The Qatari population, located at the Arabian migration crossroads of African and Eurasia, is comprised of Bedouin, Persian and African genetic subgroups. By deep exome sequencing of only 7 Qataris, including individuals in each subgroup, we identified 2,750 nonsynonymous SNPs predicted to be deleterious, many of which are linked to human health, or are in genes linked to human health. Many of these SNPs were at significantly elevated deleterious allele frequency in Qataris compared to other populations worldwide. Despite the small sample size, SNP allele frequency was highly correlated with a larger Qatari sample. Together, the data demonstrate that exome sequencing of only a small number of individuals can reveal genetic variations with potential health consequences in understudied populations.

Background

Ovarian cancer is the most deadly gynecological cancer because of late diagnosis, frequently with diffuse peritoneal metastases. Recent findings have shown that serous epithelial ovarian cancer has a narrow mutational spectrum with TP53 being the most frequently targeted when single genes are considered. It is, however, important to understand which pathways as a whole may be targeted for mutation.

Findings

Previously published mutational data provided by the cancer genome atlas networks findings on ovarian cancer was searched for statistically significant enrichment of genes in pathways. These pathways were then searched in all patients to identify the spectrum of mutations. Statistical significance was further shown through in-silico permutations of exome sequences using empirically observed mutation rates. We detected mutations in the cell adhesion pathway genes in more than 89% of serous epithelial ovarian cancer patients. This level of near universal mutational targeting of the cell adhesion pathway, including the extracellular matrix pathway, is previously unreported in epithelial ovarian cancer.

Conclusions

Taken together with previous studies on the role of cell adhesion and extracellular matrix gene expression in ovarian cancer and metastasis, our results identify pathways for which the mutational prevalence has previously been overlooked using single gene approaches. Analysis of mutations at the pathway level will be critical in studying heterogeneous diseases such as ovarian cancer.

Background

Ovarian cancer is the most deadly gynecological cancer due to late diagnosis at advanced stage with major peritoneal involvement. To date most research has focused on primary tumor. However the prognosis is directly related to residual disease at the end of the treatment. Therefore it is mandatory to focus and study the biology of meatastatic disease that is most frequently localized to the peritoneal caivty in ovarian cancer.

Methods

We used high-density gene expression arrays to investigate gene expression changes between matched primary and metastatic (peritoneal) lesions.

Results

Here we show that gene expression profiles in peritoneal metastasis are significantly different than their matched primary tumor and these changes are affected by underlying copy number variation differences among other causes. We show that differentially expressed genes are enriched in specific pathways including JAK/STAT pathway, cytokine signaling and other immune related pathways. We show that underlying copy number variations significantly affect gene expression. Indeed patients with important differences in copy number variation displayed greater gene expression differences between their primary and matched metastatic lesions.

Conclusions

Our analysis shows a very specific targeting at both the genomic and transcriptomic level to upregulate certain pathways in the peritoneal metastasis of ovarian cancer. Moreover, while primary tumors use certain pathways we identify distinct differences with metastatic lesions. The variation between primary and metastatic lesions should be considered in personalized treatment of ovarian cancer.

Tumor microenvironement is an important actor of ovarian cancer progression but the relations between mesenchymal cells and ovarian cancer cells remain unclear. The objective of this study was to determine the ovarian cancer cells' biological modifications induced by mesenchymal cells. To address this issue, we used two different ovarian cancer cell lines (NIH:OVCAR3 and SKOV3) and co-cultured them with mesenchymal cells. Upon co-culture the different cell populations were sorted to study their transcriptome and biological properties. Transcriptomic analysis revealed three biological-function gene clusters were enriched upon contact with mesenchymal cells. These were related to the increase of metastatic abilities (adhesion, migration and invasion), proliferation and chemoresistance in vitro. Therefore, contact with the mesenchymal cell niche could increase metastatic initiation and expansion through modification of cancer cells. Taken together these findings suggest that pathways involved in hetero-cellular interaction may be targeted to disrupt the acquired pro-metastatic profile.

Ovarian cancer is the most deadly gynecological cancer. The high rate of mortality is due to the large tumor burden with extensive metastatic lesion of the abdominal cavity. Despite initial chemosensitivity and improved surgical procedures, abdominal recurrence remains an issue and results in patients' poor prognosis. Transcriptomic and genetic studies have revealed significant genome pathologies in the primary tumors and yielded important information regarding carcinogenesis. There are, however, few studies on genetic alterations and their consequences in peritoneal metastatic tumors when compared to their matched ovarian primary tumors. We used high-density SNP arrays to investigate copy number variations in matched primary and metastatic ovarian cancer from 9 patients. Here we show that copy number variations acquired by ovarian tumors are significantly different between matched primary and metastatic tumors and these are likely due to different functional requirements. We show that these copy number variations clearly differentially affect specific pathways including the JAK/STAT and cytokine signaling pathways. While many have shown complex involvement of cytokines in the ovarian cancer environment we provide evidence that ovarian tumors have specific copy number variation differences in many of these genes.

New primer pairs of genomic DNA microsatellite markers were tested to assess the genetic diversity of eleven date palm genotypes. The results indicated that out of thirty, only seven primers (23.3%) failed to amplify the expected PCR fragments, while thirteen primers (43.3%) amplified monomorphic banding patterns and the remaining ten primers (33.4%) generated polymorphic banding patterns. A total of 77 alleles have been observed with a mean of 7.7 alleles per locus. The average of gene diversity was 0.80 ranging from 0.6 (in marker DP168) to 0.9 (in two markers DP157 and DP175). These new co-dominant markers will be a starting point for researchers making use of the markers for genetic mapping and diversity analysis of date palm.

New primer pairs of genomic DNA microsatellite markers were tested to assess the genetic diversity of eleven date palm genotypes. The results indicated that out of thirty, only seven primers (23.3%) failed to amplify the expected PCR fragments, while thirteen primers (43.3%) amplified monomorphic banding patterns and the remaining ten primers (33.4%) generated polymorphic banding patterns. A total of 77 alleles have been observed with a mean of 7.7 alleles per locus. The average of gene diversity was 0.80 ranging from 0.6 (in marker DP168) to 0.9 (in two markers DP157 and DP175). These new co-dominant markers will be a starting point for researchers making use of the markers for genetic mapping and diversity analysis of date palm.

Allpaths2, a method for accurately assembling small genomes with high continuity using short paired reads.

We demonstrate that genome sequences approaching finished quality can be generated from short paired reads. Using 36 base (fragment) and 26 base (jumping) reads from five microbial genomes of varied GC composition and sizes up to 40 Mb, ALLPATHS2 generated assemblies with long, accurate contigs and scaffolds. Velvet and EULER-SR were less accurate. For example, for Escherichia coli, the fraction of 10-kb stretches that were perfect was 99.8% (ALLPATHS2), 68.7% (Velvet), and 42.1% (EULER-SR).

Background

Arcobacter butzleri is a member of the epsilon subdivision of the Proteobacteria and a close taxonomic relative of established pathogens, such as Campylobacter jejuni and Helicobacter pylori. Here we present the complete genome sequence of the human clinical isolate, A. butzleri strain RM4018.

Methodology/Principal Findings

Arcobacter butzleri is a member of the Campylobacteraceae, but the majority of its proteome is most similar to those of Sulfuromonas denitrificans and Wolinella succinogenes, both members of the Helicobacteraceae, and those of the deep-sea vent Epsilonproteobacteria Sulfurovum and Nitratiruptor. In addition, many of the genes and pathways described here, e.g. those involved in signal transduction and sulfur metabolism, have been identified previously within the epsilon subdivision only in S. denitrificans, W. succinogenes, Sulfurovum, and/or Nitratiruptor, or are unique to the subdivision. In addition, the analyses indicated also that a substantial proportion of the A. butzleri genome is devoted to growth and survival under diverse environmental conditions, with a large number of respiration-associated proteins, signal transduction and chemotaxis proteins and proteins involved in DNA repair and adaptation. To investigate the genomic diversity of A. butzleri strains, we constructed an A. butzleri DNA microarray comprising 2238 genes from strain RM4018. Comparative genomic indexing analysis of 12 additional A. butzleri strains identified both the core genes of A. butzleri and intraspecies hypervariable regions, where <70% of the genes were present in at least two strains.

Conclusion/Significance

The presence of pathways and loci associated often with non-host-associated organisms, as well as genes associated with virulence, suggests that A. butzleri is a free-living, water-borne organism that might be classified rightfully as an emerging pathogen. The genome sequence and analyses presented in this study are an important first step in understanding the physiology and genetics of this organism, which constitutes a bridge between the environment and mammalian hosts.

Protein interaction maps can reveal novel pathways and functional complexes, allowing ‘guilt by association’ annotation of uncharacterized proteins. To address the need for large-scale protein interaction analyses, a bacterial two-hybrid system was coupled with a whole genome shotgun sequencing approach for microbial genome analysis. We report the first large-scale proteomics study using this system, integrating de novo genome sequencing with functional interaction mapping and annotation in a high-throughput format. We apply the approach by shotgun sequencing and annotating the genome of Rickettsia sibirica strain 246, an obligate intracellular human pathogen among the Spotted Fever Group rickettsiae. The bacteria invade endothelial cells and cause lysis after large amounts of progeny have accumulated. Little is known about specific Rickettsial virulence factors and their mode of pathogenicity. Analysis of the combined genomic sequence and protein–protein interaction data for a set of virulence related Type IV secretion system (T4SS) proteins revealed over 250 interactions and will provide insight into the mechanism of Rickettsial pathogenicity.

Background

Conserved domains in proteins have crucial roles in protein interactions, DNA binding, enzyme activity and other important cellular processes. It will be of interest to determine the proportions of genes containing such domains in the proteomes of different eukaryotes.

Results

The average proportion of conserved domains in each of five eukaryote genomes was calculated. In pairwise genome comparisons, the ratio of genes containing a given conserved domain in the two genomes on average reflected the ratio of the predicted total gene numbers of the two genomes. These ratios have been verified using a repository of databases and one of its subdivisions of conserved domains.

Conclusions

Many conserved domains occur as a constant proportion of proteome size across the five sequenced eukaryotic genomes. This raises the possibility that this proportion is maintained because of functional constraints on interacting domains. The universality of the ratio in the five eukaryotic genomes attests to its potential importance.