Biology subjects

Bolisetty, M.

Publications and source records attributed to Bolisetty, M..

6 recordsLinked to original sources

bioRxiv2020

Cellular taxonomy and spatial organization of the ventral posterior hypothalamus reveals neuroanatomical parcellation of the mammillary bodies

The ventral posterior hypothalamus (VPH) is an anatomically complex brain region implicated in arousal, reproduction, energy balance and memory processing. However, neuronal cell type diversity within the VPH is poorly understood, an impediment to deconstructing the roles of distinct VPH circuits in physiology and behavior. To address this question, we employed a droplet-based single cell RNA sequencing (scRNA-seq) approach to systematically classify molecularly distinct cell types in the mouse VPH. Analysis of >16,000 single cells revealed 20 neuronal and 18 non-neuronal cell populations, defined by suites of discriminatory markers. We validated differentially expressed genes in a selection of neuronal populations through fluorescence in situ hybridization (FISH). Focusing on the mammillary bodies (MB), we discovered transcriptionally-distinct clusters that exhibit a surprising degree of segregation within neuroanatomical subdivisions of the MB, while genetically-defined MB cell types project topographically to the anterior thalamus. This single cell transcriptomic atlas of cell types in the VPH provides a detailed resource for interrogating the circuit-level mechanisms underlying the diverse functions of VPH circuits in health and disease.

neuroscience↗

bioRxiv2019

Calculating sample size for identifying cell subpopulation in single-cell RNA-seq experiments

SO_SCPLOWUMMARYC_SCPLOWSingle-cell RNA sequencing (scRNA-seq) is a rapidly developing technology for studying gene expression at the individual cell level and is often used to identify subpopulations of cells. Although the use of scRNA-seq is steadily increasing in basic and translational research, there is currently no statistical model for calculating the optimal number of cells for use in experiments that seek to identify cell subpopulations. Here, we have developed a statistical method ncells for calculating the number of cells required to detect a rare subpopulation in a homogeneous cell population for the given type I and II error. ncells defines power as the probability of separation of subpopulations which is calculated from three user-defined parameters: the proportion of rare subpopulation, proportion of up-regulated marker genes of the subpopulation, and levels of differential expression of the marker genes. We applied ncells to the scRNA-seq data on dendritic cells and monocytes isolated from healthy blood donor to show its efficacy in calculating the optimal number of cells in identifying a novel subpopulation.

bioinformatics↗

bioRxiv2019

Single Cell Viewer (SCV): An interactive visualization data portal for single cell RNA sequence data

MotivationThanks to technological advances made in the last few years, we are now able to study transcriptomes from thousands of single cells. These have been applied widely to study various aspects of Biology. Nevertheless, comprehending and inferring meaningful biological insights from these large datasets is still a challenge. Although tools are being developed to deal with the data complexity and data volume, we do not have yet an effective visualizations and comparative analysis tools to realize the full value of these datasets.\n\nResultsIn order to address this gap, we implemented a single cell data visualization portal called Single Cell Viewer (SCV). SCV is an R shiny application that offers users rich visualization and exploratory data analysis options for single cell datasets.\n\nAvailabilitySource code for the application is available online at GitHub (http://www.github.com/neuhausi/single-cell-viewer) and there is a hosted exploration application using the same example dataset as this publication at http://periscopeapps.org/scv_tirosh.\n\nContactisaac.neuhaus@bms.com; kandasamy.ravi@bms.com

bioinformatics↗

bioRxiv2019

The genome of C57BL/6J \"Eve\", the mother of the laboratory mouse genome reference strain

Isogenic laboratory mouse strains are used to enhance reproducibility as individuals within a strain are essentially genetically identical. For the most widely used isogenic strain, C57BL/6, there is also a wealth of genetic, phenotypic, and genomic data, including one of the highest quality reference genomes (GRCm38.p6). However, laboratory mouse strains are living reagents and hence genetic drift occurs and is an unavoidable source of accumulating genetic variability that can have an impact on reproducibility over time. Nearly 20 years after the first release of the mouse reference genome, individuals from the strain it represents (C57BL/6J) are at least 26 inbreeding generations removed from the individuals used to generate the mouse reference genome. Moreover, C57BL/6J is now maintained through the periodic reintroduction of mice from cryopreserved embryo stocks that are derived from a single breeder pair, aptly named C57BL/6J Adam and Eve. To more accurately represent the genome of todays C57BL/6J mice, we have generated a de novo assembly of the C57BL/6J Eve genome (B6Eve) using high coverage, long-read sequencing, optical mapping, and short-read data. Using these data, we addressed recurring variants observed in previous mouse studies. We have also identified structural variations that impact coding sequences, closed gaps in the mouse reference assembly, some of which are in genes, and we have identified previously unannotated coding sequences through long read sequencing of cDNAs. This B6Eve assembly explains discrepant observations that have been associated with GRCm38-based analyses, and has provided data towards a reference genome that is more representative of the C57BL/6J mice that are in use today.

genomics↗

bioRxiv2017

Comprehensive Cell Type Specific Transcriptomics of the Human Kidney

The human kidney is a complex organ composed of specialized cell types. To better define this cellular complexity, we profiled the individual transcriptomes of 22,469 normal human kidney cells, identifying 27 cell types. We describe three distinct endothelial cell populations, a novel subset of intercalated cells, interstitial macrophage and dendritic cells, and identify numerous novel cell-type-specific markers, many validated using imaging mass cytometry and immunohistochemistry. Receptor-ligand analysis revealed previously unknown intercalated-endothelial and intercalated-distal nephron interactions, suggesting a role in maintenance of vascular integrity and intercalated cell survival. Notably, kidney disease-associated genes were largely expressed in proximal tubules, podocytes, endothelial and myeloid cells, highlighting an underappreciated role for endothelial cells in kidney pathologies. Our analysis also provides a resource of cell type enriched markers, solute carriers, channels and lncRNAs. In summary, this cell-type-specific transcriptome resource provides the foundation for a comprehensive understanding of kidney function and dysfunction at single cell resolution.

cell biology↗

bioRxiv2017

Ccr4 And Pop2 Control Poly(A) Tail Length In Saccharomyces cerevisiae

Messenger RNA degradation is an important aspect of post-transcriptional gene regulation and shortening the poly(A) tail is suggested to be the rate-limiting step in mRNA degradation. In Saccharomyces cerevisiae, the Ccr4-Not complex is the major deadenylase and contains two subunits with exoribonuclease domains, Ccr4 and Pop2. Although the role of Ccr4 and Pop2 in deadenylation has previously been studied using individual reporter mRNAs, their activity has not been studied transcriptome-wide. Here, we describe END-seq, a method to accurately measure poly(A) tail lengths of individual mRNAs transcriptome-wide, and have used this assay to examine the impact of deleting or mutating CCR4 and POP2 on steady state poly(A) tail length. We found that Ccr4 and Pop2 have differential effects on the poly(A) tail lengths of individual mRNAs. Additionally, though Pop2 has previously been reported to have exonuclease activity, mutations that render it catalytically inactive have no effect on steady-state poly(A) tail lengths. Furthermore, mutations that disrupt the interaction between Ccr4 and Pop2 result in longer poly(A) tails. We also observe an inverse correlation between codon optimality and poly(A) tail length - transcripts containing predominantly optimal codons display fewer changes in poly(A) tail length upon deletion of Ccr4 or Pop2 than those containing less optimal codons. Together, these results indicate that Pop2 modulates poly(A) tail length, at least partially, via its association with Ccr4 and that Pop2 improves the function of Ccr4 in regulating poly(A) tail length. These data provide important insights into poly(A) tail length dynamics in yeast and demonstrate that END-seq is an efficient and accurate method to study poly(A) tail length.

genomics↗