Evidence map›Paper›PMID 37082513›Full record

ReviewFrontiers in plant science2022

Two decades of association mapping: Insights on disease resistance in major crops.

Sunil S Gangurde, Alencar Xavier, Yogesh Dashrath Naik, Uday Chand Jha, Sagar Krushnaji Rangari, Raj Kumar, M S Sai Reddy, Sonal Channale, Dinakaran Elango, Reyazul Rouf Mir and 13 more

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in plant science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
10.1field-weighted citation impact, top 2% of its field
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

36 citing papers in PubMed, 51 citations in OpenAlex.

  1. Article
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  6. Genomic dissection of phenological and yield-associated traits in lentil (Physiology and molecular biology of plants : an international journal of functional plant biology · 2026
    Article
  7. Article
  8. Review
  9. Review
  10. Breeding jassid-resistant okra (Frontiers in plant science · 2026
    Review
  11. Article
  12. Article
  13. Article
  14. Review
  15. Integrating multi-omics and machine learning for disease resistance prediction in legumes.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2025
    Review
  16. Review
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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

23 authors at 15 institutions in 5 countries.

Sunil S GangurdeCrop Genetics and Breeding Research, United States Department of Agriculture (USDA) - Agriculture Research Service (ARS), Tifton, GA, United States.
Alencar XavierDepartment of Agronomy, Purdue University, West Lafayette, IN, United States.
Yogesh Dashrath NaikDr. Rajendra Prasad Central Agricultural University (RPCAU), Bihar, India.
Uday Chand JhaIndian Council of Agricultural Research (ICAR), Indian Institute of Pulses Research (IIPR), Kanpur, Uttar Pradesh, India.
Sagar Krushnaji RangariDr. Rajendra Prasad Central Agricultural University (RPCAU), Bihar, India.
Raj KumarDr. Rajendra Prasad Central Agricultural University (RPCAU), Bihar, India.
M S Sai ReddyDr. Rajendra Prasad Central Agricultural University (RPCAU), Bihar, India.
Sonal ChannaleCrop Health Center, University of Southern Queensland (USQ), Toowoomba, QLD, Australia.
Dinakaran ElangoDepartment of Agronomy, Iowa State University, Ames, IA, United States.
Reyazul Rouf MirFaculty of Agriculture, Sher-e-Kashmir University of Agricultural Sciences and Technology (SKUAST), Sopore, India.
Rebecca ZwartCrop Health Center, University of Southern Queensland (USQ), Toowoomba, QLD, Australia.
C LaxumanZonal Agricultural Research Station (ZARS), Kalaburagi, University of Agricultural Sciences, Raichur, Karnataka, India.
Hari Kishan SudiniInternational Crops Research Institute for the Semi-Arid Tropics (ICRISAT), Hyderabad, Telangana, India.
Manish K PandeyCrop Health Center, University of Southern Queensland (USQ), Toowoomba, QLD, Australia.
Somashekhar PunnuriCollege of Agriculture, Family Sciences and Technology, Dr. Fort Valley State University, Fort Valley, GA, United States.
Venugopal MenduDepartment of Plant Science and Plant Pathology, Montana State University, Bozeman, MT, United States.
Umesh K ReddyDepartment of Biology, West Virginia State University, West Virginia, WV, United States.
Baozhu GuoCrop Genetics and Breeding Research, United States Department of Agriculture (USDA) - Agriculture Research Service (ARS), Tifton, GA, United States.
N V P R GangaraoInternational Maize and Wheat Improvement Center (CIMMYT), Nairobi, Kenya.
Vinay K SharmaDr. Rajendra Prasad Central Agricultural University (RPCAU), Bihar, India.
Xingjun WangInstitute of Crop Germplasm Resources, Shandong Academy of Agricultural Sciences (SAAS), Jinan, China.
Chuanzhi ZhaoInstitute of Crop Germplasm Resources, Shandong Academy of Agricultural Sciences (SAAS), Jinan, China.
Mahendar ThudiDr. Rajendra Prasad Central Agricultural University (RPCAU), Bihar, India.
Central Agricultural University · INInternational Crops Research Institute for the Semi-Arid Tropics · INShandong Academy of Agricultural Sciences · CNUniversity of Southern Queensland · AUFort Valley State University · USIndian Council of Agricultural Research · INInternational Maize and Wheat Improvement Center · KEIowa State University · USMontana State University · USPurdue University West Lafayette · USSher-e-Kashmir University of Agricultural Sciences and Technology of Kashmir · INUnited States Department of Agriculture · USUniversity of Agricultural Sciences Raichur · INUniversity of Georgia · USWest Virginia State University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Climate change across the globe has an impact on the occurrence, prevalence, and severity of plant diseases. About 30% of yield losses in major crops are due to plant diseases; emerging diseases are likely to worsen the sustainable production in the coming years. Plant diseases have led to increased hunger and mass migration of human populations in the past, thus a serious threat to global food security. Equipping the modern varieties/hybrids with enhanced genetic resistance is the most economic, sustainable and environmentally friendly solution. Plant geneticists have done tremendous work in identifying stable resistance in primary genepools and many times other than primary genepools to breed resistant varieties in different major crops. Over the last two decades, the availability of crop and pathogen genomes due to advances in next generation sequencing technologies improved our understanding of trait genetics using different approaches. Genome-wide association studies have been effectively used to identify candidate genes and map loci associated with different diseases in crop plants. In this review, we highlight successful examples for the discovery of resistance genes to many important diseases. In addition, major developments in association studies, statistical models and bioinformatic tools that improve the power, resolution and the efficiency of identifying marker-trait associations. Overall this review provides comprehensive insights into the two decades of advances in GWAS studies and discusses the challenges and opportunities this research area provides for breeding resistant varieties.

Indexed as

genome wide association studieshaplotypesk-mersmulti-parent populationspangenomesplant diseases

Identifiers

PMID37082513
PMCPMC10112529
OpenAlexW4311631248

What Socratic holds

Textmetadata
LicenceCC BY
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.