Comparative transcriptomics reveals specific responding genes associated with atherosclerosis in rabbit and mouse models

A single workflow for multi-species blood transcriptomics

BACKGROUND

Blood transcriptomic analysis is widely used to provide a detailed picture of a physiological state with potential outcomes for applications in diagnostics and monitoring of the immune response to vaccines. However, multi-species transcriptomic analysis is still a challenge from a technological point of view and a standardized workflow is urgently needed to allow interspecies comparisons.

RESULTS

Here, we propose a single and complete total RNA-Seq workflow to generate reliable transcriptomic data from blood samples from humans and from animals typically used in preclinical models. Blood samples from a maximum of six individuals and four different species (rabbit, non-human primate, mouse and human) were extracted and sequenced in triplicates. The workflow was evaluated using different wet-lab and dry-lab criteria, including RNA quality and quantity, the library molarity, the number of raw sequencing reads, the Phred-score quality, the GC content, the performance of ribosomal-RNA and globin depletion, the presence of residual DNA, the strandness, the percentage of coding genes, the number of genes expressed, and the presence of saturation plateau in rarefaction curves. We identified key criteria and their associated thresholds to be achieved for validating the transcriptomic workflow. In this study, we also generated an automated analysis of the transcriptomic data that streamlines the validation of the dataset generated.

CONCLUSIONS

Our study has developed an end-to-end workflow that should improve the standardization and the inter-species comparison in blood transcriptomics studies. In the context of vaccines and drug development, RNA sequencing data from preclinical models can be directly compared with clinical data and used to identify potential biomarkers of value to monitor safety and efficacy.

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

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.