scholarly journals Single cell transcriptomics, mega-phylogeny and the genetic basis of morphological innovations in Rhizaria

2016 ◽  
Author(s):  
Anders K. Krabberød ◽  
Russell J. S. Orr ◽  
Jon Bråte ◽  
Tom Kristensen ◽  
Kjell R. Bjørklund ◽  
...  
Keyword(s):  
Single Cell ◽  
Intracellular Transport ◽  
Gene Evolution ◽  
Morphological Evolution ◽  
Specific Gene ◽  
Gene Duplications ◽  
Genetic Components ◽  
The Relationship ◽  
Protist Species ◽  
Lineage Specific Gene

AbstractThe innovation of the eukaryote cytoskeleton enabled phagocytosis, intracellular transport and cytokinesis, and is responsible for diverse eukaryotic morphologies. Still, the relationship between phenotypic innovations in the cytoskeleton and their underlying genotype is poorly understood. To explore the genetic mechanism of morphological evolution of the eukaryotic cytoskeleton we provide the first single cell transcriptomes from uncultivable, free-living unicellular eukaryotes: the radiolarian speciesLithomelissa setosaandSticholonche zanclea. Analysis of the genetic components of the cytoskeleton and mapping of the evolution of these to a revised phylogeny of Rhizaria reveals lineage-specific gene duplications and neo-functionalization of α and β tubulin in Retaria, actin in Retaria and Endomyxa, and Arp2/3 complex genes in Chlorarachniophyta. We show how genetic innovations have shaped cytoskeletal structures in Rhizaria, and how single cell transcriptomics can be applied for resolving deep phylogenies and studying gene evolution of uncultivable protist species.

scholarly journals Recruitment of toxin-like proteins with ancestral venom function supports endoparasitic lifestyles of Myxozoa

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11208
Author(s):  
Ashlie Hartigan ◽  
Adrian Jaimes-Becerra ◽  
Beth Okamura ◽  
Liam B. Doonan ◽  
Malcolm Ward ◽  
...  
Keyword(s):  
Prey Capture ◽  
Phylogenetic Analyses ◽  
Specific Gene ◽  
Gene Duplications ◽  
Free Living ◽  
Venom Toxin ◽  
Venomous Animals ◽  
Kunitz Type ◽  
Polypodium Hydriforme ◽  
Lineage Specific Gene

Cnidarians are the oldest lineage of venomous animals and use nematocysts to discharge toxins. Whether venom toxins have been recruited to support parasitic lifestyles in the Endocnidozoa (Myxozoa + Polypodium) is, however, unknown. To examine this issue we variously employed transcriptomic, proteomic, associated molecular phylogenies, and localisation studies on representative primitive and derived myxozoans (Malacosporea and Myxosporea, respectively), Polypodium hydriforme, and the free-living staurozoan Calvadosia cruxmelitensis. Our transcriptomics and proteomics analyses provide evidence for expression and translation of venom toxin homologs in myxozoans. Phylogenetic placement of Kunitz type serine protease inhibitors and phospholipase A2 enzymes reveals modification of toxins inherited from ancestral free-living cnidarian toxins, and that venom diversity is reduced in myxozoans concordant with their reduced genome sizes. Various phylogenetic analyses of the Kunitz-type toxin family in Endocnidozoa suggested lineage-specific gene duplications, which offers a possible mechanism for enhancing toxin diversification. Toxin localisation in the malacosporean Buddenbrockia plumatellae substantiates toxin translation and thus illustrates a repurposing of toxin function for endoparasite development and interactions with hosts, rather than for prey capture or defence. Whether myxozoan venom candidates are expressed in transmission stages (e.g. in nematocysts or secretory vesicles) requires further investigation.

scholarly journals The UDP-Glycosyltransferase Family in Drosophila melanogaster: Nomenclature Update, Gene Expression and Phylogenetic Analysis

2021 ◽  
Vol 12 ◽  
Author(s):  
Seung-Joon Ahn ◽  
Steven J. Marygold
Keyword(s):  
Gene Expression ◽  
Phylogenetic Analysis ◽  
Drosophila Melanogaster ◽  
Expression Patterns ◽  
Specific Gene ◽  
Uridine Diphosphate ◽  
Gene Duplications ◽  
Lipophilic Compounds ◽  
High Degree ◽  
Lineage Specific Gene

UDP-glycosyltransferases (UGTs) are important conjugation enzymes found in all kingdoms of life, catalyzing a sugar conjugation with small lipophilic compounds and playing a crucial role in detoxification and homeostasis. The UGT gene family is defined by a signature motif in the C-terminal domain where the uridine diphosphate (UDP)-sugar donor binds. UGTs have been identified in a number of insect genomes over the last decade and much progress has been achieved in characterizing their expression patterns and molecular functions. Here, we present an update of the complete repertoire of UGT genes in Drosophila melanogaster and provide a brief overview of the latest research in this model insect. A total of 35 UGT genes are found in the D. melanogaster genome, localized to chromosomes 2 and 3 with a high degree of gene duplications on the chromosome arm 3R. All D. melanogaster UGT genes have now been named in FlyBase according to the unified UGT nomenclature guidelines. A phylogenetic analysis of UGT genes shows lineage-specific gene duplications. Analysis of anatomical and induced gene expression patterns demonstrate that some UGT genes are differentially expressed in various tissues or after environmental treatments. Extended searches of UGT orthologs from 18 additional Drosophila species reveal a diversity of UGT gene numbers and composition. The roles of Drosophila UGTs identified to date are briefly reviewed, and include xenobiotic metabolism, nicotine resistance, olfaction, cold tolerance, sclerotization, pigmentation, and immunity. Together, the updated genomic information and research overview provided herein will aid further research in this developing field.

Insights into therapeutic targets and biomarkers using integrated multi-‘omics’ approaches for dilated and ischemic cardiomyopathies

2021 ◽  
Author(s):  
Austė Kanapeckaitė ◽  
Neringa Burokienė
Keyword(s):  
Machine Learning ◽  
Single Cell ◽  
Learning Algorithm ◽  
Expression Profiles ◽  
Therapeutic Targets ◽  
Development Stage ◽  
Biological Data ◽  
Specific Gene ◽  
Tissue Remodelling ◽  
Pharmacological Management

Abstract At present, heart failure (HF) treatment only targets the symptoms based on the left ventricle dysfunction severity; however, the lack of systemic ‘omics’ studies and available biological data to uncover the heterogeneous underlying mechanisms signifies the need to shift the analytical paradigm towards network-centric and data mining approaches. This study, for the first time, aimed to investigate how bulk and single cell RNA-sequencing as well as the proteomics analysis of the human heart tissue can be integrated to uncover HF-specific networks and potential therapeutic targets or biomarkers. We also aimed to address the issue of dealing with a limited number of samples and to show how appropriate statistical models, enrichment with other datasets as well as machine learning-guided analysis can aid in such cases. Furthermore, we elucidated specific gene expression profiles using transcriptomic and mined data from public databases. This was achieved using the two-step machine learning algorithm to predict the likelihood of the therapeutic target or biomarker tractability based on a novel scoring system, which has also been introduced in this study. The described methodology could be very useful for the target or biomarker selection and evaluation during the pre-clinical therapeutics development stage as well as disease progression monitoring. In addition, the present study sheds new light into the complex aetiology of HF, differentiating between subtle changes in dilated cardiomyopathies (DCs) and ischemic cardiomyopathies (ICs) on the single cell, proteome and whole transcriptome level, demonstrating that HF might be dependent on the involvement of not only the cardiomyocytes but also on other cell populations. Identified tissue remodelling and inflammatory processes can be beneficial when selecting targeted pharmacological management for DCs or ICs, respectively.

ExperimentSubset: an R package to manage subsets of Bioconductor Experiment objects

2021 ◽  
Author(s):  
Irzam Sarfraz ◽  
Muhammad Asif ◽  
Joshua D Campbell
Keyword(s):  
Single Cell ◽  
R Package ◽  
Poor Quality ◽  
Data Matrix ◽  
Supplementary Information ◽  
Data Provenance ◽  
Rna Seq ◽  
Efficient Management ◽  
The Matrix ◽  
The Relationship

Abstract Motivation R Experiment objects such as the SummarizedExperiment or SingleCellExperiment are data containers for storing one or more matrix-like assays along with associated row and column data. These objects have been used to facilitate the storage and analysis of high-throughput genomic data generated from technologies such as single-cell RNA sequencing. One common computational task in many genomics analysis workflows is to perform subsetting of the data matrix before applying down-stream analytical methods. For example, one may need to subset the columns of the assay matrix to exclude poor-quality samples or subset the rows of the matrix to select the most variable features. Traditionally, a second object is created that contains the desired subset of assay from the original object. However, this approach is inefficient as it requires the creation of an additional object containing a copy of the original assay and leads to challenges with data provenance. Results To overcome these challenges, we developed an R package called ExperimentSubset, which is a data container that implements classes for efficient storage and streamlined retrieval of assays that have been subsetted by rows and/or columns. These classes are able to inherently provide data provenance by maintaining the relationship between the subsetted and parent assays. We demonstrate the utility of this package on a single-cell RNA-seq dataset by storing and retrieving subsets at different stages of the analysis while maintaining a lower memory footprint. Overall, the ExperimentSubset is a flexible container for the efficient management of subsets. Availability and implementation ExperimentSubset package is available at Bioconductor: https://bioconductor.org/packages/ExperimentSubset/ and Github: https://github.com/campbio/ExperimentSubset. Supplementary information Supplementary data are available at Bioinformatics online.

scholarly journals Comprehensive analysis of single cell ATAC-seq data with SnapATAC

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Rongxin Fang ◽  
Sebastian Preissl ◽  
Yang Li ◽  
Xiaomeng Hou ◽  
Jacinta Lucero ◽  
...  
Keyword(s):  
Single Cell ◽  
Single Cell Analysis ◽  
Expression Patterns ◽  
Regulatory Elements ◽  
Cellular Heterogeneity ◽  
Specific Gene ◽  
Open Chromatin ◽  
Cell Type ◽  
Process Data ◽  
Cell Type Specific

AbstractIdentification of the cis-regulatory elements controlling cell-type specific gene expression patterns is essential for understanding the origin of cellular diversity. Conventional assays to map regulatory elements via open chromatin analysis of primary tissues is hindered by sample heterogeneity. Single cell analysis of accessible chromatin (scATAC-seq) can overcome this limitation. However, the high-level noise of each single cell profile and the large volume of data pose unique computational challenges. Here, we introduce SnapATAC, a software package for analyzing scATAC-seq datasets. SnapATAC dissects cellular heterogeneity in an unbiased manner and map the trajectories of cellular states. Using the Nyström method, SnapATAC can process data from up to a million cells. Furthermore, SnapATAC incorporates existing tools into a comprehensive package for analyzing single cell ATAC-seq dataset. As demonstration of its utility, SnapATAC is applied to 55,592 single-nucleus ATAC-seq profiles from the mouse secondary motor cortex. The analysis reveals ~370,000 candidate regulatory elements in 31 distinct cell populations in this brain region and inferred candidate cell-type specific transcriptional regulators.

scholarly journals SCALE: modeling allele-specific gene expression by single-cell RNA sequencing

2017 ◽  
Vol 18 (1) ◽  
Author(s):  
Yuchao Jiang ◽  
Nancy R. Zhang ◽  
Mingyao Li
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Rna Sequencing ◽  
Specific Gene ◽  
Specific Gene Expression ◽  
Scale Modeling ◽  
Single Cell Rna Sequencing ◽  
Allele Specific

scholarly journals STRUCTURE-FUNCTION RELATIONSHIPS IN THE ADIPOSE CELL

1970 ◽  
Vol 46 (2) ◽  
pp. 342-353 ◽  
Author(s):  
Samuel W. Cushman
Keyword(s):  
Electron Microscopy ◽  
Fatty Acids ◽  
Colloidal Gold ◽  
Intracellular Transport ◽  
Nonesterified Fatty Acid ◽  
Experimental Conditions ◽  
Nonesterified Fatty Acids ◽  
Adipose Cell ◽  
Cell Functions ◽  
The Relationship

Pinocytic activity in the adipose cell has been examined by measuring the uptake of colloidal gold. Pinocytic activity occurs in the isolated adipose cell under all experimental conditions; a portion of the vesicular elements of the cell can be identified by electron microscopy as pinocytic in origin. The isolated adipose cell appears to take up serum albumin by pinocytosis. Pinocytic activity in the isolated adipose cell is enhanced by epinephrine, but not by insulin. The relationship between pinocytosis and the metabolic activity of the adipose cell has been studied by measuring simultaneously the uptake of radioactive colloidal gold, the incorporation of 14C-counts from U-glucose-14C into CO2, total lipid, triglyceride glycerol and triglyceride fatty acids, and the release of nonesterified fatty acids in the absence of hormones and in the presence of insulin or epinephrine. Correlations between hormone-produced alterations in lipid metabolism and in pinocytic activity suggest that intracellular nonesterified fatty acid levels are a factor in the regulation of both the cell's pinocytic activity and its metabolism and that pinocytosis in the adipose cell functions in the extracellular-intracellular transport of nonesterified fatty acids.

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