Abstract

Low temperatures dramatically influence spikelets at the booting stage, which is an important factor that greatly reduces grain yield. Mining the genes for grain yield under low temperatures and elucidating the genetic mechanism is a key approach to breeding improved-yield crops. In this study, we generated 190 recombinant inbred lines with 155 SSR markers from a cross between Dongnong422 (a low-temperature-sensitive variety) and Kongyu131 (a low-temperature-tolerant variety). These lines were employed for linkage mapping for yield-component traits under low water temperature and control conditions in two consecutive years. As a result, 18 addition QTLs (A-QTLs) were detected using ICIM, other two analytical methods, CIM (22 A-QTLs) and MICM (8 A-QTLs) were used to demonstrate QTLs ICIM has detected, which showed that all three analytical methods gave a consistency in result. Among these QTLs, 17 QTLs (35.4%) were detected simultaneously under both cold-water-irrigated and control conditions, and these QTLs were most influential (adaptive effect) under the cold-water treatment. Five pleiotropic genomic regions controlling yield were mapped on chromosomes 6, 7, 8 and 11. Among these regions, one of the major regions located, the marker interval RM1306–RM70, was repeatedly detected for panicle length, grains per panicle, primary branch number, secondary branch number and grain density under low-water temperature and control conditions based on three analysis models. Multiple-environment joint analysis showed that nine A-QTLs were detected for seven traits. Thirteen pairs of epistatic QTLs (E-QTLs) were detected for seven traits, but for yield per plant, only seven pairs had significant environmental specificity. The QTLs detected using three analytical models under different environments showed that it is possible to use molecular breeding for cold tolerance, and the markers linked to the QTLs of stable expression could be applied to rice yield improvement in low temperatures.

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