From Gene Annotation to Function Prediction for Metagenomics

Sharifi, Fatemeh; Ye, Yuzhen

doi:10.1007/978-1-4939-7015-5_3

Cited by 14 publications

(7 citation statements)

References 15 publications

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“…We also compared our pipeline to two recently published metagenome annotation tools, Fun4Me ( 38 ) and ShotMAP ( 39 ), using the above-described artificial metagenome. Note that Fun4Me includes its own reference database, which cannot be changed on demand.…”

Section: Resultsmentioning

confidence: 99%

Functional sequencing read annotation for high precision microbiome analysis

Zhu

Miller

Marpaka

et al. 2017

Nucleic Acids Research

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The vast majority of microorganisms on Earth reside in often-inseparable environment-specific communities—microbiomes. Meta-genomic/-transcriptomic sequencing could reveal the otherwise inaccessible functionality of microbiomes. However, existing analytical approaches focus on attributing sequencing reads to known genes/genomes, often failing to make maximal use of available data. We created faser (functional annotation of sequencing reads), an algorithm that is optimized to map reads to molecular functions encoded by the read-correspondent genes. The mi-faser microbiome analysis pipeline, combining faser with our manually curated reference database of protein functions, accurately annotates microbiome molecular functionality. mi-faser’s minutes-per-microbiome processing speed is significantly faster than that of other methods, allowing for large scale comparisons. Microbiome function vectors can be compared between different conditions to highlight environment-specific and/or time-dependent changes in functionality. Here, we identified previously unseen oil degradation-specific functions in BP oil-spill data, as well as functional signatures of individual-specific gut microbiome responses to a dietary intervention in children with Prader–Willi syndrome. Our method also revealed variability in Crohn's Disease patient microbiomes and clearly distinguished them from those of related healthy individuals. Our analysis highlighted the microbiome role in CD pathogenicity, demonstrating enrichment of patient microbiomes in functions that promote inflammation and that help bacteria survive it.

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Section: Resultsmentioning

confidence: 99%

Functional sequencing read annotation for high precision microbiome analysis

Zhu

Miller

Marpaka

et al. 2017

Nucleic Acids Research

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“…Simultaneously, several pipelines were set up that integrate some of these and other previously mentioned tools, to allow direct annotation from raw sequencing data or contigs. For example, FUN4ME [164] integrates three tools: FragGeneScan for gene calling, RAPSearch2 for homology research and the MinPath [165] tool to allow biological pathway reconstruction. Classical, previously mentioned software such as MOCAT2 [129], the web portal MG-RAST v.4 [70], or the IMG/M v.5.0 [69] annotation server, also allow the comparison of metagenomic sequence reads to a reference database of functionally annotated protein families and use homology inference to annotate them.…”

Section: Wgs Metagenomicsmentioning

confidence: 99%

Metagenomic approaches in microbial ecology: an update on whole-genome and marker gene sequencing analyses

2020

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Metagenomics and marker gene approaches, coupled with high-throughput sequencing technologies, have revolutionized the field of microbial ecology. Metagenomics is a culture-independent method that allows the identification and characterization of organisms from all kinds of samples. Whole-genome shotgun sequencing analyses the total DNA of a chosen sample to determine the presence of micro-organisms from all domains of life and their genomic content. Importantly, the whole-genome shotgun sequencing approach reveals the genomic diversity present, but can also give insights into the functional potential of the micro-organisms identified. The marker gene approach is based on the sequencing of a specific gene region. It allows one to describe the microbial composition based on the taxonomic groups present in the sample. It is frequently used to analyse the biodiversity of microbial ecosystems. Despite its importance, the analysis of metagenomic sequencing and marker gene data is quite a challenge. Here we review the primary workflows and software used for both approaches and discuss the current challenges in the field.

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“…Despite the difficulties noted above, the effort is highly worthwhile in terms of both understanding basic CRISPR/Cas biology and biotechnology applications. In particular, the detailed in silico analysis done here for Type I-E system in E. coli should be extended to diverse CRISPR/Cas systems in other bacterial systems, or even to metagenomic datasets, where tools well suited for such analysis have been developed [50]. Such computational studies should provide a rational starting point for further experiments, where stand-alone computational studies proved to be important for understanding CRISPR/Cas systems [8,12,51].…”

Section: Discussionmentioning

confidence: 99%

Endogenous Gene Regulation as a Predicted Main Function of Type I-E CRISPR/Cas System in E. coli

2019

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CRISPR/Cas is an adaptive bacterial immune system, whose CRISPR array can actively change in response to viral infections. However, Type I-E CRISPR/Cas in E. coli (an established model system), appears not to exhibit such active adaptation, which suggests that it might have functions other than immune response. Through computational analysis, we address the involvement of the system in non-canonical functions. To assess targets of CRISPR spacers, we align them against both E. coli genome and an exhaustive (~230) set of E. coli viruses. We systematically investigate the obtained alignments, such as hit distribution with respect to genome annotation, propensity to target mRNA, the target functional enrichment, conservation of CRISPR spacers and putative targets in related bacterial genomes. We find that CRISPR spacers have a statistically highly significant tendency to target i) host compared to phage genomes, ii) one of the two DNA strands, iii) genomic dsDNA rather than mRNA, iv) transcriptionally active regions, and v) sequences (cis-regulatory elements) with slower turn-over rate compared to CRISPR spacers (trans-factors). The results suggest that the Type I-E CRISPR/Cas system has a major role in transcription regulation of endogenous genes, with a potential to rapidly rewire these regulatory interactions, with targets being selected through naïve adaptation.

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From Gene Annotation to Function Prediction for Metagenomics

Cited by 14 publications

References 15 publications

Functional sequencing read annotation for high precision microbiome analysis

Functional sequencing read annotation for high precision microbiome analysis

Metagenomic approaches in microbial ecology: an update on whole-genome and marker gene sequencing analyses

Endogenous Gene Regulation as a Predicted Main Function of Type I-E CRISPR/Cas System in E. coli

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