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Eukaryotic diversity is largely microbial, with macroscopic lineages (plant, animals and fungi) nesting among a plethora of diverse protists. Understanding the evolutionary relationships among eukaryotes is rapidly advancing through omics analyses, but phylogenomics are challenging for microeukaryotes, particularly uncultivable lineages, as single-cell sequencing approaches generate a mixture of sequences from hosts, associated microbiomes, and contaminants. Moreover, many analyses of eukaryotic gene families and phylogenies rely on boutique datasets and methods that are challenging for other research groups to replicate. To address these challenges, we present EukPhylo v1.0, a modular, user-friendly pipeline that enables effective data curation through phylogeny-informed contamination removal, estimation of homologous gene families (GFs), and generation of both multisequence alignments and gene trees. Analyses can use a hook database of ~15k ancient GFs or users can easily replace this hook with a set of gene families of interest. We demonstrate the power of EukPhylo, including a suite of stand-alone utilities, through analyses of 500 conserved GFs sampled from 1,000 diverse species of eukaryotes, bacteria and archaea. We show improvements in estimates of the eukaryotic tree of life, recovering clades that are well established in the literature, through successive rounds of curation using the EukPhylo contamination loop. The final trees corroborate numerous hypotheses in the literature (e.g. Opisthokonta, Rhizaria, Amoebozoa) while challenging others (e.g. CRuMs, Obazoa, Diaphoretickes). We believe that the flexibility and transparency of EukPhylo sets standards for curation of omics data for future studies.
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Ten Quick Tips for Accurate Reconstruction of Prokaryotic and Eukaryotic Genome-Scale Metabolic Models
Constraint-based metabolic modeling approaches have enhanced our knowledge and understanding of the metabolism of prokaryotes and eukaryotes. This approach highly depends on the reconstruction process of genome-scale metabolic models (Mmodels). M-models can guide effective experimental design and yield new insights into the function and control of biological systems. Despite the recent advances in the automated generation of draft metabolic network reconstructions, the manual curation of these networks remains a labor-intensive and challenging task. Thus, these ten quick tips for the manual curation process are essential for optimizing high-quality metabolic model generation in less time. This collection of tips describes in great detail the resources and methods to ensure successful reconstruction. Furthermore, it increases the scope of other protocols of metabolic modeling by including resources to reconstruct eukaryotic organisms. Thus, all tips are applicable to a wide range of eukaryotic organisms. We believe this manuscript will interest a broad audience and researchers from different disciplines, spanning from microbiology and systems biology to biotechnology.
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- Award ID(s):
- 2313313
- PAR ID:
- 10533354
- Editor(s):
- BiologyandLifeSciences, Other
- Publisher / Repository:
- Preprints.org
- Date Published:
- Edition / Version:
- 1
- Volume:
- 1
- Issue:
- 1
- Page Range / eLocation ID:
- 1-20
- Subject(s) / Keyword(s):
- Genome-scale metabolic model reconstruction manual curation quick tips systems biology
- Format(s):
- Medium: X Size: 2MB Other: xls
- Size(s):
- 2MB
- Institution:
- San Diego State University
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Posted Content:
- https://doi.org/10.20944/preprints202311.0461.v1
