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Alopecia areata is a complex genetic disease that results in hair loss due to the autoimmune-mediated attack of the hair follicle. We previously defined a role for both rare and common variants in our earlier GWAS and linkage studies. Here, we identify rare variants contributing to Alopecia Areata using a whole exome sequencing and gene-level burden analyses approach on 849 Alopecia Areata patients compared to 15,640 controls. KRT82 is identified as an Alopecia Areata risk gene with rare damaging variants in 51 heterozygous Alopecia Areata individuals (6.01%), achieving genome-wide significance ( p  = 2.18E−07). KRT82 encodes a hair-specific type II keratin that is exclusively expressed in the hair shaft cuticle during anagen phase, and its expression is decreased in Alopecia Areata patient skin and hair follicles. Finally, we find that cases with an identified damaging KRT82 variant and reduced KRT82 expression have elevated perifollicular CD8 infiltrates. In this work, we utilize whole exome sequencing to successfully identify a significant Alopecia Areata disease-relevant gene, KRT82 , and reveal a proposed mechanism for rare variant predisposition leading to disrupted hair shaft integrity. Common variants have been discovered to be associated with Alopecia Areata; however, rare variants have been less well studied. Here, the authors use whole-exome sequencing to identify associated rare variants in the hair keratin gene KRT82 . Further, they find that individuals with Alopecia Areata have reduced expression of KRT82 in the skin and hair follicle.

Human airways contain specialized rare epithelial cells including CFTR-rich ionocytes that regulate airway surface physiology and chemosensory tuft cells that produce asthma-associated inflammatory mediators. Here, using a lung cell atlas of 311,748 single cell RNA-Seq profiles, we identify 687 ionocytes (0.45%). In contrast to prior reports claiming a lack of ionocytes in the small airways, we demonstrate that ionocytes are present in small and large airways in similar proportions. Surprisingly, we find only 3 mature tuft cells (0.002%), and demonstrate that previously annotated tuft-like cells are instead highly replicative progenitor cells. These tuft-ionocyte progenitor (TIP) cells produce ionocytes as a default lineage. However, Type 2 and Type 17 cytokines divert TIP cell lineage in vitro, resulting in the production of mature tuft cells at the expense of ionocyte differentiation. Our dataset thus provides an updated understanding of airway rare cell composition, and further suggests that clinically relevant cytokines may skew the composition of disease-relevant rare cells. Human airway contains physiologically relevant yet rare cells, but their scarcity prevents thorough profiling and differentiation studies. Here the authors use single cell RNA sequencing to identify rare ionocytes and tuft cells, as well as a potential progenitor population with cytokine-guided differentiation into either the ionocytes or tuft cell lineage.

Allele-specific siRNAs (ASP-siRNAs) have emerged as promising therapeutic molecules owing to their selectivity to inhibit the mutant allele or associated single-nucleotide polymorphisms (SNPs) sparing the expression of the wild-type counterpart. Thus, a dedicated bioinformatics platform encompassing updated ASP-siRNAs and an algorithm for the prediction of their inhibitory efficacy will be helpful in tackling currently intractable genetic disorders. In the present study, we have developed the ASPsiRNA resource (http://crdd.osdd.net/servers/aspsirna/) covering three components viz (i) ASPsiDb, (ii) ASPsiPred, and (iii) analysis tools like ASP-siOffTar. ASPsiDb is a manually curated database harboring 4543 (including 422 chemically modified) ASP-siRNAs targeting 78 unique genes involved in 51 different diseases. It furnishes comprehensive information from experimental studies on ASP-siRNAs along with multidimensional genetic and clinical information for numerous mutations. ASPsiPred is a two-layered algorithm to predict efficacy of ASP-siRNAs for fully complementary mutant (Effmut) and wild-type allele (Effwild) with one mismatch by ASPsiPredSVM and ASPsiPredmatrix, respectively. In ASPsiPredSVM, 922 unique ASP-siRNAs with experimentally validated quantitative Effmut were used. During 10-fold cross-validation (10nCV) employing various sequence features on the training/testing dataset (T737), the best predictive model achieved a maximum Pearson’s correlation coefficient (PCC) of 0.71. Further, the accuracy of the classifier to predict Effmut against novel genes was assessed by leave one target out cross-validation approach (LOTOCV). ASPsiPredmatrix was constructed from rule-based studies describing the effect of single siRNA:mRNA mismatches on the efficacy at 19 different locations of siRNA. Thus, ASPsiRNA encompasses the first database, prediction algorithm, and off-target analysis tool that is expected to accelerate research in the field of RNAi-based therapeutics for human genetic diseases.

Significant innovations in next-generation sequencing techniques and bioinformatics tools have impacted our appreciation and understanding of RNA. Practical RNASeq applications have evolved in conjunction with sequence technology and bioinformatic tool advances. In this review, we explained various computational resources, tools, and bioinformatics analyses advancement for small and large non-coding RNAs. These include non-coding RNAs (ncRNAs) such as piwi, micro, circular, and long ncRNAs. In addition, this article discusses future challenges, single-cell level sequencing for non-coding RNAs, and advantages of using long-read sequencing to annotate lncRNAs.

Expressed on epidermal Langerhans cells, CD1a presents a range of self-lipid antigens found within the skin; however, the extent to which CD1a presents microbial ligands from bacteria colonizing the skin is unclear. Here we identified CD1a-dependent T cell responses to phosphatidylglycerol (PG), a ubiquitous bacterial membrane phospholipid, as well as to lysylPG, a modified PG, present in several Gram-positive bacteria and highly abundant in Staphylococcus aureus . The crystal structure of the CD1a–PG complex showed that the acyl chains were buried within the A′- and F′-pockets of CD1a, while the phosphoglycerol headgroup remained solvent exposed in the F′-portal and was available for T cell receptor contact. Using lysylPG and PG-loaded CD1a tetramers, we identified T cells in peripheral blood and in skin that respond to these lipids in a dose-dependent manner. Tetramer + CD4 +  T cell lines secreted type 2 helper T cell cytokines in response to phosphatidylglycerols as well as to co-cultures of CD1a +  dendritic cells and Staphylococcus bacteria. The expansion in patients with atopic dermatitis of CD4 + CD1a–(lysyl)PG tetramer + T cells suggests a response to lipids made by bacteria associated with atopic dermatitis and provides a link supporting involvement of PG-based lipid-activated T cells in atopic dermatitis pathogenesis. De Jong and colleagues identify staphylococcal phosphatidylglycerol lipids as antigens for human CD1a-restricted T cells, which promote type 2 immune responses and may contribute to atopic dermatitis.

Current Zika virus (ZIKV) outbreaks that spread in several areas of Africa, Southeast Asia, and in pacific islands is declared as a global health emergency by World Health Organization (WHO). It causes Zika fever and illness ranging from severe autoimmune to neurological complications in humans. To facilitate research on this virus, we have developed an integrative multi-omics platform; ZikaVR ( http://bioinfo.imtech.res.in/manojk/zikavr/ ), dedicated to the ZIKV genomic, proteomic and therapeutic knowledge. It comprises of whole genome sequences, their respective functional information regarding proteins, genes, and structural content. Additionally, it also delivers sophisticated analysis such as whole-genome alignments, conservation and variation, CpG islands, codon context, usage bias and phylogenetic inferences at whole genome and proteome level with user-friendly visual environment. Further, glycosylation sites and molecular diagnostic primers were also analyzed. Most importantly, we also proposed potential therapeutically imperative constituents namely vaccine epitopes, siRNAs, miRNAs, sgRNAs and repurposing drug candidates.

The primary forms of cicatricial (scarring) alopecia (PCA) are a group of inflammatory, irreversible hair loss disorders characterized by immune cell infiltrates targeting hair follicles (HFs). Lichen planopilaris (LPP), frontal fibrosing alopecia (FFA), and centrifugal cicatricial alopecia (CCCA) are among the main subtypes of PCAs. The pathogenesis of the different types of PCAs are poorly understood, and current treatment regimens yield inconsistent and unsatisfactory results. We performed high-throughput RNA-sequencing on scalp biopsies of a large cohort PCA patients to develop gene expression-based signatures, trained into machine-learning-based predictive models and pathways associated with dysregulated gene expression. We performed morphological and cytokine analysis to define the immune cell populations found in PCA subtypes. We identified a common PCA gene signature that was shared between LPP, FFA, and CCCA, which revealed a significant over-representation of mast cell (MC) genes, as well as downregulation of cholesterogenic pathways and upregulation of fibrosis and immune signaling genes. Immunohistological analyses revealed an increased presence of MCs in PCAs lesions. Our gene expression analyses revealed common pathways associated with PCAs, with a strong association with MCs. The indistinguishable differences in gene expression profiles and immune cell signatures between LPP, FFA, and CCCA suggest that similar treatment regimens may be effective in treating these irreversible forms of hair loss.

Glioblastoma (GBM) is the most common and deadly primary brain cancer, with limited therapeutic options. Treatment failure has been associated with intratumoral heterogeneity and the acquisition of a pronounced mesenchymal-like (MES-L) phenotype after recurrence. Here, we have screened a panel of drugs with diverse mechanisms of action across two patient-derived glioblastoma stem cells (GSCs) to characterize the dynamics of drug-mediated transcriptomic cellular state changes. Our results demonstrate that anti-tumor drugs induce significant but reversible alterations in cellular state distribution at the single-cell level in a drug-specific manner, influencing transitions between mesenchymal and the neurodevelopmental astrocytic-like (AC-L) states. Utilizing barcoded analysis in our recently developed ex vivo glioblastoma cerebral organoid (GLICO) model, we discerned distinct cell state sensitivities to the MES-L enhancing histone deacetylase inhibitor, panobinostat, which are contingent on the inducible modulation of the mesenchymal transcription factor FOSL1. The strategic combination of MES-L enhancing and MES-l suppressing genetic perturbations or drugs significantly increases anti-glioma activity in a strategy we call state-selective lethality. Overall, our findings highlight the critical role of cell state plasticity in the response of GSCs to anti-tumor therapeutic stress and underscore the potential for novel GBM combination drug strategies.

The human airway contains specialized rare epithelial cells whose roles in respiratory disease are not well understood. Ionocytes express the Cystic Fibrosis Transmembrane Conductance Regulator (CFTR), while chemosensory tuft cells express asthma-associated alarmins. However, surprisingly, exceedingly few mature tuft cells have been identified in human lung cell atlases despite the ready identification of rare ionocytes and neuroendocrine cells. To identify human rare cell progenitors and define their lineage relationship to mature tuft cells, we generated a deep lung cell atlas containing 311,748 single cell RNA-Seq (scRNA-seq) profiles from discrete anatomic sites along the large and small airways and lung lobes of explanted donor lungs that could not be used for organ transplantation. Of 154,222 airway epithelial cells, we identified 687 ionocytes (0.45%) that are present in similar proportions in both large and small airways, suggesting that they may contribute to both large and small airways pathologies in CF. In stark contrast, we recovered only 3 mature tuft cells (0.002%). Instead, we identified rare bipotent progenitor cells that can give rise to both ionocytes and tuft cells, which we termed tuft-ionocyte progenitor cells (TIP cells). Remarkably, the cycling fraction of these TIP cells was comparable to that of basal stem cells. We used scRNA-seq and scATAC-seq to predict transcription factors that mark this novel rare cell progenitor population and define intermediate states during TIP cell lineage transitions en route to the differentiation of mature ionocytes and tuft cells. The default lineage of TIP cell descendants is skewed towards ionocytes, explaining the paucity of mature tuft cells in the human airway. However, Type 2 and Type 17 cytokines, associated with asthma and CF, diverted the lineage of TIP cell descendants in vitro, resulting in the differentiation of mature tuft cells at the expense of ionocytes. Consistent with this model of mature tuft cell differentiation, we identify mature tuft cells in a patient who died from an asthma flare. Overall, our findings suggest that the immune signaling pathways active in asthma and CF may skew the composition of disease-relevant rare cells and illustrate how deep atlases are required for identifying physiologically-relevant scarce cell populations.Competing Interest StatementA.R. is a founder and equity holder of Celsius Therapeutics, an equity holder in Immunitas Therapeutics, and until August 31, 2020, was a SAB member of Syros Pharmaceuticals, Neogene Therapeutics, Asimov and Thermo Fisher Scientific. From August 1, 2020, A.R. has been an employee of Genentech and has equity in Roche.