4.5 Article

A high-quality cucumber genome assembly enhances computational comparative genomics

期刊

MOLECULAR GENETICS AND GENOMICS
卷 295, 期 1, 页码 177-193

出版社

SPRINGER HEIDELBERG
DOI: 10.1007/s00438-019-01614-3

关键词

Genome assembly; Variant calling; Comparative genomics; Polymorphism detection; Cucumber; Cucumis sativus L

资金

  1. National Science Center [2013/11/B/NZ9/00814, 2011/01/B/NZ2/01631]

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Genetic variation is expressed by the presence of polymorphisms in compared genomes of individuals that can be transferred to next generations. The aim of this work was to reveal genome dynamics by predicting polymorphisms among the genomes of three individuals of the highly inbred B10 cucumber (Cucumis sativus L.) line. In this study, bioinformatic comparative genomics was used to uncover cucumber genome dynamics (also called real-time evolution). We obtained a new genome draft assembly from long single molecule real-time (SMRT) sequencing reads and used short paired-end read data from three individuals to analyse the polymorphisms. Using this approach, we uncovered differentiation aspects in the genomes of the inbred B10 line. The newly assembled genome sequence (B10v3) has the highest contiguity and quality characteristics among the currently available cucumber genome draft sequences. Standard and newly designed approaches were used to predict single nucleotide and structural variants that were unique among the three individual genomes. Some of the variant predictions spanned protein-coding genes and their promoters, and some were in the neighbourhood of annotated interspersed repetitive elements, indicating that the highly inbred homozygous plants remained genetically dynamic. This is the first bioinformatic comparative genomics study of a single highly inbred plant line. For this project, we developed a polymorphism prediction method with optimized precision parameters, which allowed the effective detection of small nucleotide variants (SNVs). This methodology could significantly improve bioinformatic pipelines for comparative genomics and thus has great practical potential in genomic metadata handling.

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