Abstract
Meta-QTL (MQTL) analysis is a robust approach for genetic dissection of complex quantitative traits. Rice varieties adapted to non-flooded cultivation are highly desirable in breeding programs due to the water deficit global problem. In order to identify stable QTLs for major agronomic traits under water deficit conditions, we performed a comprehensive MQTL analysis on 563 QTLs from 67 rice populations published from 2001 to 2019. Yield and yield-related traits including grain weight, heading date, plant height, tiller number as well as root architecture-related traits including root dry weight, root length, root number, root thickness, the ratio of deep rooting and plant water content under water deficit condition were investigated. A total of 61 stable MQTLs over different genetic backgrounds and environments were identified. The average confidence interval of MQTLs was considerably refined compared to the initial QTLs, resulted in the identification of some well-known functionally characterized genes and several putative novel CGs for investigated traits. Ortho-MQTL mining based on genomic collinearity between rice and maize allowed identification of five ortho-MQTLs between these two cereals. The results can help breeders to improve yield under water deficit conditions.
Highlights
Meta-QTL (MQTL) analysis is a robust approach for genetic dissection of complex quantitative traits
In order to discover consensus genomic regions associated with YLD, plant height (PH), tiller number (TN), heading date (HD), grain weight (GW), root dry weight (RDW), root length (RL), root thickness (RT), roots number (RN) and rate of deep rooting (RDR) and some drought tolerance-related traits including drought response index (DRI), relative water content (RWC), canopy temperature (CT), leaf rolling (LR), leaf drying (LD) under water deficit conditions in rice, we compiled a total of 563 QTLs derived from 67 QTL populations (57 studies) reported from 2001 to 2019 (Table 1; Fig. 1A)
Through MQTL analysis this study provides an overview of genomic regions controlling YLD, yield-related traits, root architecture and plant water content including GW, HD, PH, TN, RDW, RL, RT, RN, RDR and drought tolerance (DT) under water deficit conditions in rice
Summary
Meta-QTL (MQTL) analysis is a robust approach for genetic dissection of complex quantitative traits. In order to identify stable QTLs for major agronomic traits under water deficit conditions, we performed a comprehensive MQTL analysis on 563 QTLs from 67 rice populations published from 2001 to 2019. The average confidence interval of MQTLs was considerably refined compared to the initial QTLs, resulted in the identification of some well-known functionally characterized genes and several putative novel CGs for investigated traits. A powerful approach to circumvent this issue is Meta-analysis of QTLs (MQTL), which compiles QTL data from independent studies, locations, years and genetic backgrounds in order to detect stable and reliable Q. An additional benefit of this approach is the reduction of confidence intervals (CIs) in the MQTLs leading to improved genetic resolution for marker-assisted selection (MAS) and identification of candidate genes (CGs). Several MQTL studies for drought stress have been conducted in cereals such as
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