Evidence map›Paper›PMID 39046037›Full record

ArticleJournal of biosciences2024

Defining genomic landscape for identification of potential candidate resistance genes associated with major rice diseases through MetaQTL analysis.

Simran Goyal, Dinesh Kumar Saini, Pankaj Kumar, Gurwinder Kaur, Umesh Preethi Praba, Krishna Sai Karnatam, Gautam Chhabra, Rajveer Singh, Yogesh Vikal

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Article in Journal of biosciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

9 authors.

Simran GoyalCollege of Agriculture, Punjab Agricultural University, Ludhiana 141004, India.
Dinesh Kumar Saini
Pankaj Kumar
Gurwinder Kaur
Umesh Preethi Praba
Krishna Sai Karnatam
Gautam Chhabra
Rajveer Singh
Yogesh Vikal

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rice production is severely affected by various diseases such as bacterial leaf blight (BLB), brown spot (BS), false smut (FS), foot rot (FR), rice blast (RB), and sheath blight (SB). In recent years, several quantitative trait loci (QTLs) studies involving different populations have been carried out, resulting in the identification of hundreds of resistance QTLs for each disease. These QTLs can be integrated and analyzed using meta-QTL (MQTL) analysis for better understanding of the genetic architecture underlying multiple disease resistance (MDR). This study involved an MQTL analysis on 661 QTLs (378, 161, 21, 41, 44, and 16 QTLs for SB, RB, BLB, BS, FS, and FR, respectively) retrieved from 50 individual studies published from 1995 to 2021. Of these, 503 QTLs were projected finally onto the consensus map saturated with 6,275 markers, resulting in 73 MQTLs, including 27 MDR-MQTLs conferring resistance to three or more diseases. Forty-seven MQTLs were validated using marker-trait associations identified in published genome-wide association studies. A total of 3,310 genes, including both R and defense genes, were also identified within some selected high-confidence MQTL regions that were investigated further for the syntenic relationship with barley, wheat, and maize genomes. Thirty-nine high-confidence candidate genes were selected based on their expression patterns and recommended for future studies involving functional validation, genetic engineering, and gene editing. Nineteen MQTLs were co-localized with 39 known R genes for BLB and RB diseases. These results could pave the way to utilize candidate genes in a marker-assisted breeding program for MDR in rice.

Indexed as

Disease ResistanceOryzaPlant DiseasesQuantitative Trait LociChromosome MappingChromosomes, PlantGenes, PlantGenome-Wide Association Study

Identifiers

PMID39046037

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