Mapping QTLs for chlorophyll content and chlorophyll fluorescence in wheat under heat stress

Bhusal, Nabin; Sharma, Pradeep; Sareen, Sindhu; Sarial, A. K.

doi:10.1007/s10535-018-0811-6

Cited by 41 publications

(20 citation statements)

References 44 publications

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“…Talukder et al [43] located eight QTLs in wheat using CC after thermal stress. Bhusal et al [44] used chlorophyll content and chlorophyll fluorescence parameters to identify 17 and 23 QTLs related to wheat heat tolerance in a recombinant inbred line (RIL) population, respectively. These results indicated that it is feasible to map QTLs using physiological indexes related to target traits.…”

Section: Discussionmentioning

confidence: 99%

Identification of heat-tolerance QTLs and high-temperature stress-responsive genes through conventional QTL mapping, QTL-seq and RNA-seq in tomato

et al. 2019

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Background High temperature is one of the major abiotic stresses in tomato and greatly reduces fruit yield and quality. Identifying high-temperature stress-responsive (HSR) genes and breeding heat-tolerant varieties is an effective way to address this issue. However, there are few reports on the fine mapping of heat-tolerance quantitative trait locus (QTL) and the identification of HSR genes in tomato. Here, we applied three heat tolerance-related physiological indexes, namely, relative electrical conductivity (REC), chlorophyll content (CC) and maximum photochemical quantum efficiency (Fv/Fm) of PSII (photosystem II), as well as the phenotypic index, the heat injury index (HII), and conventional QTL analysis combined with QTL-seq technology to comprehensively detect heat-tolerance QTLs in tomato seedlings. In addition, we integrated the QTL mapping results with RNA-seq to identify key HSR genes within the major QTLs. Results A total of five major QTLs were detected: qHII-1-1, qHII-1-2, qHII-1-3, qHII-2-1 and qCC-1-5 (qREC-1-3). qHII-1-1, qHII-1-2 and qHII-1-3 were located, respectively, in the intervals of 1.43, 1.17 and 1.19 Mb on chromosome 1, while the interval of qHII-2-1 was located in the intervals of 1.87 Mb on chromosome 2. The locations observed with conventional QTL mapping and QTL-seq were consistent. qCC-1-5 and qREC-1-3 for CC and REC, respectively, were located at the same position by conventional QTL mapping. Although qCC-1-5 was not detected in QTL-seq analysis, its phenotypic variation (16.48%) and positive additive effect (0.22) were the highest among all heat tolerance QTLs. To investigate the genes involved in heat tolerance within the major QTLs in tomato, RNA-seq analysis was performed, and four candidate genes (SlCathB2, SlGST, SlUBC5, and SlARG1) associated with heat tolerance were finally detected within the major QTLs by DEG analysis, qRT-PCR screening and biological function analysis. Conclusions In conclusion, this study demonstrated that the combination of conventional QTL mapping, QTL-seq analysis and RNA-seq can rapidly identify candidate genes within major QTLs for a complex trait of interest to replace the fine-mapping process, thus greatly shortening the breeding process and improving breeding efficiency. The results have important applications for the fine mapping and identification of HSR genes and breeding for improved thermotolerance.

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Section: Discussionmentioning

confidence: 99%

Identification of heat-tolerance QTLs and high-temperature stress-responsive genes through conventional QTL mapping, QTL-seq and RNA-seq in tomato

et al. 2019

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“…Using the DH population derived from the cross of Hanxuan 10 × Lumai 14, Shi, et al [44] found two QTL for Chl content at flowering and grain-filling stage on chromosome 7A with 7.32 and 8.36% of phenotypic variation, respectively, and Yang, et al [45] detected a QTL for Chl content in the interval Xwmc488 - P2071–180 on chromosome 7A under water deficient. Bhusal, et al [46] also reported a QTL for Chl a content on chromosome 7A close to the marker Xwmc388 under heat stress. Ilyas, et al [47] mapped a QTL for total Chl content on 7A flanked by Xbarc49 and Xgdm14 .…”

Section: Discussionmentioning

confidence: 99%

“…3b). Based on the common wheat consensus maps [50, 51], TaPPH-7A is considered to be near to the centromere, but is far from markers Xwmc488 and P2071–180 [45], Xwmc388 [46], Xbarc49 and Xgdm14 [47], Xcfa2257 [48], and Xgwm282 [49]. Thus, TaPPH-7A was likely a novel locus related to Chl content and TGW on chromosome 7A.…”

Section: Discussionmentioning

confidence: 99%

Identification of TaPPH-7A haplotypes and development of a molecular marker associated with important agronomic traits in common wheat

Wang

Chang

et al. 2019

BMC Plant Biol

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Background Premature senescence of flag leaf severely affects wheat yield and quality. Chlorophyll (Chl) degradation is the most obvious symptom during leaf senescence and catalyzed by a series of enzymes. Pheophytin pheophorbide hydrolase (Pheophytinase, PPH) gene encodes a Chl degradation hydrolase. Results In this study, the coding, genomic and promoter sequences of wheat TaPPH-A gene were cloned. The corresponding lengths were 1467 bp, 4479 bp and 3666 bp, respectively. Sequence structure analysis showed that TaPPH-A contained five exons and four introns. After the multiple sequences alignment of TaPPH-A genome from 36 accessions in a wheat diversity panel, four SNPs and one 2-bp InDel were observed, which formed two haplotypes, TaPPH-7A-1 and TaPPH-7A-2 . Based on the SNP at 1299 bp (A/G), a molecular marker TaPPH-7A -dCAPS was developed to distinguish allelic variation (A/G). Using the molecular markers, 13 SSR, and 116 SNP markers, a linkage map of chromosome 7A were integrated. TaPPH-A was mapped on the chromosome region flanked by Xwmc9 (0.94 cM) and AX-95634545 (1.04 cM) on 7A in a DH population. Association analysis between TaPPH-7A allelic variation and agronomic traits found that TaPPH-7A was associated with TGW in 11 of 12 environments and Chl content at grain-filling stage under drought stress using Population 1 consisted of 323 accessions. The accessions possessed TaPPH-7A-1 (A) had higher TGW and Chl content than those possessed TaPPH-7A-2 (G), thus TaPPH-7A-1 (A) was a favorable allelic variation. By analyzing the frequency of favorable allelic variation TaPPH-7A-1 (A) in Population 2 with 157 landraces and Population 3 with 348 modern cultivars, we found it increased from pre-1950 (0) to 1960s (54.5%), then maintained a relatively stable level about 56% from 1960s to 1990s. Conclusion These results suggested the favorable allelic variation TaPPH-7A-1 (A) should be valuable in enhancing grain yield by improving the source (chlorophyll content) and sink (the developing grain) simultaneously. Furthermore, the newly developed molecular marker TaPPH-7A -dCAPS could be integrated into a breeding kit of screening high TGW wheat for marker-assisted selection. Electronic supplementary material The online version of this article (10.1186/s12870-019-1901-0) contains supplementary material, which is available to authorized users.

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“…MTAs were identified for chla and chlb separately and also for total chlorophyll content on chromosomes 2BS and 3BL with the main association on 2BS at ~150Mbp being present in all measurements which could be a result of the mostly overlapping absorbance spectra of the two pigments 45 . A QTL has been identified for chlorophyll content on 2BS under heat stress, spanning nearly the entire short arm of the chromosome 46 , using ultra-high density genotyping we are able to reduce this to an interval of <5Mbp. Within this interval we identify Early Chloroplast Biogenesis 2 (ECB1)/Vanilla Cream 1 (VAC1), a pentatricopeptide repeat protein with arabidopsis mutants in the gene reducing chlorophyll content by 10 fold 47,48 .…”

Section: Using High Density Genotyping and High-throughput Phenotypinmentioning

confidence: 99%

Uncovering candidate genes involved in photosynthetic capacity using unexplored genetic variation in Spring Wheat

Joynson

Molero

Coombes

et al. 2020

Preprint

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To feed an ever-increasing population we must leverage advances in genomics and phenotyping to harness the variation in wheat breeding populations for traits like photosynthetic capacity which remains unoptimized. Here we survey a diverse set of wheat germplasm containing elite, introgression and synthetic derivative lines uncovering previously uncharacterised variation. We demonstrate how strategic integration of exotic material alleviates the D genome genetic bottleneck in wheat, increasing SNP rate by 62% largely due to Ae. tauschii synthetic wheat donors. Across the panel, 67% of the Ae.tauschii donor genome is represented as introgressions in elite backgrounds. We show how observed genetic variation together with hyperspectral reflectance data can be used to identify candidate genes for traits relating to photosynthetic capacity using association analysis. This demonstrates the value of genomic methods in uncovering hidden variation in wheat and how that variation can assist breeding efforts and increase our understanding of complex traits.

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Mapping QTLs for chlorophyll content and chlorophyll fluorescence in wheat under heat stress

Cited by 41 publications

References 44 publications

Identification of heat-tolerance QTLs and high-temperature stress-responsive genes through conventional QTL mapping, QTL-seq and RNA-seq in tomato

Identification of heat-tolerance QTLs and high-temperature stress-responsive genes through conventional QTL mapping, QTL-seq and RNA-seq in tomato

Identification of TaPPH-7A haplotypes and development of a molecular marker associated with important agronomic traits in common wheat

Uncovering candidate genes involved in photosynthetic capacity using unexplored genetic variation in Spring Wheat

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