Evidence map›Paper›PMID 28330454›Full record

ArticleBMC genomics2017

Uncovering SNP and indel variations of tetraploid cottons by SLAF-seq.

Chao Shen, Xin Jin, De Zhu, Zhongxu Lin

Abstract read
In one paragraph

Article in BMC genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.

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20citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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3 · Its place in the literature

Who cites it

20 citing papers in PubMed.

  1. Article
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  6. Genome-wide identification and development of InDel markers in tobacco (Physiology and molecular biology of plants : an international journal of functional plant biology · 2022
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  7. SNP detection and population structure evaluation ofPhysiology and molecular biology of plants : an international journal of functional plant biology · 2021
    Article
  8. Article
  9. QTL Mapping for Leaf Area of Tea Plants (Frontiers in plant science · 2021
    Article
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  11. Review
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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Chao ShenNational Key Laboratory of Crop Genetic Improvement, College of Plant Science & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
Xin JinNational Key Laboratory of Crop Genetic Improvement, College of Plant Science & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
De ZhuNational Key Laboratory of Crop Genetic Improvement, College of Plant Science & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China.
Zhongxu LinNational Key Laboratory of Crop Genetic Improvement, College of Plant Science & Technology, Huazhong Agricultural University, Wuhan, 430070, Hubei, China. linzhongxu@mail.hzau.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCotton (Gossypium spp.), as the world's most utilized textile fibre source, is an important, economically valuable crop worldwide. Understanding the genomic variation of tetraploid cotton species is important for exploitation of the excellent characteristics of wild cotton and for improving the diversity of cotton in breeding. However, the discovery of DNA polymorphisms in tetraploid cotton genomes has lagged behind other important crops.

resultsA total of 111,795,823 reads, 467,735 specific length amplified fragment (SLAF) tags and 139,176 high-quality DNA polymorphisms were identified using specific length amplified fragment sequencing (SLAF-seq), including 132,880 SNPs and 6,296 InDels between the reference genome (TM-1) and the five tetraploid cotton species. Intriguingly, gene ontology (GO) enrichment analysis revealed that a number of significant terms were related to reproduction in G. barbadense acc. 3-79. Based on the new data sets, we reconstructed phylogenetic trees that showed a high concordance to the phylogeny of diploid and polyploid cottons. A large amount of interspecific genetic variations were identified, and some of them were validated by the single-strand conformation polymorphism (SSCP) method, which will be applied in introgression genetics and breeding with G. hirsutum cv. Emian22 as the receptor and the other species as donors.

conclusionsUsing SLAF-seq, a large number of DNA polymorphisms were identified. The comprehensive analysis of DNA polymorphisms provided invaluable insights into the different tetraploid cotton species. More importantly, the identification of numerous interspecific genetic variations provides the basis and is very practical for future introgression breeding. The results presented herein provide a valuable genomic resource for new insights into the genetics and breeding of cotton.

Indexed as

INDEL MutationNucleic Acid Amplification TechniquesPolymorphism, Single NucleotideSequence Analysis, DNATetraploidyBreedingGossypiumPhylogenyInsertions/deletionsPhylogenySingle-nucleotide polymorphismsSLAF-seqTetraploid cotton

Identifiers

PMID28330454
PMCPMC5363057

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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.