Chlorophytum borivilianum, an endangered medicinal plant species is highly recognized for its aphrodisiac properties provided by saponins present in the plant. The transcriptome information of this species is limited and only few hundred expressed sequence tags (ESTs) are available in the public databases. To gain molecular insight of this plant, high throughput transcriptome sequencing of leaf RNA was carried out using Illumina's HiSeq 2000 sequencing platform. A total of 22,161,444 single end reads were retrieved after quality filtering. Available (e.g., De-Bruijn/Eulerian graph) and in-house developed bioinformatics tools were used for assembly and annotation of transcriptome. A total of 101,141 assembled transcripts were obtained, with coverage size of 22.42 Mb and average length of 221 bp. Guanine-cytosine (GC) content was found to be 44%. Bioinformatics analysis, using non-redundant proteins, gene ontology (GO), enzyme commission (EC) and kyoto encyclopedia of genes and genomes (KEGG) databases, extracted all the known enzymes involved in saponin and flavonoid biosynthesis. Few genes of the alkaloid biosynthesis, along with anticancer and plant defense genes, were also discovered. Additionally, several cytochrome P450 (CYP450) and glycosyltransferase unique sequences were also found. We identified simple sequence repeat motifs in transcripts with an abundance of di-nucleotide simple sequence repeat (SSR; 43.1%) markers. Large scale expression profiling through Reads per Kilobase per Million mapped reads (RPKM) showed major genes involved in different metabolic pathways of the plant. Genes, expressed sequence tags (ESTs) and unique sequences from this study provide an important resource for the scientific community, interested in the molecular genetics and functional genomics of C. borivilianum.

Fusarium fujikuroi causing bakanae disease has emerged as one of the major pathogen of rice across the world. The study aims to comparative genomic analysis of Fusarium fujikuroi isolates and identification of the secretary proteins of the fungus involved in rice pathogenesis. In the present study, F. fujikuroi isolate “F250” was sequenced with an assembly size of 42.47 Mb providing coverage of 96.89% on reference IMI58289 genome. A total of 13,603 protein-coding genes were predicted from genome assembly. The average gene density in the F. fujikuroi genome was 315.10 genes per Mb with an average gene length of 1.67 kb. Additionally, 134,374 single nucleotide polymorphisms (SNPs) are identified against IMI58289 isolate, with an average SNP density of 3.11 per kb of genome. Repetitive elements represent approximately 270,550 bp, which is 0.63% of the total genome. In total, 3,109 simple sequence repeats (SSRs), including 302 compound SSRs are identified in the 8,656 scaffolds. Comparative analysis of the isolates of F. fujikuroi revealed that they shared a total of 12,240 common clusters with F250 showing higher similarity with IMI58289. A total of 1,194 secretory proteins were identified in its genome among which there were 356 genes encoding carbohydrate active enzymes (CAZymes) capable for degradation of complex polysaccharides. Out of them glycoside hydrolase (GH) families were most prevalent (41%) followed by carbohydrate esterase (CE). Out of them CE8 (4 genes), PL1 (10 genes), PL3 (5 genes), and GH28 (8 genes) were prominent plant cell wall degrading enzymes families in F250 secretome. Besides this, 585 genes essential for the pathogen–host interactions were also identified. Selected genes were validated through quantitative real-time PCR analyses in resistant and susceptible genotypes of rice at different days of inoculation. The data offers a better understanding of F. fujikuroi genome and will help us enhance our knowledge on Fusarium fujikuroi–rice interactions.

Tilletia indica is an internationally quarantined fungal pathogen causing Karnal bunt of wheat. The present study carried out that the whole genome of T. indica was sequenced and identified transposable elements, pathogenicity-related genes using a comparative genomics approach. The T. indica genome assembly size of 33.7 MB was generated using Illumina and Pac Bio platforms with GC content of 55.0%. A total of 1737 scaffolds were obtained with N 50 of 58,667 bp. The ab initio gene prediction was performed using Ustilago maydis as the reference species. A total number of 10,113 genes were predicted with an average gene size of 1945 bp out of which functionally annotated genes were 7262. A total number of 3216 protein-coding genes were assigned in different categories. Out of a total number of 1877 transposable elements, gypsy had the highest count (573). Total 5772 simple sequence repeats were identified in the genome assembly, and the most abundant simple sequence repeat type was trinucleotide having 42% of total SSRs. The comparative genome analysis suggested 3751 proteins of T. indica had orthologs in five fungi, whereas 126 proteins were unique to T. indica. Secretome analysis revealed the presence of 1014 secretory proteins and few carbohydrate-active enzymes in the genome. Some putative candidate pathogenicity-related genes were identified in the genome. The whole genome of T. indica will provide a window to understand the pathogenesis mechanism, fungal life cycle, survival of teliospores, and novel strategies for management of Karnal bunt disease of wheat.

We have carried out weighted gene co-expression network analysis of Mycobacterium tuberculosis to gain insights into gene expression architecture during log phase growth. The differentially expressed genes between at least one pair of 11 different M. tuberculosis strains as source of biological variability were used for co-expression network analysis. This data included genes with highest coefficient of variation in expression. Five distinct modules were identified using topological overlap based clustering. All the modules together showed significant enrichment in biological processes: fatty acid biosynthesis, cell membrane, intracellular membrane bound organelle, DNA replication, Quinone biosynthesis, cell shape and peptidoglycan biosynthesis, ribosome and structural constituents of ribosome and transposition. We then extracted the co-expressed connections which were supported either by transcriptional regulatory network or STRING database or high edge weight of topological overlap. The genes trpC, nadC, pitA, Rv3404c, atpA, pknA, Rv0996, purB, Rv2106 and Rv0796 emerged as top hub genes. After overlaying this network on the iNJ661 metabolic network, the reactions catalyzed by 15 highly connected metabolic genes were knocked down in silico and evaluated by Flux Balance Analysis. The results showed that in 12 out of 15 cases, in 11 more than 50% of reactions catalyzed by genes connected through co-expressed connections also had altered fluxes. The modules 'Turquoise', 'Blue' and 'Red' also showed enrichment in essential genes. We could map 152 of the previously known or proposed drug targets in these modules and identified 15 new potential drug targets based on their high degree of co-expressed connections and strong correlation with module eigengenes.