Evidence map›Paper›PMID 29969983›Full record

ArticleBMC genomics2018

Genomic variations and association study of agronomic traits in flax.

Dongwei Xie, Zhigang Dai, Zemao Yang, Qing Tang, Jian Sun, Xue Yang, Xixia Song, Ying Lu, Debao Zhao, Liguo Zhang and 1 more

Abstract read
In one paragraph

Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

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

29 citing papers in PubMed.

  1. Genome Editing Approaches in Flax (International journal of molecular sciences · 2026
    Review
  2. Review
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  7. History and prospects of flax genetic markers.Frontiers in plant science · 2024
    Review
  8. The Genetic Dissection of Nitrogen Use-Related Traits in Flax (International journal of molecular sciences · 2023
    Article
  9. Article
  10. Article
  11. Diversity ofFrontiers in nutrition · 2023
    Review
  12. Article
  13. Article
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  15. Article
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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.

Dongwei XieInstitute of Bast Fiber Crops, Chinese Academy of Agricultural Sciences, Changsha, China.
Zhigang DaiInstitute of Bast Fiber Crops, Chinese Academy of Agricultural Sciences, Changsha, China.
Zemao YangInstitute of Bast Fiber Crops, Chinese Academy of Agricultural Sciences, Changsha, China.
Qing TangInstitute of Bast Fiber Crops, Chinese Academy of Agricultural Sciences, Changsha, China.
Jian SunAgricultural College, Northeast Agricultural University, Harbin, China.
Xue YangSino-Russian Agricultural Scientific and Technological Cooperation Center, Heilongjiang Academy of Agricultural Sciences, Harbin, China.
Xixia SongThe Institute of Industrial Crops, Heilongjiang Academy of Agricultural Sciences, Harbin, China.
Ying LuThe Institute of Industrial Crops, Heilongjiang Academy of Agricultural Sciences, Harbin, China.
Debao ZhaoThe Institute of Industrial Crops, Heilongjiang Academy of Agricultural Sciences, Harbin, China.
Liguo ZhangThe Institute of Industrial Crops, Heilongjiang Academy of Agricultural Sciences, Harbin, China.
Jianguang SuInstitute of Bast Fiber Crops, Chinese Academy of Agricultural Sciences, Changsha, China. su_changsha@163.com.

Funding

Agriculture Scientific and Technological Innovation Project of Chinese Academy of Agricultural Sciences ASTIP-IBFC01China Agriculture Research System CARS-19-E01Fund for the 59th Batch of Certificate of China Postdoctoral Science Foundation 2016M591302Introduction of Doctor's Personnel Scientific Research and Development Fund 201507-43National Natural Science Foundation of China 31471546Project of Heilongjiang Natural Science Foundation of China C2015031
6 · The paper itself

Abstract

backgroundFlax (Linum usitatissimum. L) is an ancient oilseed and natural fiber crop. It could be divided into three categories by use, namely oil flax, fiber flax and oil-fiber dual purpose (OF). Cultivated flax is widely used in the food and textile industry. It is of great significance to elucidate the genetic characteristics of flax collections for accelerating the process of breeding improvement in this dual purpose crop. With the development of next-generation sequencing, we can use new methods, such as SLAF-seq (specific-locus amplified fragment sequencing), to decode unknown genomes of species. In this study, a high-through sequencing of flax collections using SLAF-seq was conducted. The evolutionary tendency was defined and candidate genes associated with agronomic traits of flax species were identified by Genome-Wide Association Studying (GWAS).

resultsA flax collection consisting of 224 varieties were sequenced by SLAF-seq. In total, 346,639 SLAF tags were developed from all accessions, with an average sequencing depth of 7.19 for each accession. A total of 584,987 SNPs (single nucleotide polymorphism) with an MAF > 0.05 were identified from these SLAFs. The population structure division and phylogenetic analysis indicated a strong divergence among three kinds of flax groups. The genome-wide variation uncovered that oil flax had the highest genetic diversity and was considered to be the ancestor of fiber flax and oil-fiber flax. Sixteen associated peak SNPs for six traits were obtained by GWAS of oil-related traits using EMMAX (efficient mixed-model association eXpedited). Candidate genes and their related pathway were evaluated. A new GWAS was developed for fiber properties using the GLM (General linear model) model and a number of loci were identified.

conclusionsTo our knowledge, this is the first study on discovery multiple loci for important agronomic traits of flax species using GWAS strategy. These results will provide the highest possibility of incorporating both high fiber and good oil traits in a single variety.

Indexed as

Genome, PlantGenome-Wide Association StudyBiological EvolutionFlaxGene FlowGenetic VariationLinkage DisequilibriumPhenotypePhylogenyPolymorphism, Single NucleotideQuantitative Trait LociSequence Analysis, DNAEvolutionFlaxGenetic diversityGWASSLAF-seq

Identifiers

PMID29969983
PMCPMC6029072

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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.