Dataset Information

QTL mapping and transcriptome analysis identify candidate genes regulating pericarp thickness in sweet corn.

ABSTRACT: BACKGROUND:In recent years, the planting area of sweet corn in China has expanded rapidly. Some new varieties with high yields and good adaptabilities have emerged. However, the improvement of edible quality traits, especially through the development of varieties with thin pericarp thickness, has not been achieved to date. Pericarp thickness is a complex trait that is the key factor determining the edible quality of sweet corn. Genetic mapping combined with transcriptome analysis was used to identify candidate genes controlling pericarp thickness. RESULTS:To identify novel quantitative trait loci (QTLs) for pericarp thickness, a sweet corn BC4F3 population of 148 lines was developed using the two sweet corn lines M03 (recurrent parent) and M08 (donor parent). Additionally, a high-density genetic linkage map containing 3876 specific length amplified fragment (SLAF) tags was constructed and used for mapping QTLs for pericarp thickness. Interestingly, 14 QTLs for pericarp thickness were detected, and one stable QTL (qPT10-5) was detected across multiple years, which explained 7.78-35.38% of the phenotypic variation located on chromosome 10 (144,631,242-145,532,401). Forty-two candidate genes were found within the target region of qPT10-5. Moreover, of these 42 genes, five genes (GRMZM2G143402, GRMZM2G143389, GRMZM2G143352, GRMZM6G287947, and AC234202.1_FG004) were differentially expressed between the two parents, as revealed by transcriptome analysis. According to the gene annotation information, three genes might be considered candidates for pericarp thickness. GRMZM2G143352 and GRMZM2G143402 have been annotated as AUX/IAA transcription factor and ZIM transcription factor, respectively, while GRMZM2G143389 has been annotated as FATTY ACID EXPORT 2, chloroplastic. CONCLUSIONS:This study identified a major QTL and candidate genes that could accelerate breeding for the thin pericarp thickness variety of sweet corn, and these results established the basis for map-based cloning and further functional research.

SUBMITTER: Wu X

PROVIDER: S-EPMC7071591 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

QTL mapping and transcriptome analysis identify candidate genes regulating pericarp thickness in sweet corn.

Wu Xiaming X Wang Bo B Xie Fugui F Zhang Liping L Gong Jie J Zhu Wei W Li Xiaoqin X Feng Faqiang F Huang Jun J

BMC plant biology 20200314 1

<h4>Background</h4>In recent years, the planting area of sweet corn in China has expanded rapidly. Some new varieties with high yields and good adaptabilities have emerged. However, the improvement of edible quality traits, especially through the development of varieties with thin pericarp thickness, has not been achieved to date. Pericarp thickness is a complex trait that is the key factor determining the edible quality of sweet corn. Genetic mapping combined with transcriptome analysis was use ...[more]

PMID: 32171234

Similar Datasets

Project description:Low-temperature germination ability (LTGA) is an important characteristic for spring sowing maize. However, few maize genes related to LTGA were confirmed, and the regulatory mechanism is less clear. Here, maize-inbred lines Ye478 and Q1 with different LTGA were used to perform transcriptome analysis at multiple low-temperature germination stages, and a co-expression network was constructed by weighted gene co-expression network analysis (WGCNA). Data analysis showed that 7964 up- and 5010 down-regulated differentially expressed genes (DEGs) of Ye478 were identified at low-temperature germination stages, while 6060 up- and 2653 down-regulated DEGs of Q1 were identified. Gene ontology (GO) enrichment analysis revealed that ribosome synthesis and hydrogen peroxide metabolism were enhanced and mRNA metabolism was weakened under low-temperature stress for Ye478, while hydrogen peroxide metabolism was enhanced and mRNA metabolism was weakened for Q1. DEGs pairwise comparisons between the two genotypes found that Ye478 performed more ribosome synthesis at low temperatures compared with Q1. WGCNA analysis based on 24 transcriptomes identified 16 co-expressed modules. Of these, the MEbrown module was highly correlated with Ye478 at low-temperature stages and catalase and superoxide dismutase activity, and the MEred, MEgreen, and MEblack modules were highly correlated with Ye478 across low-temperature stages, which revealed a significant association between LTGA and these modules. GO enrichment analysis showed the MEbrown and MEred modules mainly functioned in ribosome synthesis and cell cycle, respectively. In addition, we conducted quantitative trait loci (QTL) analysis based on a doubled haploid (DH) population constructed by Ye478 and Q1 and identified a major QTL explanting 20.6% of phenotype variance on chromosome 1. In this QTL interval, we found three, four, and three hub genes in the MEbrown, MEred, and MEgreen modules, of which two hub genes (Zm00001d031951, Zm00001d031953) related to glutathione metabolism and one hub gene (Zm00001d031617) related to oxidoreductase activity could be the candidate genes for LTGA. These biological functions and candidate genes will be helpful in understanding the regulatory mechanism of LTGA and the directional improvement of maize varieties for LTGA.

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 transcriptome analysis identify candidate genes regulating pericarp thickness in sweet corn.

Publications

QTL mapping and transcriptome analysis identify candidate genes regulating pericarp thickness in sweet corn.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets