Evidence map›Paper›PMID 42595963›Full record

ArticleThe New phytologist2026

Plant species identification by genome skimming across the vascular plant tree of life.

Chun-Xia Zeng, Meng-Yuan Zhou, Alex D Twyford, Lian-Ming Gao, Zhi-Yong Zhang, Yun-Heng Ji, Hong-Tao Li, Peng-Fei Ma, Wen-Bin Yu, Zhi-Qiong Mo and 6 more

Abstract read
In one paragraph

Article in The New phytologist, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

16 authors.

Chun-Xia Zeng *Germplasm Bank of Wild Species & Yunnan Key Laboratory of Crop Wild Relative Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, Yunnan, 650201, China.ORCID https://orcid.org/0000-0002-0823-8406
Meng-Yuan Zhou *Germplasm Bank of Wild Species & Yunnan Key Laboratory of Crop Wild Relative Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, Yunnan, 650201, China.ORCID https://orcid.org/0000-0003-1492-8494
Alex D TwyfordInstitute of Ecology and Evolution, School of Biological Sciences, University of Edinburgh, Edinburgh, EH9 3FL, UK.ORCID https://orcid.org/0000-0002-8746-6617
Lian-Ming GaoCenter for Interdisciplinary Biodiversity Research & College of Forestry, Shandong Agricultural University, Tai'an, Shandong, 271018, China.ORCID https://orcid.org/0000-0001-9047-2658
Zhi-Yong ZhangKey Laboratory of Ecology of Rare and Endangered Species and Environmental Protection (Guangxi Normal University), Ministry of Education, Guilin, Guangxi, 541004, China.ORCID https://orcid.org/0000-0003-0490-4181
Yun-Heng JiState Key Laboratory of Plant Diversity and Specialty Crops, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, Yunnan, 650201, China.ORCID https://orcid.org/0000-0002-1116-7485
Hong-Tao LiGermplasm Bank of Wild Species & Yunnan Key Laboratory of Crop Wild Relative Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, Yunnan, 650201, China.ORCID https://orcid.org/0000-0002-1290-0917
Peng-Fei MaGermplasm Bank of Wild Species & Yunnan Key Laboratory of Crop Wild Relative Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, Yunnan, 650201, China.ORCID https://orcid.org/0000-0003-3061-1454
Wen-Bin YuCenter for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla, Yunnan, 666303, China.ORCID https://orcid.org/0000-0002-7643-2112
Zhi-Qiong MoGermplasm Bank of Wild Species & Yunnan Key Laboratory of Crop Wild Relative Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, Yunnan, 650201, China.ORCID https://orcid.org/0000-0002-0219-1213
Zheng-Yu ZuoCenter for Interdisciplinary Biodiversity Research & College of Forestry, Shandong Agricultural University, Tai'an, Shandong, 271018, China.ORCID https://orcid.org/0000-0002-8334-6132
Wu HuangRoyal Botanic Garden Edinburgh, Edinburgh, EH3 5LR, UK.ORCID https://orcid.org/0000-0002-5015-7167
Ting-Shuang YiGermplasm Bank of Wild Species & Yunnan Key Laboratory of Crop Wild Relative Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, Yunnan, 650201, China.ORCID https://orcid.org/0000-0001-7093-9564
Jun-Bo YangGermplasm Bank of Wild Species & Yunnan Key Laboratory of Crop Wild Relative Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, Yunnan, 650201, China.ORCID https://orcid.org/0000-0002-8917-1759
Peter M HollingsworthRoyal Botanic Garden Edinburgh, Edinburgh, EH3 5LR, UK.ORCID https://orcid.org/0000-0003-0602-0654
De-Zhu LiGermplasm Bank of Wild Species & Yunnan Key Laboratory of Crop Wild Relative Omics, Kunming Institute of Botany, Chinese Academy of Sciences, Kunming, Yunnan, 650201, China.ORCID https://orcid.org/0000-0002-4990-724X

Funding

Science and Technology Basic Resources Investigation Program of China 2021FY100200Science and Technology Basic Resources Investigation Program of China 2023YFA0915800the National Natural Science Foundation of China 32120103003the National Natural Science Foundation of China 32370245
6 · The paper itself

Abstract

Accurate species identification is essential for biodiversity conservation and sustainable use, yet standard plant DNA barcoding often fails to achieve species-level resolution. We present a large-scale empirical evaluation of genome skimming as a tool to improve plant species discrimination. Using standardised data from 1969 individuals representing 475 species from 32 genera across major lineages of the vascular plant tree of life, we compare conventional plastid + internal transcribed spacer (ITS) barcodes with genome skimming approaches. Standard barcoding using rbcL, matK, trnH-psbA and ITS resolved about half of species (49.3%), with six genera showing < 25% species discrimination. By contrast, genome skimming enabled the recovery of complete plastid genomes, yielding 57.6% species discrimination. It also generated sufficient nuclear genomic data for additional resolution from k-mer analysis, achieving 66.8% species discrimination - an average gain of 17.5% over standard barcodes - while eliminating cases of extreme failure (< 25% resolution). The recovery of complete plastomes and ribosomal DNAs from genome skims also ensures backward compatibility with existing barcode datasets. Our results demonstrate that genome skimming provides data that substantially improves species-level resolution across diverse plant lineages and offers a scalable, high-throughput approach for building comprehensive reference resources to support global biodiversity initiatives.

Indexed as

DNA Barcoding, TaxonomicGenome, PlantTreesGenome, PlastidPhylogenySpecies SpecificityDNA barcodinggenome skimsk‐mer analysisplant species identificationplastomes

Identifiers

PMID42595963
PMCPMC13539984

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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.