Gene fusions, micro-exons and splice variants define stress signaling by AP2/ERF and WRKY transcription factors in the sesame pan-genome

Evolutionary dynamics of AP2/ERF and WRKY genes, the major components of defense response were studied extensively in the sesame pan-genome. Massive variation was observed for gene copy numbers, genome location, domain structure, exon-intron structure and protein parameters. In the pan-genome, 63% of AP2/ERF members were devoid of introns whereas >99% of WRKY genes contained multiple introns. AP2 subfamily was found to be micro-exon rich with the adjoining intronic sequences sharing sequence similarity to many stress-responsive and fatty acid metabolism genes. WRKY family included extensive multi-domain gene fusions where the additional domains significantly enhanced gene and exonic sizes as well as gene copy numbers. The fusion genes were found to have roles in acquired immunity, stress response, cell and membrane integrity as well as ROS signaling. The individual genomes shared extensive synteny and collinearity although ecological adaptation was evident among the Chinese and Indian accessions. Significant positive selection effects were noticed for both micro-exon and multi-domain genes. Splice variants with changes in acceptor, donor and branch sites were common and 6-7 splice variants were detected per gene. The study ascertained vital roles of lipid metabolism and chlorophyll biosynthesis in the defense response and stress signaling pathways. 60% of the studied genes localized in the nucleus while 20% preferred chloroplast. Unique cis-element distribution was noticed in the upstream promoter region with MYB and STRE in WRKY genes while MYC was present in the AP2/ERF genes. Intron-less genes exhibited great diversity in the promoter sequences wherein the predominance of dosage effect indicated variable gene expression levels. Mimicking the NBS-LRR genes, a chloroplast localized WRKY gene, Swetha_24868, with additional domains of chorismate mutase, cAMP and voltage-dependent potassium channel was found to act as a master regulator of defense signaling, triggering immunity and reducing ROS levels.

Comparative DNA Methylome of Phytoplasma Associated Retrograde Metamorphosis in Sesame (Sesamum indicum L.)

Phytoplasma-associated diseases such as phyllody and little leaf are critical threats to sesame cultivation worldwide. The mechanism of the dramatic conversion of flowers to leafy structures leading to yield losses and the drastic reduction in leaf size due to Phytoplasma infection remains yet to be identified. Cytosine methylation profiles of healthy and infected sesame plants studied using Whole Genome Bisulfite Sequencing (WGBS) and Quantitative analysis of DNA methylation with the real-time PCR (qAMP) technique revealed altered DNA methylation patterns upon infection. Phyllody was associated with global cytosine hypomethylation, though predominantly in the CHH (where H = A, T or C) context. Interestingly, comparable cytosine methylation levels were observed between healthy and little leaf-affected plant samples in CG, CHG and CHH contexts. Among the different genomic fractions, the highest number of differentially methylated Cytosines was found in the intergenic regions, followed by promoter, exonic and intronic regions in decreasing order. Further, most of the differentially methylated genes were hypomethylated and were mainly associated with development and defense-related processes. Loci for STOREKEEPER protein-like, a DNA-binding protein and PP2-B15, an F-Box protein, responsible for plugging sieve plates to maintain turgor pressure within the sieve tubes were found to be hypomethylated by WGBS, which was confirmed by methylation-dependent restriction digestion and qPCR. Likewise, serine/threonine-protein phosphatase-7 homolog, a positive regulator of cryptochrome signaling involved in hypocotyl and cotyledon growth and probable O-methyltransferase 3 locus were determined to be hypermethylated. Phytoplasma infection-associated global differential methylation as well as the defense and development-related loci reported here for the first time significantly elucidate the mechanism of phytoplasma-associated disease development.

GinMicrosatDb: a genome-wide microsatellite markers database for sesame (Sesamum indicum L.)

Molecular breeding in sesame is still at infancy due to limited number of microsatellite markers available and the low level of polymorphism exhibited by them. Therefore, whole genome sequencing was used for development of microsatellite markers so as to ensure availability of substantial number of polymorphic markers for use in marker assisted breeding programs. Whole genome sequencing of sesame variety 'Swetha' was done using Illumina paired-end sequencing and Roche 454 shotgun sequencing technologies (GCA_000975565.1 in GenBank). 'GinMicrosatDb', a genome-wide microsatellite marker database has been developed using the whole genome sequence data of sesame variety 'Swetha'. The database consists of microsatellites localized on both linkage groups and scaffolds with their genomic co-ordinates. It provides five sets of forward and reverse primers for each of the microsatellite loci along with the flanking sequences, primer GC content, product size and melting temperature etc. The distribution of microsatellites can be viewed and selected through a genome browser as well as through a physical map. The newly identified microsatellite markers are expected to help sesame breeders in developing marker tags for traits of economic importance thereby bringing about greater efficiency in marker-assisted selection programs.

nifPred: Proteome-Wide Identification and Categorization of Nitrogen-Fixation Proteins of Diaztrophs Based on Composition-Transition-Distribution Features Using Support Vector Machine

As inorganic nitrogen compounds are essential for basic building blocks of life (e.g., nucleotides and amino acids), the role of biological nitrogen-fixation (BNF) is indispensible. All nitrogen fixing microbes rely on the same nitrogenase enzyme for nitrogen reduction, which is in fact an enzyme complex consists of as many as 20 genes. However, the occurrence of six genes viz., nifB, nifD, nifE, nifH, nifK, and nifN has been proposed to be essential for a functional nitrogenase enzyme. Therefore, identification of these genes is important to understand the mechanism of BNF as well as to explore the possibilities for improving BNF from agricultural sustainability point of view. Further, though the computational tools are available for the annotation and phylogenetic analysis of nifH gene sequences alone, to the best of our knowledge no tool is available for the computational prediction of the above mentioned six categories of nitrogen-fixation (nif) genes or proteins. Thus, we proposed an approach, which is first of its kind for the computational identification of nif proteins encoded by the six categories of nif genes. Sequence-derived features were employed to map the input sequences into vectors of numeric observations that were subsequently fed to the support vector machine as input. Two types of classifier were constructed: (i) a binary classifier for classification of nif and non-nitrogen-fixation (non-nif) proteins, and (ii) a multi-class classifier for classification of six categories of nif proteins. Higher accuracies were observed for the combination of composition-transition-distribution (CTD) feature set and radial kernel, as compared to the other feature-kernel combinations. The overall accuracies were observed >90% in both binary and multi-class classifications. The developed approach further achieved >92% accuracy, while evaluated with blind (independent) test datasets. The developed approach also produced higher accuracy in identifying nif proteins, while evaluated using proteome-wide datasets of several species. Furthermore, we established a prediction server nifPred (http://webapp.cabgrid.res.in/nifPred) to assist the scientific community for proteome-wide identification of six categories of nif proteins. Besides, the source code of nifPred is also available at https://github.com/PrabinaMeher/nifPred. The developed web server is expected to supplement the transcriptional profiling and comparative genomics studies for the identification and functional annotation of genes related to BNF.