| Literature DB >> 32205931 |
Muhammad Bilal Sarwar1, Zarnab Ahmad1,2, Batcho Agossa Anicet1, Moon Sajid1, Bushra Rashid1, Sameera Hassan1, Mukhtar Ahmed1, Tayyab Husnain1.
Abstract
The adaptive mechanisms in Agave species enable them to survive and exhibit remarkable tolerance to abiotic stresses. Quantitative real-time PCR is a highly reliable approach for validation of targeted differential gene expression. However, stable housekeeping gene(s) is prerequisite for accurate normalization of expression data by qRT-PCR. Till date, no systematic validation study for candidate housekeeping gene identification or evaluation has been carried-out in Agave species. A total of 17 candidate housekeeping genes were identified from the de novo assembled transcriptomic data of A. sisalana and rigorously analyzed for expression stability assessment under drought, heat, cold and NaCl stress. Different statistical algorithms like geNorm, BestKeeper, NormFinder, and RefFinder on expression data determined the superior housekeeping gene(s) for accurate normalization of the gene of interest (GOI). The comprehensive evaluation revealed the β-Tub 4, WIN-1 and CYC-A as the most stable, while EEF1α, GAPDH, and UBE2 were ranked as the least stable genes in pooled samples. Pairwise combination by geNorm showed that up to two housekeeping genes would be adequate to normalize the GOI expression data precisely. Validation of identified most and least stable housekeeping genes was carried-out by normalizing the expression data of AsHSP20 under abiotic stress conditions. Copy number of AsHSP20 gene supports the reliability of the genes used for normalization. This is the first report on the screening and validation of the housekeeping genes under abiotic stress condition in A. sisalana that would assist to understand the stress tolerance mechanisms by novel gene identification and accurate validation. © Prof. H.S. Srivastava Foundation for Science and Society 2020.Entities:
Keywords: Abiotic stresses; Agave sisalana; Data normalization; Housekeeping genes; Quantitative real-time PCR; Relative absolute quantification
Year: 2020 PMID: 32205931 PMCID: PMC7078421 DOI: 10.1007/s12298-020-00760-y
Source DB: PubMed Journal: Physiol Mol Biol Plants ISSN: 0974-0430