Dataset Information

Multiple Cold Tolerance Trait Phenotyping Reveals Shared Quantitative Trait Loci in Oryza sativa.

ABSTRACT: BACKGROUND:Developing chilling tolerant accessions of domesticated Asian rice is a potential source of significant crop improvement. The uniquely chilling sensitive nature of the tropically originating Oryza sativa make it the most important cereal crop that can gain significantly from improved tolerance to low temperatures. However, mechanisms underlying this complex trait are not fully understood. Oryza sativa has two subspecies with different levels of chilling tolerance, JAPONICA and INDICA, providing an ideal tool to investigate mechanistic differences in the chilling stress tolerance responses within this important crop species. RESULTS:The Rice Diversity Panel 1 (RDP1) was used to investigate a core set of Oryza sativa accessions. The tools available for this panel allowed for a comprehensive analysis of two chilling tolerance traits at multiple temperatures across a 354-cultivar subset of the RDP1. Chilling tolerance trait values were distributed as mostly subpopulation specific clusters of Tolerant, Intermediate, and Sensitive accessions. Genome-wide association study (GWAS) mapping approaches using all 354 accessions yielded a total of 245 quantitative trait loci (QTL), containing 178 unique QTL covering 25% of the rice genome, while 40 QTL were identified by multiple traits. QTL mappings using subsets of rice accession clusters yielded another 255 QTL, for a total of 500 QTL. The genes within these multiple trait QTL were analyzed for Gene Ontology (GO) term and potential pathway enrichments. Terms related to "carbohydrate biosynthesis", "carbohydrate transmembrane transport", "small molecule protein modification", and "plasma membrane" were enriched from this list. Filtering was done to identify more likely candidate pathways involved in conferring chilling tolerance, resulting in enrichment of terms related to "Golgi apparatus", "stress response", "transmembrane transport", and "signal transduction". CONCLUSIONS:Taken together, these GO term clusters revealed a likely involvement of Golgi-mediated subcellular and extracellular vesicle and intracellular carbohydrate transport as a general cold stress tolerance response mechanism to achieve cell and metabolic homeostasis under chilling stress.

SUBMITTER: Shimoyama N

PROVIDER: S-EPMC7427827 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature

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Multiple Cold Tolerance Trait Phenotyping Reveals Shared Quantitative Trait Loci in Oryza sativa.

Shimoyama Naoki N Johnson Melineeh M Beaumont André A Schläppi Michael M

Rice (New York, N.Y.) 20200814 1

<h4>Background</h4>Developing chilling tolerant accessions of domesticated Asian rice is a potential source of significant crop improvement. The uniquely chilling sensitive nature of the tropically originating Oryza sativa make it the most important cereal crop that can gain significantly from improved tolerance to low temperatures. However, mechanisms underlying this complex trait are not fully understood. Oryza sativa has two subspecies with different levels of chilling tolerance, JAPONICA and ...[more]

PMID: 32797316

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Project description:Productivity of rice, world's most important cereal is threatened by high temperature stress, intensified by climate change. Development of heat stress-tolerant varieties is one of the best strategies to maintain its productivity. However, heat stress tolerance is a multigenic trait and the candidate genes are poorly known. Therefore, we aimed to identify quantitative trait loci (QTL) for vegetative stage tolerance to heat stress in rice and the corresponding candidate genes. We used genotyping-by-sequencing to generate single nucleotide polymorphic (SNP) markers and genotype 150 F8 recombinant inbred lines (RILs) obtained by crossing heat tolerant "N22" and heat susceptible "IR64" varieties. A linkage map was constructed using 4,074 high quality SNP markers that corresponded to 1,638 recombinationally unique events in this mapping population. Six QTL for root length and two for shoot length under control conditions with 2.1-12% effect were identified. One QTL rlht5.1 was identified for "root length under heat stress," with 20.4% effect. Four QTL were identified for "root length under heat stress as percent of control" that explained the total phenotypic variation from 5.2 to 8.6%. Three QTL with 5.3-10.2% effect were identified for "shoot length under heat stress," and seven QTL with 6.6-19% effect were identified for "shoot length under heat stress expressed as percentage of control." Among the QTL identified six were overlapping between those identified using shoot traits and root traits: two were overlapping between QTL identified for "shoot length under heat stress" and "root length expressed as percentage of control" and two QTL for "shoot length as percentage of control" were overlapping a QTL each for "root length as percentage of control" and "shoot length under heat stress." Genes coding 1,037 potential transcripts were identified based on their location in 10 QTL regions for vegetative stage heat stress tolerance. Among these, 213 transcript annotations were reported to be connected to stress tolerance in previous research in the literature. These putative candidate genes included transcription factors, chaperone proteins (e.g., alpha-crystallin family heat shock protein 20 and DNAJ homolog heat shock protein), proteases, protein kinases, phospholipases, and proteins related to disease resistance and defense and several novel proteins currently annotated as expressed and hypothetical proteins.

Project description:An attempt was made in the current study to identify the main-effect and co-localized quantitative trait loci (QTLs) for germination and early seedling growth traits under low-temperature stress (LTS) conditions in rice. The plant material used in this study was an early backcross population of 230 introgression lines (ILs) in BCIF7 generation derived from the Weed Tolerant Rice-1 (WTR-1) (as the recipient) and Haoannong (HNG) (as the donor). Genetic analyses of LTS tolerance revealed a total of 27 main-effect quantitative trait loci (M-QTLs) mapped on 12 chromosomes. These QTLs explained more than 10% of phenotypic variance (PV), and average PV of 12.71% while employing 704 high-quality SNP markers. Of these 27 QTLs distributed on 12 chromosomes, 11 were associated with low-temperature germination (LTG), nine with low-temperature germination stress index (LTGS), five with root length stress index (RLSI), and two with biomass stress index (BMSI) QTLs, shoot length stress index (SLSI) and root length stress index (RLSI), seven with seed vigor index (SVI), and single QTL with root length (RL). Among them, five significant major QTLs (qLTG(I) 1 , qLTGS(I) 1-2 , qLTG(I) 5 , qLTGS(I) 5 , and qLTG(I) 7 ) mapped on chromosomes 1, 5, and 7 were associated with LTG and LTGS traits and the PV explained ranged from 16 to 23.3%. The genomic regions of these QTLs were co-localized with two to six QTLs. Most of the QTLs were growth stage-specific and found to harbor QTLs governing multiple traits. Eight chromosomes had more than four QTLs and were clustered together and designated as promising LTS tolerance QTLs (qLTTs), as qLTT 1 , qLTT 2 , qLTT 3 , qLTT 5 , qLTT 6 , qLTT 8 , qLTT 9 , and qLTT 11 . A total of 16 putative candidate genes were identified in the major M-QTLs and co-localized QTL regions distributed on different chromosomes. Overall, these significant genomic regions of M-QTLs are responsible for multiple traits and this suggested that these could serve as the best predictors of LTS tolerance at germination and early seedling growth stages. Furthermore, it is necessary to fine-map these regions and to find functional markers for marker-assisted selection in rice breeding programs for cold tolerance.

Project description:Background:Thousand grain weight is a key component of grain yield in rice, and a trait closely related to grain length (GL) and grain width (GW) that are important traits for grain quality. Causal genes for 16 quantitative trait loci (QTL) affecting these traits have been cloned, but more QTL remain to be characterized for establishing a genetic regulating network. A QTL controlling grain size in rice, qGS10, was previously mapped in the interval RM6100-RM228 on chromosome 10. This study aimed to delimitate this QTL to a more precise location. Method:A total of 12 populations were used. The ZC9 population comprised 203 S 1:2 families derived from a residual heterozygous (RH) plant in the F 9 generation of the indica rice cross Teqing (TQ)/IRBB52, segregating the upper region of RM6100-RM228 and three more regions on chromosomes 1, 9, and 11. The Ti52-1 population comprised 171 S 1 plants derived from one RH plant in F 7 of TQ/IRBB52, segregating a single interval that was in the lower portion of RM6100-RM228. The other ten populations were all derived from Ti52-1, including five S 1 populations with sequential segregating regions covering the target region and five near isogenic line (NIL) populations maintaining the same segregating pattern. QTL analysis for 1,000-grain weight, GL, and GW was performed using QTL IciMapping and SAS procedure GLM. Result:Three QTL were separated in the original qGS10 region. The qGL10.1 was located in the upper region RM6704-RM3773, shown to affect GL only. The qGS10.1 was located within a 207.1-kb interval flanked by InDel markers Te20811 and Te21018, having a stable and relatively high effect on all the three traits analyzed. The qGS10.2 was located within a 1.2-Mb interval flanked by simple sequence repeat markers RM3123 and RM6673. This QTL also affected all the three traits but the effect was inconsistent across different experiments. QTL for grain size were also detected in all the other three segregating regions. Conclusion:Three QTL for grain size that were tightly linked on the long arm of chromosome 10 of rice were separated using NIL populations with sequential segregating regions. One of them, qGS10.1, had a stable and relatively high effect on grain weight, GL, and GW, providing a good candidate for gene cloning. Another QTL, qGS10.2, had a significant effect on all the three traits but the effect was inconsistent across different experiments, providing an example of genotype-by-environmental interaction.

Dataset Information

Multiple Cold Tolerance Trait Phenotyping Reveals Shared Quantitative Trait Loci in Oryza sativa.

Publications

Multiple Cold Tolerance Trait Phenotyping Reveals Shared Quantitative Trait Loci in Oryza sativa.

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