The Human Cell Atlas is a large international collaborative effort to map all cell types of the human body. Single-cell RNA sequencing can generate high-quality data for the delivery of such an ...atlas. However, delays between fresh sample collection and processing may lead to poor data and difficulties in experimental design.
This study assesses the effect of cold storage on fresh healthy spleen, esophagus, and lung from ≥ 5 donors over 72 h. We collect 240,000 high-quality single-cell transcriptomes with detailed cell type annotations and whole genome sequences of donors, enabling future eQTL studies. Our data provide a valuable resource for the study of these 3 organs and will allow cross-organ comparison of cell types. We see little effect of cold ischemic time on cell yield, total number of reads per cell, and other quality control metrics in any of the tissues within the first 24 h. However, we observe a decrease in the proportions of lung T cells at 72 h, higher percentage of mitochondrial reads, and increased contamination by background ambient RNA reads in the 72-h samples in the spleen, which is cell type specific.
In conclusion, we present robust protocols for tissue preservation for up to 24 h prior to scRNA-seq analysis. This greatly facilitates the logistics of sample collection for Human Cell Atlas or clinical studies since it increases the time frames for sample processing.
In recent years, functional genomics approaches combining genetic information with bulk RNA-sequencing data have identified the downstream expression effects of disease-associated genetic risk ...factors through so-called expression quantitative trait locus (eQTL) analysis. Single-cell RNA-sequencing creates enormous opportunities for mapping eQTLs across different cell types and in dynamic processes, many of which are obscured when using bulk methods. Rapid increase in throughput and reduction in cost per cell now allow this technology to be applied to large-scale population genetics studies. To fully leverage these emerging data resources, we have founded the single-cell eQTLGen consortium (sc-eQTLGen), aimed at pinpointing the cellular contexts in which disease-causing genetic variants affect gene expression. Here, we outline the goals, approach and potential utility of the sc-eQTLGen consortium. We also provide a set of study design considerations for future single-cell eQTL studies.
The development of high-throughput RNA sequencing (RNA-seq) at the single-cell level has already led to profound new discoveries in biology, ranging from the identification of novel cell types to the ...study of global patterns of stochastic gene expression. Alongside the technological breakthroughs that have facilitated the large-scale generation of single-cell transcriptomic data, it is important to consider the specific computational and analytical challenges that still have to be overcome. Although some tools for analysing RNA-seq data from bulk cell populations can be readily applied to single-cell RNA-seq data, many new computational strategies are required to fully exploit this data type and to enable a comprehensive yet detailed study of gene expression at the single-cell level.
Celotno besedilo
Dostopno za:
DOBA, IJS, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SBMB, UILJ, UKNU, UL, UM, UPUK
Objectives
Ectopic fat accumulation in liver and skeletal muscle may be an essential link between abdominal obesity, insulin resistance and increased risk of cardiovascular disease after menopause. ...We hypothesized that a diet containing a relatively high content of protein and unsaturated fat mainly monounsaturated fatty acids (MUFAs) but limited carbohydrates and saturated fat would reduce lipid content in liver and muscle and increase insulin sensitivity in postmenopausal women.
Subjects
Ten healthy, nonsmoking postmenopausal women with a body mass index (BMI) >27 (28–35) kg m−2 were included in the study.
Interventions
Participants were instructed to consume an ad libitum Palaeolithic‐type diet intended to provide approximately 30 energy percentage (E%) protein, 40 E% fat (mainly MUFAs) and 30 E% carbohydrate. Intramyocellular lipid (IMCL) levels in calf muscles and liver triglyceride levels were quantified using proton magnetic resonance spectroscopy (1H‐MRS) before and 5 weeks after dietary intervention. Insulin sensitivity was estimated by homoeostasis model assessment (HOMA) indices and the euglycaemic hyperinsulinaemic clamp technique.
Results
Mean energy intake decreased by 25% with a weight loss of 4.5 kg. BMI, waist and hip circumference, waist/hip ratio and abdominal sagittal diameter also decreased significantly, as did diastolic blood pressure (mean −7 mmHg), levels of fasting serum glucose, cholesterol, triglycerides, LDL/HDL cholesterol, apolipoprotein B (ApoB) and apolipoprotein A1 (ApoA1), urinary C‐peptide and HOMA indices. Whole‐body insulin sensitivity did not change. Liver triglyceride levels decreased by 49%, whereas IMCL levels in skeletal muscle were not significantly altered.
Conclusions
A modified Palaeolithic‐type diet has strong and tissue‐specific effects on ectopic lipid deposition in postmenopausal women.
Abstract Multiplexed fluorescence in situ hybridization techniques have enabled cell-type identification, linking transcriptional heterogeneity with spatial heterogeneity of cells. However, ...inaccurate cell segmentation reduces the efficacy of cell-type identification and tissue characterization. Here, we present a method called Spot-based Spatial cell-type Analysis by Multidimensional mRNA density estimation (SSAM), a robust cell segmentation-free computational framework for identifying cell-types and tissue domains in 2D and 3D. SSAM is applicable to a variety of in situ transcriptomics techniques and capable of integrating prior knowledge of cell types. We apply SSAM to three mouse brain tissue images: the somatosensory cortex imaged by osmFISH, the hypothalamic preoptic region by MERFISH, and the visual cortex by multiplexed smFISH. Here, we show that SSAM detects regions occupied by known cell types that were previously missed and discovers new cell types.
Heart rate data collected during nonlaboratory conditions present several data-modeling challenges. First, the noise in such data is often poorly described by a simple Gaussian; it has outliers and ...errors come in bursts. Second, in large-scale studies the ECG waveform is usually not recorded in full, so one has to deal with missing information. In this paper, we propose a robust postprocessing model for such applications. Our model to infer the latent heart rate time series consists of two main components: unsupervised clustering followed by Bayesian regression. The clustering component uses auxiliary data to learn the structure of outliers and noise bursts. The subsequent Gaussian process regression model uses the cluster assignments as prior information and incorporates expert knowledge about the physiology of the heart. We apply the method to a wide range of heart rate data and obtain convincing predictions along with uncertainty estimates. In a quantitative comparison with existing postprocessing methodology, our model achieves a significant increase in performance.
Understanding the regulatory mechanisms that are responsible for an organism's response to environmental change is an important issue in molecular biology. A first and important step towards this ...goal is to detect genes whose expression levels are affected by altered external conditions. A range of methods to test for differential gene expression, both in static as well as in time-course experiments, have been proposed. While these tests answer the question whether a gene is differentially expressed, they do not explicitly address the question when a gene is differentially expressed, although this information may provide insights into the course and causal structure of regulatory programs. In this article, we propose a two-sample test for identifying intervals of differential gene expression in microarray time series. Our approach is based on Gaussian process regression, can deal with arbitrary numbers of replicates, and is robust with respect to outliers. We apply our algorithm to study the response of Arabidopsis thaliana genes to an infection by a fungal pathogen using a microarray time series dataset covering 30,336 gene probes at 24 observed time points. In classification experiments, our test compares favorably with existing methods and provides additional insights into time-dependent differential expression.
Objectives Ectopic fat accumulation in liver and skeletal muscle may be an essential link between abdominal obesity, insulin resistance and increased risk of cardiovascular disease after menopause. ...We hypothesized that a diet containing a relatively high content of protein and unsaturated fat mainly monounsaturated fatty acids (MUFAs) but limited carbohydrates and saturated fat would reduce lipid content in liver and muscle and increase insulin sensitivity in postmenopausal women.
Subjects Ten healthy, nonsmoking postmenopausal women with a body mass index (BMI) >27 (28–35) kg m −2 were included in the study.
Interventions Participants were instructed to consume an ad libitum Palaeolithic-type diet intended to provide approximately 30 energy percentage (E%) protein, 40 E% fat (mainly MUFAs) and 30 E% carbohydrate. Intramyocellular lipid (IMCL) levels in calf muscles and liver triglyceride levels were quantified using proton magnetic resonance spectroscopy ( 1 H-MRS) before and 5 weeks after dietary intervention. Insulin sensitivity was estimated by homoeostasis model assessment (HOMA) indices and the euglycaemic hyperinsulinaemic clamp technique.
Results Mean energy intake decreased by 25% with a weight loss of 4.5 kg. BMI, waist and hip circumference, waist/hip ratio and abdominal sagittal diameter also decreased significantly, as did diastolic blood pressure (mean −7 mmHg), levels of fasting serum glucose, cholesterol, triglycerides, LDL/HDL cholesterol, apolipoprotein B (ApoB) and apolipoprotein A1 (ApoA1), urinary C-peptide and HOMA indices. Whole-body insulin sensitivity did not change. Liver triglyceride levels decreased by 49%, whereas IMCL levels in skeletal muscle were not significantly altered.
Conclusions A modified Palaeolithic-type diet has strong and tissue-specific effects on ectopic lipid deposition in postmenopausal women.
PDF
