Evidence map›Paper›PMID 41705644›Full record

ArticleMolecular ecology resources2026

GeneMiner2: Accurate and Automated Recovery of Genes From Genome Skimming Data.

Xinyi Yu, Zizhen Tang, Zhen Zhang, Yongxiu Song, Hao He, Yi Shi, Jiaqing Hou, Yan Yu

Abstract read
In one paragraph

Article in Molecular ecology resources, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Xinyi YuKey Laboratory of Bio-Resources and Eco-Environment of Ministry of Education, Southwest Bio-Resources R&D Key Laboratory of Sichuan Province, Laboratory for Ex Situ Conservation and Resource Utilization of Montane Plants, College of Life Sciences, Sichuan University, Chengdu, Sichuan, China.
Zizhen TangKey Laboratory of Bio-Resources and Eco-Environment of Ministry of Education, Southwest Bio-Resources R&D Key Laboratory of Sichuan Province, Laboratory for Ex Situ Conservation and Resource Utilization of Montane Plants, College of Life Sciences, Sichuan University, Chengdu, Sichuan, China.
Zhen ZhangKey Laboratory of Bio-Resources and Eco-Environment of Ministry of Education, Southwest Bio-Resources R&D Key Laboratory of Sichuan Province, Laboratory for Ex Situ Conservation and Resource Utilization of Montane Plants, College of Life Sciences, Sichuan University, Chengdu, Sichuan, China.
Yongxiu SongKey Laboratory of Bio-Resources and Eco-Environment of Ministry of Education, Southwest Bio-Resources R&D Key Laboratory of Sichuan Province, Laboratory for Ex Situ Conservation and Resource Utilization of Montane Plants, College of Life Sciences, Sichuan University, Chengdu, Sichuan, China.ORCID https://orcid.org/0000-0002-5221-5746
Hao HeKey Laboratory of Bio-Resources and Eco-Environment of Ministry of Education, Southwest Bio-Resources R&D Key Laboratory of Sichuan Province, Laboratory for Ex Situ Conservation and Resource Utilization of Montane Plants, College of Life Sciences, Sichuan University, Chengdu, Sichuan, China.
Yi ShiKey Laboratory of Bio-Resources and Eco-Environment of Ministry of Education, Southwest Bio-Resources R&D Key Laboratory of Sichuan Province, Laboratory for Ex Situ Conservation and Resource Utilization of Montane Plants, College of Life Sciences, Sichuan University, Chengdu, Sichuan, China.
Jiaqing HouKey Laboratory of Bio-Resources and Eco-Environment of Ministry of Education, Southwest Bio-Resources R&D Key Laboratory of Sichuan Province, Laboratory for Ex Situ Conservation and Resource Utilization of Montane Plants, College of Life Sciences, Sichuan University, Chengdu, Sichuan, China.
Yan YuKey Laboratory of Bio-Resources and Eco-Environment of Ministry of Education, Southwest Bio-Resources R&D Key Laboratory of Sichuan Province, Laboratory for Ex Situ Conservation and Resource Utilization of Montane Plants, College of Life Sciences, Sichuan University, Chengdu, Sichuan, China.

Funding

National Natural Science Foundation of China 32271552National Natural Science Foundation of China 32571738Science & Technology Fundamental Resources Investigation Program 2022FY101000Sichuan Natural Science Foundation 2026NSFSCZY0116
6 · The paper itself

Abstract

With the growing accessibility of low cost genome skimming, large-scale recovery of target genes in non-model species has become feasible, providing strong data for phylogenomic and evolutionary studies. However, existing tools for data assembly including Read2Tree, HybPiper, and GeneMiner still suffer from computational difficulty and assembly errors when processing genome skimming data, especially for low-level taxa that lack closely related genome references. Here, we present GeneMiner2, an updated version of GeneMiner, as an efficient and automated gene assembly and phylogenetic tool to overcome these limitations. Compared with the previous version, GeneMiner2 introduces three key optimizations by deploying a two-level hash table that speeds up k-mer filtering, applying fine-grained read selection with strand-orientation and structural-anomaly detection to handle complex heterozygous regions, and incorporating adaptive k-mer selection in the de Bruijn assembler. Together enabling accurate assembly of target genes without the need for closely related references. Using simulated datasets with low coverage and divergent references, we validated the robustness and improved accuracy of GeneMiner2 in the assembly of single-copy genes. Moreover, using genome skimming data from the subfamily Apioideae (Apiaceae), GeneMiner2 outperformed Read2Tree and HybPiper in accuracy, completeness, and speed. Equipped with a user-friendly graphical interface, GeneMiner2 integrates functions including assembly quality control, paralog detection, tree reconstruction, and divergence time calibration, offering a robust and efficient solution for phylogenetic inference using genomic level data. GeneMiner2 supports cross-platform operation. GeneMiner2 provides a user-friendly graphical interface for desktop users, and its high-performance command-line interface is specifically optimised for high-throughput analyses on Linux servers and computing clusters. Installation instructions, detailed documentation, and source code are available on GitHub (https://github.com/sculab/GeneMiner2).

Indexed as

Computational BiologyGenomicsSoftwarePhylogenySequence Analysis, DNAadaptive k‐mer selectionassembly toolfine‐grained read selectionphylogenetic marker

Identifiers

PMID41705644
PMCPMC12914762

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.