Disability and genetics in the era of genomic medicine

Genomic medicine offers a growing number of methods to diagnose, cure or prevent disability. Although many disabled people welcome these advances, others have reservations about the impact of genetic knowledge on disabled people's lives, arguing that genetic science might exacerbate the deep ambivalence that society as a whole has towards physical difference and anomaly. It is also possible, however, that being able to specify the genetic bases of disability, and distinguish them from other causative factors, will contribute to a fuller understanding of disability and a better response to disabled people.     

Signalling in the genomic era

For a complex organism, short range signalling is not sufficient to coordinate the behaviour of all cells composing itself. The response to stimuli is the reprogramming of cell activity (resulting in differentiation, proliferation, stand by or apoptosis depending on the set of signals). Cells own elaborate and complex systems of proteins that enable them to communicate, including both secreted signalling molecules and related factors, deriving from relic mechanisms. The intra and intercellular signalling are actively studied not only to comprehend the basic mechanisms that allowed the evolution of mammals species on earth, but also because the alteration of one or more of these pathways is recognized to be involved in a crescent number of human diseases, both degenerative and tumoural. That is, a growing body of evidences suggest that every human disease may be analyzed and classified by a “signalling disease” point of view. This approach opens new therapeutic perspectives, virtually amplifying for every single disease the number of therapeutic targets (in terms of both genes and proteins) to upstream and/or downstream, short and/or long distance proteins interacting with the altered molecule, thus individuating many other targets to which act upon.     

Moving beyond genome sequencing into personalized genomic medicine: biological and computing challenges

A report of the second annual Beyond the Genome conference held on the 19-22 September 2011 at The Universities at Shady Grove, Rockville, Maryland, USA, where increases in computing that may help make personal genomics a reality were a major focus.     

Mouse biodiversity in the genomic era

Comparative genomics has developed by comparison of distantly related genomes, for which the link between the reported evolutionary changes and species development/physiology/ecology is not obvious. It is argued that the mouse (genus Mus) is an optimal model for microevolutionary genomics in vertebrates. This is because the mouse genome sequence, physical and genetic map have been completed, because mouse genetics, morpho-anatomy, pathology, behavior and ecology are well-studied, and because the Mus genus is a diverse, well- documented taxon, allowing comparative studies at the level of individual, population, subspecies, and species. The potential of the interaction between mouse genome and mouse biodiversity is illustrated by recent studies of speciation in the house mouse Mus musculus, and studies about the evolution of isochores, the peculiar pattern of GC-content variation across mammalian genomes.     

Managing peptidases in the genomic era

The enzymes that hydrolyse peptide bonds, called peptidases or proteases, are very important to mankind and are also very numerous. The many scientists working on these enzymes are rapidly acquiring new data, and they need good methods to store it and retrieve it. The storage and retrieval require effective systems of classification and nomenclature, and it is the design and implementation of these that we mean by 'managing' peptidases. Ten years ago Rawlings and Barrett proposed the first comprehensive system for the classification of peptidases, which included a set of simple names for the families. In the present article we describe how the system has developed since then. The peptidase classification has now been adopted for use by many other databases, and provides the structure around which the MEROPS protease database (http://merops.sanger.ac.uk) is built.     

Rats in the genomic era.

The rat genome project and the resources that it has generated are transforming the translation of rat biology to human medicine. The rat genome was sequenced to a high quality "draft," the structure and location of the genes were predicted, and a global assessment was published (Gibbs RA et al., Nature 428: 493-521, 2004). Since that time, researchers have made use of the genome sequence and annotations and related resources. We take this opportunity to review the currently available rat genome resources and to discuss the progress and future plans for the rat genome.     

Molecular dating in the genomic era

The comparison of DNA and protein sequences of extant species might be informative for reconstructing the chronology of evolutionary events on Earth. A phylogenetic tree inferred from molecular data directly depicts the evolutionary affinities of species and indirectly allows estimating the age of their origin and diversification. Molecular dating is achieved by assuming the molecular clock hypothesis, i.e., that the rate of change of nucleotide and amino acid sequences is on average constant over geological time. If paleontological calibrations are available, then absolute divergence times of species can be estimated. However, three major difficulties potentially hamper molecular dating : (1) a limited sample of genes and organisms, (2) a limited number of fossil references, and (3) pervasive variations of molecular evolutionary rates among genomes and species. To circumvent these problems, different solutions have been recently proposed. Larger data sets are built with more genes and more species sampled through the mining of an increasing number of genomes. Moreover, independent key fossils are identified to calibrate molecular clocks, and the uncertainty on their age is integrated in subsequent analyses. Finally, models of molecular rate variations are constructed, and incorporated in the so-called relaxed molecular clock approaches. As an illustration of these improvements, we mention that the debated age of the animal (bilaterian metazoans) diversification may have occurred between 642-761 million years ago (Mya), roughly 100 Ma before the Cambrian explosion. Among mammals, the initial diversification of major placental groups may have taken place around 100 Mya, well before the Cretaceous/Tertiary boundary marking the extinction of dinosaurs.     

Evolution enters the genomic era

A report on the 18th Congress of the European Society for Evolutionary Biology (ESEB), Aarhus, Denmark, 20-25 August, 2001.     

Proteomics and personalized medicine: a focus on kidney disease

ABSTRACT

Introduction: Inter-individual variability in response to drug treatment has induced an increased demand for decisions via personalize medicine. Also, the contribution of proteomics to the era of personalized medicine would seem to be vital in improving therapeutic outcomes.

Areas covered: We review validated biomarkers discovered by proteomics techniques and their use in personalized medicine with the focus on kidney diseases. We discuss this topic with a special emphasis on recent publications and relevant initiatives and depict some limitations that remain for personalized medicine.

Expert opinion: The development of highly accurate biomarkers is essential for optimizing the management of kidney diseases. Various biomarkers of kidney diseases have been identified using proteomic techniques. However, only a few of these biomarkers showed the potential to be used in clinical practice concerning personalized medicine. Therefore, it becomes evident that the combination of multiple biomarkers confers higher accuracy and the ability to depict complex pathophysiological conditions, a prerequisite for personalized treatment. CKD273, a multimarker panel for early CKD detection may serve as a first example for personalized medicine in nephrology. Based on this successful example, proteomics is expected to develop into the key technology to guide personalized intervention.     

Bacterial strain typing in the genomic era

Bacterial strain typing, or identifying bacteria at the strain level, is particularly important for diagnosis, treatment, and epidemiological surveillance of bacterial infections. This is especially the case for bacteria exhibiting high levels of antibiotic resistance or virulence, and those involved in nosocomial or pandemic infections. Strain typing also has applications in studying bacterial population dynamics. Over the last two decades, molecular methods have progressively replaced phenotypic assays to type bacterial strains. In this article, we review the current bacterial genotyping methods and classify them into three main categories: (1) DNA banding pattern-based methods, which classify bacteria according to the size of fragments generated by amplification and/or enzymatic digestion of genomic DNA, (2) DNA sequencing-based methods, which study the polymorphism of DNA sequences, and (3) DNA hybridization-based methods using nucleotidic probes. We described and compared the applications of genotyping methods to the study of bacterial strain diversity. We also discussed the selection of appropriate genotyping methods and the challenges of bacterial strain typing, described the current trends of genotyping methods, and investigated the progresses allowed by the availability of genomic sequences.     

Exploring prokaryotic diversity in the genomic era

Our understanding of prokaryote biology from study of pure cultures and genome sequencing has been limited by a pronounced sampling bias towards four bacterial phyla - Proteobacteria, Firmicutes, Actinobacteria and Bacteroidetes - out of 35 bacterial and 18 archaeal phylum-level lineages. This bias is beginning to be rectified by the use of phylogenetically directed isolation strategies and by directly accessing microbial genomes from environmental samples.     

Reconstructing human origins in the genomic era

Analyses of recently acquired genomic sequence data are leading to important insights into the early evolution of anatomically modern humans, as well as into the more recent demographic processes that accompanied the global radiation of Homo sapiens. Some of the new results contradict early, but still influential, conclusions that were based on analyses of gene trees from mitochondrial DNA and Y-chromosome sequences. In this review, we discuss the different genetic and statistical methods that are available for studying human population history, and identify the most plausible models of human evolution that can accommodate the contrasting patterns observed at different loci throughout the genome.     

Metagenomics and personalized medicine

The microbiome is a complex community of Bacteria, Archaea, Eukarya, and viruses that infect humans and live in our tissues. It contributes the majority of genetic information to our metagenome and, consequently, influences our resistance and susceptibility to diseases, especially common inflammatory diseases, such as type 1 diabetes, ulcerative colitis, and Crohn's disease. Here we discuss how host-gene-microbial interactions are major determinants for the development of these multifactorial chronic disorders and, thus, for the relationship between genotype and phenotype. We also explore how genome-wide association studies (GWAS) on autoimmune and inflammatory diseases are uncovering mechanism-based subtypes for these disorders. Applying these emerging concepts will permit a more complete understanding of the etiologies of complex diseases and underpin the development of both next-generation animal models and new therapeutic strategies for targeting personalized disease phenotypes.     

Pharmacogenomics and personalized medicine in neuropsychiatry

Despite the need for more effective treatments for psychiatric disorders, development of new medications has stalled. Here we discuss the promise of personalized medicine in developing more efficacious and individualized pharmacotherapies that take into account genetic variation and target groups of patients who share biology, not just symptoms.