Data set for the genome-wide transcriptome analysis of human epidermal melanocytes

Single-cell profiling of MC1R-inhibited melanocytes

The human red hair color (RHC) trait is caused by increased pheomelanin (red-yellow) and reduced eumelanin (black-brown) pigment in skin and hair due to diminished melanocortin 1 receptor (MC1R) function. In addition, individuals harboring the RHC trait are predisposed to melanoma development. While MC1R variants have been established as causative of RHC and are a well-defined risk factor for melanoma, it remains unclear mechanistically why decreased MC1R signaling alters pigmentation and increases melanoma susceptibility. Here, we use single-cell RNA sequencing (scRNA-seq) of melanocytes isolated from RHC mouse models to define a MC1R-inhibited Gene Signature (MiGS) comprising a large set of previously unidentified genes which may be implicated in melanogenesis and oncogenic transformation. We show that one of the candidate MiGS genes, TBX3, a well-known anti-senescence transcription factor implicated in melanoma progression, binds both E-box and T-box elements to regulate genes associated with melanogenesis and senescence bypass. Our results provide key insights into further mechanisms by which melanocytes with reduced MC1R signaling may regulate pigmentation and offer new candidates of study toward understanding how individuals with the RHC phenotype are predisposed to melanoma.

High temperature influences DNA methylation and transcriptional profiles in sea urchins (Strongylocentrotus intermedius)

BACKGROUND

DNA methylation plays an important role in life processes by affecting gene expression, but it is still unclear how DNA methylation is controlled and how it regulates gene transcription under high temperature stress conditions in Strongylocentrotus intermedius. The potential link between DNA methylation variation and gene expression changes in response to heat stress in S. intermedius was investigated by MethylRAD-seq and RNA-seq analysis. We screened DNA methylation driver genes in order to comprehensively elucidate the regulatory mechanism of its high temperature adaptation at the DNA/RNA level.

RESULTS

The results revealed that high temperature stress significantly affected not only the DNA methylation and transcriptome levels of S. intermedius (P < 0.05), but also growth. MethylRAD-seq analysis revealed 12,129 CG differential methylation sites and 966 CWG differential methylation sites, and identified a total of 189 differentially CG methylated genes and 148 differentially CWG methylated genes. Based on KEGG enrichment analysis, differentially expressed genes (DEGs) are mostly enriched in energy and cell division, immune, and neurological damage pathways. Further RNA-seq analysis identified a total of 1968 DEGs, of which 813 genes were upregulated and 1155 genes were downregulated. Based on the joint MethylRAD-seq and RNA-seq analysis, metabolic processes such as glycosaminoglycan degradation, oxidative phosphorylation, apoptosis, glutathione metabolism, thermogenesis, and lysosomes are regulated by DNA methylation.

CONCLUSIONS

High temperature affected the DNA methylation and expression levels of genes such as MOAP-1, GGT1 and RDH8, which in turn affects the metabolism of HPSE, Cox, glutathione, and retinol, thereby suppressing the immune, energy metabolism, and antioxidant functions of the organism and finally manifesting as stunted growth. In summary, the observations in the present study improve our understanding of the molecular mechanism of the response to high temperature stress in sea urchin.

Analysis of the gene transcription patterns and DNA methylation characteristics of triploid sea cucumbers (Apostichopus japonicus)

Breeding of polyploid aquatic animals is still an important approach and research hotspot for realizing the economic benefits afforded by the improvement of aquatic animal germplasm. To better understand the molecular mechanisms of the growth of triploid sea cucumbers, we performed gene expression and genome-wide comparisons of DNA methylation using the body wall tissue of triploid sea cucumbers using RNA-seq and MethylRAD-seq technologies. We clarified the expression pattern of triploid sea cucumbers and found no dosage effect. DEGs were significantly enriched in the pathways of nucleic acid and protein synthesis, cell growth, cell division, and other pathways. Moreover, we characterized the methylation pattern changes and found 615 differentially methylated genes at CCGG sites and 447 differentially methylated genes at CCWGG sites. Integrative analysis identified 23 genes (such as Guf1, SGT, Col5a1, HAL, HPS1, etc.) that exhibited correlations between promoter methylation and expression. Altered DNA methylation and expression of various genes suggested their roles and potential functional interactions in the growth of triploid sea cucumbers. Our data provide new insights into the epigenetic and transcriptomic alterations of the body wall tissue of triploid sea cucumbers and preliminarily elucidate the molecular mechanism of their growth, which is of great significance for the breeding of fine varieties of sea cucumbers.

BayesPI-BAR2: A New Python Package for Predicting Functional Non-coding Mutations in Cancer Patient Cohorts

Most of somatic mutations in cancer occur outside of gene coding regions. These mutations may disrupt the gene regulation by affecting protein-DNA interaction. A study of these disruptions is important in understanding tumorigenesis. However, current computational tools process DNA sequence variants individually, when predicting the effect on protein-DNA binding. Thus, it is a daunting task to identify functional regulatory disturbances among thousands of mutations in a patient. Previously, we have reported and validated a pipeline for identifying functional non-coding somatic mutations in cancer patient cohorts, by integrating diverse information such as gene expression, spatial distribution of the mutations, and a biophysical model for estimating protein binding affinity. Here, we present a new user-friendly Python package BayesPI-BAR2 based on the proposed pipeline for integrative whole-genome sequence analysis. This may be the first prediction package that considers information from both multiple mutations and multiple patients. It is evaluated in follicular lymphoma and skin cancer patients, by focusing on sequence variants in gene promoter regions. BayesPI-BAR2 is a useful tool for predicting functional non-coding mutations in whole genome sequencing data: it allows identification of novel transcription factors (TFs) whose binding is altered by non-coding mutations in cancer. BayesPI-BAR2 program can analyze multiple datasets of genome-wide mutations at once and generate concise, easily interpretable reports for potentially affected gene regulatory sites. The package is freely available at http://folk.uio.no/junbaiw/BayesPI-BAR2/.

Data set for the genome-wide transcriptome analysis of human epidermal melanocytes

The data in this article contains data related to the research articled entitle Genome-wide transcriptome analysis of human epidermal melanocytes. This data article contains a complete list of gene and transcript isoform expression in human epidermal melanocytes. Transcript isoforms that are differentially expressed in lightly versus darkly pigmented melanocytes are identified. We also provide data showing the gene expression profiles of cell signaling gene families (receptors, ion channels, and transcription factors) in melanocytes. The raw sequencing data used to perform this transcriptome analysis is located in the NCBI Sequence Read Archive under Accession No. SRP039354 http://dx.doi.org/10.7301/Z0MW2F2N.