{'fraction_non_alphanumeric': 0.03287671232876712, 'fraction_numerical': 0.03744292237442922, 'mean_word_length': 5.137254901960785, 'pattern_counts': {'":': 0, '<': 1, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Genome-Wide Association Study (GWAS) For Cold Tolerance at The Bud Burst Stage in Rice Using SNP Markers


 Background: Rice is a crop that is very sensitive to low temperature, and its morphological development and production are greatly affected by low temperature. Therefore, understanding the genetic basis of cold tolerance in rice is of great significance for mining favorable genes and cultivating excellent rice varieties. However, there were limited studies focusing on cold tolerance at the bud burst stage, therefore, considerable attention should be paid to the genetic basis of cold tolerance at the bud burst stage (CTBB).Results: In this study, a natural population consisting of 211 rice landraces collected from 15 provinces of China and other countries were firstly used to evaluate the cold tolerance at the bud burst stage. Population structure analysis showed that this population divided into three groups and was rich in genetic diversity. Our evaluation results confered that the japonica rice was more tolerance to cold at the bud burst stage than indica rice. Genome-wide association study (GWAS) were performed through the phenotypic data of 211 rice landraces and 36,727 SNPs dataset under a mixed linear model, and 12 QTLs (P < 0.0001) were identified according to the seedling survival rate (SSR) treated at 4 ℃, in which there are five QTLs (qSSR2-2, qSSR3-1, qSSR3-2, qSSR3-3 and qSSR9) which were co-located with previous studies, and seven QTLs (qSSR2-1, qSSR3-4, qSSR3-5, qSSR3-6, qSSR3-7, qSSR4 and qSSR7) which were reported for the first time. Among these QTLs, qSSR9, harboring the highest-peak SNP, explained biggest phenotypic variation. Through bioinformatics analysis, five genes (LOC_Os09g12440, LOC_Os09g12470, LOC_Os09g12520, LOC_Os09g12580 and LOC_Os09g12720) were nominated as candidates for qSSR9. Conclusion: This natural population consisting of 211 rice landraces with high density SNPs will serve as a better choice for identifying rice QTLs/genes in future, and the detected QTLs associated with cold tolerance in rice bud burst stage will be conducive to further mining favorable genes and breeding of rice varieties under cold stress.