Principal component values of all 14 individuals according to the expression levels of all genes (FPKM) obtained in the reference-based method.

Principal component values of all 14 individuals according to the expression levels of all genes (FPKM) obtained in the reference-based method.</p

Temporal dynamics of the bat wing transcriptome: Insight into gene-expression changes that enable protection against pathogen

Skin acts as a mechanical barrier between the body and its surrounding environment and plays an important role in resistance to pathogens. However, we still know little regarding skin responses to physiological changes, particularly with regard to responses against potential pathogens. We herein executed RNA-seq on the wing of the Rhinolophus ferrumequinum to assess gene-expression variations at four physiological stages: pre-hibernation, hibernation (early-hibernation and late-hibernation), and post-hibernation, as well as the gene-expression patterns of infected and uninfected bats with the Pseudogymnoascus destructans (Pd). Our results showed that a greater number of differentially expressed genes between the more disparate physiological stages. Functional enrichment analysis showed that the down-regulated response pathways in hibernating bats included phosphorus metabolism and immune response, indicating metabolic suppression and decreased whole immune function. We also found up-regulated genes in post-hibernating bats that included C-type lectin receptor signalling, Toll-like receptor signalling pathway, and cell adhesion, suggesting that the immune response and skin integrity of the wing were improved after bats emerged from their hibernation and that this facilitated clearing Pd from the integument. Additionally, we found that the genes involved in cytokine or chemokine activity were up-regulated in late-hibernation compared to early-hibernation and that FOSB regulation of immune cell activation was differentially expressed in bats infected with Pd during late-hibernation, implying that the host’s innate immune function was enhanced during late-hibernation so as to resist pathogenic infection. Our findings highlight the concept that maintenance of intrinsic immunity provides protection against pathogenic infections in highly resistant bats.</p

Clustering results of the remaining samples excluding outliers based on genes obtained by the two methods.

(a) Expression heatmap clustering based on all differentially expressed genes (DEGs) obtained by pairwise comparisons (HN vs. JL, HN vs. YN, and YN vs. JL) in the reference-based method. (b) Expression heatmap clustering based on all DEGs in the reference-free method. Gene expression levels are depicted as standardized (log2-FPKM+1).</p

GSEA ranked gene list for HN vs. JL.

Differences in gene expression within tissues can lead to differences in tissue function. Understanding the transcriptome of a species helps elucidate the molecular mechanisms underlying phenotypic divergence. According to the presence or absence of a reference genome of for a studied species, transcriptome analyses can be divided into reference‑based and reference‑free methods, respectively. Presently, comparisons of complete transcriptome analysis results between those two methods are still rare. In this study, we compared the cochlear transcriptome analysis results of greater horseshoe bats (Rhinolophus ferrumequinum) from three lineages in China with different acoustic phenotypes using reference‑based and reference‑free methods to explore their differences in subsequent analysis. The results gained by reference-based results had lower false-positive rates and were more accurate because differentially expressed genes among the three populations obtained by this method had greater reliability and a higher annotation rate. Some phenotype-related enrichment terms, including those related to inorganic molecules and proton transmembrane channels, were also obtained only by the reference-based method. However, the reference‑based method might have the limitation of incomplete information acquisition. Thus, we believe that a combination of reference‑free and reference‑based methods is ideal for transcriptome analyses. The results of our study provided a reference for the selection of transcriptome analysis methods in the future.</div

Principal component values of 11 individuals excluding the three outlier samples according to the expression levels of all genes (FPKM) obtained in the reference-based method.

Principal component values of 11 individuals excluding the three outlier samples according to the expression levels of all genes (FPKM) obtained in the reference-based method.</p

Mapping locations statistics of unigenes on the reference genome.

sseq_chrid represents the ID of chromosome which the unigenes were mapped to. ‘sstart’ and ‘send’ represent the locations of start and end bases on the mapped chromosome, respectively. ‘qstart’ and ‘qend’ represent the locations of start and end bases, respectively, of the unigenes mapped to the chromosome. (XLSX)</p

DEGs obtained by pairwise comparisons of the three populations in the reference-free method.

DEGs obtained by pairwise comparisons of the three populations in the reference-free method.</p

Complete results of the KEGG enrichment analysis for the merged gene set in modules significantly associated with RF by the reference-based method.

Complete results of the KEGG enrichment analysis for the merged gene set in modules significantly associated with RF by the reference-based method.</p

Complete results of the KEGG enrichment analysis for the genes shared by the two methods.

Complete results of the KEGG enrichment analysis for the genes shared by the two methods.</p

Gene details of 14 individuals obtained by the reference-based method.

Gene details of 14 individuals obtained by the reference-based method.</p