Author
PANDEY, MANISH - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India | |
UPADHYAYA, HARI - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India | |
RATHORE, ABHISHEK - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India | |
VADEZ, VINCENT - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India | |
SHESHSHAYEE, MS - University Of Agricultural Sciences | |
SRISWATHI, MANDA - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India | |
GOVIL, MANSEE - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India | |
KUMAR, ASHISH - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India | |
GOWDA, MVC - University Of Agricultural Sciences | |
SHARMA, SHIVALI - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India | |
HAMIDOU, FALALOU - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - Nigeria | |
KUMAR, V - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India | |
KHERA, PAWAN - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India | |
BHAT, RAMESH - University Of Agricultural Sciences | |
KHAN, AAMIR - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India | |
SINGH, SUBE - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India | |
LI, HONGJIE - Shandong Academy Of Agricultural Sciences | |
MONYO, EMMANUEL - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India | |
NADAF, HL - University Of Agricultural Sciences | |
MUKRI, GANAPATI - University Of Agricultural Sciences | |
JACKSON, SCOTT - University Of Georgia | |
Guo, Baozhu | |
LIANG, XUANQIANG - Guangdong Academy Of Agricultural Sciences | |
VARSHNEY, RAJEEV - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India |
Submitted to: Meeting Abstract
Publication Type: Abstract Only Publication Acceptance Date: 11/8/2014 Publication Date: 11/10/2014 Citation: Pandey, M.K., Upadhyaya, H.D., Rathore, A., Vadez, V., Sheshshayee, M., Sriswathi, M., Govil, M., Kumar, A., Gowda, M., Sharma, S., Hamidou, F., Kumar, V.A., Khera, P., Bhat, R.S., Khan, A.W., Singh, S., Li, H., Monyo, E., Nadaf, H., Mukri, G., Jackson, S.A., Guo, B., Liang, X., Varshney, R.K. 2014. Comprehensive association analysis for 50 agronomic traits in peanut using the "reference set" comprising 300 genotypes from 48 countries of the semi-arid tropics of the world. Meeting Abstract. Advances in Arachis through Genomics and Biotechnology (AAGB) meeting, November 10-14, 2014, Savannah, Georgia. Interpretive Summary: Technical Abstract: Peanut is an important source of nutrition and supports livelihood for millions of small-holder farmers in the semi-arid tropics (SAT) of world. Newly developed peanut cultivars could not yield to its original potential due to several biotic and abiotic stress factors. Under such circumstances, the integration of genomics tools with on-going genetic improvement approaches is expected to facilitate accelerated development of improved cultivars. In this context, high-resolution genotyping and multiple season phenotyping data for 50 important agronomic, disease and quality traits were generated on the ‘reference set’ of peanut. The above data were then subjected to comprehensive analyses for allelic diversity, population structure, linkage disequilibrium (LD) decay and marker-trait association (MTA) in the ‘reference set’. Each genotype of this set can be differentiated with each other using either a unique allele detected by a single SSR or a combination of unique alleles by two or more than two SSRs. The DArT markers (2.0 alleles/locus, 0.125 PIC) showed lower allele frequency and polymorphic information content (PIC) than SSR markers (22.21 alleles /locus, 0.715 PIC). Multi-allelic SSRs identified three sub-groups while the LD simulation trend line based on squared-allele frequency correlations (r2) predicted LD decay of 15-20 cM. Association analysis resulted in identification of 524 highly significant MTAs (p value >2.1x10-6) with wide phenotypic variance range (5.81-90.09%) for 36 traits. These MTAs upon validation may be deployed in genomics-assisted breeding for developing improved peanut cultivars with enhanced resistance/tolerance to different stress and higher pod yield with improved oil/ seed/ nutritional quality. |