Evidence map›Paper›PMID 29098463›Full record

ArticleRice (New York, N.Y.)2017

Mapping QTLs using a novel source of salinity tolerance from Hasawi and their interaction with environments in rice.

M Akhlasur Rahman, Isaac Kofi Bimpong, J B Bizimana, Evangeline D Pascual, Marydee Arceta, B P Mallikarjuna Swamy, Faty Diaw, M Sazzadur Rahman, R K Singh

Abstract read
In one paragraph

Article in Rice (New York, N.Y.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed, 2 pooled it
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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

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

27 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Review
  5. Article
  6. Genomic prediction and QTL analysis for grain Zn content and yield inJournal of plant biochemistry and biotechnology · 2024
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  17. QTL mapping under salt stress in rice using a Kalarata-Azucena population.Euphytica: Netherlands journal of plant breeding · 2022
    Article
  18. Review
  19. Salt tolerance in rice: seedling and reproductive stage QTL mapping come of age.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2021
    Review
  20. Article
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

9 authors.

M Akhlasur RahmanInternational Rice Research Institute (IRRI), DAPO Box 7777, Metro Manila, Philippines.
Isaac Kofi BimpongAfrica Rice Center, Sahel Regional Station, BP 96, St Louis, Senegal.
J B BizimanaIRRI-ESA Office, Bujumbura, Burundi.
Evangeline D PascualInstitute of Biological Sciences, University of the Philippines at Los Baños, Laguna, Philippines.
Marydee ArcetaInternational Rice Research Institute (IRRI), DAPO Box 7777, Metro Manila, Philippines.
B P Mallikarjuna SwamyInternational Rice Research Institute (IRRI), DAPO Box 7777, Metro Manila, Philippines.
Faty DiawAfrica Rice Center, Sahel Regional Station, BP 96, St Louis, Senegal.
M Sazzadur RahmanBangladesh Rice Research Institute, Gazipur, 1701, Bangladesh.
R K SinghInternational Rice Research Institute (IRRI), DAPO Box 7777, Metro Manila, Philippines. r.k.singh@irri.org.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSalinity is one of the most severe and widespread abiotic stresses that affect rice production. The identification of major-effect quantitative trait loci (QTLs) for traits related to salinity tolerance and understanding of QTL × environment interactions (QEIs) can help in more precise and faster development of salinity-tolerant rice varieties through marker-assisted breeding. Recombinant inbred lines (RILs) derived from IR29/Hasawi (a novel source of salinity) were screened for salinity tolerance in the IRRI phytotron in the Philippines (E1) and in two other diverse environments in Senegal (E2) and Tanzania (E3). QTLs were mapped for traits related to salinity tolerance at the seedling stage.

resultsThe RILs were genotyped using 194 polymorphic SNPs (single nucleotide polymorphisms). After removing segregation distortion markers (SDM), a total of 145 and 135 SNPs were used to construct a genetic linkage map with a length of 1655 and 1662 cM, with an average marker density of 11.4 cM in E1 and 12.3 cM in E2 and E3, respectively. A total of 34 QTLs were identified on 10 chromosomes for five traits using ICIM-ADD and segregation distortion locus (SDL) mapping (IM-ADD) under salinity stress across environments. Eight major genomic regions on chromosome 1 between 170 and 175 cM (qSES1.3, qSES1.4, qSL1.2, qSL1.3, qRL1.1, qRL1.2, qFWsht1.2, qDWsht1.2), chromosome 4 at 32 cM (qSES4.1, qFWsht4.2, qDWsht4.2), chromosome 6 at 115 cM (qFWsht6.1, qDWsht6.1), chromosome 8 at 105 cM (qFWsht8.1, qDWsht8.1), and chromosome 12 at 78 cM (qFWsht12.1, qDWsht12.1) have co-localized QTLs for the multiple traits that might be governing seedling stage salinity tolerance through multiple traits in different phenotyping environments, thus suggesting these as hot spots for tolerance of salinity. Forty-nine and 30 significant pair-wise epistatic interactions were detected between QTL-linked and QTL-unlinked regions using single-environment and multi-environment analyses.

conclusionsThe identification of genomic regions for salinity tolerance in the RILs showed that Hasawi possesses alleles that are novel for salinity tolerance. The common regions for the multiple QTLs across environments as co-localized regions on chromosomes 1, 4, 6, 8, and 12 could be due to linkage or pleiotropic effect, which might be helpful for multiple QTL introgression for marker-assisted breeding programs to improve the salinity tolerance of adaptive and popular but otherwise salinity-sensitive rice varieties.

Indexed as

Hasawi-aus rice landraceNovel QTLsQTL × environment interactionsSeedling-stage salinity toleranceSingle nucleotide polymorphism (SNP)

Identifiers

PMID29098463
PMCPMC5668218

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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.