Dataset Information

CSMET: comparative genomic motif detection via multi-resolution phylogenetic shadowing.

ABSTRACT: Functional turnover of transcription factor binding sites (TFBSs), such as whole-motif loss or gain, are common events during genome evolution. Conventional probabilistic phylogenetic shadowing methods model the evolution of genomes only at nucleotide level, and lack the ability to capture the evolutionary dynamics of functional turnover of aligned sequence entities. As a result, comparative genomic search of non-conserved motifs across evolutionarily related taxa remains a difficult challenge, especially in higher eukaryotes, where the cis-regulatory regions containing motifs can be long and divergent; existing methods rely heavily on specialized pattern-driven heuristic search or sampling algorithms, which can be difficult to generalize and hard to interpret based on phylogenetic principles. We propose a new method: Conditional Shadowing via Multi-resolution Evolutionary Trees, or CSMET, which uses a context-dependent probabilistic graphical model that allows aligned sites from different taxa in a multiple alignment to be modeled by either a background or an appropriate motif phylogeny conditioning on the functional specifications of each taxon. The functional specifications themselves are the output of a phylogeny which models the evolution not of individual nucleotides, but of the overall functionality (e.g., functional retention or loss) of the aligned sequence segments over lineages. Combining this method with a hidden Markov model that autocorrelates evolutionary rates on successive sites in the genome, CSMET offers a principled way to take into consideration lineage-specific evolution of TFBSs during motif detection, and a readily computable analytical form of the posterior distribution of motifs under TFBS turnover. On both simulated and real Drosophila cis-regulatory modules, CSMET outperforms other state-of-the-art comparative genomic motif finders.

SUBMITTER: Ray P

PROVIDER: S-EPMC2396503 | biostudies-literature | 2008 Jun

REPOSITORIES: biostudies-literature

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CSMET: comparative genomic motif detection via multi-resolution phylogenetic shadowing.

Ray Pradipta P Shringarpure Suyash S Kolar Mladen M Xing Eric P EP

PLoS computational biology 20080606 6

Functional turnover of transcription factor binding sites (TFBSs), such as whole-motif loss or gain, are common events during genome evolution. Conventional probabilistic phylogenetic shadowing methods model the evolution of genomes only at nucleotide level, and lack the ability to capture the evolutionary dynamics of functional turnover of aligned sequence entities. As a result, comparative genomic search of non-conserved motifs across evolutionarily related taxa remains a difficult challenge, ...[more]

PMID: 18535663

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Project description:Transmission of arthropod-borne apicomplexan parasites that cause disease and result in death or persistent infection represents a major challenge to global human and animal health. First described in 1901 as Piroplasma equi, this re-emergent apicomplexan parasite was renamed Babesia equi and subsequently Theileria equi, reflecting an uncertain taxonomy. Understanding mechanisms by which apicomplexan parasites evade immune or chemotherapeutic elimination is required for development of effective vaccines or chemotherapeutics. The continued risk of transmission of T. equi from clinically silent, persistently infected equids impedes the goal of returning the U. S. to non-endemic status. Therefore comparative genomic analysis of T. equi was undertaken to: 1) identify genes contributing to immune evasion and persistence in equid hosts, 2) identify genes involved in PBMC infection biology and 3) define the phylogenetic position of T. equi relative to sequenced apicomplexan parasites.The known immunodominant proteins, EMA1, 2 and 3 were discovered to belong to a ten member gene family with a mean amino acid identity, in pairwise comparisons, of 39%. Importantly, the amino acid diversity of EMAs is distributed throughout the length of the proteins. Eight of the EMA genes were simultaneously transcribed. As the agents that cause bovine theileriosis infect and transform host cell PBMCs, we confirmed that T. equi infects equine PBMCs, however, there is no evidence of host cell transformation. Indeed, a number of genes identified as potential manipulators of the host cell phenotype are absent from the T. equi genome. Comparative genomic analysis of T. equi revealed the phylogenetic positioning relative to seven apicomplexan parasites using deduced amino acid sequences from 150 genes placed it as a sister taxon to Theileria spp.The EMA family does not fit the paradigm for classical antigenic variation, and we propose a novel model describing the role of the EMA family in persistence. T. equi has lost the putative genes for host cell transformation, or the genes were acquired by T. parva and T. annulata after divergence from T. equi. Our analysis identified 50 genes that will be useful for definitive phylogenetic classification of T. equi and closely related organisms.

Project description:IntroductionGenomic aberrations in the form of subchromosomal DNA copy number changes are a hallmark of epithelial cancers, including breast cancer. The goal of the present study was to analyze such aberrations in breast cancer at high resolution.MethodsWe employed high-resolution array comparative genomic hybridization with 4,134 bacterial artificial chromosomes that cover the genome at 0.9 megabase resolution to analyze 47 primary breast tumors and 18 breast cancer cell lines.ResultsCommon amplicons included 8q24.3 (amplified in 79% of tumors, with 5/47 exhibiting high level amplification), 1q32.1 and 16p13.3 (amplified in 66% and 57% of tumors, respectively). Moreover, we found several positive correlations between specific amplicons from different chromosomes, suggesting the existence of cooperating genetic loci. Queried by gene, the most frequently amplified kinase was PTK2 (79% of tumors), whereas the most frequently lost kinase was PTK2B (hemizygous loss in 34% of tumors). Amplification of ERBB2 as measured by comparative genomic hybridization (CGH) correlated closely with ERBB2 DNA and RNA levels measured by quantitative PCR as well as with ERBB2 protein levels. The overall frequency of recurrent losses was lower, with no region lost in more than 50% of tumors; the most frequently lost tumor suppressor gene was RB1 (hemizygous loss in 26% of tumors). Finally, we find that specific copy number changes in cell lines closely mimicked those in primary tumors, with an overall Pearson correlation coefficient of 0.843 for gains and 0.734 for losses.ConclusionHigh resolution CGH analysis of breast cancer reveals several regions where DNA copy number is commonly gained or lost, that non-random correlations between specific amplicons exist, and that specific genetic alterations are maintained in breast cancer cell lines despite repeat passage in tissue culture. These observations suggest that genes within these regions are critical to the malignant phenotype and may thus serve as future therapeutic targets.

Dataset Information

CSMET: comparative genomic motif detection via multi-resolution phylogenetic shadowing.

Publications

CSMET: comparative genomic motif detection via multi-resolution phylogenetic shadowing.

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