Project description:Interindividual heterogeneity in drug response is a central feature of all drug therapies. Studies in individual patients, families, and populations over the past several decades have identified variants in genes encoding drug elimination or drug target pathways that in some cases contribute substantially to variable efficacy and toxicity. Important associations of pharmacogenomics in cardiovascular medicine include clopidogrel and risk for in-stent thrombosis, steady-state warfarin dose, myotoxicity with simvastatin, and certain drug-induced arrhythmias. This review describes methods used to accumulate and validate these findings and points to approaches--now being put in place at some centers--to implementing them in clinical care.
Project description:Cardiovascular disease (CVD) is a heterogeneous, complex trait that has a major impact on human morbidity and mortality. Common genetic variation may predispose to common forms of CVD in the community, and rare genetic conditions provide unique pathogenetic insights into these diseases. With the advent of the Human Genome Project and the genomic era, new tools and methodologies have revolutionised the field of genetic research in cardiovascular medicine. In this review, we describe the rationale for the current emphasis on large-scale genomic studies, elaborate on genome wide association studies and summarise the impact of genomics on clinical cardiovascular medicine and how this may eventually lead to new therapeutics and personalised medicine.
Project description:Pharmacogenomics has a burgeoning role in cardiovascular medicine, from warfarin dosing to antiplatelet choice, with recent developments in sequencing bringing the promise of personalised medicine ever closer to the bedside. Further scientific evidence, real-world clinical trials, and economic modelling are needed to fully realise this potential. Additionally, tools such as polygenic risk scores, and results from Mendelian randomisation analyses, are only in the early stages of clinical translation and merit further investigation. Genetically targeted rational drug design has a strong evidence base and, due to the nature of genetic data, academia, direct-to-consumer companies, healthcare systems, and industry may meet in an unprecedented manner. Data sharing navigation may prove problematic. The present manuscript addresses these issues and concludes a need for further guidance to be provided to prescribers by professional bodies to aid in the consideration of such complexities and guide translation of scientific knowledge to personalised clinical action, thereby striving to improve patient care. Additionally, technologic infrastructure equipped to handle such large complex data must be adapted to pharmacogenomics and made user friendly for prescribers and patients alike.
Project description:Chickpea is an important grain legume used as a rich source of protein in human diet. The narrow genetic diversity and limited availability of genomic resources are the major constraints in implementing breeding strategies and biotechnological interventions for genetic enhancement of chickpea. We developed an integrated Chickpea Transcriptome Database (CTDB), which provides the comprehensive web interface for visualization and easy retrieval of transcriptome data in chickpea. The database features many tools for similarity search, functional annotation (putative function, PFAM domain and gene ontology) search and comparative gene expression analysis. The current release of CTDB (v2.0) hosts transcriptome datasets with high quality functional annotation from cultivated (desi and kabuli types) and wild chickpea. A catalog of transcription factor families and their expression profiles in chickpea are available in the database. The gene expression data have been integrated to study the expression profiles of chickpea transcripts in major tissues/organs and various stages of flower development. The utilities, such as similarity search, ortholog identification and comparative gene expression have also been implemented in the database to facilitate comparative genomic studies among different legumes and Arabidopsis. Furthermore, the CTDB represents a resource for the discovery of functional molecular markers (microsatellites and single nucleotide polymorphisms) between different chickpea types. We anticipate that integrated information content of this database will accelerate the functional and applied genomic research for improvement of chickpea. The CTDB web service is freely available at http://nipgr.res.in/ctdb.html.
Project description:The development of high-throughput sequencing (next-generation sequencing technology (NGS)) and the continuous increase in experimental throughput require the upstream sample processing steps of NGS to be as simple as possible to improve the efficiency of the entire NGS process. The transposition system has fast "cut and paste" and "copy and paste" functions, and has been innovatively applied to the NGS field. For example, the Assay for Transposase-Accessible Chromatin with high throughput sequencing (ATAC-Seq) uses high-throughput sequencing to detect chromatin regions accessible by Tn5 transposase. Linear Amplification via Transposon Insertion (LIANTI) uses Tn5 transposase for linear amplification, haploid typing, and structural variation detection. Not only is it efficient and simple, it effectively shortens the time for NGS sample library construction, realizes large-scale and rapid sequencing, improves sequencing resolution, and can be flexibly modified for more technological innovation.
Project description:The Rice TOGO Browser is an online public resource designed to facilitate integration and visualization of mapping data of bacterial artificial chromosome (BAC)/P1-derived artificial chromosome (PAC) clones, genes, restriction fragment length polymorphism (RFLP)/simple sequence repeat (SSR) markers and phenotype data represented as quantitative trait loci (QTLs) onto the genome sequence, and to provide a platform for more efficient utilization of genome information from the point of view of applied genomics as well as functional genomics. Three search options, namely keyword search, region search and trait search, generate various types of data in a user-friendly interface with three distinct viewers, a chromosome viewer, an integrated map viewer and a sequence viewer, thereby providing the opportunity to view the position of genes and/or QTLs at the chromosomal level and to retrieve any sequence information in a user-defined genome region. Furthermore, the gene list, marker list and genome sequence in a specified region delineated by RFLP/SSR markers and any sequences designed as primers can be viewed and downloaded to support forward genetics approaches. An additional feature of this database is the graphical viewer for BLAST search to reveal information not only for regions with significant sequence similarity but also for regions adjacent to those with similarity but with no hits between sequences. An easy to use and intuitive user interface can help a wide range of users in retrieving integrated mapping information including agronomically important traits on the rice genome sequence. The database can be accessed at http://agri-trait.dna.affrc.go.jp/.
Project description:PurposeThis article provides an update on cardiovascular genomics using three clinically relevant exemplars, including myocardial infarction (MI) and coronary artery disease (CAD), stroke, and sudden cardiac death (SCD). ORGANIZATIONAL CONSTRUCT: Recent advances in cardiovascular genomic research, testing, and clinical implications are presented.MethodsGenomic nurse experts reviewed and summarized recent salient literature to provide updates on three selected cardiovascular genomic conditions.FindingsResearch is ongoing to discover comprehensive genetic markers contributing to many common forms of cardiovascular disease (CVD), including MI and stroke. However, genomic technologies are increasingly being used clinically, particularly in patients with long QT syndrome (LQTS) or hypertrophic cardiomyopathy (HCM) who are at risk for SCD.ConclusionsCurrently, there are no clinically recommended genetic tests for many common forms of CVD even though direct-to-consumer genetic tests are being marketed to healthcare providers and the general public. On the other hand, genetic testing for patients with certain single gene conditions, including channelopathies (e.g., LQTS) and cardiomyopathies (e.g., HCM), is recommended clinically.Clinical relevanceNurses play a pivotal role in cardiogenetics and are actively engaged in direct clinical care of patients and families with a wide variety of heritable conditions. It is important for nurses to understand current development of cardiovascular genomics and be prepared to translate the new genomic knowledge into practice.
Project description:Nonnegative matrix factorization (NMF) is widely used to analyze high-dimensional count data because, in contrast to real-valued alternatives such as factor analysis, it produces an interpretable parts-based representation. However, in applications such as spatial transcriptomics, NMF fails to incorporate known structure between observations. Here, we present nonnegative spatial factorization (NSF), a spatially-aware probabilistic dimension reduction model based on transformed Gaussian processes that naturally encourages sparsity and scales to tens of thousands of observations. NSF recovers ground truth factors more accurately than real-valued alternatives such as MEFISTO in simulations, and has lower out-of-sample prediction error than probabilistic NMF on three spatial transcriptomics datasets from mouse brain and liver. Since not all patterns of gene expression have spatial correlations, we also propose a hybrid extension of NSF that combines spatial and nonspatial components, enabling quantification of spatial importance for both observations and features. A TensorFlow implementation of NSF is available from https://github.com/willtownes/nsf-paper .