Počet záznamů: 1
Improved recovery and annotation of genes in metagenomes through the prediction of fungal introns
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SYSNO ASEP 0577005 Druh ASEP J - Článek v odborném periodiku Zařazení RIV J - Článek v odborném periodiku Poddruh J Článek ve WOS Název Improved recovery and annotation of genes in metagenomes through the prediction of fungal introns Tvůrce(i) Le, A. V. (CZ)
Větrovský, Tomáš (MBU-M) ORCID, RID
Baručić, D. (CZ)
Saraiva, J. P. (DE)
Dobbler, Priscila Thiago (MBU-M) ORCID, RID
Kohout, Petr (MBU-M) ORCID, RID
Pospíšek, M. (CZ)
da Rocha, U. N. (DE)
Kléma, J. (CZ)
Baldrian, Petr (MBU-M) RID, ORCIDZdroj.dok. Molecular Ecology Resources - ISSN 1755-098X
Roč. 23, č. 8 (2023), s. 1800-1811Poč.str. 12 s. Jazyk dok. eng - angličtina Země vyd. GB - Velká Británie Klíč. slova artificial intelligence ; eukaryote ; fungi ; gene prediction ; intron ; metagenomics Obor OECD Microbiology CEP GA21-17749S GA ČR - Grantová agentura ČR Výzkumná infrastruktura e-INFRA CZ - 90140 - CESNET, zájmové sdružení právnických osob Způsob publikování Omezený přístup Institucionální podpora MBU-M - RVO:61388971 UT WOS 001045828600001 EID SCOPUS 85167618234 DOI 10.1111/1755-0998.13852 Anotace Metagenomics provides a tool to assess the functional potential of environmental and host-associated microbiomes based on the analysis of environmental DNA: assembly, gene prediction and annotation. While gene prediction is straightforward for most bacterial and archaeal taxa, it has limited applicability in the majority of eukaryotic organisms, including fungi that contain introns in gene coding sequences. As a consequence, eukaryotic genes are underrepresented in metagenomics datasets and our understanding of the contribution of fungi and other eukaryotes to microbiome functioning is limited. Here, we developed a machine intelligence-based algorithm that predicts fungal introns in environmental DNA with reasonable precision and used it to improve the annotation of environmental metagenomes. Intron removal increased the number of predicted genes by up to 9.1% and improved the annotation of several others. The proportion of newly predicted genes increased with the share of eukaryotic genes in the metagenome and-within fungal taxa-increased with the number of introns per gene. Our approach provides a tool named SVMmycointron for improved metagenome annotation, especially of microbiomes with a high proportion of eukaryotes. The scripts described in the paper are made publicly available and can be readily utilized by microbiome researchers analysing metagenomics data. Pracoviště Mikrobiologický ústav Kontakt Eliška Spurná, eliska.spurna@biomed.cas.cz, Tel.: 241 062 231 Rok sběru 2024 Elektronická adresa https://onlinelibrary.wiley.com/doi/10.1111/1755-0998.13852
Počet záznamů: 1