Variation in Rubisco activase (RCAβ) gene promoters and expression in soybean [Glycine max (L.) Merr.]
Author(s) -
Maoni Chao,
Zhitong Yin,
Derong Hao,
Jinyu Zhang,
Haina Song,
Ailing Ning,
Xiaoming Xu,
Deyue Yu
Publication year - 2013
Publication title -
journal of experimental botany
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.616
H-Index - 242
eISSN - 1460-2431
pISSN - 0022-0957
DOI - 10.1093/jxb/ert346
Subject(s) - promoter , biology , rubisco , expression quantitative trait loci , genetics , gene expression , gene , single nucleotide polymorphism , regulation of gene expression , gene isoform , genetic variation , regulatory sequence , genotype
Understanding the genetic basis of Rubisco activase (RCA) gene regulation and altering its expression levels to optimize Rubisco activation may provide an approach to enhance plant productivity. However, the genetic mechanisms and the effect of RCA expression on phenotype are still unknown in soybean. This work analysed the expression of RCA genes and demonstrated that two RCA isoforms presented different expression patterns. Compared with GmRCAα, GmRCAβ was expressed at higher mRNA and protein levels. In addition, GmRCAα and GmRCAβ were positively correlated with chlorophyll fluorescence parameters and seed yield, suggesting that changes in expression of RCA has a potential applicability in breeding for enhanced soybean productivity. To identify the genetic factors that cause expression level variation of GmRCAβ, expression quantitative trait loci (eQTL) mapping was combined with allele mining in a natural population including 219 landraces. The eQTL mapping showed that a combination of both cis- and trans-acting eQTLs might control GmRCAβ expression. As promoters can affect both cis- and trans-acting eQTLs by altering cis-acting regulatory elements or transcription factor binding sites, this work subsequently focused on the promoter region of GmRCAβ. Single-nucleotide polymorphisms in the GmRCAβ promoter were identified and shown to correlate with expression level diversity. These SNPs were classified into two groups, A and B. Further transient expression showed that GUS expression driven by the group A promoter was stronger than that by the group B promoter, suggesting that promoter sequence types could influence gene expression levels. These results would improve understanding how variation within promoters affects gene expression and, ultimately, phenotypic diversity in natural populations.
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