Expansin gene family database: A comprehensive bioinformatics resource for plant expansin multigene family

• Published in: Journal of bioinformatics and computational biology Vol. 21; no. 3; p. 2350015
• Main Authors: Kök, Büşra Özkan, Celik Altunoglu, Yasemin, Öncül, Ali Burak, Karaci, Abdulkadir, Cengiz Baloglu, Mehmet
• Format: Journal Article
• Language: English
• Published: Singapore 01.06.2023
• Subjects: Amino Acid Sequence; Computational Biology; Gene Expression Regulation, Plant; Genes, Plant; Multigene Family; Plant Proteins - genetics; Plant Proteins - metabolism; Plants - genetics; deep learning; Expansin gene family; characterization; plants; bioinformatics; blast
• ISSN: 1757-6334
• DOI: 10.1142/S0219720023500154

Expansins, which are plant cell wall loosening proteins associated with cell growth, have been identified as a multigene family. Plant expansin proteins are an important family that functions in cell growth and many of developmental processes including wall relaxation, fruit softening, abscission, seed germination, mycorrhiza and root nodule formation, biotic and abiotic stress resistance, invasion of pollen tube stigma and organogenesis. In addition, it is thought that increasing the efficiency of plant expansin genes in plants plays a significant role, especially in the production of secondary bioethanol. When the studies on the expansin genes are examined, it is seen that the expansin genes are a significant gene family in the cell wall expansion mechanism. Therefore, understanding the efficacy of expansin genes is of great importance. Considering the importance of this multigene family, we aimed to create a comprehensively informed database of plant expansin proteins and their properties. The expansin gene family database provides comprehensive online data for the expansin gene family members in the plants. We have designed a new website accessible to the public, including expansin gene family members in 70 plants and their features including gene, coding and peptide sequences, chromosomal location, amino acid length, molecular weight, stability, conserved motif and domain structure and predicted three-dimensional architecture. Furthermore, a deep learning system was developed to detect unknown genes belonging to the expansin gene family. In addition, we provided the blast process within the website by establishing a connection to the NCBI BLAST site in the tools section. Thus, the expansin gene family database becomes a useful database for researchers that enables access to all datasets simultaneously with its user-friendly interface. Our server can be reached freely at the following link (http://www.expansingenefamily.com/).