Evidence map›Paper›PMID 37209309›Full record

ArticleFunctional & integrative genomics2023

Comparative transcriptome profiling of near isogenic lines PBW343 and FLW29 to unravel defense related genes and pathways contributing to stripe rust resistance in wheat.

Zahoor Ahmad Mir, Divya Chauhan, Anjan Kumar Pradhan, Vivek Srivastava, Divya Sharma, Neeraj Budhlakoti, Dwijesh Chandra Mishra, Vasudha Jadon, Tanmaya Kumar Sahu, Monendra Grover and 8 more

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Article in Functional & integrative genomics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
2.4field-weighted citation impact, top 11% 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

4 citing papers in PubMed, 6 citations in OpenAlex.

  1. Review
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  4. Genome-wide identification and characterization ofFrontiers in plant science · 2023
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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

18 authors at 4 institutions in 1 country.

Zahoor Ahmad MirICAR-National Bureau of Plant Genetic Resources, New Delhi, 110012, India.
Divya ChauhanICAR-National Bureau of Plant Genetic Resources, New Delhi, 110012, India.
Anjan Kumar PradhanICAR-National Bureau of Plant Genetic Resources, New Delhi, 110012, India.
Vivek SrivastavaICAR-National Bureau of Plant Genetic Resources, New Delhi, 110012, India.
Divya SharmaICAR-National Bureau of Plant Genetic Resources, New Delhi, 110012, India.
Neeraj BudhlakotiICAR-Indian Agricultural Statistics Research Institute, New Delhi, 110012, India.
Dwijesh Chandra MishraICAR-Indian Agricultural Statistics Research Institute, New Delhi, 110012, India.
Vasudha JadonICAR-National Bureau of Plant Genetic Resources, New Delhi, 110012, India.
Tanmaya Kumar SahuICAR-National Bureau of Plant Genetic Resources, New Delhi, 110012, India.
Monendra GroverICAR-Indian Agricultural Statistics Research Institute, New Delhi, 110012, India.
Om Prakash GangwarICAR-Indian Institute of Wheat and Barley Research, Flowerdale, Shimla, Himachal, Pradesh, 171002, India.
Subodh KumarICAR-Indian Institute of Wheat and Barley Research, Flowerdale, Shimla, Himachal, Pradesh, 171002, India.
S C BhardwajICAR-Indian Institute of Wheat and Barley Research, Flowerdale, Shimla, Himachal, Pradesh, 171002, India.
Jasdeep C PadariaICAR-National Institute for Plant Biotechnology, New Delhi, 110012, India.
Amit Kumar SinghICAR-National Bureau of Plant Genetic Resources, New Delhi, 110012, India.
Anil RaiICAR-Indian Agricultural Statistics Research Institute, New Delhi, 110012, India.
G P SinghICAR-National Bureau of Plant Genetic Resources, New Delhi, 110012, India.
Sundeep KumarICAR-National Bureau of Plant Genetic Resources, New Delhi, 110012, India. Sundeep.Kumar@icar.gov.in.
National Bureau of Plant Genetic Resources · INIndian Agricultural Statistics Research Institute · INIndian Institute of Wheat and Barley Research · INNational Research Centre on Plant Biotechnology · IN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Stripe rust (Sr), caused by Puccinia striiformis f. sp. tritici (Pst), is the most devastating disease that poses serious threat to the wheat-growing nations across the globe. Developing resistant cultivars is the most challenging aspect in wheat breeding. The function of resistance genes (R genes) and the mechanisms by which they influence plant-host interactions are poorly understood. In the present investigation, comparative transcriptome analysis was carried out by involving two near-isogenic lines (NILs) PBW343 and FLW29. The seedlings of both the genotypes were inoculated with Pst pathotype 46S119. In total, 1106 differentially expressed genes (DEGs) were identified at early stage of infection (12 hpi), whereas expressions of 877 and 1737 DEGs were observed at later stages (48 and 72 hpi) in FLW29. The identified DEGs were comprised of defense-related genes including putative R genes, 7 WRKY transcriptional factors, calcium, and hormonal signaling associated genes. Moreover, pathways involved in signaling of receptor kinases, G protein, and light showed higher expression in resistant cultivar and were common across different time points. Quantitative real-time PCR was used to further confirm the transcriptional expression of eight critical genes involved in plant defense mechanism against stripe rust. The information about genes are likely to improve our knowledge of the genetic mechanism that controls the stripe rust resistance in wheat, and data on resistance response-linked genes and pathways will be a significant resource for future research.

Indexed as

BasidiomycotaTriticumDisease ResistanceGene Expression ProfilingGenotypePlant BreedingPlant DiseasesDEGsPuccinia striiformis (Pst)R-gene mediated resistanceStripe rustTranscriptome

Identifiers

PMID37209309
OpenAlexW4377138659

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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.