| Literature DB >> 35971335 |
Chelliah Anuradha1, Arumugam Chandrasekar1, Suthanthiram Backiyarani1, Subbaraya Uma1.
Abstract
Banana is one of the major food crops and its production is subject to many pests and diseases. Banana breeding exploits wild relatives and progenitor species for the introgression of resistant genes (R) into cultivated varieties to overcome these hurdles. With advances in sequencing technologies, whole-genome sequences are available for many Musa spp. and many of them are potential donors of disease resistance genes. Considering their potential role, R genes from these species were explored to develop an user-friendly open-access database that will be useful for studying and implementing disease resistance in bananas. MusaRgene database is complemented with complete details of 3598 R genes identified from eight Musa spp. and rice, Arabidopsis, sorghum along with its classification and separate modules on its expression under various stresses in resistant and susceptible cultivars and corresponding SSRs are also provided. This database can be regarded as the primary resource of information on R genes from bananas and their relatives. R genes from other allele mining studies are also incorporated which will enable the identification of its homolog in related Musa spp. MusaRgene database will aid in the identification of genes and markers associated, cloning of full-length R genes, and genetic transformation or gene editing of the R genes in susceptible cultivars. Multiple R genes can also be identified for pyramiding the genes to increase the level of resistance and durability. Overall, this database will facilitate the understanding of defense mechanisms in bananas against biotic or abiotic stresses leading to the development of promising disease-resistant varieties. © King Abdulaziz City for Science and Technology 2022, Springer Nature or its licensor holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.Entities:
Keywords: DEG; Database; Musa spp.; MySQL; PHP; R genes; SSR
Year: 2022 PMID: 35971335 PMCID: PMC9374869 DOI: 10.1007/s13205-022-03285-1
Source DB: PubMed Journal: 3 Biotech ISSN: 2190-5738 Impact factor: 2.893