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Distinct Retrotransposon Evolution Profile in the Genome of Rabbit (Oryctolagus cuniculus).

Naisu YangBohao ZhaoYang ChenEnrico D'AlessandroCai ChenTing JiXinsheng WuChengyi Song
Published in: Genome biology and evolution (2022)
Although the rabbit genome has already been annotated, it is mobilome remains largely unknown. Here, multiple pipelines were used to de novo mine and annotate the mobilome in rabbit. Four families and 19 subfamilies of LINE1s, two families and nine subfamilies of SINEs, and 12 ERV families were defined in rabbit based on sequence identity, structural organization, and phylogenetic tree. The analysis of insertion age and polymerase chain reaction suggests that a number of families are very young and may remain active, such as L1B, L1D, OcuSINEA, and OcuERV1. RepeatMasker annotation revealed a distinct transposable element landscape within the genome, with approximately two million copies of SINEs, representing the greatest proportion of the genome (19.61%), followed by LINEs (15.44%), and LTRs (4.11%), respectively, considerably different from most other mammal mobilomes except hedgehog and tree shrew, in which LINEs have the highest proportion. Furthermore, a very high rate of insertion polymorphisms (>85%) for the youngest subfamily (OcuSINEA1) was identified by polymerase chain reaction. The majority of retrotransposon insertions overlapped with protein-coding regions (>80%) and lncRNA (90%) genes. Genomic distribution bias was observed for retrotransposons, with those immediately upstream (-1 kb) and downstream (1 kb) of genes significantly depleted. Local GC content in 50-kb widows had significantly negative correlations with LINE (rs=-0.996) and LTR (rs=-0.829) insertions. The current study revealed a distinct mobilome landscape in rabbit, which will assist in the elucidation of the evolution of the genome of lagomorphs, and even other mammals.
Keyphrases
  • genome wide
  • single cell
  • dna methylation
  • gene expression
  • long non coding rna
  • genome wide identification
  • transcription factor
  • bioinformatics analysis