Network Inference on RNA-Seq Data from Mammalian Retina

The mammalian retina is an intricate network of cells communicating and cooperating to convey light stimuli to the visual cortex of the brain. Moreover, it is the most accessible part of the Central Nervous System and hence a valuable model to study the CNS. A hierarchical scheme of transcription factors (TF) that determine each cells’ identity is regularly expressed following a precise timeline, since the early stages of development of the embryo. The interplay of those TF controls univocal flows of transcription and genetic programs which direct cells’ identities, maintain their specific expression patterns and guarantee the survival of each cell type. Despite the large interest of the scientific community on retina, and the large variety of databases collecting gene expression profiles from multiple species, very few Next Generation Sequencing experiments on this tissue were collected in public available data. We generated a co-expression net work using porcine whole retina RNA-seq data produced in our laboratory to characterise the retina specific Gene Regulatory Networks, which are disrupted in retinal diseases. Our inferred network shows good performance and reliability of the predicted connections. We characterised retina-specific processes by comparing our dataset with a RNA-seq study on 10 porcine tissues. Furthermore, we characterised the genome-wide functional effects of a synthetic transcription factor composed of a DNA-binding domain targeted to a 20 bp of Rhodopsin (RHO) cis-regulatory sequence, which induced RHO specific transcriptional silencing upon adeno-associated viral (AAV) vector delivery. Finally, we assessed the rod-specific repression of RHO after FACS-sorting photoreceptors interfered with our construct, and confirmed this results on single cells by qPCR

484. Preclinical Proof of Concept of Transcriptional Silencing and Replacement Strategy for Treatment of Retinitis Pigmentosa Due To RHODOPSIN Mutations

Silencing and replacement strategy is a promising approach to overcome mutational heterogeneity of genetic defects. In autosomal dominant retinitis pigmentosa (adRP) due to rhodopsin gene (RHO) approximately 200 different mutations have been described, posing a challenge for the design of effective therapeutics.We designed a silencing and replacement strategy based on transcriptional silencing through an artificial zinc finger DNA-binding protein lacking effector domains (ZF6DBD), and tested both efficacy and safety in two animal models.In a murine model of adRP, we show that AAV-mediate retinal delivery (AAV2/8-CMV-ZF6-DBD) is associated with selective transcriptional silencing of the human mutated allele resulting in morphological and functional (Electroretinography, ERG a-wave and b-wave responses) rescue. We then tested the effect of transcriptional silencing in the porcine large pre-clinical model. Delivery of a low dose (AAV2/8-CMV-ZF6-DBD, 1×10e10 vector genomes, vg) of the ZF6 transcriptional silencer to the porcine retina resulted in robust transcriptional silencing of the endogenous porcine RHO transcript. Cell sorting of transduced photoreceptors showed an almost complete RHO transcriptional silencing effect (90% RHO transcriptional repression), underscoring the potency of the system. To determine the safety of the zinc-finger silencer we performed extensive RNA-seq analysis on treated and control retinae. The data sets generated demonstrate selective RHO gene transcriptional repression and a remarkably low number of differential expressed genes (DEGs), supporting specificity and thus, safety. The co-administration to the porcine retina of the AAV-ZF6 silencer (AAV2/8-CMV-ZF6-DBD) and the AAV-RHO replacement (5×10e11 vg, AAV2/8-GNAT1-HumanRHO) constructs resulted in a balanced silencing and replacement effect. This data support the use of zinc-finger based RHO transcriptional silencing for the development of a clinical trial for adRP patients

320 transcriptional silencing via synthetic dna binding protein lacking canonical repressor domains as a potent tool to generate therapeutics

Transcription factors (TFs) function by the combined activity of their DNA-binding domains (DBDs) and effector domains (EDs). Here we show that in vivo delivery of an engineered DNA-binding protein uncoupled from the repressor domain entails complete and gene-specific transcriptional silencing. To silence RHODOPSIN (RHO) gain-of-function mutations, we engineered a synthetic DNA-binding protein lacking canonical repressor domains and targeted to the regulatory region of the RHO gene. AAV-mediate retinal delivery at a low dose (AAV2/8-CMV-ZF6-DBD, 1×10e10 vector genomes, vg) in the porcine retina resulted in selective transcriptional silencing of RHO expression. The rod photoreceptors (the RHO expressing cells) transduced cells when isolated by FACS-sorting showed the remarkable 90% RHO transcriptional repression. To evaluate genome-wide transcriptional specificity, we analyzed the porcine retina transcriptome by RNA sequencing (RNA-Seq). The differentially expressed genes (DEGs) analysis showed that only 19 genes were perturbed. In this study, we describe a system based on a synthetic DNA binding protein enabling targeted transcriptional silencing of the RHO gene by in vivo gene transfer. The high rate of transcriptional silencing occurring in transduced cells supports applications of this regulatory genomic interference with a synthetic trans-acting factor for diseases requiring gene silencing in a large number of affected cells, including for instance a number of neurodegeneration disorders. The result support a novel mode of gene targeted silencing with a DNA-binding protein lacking intrinsic activity

Targeted single-cell RNA sequencing of transcription factors facilitates biological insights from human cell experimental models

Single-cell RNA sequencing (scRNA-seq) is a widely used method for identifying cell types and trajectories in biologically heterogeneous samples, but it is limited in its detection and quantification of lowly expressed genes. This results in missing important biological signals, such as the expression of key transcription factors (TFs) driving cellular differentiation. We show that targeted sequencing of ∼1000 TFs (scCapture-seq) in iPSC-derived neuronal cultures greatly improves the biological information garnered from scRNA-seq. Increased TF resolution enhanced cell type identification, developmental trajectories, and gene regulatory networks. This allowed us to resolve differences among neuronal populations, which were generated in two different laboratories using the same differentiation protocol. ScCapture-seq improved TF-gene regulatory network inference and thus identified divergent patterns of neurogenesis into either excitatory cortical neurons or inhibitory interneurons. Furthermore, scCapture-seq revealed a role for of retinoic acid signaling in the developmental divergence between these different neuronal populations. Our results show that TF targeting improves the characterization of human cellular models and allows identification of the essential differences between cellular populations, which would otherwise be missed in traditional scRNA-seq. scCapture-seq TF targeting represents a cost-effective enhancement of scRNA-seq, which could be broadly applied to improve scRNA-seq resolution

Targeted single-cell RNA sequencing of transcription factors facilitates biological insights from human cell experimental models

Single-cell RNA sequencing (scRNA-seq) is a widely used method for identifying cell types and trajectories in biologically heterogeneous samples, but it is limited in its detection and quantification of lowly expressed genes. This results in missing important biological signals, such as the expression of key transcription factors (TFs) driving cellular differentiation. We show that targeted sequencing of ∼1000 TFs (scCapture-seq) in iPSC-derived neuronal cultures greatly improves the biological information garnered from scRNA-seq. Increased TF resolution enhanced cell type identification, developmental trajectories, and gene regulatory networks. This allowed us to resolve differences among neuronal populations, which were generated in two different laboratories using the same differentiation protocol. ScCapture-seq improved TF-gene regulatory network inference and thus identified divergent patterns of neurogenesis into either excitatory cortical neurons or inhibitory interneurons. Furthermore, scCapture-seq revealed a role for of retinoic acid signaling in the developmental divergence between these different neuronal populations. Our results show that TF targeting improves the characterization of human cellular models and allows identification of the essential differences between cellular populations, which would otherwise be missed in traditional scRNA-seq. scCapture-seq TF targeting represents a cost-effective enhancement of scRNA-seq, which could be broadly applied to improve scRNA-seq resolution

An immunodominant NP105-113-B*07:02 cytotoxic T cell response controls viral replication and is associated with less severe COVID-19 disease.

Funder: RCUK | Medical Research Council (MRC); doi: https://doi.org/10.13039/501100000265Funder: Chinese Academy of Medical Sciences (CAMS); doi: https://doi.org/10.13039/501100005150Funder: Wellcome Trust (Wellcome); doi: https://doi.org/10.13039/100004440NP105-113-B*07:02-specific CD8+ T cell responses are considered among the most dominant in SARS-CoV-2-infected individuals. We found strong association of this response with mild disease. Analysis of NP105-113-B*07:02-specific T cell clones and single-cell sequencing were performed concurrently, with functional avidity and antiviral efficacy assessed using an in vitro SARS-CoV-2 infection system, and were correlated with T cell receptor usage, transcriptome signature and disease severity (acute n = 77, convalescent n = 52). We demonstrated a beneficial association of NP105-113-B*07:02-specific T cells in COVID-19 disease progression, linked with expansion of T cell precursors, high functional avidity and antiviral effector function. Broad immune memory pools were narrowed postinfection but NP105-113-B*07:02-specific T cells were maintained 6 months after infection with preserved antiviral efficacy to the SARS-CoV-2 Victoria strain, as well as Alpha, Beta, Gamma and Delta variants. Our data show that NP105-113-B*07:02-specific T cell responses associate with mild disease and high antiviral efficacy, pointing to inclusion for future vaccine design

A blood atlas of COVID-19 defines hallmarks of disease severity and specificity.

Treatment of severe COVID-19 is currently limited by clinical heterogeneity and incomplete description of specific immune biomarkers. We present here a comprehensive multi-omic blood atlas for patients with varying COVID-19 severity in an integrated comparison with influenza and sepsis patients versus healthy volunteers. We identify immune signatures and correlates of host response. Hallmarks of disease severity involved cells, their inflammatory mediators and networks, including progenitor cells and specific myeloid and lymphocyte subsets, features of the immune repertoire, acute phase response, metabolism, and coagulation. Persisting immune activation involving AP-1/p38MAPK was a specific feature of COVID-19. The plasma proteome enabled sub-phenotyping into patient clusters, predictive of severity and outcome. Systems-based integrative analyses including tensor and matrix decomposition of all modalities revealed feature groupings linked with severity and specificity compared to influenza and sepsis. Our approach and blood atlas will support future drug development, clinical trial design, and personalized medicine approaches for COVID-19

Mudata trimodal dataset small feature set

smaller HVG subsets of teaseq for testing</p