An orthologous gene coevolution network provides insight into eukaryotic cellular and genomic structure and function

Steenwyk, Jacob L.; Phillips, Megan; Yang, Feng; Date, Swapneeta; Graham, Todd R.; Berman, Judith; Hittinger, Chris Todd; Rokas, Antonis

doi:10.1101/2021.07.09.451830

Cited by 3 publications

(3 citation statements)

References 77 publications

(180 reference statements)

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“…(1) Xenarthra (eutherian mammals from the Americas) and Afrotheria (eutherian mammals from Africa) are sister to all other Eutheria [33,34]; (2) Afrotheria are sister to all other Eutheria [35,36]; and (3) Xenarthra are sister to a clade of both Afrotheria and Eutheria (Fig 4A). Resolution of this conflict has important implications for understanding the historical biogeography of these organisms.…”

Section: Sc-ogs and Snap-ogs Have Similar Patterns Of Support In A Co...mentioning

confidence: 99%

“…Molecular evolution studies, such as species tree inference, genome-wide surveys of positive selection, evolutionary rate estimation, measures of gene-gene coevolution, and others typically rely on single-copy orthologs (SC-OGs), a group of homologous genes that originated via speciation and are present in single-copy among species of interest (Rokas et al, 2003;Jeffares et al, 2015;Li et al, 2017;Wu et al, 2017;Dong et al, 2019;Steenwyk et al, 2021c). In contrast, paralogs, homologous genes that originated via duplication and are often members of large gene families, are typically absent from these studies (Fig 1).…”

Section: Introductionmentioning

confidence: 99%

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OrthoSNAP: a tree splitting and pruning algorithm for retrieving single-copy orthologs from gene family trees

Steenwyk

Goltz²,

Buida³

et al. 2021

Preprint

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Molecular evolution studies, such as phylogenomic studies and genome-wide surveys of positive selection, often rely on gene families of single-copy orthologs (SC-OGs). In contrast, large gene families with multiple homologs in one or more species—a phenomenon observed among several important families of genes such as transporters and transcription factors—are often ignored because identifying and retrieving SC-OGs nested within them is challenging. To address this issue and increase the number of markers used in molecular evolution studies, we developed orthoSNAP, a software that uses a phylogenetic framework to simultaneously split gene families into SC-OGs and prune species-specific inparalogs. We term SC-OGs identified by orthoSNAP as SNAP-OGs because they are identified using a splitting and pruning procedure. From 46,645 orthologous groups of genes inferred using graph-based clustering of sequence similarity scores across four separate eukaryotic datasets, we identified 6,634 SC-OGs; using orthoSNAP on the remaining 40,011 orthologous groups of genes, we identified an additional 6,630 SNAP-OGs. Comparison of SNAP-OGs and SC-OGs revealed that their phylogenetic information content was similar. orthoSNAP is useful for increasing the number of markers used in molecular evolution data matrices, a critical step for robustly inferring and exploring the tree of life.

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Section: Sc-ogs and Snap-ogs Have Similar Patterns Of Support In A Co...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

OrthoSNAP: a tree splitting and pruning algorithm for retrieving single-copy orthologs from gene family trees

Steenwyk

Goltz²,

Buida³

et al. 2021

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

“…Molecular evolution studies, such as species tree inference, genome-wide surveys of selection, evolutionary rate estimation, measures of gene-gene coevolution, and others typically rely on single-copy orthologs (SC-OGs), a group of homologous genes that originated via speciation and are present in single copy among species of interest [1][2][3][4][5][6]. In contrast, paralogs-homologous genes that originated via duplication and are often members of large gene families-are typically absent from these studies (Fig 1).…”

Section: Introductionmentioning

confidence: 99%

OrthoSNAP: A tree splitting and pruning algorithm for retrieving single-copy orthologs from gene family trees

Steenwyk

Goltz²,

Buida³

et al. 2022

PLoS Biol

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Molecular evolution studies, such as phylogenomic studies and genome-wide surveys of selection, often rely on gene families of single-copy orthologs (SC-OGs). Large gene families with multiple homologs in 1 or more species—a phenomenon observed among several important families of genes such as transporters and transcription factors—are often ignored because identifying and retrieving SC-OGs nested within them is challenging. To address this issue and increase the number of markers used in molecular evolution studies, we developed OrthoSNAP, a software that uses a phylogenetic framework to simultaneously split gene families into SC-OGs and prune species-specific inparalogs. We term SC-OGs identified by OrthoSNAP as SNAP-OGs because they are identified using a splitting and pruning procedure analogous to snapping branches on a tree. From 415,129 orthologous groups of genes inferred across 7 eukaryotic phylogenomic datasets, we identified 9,821 SC-OGs; using OrthoSNAP on the remaining 405,308 orthologous groups of genes, we identified an additional 10,704 SNAP-OGs. Comparison of SNAP-OGs and SC-OGs revealed that their phylogenetic information content was similar, even in complex datasets that contain a whole-genome duplication, complex patterns of duplication and loss, transcriptome data where each gene typically has multiple transcripts, and contentious branches in the tree of life. OrthoSNAP is useful for increasing the number of markers used in molecular evolution data matrices, a critical step for robustly inferring and exploring the tree of life.

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Phylogenomic prediction of interaction networks in the presence of gene duplication

Forsythe,

Gatts,

Lane

et al. 2024

Preprint

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Assigning gene function from genome sequences is a rate-limiting step in molecular biology research. A protein’s position within an interaction network can potentially provide insights into its molecular mechanisms. Phylogenetic analyses of evolutionary rate covariation (ERC) have been shown to be effective for large-scale prediction of functional interactions from protein sequence data. However, gene duplication, gene loss, and other sources of phylogenetic incongruence are barriers for analyzing ERC on a genome-wide basis. Here, we developedERCnet, a bioinformatic program designed to overcome these challenges, facilitating efficient all-vs-all ERC analyses for large protein sequence datasets. We compiled a sample set of 35 angiosperm genomes to test the performance ofERCnet,including its sensitivity to user-defined analysis parameters such as input dataset size, branch-length measurement strategy, and significance threshold for defining ERC hits. We find that our novel ‘branch-by-branch’ length measurements outperforms ‘root-to-tip’ approaches in most cases, offering a valuable new strategy for performing ERC even in the presence of extensive gene duplication. Further, we demonstrate that the number of genomes and the species composition both have profound effects on the genes that are predicted to interact. Our systematic exploration of the performance ofERCnetprovides a roadmap for design of future ERC analyses to predict functional interactions in a wide array of genomic datasets.ERCnetcode is freely available athttps://github.com/EvanForsythe/ERCnet.

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An orthologous gene coevolution network provides insight into eukaryotic cellular and genomic structure and function

Cited by 3 publications

References 77 publications

OrthoSNAP: a tree splitting and pruning algorithm for retrieving single-copy orthologs from gene family trees

OrthoSNAP: a tree splitting and pruning algorithm for retrieving single-copy orthologs from gene family trees

OrthoSNAP: A tree splitting and pruning algorithm for retrieving single-copy orthologs from gene family trees

Phylogenomic prediction of interaction networks in the presence of gene duplication

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