Indra Neil Sarkar

Character-based DNA barcoding allows discrimination of genera, species and populations in Odonata

DNA barcoding has become a promising means for identifying organisms of all life stages. Currently, phenetic approaches and tree-building methods have been used to define species boundaries and discover ‘cryptic species’. However, a universal threshold of genetic distance values to distinguish taxonomic groups cannot be determined. As an alternative, DNA barcoding approaches can be ‘character based’, whereby species are identified through the presence or absence of discrete nucleotide substitutions (character states) within a DNA sequence. We demonstrate the potential of character-based DNA barcodes by analysing 833 odonate specimens from 103 localities belonging to 64 species. A total of 54 species and 22 genera could be discriminated reliably through unique combinations of character states within only one mitochondrial gene region (NADH dehydrogenase 1). Character-based DNA barcodes were further successfully established at a population level discriminating seven population-specific entities out of a total of 19 populations belonging to three species. Thus, for the first time, DNA barcodes have been found to identify entities below the species level that may constitute separate conservation units or even species units. Our findings suggest that character-based DNA barcoding can be a rapid and reliable means for (i) the assignment of unknown specimens to a taxonomic group, (ii) the exploration of diagnosability of conservation units, and (iii) complementing taxonomic identification systems.

CAOS software for use in character-based DNA barcoding

The success of character‐based DNA barcoding depends on the efficient identification of diagnostic character states from molecular sequences that have been organized hierarchically (e.g. according to phylogenetic methods). Similarly, the reliability of these identified diagnostic character states must be assessed according to their ability to diagnose new sequences. Here, a set of software tools is presented that implement the previously described Characteristic Attribute Organization System for both diagnostic identification and diagnostic‐based classification. The software is publicly available from http://sarkarlab.mbl.edu/CAOS.

OrthologID: automation of genome-scale ortholog identification within a parsimony framework

MOTIVATION The determination of gene orthology is a prerequisite for mining and utilizing the rapidly increasing amount of sequence data for genome-scale phylogenetics and comparative genomic studies. Until now, most researchers use pairwise distance comparisons algorithms, such as BLAST, COG, RBH, RSD and INPARANOID, to determine gene orthology. In contrast, orthology determination within a character-based phylogenetic framework has not been utilized on a genomic scale owing to the lack of efficiency and automation. RESULTS We have developed OrthologID, a Web application that automates the labor-intensive procedures of gene orthology determination within a character-based phylogenetic framework, thus making character-based orthology determination on a genomic scale possible. In addition to generating gene family trees and determining orthologous gene sets for complete genomes, OrthologID can also identify diagnostic characters that define each orthologous gene set, as well as diagnostic characters that are responsible for classifying query sequences from other genomes into specific orthology groups. The OrthologID database currently includes several complete plant genomes, including Arabidopsis thaliana, Oryza sativa, Populus trichocarpa, as well as a unicellular outgroup, Chlamydomonas reinhardtii. To improve the general utility of OrthologID beyond plant species, we plan to expand our sequence database to include the fully sequenced genomes of prokaryotes and other non-plant eukaryotes. AVAILABILITY http://nypg.bio.nyu.edu/orthologid/

Appearance of new tetraspanin genes during vertebrate evolution

A detailed phylogenetic analysis of tetraspanins from 10 fully sequenced metazoan genomes and several fungal and protist genomes gives insight into their evolutionary origins and organization. Our analysis suggests that the superfamily can be divided into four large families. These four families-the CD family, CD63 family, uroplakin family, and RDS family-are further classified as consisting of several ortholog groups. The clustering of several ortholog groups together, such as the CD9/Tsp2/CD81 cluster, suggests functional relatedness of those ortholog groups. The fact that our studies are based on whole genome analysis enabled us to estimate not only the phylogenetic relationships among the tetraspanins, but also the first appearance in the tree of life of certain tetraspanin ortholog groups. Taken together, our data suggest that the tetraspanins are derived from a single (or a few) ancestral gene(s) through sequence divergence, rather than convergence, and that the majority of tetraspanins found in the human genome are vertebrate (21 instances), tetrapod (4 instances), or mammalian (6 instances) inventions.

The impact of taxon sampling on phylogenetic inference: a review of two decades of controversy

Over the past two decades, there has been a long-standing debate about the impact of taxon sampling on phylogenetic inference. Studies have been based on both real and simulated data sets, within actual and theoretical contexts, and using different inference methods, to study the impact of taxon sampling. In some cases, conflicting conclusions have been drawn for the same data set. The main questions explored in studies to date have been about the effects of using sparse data, adding new taxa, including more characters from genome sequences and using different (or concatenated) locus regions. These questions can be reduced to more fundamental ones about the assessment of data quality and the design guidelines of taxon sampling in phylogenetic inference experiments. This review summarizes progress to date in understanding the impact of taxon sampling on the accuracy of phylogenetic analysis.

Translational bioinformatics: linking knowledge across biological and clinical realms

Nearly a decade since the completion of the first draft of the human genome, the biomedical community is positioned to usher in a new era of scientific inquiry that links fundamental biological insights with clinical knowledge. Accordingly, holistic approaches are needed to develop and assess hypotheses that incorporate genotypic, phenotypic, and environmental knowledge. This perspective presents translational bioinformatics as a discipline that builds on the successes of bioinformatics and health informatics for the study of complex diseases. The early successes of translational bioinformatics are indicative of the potential to achieve the promise of the Human Genome Project for gaining deeper insights to the genetic underpinnings of disease and progress toward the development of a new generation of therapies.

Data analysis and data mining: current issues in biomedical informatics.

BACKGROUND Medicine and biomedical sciences have become data-intensive fields, which, at the same time, enable the application of data-driven approaches and require sophisticated data analysis and data mining methods. Biomedical informatics provides a proper interdisciplinary context to integrate data and knowledge when processing available information, with the aim of giving effective decision-making support in clinics and translational research. OBJECTIVES To reflect on different perspectives related to the role of data analysis and data mining in biomedical informatics. METHODS On the occasion of the 50th year of Methods of Information in Medicine a symposium was organized, which reflected on opportunities, challenges and priorities of organizing, representing and analysing data, information and knowledge in biomedicine and health care. The contributions of experts with a variety of backgrounds in the area of biomedical data analysis have been collected as one outcome of this symposium, in order to provide a broad, though coherent, overview of some of the most interesting aspects of the field. RESULTS The paper presents sections on data accumulation and data-driven approaches in medical informatics, data and knowledge integration, statistical issues for the evaluation of data mining models, translational bioinformatics and bioinformatics aspects of genetic epidemiology. CONCLUSIONS Biomedical informatics represents a natural framework to properly and effectively apply data analysis and data mining methods in a decision-making context. In the future, it will be necessary to preserve the inclusive nature of the field and to foster an increasing sharing of data and methods between researchers.

Bioinformatics opportunities for identification and study of medicinal plants

Plants have been used as a source of medicine since historic times and several commercially important drugs are of plant-based origin. The traditional approach towards discovery of plant-based drugs often times involves significant amount of time and expenditure. These labor-intensive approaches have struggled to keep pace with the rapid development of high-throughput technologies. In the era of high volume, high-throughput data generation across the biosciences, bioinformatics plays a crucial role. This has generally been the case in the context of drug designing and discovery. However, there has been limited attention to date to the potential application of bioinformatics approaches that can leverage plant-based knowledge. Here, we review bioinformatics studies that have contributed to medicinal plants research. In particular, we highlight areas in medicinal plant research where the application of bioinformatics methodologies may result in quicker and potentially cost-effective leads toward finding plant-based remedies.

Origins of amyloid-β

BackgroundAmyloid-β plaques are a defining characteristic of Alzheimer Disease. However, Amyloid-β deposition is also found in other forms of dementia and in non-pathological contexts. Amyloid-β deposition is variable among vertebrate species and the evolutionary emergence of the amyloidogenic property is currently unknown. Evolutionary persistence of a pathological peptide sequence may depend on the functions of the precursor gene, conservation or mutation of nucleotides or peptide domains within the precursor gene, or a species-specific physiological environment.ResultsIn this study, we asked when amyloidogenic Amyloid-β first arose using phylogenetic trees constructed for the Amyloid-β Precursor Protein gene family and by modeling the potential for Amyloid-β aggregation across species in silico. We collected the most comprehensive set of sequences for the Amyloid-β Precursor Protein family using an automated, iterative meta-database search and constructed a highly resolved phylogeny. The analysis revealed that the ancestral gene for invertebrate and vertebrate Amyloid-β Precursor Protein gene families arose around metazoic speciation during the Ediacaran period. Synapomorphic frequencies found domain-specific conservation of sequence. Analyses of aggregation potential showed that potentially amyloidogenic sequences are a ubiquitous feature of vertebrate Amyloid-β Precursor Protein but are also found in echinoderm, nematode, and cephalochordate, and hymenoptera species homologues.ConclusionsThe Amyloid-β Precursor Protein gene is ancient and highly conserved. The amyloid forming Amyloid-β domains may have been present in early deuterostomes, but more recent mutations appear to have resulted in potentially unrelated amyoid forming sequences. Our results further highlight that the species-specific physiological environment is as critical to Amyloid-β formation as the peptide sequence.

Salivary Transcriptome of the North American Medicinal Leech, Macrobdella decora

Abstract A variety of bioactive proteins from medicinal leeches, like species of Hirudo, have been characterized and evaluated for their potential therapeutic biomedical properties. However, there has not previously been a comprehensive attempt to fully characterize the salivary transcriptome of a medicinal leech that would allow a clearer understanding of the suite of polypeptides employed by these sanguivorous annelids and provide insights regarding their evolutionary origins. An Expressed Sequence Tag (EST) library-based analysis of the salivary transcriptome of the North American medicinal leech, Macrobdella decora, reveals a complex cocktail of anticoagulants and other bioactive secreted proteins not previously known to exist in a single leech. Transcripts were identified that correspond to each of saratin, bdellin, destabilase, hirudin, decorsin, endoglucoronidase, antistatin, and eglin, as well as to other previously uncharacterized predicted serine protease inhibitors, lectoxin-like c-type lectins, ficolin, disintegrins and histidine-rich proteins. This work provides a lens into the richness of bioactive polypeptides that are associated with sanguivory. In the context of a well-characterized molecular phylogeny of leeches, the results allow for preliminary evaluation of the relative evolutionary origins and historical conservation of leech salivary components. The goal of identifying evolutionarily significant residues associated with biomedically significant phenomena implies continued insights from a broader sampling of blood-feeding leech salivary transcriptomes.