Dataset Information

IONS: Identification of Orthologs by Neighborhood and Similarity-an Automated Method to Identify Orthologs in Chromosomal Regions of Common Evolutionary Ancestry and its Application to Hemiascomycetous Yeasts.

ABSTRACT: Comparative sequence analysis is widely used to infer gene function and study genome evolution and requires proper ortholog identification across different genomes. We have developed a program for the Identification of Orthologs in one-to-one relationship by Neighborhood and Similarity (IONS) between closely related species. The algorithm combines two levels of evidence to determine co-ancestrality at the genome scale: sequence similarity and shared neighborhood. The method was initially designed to provide anchor points for syntenic blocks within the Génolevures project concerning nine hemiascomycetous yeasts (about 50,000 genes) and is applicable to different input databases. Comparison based on use of a Rand index shows that the results are highly consistent with the pillars of the Yeast Gene Order Browser, a manually curated database. Compared with SYNERGY, another algorithm reporting homology relationships, our method's main advantages are its automation and the absence of dataset-dependent parameters, facilitating consistent integration of newly released genomes.

SUBMITTER: Seret ML

PROVIDER: S-EPMC3169350 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

IONS: Identification of Orthologs by Neighborhood and Similarity-an Automated Method to Identify Orthologs in Chromosomal Regions of Common Evolutionary Ancestry and its Application to Hemiascomycetous Yeasts.

Seret Marie-Line ML Baret Philippe V PV

Evolutionary bioinformatics online 20110830

Comparative sequence analysis is widely used to infer gene function and study genome evolution and requires proper ortholog identification across different genomes. We have developed a program for the Identification of Orthologs in one-to-one relationship by Neighborhood and Similarity (IONS) between closely related species. The algorithm combines two levels of evidence to determine co-ancestrality at the genome scale: sequence similarity and shared neighborhood. The method was initially designe ...[more]

PMID: 21918595

Similar Datasets

Project description:We identified putative long terminal repeat- (LTR) retrotransposon sequences among the 50,000 random sequence tags (RSTs) obtained by the Génolevures project from genomic libraries of 13 Hemiascomycetes species. In most cases additional sequencing enabled us to assemble the whole sequences of these retrotransposons. These approaches identified 17 distinct families, 10 of which are defined by full-length elements. We also identified five families of solo LTRs that were not associated with retrotransposons. Ty1-like retrotransposons were found in four of five species that are phylogenetically related to Saccharomyces cerevisiae (S. uvarum, S. exiguus, S. servazzii, and S. kluyveri but not Zygosaccharomyces rouxii), and in two of three Kluyveromyces species (K. lactis and K. marxianus but not K. thermotolerans). Only multiply crippled elements could be identified in the K. lactis and S. servazzii strains analyzed, and only solo LTRs could be identified in S. uvarum. Ty4-like elements were only detected in S. uvarum, indicating that these elements appeared recently before speciation of the Saccharomyces sensu stricto species. Ty5-like elements were detected in S. exiguus, Pichia angusta, and Debaryomyces hansenii. A retrotransposon homologous with Tca2 from Candida albicans, an element absent from S. cerevisiae, was detected in the closely related species D. hansenii. A complete Ty3/gypsy element was present in S. exiguus, whereas only partial, often degenerate, sequences resembling this element were found in S. servazzii, Z. rouxii, S. kluyveri, C. tropicalis, and Yarrowica lipolytica. P. farinosa (syn. P. sorbitophila) is currently the only yeast species in which no LTR retrotransposons or remnants have been found. Thorough analysis of protein sequences, structural characteristics of the elements, and phylogenetic relationships deduced from these data allowed us to propose a classification for the Ty1/copia elements of hemiascomycetous yeasts and a model of LTR-retrotransposon evolution in yeasts.

Project description:We address the problem of homology identification in complex multidomain families with varied domain architectures. The challenge is to distinguish sequence pairs that share common ancestry from pairs that share an inserted domain but are otherwise unrelated. This distinction is essential for accuracy in gene annotation, function prediction, and comparative genomics. There are two major obstacles to multidomain homology identification: lack of a formal definition and lack of curated benchmarks for evaluating the performance of new methods. We offer preliminary solutions to both problems: 1) an extension of the traditional model of homology to include domain insertions; and 2) a manually curated benchmark of well-studied families in mouse and human. We further present Neighborhood Correlation, a novel method that exploits the local structure of the sequence similarity network to identify homologs with great accuracy based on the observation that gene duplication and domain shuffling leave distinct patterns in the sequence similarity network. In a rigorous, empirical comparison using our curated data, Neighborhood Correlation outperforms sequence similarity, alignment length, and domain architecture comparison. Neighborhood Correlation is well suited for automated, genome-scale analyses. It is easy to compute, does not require explicit knowledge of domain architecture, and classifies both single and multidomain homologs with high accuracy. Homolog predictions obtained with our method, as well as our manually curated benchmark and a web-based visualization tool for exploratory analysis of the network neighborhood structure, are available at http://www.neighborhoodcorrelation.org. Our work represents a departure from the prevailing view that the concept of homology cannot be applied to genes that have undergone domain shuffling. In contrast to current approaches that either focus on the homology of individual domains or consider only families with identical domain architectures, we show that homology can be rationally defined for multidomain families with diverse architectures by considering the genomic context of the genes that encode them. Our study demonstrates the utility of mining network structure for evolutionary information, suggesting this is a fertile approach for investigating evolutionary processes in the post-genomic era.

Project description:Geologically, Panama belongs to the Central American land-bridge between North and South America crossed by Homo sapiens >14 ka ago. Archaeologically, it belongs to a wider Isthmo-Colombian Area. Today, seven indigenous ethnic groups account for 12.3% of Panama's population. Five speak Chibchan languages and are characterized by low genetic diversity and a high level of differentiation. In addition, no evidence of differential structuring between maternally and paternally inherited genes has been reported in isthmian Chibchan cultural groups. Recent data have shown that 83% of the Panamanian general population harbour mitochondrial DNAs (mtDNAs) of Native American ancestry. Considering differential male/female mortality at European contact and multiple degrees of geographical and genetic isolation over the subsequent five centuries, the Y-chromosome Native American component is expected to vary across different geographic regions and communities in Panama. To address this issue, we investigated Y-chromosome variation in 408 modern males from the nine provinces of Panama and one indigenous territory (the comarca of Kuna Yala). In contrast to mtDNA data, the Y-chromosome Native American component (haplogroup Q) exceeds 50% only in three populations facing the Caribbean Sea: the comarca of Kuna Yala and Bocas del Toro province where Chibchan languages are spoken by the majority, and the province of Colón where many Kuna and people of mixed indigenous-African-and-European descent live. Elsewhere the Old World component is dominant and mostly represented by western Eurasian haplogroups, which signal the strong male genetic impact of invaders. Sub-Saharan African input accounts for 5.9% of male haplotypes. This reflects the consequences of the colonial Atlantic slave trade and more recent influxes of West Indians of African heritage. Overall, our findings reveal a local evolution of the male Native American ancestral gene pool, and a strong but geographically differentiated unidirectional sex bias in the formation of local modern Panamanian populations.

Dataset Information

IONS: Identification of Orthologs by Neighborhood and Similarity-an Automated Method to Identify Orthologs in Chromosomal Regions of Common Evolutionary Ancestry and its Application to Hemiascomycetous Yeasts.

Publications

IONS: Identification of Orthologs by Neighborhood and Similarity-an Automated Method to Identify Orthologs in Chromosomal Regions of Common Evolutionary Ancestry and its Application to Hemiascomycetous Yeasts.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets