Dataset Information

A computational pipeline to discover highly phylogenetically informative genes in sequenced genomes: application to Saccharomyces cerevisiae natural strains.

ABSTRACT: The quest for genes representing genetic relationships of strains or individuals within populations and their evolutionary history is acquiring a novel dimension of complexity with the advancement of next-generation sequencing (NGS) technologies. In fact, sequencing an entire genome uncovers genetic variation in coding and non-coding regions and offers the possibility of studying Saccharomyces cerevisiae populations at the strain level. Nevertheless, the disadvantageous cost-benefit ratio (the amount of details disclosed by NGS against the time-expensive and expertise-demanding data assembly process) still precludes the application of these techniques to the routinely assignment of yeast strains, making the selection of the most reliable molecular markers greatly desirable. In this work we propose an original computational approach to discover genes that can be used as a descriptor of the population structure. We found 13 genes whose variability can be used to recapitulate the phylogeny obtained from genome-wide sequences. The same approach that we prove to be successful in yeasts can be generalized to any other population of individuals given the availability of high-quality genomic sequences and of a clear population structure to be targeted.

SUBMITTER: Ramazzotti M

PROVIDER: S-EPMC3351171 | biostudies-literature | 2012 May

REPOSITORIES: biostudies-literature

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A computational pipeline to discover highly phylogenetically informative genes in sequenced genomes: application to Saccharomyces cerevisiae natural strains.

Ramazzotti Matteo M Berná Luisa L Stefanini Irene I Cavalieri Duccio D

Nucleic acids research 20120120 9

The quest for genes representing genetic relationships of strains or individuals within populations and their evolutionary history is acquiring a novel dimension of complexity with the advancement of next-generation sequencing (NGS) technologies. In fact, sequencing an entire genome uncovers genetic variation in coding and non-coding regions and offers the possibility of studying Saccharomyces cerevisiae populations at the strain level. Nevertheless, the disadvantageous cost-benefit ratio (the a ...[more]

PMID: 22266652

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Project description:BackgroundMobile Genetic Elements (MGEs) are selfish DNA integrated in the genomes. Their detection is mainly based on consensus-like searches by scanning the investigated genome against the sequence of an already identified MGE. Mobilomics aims at discovering all the MGEs in a genome and understanding their dynamic behavior: The data for this kind of investigation can be provided by comparative genomics of closely related organisms. The amount of data thus involved requires a strong computational effort, which should be alleviated.ResultsOur approach proposes to exploit the high similarity among homologous chromosomes of different strains of the same species, following a progressive comparative genomics philosophy. We introduce a software tool based on our new fast algorithm, called regender, which is able to identify the conserved regions between chromosomes. Our case study is represented by a unique recently available dataset of 39 different strains of S.cerevisiae, which regender is able to compare in few minutes. By exploring the non-conserved regions, where MGEs are mainly retrotransposons called Tys, and marking the candidate Tys based on their length, we are able to locate a priori and automatically all the already known Tys and map all the putative Tys in all the strains. The remaining putative mobile elements (PMEs) emerging from this intra-specific comparison are sharp markers of inter-specific evolution: indeed, many events of non-conservation among different yeast strains correspond to PMEs. A clustering based on the presence/absence of the candidate Tys in the strains suggests an evolutionary interconnection that is very similar to classic phylogenetic trees based on SNPs analysis, even though it is computed without using phylogenetic information.ConclusionsThe case study indicates that the proposed methodology brings two major advantages: (a) it does not require any template sequence for the wanted MGEs and (b) it can be applied to infer MGEs also for low coverage genomes with unresolved bases, where traditional approaches are largely ineffective.

Project description:DNA replication initiates from multiple replication origins (ORIs) in eukaryotes. Discovery and characterization of replication origins are essential for a better understanding of the molecular mechanism of DNA replication. In this study, the features of autonomously replicating sequences (ARSs) in Saccharomyces cerevisiae have been comprehensively analyzed as follows. Firstly, we carried out the analysis of the ARSs available in S. cerevisiae S288C. By evaluating the sequence similarity of experimentally established ARSs, we found that 94.32% of ARSs are unique across the whole genome of S. cerevisiae S288C and those with high sequence similarity are prone to locate in subtelomeres. Subsequently, we built a non-redundant dataset with a total of 520 ARSs, which are based on ARSs annotation of S. cerevisiae S288C from SGD and then supplemented with those from OriDB and DeOri databases. We conducted a large-scale comparison of ORIs among the diverse budding yeast strains from a population genomics perspective. We found that 82.7% of ARSs are not only conserved in genomic sequence but also relatively conserved in chromosomal position. The non-conserved ARSs tend to distribute in the subtelomeric regions. We also conducted a pan-genome analysis of ARSs among the S. cerevisiae strains, and a total of 183 core ARSs existing in all yeast strains were determined. We extracted the genes adjacent to replication origins among the 104 yeast strains to examine whether there are differences in their gene functions. The result showed that the genes involved in the initiation of DNA replication, such as orc3, mcm2, mcm4, mcm6, and cdc45, are conservatively located adjacent to the replication origins. Furthermore, we found the genes adjacent to conserved ARSs are significantly enriched in DNA binding, enzyme activity, transportation, and energy, whereas for the genes adjacent to non-conserved ARSs are significantly enriched in response to environmental stress, metabolites biosynthetic process and biosynthesis of antibiotics. In general, we characterized the replication origins from the genome-wide and population genomics perspectives, which would provide new insights into the replication mechanism of S. cerevisiae and facilitate the design of algorithms to identify genome-wide replication origins in yeast.

Dataset Information

A computational pipeline to discover highly phylogenetically informative genes in sequenced genomes: application to Saccharomyces cerevisiae natural strains.

Publications

A computational pipeline to discover highly phylogenetically informative genes in sequenced genomes: application to Saccharomyces cerevisiae natural strains.

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