OrthoHMM: Improved Inference of Ortholog Groups using Hidden Markov Models DOI Creative Commons
Jacob L. Steenwyk, Thomas J. Buida, Antonis Rokas

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 12, 2024

Abstract Accurate orthology inference is essential for comparative genomics and phylogenomics. However, challenged by sequence divergence, which pronounced among anciently diverged organisms. We present OrthoHMM, an algorithm that infers orthologous gene groups using Hidden Markov Models parameterized from substitution matrices, enables better detection of remote homologs. Benchmarking indicates OrthoHMM outperforms currently available methods; example, a curated set Bilaterian orthogroups, showed 10.3 – 138.9% improvement in precision. Rank-based benchmarking orthogroups novel dataset organisms three major eukaryotic kingdoms revealed had the best overall performance (6.7 97.8% improvement). These findings suggest improve orthogroup inference.

Language: Английский

Ctenophores and parahoxozoans independently evolved functionally diverse voltage-gated K+ channels DOI
Benjamin T. Simonson,

Zhaoyang Jiang,

Joseph F. Ryan

et al.

The Journal of General Physiology, Journal Year: 2025, Volume and Issue: 157(3)

Published: Feb. 27, 2025

The ctenophore species Mnemiopsis leidyi is known to have a large set of voltage-gated K+ channels, but little about the functional diversity these channels or their evolutionary history in other species. Here, we searched genomes two additional species, Beroe ovata and Hormiphora californensis, for functionally expressed subset M. channels. We found that last common ancestor three disparate lineages probably had at least 33 Two genes belong EAG family, remaining 31 Shaker family form single clade within animal/choanoflagellate phylogeny. additionally evidence 10 transcriptome early branching lineage Euplokamis dunlapae, suggesting diversification was already underway evolution. 16 Shakers they encode diverse array conductances with orthologs many classic subtypes cnidarians bilaterians. Analysis data show are wide variety cell types, including neurons, muscle, comb cells, colloblasts. Ctenophores therefore appear independently evolved much channel shared between

Language: Английский

Citations

1

Evolutionary plasticity and functional repurposing of the essential metabolic enzyme MoeA DOI Creative Commons
Daniela Megrian, Mariano Martínez, Pedro M. Alzari

et al.

Communications Biology, Journal Year: 2025, Volume and Issue: 8(1)

Published: Jan. 14, 2025

Abstract MoeA, also known as gephyrin in higher eukaryotes, is an enzyme essential for molybdenum cofactor (Moco) biosynthesis and involved GABA GlyR receptor clustering at the synapse animals. We recently discovered that Actinobacteria have a repurposed version of MoeA (Glp) linked to bacterial cell division. Since exists all domains life, our study explores how it gained multifunctionality over time. use phylogenetic inference protein structure analyses its diversity evolutionary history. Glp-expressing Bacteria least two copies gene, analysis their putative active sites suggests Glp lost enzymatic role. In Archaea, we find ancestral duplication, with one paralog may bind tungsten instead molybdenum. Early eukaryotes acquired from Bacteria, MogA fused opisthokont ancestors, finally roles anchoring inhibitory neurotransmitters. Our findings highlight MoeA’s functional versatility repurposing.

Language: Английский

Citations

0

Morphogenesis of Fractofusus andersoni and the nature of early animal development DOI Creative Commons
Frances S. Dunn, Philip C. J. Donoghue, Alexander Liu

et al.

Nature Communications, Journal Year: 2025, Volume and Issue: 16(1)

Published: April 11, 2025

Language: Английский

Citations

0

OrthoHMM: Improved Inference of Ortholog Groups using Hidden Markov Models DOI Creative Commons
Jacob L. Steenwyk, Thomas J. Buida, Antonis Rokas

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 12, 2024

Abstract Accurate orthology inference is essential for comparative genomics and phylogenomics. However, challenged by sequence divergence, which pronounced among anciently diverged organisms. We present OrthoHMM, an algorithm that infers orthologous gene groups using Hidden Markov Models parameterized from substitution matrices, enables better detection of remote homologs. Benchmarking indicates OrthoHMM outperforms currently available methods; example, a curated set Bilaterian orthogroups, showed 10.3 – 138.9% improvement in precision. Rank-based benchmarking orthogroups novel dataset organisms three major eukaryotic kingdoms revealed had the best overall performance (6.7 97.8% improvement). These findings suggest improve orthogroup inference.

Language: Английский

Citations

1