The Chinese forest musk deer (Moschus berezovskii Flerov) is an endangered artiodactyl mammal. The musk secreted by sexually mature males is highly valued for alleged pharmaceutical properties and perfume manufacturing. However, the genomic and transcriptomic resources of musk deer remain deficiently represented and poorly understood. Next-generation sequencing technique is an efficient method for generating an enormous amount of sequence data that can represent a large number of genes and their expression levels. In the present study, we used Illumina HiSeq technology to perform de novo assembly of heart and musk gland transcriptomes from the Chinese forest musk deer. A total of 239,383 transcripts and 176,450 unigenes were obtained, of which 37,329 unigenes were matched to known sequences in the NCBI nonredundant protein (Nr) database; 31,039 unigenes were assigned to 61 GO terms, and 11,782 to 332 KEGG pathways. Additionally, 592 and 2282 differentially expressed genes were found to be specifically expressed in the heart and musk gland, respectively. The abundant transcriptomic data generated in the present report will provide a comprehensive sequence resource for Chinese forest musk deer as well as lay down a foundation which will help in accelerating genetic and functional genomics research in this species.

Research of epithelial cells in musk gland is lacking. There are no good characterized epithelial cell lines that can provide complementary in vitro models for in vivo research. We successfully cultivated epithelial cells of musk gland for the first time. The protocol described here produces epithelial cell lines from the mature secreting musk gland. Based on morphological observation, epithelial cells of musk gland were isolated and cultured in vitro. After the third passage, the musk gland-derived cells were filled with many lipid droplets and proliferated well. We used gas chromatography and mass spectrometry to explore the chemical composition of lipid droplets in the musk gland-derived cells. The main components of secreted lipid droplet were alkanes, esters, amines, alcohols, ketones, organic acids, and aldehydes. Muscone, which is the main active compound of musk, was not found. This is a new attempt in the field of animal musk to obtain naturally secreted animal musk in vitro by cloning specialized cells. In conclusion, this study provides a reference at the cellular level to further analyze the biology and physiology of the musk gland epithelium and secretion mechanism of musk deer.

Musk secretion in male musk deer is regarded as a propitious mode of sexual election to attract a greater number of females. However, the genetic mechanisms of musk secretion are still poorly understood and unresolved making it necessary to elucidate the possible genetic mechanisms of musk formation. In the present study, we used heart and musk gland tissues from a male musk deer for next-generation mRNA sequencing, integrated with de novo assembly, unigenes annotation and differentially expressed genes analysis. A total of 239,383 transcripts and 208,730 unigenes were obtained from 2 pooled RNA samples. Annotated analysis indicated steroid compound metabolism (steroid biosynthesis, steroid hormone biosynthesis, aldosterone-regulated sodium reabsorption, terpenoid backbone biosynthesis) related to musk formation were annotated to many pathways; relevant genes were identified as well. In addition, 8,986 differentially expressed genes (6,068 up- and 2,198 down-regulated) between heart and musk gland were identified, among them, steroid component metabolism were abundant. Further exploration of functional enrichment analysis showed that pathways involved in musk secretion were up-regulated in musk gland compared with heart, especially steroid biosynthesis and terpenoid backbone biosynthesis whose metabolic productions were key components of musk. We identified several candidate genes such as DHCR7, DHCR24, NSDHL, CYP3A5, FDFT1, FDPS and HMGCL which were closely involved in metabolism of steroid, terpenoid and ketone bodies. Our data are expected to represent the most comprehensive sequence resource available for the forest musk deer so far, and provide a basis for further research on molecular genetics and functional genomics of musk secretion.

Background: Ferroptosis is a newly identified regulated cell death characterized by iron-dependent lipid peroxidation and subsequent membrane oxidative damage, which has been implicated in multiple types of cancers. The multi-omics differences between cancer cell lines with high/low ferroptosis scores remain to be elucidated.Methods and Materials: We used RNA-seq gene expression, gene mutation, miRNA expression, metabolites, copy number variation, and drug sensitivity data of cancer cell lines from DEPMAP to detect multi-omics differences associated with ferroptosis. Based on the gene expression data of cancer cell lines, we performed LASSO-Logistic regression analysis to build a ferroptosis-related model. Lung adenocarcinoma (LUAD), lung squamous cell carcinoma (LUSC), esophageal cancer (ESCA), bladder cancer (BLCA), cervical cancer (CESC), and head and neck cancer (HNSC) patients from the TCGA database were used as validation cohorts to test the efficacy of this model.Results: After stratifying the cancer cell lines into high score (HS) and low score (LS) groups according to the median of ferroptosis scores generated by gene set variation analysis, we found that IC50 of 66 agents such as oxaliplatin (p < 0.001) were significantly different, among which 65 were higher in the HS group. 851 genes such as KEAP1 and NRAS were differentially muted between the two groups. Differentially expressed genes, miRNAs and metabolites were also detected—multiple items such as IL17F (logFC = 6.58, p < 0.001) differed between the two groups. Unlike the TCGA data generated by bulk RNA-seq, the gene expression data in DEPMAP are from pure cancer cells, so it could better reflect the traits of tumors in cancer patients. Thus, we built a 15-signature model (AUC = 0.878) based on the gene expression data of cancer cell lines. The validation cohorts demonstrated a higher mutational rate of NFE2L2 and higher expression levels of 12 ferroptosis-related genes in HS groups.Conclusion: This article systemically analyzed multi-omics differences between cancer cell lines with high/low ferroptosis scores and a ferroptosis-related model was developed for multiple cancer types. Our findings could improve our understanding of the role of ferroptosis in cancer and provide new insight into treatment for malignant tumors.