Diversity, Phylogenetic Relationships, And Expression Profiles Of Invertase Inhibitor Genes In Sweetpotato
Acheampong, S.; Sederoff, H.; Olukolu, B. A.; Asare, A.; Yencho, G.
Show abstract
Invertases and their inhibitor proteins are key regulators of carbon allocation in plants. Manipulation of invertase inhibitor (ITI) activity can potentially increase crop yield. The aim of this study was to determine the sequence diversity, phylogenetic relationships, and expression profiles of ITI genes in sweetpotato(Ipomoea batatas).. The coding sequences of two ITI paralogs (SPITI1 and SPITI2) were cloned from two sweetpotato varieties (Beauregard and Jewel) and sequenced. The DNA sequences were used to deduce amino acids sequences and predicted protein properties. Quantitative PCR (qPCR) was carried out to study the expression profiles of the genes at different developmental stages. The results show that introns are absent in both SPITI paralogs. SNPs, Indels, and variable simple sequence repeats (SSR) were present in the SPITI1 paralog, however, only SNPs were identified in the SPITI2 paralog. The predicted SPITI1 protein had 168, 172, or 174 amino acid residues, and molecular weights ranging from 17.88 to 18.38 kDa. In contrast, SPITI2 coded for a protein with 192 amino acid residues, with molecular weight ranging from 20.59 to 20.65 kDa. All conserved domains of ITI proteins were present in both protein isoforms. Phylogenetic analysis indicated that SPITI genes were more closely related to I.trifida and I.triloba than I.nil, thus, suggesting their evolutionary relationship and conservation. A qPCR study indicated that both SPITI genes were expressed in all the sample tissues, though relative expression values differed across tissues at different developmental stages. This is the first study reporting diversity of SPITI genes and of an ~18 kDA isoform in sweetpotato. The findings may enable design of genetic engineering strategies for SPITI genes, including CRISPR/Cas gene editing in sweetpotato.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Structural and functional analysis of genes with potential involvement in resistance to coffee leaf rust: a functional marker based approach 96%
- Mapping and DNA sequence characterisation of the Rysto locus conferring extreme virus resistance to potato cultivar ‘White Lady’ 96%
- Linkage disequilibrium and population structure in a core collection of Brassica napus (L.) 96%
Similar papers in this journal
- Reference-Aided Full-length Transcript Assembly, cDNA Cloning, and Molecular Characterization of 1 Coronatine-insensitive 1b (COI1b) Gene in Coconut (Cocos nucifera L.) 97%
- Genome-wide association links candidate genes to fruit firmness, fruit flesh color, flowering time, and soluble solid content in apricot (Prunus armeniaca) 95%
- Expression analysis of defense-related genes in cucumber (Cucumis sativus L.) against Phytophthora melonis 95%
Similar papers in this journal
- Molecular characterization revealed the role of thaumatin-like proteins in stress response in bread wheat 96%
- Molecular identification and functional analysis of HrpZ2, a new member of harpin superfamily from Pseudomonas syringae inducing hypersensitive response in tobacco. 95%
- A Combinatorial Approach of Biparental QTL Mapping and Genome-Wide Association Analysis Identifies Candidate Genes for Phytophthora Blight Resistance in Sesame 95%
Similar papers in this journal
- Comparative analysis of chloroplast genomes indicated different origin for Indian Tea (Camellia assamica) cv TV-1 as compared to Chinese tea 96%
- BREAKING THE TIGHT GENETIC LINKAGE BETWEEN THE a1 AND sh2 GENES LED TO THE DEVELOPMENT OF ANTHOCYANIN-RICH PURPLE-PERICARP SUPER-SWEETCORN 95%
- Evidence for the Involvement of Vernalization-related Genes in the Regulation of Cold-induced Ripening in 'D'Anjou' and 'Bartlett' Pear Fruit 95%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.