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ARS Home » Southeast Area » Tifton, Georgia » Crop Protection and Management Research » Research » Publications at this Location » Publication #311812
Title: Identification of conjoint genomic regions for multiple traits using RIL populations through meta-QTL analysis in peanut

Author
item KHERA, PAWAN - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India
item SHASIDHAR, YADURU - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India
item PANDEY, MANISH - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India
item SRISWATHI, MANDA - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India
item VADEZ, VINCENT - International Crops Research Institute For Semi-Arid Tropics (ICRISAT) - India
item HONG, YANBIN - Guangdong Academy Of Agricultural Sciences
item YU, SHANLIN - Shandong Research Institute
item LIANG, XUANQIANG - Guangdong Academy Of Agricultural Sciences
item LI, HONGJIE - Shandong Research Institute
item Guo, Baozhu
item 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: Khera, P., Shasidhar, Y., Pandey, M.K., Sriswathi, M., Vadez, V., Hong, Y., Yu, S., Liang, X., Li, H., Guo, B., Varshney, R.K. 2014. Identification of conjoint genomic regions for multiple traits using RIL populations through meta-QTL analysis in peanut. Meeting Abstract. Advanced in Arachis through Genomics and Biotechnology (AAGB) meeting, November 10-14, 2014, Savannah, Georgia.

Interpretive Summary:

Technical Abstract: In recent years, several quantitative trait locus (QTL) studies have been conducted for tolerance to drought, resistance to foliar diseases and yield-related traits in peanut. Number as well as position of the identified QTLs for a given trait, however, differed in different studies mainly because of the use of different mapping populations and different kind of markers. For instance, 205 QTLs with varied degree of phenotypic variance (PV) were identified for drought and related traits in three mapping populations (TAG 24 × ICGV 86031, ICGS 76 × CSMG 84-1 and ICGS 44 × ICGS 76). Therefore it is really challenging to target the appropriate QTLs in molecular breeding for improving drought tolerance in peanut. Hence there is need to conjoin the results of these studies to make a better conclusion on number and positions of QTLs for their use in genomic-assisted breeding (GAB). The present study has been planned on combining the QTL information detected in three different RIL populations into a consensus map and identifying important genomic regions through meta-QTL analysis. The meta-QTL analysis confined the earlier identified QTLs to 42 meta-QTLs. Mean confidence interval (CI) of 42 meta-QTLs was found 5.51 cM and mean phenotypic variance of the meta-QTLs was estimated as 7.34%. Interestingly, 16 meta-QTLs harboured more than two component traits. Efforts are underway to collate more QTLs from additional RIL populations. In summary, meta-QTL analysis has redefined the QTL positions irrespective of the genetic background and provided meta-QTLs with more confidence and higher precision for developing superior cultivars through molecular breeding.