Identification of genomic regions associated with root system architecture in rice using meta˗analysis of QTL

Document Type : Research Paper

Authors

1 Department of Agronomy & Plant Breeding, Faculty of Agriculture and Natural Resources, University of Mohaghegh Ardabili, Ardabil, Iran.

2 Department of Systems Biology, Agricultural Biotechnology Research Institute of Iran (ABRII), Agricultural Research, Education and Extension Organization (AREEO), Karaj, Iran.

Abstract

The root system architecture and the related traits are important factors for moisture uptake from deep soils. Information on QTLs controlling rice root system architecture was collected from the related papers and databases. A genome-wide meta-analysis was conducted on the QTLs using data from 28 independent QTL mapping studies in 38 different rice populations. Among the 312 QTL regions that were mapped on the reference genetic map, 84 and 228 QTL regions were identified under normal moisture conditions and drought stress, respectively. After projection and displaying the QTLs on the reference consensus map, the meta-QTL analysis was performed using BioMercator software version 4.2. A total of 69 significant MQTLs regions were detected on the 12 rice chromosomes. The identified meta-QTL regions included 5-32 initial QTLs and reflecting multiple QTLs for 3-5 traits associated with root architecture. After evaluating the confidence intervals and the number of initial QTLs for each meta-QTL region, 23 meta-QTL regions were selected as the most important ones and the genes located in the MQTL regions were identified. WRKY, ARF, IAA, EXPA, WOX, HOX, YUCCA, RHL and NAC were among the important candidate genes involved in rice root system architecture, which were located in the MQTL regions. Interestingly, 60 MQTLs were co-located with SNP peak positions reported in rice genome-wide association studies (GWAS) for root morphological traits. The promising candidate genes and MQTLs can be used for genetic engineering and MQTL-assisted breeding of root traits to improve yield potential, stability and efficiency in water deficit environments for rice.

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Main Subjects


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