Variation and QTL Analysis of Dynamic Tillering in Rice Under Nitrogen and Straw Return Treatments

Yang Shui, Faping Guo, Youlin Peng, Wei Yin, Pan Qi, Yungao Hu () and Shengmin Yan ()
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Yang Shui: Zigong Academy of Agricultural Science, Zigong 643000, China
Faping Guo: Yazhouwan National Laboratory, Sanya 572704, China
Youlin Peng: Yazhouwan National Laboratory, Sanya 572704, China
Wei Yin: Zigong Academy of Agricultural Science, Zigong 643000, China
Pan Qi: School of Life Science and Engineering, Southwest University of Science and Technology, Mianyang 621010, China
Yungao Hu: School of Life Science and Engineering, Southwest University of Science and Technology, Mianyang 621010, China
Shengmin Yan: Zigong Academy of Agricultural Science, Zigong 643000, China

Agriculture, 2025, vol. 15, issue 11, 1-22

Abstract: Rice tillering is an important trait that is genetically and environmentally co-regulated. Nitorgen is one of the key nutrients affecting tillering, and straw return further affects tiller development by altering soil heterogeneity. In order to analyze the genetic regulation mechanism of rice tillering and its interactions with the environment, 124 recombinant inbred line (RIL) populations derived from two superior Peijiu lines, 9311 and PA64s, were used as materials in this study, and the dynamic tillering phenotypes were measured under three treatments (no nitrogen application, nitrogen application, and nitrogen + straw return) for two consecutive years. Using an existing genetic map, we conducted single-environment, multi-environment, and meta-QTL analyses to systematically identify tiller-related genetic loci and their environmental interactions. The main findings were as follows: (1) A total of 57 QTLs were identified in the single-environment QTL analysis, of which 44 were unreported new QTLs. Four QTLs showed temporal pleiotropy, ten QTLs contributed more than 10% to the phenotypes under the no-N treatment, and five QTLs contributed more than 10% under the straw return treatment. Among them, the phenotypic contribution of mks1-355 ( qD1tn1-3 ) and mks1-352 ( qD2TN1-2 ) both exceeded 40%. (2) Multi-environmental QTL analysis detected 15 QTLs. Of these, qmD1TN1 (mks1-356) showed no environmental interaction effect, while qmD1TN12 (mks12-267), qmD2TN1 (mks1-334), qmD2TN3-1 (mks3-105), and qmD5TN6 (mks6-71) exhibited antagonistic pleiotropy, suggesting that these QTL need to be considered for environmental specificity in breeding. (3) Meta-QTL analysis localized 52 MQTLs, of which MQTL3.1 and MQTL6.8 contained 82 and 59 candidate genes, respectively, and no reported tiller-related genes were found. (4) mks1-355 ( qD1tn1-3 ), mks1-352 ( qD2TN1-2 ), and mks1-356 ( qmD1TN1 ) may be located in the same genetic locus, and their phenotypic contributions were more than 40%. These QTLs were detected stably for two consecutive years, and they may be the main effector QTLs in tillering that are less affected by the environment. Further analysis revealed that these QTLs corresponded to MQTL1.6, which contains 56 candidate genes. Of these, the expression level of OsSPL2 gene in the parental line 9311 was significantly higher than that of PA64s, and there were polymorphic differences in the coding region. It was hypothesized that OsSPL2 was the main effector gene of this QTL. This study provides important genetic resources for mining candidate genes related to tillering and nitrogen efficiency in rice and lays a theoretical foundation for directional breeding and molecular marker development in specific environments.

Keywords: rice; dynamic tillering; single-environment QTL analysis; multi-environment QTL analysis; meta-analysis; high nitrogen efficiency (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2025
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