Evidence map›Paper›PMID 24564784›Full record

ArticleBMC genomics2014

A comprehensive genetic map of sugarcane that provides enhanced map coverage and integrates high-throughput Diversity Array Technology (DArT) markers.

Karen S Aitken, Meredith D McNeil, Scott Hermann, Peter C Bundock, Andrzej Kilian, Katarzyna Heller-Uszynska, Robert J Henry, Jingchuan Li

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
11.2field-weighted citation impact, top 2% 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

27 citing papers in PubMed, 86 citations in OpenAlex.

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  11. An Overview of the Genetics and Genomics of theFrontiers in plant science · 2021
    Review
  12. Article
  13. Development of an Axiom Sugarcane100K SNP array for genetic map construction and QTL identification.TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik · 2019
    Article
  14. Article
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  18. The Endophytic StrainFrontiers in microbiology · 2018
    Article
  19. Article
  20. The Challenge of Analyzing the Sugarcane Genome.Frontiers in plant science · 2018
    Review
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 4 institutions in 1 country.

Karen S AitkenCSIRO Plant Industry, Queensland Bioscience Precinct, 306 Carmody Rd, St Lucia, QLD 4067, Australia. Karen.aitken@csiro.au.
Meredith D McNeil
Scott Hermann
Peter C Bundock
Andrzej Kilian
Katarzyna Heller-Uszynska
Robert J Henry
Jingchuan Li
Commonwealth Scientific and Industrial Research Organisation · AUPlant Industry · AUSouthern Cross University · AUUniversity of Queensland · AU

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSugarcane genetic mapping has lagged behind other crops due to its complex autopolyploid genome structure. Modern sugarcane cultivars have from 110-120 chromosomes and are in general interspecific hybrids between two species with different basic chromosome numbers: Saccharum officinarum (2n = 80) with a basic chromosome number of 10 and S. spontaneum (2n = 40-128) with a basic chromosome number of 8. The first maps that were constructed utilised the single dose (SD) markers generated using RFLP, more recent maps generated using AFLP and SSRs provided at most 60% genome coverage. Diversity Array Technology (DArT) markers are high throughput allowing greater numbers of markers to be generated.

resultsProgeny from a cross between a sugarcane variety Q165 and a S. officinarum accession IJ76-514 were used to generate 2467 SD markers. A genetic map of Q165 was generated containing 2267 markers, These markers formed 160 linkage groups (LGs) of which 147 could be placed using allelic information into the eight basic homology groups (HGs) of sugarcane. The HGs contained from 13 to 23 LGs and from 204 to 475 markers with a total map length of 9774.4 cM and an average density of one marker every 4.3 cM. Each homology group contained on average 280 markers of which 43% were DArT markers 31% AFLP, 16% SSRs and 6% SNP markers. The multi-allelic SSR and SNP markers were used to place the LGs into HGs.

conclusionsThe DArT array has allowed us to generate and map a larger number of markers than ever before and consequently to map a larger portion of the sugarcane genome. This larger number of markers has enabled 92% of the LGs to be placed into the 8 HGs that represent the basic chromosome number of the ancestral species, S. spontaneum. There were two HGs (HG2 and 8) that contained larger numbers of LGs verifying the alignment of two sets of S. officinarum chromosomes with one set of S. spontaneum chromosomes and explaining the difference in basic chromosome number between the two ancestral species. There was also evidence of more complex structural differences between the two ancestral species.

Indexed as

Genetic MarkersGenome, PlantAmplified Fragment Length Polymorphism AnalysisChromosome MappingGenetic VariationMicrosatellite RepeatsPolymorphism, Single NucleotideSaccharumGenetic Markers

Identifiers

PMID24564784
PMCPMC4007999
OpenAlexW2164853371

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

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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.