Dataset Information

Computational Prediction of Phylogenetically Conserved Sequence Motifs for Five Different Candidate Genes in Type II Diabetic Nephropathy.

ABSTRACT: BACKGROUND: Computational identification of phylogenetic motifs helps to understand the knowledge about known functional features that includes catalytic site, substrate binding epitopes, and protein-protein interfaces. Furthermore, they are strongly conserved among orthologs, indicating their evolutionary importance. The study aimed to analyze five candidate genes involved in type II diabetic nephropathy and to predict phylogenetic motifs from their corresponding orthologous protein sequences. METHODS: AKR1B1, APOE, ENPP1, ELMO1 and IGFBP1 are the genes that have been identified as an important target for type II diabetic nephropathy through experimental studies. Their corresponding protein sequences, structures, orthologous sequences were retrieved from UniprotKB, PDB, and PHOG database respectively. Multiple sequence alignments were constructed using ClustalW and phylogenetic motifs were identified using MINER. The occurrence of amino acids in the obtained phylogenetic motifs was generated using WebLogo and false positive expectations were calculated against phylogenetic similarity. RESULTS: In total, 17 phylogenetic motifs were identified from the five proteins and the residues such as glycine, leucine, tryptophan, aspartic acid were found in appreciable frequency whereas arginine identified in all the predicted PMs. The result implies that these residues can be important to the functional and structural role of the proteins and calculated false positive expectations implies that they were generally conserved in traditional sense. CONCLUSION: The prediction of phylogenetic motifs is an accurate method for detecting functionally important conserved residues. The conserved motifs can be used as a potential drug target for type II diabetic nephropathy.

SUBMITTER: Sindhu T

PROVIDER: S-EPMC3469011 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Computational Prediction of Phylogenetically Conserved Sequence Motifs for Five Different Candidate Genes in Type II Diabetic Nephropathy.

Sindhu T T Rajamanikandan S S Srinivasan P P

Iranian journal of public health 20120731 7

<h4>Background</h4>Computational identification of phylogenetic motifs helps to understand the knowledge about known functional features that includes catalytic site, substrate binding epitopes, and protein-protein interfaces. Furthermore, they are strongly conserved among orthologs, indicating their evolutionary importance. The study aimed to analyze five candidate genes involved in type II diabetic nephropathy and to predict phylogenetic motifs from their corresponding orthologous protein sequ ...[more]

PMID: 23113206

Similar Datasets

Project description:BackgroundA substantial fraction of non-coding DNA sequences of multicellular eukaryotes is under selective constraint. In particular, approximately 5% of the human genome consists of conserved non-coding sequences (CNSs). CNSs differ from other genomic sequences in their nucleotide composition and must play important functional roles, which mostly remain obscure.ResultsWe investigated relative abundances of short sequence motifs in all human CNSs present in the human/mouse whole-genome alignments vs. three background sets of sequences: (i) weakly conserved or unconserved non-coding sequences (non-CNSs); (ii) near-promoter sequences (located between nucleotides -500 and -1500, relative to a start of transcription); and (iii) random sequences with the same nucleotide composition as that of CNSs. When compared to non-CNSs and near-promoter sequences, CNSs possess an excess of AT-rich motifs, often containing runs of identical nucleotides. In contrast, when compared to random sequences, CNSs contain an excess of GC-rich motifs which, however, lack CpG dinucleotides. Thus, abundance of short sequence motifs in human CNSs, taken as a whole, is mostly determined by their overall compositional properties and not by overrepresentation of any specific short motifs. These properties are: (i) high AT-content of CNSs, (ii) a tendency, probably due to context-dependent mutation, of A's and T's to clump, (iii) presence of short GC-rich regions, and (iv) avoidance of CpG contexts, due to their hypermutability. Only a small number of short motifs, overrepresented in all human CNSs are similar to binding sites of transcription factors from the FOX family.ConclusionHuman CNSs as a whole appear to be too broad a class of sequences to possess strong footprints of any short sequence-specific functions. Such footprints should be studied at the level of functional subclasses of CNSs, such as those which flank genes with a particular pattern of expression. Overall properties of CNSs are affected by patterns in mutation, suggesting that selection which causes their conservation is not always very strong.

Project description:BackgroundNucleic acids containing guanine tracts can form quadruplex structures via non-Watson-Crick base pairing. Formation of G-quadruplexes is associated with the regulation of important biological functions such as transcription, genetic instability, DNA repair, DNA replication, epigenetic mechanisms, regulation of translation, and alternative splicing. G-quadruplexes play important roles in human diseases and are being considered as targets for a variety of therapies. Identification of functional G-quadruplexes and the study of their overall distribution in genomes and transcriptomes is an important pursuit. Traditional computational methods map sequence motifs capable of forming G-quadruplexes but have difficulty in distinguishing motifs that occur by chance from ones which fold into G-quadruplexes.ResultsWe present Quadruplex forming 'G'-rich sequences (QGRS)-Conserve, a computational method for calculating motif conservation across exomes and supports filtering to provide researchers with more precise methods of studying G-quadruplex distribution patterns. Our method quantitatively evaluates conservation between quadruplexes found in homologous nucleotide sequences based on several motif structural characteristics. QGRS-Conserve also efficiently manages overlapping G-quadruplex sequences such that the resulting datasets can be analyzed effectively.ConclusionsWe have applied QGRS-Conserve to identify a large number of G-quadruplex motifs in the human exome conserved across several mammalian and non-mammalian species. We have successfully identified multiple homologs of many previously published G-quadruplexes that play post-transcriptional regulatory roles in human genes. Preliminary large-scale analysis identified many homologous G-quadruplexes in the 5'- and 3'-untranslated regions of mammalian species. An expectedly smaller set of G-quadruplex motifs was found to be conserved across larger phylogenetic distances. QGRS-Conserve provides means to build datasets that can be filtered and categorized in a variety of biological dimensions for more targeted studies in order to better understand the roles that G-quadruplexes play.

Dataset Information

Computational Prediction of Phylogenetically Conserved Sequence Motifs for Five Different Candidate Genes in Type II Diabetic Nephropathy.

Publications

Computational Prediction of Phylogenetically Conserved Sequence Motifs for Five Different Candidate Genes in Type II Diabetic Nephropathy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets