Understanding genetic control of drought tolerance through meta-QTL analysis for genomics-assisted improvement of drought tolerance in peanut (Arachis hypogaeaL.)

Authors: KHERA, PAWAN - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India; SHASIDHAR, Y - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India; PANDEY, MANISH - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India; SRISWATHI, MANDA - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India; VADEZ, VINCENT - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India; YU, SHAN - Shandong Peanut Research Institute; ISOBE, SACHIKO - Kazusa Dna Research Institute; Guo, Baozhu; VARSHNEY, RAJEEV - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India

Submitted to: Meeting Proceedings
Publication Type: Proceedings
Publication Acceptance Date: 5/1/2013
Publication Date: 6/17/2013
Citation: Khera, P., Shasidhar, Y., Pandey, M.K., Sriswathi, M., Vadez, V., Yu, S.L., Isobe, S., Guo, B., Varshney, R.K. 2013. Understanding genetic control of drought tolerance through meta-QTL analysis for genomics-assisted improvement of drought tolerance in peanut (Arachis hypogaeaL.). Proceedings of the Sixth International Conference of the Peanut Research Community, Advances in Arachis through Genomics & Biotechnology, June 17-21, 2013, Zhengzhou, China.

Interpretive Summary: Majority of peanut is cultivated in the semi-arid tropical regions of the world where abiotic stresses especially drought is a major constraint for crop production. With an objective of undertaking molecular breeding approaches for developing superior lines with enhanced drought tolerance, several QTL mapping studies involving many mapping populations were undertaken in the recent past. As a result, hundreds of QTLs with 2.51 to 40.10% phenotypic variation for a number of drought tolerance related traits were identified. It is nearly impossible to transfer all these QTLs from different donor lines into a single genetic background. Furthermore, QTLs for the same phenotype can have different expression under different environments due to large and variable G × E interaction. Therefore, meta-QTL analysis has been undertaken to identify consistent/ stable QTLs expressing across different genetic background and environments. Meta-QTL analysis, conducted using 205 individual QTL reported previously in three mapping populations (TAG 24 × ICGV 86031, ICGS 76 × CSMG 84-1 and ICGS 44 × ICGS 76), resulted in the identification of 42 meta-QTL for drought tolerance related traits. Mean confidence interval (CI) of 42 meta-QTLs was 5.51 cM and mean phenotypic variance was 7.34%. Interestingly, 16 meta-QTLs harbour more than two component traits. In summary, the information generated through meta-QTL analysis for drought tolerance would be useful in elucidating the genetic control of the trait as well as identify the candidate markers for deploying genomic-assisted breeding for developing superior lines with enhanced drought tolerance.

Technical Abstract: Majority of peanut is cultivated in the semi-arid tropical regions of the world where abiotic stresses especially drought is a major constraint for crop production. With an objective of undertaking molecular breeding approaches for developing superior lines with enhanced drought tolerance, several QTL mapping studies involving many mapping populations were undertaken in the recent past. As a result, hundreds of QTLs with 2.51 to 40.10% phenotypic variation for a number of drought tolerance related traits were identified. It is nearly impossible to transfer all these QTLs from different donor lines into a single genetic background. Furthermore, QTLs for the same phenotype can have different expression under different environments due to large and variable G × E interaction. Therefore, meta-QTL analysis has been undertaken to identify consistent/ stable QTLs expressing across different genetic background and environments. Meta-QTL analysis, conducted using 205 individual QTL reported previously in three mapping populations (TAG 24 × ICGV 86031, ICGS 76 × CSMG 84-1 and ICGS 44 × ICGS 76), resulted in the identification of 42 meta-QTL for drought tolerance related traits. Mean confidence interval (CI) of 42 meta-QTLs was 5.51 cM and mean phenotypic variance was 7.34%. Interestingly, 16 meta-QTLs harbour more than two component traits. In summary, the information generated through meta-QTL analysis for drought tolerance would be useful in elucidating the genetic control of the trait as well as identify the candidate markers for deploying genomic-assisted breeding for developing superior lines with enhanced drought tolerance.