Identification of resistance gene analogs of the NBS-LRR family through transcriptome probing and in silico prediction of the expressome of Dalbergia sissoo under dieback disease stress

Siddra Ijaz; Imran Ul Haq; Iqrar Ahmad Khan; Hayssam M Ali; Sukhwinder Kaur; Hafiza Arooj Razzaq

doi:10.3389/fgene.2022.1036029

Identification of resistance gene analogs of the NBS-LRR family through transcriptome probing and in silico prediction of the expressome of Dalbergia sissoo under dieback disease stress

Front Genet. 2022 Oct 7:13:1036029. doi: 10.3389/fgene.2022.1036029. eCollection 2022.

Authors

Siddra Ijaz¹, Imran Ul Haq², Iqrar Ahmad Khan³, Hayssam M Ali⁴, Sukhwinder Kaur⁵, Hafiza Arooj Razzaq¹

Affiliations

¹ Centre of Agricultural Biochemistry and Biotechnology, University of Agriculture Faisalabad, Faisalabad, Pakistan.
² Department of Plant Pathology, University of Agriculture Faisalabad, Faisalabad, Pakistan.
³ Institute of Horticultural Sciences, University of Agriculture Faisalabad, Faisalabad, Pakistan.
⁴ Botany and Microbiology Department, College of Science, King Saud University, Riyadh, Saudi Arabia.
⁵ Department of Plant Pathology, University of California, Davis, Davis, CA, United States.

Abstract

Dalbergia sissoo is an important timber tree, and dieback disease poses a dire threat to it toward extinction. The genomic record of D. sissoo is not available yet on any database; that is why it is challenging to probe the genetic elements involved in stress resistance. Hence, we attempted to unlock the genetics involved in dieback resistance through probing the NBS-LRR family, linked with mostly disease resistance in plants. We analyzed the transcriptome of D. sissoo under dieback challenge through DOP-rtPCR analysis using degenerate primers from conserved regions of NBS domain-encoded gene sequences. The differentially expressed gene sequences were sequenced and in silico characterized for predicting the expressome that contributes resistance to D. sissoo against dieback. The molecular and bioinformatic analyses predicted the presence of motifs including ATP/GTP-binding site motif A (P-loop NTPase domain), GLPL domain, casein kinase II phosphorylation site, and N-myristoylation site that are the attributes of proteins encoded by disease resistance genes. The physicochemical characteristics of identified resistance gene analogs, subcellular localization, predicted protein fingerprints, in silico functional annotation, and predicted protein structure proved their role in disease and stress resistance.

Keywords: Dalbergia sissoo; NBS-LRR; computational biology; functional annotation; resistance gene analogs.