Farm animal genomics and informatics: an update

Farm animal genomics is of interest to a wide audience of researchers because of the utility derived from understanding how genomics and proteomics function in various organisms. Applications such as xenotransplantation, increased livestock productivity, bioengineering new materials, products and even fabrics are several reasons for thriving farm animal genome activity. Currently mined in rapidly growing data warehouses, completed genomes of chicken, fish and cows are available but are largely stored in decentralized data repositories. In this paper, we provide an informatics primer on farm animal bioinformatics and genome project resources which drive attention to the most recent advances in the field. We hope to provide individuals in biotechnology and in the farming industry with information on resources and updates concerning farm animal genome projects

Identification of independent association signals and putative functional variants for breast cancer risk through fine-scale mapping of the 12p11 locus.

BACKGROUND: Multiple recent genome-wide association studies (GWAS) have identified a single nucleotide polymorphism (SNP), rs10771399, at 12p11 that is associated with breast cancer risk. METHOD: We performed a fine-scale mapping study of a 700 kb region including 441 genotyped and more than 1300 imputed genetic variants in 48,155 cases and 43,612 controls of European descent, 6269 cases and 6624 controls of East Asian descent and 1116 cases and 932 controls of African descent in the Breast Cancer Association Consortium (BCAC; http://bcac.ccge.medschl.cam.ac.uk/ ), and in 15,252 BRCA1 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Stepwise regression analyses were performed to identify independent association signals. Data from the Encyclopedia of DNA Elements project (ENCODE) and the Cancer Genome Atlas (TCGA) were used for functional annotation. RESULTS: Analysis of data from European descendants found evidence for four independent association signals at 12p11, represented by rs7297051 (odds ratio (OR) = 1.09, 95 % confidence interval (CI) = 1.06-1.12; P = 3 × 10(-9)), rs805510 (OR = 1.08, 95 % CI = 1.04-1.12, P = 2 × 10(-5)), and rs1871152 (OR = 1.04, 95 % CI = 1.02-1.06; P = 2 × 10(-4)) identified in the general populations, and rs113824616 (P = 7 × 10(-5)) identified in the meta-analysis of BCAC ER-negative cases and BRCA1 mutation carriers. SNPs rs7297051, rs805510 and rs113824616 were also associated with breast cancer risk at P < 0.05 in East Asians, but none of the associations were statistically significant in African descendants. Multiple candidate functional variants are located in putative enhancer sequences. Chromatin interaction data suggested that PTHLH was the likely target gene of these enhancers. Of the six variants with the strongest evidence of potential functionality, rs11049453 was statistically significantly associated with the expression of PTHLH and its nearby gene CCDC91 at P < 0.05. CONCLUSION: This study identified four independent association signals at 12p11 and revealed potentially functional variants, providing additional insights into the underlying biological mechanism(s) for the association observed between variants at 12p11 and breast cancer risk.UK funding includes Cancer Research UK and NIH.This is the final version of the article. It first appeared from BioMed Central via http://dx.doi.org/10.1186/s13058-016-0718-

Remarkable sequence signatures in archaeal genomes

Complete archaeal genomes were probed for the presence of long (≥ 25 bp) oligonucleotide repeats (words). We detected the presence of many words distributed in tandem with narrow ranges of periodicity (i.e., spacer length between repeats). Similar words were not identified in genomes of non-archaeal species, namely Escherichia coli, Bacillus subtilis, Haemophilus influenzae, Mycoplasma genitalium and Mycoplasma pneumoniae. BLAST similarity searches against the GenBank nucleotide sequence database revealed that these words were archaeal species-specific, indicating that they are of a signature character. Sequence analysis and genome viewing tools showed these repeats to be restricted to non-coding regions. Thus, archaea appear to possess a non-coding genomic signature that is absent in bacterial species. The identification of a species-specific genomic signature would be of great value to archaeal genome mapping, evolutionary studies and analyses of genome complexity

Ab Initio Study of Alkylation of Guanine-Cytosine Base Pair by Sulfur and Nitrogen Mustards

International audienceQuantum modeling of the N7(G) alkylation of guanine-cytosine (G-C) base pair by sulfur (HD) and nitrogen mustard (HN2) was performed by using the Density Functional Theory (DFT) BPW91/6-31G++DP procedure. The vibrational IR and Raman spectra are discussed with regard to the N7 position of guanine when electrophilic HD+ episulfonium and HN2+ aziridinium attack the G-C base pair. Thermodynamic and polarizability considerations are also presented. The computed electronic chemical potential and the electrophilicity of the studied species indicate that an electronic transfer is produced from the nucleophile (G-C) base pair to the electrophile HD+ episulfonium or HN2+ aziridinium during the alkylation process

Utilizing geospatial artificial intelligence to map cancer disparities across health regions

We have developed an innovative tool, the Intelligent Catchment Analysis Tool (iCAT), designed to identify and address healthcare disparities across specific regions. Powered by Artificial Intelligence and Machine Learning, our tool employs a robust Geographic Information System (GIS) to map healthcare outcomes and disease disparities. iCAT allows users to query publicly available data sources, health system data, and treatment data, offering insights into gaps and disparities in diagnosis and treatment paradigms. This project aims to promote best practices to bridge the gap in healthcare access, resources, education, and economic opportunities. The project aims to engage local and regional stakeholders in data collection and evaluation, including patients, providers, and organizations. Their active involvement helps refine the platform and guides targeted interventions for more effective outcomes. In this paper, we present two sample illustrations demonstrating how iCAT identifies healthcare disparities and analyzes the impact of social and environmental variables on outcomes. Over time, this platform can help communities make decisions to optimize resource allocation

Ezrin Overexpression by Transformed Human Ovarian Surface Epithelial Cells, Ovarian Cleft Cells, and Serous Ovarian Adenocarcinoma Cells

Objectives: We have shown that ezrin expression correlates with ovarian epithelial cancer (OVCA) cell proliferation and metastatic behavior. In this study, we evaluated ezrin expression in transformed ovarian superficial epithelial cells (OSE) in ovarian clefts and in culture. Study Design: Immunohistochemistry and Western blotting for immunoreactive ezrin (ir-ezrin) in normal ovarian tissue, cultured OSE, and ovarian epithelial cancer cells. Results: While ir-ezrin was not demonstrable in normal cuboidal surface cells or interior ovarian organelles, cells lining the ovarian clefts strongly expressed ir-ezrin. Long-term culture of OSE increased ezrin expression and cytological abnormalities. Administration of estradiol and insulin at levels reported in inclusions dramatically induced OSE ir-ezrin expression to OVCA levels and membrane specializations; ruffling, pseudopodia and filopodia. Moreover epidermal growth factor (EGF) drastically increased ezrin translocation in OSE cells in a time-dependent manner. Conclusions: Ezrin expression by OSE increases during transformation. Ezrin expression is responsive to estradiol and growth factors previously shown to be present in ovarian inclusions. These findings suggest that the microenvironment in ovarian inclusions and clefts contributes to the development of OVCA. Our findings elaborate on the mechanism of the ovarian origin of OVCA

Experimental and computational studies indicate specific binding of pVHL protein to Aurora-A kinase.

International audienceOverexpression of Aurora-A kinase is commonly detected in many cancers, whereas the von Hippel-Lindau protein (pVHL) is frequently mutated or absent in renal cell carcinoma and is involved in the Ub proteasome complex, an important degradation pathway. In order to establish a link between Aurora-A overexpression and lack of pVHL protein, we hypothesized that pVHL regulates Aurora-A expression through a physical interaction. We present the first evidence, from both biological assays and computational biology techniques, that human pVHL binds strongly to Aurora-A kinase. Extensive molecular modeling, docking, and dynamic simulations demonstrate that the structure of the pVHL protein would allow it to bind to the TPX2 binding region of Aurora-A. In view of Aurora-A's importance as a therapeutic target for the treatment of cancer, this observation provides novel insights into the Aurora-A/pVHL pathway. In addition, the detailed Aurora-A/pVHL binding structure obtained will be valuable for the design of future Aurora-A inhibitors as therapeutic agents