Evidence map›Paper›PMID 31412771›Full record

ArticleBMC genetics2019

The first genetic map for yellow lupin enables genetic dissection of adaptation traits in an orphan grain legume crop.

Muhammad Munir Iqbal, Mark Huynh, Joshua A Udall, Andrzej Kilian, Kedar N Adhikari, Jens D Berger, William Erskine, Matthew N Nelson

Open access · diamondAbstract read
In one paragraph

Article in BMC genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
4.7field-weighted citation impact, top 6% 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

14 citing papers in PubMed, 21 citations in OpenAlex.

  1. Article
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  8. Review
  9. Horticulture research · 2022
    Article
  10. Quantitative Control of Early Flowering in White Lupin (International journal of molecular sciences · 2021
    Article
  11. Article
  12. Phenotypic characterisation and linkage mapping of domestication syndrome traits in yellow lupin (Lupinus luteus L.).TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2020
    Article
  13. Review
  14. 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

8 authors at 6 institutions in 2 countries.

Muhammad Munir IqbalSchool of Agriculture and Environment, The University of Western Australia, Perth, WA, Australia. munirqbl@gmail.com.ORCID 0000-0002-7712-3063
Mark HuynhThe College of Life Sciences, Brigham Young University, Provo, UT, USA.
Joshua A UdallUSDA-ARS Southern Plains Agricultural Research Center, 2881 F&B Rd., College Station, TX, 77845, USA.
Andrzej KilianDiversity Arrays Technology, University of Canberra, Canberra, Australia.
Kedar N AdhikariSchool of Life and Environmental Sciences, I A Watson Grains Research Centre, The University of Sydney, Narrabri, NSW, Australia.
Jens D BergerAgriculture and Food, CSIRO, Floreat, WA, Australia.
William ErskineSchool of Agriculture and Environment, The University of Western Australia, Perth, WA, Australia.
Matthew N NelsonAgriculture and Food, CSIRO, Floreat, WA, Australia.
Commonwealth Scientific and Industrial Research Organisation · AUThe University of Western Australia · AUBrigham Young University · USSouthern Plains Agricultural Research Center · USThe University of Sydney · AUUniversity of Canberra · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundYellow lupin (Lupinus luteus L.) is a promising grain legume for productive and sustainable crop rotations. It has the advantages of high tolerance to soil acidity and excellent seed quality, but its current yield potential is poor, especially in low rainfall environments. Key adaptation traits such as phenology and enhanced stress tolerance are often complex and controlled by several genes. Genomic-enabled technologies may help to improve our basic understanding of these traits and to provide selective markers in breeding. However, in yellow lupin there are very limited genomic resources to support research and no published information is available on the genetic control of adaptation traits.

resultsWe aimed to address these deficiencies by developing the first linkage map for yellow lupin and conducting quantitative trait locus (QTL) analysis of yield under well-watered (WW) and water-deficit (WT) conditions. Two next-generation sequencing marker approaches - genotyping-by-sequencing (GBS) and Diversity Array Technology (DArT) sequencing - were employed to genotype a recombinant inbred line (RIL) population developed from a bi-parental cross between wild and domesticated parents. A total of 2,458 filtered single nucleotide polymorphism (SNP) and presence / absence variation (PAV) markers were used to develop a genetic map comprising 40 linkage groups, the first reported for this species. A number of significant QTLs controlling total biomass and 100-seed weight under two water (WW and WD) regimes were found on linkage groups YL-03, YL-09 and YL-26 that together explained 9 and 28% of total phenotypic variability. QTLs associated with length of the reproductive phase and time to flower were found on YL-01, YL-21, YL-35 and YL-40 that together explained a total of 12 and 44% of total phenotypic variation.

conclusionThese genomic resources and the QTL information offer significant potential for use in marker-assisted selection in yellow lupin.

Indexed as

Chromosome MappingQuantitative Trait, HeritableQuantitative Trait LociAnalysis of VarianceCrops, AgriculturalEdible GrainGenetic LinkageGenetic MarkersGenotypeInbreedingLupinusPhenotypePlant BreedingGenetic MarkersAdaptation traitsLinkage mapPhenologyQTL analysisYellow lupin

Identifiers

PMID31412771
PMCPMC6694670
OpenAlexW2967731136

What OpenQuestion holds

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LicenceCC BY
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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.