Evidence map›Paper›PMID 41224779›Full record

ArticleNature communications2025

Augmenting microbial phylogenomic signal with tailored marker gene sets.

Henry Secaira-Morocho, Xiaofang Jiang, Qiyun Zhu

Abstract read
In one paragraph

Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

3 authors.

Henry Secaira-MorochoCenter for Fundamental and Applied Microbiomics and School of Life Sciences, Arizona State University, Tempe, AZ, USA.ORCID http://orcid.org/0000-0002-3409-1284
Xiaofang JiangNational Library of Medicine, National Institutes of Health, Bethesda, MD, USA.ORCID http://orcid.org/0000-0002-0955-8284
Qiyun ZhuCenter for Fundamental and Applied Microbiomics and School of Life Sciences, Arizona State University, Tempe, AZ, USA. qiyun.zhu@asu.edu.ORCID http://orcid.org/0000-0002-3568-6271

Funding

ADHS | Arizona Biomedical Research Commission (ABRC) RFGA2023-008-15
6 · The paper itself

Abstract

Phylogenetic marker genes are traditionally selected from a fixed collection of whole genomes representing major microbial phyla, covering only a small fraction of gene families. However, most microbial diversity resides in metagenome-assembled genomes, which exhibit taxonomic imbalance and harbor gene families that do not fit the criteria for universal orthologs. To address these limitations, we introduce TMarSel, a software tool for automated, free-from-expert opinion, and tailored marker selection for deep microbial phylogenomics. TMarSel allows users to select a variable number of markers and copies based on KEGG and EggNOG gene family annotations, enabling a systematic evaluation of the phylogenetic signal from the entire gene family pool. We show that an expanded marker selection tailored to the input genomes improves the accuracy of phylogenetic trees across simulated and real-world datasets of whole genomes and metagenome-assembled genomes compared to previous markers, even when metagenome-assembled genomes lack a fraction of open reading frames. The selected markers have functional annotations related to metabolism, cellular processes, and environmental information processing, in addition to replication, translation, and transcription. TMarSel provides flexibility in the number of markers, copies, and annotation databases while remaining robust against taxonomic imbalance and incomplete genomic data.

Indexed as

BacteriaMetagenomicsPhylogenyGenetic MarkersGenome, BacterialMetagenomeMolecular Sequence AnnotationSoftwareGenetic Markers

Identifiers

PMID41224779
PMCPMC12612119

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

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.