miRNA Biogenesis and Regulation of Diseases: An Updated Overview.

MicroRNAs (miRNAs) are small RNA molecules, with their role in gene silencing and translational repression by binding to the target mRNAs. Since it was discovered in 1993, miRNA is found in all eukaryotic cells conserved across the species. miRNA-size molecules are also known to be found in prokaryotes. Regulation of miRNAs is extensively studied for their role in biological processes as well as in development and progression of various human diseases including neurodegenerative diseases, cardiovascular disease, and cancer. miRNA-based therapy has a promising application, and with a good delivery system, miRNA therapeutics can potentially be a success. miRNAs and EVs have potential therapeutic and prognostic application in a range of disease models. This chapter summarizes miRNA biogenesis and explores their potential roles in a variety of diseases. miRNAs hold huge potential for diagnostic and prognostic biomarkers and as predictors of drug response.

GOLD standard dataset for Alzheimer genes.

Alzheimer disease is a genetically complex multigenic neurodegenerative disorder, resulting from the interaction between multiple genes. Most of the earlier studies reported only few specific genes that have involvement in Alzheimer. However more than hundreds of susceptible genes have been observed, that have significant role in the development and progression of Alzheimer. Among all the existing data resources, Genetic association database is the most popular data source that contains information about genes, their association classes into positive, negative and neutral class and supporting reference. However, it contains lot of false positives and negatives associations. We have taken this data as reference and performed the double fold cross validation to compile the comprehensive list of Alzheimer genes, their association class viz, positive, negative or ambiguous with the disease and reference sentence confirming the association. The data generated will be used as a GOLD standard reference data set for the training of machine learning classifier to predict the classification of published literature not only in Alzheimer but in other diseases as well. In addition, positive associated genes data can also be used for the system level modelling or meta analysis of Alzheimer.

MiRNA Biogenesis and Regulation of Diseases: An Overview.

MicroRNAs (miRNAs) are small RNA molecules, with their role in gene silencing and translational repression by binding to target mRNAs. Since it was discovered in 1993, miRNA are found in all eukaryotic cells conserved across the species. In recent years, regulation of miRNAs are extensively studied for their role in biological processes as well as in development and progression of various human diseases including retinal disorder, neurodegenerative diseases, cardiovascular disease and cancer. This chapter summarises miRNA biogenesis and explores their potential roles in a variety of diseases. miRNAs holds huge potential for diagnostic and prognostic biomarkers, and as predictors of drug response.

Episodes of horizontal gene-transfer and gene-fusion led to co-existence of different metal-ion specific glyoxalase I.

Glyoxalase pathway plays an important role in stress adaptation and many clinical disorders. The first enzyme of this pathway, glyoxalase I (GlxI), uses methylglyoxal as a substrate and requires either Ni(II)/Co(II) or Zn(II) for activity. Here we have investigated the origin of different metal ion specificities of GlxI and subsequent pattern of inheritance during evolution. Our results suggest a primitive origin of single-domain Ni dependent GlxI [Ni-GlxI]. This subsequently evolved into Zn activated GlxI [Zn-GlxI] in deltaproteobacteria. However, origin of eukaryotic Zn-GlxI is different and can be traced to GlxI from Candidatus pelagibacter and Sphingomonas. In eukaryotes GlxI has evolved as two-domain protein but the corresponding Zn form is lost in plants/higher eukaryotes. In plants gene expansion has given rise to multiple two-domain Ni-GlxI which are differentially regulated under abiotic stress conditions. Our results suggest that different forms of GlxI have evolved to help plants adapt to stress.

Next-Generation Anchor Based Phylogeny (NexABP): constructing phylogeny from next-generation sequencing data.

Whole genome sequences are ideally suited for deriving evolutionary relationship among organisms. With the availability of Next Generation sequencing (NGS) datasets in an unprecedented scale, it will be highly desirable if phylogenetic analysis can be carried out using short read NGS data. We described here an anchor based approach NexABP for phylogenetic construction of closely related strains/isolates from NGS data. This approach can be used even in the absence of a fully assembled reference genome and works by reducing the complexity of the datasets without compromising results. NexABP was used for constructing phylogeny of different strains of some of the common pathogens, such as Mycobacterium tuberculosis, Vibrio cholera and Escherichia coli. In addition to classification into distinct lineages, NexABP could resolve inner branches and also allow statistical testing using bootstrap analysis. We believe that there are some clear advantages of using NexABP based phylogenetic analysis as compared to other methods.

Genome-wide survey of natural selection on functional, structural, and network properties of polymorphic sites in Saccharomyces paradoxus.

BACKGROUND: To characterize the genetic basis of phenotypic evolution, numerous studies have identified individual genes that have likely evolved under natural selection. However, phenotypic changes may represent the cumulative effect of similar evolutionary forces acting on functionally related groups of genes. Phylogenetic analyses of divergent yeast species have identified functional groups of genes that have evolved at significantly different rates, suggestive of differential selection on the functional properties. However, due to environmental heterogeneity over long evolutionary timescales, selection operating within a single lineage may be dramatically different, and it is not detectable via interspecific comparisons alone. Moreover, interspecific studies typically quantify selection on protein-coding regions using the D(n)/D(s) ratio, which cannot be extended easily to study selection on noncoding regions or synonymous sites. The population genetic-based analysis of selection operating within a single lineage ameliorates these limitations. FINDINGS: We investigated selection on several properties associated with genes, promoters, or polymorphic sites, by analyzing the derived allele frequency spectrum of single nucleotide polymorphisms (SNPs) in 28 strains of Saccharomyces paradoxus. We found evidence for significant differential selection between many functionally relevant categories of SNPs, underscoring the utility of function-centric approaches for discovering signatures of natural selection. When comparable, our findings are largely consistent with previous studies based on interspecific comparisons, with one notable exception: our study finds that mutations from an ancient amino acid to a relatively new amino acid are selectively disfavored, whereas interspecific comparisons have found selection against ancient amino acids. Several of our findings have not been addressed through prior interspecific studies: we find that synonymous mutations from preferred to unpreferred codons are selected against and that synonymous SNPs in the linker regions of proteins are relatively less constrained than those within protein domains. CONCLUSIONS: We present the first global survey of selection acting on various functional properties in S. paradoxus. We found that selection pressures previously detected over long evolutionary timescales have also shaped the evolution of S. paradoxus. Importantly, we also make novel discoveries untenable via conventional interspecific analyses.

Anchor-based whole genome phylogeny (ABWGP): a tool for inferring evolutionary relationship among closely related microorganisms [corrected].

Phenotypic behavior of a group of organisms can be studied using a range of molecular evolutionary tools that help to determine evolutionary relationships. Traditionally a gene or a set of gene sequences was used for generating phylogenetic trees. Incomplete evolutionary information in few selected genes causes problems in phylogenetic tree construction. Whole genomes are used as remedy. Now, the task is to identify the suitable parameters to extract the hidden information from whole genome sequences that truly represent evolutionary information. In this study we explored a random anchor (a stretch of 100 nucleotides) based approach (ABWGP) for finding distance between any two genomes, and used the distance estimates to compute evolutionary trees. A number of strains and species of Mycobacteria were used for this study. Anchor-derived parameters, such as cumulative normalized score, anchor order and indels were computed in a pair-wise manner, and the scores were used to compute distance/phylogenetic trees. The strength of branching was determined by bootstrap analysis. The terminal branches are clearly discernable using the distance estimates described here. In general, different measures gave similar trees except the trees based on indels. Overall the tree topology reflected the known biology of the organisms. This was also true for different strains of Escherichia coli. A new whole genome-based approach has been described here for studying evolutionary relationships among bacterial strains and species.

Young proteins experience more variable selection pressures than old proteins.

It is well known that young proteins tend to experience weaker purifying selection and evolve more quickly than old proteins. Here, we show that, in addition, young proteins tend to experience more variable selection pressures over time than old proteins. We demonstrate this pattern in three independent taxonomic groups: yeast, Drosophila, and mammals. The increased variability of selection pressures on young proteins is highly significant even after controlling for the fact that young proteins are typically shorter and experience weaker purifying selection than old proteins. The majority of our results are consistent with the hypothesis that the function of a young gene tends to change over time more readily than that of an old gene. At the same time, our results may be caused in part by young genes that serve constant functions over time, but nevertheless appear to evolve under changing selection pressures due to depletion of adaptive mutations. In either case, our results imply that the evolution of a protein-coding sequence is partly determined by its age and origin, and not only by the phenotypic properties of the encoded protein. We discuss, via specific examples, the consequences of these findings for understanding of the sources of evolutionary novelty.

ABWGAT: anchor-based whole genome analysis tool.

SUMMARY: Large numbers of genomes are being sequenced regularly and the rate will go up in future due to availability of new genome sequencing techniques. In order to understand genotype to phenotype relationships, it is necessary to identify sequence variations at the genomic level. Alignment of a pair of genomes and parsing the alignment data is an accepted approach for identification of variations. Though there are a number of tools available for whole-genome alignment, none of these allows automatic parsing of the alignment and identification of different kinds of genomic variants with high degree of sensitivity. Here we present a simple web-based interface for whole genome comparison named ABWGAT (Anchor-Based Whole Genome Analysis Tool) that is simple to use. The output is a list of variations such as SNVs, indels, repeat expansion and inversion. AVAILABILITY: The web server is freely available to non-commercial users at the following address http://abwgc.jnu.ac.in/_sarba. Supplementary data are available at http://abwgc.jnu.ac.in/_sarba/cgi-bin/abwgc_retrival.cgi using job id 524, 526 and 528. CONTACT: dsarbashis@gmail.com; alok.bhattacharya@gmail.com

Single-nucleotide variations associated with Mycobacterium tuberculosis KwaZulu-Natal strains.

The occurrence of drug resistance in Mycobacterium tuberculosis, the aetiological agent of tuberculosis (TB), is hampering the management and control of TB in the world. Here we present a computational analysis of recently sequenced drug-sensitive (DS), multidrug-resistant (MDR) and extensively drug-resistant (XDR) strains of M. tuberculosis. Single-nucleotide variations (SNVs) were identified in a pair-wise manner using the anchor-based whole genome comparison (ABWGC) tool and its modified version. For this analysis, four fully sequenced genomes of different strains of M. tuberculosis were taken along with three KwaZulu-Natal (KZN) strains isolated from South Africa including one XDR and one MDR strain. KZN strains were compared with other fully sequenced strains and also among each other. The variations were analysed with respect to their biological influence as a result of either altered structure or synthesis. The results suggest that the DR phenotype may be due to changes in a number of genes. The database on KZN strains can be accessed through the website http://mirna.jnu.ac.in/mgdd/.

MGDD: Mycobacterium tuberculosis genome divergence database.

BACKGROUND: Variation in genomes among different closely-related organisms can be linked to phenotypic differences. A number of mechanisms, such as replication error, repeat expansion and contraction, recombination and transposition can contribute to genomic differences. These processes lead to generation of SNPs, different types of repeat-based and transposons or IS-element-based polymorphisms, inversions and duplications and changes in synteny. A database of all the variations in a group of organisms is not only useful for understanding genotype-phenotype relationship but also in clinical applications. There is no database available at present that provides information about detailed genomic variations among different strains and species of Mycobacterium tuberculosis complex, organisms responsible for human diseases. DESCRIPTION: MGDD is a free web-based database that allows quick user friendly search to find different types of genomic variations among a group of fully sequenced organisms belonging to M. tuberculosis complex. The searches are based on data generated by pair wise comparison using a tool that has already been described. Different types of variations that can be searched are SNPs, indels, tandem repeats and divergent regions. The searches can be designed to find specific variations either in a given gene or any given location of the query genome with respect to any other genome currently available. CONCLUSION: Web-based database MGDD can help to find all the possible differences that exists between two strains or species of M. tuberculosis complex. The search tool is very user-friendly and can be used by anyone not familiar with computational methods and will be useful to both clinicians and researchers working on tuberculosis and other Mycobacterial diseases.

Comparative analysis of bacterial genomes: identification of divergent regions in mycobacterial strains using an anchor-based approach.

Comparative genomic approaches are useful in identifying molecular differences between organisms. Currently available methods fail to identify small changes in genomes, such as expansion of short repetitive motifs and to analyse divergent sequences. In this report, we describe an anchor-based whole genome comparison (ABWGC) method. ABWGC is based on random sampling of anchor sequences from one genome, followed by analysis of sampled and homologous regions from the target genome. The method was applied to compare two strains of Mycobacterium tuberculosis CDC1551 and H37Rv. ABWGC was able to identify a total of 104 indels including 20 expansion of short repetitive sequences and five recombination events. It included 18 new unidentified genomic differences. ABWGC also identified 188 SNPs including eight new ones. The method was also used to compare M. tuberculosis H37Rv and M. avium genomes. ABWGC was able to correctly pick 1002 additional indels (size >100 nt) between the two organisms in contrast to MUMmer, a popular tool for comparative genomics. ABWGC was able to identify correctly repeat expansion and indels in a set of simulated sequences. The study also revealed important role of small repeat expansion in the evolution of M. tuberculosis strains.