Evidence map›Paper›PMID 40663195›Full record

ArticleArchives of microbiology2025

Deciphering mating type and population genetic landscape of Magnaporthe population adapted to millets and rice in blast hotspots of India.

K B Palanna, Gutha Venkata Ramesh, Prasanna S Koti, H D Vinaykumar, Divya Bhandhari, H R Raveendra, T S S K Patro, T V Krishna, T E Nagaraja, R Madhusudhana and 1 more

Abstract read
PubMed Publisher
In one paragraph

Article in Archives of microbiology, 2025. 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

11 authors.

K B PalannaPC Unit, ICAR-AICRP on Small millets, University of Agricultural Sciences, GKVK, Bangalore, Karnataka, India. kbpalanna@gmail.com.ORCID http://orcid.org/0000-0001-6358-8989
Gutha Venkata RameshKrishi Vigyan Kendra (KVK), Eastern Regional Station, ICAR-National Dairy Research Institute (NDRI), Nadia II, Kalyani, 741235, West Bengal, India. Rameshgutha02@gmail.com.ORCID http://orcid.org/0000-0001-6197-523X
Prasanna S KotiDepartment of Plant Biotechnology, University of Agricultural Sciences, GKVK, Bangalore, Karnataka, India.
H D VinaykumarPC Unit, ICAR-AICRP on Small millets, University of Agricultural Sciences, GKVK, Bangalore, Karnataka, India.
Divya BhandhariRegional Station, ICAR-Indian Institute of Wheat & Barley Research, Flowerdale, Shimla, Himachal Pradesh, India.
H R RaveendraICAR-AICRP on Small millets Zonal Agril. Research Station, V.C. Farm, Mandya, Karnataka, India.
T S S K PatroAgricultural Research Station, Gajularega, Vizianagaram, Andra Pradesh, India.
T V KrishnaZonal Agricultural Research Station, ICAR-AICRP on Arid Legumes, University of Agricultural Sciences, GKVK, Bangalore, Karnataka, India.
T E NagarajaPC Unit, ICAR-AICRP on Small millets, University of Agricultural Sciences, GKVK, Bangalore, Karnataka, India.
R MadhusudhanaICAR-Indian Institute of Millets Research, Rajendranagar, Hyderabad, Telangana, India.
C Tara SatyavathiICAR-Indian Institute of Millets Research, Rajendranagar, Hyderabad, Telangana, India.

Funding

DST-Science and Engineering Research Board SERB-EEQ/2019/000678
6 · The paper itself

Abstract

Blast disease caused by Magnaporthe spp. is one of the most destructive diseases affecting graminaceous hosts such as rice and millet crops worldwide. Understanding the reproductive biology and the genetic structure of the pathogen is essential for devising effective management strategies. The current study aimed to assess the mating type distribution, fertility status, DNA polymorphism, gene flow and the population structure of Magnaporthe spp. infecting millets and rice across major blast hotspots of India. Mating type-specific PCR amplification of 136 isolates targeting MAT1-1 and MAT1-2 idiomorphs revealed diverse reproductive strategies. Among the millet-infecting isolates (n = 127), 36.22% were male fertile, 26.77% female fertile, 17.32% hermaphroditic and 19.68% unknown. Rice infecting isolates displayed a mixed mating profile, while bajra isolates were unknown. The presence of both mating types and hermaphroditism suggests potential for sexual recombination, posing a risk of increased genetic variability and virulence. The sequence-based polymorphism analysis of 114 isolates (from finger and foxtail millet) revealed 187 segregating sites and 208 mutations, including 117 singleton sites. The population exhibited high Hd (0.982) and moderate nucleotide diversity (π = 0.0053), indicating significant genetic richness and potential for adaptive evolution. Neutrality tests Tajima's D (-2.418), Fu and Li's D* (-5.197), and F* (-4.752) were significantly negative (p < 0.02) supporting recent population expansion or purifying selection. Population differentiation analyses showed low Gst (0.0217), moderate Fst (0.0797) with high gene flow (Nm = 11.27) reflecting limited population subdivision with ongoing genetic exchange. Haplotype network analysis identified 95 unique haplotypes with most being singletons, supporting high mutational diversity. A central haplotype (Hap_39), comprising 15 isolates of different mating types represents a potential ancestral or broadly adapted lineage. Interestingly, hermaphroditic isolates predominantly clustered in a distinct clade suggesting reproductive isolation and host-specific evolutionary trajectories. AMOVA revealed that 93.27% of genetic variation existed within populations and 6.73% among populations (Φ

Indexed as

Genes, Mating Type, FungalMagnaportheMilletsOryzaPlant DiseasesGene FlowGenetic VariationIndiaPhylogenyPolymorphism, GeneticVirulenceBlast pathogenGenealogyHaplotypingMating typePathogen evolutionPopulation structure

Identifiers

What OpenQuestion 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 OpenQuestion graph.