) Manhattan plots for survival percentage e) Q/Q plots for anaerobic response index f) Manhattan plots for anaerobic response index. (PPTX 1092 kb)

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Rohilla, M., Singh, N., Mazumder, A. et al. Genome-wide association studies using 50 K rice genic SNP chip unveil genetic architecture for anaerobic germination of deep-water rice population of Assam, India. Mol Genet Genomics 295, 1211–1226 (2020). https://doi.org/10.1007/s00438-020-01690-w

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