Androgenetic alopecia is a highly prevalent condition mainly affecting men. This complex trait is related to aging and genetics; however, multiple other factors, for example, lifestyle, are also involved. Despite its prevalence, the underlying biology of androgenetic alopecia remains elusive, and thus advances in its treatment have been hindered. Herein, we review the functional anatomy of hair follicles and the cell signaling events that play a role in follicle cycling. We also discuss the pathology of androgenetic alopecia and the known molecular mechanisms underlying this condition. Additionally, we describe studies comparing the transcriptional differences in hair follicles between balding and non-balding scalp regions. Given the genetic contribution, we also discuss the most significant risk variants found to be associated with androgenetic alopecia. A more comprehensive understanding of this pathology may be generated through using multi-omics approaches.

Background: Normalization is a critical step in the analysis of single-cell RNA-sequencing (scRNA-seq) datasets. Its main goal is to make gene counts comparable within and between cells. To do so, normalization methods must account for technical and biological variability. Numerous normalization methods have been developed addressing different sources of dispersion and making specific assumptions about the count data. Main body: The selection of a normalization method has a direct impact on downstream analysis, for example differential gene expression and cluster identification. Thus, the objective of this review is to guide the reader in making an informed decision on the most appropriate normalization method to use. To this aim, we first give an overview of the different single cell sequencing platforms and methods commonly used including isolation and library preparation protocols. Next, we discuss the inherent sources of variability of scRNA-seq datasets. We describe the categories of normalization methods and include examples of each. We also delineate imputation and batch-effect correction methods. Furthermore, we describe data-driven metrics commonly used to evaluate the performance of normalization methods. We also discuss common scRNA-seq methods and toolkits used for integrated data analysis. Conclusions: According to the correction performed, normalization methods can be broadly classified as within and between-sample algorithms. Moreover, with respect to the mathematical model used, normalization methods can further be classified into: global scaling methods, generalized linear models, mixed methods, and machine learning-based methods. Each of these methods depict pros and cons and make different statistical assumptions. However, there is no better performing normalization method. Instead, metrics such as silhouette width, K-nearest neighbor batch-effect test, or Highly Variable Genes are recommended to assess the performance of normalization methods.

Adipose-derived stem cells (ADSCs) are a heterogeneous cell population that may be enriched by positive selection with antibodies against the low-affinity nerve growth factor receptor (LNGFR or CD271), yielding a selective cell universe with higher proliferation and differentiation potential. This paper addresses the need for determining the quantity of ADSCs positive for the CD271 receptor and its correlation with donor's age. Mononuclear cells were harvested from the lower backs of 35 female donors and purified using magnetic beads. Multipotency capacity was tested by the expression of stemness genes and through differentiation into preosteoblasts and adipocytes. A significant statistical difference was found in CD271⁺concentrations between defined age intervals. The highest yield was found within women on the 30–40-year-old age range. CD271⁺ADSCs from all age groups showed differentiation capabilities as well as expression of typical multipotent stem cell genes. Our data suggest that the amount of CD271⁺cells correlates inversely with age. However, the ability to obtain these cells was maintained through all age ranges with a yield higher than what has been reported from bone marrow. Our findings propose CD271⁺ADSCs as the primary choice for tissue regeneration and autologous stem cell therapies in older subjects.

Chromatin architecture influences transcription by modulating the physical access of regulatory factors to DNA, playing fundamental roles in cell identity. Studies on dopaminergic differentiation have identified coding genes, but the relationship with non-coding genes or chromatin accessibility remains elusive. Using RNA-Seq and ATAC-Seq we profiled differentially expressed transcripts and open chromatin regions during early dopaminergic neuron differentiation. Hierarchical clustering of differentially expressed genes, resulted in 6 groups with unique characteristics. Surprisingly, the abundance of long non-coding RNAs (lncRNAs) was high in the most downregulated transcripts, and depicted positive correlations with target mRNAs. We observed that open chromatin regions decrease upon differentiation. Enrichment analyses of accessibility depict an association between open chromatin regions and specific functional pathways and gene-sets. A bioinformatic search for motifs allowed us to identify transcription factors and structural nuclear proteins that potentially regulate dopaminergic differentiation. Interestingly, we also found changes in protein and mRNA abundance of the CCCTC-binding factor, CTCF, which participates in genome organization and gene expression. Furthermore, assays demonstrated co-localization of CTCF with Polycomb-repressed chromatin marked by H3K27me3 in pluripotent cells, progressively decreasing in neural precursor cells and differentiated neurons. Our work provides a unique resource of transcription factors and regulatory elements, potentially involved in the acquisition of human dopaminergic neuron cell identity.

The blood-brain barrier (BBB), formed by specialized endothelial cells (ECs), regulates the extracellular composition of the central nervous system (CNS). Little is known about whether there are regional specializations of the BBB that may control the function of specific neural circuits. We use single cell RNA-seq to characterize ECs from nine CNS regions in male mice: cortex, hippocampus, cerebellum, spinal cord, striatum, thalamus, hypothalamus, midbrain, and medulla/pons. Although there is a core BBB transcriptional profile, there are significant regional specializations. Stra6, a retinoid transporter, is highly enriched in the BBB of the nucleus accumbens shell (ShNAc) and ventral cochlear nucleus, and is controlled by dietary vitamin A, through endothelial RARƔ. EC Stra6 regulates the deposition of retinoids specifically in the ShNAc and cochlear nucleus, and is required for the function of the ShNAc, in a retinoid-dependent manner. Thus regional specializations of the BBB can regulate the function of local brain regions.

Neural induction, both in vivo and in vitro, includes cellular and molecular changes that result in phenotypic specialization related to specific transcriptional patterns. These changes are achieved through the implementation of complex gene regulatory networks. Furthermore, these regulatory networks are influenced by epigenetic mechanisms that drive cell heterogeneity and cell-type specificity, in a controlled and complex manner. Epigenetic marks, such as DNA methylation and histone residue modifications, are highly dynamic and stage-specific during neurogenesis. Genome-wide assessment of these modifications has allowed the identification of distinct non-coding regulatory regions involved in neural cell differentiation, maturation, and plasticity. Enhancers are short DNA regulatory regions that bind transcription factors (TFs) and interact with gene promoters to increase transcriptional activity. They are of special interest in neuroscience because they are enriched in neurons and underlie the cell-type-specificity and dynamic gene expression profiles. Classification of the full epigenomic landscape of neural subtypes is important to better understand gene regulation in brain health and during diseases. Advances in novel next-generation high-throughput sequencing technologies, genome editing, Genome-wide association studies (GWAS), stem cell differentiation, and brain organoids are allowing researchers to study brain development and neurodegenerative diseases with an unprecedented resolution. Herein, we describe important epigenetic mechanisms related to neurogenesis in mammals. We focus on the potential roles of neural enhancers in neurogenesis, cell-fate commitment, and neuronal plasticity. We review recent findings on epigenetic regulatory mechanisms involved in neurogenesis and discuss how sequence variations within enhancers may be associated with genetic risk for neurological and psychiatric disorders.