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Insight into the Organization of the B10v3 Cucumber Genome by Integration of Biological and Bioinformatic Data.

Szymon TurekWojciech PląderYoshikazu HoshiAgnieszka SkarzyńskaMagdalena Ewa Pawełkowicz
Published in: International journal of molecular sciences (2023)
The availability of a well-organized and annotated reference genome is essential for genome research and the analysis of re-sequencing approaches. The B10v3 cucumber ( Cucumis sativus L.) reference genome has been sequenced and assembled into 8035 contigs, a small fraction of which have been mapped to individual chromosomes. Currently, bioinformatics methods based on comparative homology have made it possible to re-order the sequenced contigs by mapping them to the reference genomes. The B10v3 genome (North-European, Borszczagowski line) was rearranged against the genomes of cucumber 9930 ('Chinese Long' line) and Gy14 (North American line). Furthermore, a better insight into the organization of the B10v3 genome was obtained by integrating the data available in the literature on the assignment of contigs to chromosomes in the B10v3 genome with the results of the bioinformatic analysis. The combination of information on the markers used in the assembly of the B10v3 genome and the results of FISH and DArT-seq experiments confirmed the reliability of the in silico assignment. Approximately 98% of the protein-coding genes within the chromosomes were assigned and a significant proportion of the repetitive fragments in the sequenced B10v3 genome were identified using the RagTag programme. In addition, BLAST analyses provided comparative information between the B10v3 genome and the 9930 and Gy14 data sets. This revealed both similarities and differences in the functional proteins found between the coding sequences region in the genomes. This study contributes to better knowledge and understanding of cucumber genome line B10v3.
Keyphrases
  • genome wide
  • electronic health record
  • systematic review
  • healthcare
  • big data
  • machine learning
  • transcription factor
  • high frequency
  • artificial intelligence
  • amino acid
  • protein protein