Somatic Mutational Profile of High-Grade Serous Ovarian Carcinoma and Triple-Negative Breast Carcinoma in Young and Elderly Patients: Similarities and Divergences

Background: Triple-negative breast cancer (TNBC) and High-Grade Serous Ovarian Cancer (HGSOC) are aggressive malignancies that share similarities; however, different ages of onset may reflect distinct tumor behaviors. Thus, our aim was to compare somatic mutations in potential driver genes in 109 TNBC and 81 HGSOC from young (Y ≤ 40 years) and elderly (E ≥ 75 years) patients. Methods: Open access mutational data (WGS or WES) were collected for TNBC and HGSOC patients. Potential driver genes were those that were present in the Cancer Gene Census—CGC, the Candidate Cancer Gene Database—CCGD, or OncoKB and those that were considered pathogenic in variant effect prediction tools. Results: Mutational signature 3 (homologous repair defects) was the only gene that was represented in all four subgroups. The median number of mutated CGCs per sample was similar in HGSOC (Y:3 vs. E:4), but it was higher in elderly TNBC than it was in young TNBC (Y:3 vs. E:6). At least 90% of the samples from TNBC and HGSOC from Y and E patients presented at least one known affected TSG. Besides TP53, which was mutated in 67–83% of the samples, the affected TSG in TP53 wild-type samples were NF1 (yHGSOC and yTNBC), PHF6 (eHGSOC and yTNBC), PTEN, PIK3R1 and ZHFX3 (yTNBC), KMT2C, ARID1B, TBX3, and ATM (eTNBC). A few samples only presented one affected oncogene (but no TSG): KRAS and TSHR in eHGSOC and RAC1 and PREX2 (a regulator of RAC1) in yTNBC. At least ⅔ of the tumors presented mutated oncogenes associated with tumor suppressor genes; the Ras and/or PIK3CA signaling pathways were altered in 15% HGSOC and 20–35% TNBC (Y vs. E); DNA repair genes were mutated in 19–33% of the HGSOC tumors but were more frequently mutated in E-TNBC (56%). However, in HGSOC, 9.5% and 3.3% of the young and elderly patients, respectively, did not present any tumors with an affected CGC nor did 4.65% and none of the young and elderly TNBC patients. Conclusion: Most HGSOC and TNBC from young and elderly patients present an affected TSG, mainly TP53, as well as mutational signature 3; however, a few tumors only present an affected oncogene or no affected cancer-causing genes.

RefSeq Functional Elements as experimentally assayed nongenic reference standards and functional interactions in human and mouse

Eukaryotic genomes contain many nongenic elements that function in gene regulation, chromosome organization, recombination, repair or replication, and mutation of those elements can affect genome function and cause disease. While numerous epigenomic studies provide high coverage of gene regulatory regions, those data are not usually exposed in traditional genome annotation, and can be difficult to access and interpret without field-specific expertise. The National Center for Biotechnology Information (NCBI) therefore provides RefSeq Functional Elements (RefSeqFEs), which represent experimentally validated human and mouse nongenic elements derived from the literature. The curated dataset is comprised of richly annotated sequence records, descriptive records in the NCBI Gene database, reference genome feature annotation, and activity-based interactions between nongenic regions, target genes and each other. The dataset provides succinct functional details and transparent experimental evidence, leverages data from multiple experimental sources, is readily accessible and adaptable, and utilizes a flexible data model. The data have multiple uses for basic functional discovery, bioinformatics studies, genetic variant interpretation, as known positive controls for epigenomic data evaluation, and as reference standards for functional interactions. Comparisons to other gene regulatory datasets show that the RefSeqFE dataset includes a wider range of feature types representing more areas of biology, but it is comparatively smaller and subject to data selection biases. RefSeqFEs thus provide an alternative and complementary resource for experimentally assayed functional elements, with future dataset growth expected.

Potential Key Genes Associated with Stroke types and its subtypes: A Computational Approach

To investigate prospective key genes and pathways associated with the pathogenesis and prognosis of stroke types along with subtypes. Human genes using genome assembly build 38 patch release 13 with known gene symbols through NCBI gene database (https://www.ncbi.nlm.nih.gov/gene) were fetched. PubMed advanced queries were constructed using stroke-related keywords and associations were calculated using Normalized pointwise mutual information (nPMI) between each gene symbol and queries. Genes related with stroke risk within their types and subtypes were investigated in order to discover genetic markers to predict individuals who are at the risk of developing stroke with their subtypes. A total of 2,785 (9.4%) genes were found to be linked to the risk of stroke. Based on stroke types, 1,287 (46.2%) and 376 (13.5%) genes were found to be related with IS and HS respectively. Further stratification of IS based on TOAST classification, 86 (6.6%) genes were confined to Large artery atherosclerosis; 131 (10.1%) and 130 (10%) genes were related with the risk of small vessel disease and Cardioembolism subtypes of IS. Besides, a prognostic panel of 9 genes signature consisting of CYP4A11, ALOX5P, NOTCH, NINJ2, FGB, MTHFR, PDE4D, HDAC9, and ZHFX3 can be treated as a diagnostic marker to predict individuals who are at the risk of developing stroke with their subtypes.

Strategy for searching potential partner genes of Drosophila melanogaster Sws gene

Aim. The Drosophila swiss cheese (sws) gene is a mammalian ortholog of neuropathy target esterase (NTE or PNPLA6). This protein is involved in the functioning of the nervous system and causes some kinds of polyneuropathy with the mechanism unknown. Genes-interactors of the sws gene should be found to investigate the cellular mechanism of SWS/NTE-dependent neuropathy formation and to find out what signaling pathways SWS is involved in. Methods. The search was done in the Drosophila database – Flybase, in the NCBI (Gene) database to search for orthologs, and the String web resource was used in the case of potential protein interactions. Results. Only four experimentally identified genes-interactors were listed in the Flybase. Based on the expression changes data of 28 genes at PNPLA6 silencing, a theoretical search for the corresponding orthologs in Drosophila was done. The in silico assay predicted 10 proteins that are probably functioning within one metabolic pathway. Conclusions. The methods applied gave us a wide list of genes that can interact with sws at different levels: from the expression pattern to the phenotype. Therefore, 25 potentially partner genes were selected to verify the genetic interaction of these genes in vivo. Keywords: gene swiss cheese, neuropathy target esterase, neurodegeneration, in silico analysis, genes interaction, Drosophila melanogaster.

Molecular cloning and characterization of common marmoset SULT1C subfamily members that catalyze the sulfation of thyroid hormones

Cytosolic sulfotransferase SULT1C subfamily is one of the most flexible gene subfamily during mammalian evolution. The physiological functions of SULT1C enzymes still remain to be fully understood. In this study, common marmoset (Callithrix jacchus), a promising primate animal model, was used to investigate the functional relevance of the SULT1C subfamily. Gene database search revealed three intact SULT1C genes and a pseudogene in its genome. These four genes were named SULT1C1, SULT1C2, SULT1C3P, and SULT1C5, according to the sequence homology and gene location. Since SULT1C5 is the orthologous gene for human SULT1C2P, we propose, here, to revisit the designation of human SULT1C2P to SULT1C5P. Purified recombinant SULT1C enzymes showed sulfating activities toward a variety of xenobiotic compounds and thyroid hormones. Kinetic analysis revealed high catalytic activities of SULT1C1 and SULT1C5 for 3,3’-T2. It appears therefore that SULT1C isoforms may play a role in the thyroid hormone metabolism in common marmoset.

DiTing: A Pipeline to Infer and Compare Biogeochemical Pathways From Metagenomic and Metatranscriptomic Data

Metagenomics and metatranscriptomics are powerful methods to uncover key micro-organisms and processes driving biogeochemical cycling in natural ecosystems. Databases dedicated to depicting biogeochemical pathways (for example, metabolism of dimethylsulfoniopropionate (DMSP), which is an abundant organosulfur compound) from metagenomic/metatranscriptomic data are rarely seen. Additionally, a recognized normalization model to estimate the relative abundance and environmental importance of pathways from metagenomic and metatranscriptomic data has not been organized to date. These limitations impact the ability to accurately relate key microbial-driven biogeochemical processes to differences in environmental conditions. Thus, an easy-to-use, specialized tool that infers and visually compares the potential for biogeochemical processes, including DMSP cycling, is urgently required. To solve these issues, we developed DiTing, a tool wrapper to infer and compare biogeochemical pathways among a set of given metagenomic or metatranscriptomic reads in one step, based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) and a manually created DMSP cycling gene database. Accurate and specific formulae for over 100 pathways were developed to calculate their relative abundance. Output reports detail the relative abundance of biogeochemical pathways in both text and graphical format. DiTing was applied to simulated metagenomic data and resulted in consistent genetic features of simulated benchmark genomic data. Subsequently, when applied to natural metagenomic and metatranscriptomic data from hydrothermal vents and the Tara Ocean project, the functional profiles predicted by DiTing were correlated with environmental condition changes. DiTing can now be confidently applied to wider metagenomic and metatranscriptomic datasets, and it is available at https://github.com/xuechunxu/DiTing.

Online database for brain cancer-implicated genes: exploring the subtype-specific mechanisms of brain cancer

Background Brain cancer is one of the eight most common cancers occurring in people aged 40+ and is the fifth-leading cause of cancer-related deaths for males aged 40–59. Accurate subtype identification is crucial for precise therapeutic treatment, which largely depends on understanding the biological pathways and regulatory mechanisms associated with different brain cancer subtypes. Unfortunately, the subtype-implicated genes that have been identified are scattered in thousands of published studies. So, systematic literature curation and cross-validation could provide a solid base for comparative genetic studies about major subtypes. Results Here, we constructed a literature-based brain cancer gene database (BCGene). In the current release, we have a collection of 1421 unique human genes gathered through an extensive manual examination of over 6000 PubMed abstracts. We comprehensively annotated those curated genes to facilitate biological pathway identification, cancer genomic comparison, and differential expression analysis in various anatomical brain regions. By curating cancer subtypes from the literature, our database provides a basis for exploring the common and unique genetic mechanisms among 40 brain cancer subtypes. By further prioritizing the relative importance of those curated genes in the development of brain cancer, we identified 33 top-ranked genes with evidence mentioned only once in the literature, which were significantly associated with survival rates in a combined dataset of 2997 brain cancer cases. Conclusion BCGene provides a useful tool for exploring the genetic mechanisms of and gene priorities in brain cancer. BCGene is freely available to academic users at http://soft.bioinfo-minzhao.org/bcgene/.

AMRFinderPlus and the Reference Gene Catalog facilitate examination of the genomic links among antimicrobial resistance, stress response, and virulence

Antimicrobial resistance (AMR) is a significant public health threat. With the rise of affordable whole genome sequencing, in silico approaches to assessing AMR gene content can be used to detect known resistance mechanisms and potentially identify novel mechanisms. To enable accurate assessment of AMR gene content, as part of a multi-agency collaboration, NCBI developed a comprehensive AMR gene database, the Bacterial Antimicrobial Resistance Reference Gene Database and the AMR gene detection tool AMRFinder. Here, we describe the expansion of the Reference Gene Database, now called the Reference Gene Catalog, to include putative acid, biocide, metal, stress resistance genes, in addition to virulence genes and species-specific point mutations. Genes and point mutations are classified by broad functions, as well as more detailed functions. As we have expanded both the functional repertoire of identified genes and functionality, NCBI released a new version of AMRFinder, known as AMRFinderPlus. This new tool allows users the option to utilize only the core set of AMR elements, or include stress response and virulence genes, too. AMRFinderPlus can detect acquired genes and point mutations in both protein and nucleotide sequence. In addition, the evidence used to identify the gene has been expanded to include whether nucleotide or protein sequence was used, its location in the contig, and presence of an internal stop codon. These database improvements and functional expansions will enable increased precision in identifying AMR genes, linking AMR genotypes and phenotypes, and determining possible relationships between AMR, virulence, and stress response.

Investigating autism associated genes in C. elegans reveals candidates with a role in social behaviour

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterised by a triad of behavioural impairments and includes disruption in social behaviour. ASD has a clear genetic underpinning and hundreds of genes are implicated in its aetiology. However, how single penetrant genes disrupt activity of neural circuits which lead to affected behaviours is only beginning to be understood and less is known about how low penetrant genes interact to disrupt emergent behaviours. Investigations are well served by experimental approaches that allow tractable investigation of the underpinning genetic basis of circuits that control behaviours that operate in the biological domains that are neuro-atypical in autism. The model organism C. elegans provides an experimental platform to investigate the effect of genetic mutations on behavioural outputs including those that impact social biology. Here we use progeny-derived social cues that modulate C. elegans food leaving to assay genetic determinants of social behaviour. We used the SAFRI Gene database to identify C. elegans orthologues of human ASD associated genes. We identified a number of mutants that displayed selective deficits in response to progeny. The genetic determinants of this complex social behaviour highlight the important contribution of synaptopathy and implicates genes within cell signalling, epigenetics and phospholipid metabolism functional domains. The approach overlaps with a growing number of studies that investigate potential molecular determinants of autism in C. elegans. However, our use of a complex, sensory integrative, emergent behaviour provides routes to enrich new or underexplored biology with the identification of novel candidate genes with a definable role in social behaviour.

Deep ocean metagenomes provide insight into the metabolic architecture of bathypelagic microbial communities

The deep sea, the largest ocean’s compartment, drives planetary-scale biogeochemical cycling. Yet, the functional exploration of its microbial communities lags far behind other environments. Here we analyze 58 metagenomes from tropical and subtropical deep oceans to generate the Malaspina Gene Database. Free-living or particle-attached lifestyles drive functional differences in bathypelagic prokaryotic communities, regardless of their biogeography. Ammonia and CO oxidation pathways are enriched in the free-living microbial communities and dissimilatory nitrate reduction to ammonium and H2 oxidation pathways in the particle-attached, while the Calvin Benson-Bassham cycle is the most prevalent inorganic carbon fixation pathway in both size fractions. Reconstruction of the Malaspina Deep Metagenome-Assembled Genomes reveals unique non-cyanobacterial diazotrophic bacteria and chemolithoautotrophic prokaryotes. The widespread potential to grow both autotrophically and heterotrophically suggests that mixotrophy is an ecologically relevant trait in the deep ocean. These results expand our understanding of the functional microbial structure and metabolic capabilities of the largest Earth aquatic ecosystem.