Whole-Genome Sequencing of Chinese Yellow Catfish Provides a Valuable Genetic Resource for High-Throughput Identification of Toxin Genes.
Shiyong ZhangJia LiQin QinWei LiuChao BianYunhai YiMinghua WangLiqiang ZhongXinxin YouShengkai TangYanshan LiuYu HuangRuobo GuJunmin XuWenji BianQiong ShiXiaohui ChenPublished in: Toxins (2018)
Naturally derived toxins from animals are good raw materials for drug development. As a representative venomous teleost, Chinese yellow catfish (Pelteobagrus fulvidraco) can provide valuable resources for studies on toxin genes. Its venom glands are located in the pectoral and dorsal fins. Although with such interesting biologic traits and great value in economy, Chinese yellow catfish is still lacking a sequenced genome. Here, we report a high-quality genome assembly of Chinese yellow catfish using a combination of next-generation Illumina and third-generation PacBio sequencing platforms. The final assembly reached 714 Mb, with a contig N50 of 970 kb and a scaffold N50 of 3.65 Mb, respectively. We also annotated 21,562 protein-coding genes, in which 97.59% were assigned at least one functional annotation. Based on the genome sequence, we analyzed toxin genes in Chinese yellow catfish. Finally, we identified 207 toxin genes and classified them into three major groups. Interestingly, we also expanded a previously reported sex-related region (to ≈6 Mb) in the achieved genome assembly, and localized two important toxin genes within this region. In summary, we assembled a high-quality genome of Chinese yellow catfish and performed high-throughput identification of toxin genes from a genomic view. Therefore, the limited number of toxin sequences in public databases will be remarkably improved once we integrate multi-omics data from more and more sequenced species.
Keyphrases
- genome wide
- escherichia coli
- bioinformatics analysis
- high throughput
- dna methylation
- genome wide identification
- copy number
- single cell
- rheumatoid arthritis
- healthcare
- genome wide analysis
- mental health
- cross sectional
- big data
- transcription factor
- machine learning
- spinal cord injury
- gene expression
- artificial intelligence