Jasmin H. Bavarva

Characterizing the Genetic Basis for Nicotine Induced Cancer Development: A Transcriptome Sequencing Study.

Nicotine is a known risk factor for cancer development and has been shown to alter gene expression in cells and tissue upon exposure. We used Illumina® Next Generation Sequencing (NGS) technology to gain unbiased biological insight into the transcriptome of normal epithelial cells (MCF-10A) to nicotine exposure. We generated expression data from 54,699 transcripts using triplicates of control and nicotine stressed cells. As a result, we identified 138 differentially expressed transcripts, including 39 uncharacterized genes. Additionally, 173 transcripts that are primarily associated with DNA replication, recombination, and repair showed evidence for alternative splicing. We discovered the greatest nicotine stress response by HPCAL4 (up-regulated by 4.71 fold) and NPAS3 (down-regulated by -2.73 fold); both are genes that have not been previously implicated in nicotine exposure but are linked to cancer. We also discovered significant down-regulation (-2.3 fold) and alternative splicing of NEAT1 (lncRNA) that may have an important, yet undiscovered regulatory role. Gene ontology analysis revealed nicotine exposure influenced genes involved in cellular and metabolic processes. This study reveals previously unknown consequences of nicotine stress on the transcriptome of normal breast epithelial cells and provides insight into the underlying biological influence of nicotine on normal cells, marking the foundation for future studies.

Gene Expression Profiling of Human Vaginal Cells In Vitro Discriminates Compounds with Pro-Inflammatory and Mucosa-Altering Properties: Novel Biomarkers for Preclinical Testing of HIV Microbicide Candidates

Background Inflammation and immune activation of the cervicovaginal mucosa are considered factors that increase susceptibility to HIV infection. Therefore, it is essential to screen candidate anti-HIV microbicides for potential mucosal immunomodulatory/inflammatory effects prior to further clinical development. The goal of this study was to develop an in vitro method for preclinical evaluation of the inflammatory potential of new candidate microbicides using a microarray gene expression profiling strategy. Methods To this end, we compared transcriptomes of human vaginal cells (Vk2/E6E7) treated with well-characterized pro-inflammatory (PIC) and non-inflammatory (NIC) compounds. PICs included compounds with different mechanisms of action. Gene expression was analyzed using Affymetrix U133 Plus 2 arrays. Data processing was performed using GeneSpring 11.5 (Agilent Technologies, Santa Clara, CA). Results Microarraray comparative analysis allowed us to generate a panel of 20 genes that were consistently deregulated by PICs compared to NICs, thus distinguishing between these two groups. Functional analysis mapped 14 of these genes to immune and inflammatory responses. This was confirmed by the fact that PICs induced NFkB pathway activation in Vk2 cells. By testing microbicide candidates previously characterized in clinical trials we demonstrated that the selected PIC-associated genes properly identified compounds with mucosa-altering effects. The discriminatory power of these genes was further demonstrated after culturing vaginal cells with vaginal bacteria. Prevotella bivia, prevalent bacteria in the disturbed microbiota of bacterial vaginosis, induced strong upregulation of seven selected PIC-associated genes, while a commensal Lactobacillus gasseri associated to vaginal health did not cause any changes. Conclusions In vitro evaluation of the immunoinflammatory potential of microbicides using the PIC-associated genes defined in this study could help in the initial screening of candidates prior to entering clinical trials. Additional characterization of these genes can provide further insight into the cervicovaginal immunoinflammatory and mucosal-altering processes that facilitate or limit HIV transmission with implications for the design of prevention strategies.

Next in line in next-generation sequencing: are we there yet?

Next-generation sequencing (NGS) technologies have provided us with an opportunity to explore genomes with unprecedented detail. Alongside these advancements, NGS has its own challenges (much like all technology) creating a plethora of analytical and biological considerations before these methods can be standardized. Meanwhile, encouraging single-cell sequencing has become a recent trend among scientists who are optimistic that this approach will better characterize cancer (and other similarly complex diseases) [1,2]. The technology necessary to sequence a complete genome from a ‘single’ cell has been available, but now, combined with growing popularity and mainstream acceptance, these methods are soon to become pedestrian tools, among a list of many existing NGS technologies. Will this technique be the missing link to scaffold data between genome sequencing methods, which currently contribute volumes of data but with nominal insight into therapies? To answer these questions we have chosen to review current trends in sequencing technology and relative to novel therapies.

Standardizing Next-Generation Sequencing Experiments and Analysis Methods

To the Editor: The past few years have seen the emergence of new strategies for high-throughput DNA sequencing that have invigorated life science research. Because of these technological advances, the available sequencing data continue to expand. Additionally, cost reductions have made access to sequences of entire genomes easier for established laboratories and even easier for small research groups. A lack of consensus exists, however, on how best to design and analyze next-generation sequencing (NGS) studies and how to compare these data to previous and future work. Comparing different sequencing platforms and analysis methods, and thus their interpretations, is becoming more complicated. The main purpose of such studies is somehow getting lost in the process of experimental design as biologists confront new territory with NGS work, which requires handling more complex and powerful statistical methods and produces large data sets. Every new tool or method is being compared with existing methods, and investigators are using statistical arguments to propose that the new methods are better. Kiezun et al. (1) have recently …

Improved variation calling via an iterative backbone remapping and local assembly method for bacterial genomes.

Sequencing data analysis remains limiting and problematic, especially for low complexity repeat sequences and transposon elements due to inherent sequencing errors and short sequence read lengths. We have developed a program, ReviSeq, which uses a hybrid method composed of iterative remapping and local assembly upon a bacterial sequence backbone. Application of this method to six Brucella suis field isolates compared to the newly revised B. suis 1330 reference genome identified on average 13, 15, 19 and 9 more variants per sample than STAMPY/SAMtools, BWA/SAMtools, iCORN and BWA/PINDEL pipelines, and excluded on average 4, 2, 3 and 19 variants per sample, respectively. In total, using this iterative approach, we identified on average 87 variants including SNVs, short INDELs and long INDELs per strain when compared to the reference. Our program outperforms other methods especially for long INDEL calling. The program is available at http://reviseq.sourceforge.net.

Updating microbial genomic sequences: improving accuracy & innovation

BackgroundMany bacterial genome sequences completed using the Sanger method may contain assembly errors due in-part to low sequence coverage driven by cost.FindingsTo illustrate the need for re-sequencing of pre-nextgen genomes and to validate sequenced genomes, we conducted a series of experiments, using high coverage sequencing data generated by a Illumina Miseq sequencer to sequence genomic DNAs of Bacteroides fragilis NCTC 9343, Salmonella enterica subsp. enterica serovar Paratyphi A str. ATCC 9150, Vibrio cholerae O1 biovar El Tor str. N16961, Bacillus halodurans C-125 and Caulobacter crescentus CB15, which had previously been sequenced by the Sanger method during the early 2000’s.ConclusionsThis study revealed a number of discrepancies between the published assemblies and sequence read alignments for all five bacterial species, suggesting that the continued use of these error-containing genomes and their genetic information may contribute to false conclusions and/or incorrect future discoveries when they are used.

Life cycle of an n-globin pseudogene microsatellite locus

Microsatellites are composed of tandemly repeated short motifs of 1–6 nucleotides. They are common in eukaryotic genomes; in humans they make up as much as 3% of the genome (Lander et al., 2001). These repeat-containing loci tend to be hypervariable with variation occurring among individuals of the same species as well as between species. The origin and evolution of microsatellites remain a major puzzle. The birth of a tetranucleotide repeat (ATGT) in the lineage leading to African apes (gorilla, bonobo and chimpanzee) and humans was documented in the n-globin pseudogene (Messier et al., 1996). To test whether the locus is under further expansion or degeneration or if there are any variations as proposed in the life-cycle of the microsatellites (Buschiazzo and Gemmell, 2006), we analyzed positions chr11:5263801:5263831 (hg19) in 82 samples from the 1000 Genomes Project (Genomes Project et al., 2010). To obtain reliable read coverage for the locus, we selected Illumina exome sequencing data and visually inspected the INDEL length in the reads aligned to the locus. We found a repeat deletion (4 bases) of the 4-mer microsatellite locus in 46 samples (56%) relative to reference allele, as supported by at least two reads in each sample. We assume that the longer (reference) microsatellite allele is ancestral, as at least two mutations are reported in this allele (rs34312249 and rs147740082), suggesting a degeneration process of the pure microsatellite locus. The short allele had 28% frequency in analyzed samples. The genus Homo is believed to have evolved 2.0 Myr (Curnoe, 2010) and modern humans 0.2 Myr (Vigilant et al., 1991) ago. Last evolutionary change in the n-globin pseudogene locus is documented between chimpanzees and humans when the microsatellite locus was expanded in humans. Unfortunately, intraspecies variation in the locus is unknown in chimpanzees and gorillas and we were unable to find the locus in the Neanderthal genome, presumably due to its incompleteness (Green et al., 2006). The locus alteration from orangutan to gorilla took ~7.0 Myr followed by species evolution with no change in the locus (gorilla to chimpanzee). Similarly, the evolution of the chimpanzee to the genus Homo took ~3.0 Myr with an accompanying n-globin microsatellite locus expansion. As time required for subsequent stage of life cycle seems to decrease by about 50% (Birth: ~7 Myr, Expansion: ~3 Myr, Degeneration: 1.8 Myr) (Figure ​(Figure1A),1A), it appears that the plausible death of the n-globin pseudogene microsatellite locus is expected within the next ~0.9 Myr (Figure ​(Figure1B).1B). However, human demography and unknown fitness effects of the microsatellite polymorphism can influence the locus evolutionary dynamics. Figure 1 Evolution and life cycle of an n-globin pseudogene microsatellite locus. (A) Evolutionary time estimate for the species emergence and corresponding change in the n-globin pseudogene microsatellite locus, illustrating different stages of life cycle and ... To test whether the scenario (life cycle of microsatellites) can be applied to other microsatellite loci, we reanalyzed our microsatellite data from multiple species (Galindo et al., 2009). We observed the birth, expansion, and degeneration of several microsatellite loci in four microsatellite motif families in human, chimpanzee, orangutan, rhesus macaque, marmoset and mouse genomes. Although, there were few loci that showed deviations from the expected life-cycle, such as AATGG repeat in DMD and HEPH gene that showed stability for an extended period of time, and in PCNXL2 where it showed one repeat diminution in chimpanzee compared to orangutan and human, majority of the repeats arguably followed the proposed life cycle. Overall, it would be of great scientific significance to constantly monitor a number of marker microsatellite loci for genetic deviations as time progresses and more samples are being sequenced.