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Accurate discrimination of conserved coding and non-coding regions through multiple indicators of evolutionary dynamics.

ABSTRACT: BACKGROUND: The conservation of sequences between related genomes has long been recognised as an indication of functional significance and recognition of sequence homology is one of the principal approaches used in the annotation of newly sequenced genomes. In the context of recent findings that the number non-coding transcripts in higher organisms is likely to be much higher than previously imagined, discrimination between conserved coding and non-coding sequences is a topic of considerable interest. Additionally, it should be considered desirable to discriminate between coding and non-coding conserved sequences without recourse to the use of sequence similarity searches of protein databases as such approaches exclude the identification of novel conserved proteins without characterized homologs and may be influenced by the presence in databases of sequences which are erroneously annotated as coding. RESULTS: Here we present a machine learning-based approach for the discrimination of conserved coding sequences. Our method calculates various statistics related to the evolutionary dynamics of two aligned sequences. These features are considered by a Support Vector Machine which designates the alignment coding or non-coding with an associated probability score. CONCLUSION: We show that our approach is both sensitive and accurate with respect to comparable methods and illustrate several situations in which it may be applied, including the identification of conserved coding regions in genome sequences and the discrimination of coding from non-coding cDNA sequences.

SUBMITTER: Re M

PROVIDER: S-EPMC2758873 | biostudies-other | 2009

REPOSITORIES: biostudies-other

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Accurate discrimination of conserved coding and non-coding regions through multiple indicators of evolutionary dynamics.

Rè Matteo M Pesole Graziano G Horner David S DS

BMC bioinformatics 20090908

<h4>Background</h4>The conservation of sequences between related genomes has long been recognised as an indication of functional significance and recognition of sequence homology is one of the principal approaches used in the annotation of newly sequenced genomes. In the context of recent findings that the number non-coding transcripts in higher organisms is likely to be much higher than previously imagined, discrimination between conserved coding and non-coding sequences is a topic of considera ...[more]

PMID: 19737408

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Project description:Background: Long non-coding RNAs (lncRNAs), which are generally less functionally characterized or less annotated, evolve more rapidly than mRNAs and substantially possess fewer sequence conservation patterns than protein-coding genes across divergent species. People assume that the functional inference could be conducted on the evolutionarily conserved long non-coding RNAs as they are most likely to be functional. In the past decades, substantial progress has been made in discussions on the evolutionary conservation of non-coding genomic regions from multiple perspectives. However, understanding their conservation and the functions associated with sequence conservation in relation to further corresponding phenotypic variability or disorders still remains incomplete. Results: Accordingly, we determined a highly conserved region (HCR) to verify the sequence conservation among long non-coding RNAs and systematically profiled homologous long non-coding RNA clusters in humans and mice based on the detection of highly conserved regions. Moreover, according to homolog clustering, we explored the potential function inference via highly conserved regions on representative long non-coding RNAs. On lncRNA XACT, we investigated the potential functional competence between XACT and lncRNA XIST by recruiting miRNA-29a, regulating the downstream target genes. In addition, on lncRNA LINC00461, we examined the interaction relationship between LINC00461 and SND1. This interaction or association may be perturbed during the progression of glioma. In addition, we have constructed a website with user-friendly web interfaces for searching, analyzing, and downloading to present the homologous clusters of humans and mice. Conclusion: Collectively, homolog clustering via the highly conserved region definition and detection on long non-coding RNAs, as well as the functional explorations on representative sequences in our research, would provide new evidence for the potential function of long non-coding RNAs. Our results on the remarkable roles of long non-coding RNAs would presumably provide a new theoretical basis and candidate diagnostic indicators for tumors.

Project description:The objective of this paper is to examine associations between multiple measures of discrimination (i.e., everyday, lifetime, and appraised burden) and components of allostatic load (AL). We drew on pooled cross-sectional data from the Biomarker Project of the Midlife in the United States study (n = 2118). Ages ranged from 25 to 84 years and included mostly Black (n = 389) and white (n = 1598) adults. Quasi-Poisson models were fit to estimate prevalence ratios for each discrimination measure and high-risk quartiles across seven physiological systems (i.e., sympathetic and parasympathetic nervous system; HPA axis; inflammation; cardiovascular; metabolic glucose; and metabolic lipids) and overall AL scores. In fully adjusted models, everyday discrimination was associated with elevated lipids (aPR: 1.07; 95% CI 1.01, 1.13). Lifetime experiences of discrimination were associated with lower sympathetic nervous system (aPR: 0.82; 95% CI: 0.69, 0.98) and greater cardiovascular risk scores (aPR: 1.17; 95% CI: 1.02, 1.34) among those reporting three or more experiences, as well as increased inflammation (aPR: 1.13; 95% CI: 1.02, 1.25; aPR: 1.28; 95% CI: 1.14, 1.43), metabolic glucose (aPR: 1.35; 95% CI: 1.19, 1.54; aPR: 1.45; 95% CI: 1.24, 1.68), and metabolic lipids (aPR: 1.13; 95% CI: 1.03, 1.24; aPR: 1.28; 95% CI: 1.15, 1.43) scores for those reporting one to two and three or more experiences. Appraised burden yielded nuanced associations with metabolic glucose and parasympathetic nervous system scores. Everyday and lifetime measures were also associated with higher overall AL, though burden of discrimination was only associated with AL among those reporting "a little" burden. While AL summary scores provide insight into the cumulative impacts of discrimination on health, there appear to be distinct physiologic pathways through which varying forms of discrimination contribute to AL and, ultimately, to poorer health. These unique pathways may be useful in identifying potential points of intervention to mitigate the impacts of discrimination on health inequities.

Dataset Information

Accurate discrimination of conserved coding and non-coding regions through multiple indicators of evolutionary dynamics.

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Accurate discrimination of conserved coding and non-coding regions through multiple indicators of evolutionary dynamics.

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