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Abstract Using computational tools, bulk transcriptomics can be deconvoluted to estimate the abundance of constituent cell types. However, existing deconvolution methods are conditioned on the assumption that the whole study population is served by a single reference panel, ignoring person-to-person heterogeneity. Here, we present imply, a novel algorithm to deconvolute cell type proportions using personalized reference panels. Simulation studies demonstrate reduced bias compared with existing methods. Real data analyses on longitudinal consortia show disparities in cell type proportions are associated with several disease phenotypes in Type 1 diabetes and Parkinson’s disease. imply is available through the R/Bioconductor package ISLET at https://bioconductor.org/packages/ISLET/ .

Using computational tools, bulk transcriptomics can be deconvoluted to estimate the abundance of constituent cell types. However, existing deconvolution methods are conditioned on the assumption that the whole study population is served by a single reference panel, ignoring person-to-person heterogeneity. Here, we present imply, a novel algorithm to deconvolute cell type proportions using personalized reference panels. Simulation studies demonstrate reduced bias compared with existing methods. Real data analyses on longitudinal consortia show disparities in cell type proportions are associated with several disease phenotypes in Type 1 diabetes and Parkinson's disease. imply is available through the R/Bioconductor package ISLET at https://bioconductor.org/packages/ISLET/. [ABSTRACT FROM AUTHOR]

Abstract Background Biological processes are controlled by groups of genes acting in concert. Investigating gene–gene interactions within different cell types can help researchers understand the regulatory mechanisms behind human complex diseases, such as tumors. Methods We collected extensive single-cell RNA-seq data from tumors, involving 563 patients with 44 different tumor types. Through our analysis, we identified various cell types in tumors and created an atlas of different immune cell subsets across different tumor types. Using the SCINET method, we reconstructed interactome networks specific to different cell types. Diverse functional data was then integrated to gain biological insights into the networks, including somatic mutation patterns and gene functional annotation. Additionally, genes with prognostic relevance within the networks were also identified. We also examined cell–cell communications to investigate how gene interactions modulate cell–cell interactions. Results We developed a data portal called CellNetdb for researchers to study cell-type-specific interactome networks. Our findings indicate that these networks can be used to identify genes with topological specificity in different cell types. We also found that prognostic genes can deconvolved into cell types through analyzing network connectivity. Additionally, we identified commonalities and differences in cell-type-specific networks across different tumor types. Our results suggest that these networks can be used to prioritize risk genes. Conclusions This study presented CellNetdb, a comprehensive repository featuring an atlas of cell-type-specific interactome networks across 44 human tumor types. The findings underscore the utility of these networks in delineating the intricacies of tumor microenvironments and advancing the understanding of molecular mechanisms underpinning human tumors.

The integration of feedforward (sensory) and feedback (top-down) neuronal signals is a principal function of the neocortex. Yet, we have limited insight into how these information streams are combined by individual neurons. Using a two-color optogenetic strategy, we found that layer 5 pyramidal neurons in the posterior parietal cortex receive monosynaptic dual innervation, combining sensory inputs with top-down signals. Subclasses of layer 5 pyramidal neurons integrated these synapses with distinct temporal dynamics. Specifically, regular spiking cells exhibited supralinear enhancement of delayed-but not coincident-inputs, while intrinsic burst-firing neurons selectively boosted coincident synaptic events. These subthreshold integration characteristics translated to a nonlinear summation of action potential firing. Complementing electrophysiology with computational modeling, we found that distinct integration profiles arose from a cell-type-specific interaction of ionic mechanisms and feedforward inhibition. These data provide insight into the cellular properties that guide the nonlinear interaction of distinct long-range afferents in the neocortex.

Background: Biological processes are controlled by groups of genes acting in concert. Investigating gene–gene interactions within different cell types can help researchers understand the regulatory mechanisms behind human complex diseases, such as tumors. Methods: We collected extensive single-cell RNA-seq data from tumors, involving 563 patients with 44 different tumor types. Through our analysis, we identified various cell types in tumors and created an atlas of different immune cell subsets across different tumor types. Using the SCINET method, we reconstructed interactome networks specific to different cell types. Diverse functional data was then integrated to gain biological insights into the networks, including somatic mutation patterns and gene functional annotation. Additionally, genes with prognostic relevance within the networks were also identified. We also examined cell–cell communications to investigate how gene interactions modulate cell–cell interactions. Results: We developed a data portal called CellNetdb for researchers to study cell-type-specific interactome networks. Our findings indicate that these networks can be used to identify genes with topological specificity in different cell types. We also found that prognostic genes can deconvolved into cell types through analyzing network connectivity. Additionally, we identified commonalities and differences in cell-type-specific networks across different tumor types. Our results suggest that these networks can be used to prioritize risk genes. Conclusions: This study presented CellNetdb, a comprehensive repository featuring an atlas of cell-type-specific interactome networks across 44 human tumor types. The findings underscore the utility of these networks in delineating the intricacies of tumor microenvironments and advancing the understanding of molecular mechanisms underpinning human tumors. [ABSTRACT FROM AUTHOR]

Rabies-viruses-based retrograde tracers can spread across multiple synapses in a retrograde direction in the nervous system of rodents and primates, making them powerful tools for determining the structure and function of the complicated neural circuits of the brain. However, they have some limitations, such as posing high risks to human health and the inability to retrograde trans-synaptic label inputs from genetically-defined starter neurons. Here, we established a new retrograde trans-multi-synaptic tracing method through brain-wide rabies virus glycoprotein (RVG) compensation, followed by glycoprotein-deleted rabies virus (RV- Δ G) infection in specific brain regions. Furthermore, in combination with the avian tumor virus receptor A (TVA) controlled by a cell-type-specific promoter, we found that EnvA-pseudotyped RV- Δ G can mediate efficient retrograde trans-multi-synaptic transduction from cell-type-specific starter neurons. This study provides new alternative methods for neuroscience researchers to analyze the input neural networks of rodents and nonhuman primates. [ABSTRACT FROM AUTHOR]

Rabies-viruses-based retrograde tracers can spread across multiple synapses in a retrograde direction in the nervous system of rodents and primates, making them powerful tools for determining the structure and function of the complicated neural circuits of the brain. However, they have some limitations, such as posing high risks to human health and the inability to retrograde trans-synaptic label inputs from genetically-defined starter neurons. Here, we established a new retrograde trans-multi-synaptic tracing method through brain-wide rabies virus glycoprotein (RVG) compensation, followed by glycoprotein-deleted rabies virus (RV-[Formula: see text]G) infection in specific brain regions. Furthermore, in combination with the avian tumor virus receptor A (TVA) controlled by a cell-type-specific promoter, we found that EnvA-pseudotyped RV-[Formula: see text]G can mediate efficient retrograde trans-multi-synaptic transduction from cell-type-specific starter neurons. This study provides new alternative methods for neuroscience researchers to analyze the input neural networks of rodents and nonhuman primates.

Genome-wide association studies have revealed that the regulation of gene expression bridges genetic variants and complex phenotypes. Profiling of the bulk transcriptome coupled with linkage analysis (expression quantitative trait locus (eQTL) mapping) has advanced our understanding of the relationship between genetic variants and gene regulation in the context of complex phenotypes. However, bulk transcriptomics has inherited limitations as the regulation of gene expression tends to be cell-type-specific. The advent of single-cell RNA-seq technology now enables the identification of the celltype-specific regulation of gene expression through a single-cell eQTL (sceQTL). In this review, we first provide an overview of sc-eQTL studies, including data processing and the mapping procedure of the sc-eQTL. We then discuss the benefits and limitations of sc-eQTL analyses. Finally, we present an overview of the current and future applications of sc-eQTL discoveries. [ABSTRACT FROM AUTHOR]

Epigenetic-mediated gene regulation orchestrates brain cell-type gene expression programs, and epigenetic dysregulation is a major driver of aging and disease-associated changes. Proteins that mediate gene regulation are mostly localized to the nucleus; however, nuclear-localized proteins are often underrepresented in gene expression studies and have been understudied in the context of the brain. To address this challenge, we have optimized an approach for nuclei isolation that is compatible with proteomic analysis. This was coupled to a mass spectrometry protocol for detecting proteins in low-concentration samples. We have generated nuclear proteomes for neurons, microglia, and oligodendrocytes from the mouse brain cortex and identified cell-type nuclear proteins associated with chromatin structure and organization, chromatin modifiers such as transcription factors, and RNA-binding proteins, among others. Our nuclear proteomics platform paves the way for assessing brain cell type changes in the nuclear proteome across health and disease, such as neurodevelopmental, aging, neurodegenerative, and neuroinflammatory conditions. Data are available via ProteomeXchange with the identifier PXD053515.

Calling differential methylation at a cell-type level from tissue-level bulk data is a fundamental challenge in genomics that has recently received more attention. These studies most often aim at identifying statistical associations rather than causal effects. However, existing methods typically make an implicit assumption about the direction of effects, and thus far, little to no attention has been given to the fact that this directionality assumption may not hold and can consequently affect statistical power and control for false positives. We demonstrate that misspecification of the model directionality can lead to a drastic decrease in performance and increase in risk of spurious findings in cell-type-specific differential methylation analysis, and we discuss the need to carefully consider model directionality before choosing a statistical method for analysis.

The glutamatergic and GABAergic neurons in the ventral tegmental area (VTA) and substantia nigra pars compacta (SNc) mediated diverse brain functions. However, their whole-brain neural connectivity has not been comprehensively mapped. Here we used the virus tracers to characterize the whole-brain inputs and outputs of glutamatergic and GABAergic neurons in VTA and SNc. We found that these neurons received similar inputs from upstream brain regions, but some quantitative differences were also observed. Neocortex and dorsal striatum provided a greater share of input to VTA glutamatergic neurons. Periaqueductal gray and lateral hypothalamic area preferentially innervated VTA GABAergic neurons. Specifically, superior colliculus provided the largest input to SNc glutamatergic neurons. Compared to input patterns, the output patterns of glutamatergic and GABAergic neurons in the VTA and SNc showed significant preference to different brain regions. Our results laid the anatomical foundation for understanding the functions of cell-type-specific neurons in VTA and SNc. [ABSTRACT FROM AUTHOR]

The glutamatergic and GABAergic neurons in the ventral tegmental area (VTA) and substantia nigra pars compacta (SNc) mediated diverse brain functions. However, their whole-brain neural connectivity has not been comprehensively mapped. Here we used the virus tracers to characterize the whole-brain inputs and outputs of glutamatergic and GABAergic neurons in VTA and SNc. We found that these neurons received similar inputs from upstream brain regions, but some quantitative differences were also observed. Neocortex and dorsal striatum provided a greater share of input to VTA glutamatergic neurons. Periaqueductal gray and lateral hypothalamic area preferentially innervated VTA GABAergic neurons. Specifically, superior colliculus provided the largest input to SNc glutamatergic neurons. Compared to input patterns, the output patterns of glutamatergic and GABAergic neurons in the VTA and SNc showed significant preference to different brain regions. Our results laid the anatomical foundation for understanding the functions of cell-type-specific neurons in VTA and SNc.

Epigenetic gene regulation is a major control mechanism of gene expression. Most existing methods for modeling control mechanisms of gene expression use only a single epigenetic marker and very few methods are successful in modeling complex mechanisms of gene regulations using multiple epigenetic markers on transcriptional regulation. In this paper, we propose a multi-attention based deep learning model that integrates multiple markers to characterize complex gene regulation mechanisms. In experiments with 18 cell line multi-omics data, our proposed model predicted the gene expression level more accurately than the state-of-the-art model. Moreover, the model successfully revealed cell-type-specific gene expression control mechanisms. Finally, the model was used to identify genes enriched for specific cell types in terms of their functions and epigenetic regulation.

Enhancers are the primary DNA regulatory elements that confer cell type specificity of gene expression. Recent studies characterizing individual enhancers have revealed their potential to direct heterologous gene expression in a highly cell-type-specific manner. However, it has not yet been possible to systematically identify and test the function of enhancers for each of the many cell types in an organism. We have developed PESCA, a scalable and generalizable method that leverages ATAC- and single-cell RNA-sequencing protocols, to characterize cell-type-specific enhancers that should enable genetic access and perturbation of gene function across mammalian cell types. Focusing on the highly heterogeneous mammalian cerebral cortex, we apply PESCA to find enhancers and generate viral reagents capable of accessing and manipulating a subset of somatostatin-expressing cortical interneurons with high specificity. This study demonstrates the utility of this platform for developing new cell-type-specific viral reagents, with significant implications for both basic and translational research.

An expression quantitative trait locus (eQTL) is a chromosomal region where genetic variants are associated with the expression levels of specific genes that can be both nearby or distant. The identifications of eQTLs for different tissues, cell types, and contexts have led to a better understanding of the dynamic regulations of gene expressions and implications of functional genes and variants for complex traits and diseases. Although most eQTL studies have been performed on data collected from bulk tissues, recent studies have demonstrated the importance of cell-type-specific and context-dependent gene regulations in biological processes and disease mechanisms. In this review, we discuss statistical methods that have been developed to enable the detection of cell-type-specific and context-dependent eQTLs from bulk tissues, purified cell types, and single cells. We also discuss the limitations of the current methods and future research opportunities., Competing Interests: Conflict of interest The authors declare no conflict of interest., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The nucleus accumbens (NAc) is clearly implicated in reward processing and drug addiction, as well as in numerous neurological and psychiatric disorders; nevertheless, the circuit mechanisms underlying the diverse functions of the NAc remain poorly understood. Here, we characterized the whole-brain and monosynaptic inputs to two main projection cell types – D1 dopamine receptor expressing medium spiny neurons (D1R-MSNs) and D2 dopamine receptor expressing medium spiny neurons (D2R-MSNs) – within the NAc core and NAc shell by rabies-mediated trans-synaptic tracing. We discovered that D1R-MSNs and D2R-MSNs in both NAc subregions receive similar inputs from diverse sources. Inputs to the NAc core are broadly scattered, whereas inputs to the NAc shell are relatively concentrated. Furthermore, we identified numerous brain areas providing important contrasting inputs to different NAc subregions. The anterior cortex preferentially innervates the NAc core for both D1R-MSNs and D2R-MSNs, whereas the lateral hypothalamic area (LH) preferentially targets D1R-MSNs in the NAc shell. Characterizing the cell-type-specific connectivity of different NAc subregions lays a foundation for studying how diverse functions of the NAc are mediated by specific pathways.

In the early embryo of vascular plants, the different cell types and stem cells of the seedling are specified as the embryo develops from a zygote towards maturity. How the key steps in cell and tissue specification are instructed by genome-wide transcriptional activity is poorly understood. Progress in defining transcriptional regulation at the genome-wide level in plant embryos has been hampered by difficulties associated with capturing cell-type-specific transcriptomes in this small and inaccessible structure. We recently adapted a two-component genetic nucleus labelling system called INTACT to isolate nuclei from distinct cell types at different stages of Arabidopsis thaliana embryogenesis. We have used these to generate a transcriptomic atlas of embryo development following microarray-based expression profiling. Here, we present a general description of the adapted INTACT procedure, including the two-component labelling system, seed isolation, nuclei preparation and purification, as well as transcriptomic profiling. We also compare nuclear and cellular transcriptomes from the early Arabidopsis embryo to assess nucleocytoplasmic differences and discuss how these differences can be used to infer regulation of gene activity. [ABSTRACT FROM AUTHOR]

The nucleus accumbens (NAc) is clearly implicated in reward processing and drug addiction, as well as in numerous neurological and psychiatric disorders; nevertheless, the circuit mechanisms underlying the diverse functions of the NAc remain poorly understood. Here, we characterized the whole-brain and monosynaptic inputs to two main projection cell types – D1 dopamine receptor expressing medium spiny neurons (D1R-MSNs) and D2 dopamine receptor expressing medium spiny neurons (D2R-MSNs) – within the NAc core and NAc shell by rabies-mediated trans-synaptic tracing. We discovered that D1R-MSNs and D2R-MSNs in both NAc subregions receive similar inputs from diverse sources. Inputs to the NAc core are broadly scattered, whereas inputs to the NAc shell are relatively concentrated. Furthermore, we identified numerous brain areas providing important contrasting inputs to different NAc subregions. The anterior cortex preferentially innervates the NAc core for both D1R-MSNs and D2R-MSNs, whereas the lateral hypothalamic area (LH) preferentially targets D1R-MSNs in the NAc shell. Characterizing the cell-type-specific connectivity of different NAc subregions lays a foundation for studying how diverse functions of the NAc are mediated by specific pathways. [ABSTRACT FROM AUTHOR]

Progenitor cells are critical in preserving organismal homeostasis, yet their diversity and dynamics in the aged brain remain underexplored. We introduced TrackerSci , a single-cell genomic method that combines newborn cell labeling and combinatorial indexing to characterize the transcriptome and chromatin landscape of proliferating progenitor cells in vivo. Using TrackerSci , we investigated the dynamics of newborn cells in mouse brains across various ages and in a mouse model of Alzheimer's disease. Our dataset revealed diverse progenitor cell types in the brain and their epigenetic signatures. We further quantified aging-associated shifts in cell-type-specific proliferation and differentiation and deciphered the associated molecular programs. Extending our study to the progenitor cells in the aged human brain, we identified conserved genetic signatures across species and pinpointed region-specific cellular dynamics, such as the reduced oligodendrogenesis in the cerebellum. We anticipate that TrackerSci will be broadly applicable to unveil cell-type-specific temporal dynamics in diverse systems. [Display omitted] • TrackerSci for characterizing the diversity and dynamics of progenitor cells in vivo • The epigenetic and genetic signatures of brain progenitor cell types • Aging-associated cell-type-specific alterations in proliferation and differentiation • Region-specific changes of oligodendrogenesis in the aged human brain A comprehensive view of single-cell transcriptome and chromatin accessibility dynamics of brain newborn cells provides insights into aging-associated shifts in cell-type-specific proliferation and differentiation and associated molecular programs. [ABSTRACT FROM AUTHOR]

Recent developments in our understanding of the interactions between long non-coding RNAs (lncRNAs) and cellular components have improved treatment approaches for various human diseases including cancer, vascular diseases, and neurological diseases. Although investigation of specific lncRNAs revealed their role in the metabolism of cellular RNA, our understanding of their contribution to post-transcriptional regulation is relatively limited. In this study, we explore the role of lncRNAs in modulating alternative splicing and their impact on downstream protein−RNA interaction networks. Analysis of alternative splicing events across 39 lncRNA knockdown and wildtype RNA-sequencing datasets from three human cell lines—HeLa (cervical cancer), K562 (myeloid leukemia), and U87 (glioblastoma)—resulted in the high-confidence (false discovery rate (fdr) < 0.01) identification of 11,630 skipped exon events and 5895 retained intron events, implicating 759 genes to be impacted at the post-transcriptional level due to the loss of lncRNAs. We observed that a majority of the alternatively spliced genes in a lncRNA knockdown were specific to the cell type. In tandem, the functions annotated to the genes affected by alternative splicing across each lncRNA knockdown also displayed cell-type specificity. To understand the mechanism behind this cell-type-specific alternative splicing pattern, we analyzed RNA-binding protein (RBP)−RNA interaction profiles across the spliced regions in order to observe cell-type-specific alternative splice event RBP binding preference. Despite limited RBP binding data across cell lines, alternatively spliced events detected in lncRNA perturbation experiments were associated with RBPs binding in proximal intron−exon junctions in a cell-type-specific manner. The cellular functions affected by alternative splicing were also affected in a cell-type-specific manner. Based on the RBP binding profiles in HeLa and K562 cells, we hypothesize that several lncRNAs are likely to exhibit a sponge effect in disease contexts, resulting in the functional disruption of RBPs and their downstream functions. We propose that such lncRNA sponges can extensively rewire post-transcriptional gene regulatory networks by altering the protein−RNA interaction landscape in a cell-type-specific manner.

Genome-wide association studies have revealed that the regulation of gene expression bridges genetic variants and complex phenotypes. Profiling of the bulk transcriptome coupled with linkage analysis (expression quantitative trait locus (eQTL) mapping) has advanced our understanding of the relationship between genetic variants and gene regulation in the context of complex phenotypes. However, bulk transcriptomics has inherited limitations as the regulation of gene expression tends to be cell-type-specific. The advent of single-cell RNA-seq technology now enables the identification of the cell-type-specific regulation of gene expression through a single-cell eQTL (sc-eQTL). In this review, we first provide an overview of sc-eQTL studies, including data processing and the mapping procedure of the sc-eQTL. We then discuss the benefits and limitations of sc-eQTL analyses. Finally, we present an overview of the current and future applications of sc-eQTL discoveries., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Luo, Wu, Cheng, Chen, Wang and Song.)

Systemic lupus erythematosus (SLE) is a complex autoimmune disease involving multiple immune cells. To elucidate SLE pathogenesis, it is essential to understand the dysregulated gene expression pattern linked to various clinical statuses with a high cellular resolution. Here, we conducted a large-scale transcriptome study with 6,386 RNA sequencing data covering 27 immune cell types from 136 SLE and 89 healthy donors. We profiled two distinct cell-type-specific transcriptomic signatures: disease-state and disease-activity signatures, reflecting disease establishment and exacerbation, respectively. We then identified candidate biological processes unique to each signature. This study suggested the clinical value of disease-activity signatures, which were associated with organ involvement and therapeutic responses. However, disease-activity signatures were less enriched around SLE risk variants than disease-state signatures, suggesting that current genetic studies may not well capture clinically vital biology. Together, we identified comprehensive gene signatures of SLE, which will provide essential foundations for future genomic and genetic studies. [Display omitted] • A large-scale bulk transcriptome study of 27 immune cell types for SLE • Two distinct gene signatures from case-control and disease-activity comparisons • Combination of unsupervised and supervised approaches • Detailed investigation of five major topics, e.g., biology, treatment, and genetics A large-scale transcriptome analysis of 27 immune cell types from systemic lupus erythematous patients and healthy controls reveals two distinct pathological signatures of disease establishment and exacerbation, which could be informative for drug target discovery. [ABSTRACT FROM AUTHOR]

Albert Einstein said that one should make everything as simple as possible, but not simpler. Likewise, biologists have often relied upon simplifying assumptions to study the fundamental properties of biological systems. To understand how complex multicellular plants respond to stresses such as high salinity, organ or organism-scale experiments have often been the standard and have led to important discoveries. However, recently, through the use of cell-type-specific analyses, it has become clear that most salt-stress regulation occurs at the scale of the cell or tissue type. Salt stress has been revealed to cause complex changes in growth, development and physiology that are dynamically regulated in both space and time. Thus, the next most important discoveries regarding how plants perceive, respond and adapt to this environmental stimulus will require approaches that enable high-resolution spatial and temporal observations to be made. In this review, we highlight studies taking both a genomic and sub-genomic approach to understand the salt response at high spatial resolution. These present and future studies will help lead to a more sophisticated understanding of the root as a complex system, which integrates information from different cell layers to generate synchronized changes necessary for the survival of the plant. [ABSTRACT FROM AUTHOR]

Calling differential methylation at a cell-type level from tissue-level bulk data is a fundamental challenge in genomics that has recently received more attention. These studies most often aim at identifying statistical associations rather than causal effects. However, existing methods typically make an implicit assumption about the direction of effects, and thus far, little to no attention has been given to the fact that this directionality assumption may not hold and can consequently affect statistical power and control for false positives. We demonstrate that misspecification of the model directionality can lead to a drastic decrease in performance and increase in risk of spurious findings in cell-type-specific differential methylation analysis, and we discuss the need to carefully consider model directionality before choosing a statistical method for analysis., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Rahmani, Jew and Halperin.)

Gaining independent genetic access to discrete cell types is critical to interrogate their biological functions as well as to deliver precise gene therapy. Transcriptomics has allowed us to profile cell populations with extraordinary precision, revealing that cell types are typically defined by a unique combination of genetic markers. Given the lack of adequate tools to target cell types based on multiple markers, most cell types remain inaccessible to genetic manipulation. Here we present CaSSA, a platform to create unlimited genetic switches based on CRISPR/Cas9 (Ca) and the DNA repair mechanism known as single-strand annealing (SSA). CaSSA allows engineering of independent genetic switches, each responding to a specific gRNA. Expressing multiple gRNAs in specific patterns enables multiplex cell-type-specific manipulations and combinatorial genetic targeting. CaSSA is a new genetic tool that conceptually works as an unlimited number of recombinases and will facilitate genetic access to cell types in diverse organisms. • A new technology to gain independent genetic access to discrete cell types • The multiplexing potential of CRISPR exploited to create infinite genetic switches • A gene trap system to discover lineage-specific genes • Multi-gene intersectional genetics in a vertebrate and invertebrate model Cell-specific gene modification is immensely crucial for basic biology as well as to deliver precise gene therapy. Garcia-Marques et al. present a breakthrough technology to genetically access specific cell types based on the expression of a precise combination of genes. [ABSTRACT FROM AUTHOR]

Epigenetic gene regulation is a major control mechanism of gene expression. Most existing methods for modeling control mechanisms of gene expression use only a single epigenetic marker and very few methods are successful in modeling complex mechanisms of gene regulations using multiple epigenetic markers on transcriptional regulation. In this paper, we propose a multi-attention based deep learning model that integrates multiple markers to characterize complex gene regulation mechanisms. In experiments with 18 cell line multi-omics data, our proposed model predicted the gene expression level more accurately than the state-of-the-art model. Moreover, the model successfully revealed cell-type-specific gene expression control mechanisms. Finally, the model was used to identify genes enriched for specific cell types in terms of their functions and epigenetic regulation., (Copyright © 2020 Kang, Lee, Lee and Kim.)

Recent developments in our understanding of the interactions between long non-coding RNAs (lncRNAs) and cellular components have improved treatment approaches for various human diseases including cancer, vascular diseases, and neurological diseases. Although investigation of specific lncRNAs revealed their role in the metabolism of cellular RNA, our understanding of their contribution to post-transcriptional regulation is relatively limited. In this study, we explore the role of lncRNAs in modulating alternative splicing and their impact on downstream protein–RNA interaction networks. Analysis of alternative splicing events across 39 lncRNA knockdown and wildtype RNA-sequencing datasets from three human cell lines—HeLa (cervical cancer), K562 (myeloid leukemia), and U87 (glioblastoma)—resulted in the high-confidence (false discovery rate (fdr) < 0.01) identification of 11,630 skipped exon events and 5895 retained intron events, implicating 759 genes to be impacted at the post-transcriptional level due to the loss of lncRNAs. We observed that a majority of the alternatively spliced genes in a lncRNA knockdown were specific to the cell type. In tandem, the functions annotated to the genes affected by alternative splicing across each lncRNA knockdown also displayed cell-type specificity. To understand the mechanism behind this cell-type-specific alternative splicing pattern, we analyzed RNA-binding protein (RBP)–RNA interaction profiles across the spliced regions in order to observe cell-type-specific alternative splice event RBP binding preference. Despite limited RBP binding data across cell lines, alternatively spliced events detected in lncRNA perturbation experiments were associated with RBPs binding in proximal intron–exon junctions in a cell-type-specific manner. The cellular functions affected by alternative splicing were also affected in a cell-type-specific manner. Based on the RBP binding profiles in HeLa and K562 cells, we hypothesize that several lncRNAs are likely to exhibit a sponge effect in disease contexts, resulting in the functional disruption of RBPs and their downstream functions. We propose that such lncRNA sponges can extensively rewire post-transcriptional gene regulatory networks by altering the protein–RNA interaction landscape in a cell-type-specific manner. [ABSTRACT FROM AUTHOR]

Enhancers are the primary DNA regulatory elements that confer cell type specificity of gene expression. Recent studies characterizing individual enhancers have revealed their potential to direct heterologous gene expression in a highly cell-type-specific manner. However, it has not yet been possible to systematically identify and test the function of enhancers for each of the many cell types in an organism. We have developed PESCA, a scalable and generalizable method that leverages ATAC- and single-cell RNA-sequencing protocols, to characterize cell-type-specific enhancers that should enable genetic access and perturbation of gene function across mammalian cell types. Focusing on the highly heterogeneous mammalian cerebral cortex, we apply PESCA to find enhancers and generate viral reagents capable of accessing and manipulating a subset of somatostatin-expressing cortical interneurons with high specificity. This study demonstrates the utility of this platform for developing new cell-type-specific viral reagents, with significant implications for both basic and translational research., Competing Interests: SH, CT, MN, HS, CK, OW, EA, JG, CH, EG, MG No competing interests declared, (© 2019, Hrvatin et al.)

Alternative splicing (AS) allows a single gene to generate multiple protein isoforms. It has been hypothesized that AS plays a role in brain wiring by increasing the number of cell recognition molecules necessary for forming connections between neurons. Many studies have characterized isoform expression patterns of various genes in the brain, but very few have addressed whether specific isoforms play a functional role in neuronal wiring. In our recent work, we reported the cell-type-specific AS of the cell recognition molecule Dscam2. Exclusive expression of Dscam2 isoforms allows tightly associated neurons to signal repulsion selectively within the same cell-types, without interfering with one another. We show that preventing cell-specific isoform expression in 2 closely associated neurons disrupts their axon terminal morphology. We propose that the requirement for isoform specificity extends to synapses and discuss experiments that can test this directly. Factors that regulate Dscam2 cell-type-specific AS likely regulate the splicing of many genes involved in neurodevelopment. These regulators of alternative splicing may act broadly to control many genes involved in the development of specific neuron types. Identifying these factors is a key step in understanding how AS contributes to the brain connectome.

Systemic lupus erythematosus (SLE) is an autoimmune disease characterized by complex interplay among immune cell types. SLE activity is experimentally assessed by several blood tests, including gene expression profiling of heterogeneous populations of cells in peripheral blood. To better understand the contribution of different cell types in SLE pathogenesis, we applied the two methods in cell-type-specific differential expression analysis, csSAM and DSection, to identify cell-type-specific gene expression differences in heterogeneous gene expression measures obtained using RNA-seq technology. We identified B-cell-, monocyte-, and neutrophil-specific gene expression differences. Immunoglobulin-coding gene expression was altered in B-cells, while a ribosomal signature was prominent in monocytes. On the contrary, genes differentially expressed in the heterogeneous mixture of cells did not show any functional enrichment. Our results identify antigen binding and structural constituents of ribosomes as functions altered by B-cell- and monocyte-specific gene expression differences, respectively. Finally, these results position both csSAM and DSection methods as viable techniques for cell-type-specific differential expression analysis, which may help uncover pathogenic, cell-type-specific processes in SLE.

The striatum plays a key role in mediating the acute and chronic effects of addictive drugs, with drugs of abuse causing long-lasting molecular and cellular alterations in both dorsal striatum and nucleus accumbens (ventral striatum). Despite the wealth of research on the biological actions of abused drugs in striatum, until recently, the distinct roles of the striatum's two major subtypes of medium spiny neurons (MSNs) in drug addiction remained elusive. Recent advances in cell-type-specific technologies, including fluorescent reporter mice, transgenic, or knockout mice, and viral-mediated gene transfer, have advanced the field toward a more comprehensive understanding of the two MSN subtypes in the long-term actions of drugs of abuse. Here we review progress in defining the distinct molecular and functional contributions of the two MSN subtypes in mediating addiction.