Background: TheAzadirachta indica(neem) tree is a source of a wide number of natural products, including the potent biopesticide azadirachtin. In spite of its widespread applications in agriculture and medicine, the molecular aspects of the biosynthesis of neem terpenoids remain largely unexplored. The current report describes the draft genome and four transcriptomes ofA. indicaand attempts to contextualise the sequence information in terms of its molecular phylogeny, transcript expression and terpenoid biosynthesis pathways.A. indicais the first member of the familyMeliaceaeto be sequenced using next generation sequencing approach.Results: The genome and transcriptomes ofA. indicawere sequenced using multiple sequencing platforms and libraries. TheA. indicagenome is AT-rich, bears few repetitive DNA elements and comprises about 20,000 genes. The molecular phylogenetic analyses groupedA. indicatogether withCitrus sinensisfrom theRutaceaefamily validating its conventional taxonomic classification. Comparative transcript expression analysis showed either exclusive or enhanced expression of known genes involved in neem terpenoid biosynthesis pathways compared to other sequenced angiosperms. Genome and transcriptome analyses inA. indicaled to the identification of repeat elements, nucleotide composition and expression profiles of genes in various organs.Conclusions: This study onA. indicagenome and transcriptomes will provide a model for characterization of metabolic pathways involved in synthesis of bioactive compounds, comparative evolutionary studies among variousMeliaceaefamily members and help annotate their genomes. A better understanding of molecular pathways involved in the azadirachtin synthesis inA. indicawill pave ways for bulk production of environment friendly biopesticides.

Background: The rapid advancements in the field of genome sequencing are aiding our understanding on many biological systems. In the last five years, computational biologists and bioinformatics specialists have come up with newer, better and more efficient tools towards the discovery, analysis and interpretation of different genomic variants from high-throughput sequencing data. Availability of reliable simulated dataset is essential and is the first step towards testing any newly developed analytical tools for variant discovery. Although there are tools currently available that can simulate variants, none present the possibility of simulating all the three major types of variations (Single Nucleotide Polymorphisms, Insertions and Deletions and Copy Number Variations) and can generate reads taking a realistic error-model into consideration. Therefore, an efficient simulator and read generator is needed that can simulate variants taking the error rates of true biological samples into consideration. Results: We report SInC (Snp, Indel and Cnv) an open-source variant simulator and read generator capable of simulating all the three common types of biological variants taking into account a distribution of base quality score from a most commonly used next-generation sequencing instrument from Illumina. SInC is capable of generating single- and paired-end reads with user-defined insert size and with high efficiency compared to the other existing tools. SInC, due to its multi-threaded capability during read generation, has a low time footprint. SInC is currently optimised to work in limited infrastructure setup and can efficiently exploit the commonly used quad-core desktop architecture to simulate short sequence reads with deep coverage for large genomes. Conclusions: We have come up with a user-friendly multi-variant simulator and read-generator tools called SInC. SInC can be downloaded from http://sourceforge.net/projects/sincsimulator.

Oral tongue squamous cell carcinomas (OTSCC) are a homogenous group of aggressive tumors in the head and neck region that spread early to lymph nodes and have a higher incidence of regional failure. In addition, there is a rising incidence of oral tongue cancer in younger populations. Studies on functional DNA methylation changes linked with altered gene expression are critical for understanding the mechanisms underlying tumor development and metastasis. Such studies also provide important insight into biomarkers linked with viral infection, tumor metastasis, and patient survival in OTSCC. Therefore, we performed genome-wide methylation analysis of tumors (N = 52) and correlated altered methylation with differential gene expression. The minimal tumor-specific DNA 5-methylcytosine signature identified genes near 16 different differentially methylated regions, which were validated using genomic data from The Cancer Genome Atlas cohort. In our cohort, hypermethylation of MIR10B was significantly associated with the differential expression of its target genes NR4A3 and BCL2L11 (P = 0.0125 and P = 0.014, respectively), which was inversely correlated with disease-free survival (P = 9E−15 and P = 2E−15, respectively) in patients. Finally, differential methylation in FUT3, TRIM5, TSPAN7, MAP3K8, RPS6KA2, SLC9A9, and NPAS3 genes was found to be predictive of certain clinical and epidemiologic parameters. Implications: This study reveals a functional minimal methylation profile in oral tongue tumors with associated risk habits, clinical, and epidemiologic outcomes. In addition, NR4A3 downregulation and correlation with patient survival suggests a potential target for therapeutic intervention in oral tongue tumors. Data from the current study are deposited in the NCBI Geo database (accession number GSE75540). Mol Cancer Res; 14(9); 805–19. ©2016 AACR.

Neem (Azadirachta indica A. Juss.), an evergreen tree of the Meliaceae family, is known for its medicinal, cosmetic, pesticidal and insecticidal properties. We had previously sequenced and published the draft genome of a neem plant, using mainly short read sequencing data. In this report, we present an improved genome assembly generated using additional short reads from Illumina and long reads from Pacific Biosciences SMRT sequencer. We assembled short reads and error-corrected long reads using Platanus, an assembler designed to perform well for heterozygous genomes. The updated genome assembly (v2.0) yielded 3- and 3.5-fold increase in N50 and N75, respectively; 2.6-fold decrease in the total number of scaffolds; 1.25-fold increase in the number of valid transcriptome alignments; 13.4-fold less misassembly and 1.85-fold increase in the percentage repeat, over the earlier assembly (v1.0). The current assembly also maps better to the genes known to be involved in the terpenoid biosynthesis pathway. Together, the data represent an improved assembly of the A. indica genome.

Accurate detection of human papillomavirus (HPV) in oral cavity squamous cell carcinoma (OSCC) is essential to understanding the role of HPV in disease prognosis and management of patients. We used different analytes and methods to understand the true prevalence of HPV in a cohort of patients with OSCC with different molecular backgrounds, and we correlated HPV data with patient survival. We integrated data from multiple analytes (HPV DNA, HPV RNA, and p16), assays (immunohistochemistry, polymerase chain reaction [PCR], quantitative PCR [qPCR], and digital PCR), and molecular changes (somatic mutations and DNA methylation) from 153 patients with OSCC to correlate p16 expression, HPV DNA, and HPV RNA with HPV incidence and patient survival. High prevalence (33% to 58%) of HPV16/18 DNA did not correlate with the presence of transcriptionally active viral genomes (15%) in tumors. Eighteen percent of the tumors were p16 positive and only 6% were both HPV DNA and HPV RNA positive. Most tumors with relatively high copy number HPV DNA and/or HPV RNA, but not with HPV DNA alone (irrespective of copy number), were wild-type for TP53 and CASP8 genes. In our study, p16 protein, HPV DNA, and HPV RNA, either alone or in combination, did not correlate with patient survival. Nine HPV-associated genes stratified the virus-positive from the virus-negative tumor group with high confidence (P < .008) when HPV DNA copy number and/or HPV RNA were considered to define HPV positivity, and not HPV DNA alone, irrespective of copy number (P < .2). In OSCC, the presence of both HPV RNA and p16 is rare. HPV DNA alone is not an accurate measure of HPV positivity and therefore may not be informative. HPV DNA, HPV RNA, and p16 do not correlate with patients’ outcome.