Dataset Information

QTL mapping and candidate gene analysis for yield and grain weight/size in Tartary buckwheat.

ABSTRACT:

Background

Grain weight/size influences not only grain yield (GY) but also nutritional and appearance quality and consumer preference in Tartary buckwheat. The identification of quantitative trait loci (QTLs)/genes for grain weight/size is an important objective of Tartary buckwheat genetic research and breeding programs.

Results

Herein, we mapped the QTLs for GY, 1000-grain weight (TGW), grain length (GL), grain width (GW) and grain length-width ratio (L/W) in four environments using 221 recombinant inbred lines (XJ-RILs) derived from a cross of 'Xiaomiqiao × Jinqiaomai 2'. In total, 32 QTLs, including 7 for GY, 5 for TGW, 6 for GL, 11 for GW and 3 for L/W, were detected and distributed in 24 genomic regions. Two QTL clusters, qClu-1-3 and qClu-1-5, located on chromosome Ft1, were revealed to harbour 7 stable major QTLs for GY (qGY1.2), TGW (qTGW1.2), GL (qGL1.1 and qGL1.4), GW (qGW1.7 and qGW1.10) and L/W (qL/W1.2) repeatedly detected in three and above environments. A total of 59 homologues of 27 known plant grain weight/size genes were found within the physical intervals of qClu-1-3 and qClu-1-5. Six homologues, FtBRI1, FtAGB1, FtTGW6, FtMADS1, FtMKK4 and FtANT, were identified with both non-synonymous SNP/InDel variations and significantly differential expression levels between the two parents, which may play important roles in Tatary buckwheat grain weight/size control and were chosen as core candidate genes for further investigation.

Conclusions

Two stable major QTL clusters related to grain weight/size and six potential key candidate genes were identified by homology comparison, SNP/InDel variations and qRT‒qPCR analysis between the two parents. Our research provides valuable information for improving grain weight/size and yield in Tartary buckwheat breeding.

SUBMITTER: Li R

PROVIDER: S-EPMC9878770 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

QTL mapping and candidate gene analysis for yield and grain weight/size in Tartary buckwheat.

Li Ruiyuan R Chen Zhengfeng Z Zheng Ran R Chen Qingfu Q Deng Jiao J Li Hongyou H Huang Juan J Liang Chenggang C Shi Taoxiong T

BMC plant biology 20230126 1

<h4>Background</h4>Grain weight/size influences not only grain yield (GY) but also nutritional and appearance quality and consumer preference in Tartary buckwheat. The identification of quantitative trait loci (QTLs)/genes for grain weight/size is an important objective of Tartary buckwheat genetic research and breeding programs.<h4>Results</h4>Herein, we mapped the QTLs for GY, 1000-grain weight (TGW), grain length (GL), grain width (GW) and grain length-width ratio (L/W) in four environments u ...[more]

PMID: 36703107

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Project description:BackgroundTartary buckwheat (Fagopyrum tataricum), an important pseudocereal crop, has high economic value due to its nutritional and medicinal properties. However, dehulling of Tartary buckwheat is difficult owing to its thick and tough hull, which has greatly limited the development of the Tartary buckwheat processing industry. The construction of high-resolution genetic maps serves as a basis for identifying quantitative trait loci (QTLs) and qualitative trait genes for agronomic traits. In this study, a recombinant inbred lines (XJ-RILs) population derived from a cross between the easily dehulled Rice-Tartary type and Tartary buckwheat type was genotyped using restriction site-associated DNA (RAD) sequencing to construct a high-density SNP genetic map. Furthermore, QTLs for 1000-grain weight (TGW) and genes controlling hull type were mapped in multiple environments.ResultsIn total, 4151 bin markers comprising 122,185 SNPs were used to construct the genetic linkage map. The map consisted of 8 linkage groups and covered 1444.15 cM, with an average distance of 0.35 cM between adjacent bin markers. Nine QTLs for TGW were detected and distributed on four loci on chromosome 1 and 4. A major locus detected in all three trials was mapped in 38.2-39.8 cM region on chromosome 1, with an LOD score of 18.1-37.0, and explained for 23.6-47.5% of the phenotypic variation. The genes controlling hull type were mapped to chromosome 1 between marker Block330 and Block331, which was closely followed by the major locus for TGW. The expression levels of the seven candidate genes controlling hull type present in the region between Block330 and Block336 was low during grain development, and no significant difference was observed between the parental lines. Six non-synonymous coding SNPs were found between the two parents in the region.ConclusionsWe constructed a high-density SNP genetic map for the first time in Tartary buckwheat. The mapped major loci controlling TGW and hull type will be valuable for gene cloning and revealing the mechanism underlying grain development and easy dehulling, and marker-assisted selection in Tartary buckwheat.

Project description:BackgroundCastor (Ricinus communis L., 2n = 2x = 20) is an important industrial crop, due to its oil is very important to the global special chemical industry. Seed size and seed weight are fundamentally important in determining castor yield, while little is known about it. In this study, QTL analysis and candidate gene mining of castor seed size and seed weight were conducted with composite interval mapping (CIM), inclusive composite interval mapping (ICIM) and marker enrichment strategy in 4 populations, i.e., populations F2, BC1, S1-1 and S1-2, derived from 2 accessions with significant phenotypic differences.ResultsIn the QTL primary mapping, 2 novel QTL clusters were detected in marker intervals RCM520-RCM76 and RCM915-RCM950. In order to verify their accuracy and to narrow their intervals, QTL remapping was carried out in populations F2 and BC1. Among them, 44 and 30 QTLs underlying seed size and seed weight were detected in F2 population using methods CIM and ICIM-ADD respectively, including 4-9 and 3-5 ones conferring each trait were identified with a phenotypic variation explained ranged from 37.92 to 115.81% and 32.86-45.98% respectively. The remapping results in BC1 population were consistent with those in F2 population. Importantly, 3 QTL clusters (i.e. QTL-cluster1, QTL-cluster2 and QTL-cluster3) were found in marker intervals RCM74-RCM76 (37.1 kb), RCM930-RCM950 (259.8 kb) and RCM918-RCM920 (172.9 kb) respectively; in addition, all of them were detected again, the former one was found in the S1-2 population, and the latter two were found simultaneously in the populations S1-1 and S1-2. Finally, 6 candidate genes (i.e. LOC8266555, LOC8281168, LOC8281151, LOC8259066, LOC8258591 and LOC8270077) were screened in the above QTL clusters, they were differentially expressed in multiple seed tissues of both parents, signifying the potential role in regulating seed size and seed weight.ConclusionThe above results not only provide new insights into the genetic structure of seed size and seed weight in castor, but also lay the foundation for the functional identification of these candidate genes.

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Project description:Development and use of genome-wide informative simple sequence repeat (SSR) markers and novel integrated genomic strategies are vital to drive genomics-assisted breeding applications and for efficient dissection of quantitative trait loci (QTLs) underlying complex traits in rice. The present study developed 6244 genome-wide informative SSR markers exhibiting in silico fragment length polymorphism based on repeat-unit variations among genomic sequences of 11 indica, japonica, aus, and wild rice accessions. These markers were mapped on diverse coding and non-coding sequence components of known cloned/candidate genes annotated from 12 chromosomes and revealed a much higher amplification (97%) and polymorphic potential (88%) along with wider genetic/functional diversity level (16-74% with a mean 53%) especially among accessions belonging to indica cultivar group, suggesting their utility in large-scale genomics-assisted breeding applications in rice. A high-density 3791 SSR markers-anchored genetic linkage map (IR 64 × Sonasal) spanning 2060 cM total map-length with an average inter-marker distance of 0.54 cM was generated. This reference genetic map identified six major genomic regions harboring robust QTLs (31% combined phenotypic variation explained with a 5.7-8.7 LOD) governing grain weight on six rice chromosomes. One strong grain weight major QTL region (OsqGW5.1) was narrowed-down by integrating traditional QTL mapping with high-resolution QTL region-specific integrated SSR and single nucleotide polymorphism markers-based QTL-seq analysis and differential expression profiling. This led us to delineate two natural allelic variants in two known cis-regulatory elements (RAV1AAT and CARGCW8GAT) of glycosyl hydrolase and serine carboxypeptidase genes exhibiting pronounced seed-specific differential regulation in low (Sonasal) and high (IR 64) grain weight mapping parental accessions. Our genome-wide SSR marker resource (polymorphic within/between diverse cultivar groups) and integrated genomic strategy can efficiently scan functionally relevant potential molecular tags (markers, candidate genes and alleles) regulating complex agronomic traits (grain weight) and expedite marker-assisted genetic enhancement in rice.

Dataset Information

QTL mapping and candidate gene analysis for yield and grain weight/size in Tartary buckwheat.

Background

Results

Conclusions

Publications

QTL mapping and candidate gene analysis for yield and grain weight/size in Tartary buckwheat.

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