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Amino acid based de Bruijn graph algorithm for identifying complete coding genes from metagenomic and
Jiemeng Liu1,2, Qichao Lian1, Yamao Chen1
1State key Laboratory of Genetic Engineering, Institute of Plant Biology, School of Life Sciences, Fudan University, Shanghai 200433, China.
Nucleic Acids Research
|January 19, 2019
Summary
This study introduces MetaPA, a novel bioinformatic tool for assembling proteins from metagenomic and metatranscriptomic data. MetaPA effectively reconstructs microbial protein sequences, aiding in the characterization of microbial communities.
Area of Science:
- Microbiology
- Bioinformatics
- Genomics
Background:
- Next-generation sequencing (NGS) advances metagenomic studies, revealing microbial community structures.
- Assembling prokaryotic genomes ab initio is crucial for retrieving complete metabolic pathway genes due to limited microbial genome data.
- Handling large metagenomic datasets and complex microbial compositions poses challenges for bioinformatic tool development.
Purpose of the Study:
- To present MetaPA, an efficient protein assembler for metagenomic and metatranscriptomic data.
- To address the challenges in assembling microbial proteins from complex sequencing data.
- To improve the characterization of microbial communities and their functions.
Main Methods:
- Developed MetaPA, a protein assembler utilizing de Bruijn graph searching on oligopeptide spaces.
- Applied MetaPA to both metagenomic and metatranscriptomic sequencing data.
- Incorporated public homologous protein sequences to guide the assembly process.
Main Results:
- MetaPA achieved 85% assembly of total proteins with 83% precision on high-throughput sequencing datasets.
- Successfully identified the majority of actively transcribed genes in metatranscriptomic data.
- Demonstrated high performance in assembling complete protein sequences.
Conclusions:
- MetaPA shows significant potential for characterizing microbial composition and abundance in metagenomic studies.
- The tool is effective for analyzing actively transcribed genes in metatranscriptomic studies.
- MetaPA offers a robust solution for assembling microbial proteins from complex sequencing data.
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