NCBI Orthologs: Public Resource and Scalable Method for Computing High-Precision Orthologs Across Eukaryotic Genomes

Orthologs are fundamental for enabling comparative genomics analyses that further our understanding of eukaryotic biology. The unprecedented increase in the availability of high-quality eukaryotic genomes necessitates scalable and accurate methods for orthology inference. The National Center for Biotechnology Information (NCBI) developed "NCBI Orthologs", a resource and a computational pipeline designed to meet this challenge within the NCBI RefSeq framework. This system integrates protein similarity, nucleotide alignment, and microsynteny to achieve high-precision ortholog assignments across diverse eukaryotes. The pipeline leverages high-quality RefSeq annotations and processes genomes individually, ensuring scalability. Resulting ortholog data, organized into gene-level anchored sets, enables propagation of functional annotation information and facilitates comparative genomics. Critically, these data are integrated into the NCBI Gene resource, providing users with access from various entry points. The NCBI Datasets resource provides an intuitive interface to explore orthologous relationships on the web and allows bulk data download via the web, command-line tools, and an API. We detail the methodology, including anchor species selection and the decision tree used to arrive at high-confidence one-to-one orthology relationships. NCBI Orthologs is a valuable resource for facilitating functional annotation efforts and enhancing our understanding of eukaryotic gene evolution.

Authors

Institutions

Publication Details

Journal
Journal of Molecular Evolution
Published
2025-09-25
DOI
https://doi.org/10.1007/s00239-025-10268-2
Citations
4
Primary Topic
Genomics and Phylogenetic Studies
Type
article
Field-Weighted Citation Impact
3.22

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

NCBI Orthologs: Public Resource and Scalable Method for Computing High-Precision Orthologs Across Eukaryotic Genomes

Barbara Robbertse, Françoise Thibaud-Nissen, Eyal Mozes, Vamsi K. Kodali et al.
4 citations
Journal of Molecular Evolution
Genomics and Phylogenetic Studies
3.22
article

NCBI Orthologs: Public Resource and Scalable Method for Computing High-Precision Orthologs Across Eukaryotic Genomes

Barbara Robbertse, Françoise Thibaud-Nissen, Eyal Mozes, Vamsi K. Kodali, Terence D. Murphy, Dong‐Ha Oh, Patrick Masterson, Eric Cox, Kelly M. McGarvey, John Torcivia-Rodriguez, Craig Wallin, Mirian T. N. Tsuchiya, Olga Ermolaeva, Alexander Astashyn, J. Bradley Holmes, Vichet Hem, Laurie Breen, Robert Falk, Nuala A. O’Leary, WF Anderson
article en
4 citations

Abstract

Orthologs are fundamental for enabling comparative genomics analyses that further our understanding of eukaryotic biology. The unprecedented increase in the availability of high-quality eukaryotic genomes necessitates scalable and accurate methods for orthology inference. The National Center for Biotechnology Information (NCBI) developed "NCBI Orthologs", a resource and a computational pipeline designed to meet this challenge within the NCBI RefSeq framework. This system integrates protein similarity, nucleotide alignment, and microsynteny to achieve high-precision ortholog assignments across diverse eukaryotes. The pipeline leverages high-quality RefSeq annotations and processes genomes individually, ensuring scalability. Resulting ortholog data, organized into gene-level anchored sets, enables propagation of functional annotation information and facilitates comparative genomics. Critically, these data are integrated into the NCBI Gene resource, providing users with access from various entry points. The NCBI Datasets resource provides an intuitive interface to explore orthologous relationships on the web and allows bulk data download via the web, command-line tools, and an API. We detail the methodology, including anchor species selection and the decision tree used to arrive at high-confidence one-to-one orthology relationships. NCBI Orthologs is a valuable resource for facilitating functional annotation efforts and enhancing our understanding of eukaryotic gene evolution.

Journal of Molecular EvolutionVol. 93(6)
National Institutes of Health (US), National Center for Biotechnology Information (US)
U.S. Department of Health and Human Services, National Institutes of Health, U.S. National Library of Medicine
Openalex Percentile: Top 8%
Genomics and Phylogenetic Studies
3.22
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.