Dataset Information

Integrated RNA-Seq Analysis and Meta-QTLs Mapping Provide Insights into Cold Stress Response in Rice Seedling Roots.

ABSTRACT: Rice (Oryza sativa L.) is a widely cultivated food crop around the world, especially in Asia. However, rice seedlings often suffer from cold stress, which affects their growth and yield. Here, RNA-seq analysis and Meta-QTLs mapping were performed to understand the molecular mechanisms underlying cold tolerance in the roots of 14-day-old seedlings of rice (RPY geng, cold-tolerant genotype). A total of 4779 of the differentially expressed genes (DEGs) were identified, including 2457 up-regulated and 2322 down-regulated DEGs. The GO, COG, KEEG, and Mapman enrichment results of DEGs revealed that DEGs are mainly involved in carbohydrate transport and metabolism, signal transduction mechanisms (plant hormone signal transduction), biosynthesis, transport and catabolism of secondary metabolites (phenylpropanoid biosynthesis), defense mechanisms, and large enzyme families mechanisms. Notably, the AP2/ERF-ERF, NAC, WRKY, MYB, C2H2, and bHLH transcription factors participated in rice's cold-stress response and tolerance. On the other hand, we mapped the identified DEGs to 44 published cold-stress-related genes and 41 cold-tolerant Meta-QTLs regions. Of them, 12 DEGs were the published cold-stress-related genes and 418 DEGs fell into the cold-tolerant Meta-QTLs regions. In this study, the identified DEGs and the putative molecular regulatory network can provide insights for understanding the mechanism of cold stress tolerance in rice. In addition, DEGs in KEGG term-enriched terms or cold-tolerant Meta-QTLs will help to secure key candidate genes for further functional studies on the molecular mechanism of cold stress response in rice.

SUBMITTER: Kong W

PROVIDER: S-EPMC7369714 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

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Integrated RNA-Seq Analysis and Meta-QTLs Mapping Provide Insights into Cold Stress Response in Rice Seedling Roots.

Kong Weilong W Zhang Chenhao C Qiang Yalin Y Zhong Hua H Zhao Gangqing G Li Yangsheng Y

International journal of molecular sciences 20200629 13

Rice (<i>Oryza sativa</i> L.) is a widely cultivated food crop around the world, especially in Asia. However, rice seedlings often suffer from cold stress, which affects their growth and yield. Here, RNA-seq analysis and Meta-QTLs mapping were performed to understand the molecular mechanisms underlying cold tolerance in the roots of 14-day-old seedlings of rice (RPY geng, cold-tolerant genotype). A total of 4779 of the differentially expressed genes (DEGs) were identified, including 2457 up-regu ...[more]

PMID: 32610550

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Project description:UnlabelledCold stress causes various injuries to rice seedlings in low-temperature and high-altitude areas and is therefore an important factor affecting rice production in such areas. In this study, root conductivity (RC) was used as an indicator to map quantitative trait loci (QTLs) of cold tolerance in Oryza rufipogon Griff., Dongxiang wild rice (DX), at its two-leaf stage. The correlation coefficients between RC and the plant survival rate (PSR) at the seedling and maturity stages were -0.85 and -0.9 (P = 0.01), respectively, indicating that RC is a reliable index for evaluating cold tolerance of rice. A preliminary mapping group was constructed from 151 BC2F1 plants using DX as a cold-tolerant donor and the indica variety Nanjing 11 (NJ) as a recurrent parent. A total of 113 codominant simple-sequence repeat (SSR) markers were developed, with a parental polymorphism of 17.3%. Two cold-tolerant QTLs, named qRC10-1 and qRC10-2 were detected on chromosome 10 by composite interval mapping. qRC10-1 (LOD = 3.1, RM171-RM1108) was mapped at 148.3 cM, and qRC10-2 (LOD = 6.1, RM25570-RM304) was mapped at 163.3 cM, which accounted for 9.4% and 32.1% of phenotypic variances, respectively. To fine map the major locus qRC10-2, NJ was crossed with a BC4F2 plant (L188-3), which only carried the QTL qRC10-2, to construct a large BC5F2 fine-mapping population with 13,324 progenies. Forty-five molecular markers were designed to evenly cover qRC10-2, and 10 markers showed polymorphisms between DX and NJ. As a result, qRC10-2 was delimited to a 48.5-kb region between markers qc45 and qc48. In this region, Os10g0489500 and Os10g0490100 exhibited different expression patterns between DX and NJ. Our results provide a basis for identifying the gene(s) underlying qRC10-2, and the markers developed here may be used to improve low-temperature tolerance of rice seedling and maturity stages via marker-assisted selection (MAS).Key messageWith root electrical conductivity used as a cold-tolerance index, the quantitative trait locus qRC10-2 was fine mapped to a 48.5-kb candidate region, and Os10g0489500 and Os10g0490100 were identified as differently expressed genes for qRC10-2.

Project description:The vigorous shoots and roots help to improve drought resistance and post-transplanting recovery in rice seedlings (Oryza sativa L.). Hundreds of loci related to root system have been identified recently, but little research has been done on shoot traits, and the relationship between roots and shoots development is also still unclear. The objective of this study was to identify associated loci for roots and shoots in rice seedlings as well as to screen pleiotropic QTLs involved in coordinated development of roots and shoots. Using mini core collection of 273 cultivated rice accessions and 280 simple-sequence repeat markers, we investigated six traits [root length (RL), root thickness (RT), root weight (RW), shoot length (SL), shoot weight (SW) and ratio of root-to-shoot mass] in seedlings. Study was performed in hydroponic medium and genetic analysis was performed by association mapping using general linear model (GLM) with population structure (Q) and mixed linear model (MLM) involving Q and familial relatedness (K). Two subgroups indica and japonica showed significant differences in RT, RW and SW. Maximum correlation was observed between RW and SW. Using GLM 65 QTLs for root and 43 QTLs associated with shoot traits were detected. Among them, seven QTLs were present between RL and RW and five common QTLs were detected between SL and SW with high phenotypic variation effects (PVEs). Two key pleiotropic QTLs were also identified involved in collaborative development of roots and shoots in rice seedlings. Importantly, 17 and 10 QTLs were identified for root and shoot traits respectively in both studies of GLM and MLM. More common QTLs with high PVEs between root and shoot traits suggested that longitudinal growth (RL and SL) played an important role in accumulation of biomass (RW and SW). Considering the obvious phenotypic differences and fewer common QTLs between indica and japonica, we suggested that there could be different mechanisms of seedling development between both subpopulations. Key pleiotropic QTLs and QTLs identified for root and shoot traits in both studies of GLM and MLM could be preferentially used in marker-assisted breeding for strong rice seedling.

Dataset Information

Integrated RNA-Seq Analysis and Meta-QTLs Mapping Provide Insights into Cold Stress Response in Rice Seedling Roots.

Publications

Integrated RNA-Seq Analysis and Meta-QTLs Mapping Provide Insights into Cold Stress Response in Rice Seedling Roots.

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