Evidence map›Paper›PMID 26394049›Full record

ArticlePloS one2015

Co-Inheritance Analysis within the Domains of Life Substantially Improves Network Inference by Phylogenetic Profiling.

Junha Shin, Insuk Lee

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

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16citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

Who cites it

16 citing papers in PubMed.

  1. Article
  2. Article
  3. Identification of hidden associations among eukaryotic genes through statistical analysis of coevolutionary transitions.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
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  5. Article
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  9. Article
  10. A Genome-Scale Co-Functional Network ofMolecules and cells · 2019
    Article
  11. Article
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  13. Article
  14. Review
  15. Article
  16. Article
4 · The record

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5 · Who and what money

Authors and funding

2 authors.

Junha ShinDepartment of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, Korea.
Insuk LeeDepartment of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Phylogenetic profiling, a network inference method based on gene inheritance profiles, has been widely used to construct functional gene networks in microbes. However, its utility for network inference in higher eukaryotes has been limited. An improved algorithm with an in-depth understanding of pathway evolution may overcome this limitation. In this study, we investigated the effects of taxonomic structures on co-inheritance analysis using 2,144 reference species in four query species: Escherichia coli, Saccharomyces cerevisiae, Arabidopsis thaliana, and Homo sapiens. We observed three clusters of reference species based on a principal component analysis of the phylogenetic profiles, which correspond to the three domains of life-Archaea, Bacteria, and Eukaryota-suggesting that pathways inherit primarily within specific domains or lower-ranked taxonomic groups during speciation. Hence, the co-inheritance pattern within a taxonomic group may be eroded by confounding inheritance patterns from irrelevant taxonomic groups. We demonstrated that co-inheritance analysis within domains substantially improved network inference not only in microbe species but also in the higher eukaryotes, including humans. Although we observed two sub-domain clusters of reference species within Eukaryota, co-inheritance analysis within these sub-domain taxonomic groups only marginally improved network inference. Therefore, we conclude that co-inheritance analysis within domains is the optimal approach to network inference with the given reference species. The construction of a series of human gene networks with increasing sample sizes of the reference species for each domain revealed that the size of the high-accuracy networks increased as additional reference species genomes were included, suggesting that within-domain co-inheritance analysis will continue to expand human gene networks as genomes of additional species are sequenced. Taken together, we propose that co-inheritance analysis within the domains of life will greatly potentiate the use of the expected onslaught of sequenced genomes in the study of molecular pathways in higher eukaryotes.

Indexed as

Inheritance PatternsPhylogenyAmino Acid SequenceGenome, HumanHigh-Throughput Nucleotide SequencingHumansPrincipal Component AnalysisSpecies Specificity

Identifiers

PMID26394049
PMCPMC4578931

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.