Dataset Information

Quantitative frame analysis and the annotation of GC-rich (and other) prokaryotic genomes. An application to Anaeromyxobacter dehalogenans.

ABSTRACT: Graphical representations of contrasts in GC usage among codon frame positions (frame analysis) provide evidence of genes missing from the annotations of prokaryotic genomes of high GC content but the qualitative approach of visual frame analysis prevents its applicability on a genomic scale.We developed two quantitative methods for the identification and statistical characterization in sequence regions of three-base periodicity (hits) associated with open reading frame structures. The methods were implemented in the N-Profile Analysis Computational Tool (NPACT), which highlights in graphical representations inconsistencies between newly identified ORFs and pre-existing annotations of coding-regions. We applied the NPACT procedures to two recently annotated strains of the deltaproteobacterium Anaeromyxobacter dehalogenans, identifying in both genomes numerous conserved ORFs not included in the published annotation of coding regions.NPACT is available as a web-based service and for download at http://genome.ufl.edu/npact.lucianob@ufl.eduSupplementary data are available at Bioinformatics online.

SUBMITTER: Oden S

PROVIDER: S-EPMC4595893 | biostudies-literature | 2015 Oct

REPOSITORIES: biostudies-literature

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Quantitative frame analysis and the annotation of GC-rich (and other) prokaryotic genomes. An application to Anaeromyxobacter dehalogenans.

Oden Steve S Brocchieri Luciano L

Bioinformatics (Oxford, England) 20150604 20

<h4>Motivation</h4>Graphical representations of contrasts in GC usage among codon frame positions (frame analysis) provide evidence of genes missing from the annotations of prokaryotic genomes of high GC content but the qualitative approach of visual frame analysis prevents its applicability on a genomic scale.<h4>Results</h4>We developed two quantitative methods for the identification and statistical characterization in sequence regions of three-base periodicity (hits) associated with open read ...[more]

PMID: 26048600

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Project description:BackgroundAccurate annotation of translation initiation sites (TISs) is essential for understanding the translation initiation mechanism. However, the reliability of TIS annotation in widely used databases such as RefSeq is uncertain due to the lack of experimental benchmarks.ResultsBased on a homogeneity assumption that gene translation-related signals are uniformly distributed across a genome, we have established a computational method for a large-scale quantitative assessment of the reliability of TIS annotations for any prokaryotic genome. The method consists of modeling a positional weight matrix (PWM) of aligned sequences around predicted TISs in terms of a linear combination of three elementary PWMs, one for true TIS and the two others for false TISs. The three elementary PWMs are obtained using a reference set with highly reliable TIS predictions. A generalized least square estimator determines the weighting of the true TIS in the observed PWM, from which the accuracy of the prediction is derived. The validity of the method and the extent of the limitation of the assumptions are explicitly addressed by testing on experimentally verified TISs with variable accuracy of the reference sets. The method is applied to estimate the accuracy of TIS annotations that are provided on public databases such as RefSeq and ProTISA and by programs such as EasyGene, GeneMarkS, Glimmer 3 and TiCo. It is shown that RefSeq's TIS prediction is significantly less accurate than two recent predictors, Tico and ProTISA. With convincing proofs, we show two general preferential biases in the RefSeq annotation, i.e. over-annotating the longest open reading frame (LORF) and under-annotating ATG start codon. Finally, we have established a new TIS database, SupTISA, based on the best prediction of all the predictors; SupTISA has achieved an average accuracy of 92% over all 532 complete genomes.ConclusionLarge-scale computational evaluation of TIS annotation has been achieved. A new TIS database much better than RefSeq has been constructed, and it provides a valuable resource for further TIS studies.

Project description:The versatile soil bacterium Anaeromyxobacter dehalogenans lacks the hallmark denitrification genes nirS and nirK (encoding NO2-→NO reductases) and couples growth to NO3- reduction to NH4+ (respiratory ammonification) and to N2O reduction to N2A. dehalogenans also grows by reducing Fe(III) to Fe(II), which chemically reacts with NO2- to form N2O (i.e., chemodenitrification). Following the addition of 100 μmol of NO3- or NO2- to Fe(III)-grown axenic cultures of A. dehalogenans, 54 (±7) μmol and 113 (±2) μmol N2O-N, respectively, were produced and subsequently consumed. The conversion of NO3- to N2 in the presence of Fe(II) through linked biotic-abiotic reactions represents an unrecognized ecophysiology of A. dehalogenans The new findings demonstrate that the assessment of gene content alone is insufficient to predict microbial denitrification potential and N loss (i.e., the formation of gaseous N products). A survey of complete bacterial genomes in the NCBI Reference Sequence database coupled with available physiological information revealed that organisms lacking nirS or nirK but with Fe(III) reduction potential and genes for NO3- and N2O reduction are not rare, indicating that NO3- reduction to N2 through linked biotic-abiotic reactions is not limited to A. dehalogenans Considering the ubiquity of iron in soils and sediments and the broad distribution of dissimilatory Fe(III) and NO3- reducers, denitrification independent of NO-forming NO2- reductases (through combined biotic-abiotic reactions) may have substantial contributions to N loss and N2O flux.IMPORTANCE Current attempts to gauge N loss from soils rely on the quantitative measurement of nirK and nirS genes and/or transcripts. In the presence of iron, the common soil bacterium Anaeromyxobacter dehalogenans is capable of denitrification and the production of N2 without the key denitrification genes nirK and nirS Such chemodenitrifiers denitrify through combined biotic and abiotic reactions and have potentially large contributions to N loss to the atmosphere and fill a heretofore unrecognized ecological niche in soil ecosystems. The findings emphasize that the comprehensive understanding of N flux and the accurate assessment of denitrification potential can be achieved only when integrated studies of interlinked biogeochemical cycles are performed.

Dataset Information

Quantitative frame analysis and the annotation of GC-rich (and other) prokaryotic genomes. An application to Anaeromyxobacter dehalogenans.

Publications

Quantitative frame analysis and the annotation of GC-rich (and other) prokaryotic genomes. An application to Anaeromyxobacter dehalogenans.

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