Evidence map›Paper›PMID 40164996›Full record

ArticleThe plant genome2025

Assessing the utility of genomic selection to breed for durable Ascochyta blight resistance in chickpea.

Zibei Lin, Yongjun Li, Adnan Riaz, Shimna Sudheesh, Shahin Yazdifar, Judith Atieno, Sara Blake, Janine Croser, Joshua Fanning, Matthew J Hayden and 1 more

Abstract read
In one paragraph

Article in The plant genome, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Integrated Breeding Approaches for Ascochyta Blight Resistance in Chickpea.International journal of molecular sciences · 2026
    Review
  2. Review
  3. Article
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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

11 authors.

Zibei LinAgriculture Victoria Research, Department of Energy, Environment and Climate Action, Bundoora, Victoria, Australia.ORCID https://orcid.org/0009-0001-8325-4326
Yongjun LiAgriculture Victoria Research, Department of Energy, Environment and Climate Action, Bundoora, Victoria, Australia.
Adnan RiazAgriculture Victoria Research, Department of Energy, Environment and Climate Action, Bundoora, Victoria, Australia.
Shimna SudheeshAgriculture Victoria Research, Department of Energy, Environment and Climate Action, Bundoora, Victoria, Australia.
Shahin YazdifarAgriculture Victoria Research, Department of Energy, Environment and Climate Action, Bundoora, Victoria, Australia.
Judith AtienoSouth Australian Research and Development Institute, Hartley Grove, Urrbrae, South Australia, Australia.
Sara BlakeSouth Australian Research and Development Institute, Hartley Grove, Urrbrae, South Australia, Australia.
Janine CroserSouth Australian Research and Development Institute, Hartley Grove, Urrbrae, South Australia, Australia.
Joshua FanningSchool of Applied Systems Biology, La Trobe University, Bundoora, Victoria, Australia.ORCID https://orcid.org/0000-0002-7730-8498
Matthew J HaydenAgriculture Victoria Research, Department of Energy, Environment and Climate Action, Bundoora, Victoria, Australia.
Sukhjiwan KaurAgriculture Victoria Research, Department of Energy, Environment and Climate Action, Bundoora, Victoria, Australia.

Funding

Agriculture Victoria
6 · The paper itself

Abstract

Ascochyta blight (AB) is one of the most devastating fungal diseases of chickpea (Cicer arietinum L.). Conventional breeding has focused on exploiting and introgressing major genes (qualitative effect) to improve AB resistance in released varieties. However, such approaches are time-consuming and prone to the breakdown of disease resistance due to the fast evolution of AB pathogen. Genomic selection (GS) offers a promising alternative by predicting breeding values using genome-wide single nucleotide polymorphisms (SNPs), regardless of major or minor effects. To our knowledge, this is the first study to develop and implement GS to improve AB resistance in chickpea. Over 4 years, 2790 chickpea lines, representing a broad range of germplasm collections primarily sourced from the Australian Grains Genebank, were evaluated for AB disease response in the field and in an outdoor pot-based facility. Plants were genotyped with the Illumina multispecies pulse 30K SNP array, resulting in 23,239 high-quality SNPs distributed across the genome. Intermediate-to-high genomic prediction accuracies (0.40-0.90) were achieved across validation scenarios. Bayesian modeling identified six major QTL explaining 33% of the genetic variance for AB resistance, with the remaining variance explained by minor effect genes. Using genomic estimated breeding values (GEBVs), 462 lines of the 2790 lines were predicted to have higher resistance compared to the released check varieties, revealing the potential of further improvement of AB resistance for the industry. The desirable genomic prediction accuracy obtained in the study supports the applicability of GS to breed for AB resistance in chickpea.

Indexed as

AscomycotaCicerDisease ResistancePlant BreedingPlant DiseasesSelection, GeneticGenome, PlantGenomicsGenotypePolymorphism, Single Nucleotide

Identifiers

PMID40164996
PMCPMC11958870

What Socratic holds

Textmetadata
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 Socratic graph.