scholarly journals Batch effects and the effective design of single-cell gene expression studies

2016 ◽  
Author(s):  
Po-Yuan Tung ◽  
John D. Blischak ◽  
Chiaowen Joyce Hsiao ◽  
David A. Knowles ◽  
Jonathan E. Burnett ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Induced Pluripotent Stem Cell ◽  
Expression Levels ◽  
Amplification Bias ◽  
Expression Studies ◽  
Cell Gene Expression ◽  
Gene Expression Studies ◽  
Induced Pluripotent ◽  
Gene Expression Levels

AbstractSingle cell RNA sequencing (scRNA-seq) can be used to characterize variation in gene expression levels at high resolution. However, the sources of experimental noise in scRNA-seq are not yet well understood. We investigated the technical variation associated with sample processing using the single cell Fluidigm C1 platform. To do so, we processed three C1 replicates from three human induced pluripotent stem cell (iPSC) lines. We added unique molecular identifiers (UMIs) to all samples, to account for amplification bias. We found that the major source of variation in the gene expression data was driven by genotype, but we also observed substantial variation between the technical replicates. We observed that the conversion of reads to molecules using the UMIs was impacted by both biological and technical variation, indicating that UMI counts are not an unbiased estimator of gene expression levels. Based on our results, we suggest a framework for effective scRNA-seq studies.

scholarly journals Batch effects and the effective design of single-cell gene expression studies

2017 ◽  
Vol 7 (1) ◽  
Author(s):  
Po-Yuan Tung ◽  
John D. Blischak ◽  
Chiaowen Joyce Hsiao ◽  
David A. Knowles ◽  
Jonathan E. Burnett ◽  
...  
Keyword(s):  
Gene Expression ◽  
Single Cell ◽  
Batch Effects ◽  
Expression Studies ◽  
Cell Gene Expression ◽  
Gene Expression Studies ◽  
Cell Gene ◽  
Effective Design

scholarly journals Single cell genomic characterization reveals the cellular reprogramming of the gastric tumor microenvironment

2019 ◽  
Author(s):  
Anuja Sathe ◽  
Sue Grimes ◽  
Billy T. Lau ◽  
Jiamin Chen ◽  
Carlos Suarez ◽  
...  
Keyword(s):  
Gene Expression ◽  
Tumor Microenvironment ◽  
Single Cell ◽  
Normal Tissue ◽  
Gene Expression Program ◽  
Expression Studies ◽  
Cell Gene Expression ◽  
Gene Expression Studies ◽  
Expression Program ◽  
Cell Gene

ABSTRACTPurposeThe tumor microenvironment (TME) consists of a heterogenous cellular milieu that can influence cancer cell behavior. The characteristics of the cellular TME have a dramatic impact on treatments such as immunotherapy. These features can be revealed with single-cell RNA sequencing (scRNA-seq). We hypothesized that single cell gene expression studies of gastric cancer (GC) together with paired normal tissue and peripheral blood mononuclear cells (PBMCs) would identify critical elements of cellular dysregulation not apparent with other approaches.MethodsSingle cell gene expression studies were conducted on seven patients with GC and one patient with intestinal metaplasia. We sequenced 56,167 cells comprising GC (32,407 cells), paired normal tissue (18,657 cells) and PBMCs (5,103 cells). Protein expression of genes of interest was validated by multiplex immunofluorescence.ResultsTumor epithelium had copy number alterations and a distinct gene expression program compared to normal with intra-tumor heterogeneity. The GC TME was significantly enriched for stromal cells, macrophages, dendritic cells (DCs) and Tregs. TME-exclusive stromal cells expressed extracellular matrix components distinct from normal tissue. Macrophages were transcriptionally heterogenous and did not conform to a binary M1/M2 paradigm. Gene expression program of tumor DCs was unique from PBMC DCs. TME-specific cytotoxic T cells comprised of two exhausted heterogenous subsets. Helper, cytotoxic T, Treg and NK cells expressed multiple immune checkpoint or costimulatory molecules. Receptor-ligand analysis revealed TME-exclusive inter-cellular communication.ConclusionsSingle cell gene expression studies revealed widespread reprogramming across multiple cellular elements in the milieu of the GC TME. Cellular remodeling was delineated by changes in cell numbers, transcriptional states and inter-cellular interactions. This characterization facilitates understanding of tumor biology and enables the identification of novel molecular targets including for cancer immunotherapy.STATEMENT OF TRANSLATIONAL RELEVANCEWe leveraged the power of single-cell genomics to characterize the heterogenous cell types and states in the tumor microenvironment (TME). By profiling thousands of single cells from surgical resections of gastric cancer together with paired normal mucosa and peripheral blood mononuclear cells (PBMCs), we determined the deviations in the TME from physiological conditions. Our analysis revealed a cellular reprogramming of the TME compared to normal mucosa in immune and stromal lineages. We detected transcriptional heterogeneity within macrophages and a TME-specific gene expression program in dendritic cells. Cytotoxic T cells in the TME had heterogenous profiles of exhaustion and expression of multiple immune checkpoint and costimulatory molecules. We constructed a receptor-ligand based inter-cellular communications network that was exclusive to tumor tissue. These discoveries provide information at a highly granular cellular resolution enabling advances in cancer biology, biomarker discovery and identification of treatment targets such as for immunotherapy.

scholarly journals Automated cell cycle and cell size measurements for single-cell gene expression studies

2018 ◽  
Vol 11 (1) ◽  
Author(s):  
Anissa Guillemin ◽  
Angélique Richard ◽  
Sandrine Gonin-Giraud ◽  
Olivier Gandrillon
Keyword(s):  
Gene Expression ◽  
Cell Cycle ◽  
Single Cell ◽  
Cell Size ◽  
Expression Studies ◽  
Cell Gene Expression ◽  
Gene Expression Studies ◽  
Cell Gene

scholarly journals Validation of Suitable Reference Genes for Gene Expression Studies on Yak Testis Development

Animals ◽  
2020 ◽  
Vol 10 (2) ◽  
pp. 182 ◽  
Author(s):  
Xuelan Zhou ◽  
Xiaoyun Wu ◽  
Min Chu ◽  
Chunnian Liang ◽  
Xuezhi Ding ◽  
...  
Keyword(s):  
Gene Expression ◽  
Candidate Genes ◽  
Reference Genes ◽  
Developmental Stages ◽  
Immature Stages ◽  
Expression Levels ◽  
Testis Development ◽  
Expression Studies ◽  
Gene Expression Studies ◽  
Gene Expression Levels

Testis has an important function in male reproduction. Its development is regulated by a large number of genes. The real-time reserve transcriptase-quantitative polymerase chain reaction (RT-qPCR) is a useful tool to evaluate the gene expression levels. However, unsuitable reference genes (RGs) can cause the misinterpretation of gene expression levels. Unfortunately, the ideal RGs for yak testis development are yet to be studied. In this study, 13 commonly used RGs were selected to identify the most stable RGs in yak testis at four different developmental stages, including two immature stages (6 months and 18 months) and two mature stages (30 months and 6 years). This study used GeNorm, NormFinder, BestKeeper, ∆Ct, and RefFinder programs to evaluate the stability of 13 candidate genes. The results of RefFinder showed that the stabilities of TATA box-binding protein (TBP) and ubiquitously expressed transcript protein (UXT) were ranked the top two across all developmental stages. TBP and hydroxymethylbilane synthase (HMBS) were stably expressed in immature stages, while mitochondrial ribosomal protein L39 (MRPL39) and TBP had higher stability than other candidate genes in mature stages. This study provided valuable information for gene expression studies to assist further investigation on the molecular mechanisms in underlying yak testis development.

Expression of Factors in the Hepatocyte Growth Factor (HGF) Pathway in Whole Bone Marrow Biopsies in Association to the Osteolytic Bone Disease of Multiple Myeloma

Blood ◽  
2012 ◽  
Vol 120 (21) ◽  
pp. 3977-3977
Author(s):  
Ida Bruun Kristensen ◽  
Jacob Haaber ◽  
Maria B Lyng ◽  
Lise Pedersen ◽  
Lars Melholt Rasmussen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Protein Level ◽  
Expression Levels ◽  
Protein Levels ◽  
Spearman's Rho ◽  
Spearman’S Rho ◽  
Osteolytic Bone Disease ◽  
Gene Expression Studies ◽  
Novel Strategy ◽  
Gene Expression Levels

Abstract Abstract 3977 Osteolytic bone disease (OBD) in multiple myeloma (MM) is known to be caused by a combination of osteoclast hyperactivation and osteoblast inhibition. One of the pathways known to be involved in osteoblast inhibition from in vitro studies is the HGF pathway consisting of HGF, its receptor MET, the co-receptor Syndecan-1 (SDC-1), the partial MET antagonist Decorin and HGF activator responsible for HGF processing to its active form. So far, gene expression studies in MM have been performed on isolated MM plasma cells or bone marrow (BM) aspirates, which are not completely representative of the cell composition in the BM micro-environment. We used a novel strategy, whereby gene expression of factors associated with the HGF pathway was evaluated in snap-frozen BM biopsies, and moreover we determined the protein levels in matched BM plasma samples. An additional BM core biopsy obtained during the diagnostic procedure of MM patients was snap-frozen. Biopsies were cut, homogenized and RNA was purified and analyzed by qRT-PCR using low density arrays (Applied Biosystems). The relative quantitative gene expression was calculated using 3 internal reference genes (ABL, GAPDH and GUS). OBD was evaluated using standard radiographs. All patients were untreated and did not receive medicine that could influence bone remodeling. We examined 10 healthy volunteers (HV), 35 monoclonal gammopathy of unknown significance (MGUS) and 65 untreated MM patients, which according to radiographic findings were divided into NO/LOW and advanced OBD, i.e. OBD in ≥2 regions. ELISA was performed on a total of 31 matched BM plasma samples of HV, MGUS and MM obtained at the same time point as the biopsies. In addition, extra samples without gene data (N=52) were analyzed. Commercial kits for SDC-1 (Diaclone), HGF (RnD, Quantikine) and Decorin (RnD, Duoset) were run in duplicates according to manufacturer's instructions. Gene expression of HGF, SDC1, and MET were significantly different comparing HV, MGUS, no/low and advanced OBD (p<0.05) (For HGF, see figure 1). Decorin was not associated to OBD. HGF activator was not expressed in any of our samples, but only in the positive control. A significant correlation between gene and protein expression levels measured by ELISA was found for SDC-1 (Spearman's rho= 0.463, p=0.0058) and HGF (Spearman's rho=0.45, p=0.01). No correlation was found between Decorin gene levels and BM plasma levels (Spearman's rho =-0.24, p=0.22). The protein level of SDC-1 and HGF in BM plasma were both upregulated in MM and associated significantly to OBD level (p<0.05), while Decorin were significantly downregulated in MGUS and MM samples compared to HVs (p<0.05). A significant difference in HGF BM plasma levels were found between patients with no/limited OBD (median: 1.7ng/mL) and advanced OBD (median: 6.2ng/mL) in BM plasma. In our expression study reflecting the in vivo situation in MM patients, genes in the HGF pathway and proteins were significantly associated to OBD. The use of whole snap-frozen BM biopsies is a novel strategy for evaluation of gene expression in MM making it possible to investigate patients independent of degree of MM plasma cell infiltration. In addition to the dys-regulated gene expression levels alteration of SDC-1 and HGF was also observed at protein level, supporting the gene expression findings, and underscoring the usefulness of BM biopsies for gene expression studies in MM. Furthermore, our study for the first time shows up regulation of HGF in association with OBD at both gene and protein level in a large clinical material. Figure 1A. HGF Gene Expression levels in whole snap-frozen BM biopsies. Figure 1B. HGF protein levels in BM plasma (pg/mL). 1 = HV, 2 = MGUS, 3 = no/low OBD MM, 4 = advanced OBD MM. Figure 1A. HGF Gene Expression levels in whole snap-frozen BM biopsies. Figure 1B. HGF protein levels in BM plasma (pg/mL). 1 = HV, 2 = MGUS, 3 = no/low OBD MM, 4 = advanced OBD MM. Disclosures: No relevant conflicts of interest to declare.

Identification of reference genes for gene expression studies during seed germination and seedling establishment in Ricinus communis L.

2014 ◽  
Vol 24 (4) ◽  
pp. 341-352 ◽  
Author(s):  
Paulo R. Ribeiro ◽  
Bas J. W. Dekkers ◽  
Luzimar G. Fernandez ◽  
Renato D. de Castro ◽  
Wilco Ligterink ◽  
...  
Keyword(s):  
Gene Expression ◽  
Seed Germination ◽  
Reference Genes ◽  
Target Genes ◽  
Ricinus Communis ◽  
Quantitative Polymerase Chain Reaction ◽  
Optimal Combination ◽  
Expression Levels ◽  
Gene Expression Studies ◽  
Gene Expression Levels

AbstractReverse transcription-quantitative polymerase chain reaction (RT-qPCR) is an important technology to analyse gene expression levels during plant development or in response to different treatments. An important requirement to measure gene expression levels accurately is a properly validated set of reference genes. In this context, we analysed the potential use of 17 candidate reference genes across a diverse set of samples, including several tissues, different stages and environmental conditions, encompassing seed germination and seedling growth in Ricinus communis L. These genes were tested by RT-qPCR and ranked according to the stability of their expression using two different approaches: GeNorm and NormFinder. GeNorm and Normfinder indicated that ACT, POB and PP2AA1 comprise the optimal combination for normalization of gene expression data in inter-tissue (heterogeneous sample panel) studies. We also describe the optimal combination of reference genes for a subset of root, endosperm and cotyledon samples. In general, the most stable genes suggested by GeNorm are very consistent with those indicated by NormFinder, which highlights the strength of the selection of reference genes in our study. We also validated the selected reference genes by normalizing the expression levels of three target genes involved in energy metabolism with the reference genes suggested by GeNorm and NormFinder. The approach used in this study to identify stably expressed genes, and thus potential reference genes, was applied successfully for R. communis and it provides important guidelines for RT-qPCR studies in seeds and seedlings for other species (especially in those cases where extensive microarray data are not available).

scholarly journals Single Cell Sequencing of Induced Pluripotent Stem Cell Derived Retinal Ganglion Cells (iPSC-RGC) Reveals Distinct Molecular Signatures and RGC Subtypes

Genes ◽  
2021 ◽  
Vol 12 (12) ◽  
pp. 2015
Author(s):  
Harini V. Gudiseva ◽  
Vrathasha Vrathasha ◽  
Jie He ◽  
Devesh Bungatavula ◽  
Joan M. O’Brien ◽  
...  
Keyword(s):  
Gene Expression ◽  
Stem Cell ◽  
Single Cell ◽  
Retinal Ganglion Cells ◽  
Pluripotent Stem Cell ◽  
Ganglion Cells ◽  
Induced Pluripotent Stem Cell ◽  
Retinal Ganglion ◽  
Single Cell Sequencing ◽  
Induced Pluripotent

We intend to identify marker genes with differential gene expression (DEG) and RGC subtypes in cultures of human-induced pluripotent stem cell (iPSC)-derived retinal ganglion cells. Single-cell sequencing was performed on mature and functional iPSC-RGCs at day 40 using Chromium Single Cell 3’ V3 protocols (10X Genomics). Sequencing libraries were run on Illumina Novaseq to generate 150 PE reads. Demultiplexed FASTQ files were mapped to the hg38 reference genome using the STAR package, and cluster analyses were performed using a cell ranger and BBrowser2 software. QC analysis was performed by removing the reads corresponding to ribosomal and mitochondrial genes, as well as cells that had less than 1X mean absolute deviation (MAD), resulting in 4705 cells that were used for further analyses. Cells were separated into clusters based on the gene expression normalization via PCA and TSNE analyses using the Seurat tool and/or Louvain clustering when using BBrowser2 software. DEG analysis identified subsets of RGCs with markers like MAP2, RBPMS, TUJ1, BRN3A, SOX4, TUBB3, SNCG, PAX6 and NRN1 in iPSC-RGCs. Differential expression analysis between separate clusters identified significant DEG transcripts associated with cell cycle, neuron regulatory networks, protein kinases, calcium signaling, growth factor hormones, and homeobox transcription factors. Further cluster refinement identified RGC diversity and subtype specification within iPSC-RGCs. DEGs can be used as biomarkers for RGC subtype classification, which will allow screening model systems that represent a spectrum of diseases with RGC pathology.

Abstract P069: White Cell Gene Expression Related To Immune Function And Cumulative Blood Pressure During Young Adulthood And Middle Age: Coronary Artery Risk Development In Young Adults (CARDIA)

Circulation ◽  
2021 ◽  
Vol 143 (Suppl_1) ◽  
Author(s):  
Myron D Gross ◽  
Bharat Thyagarajan ◽  
Sithara Vivek ◽  
David R Jacobs
Keyword(s):  
Oxidative Stress ◽  
Gene Expression ◽  
Blood Pressure ◽  
Middle Age ◽  
Public Health Problem ◽  
Antihypertensive Medications ◽  
Expression Levels ◽  
Cell Gene Expression ◽  
Cell Gene ◽  
Gene Expression Levels

Introduction: High blood pressure (BP) is a global public health problem that is strongly associated with many aspects of cardiovascular disease. Approximately 90% of hypertension cases have unknown cause. Studies of white blood cell gene expression may help to clarify the pathobiology. Methods: Gene expression (25 genes) was assayed in CARDIA at the Year 25 Exam (N=3,074 black and white men and women in 4 US cities, examined in 2010-2011, age 42-56 years). Whole blood was collected in PAXgene Blood RNA tubes; mRNA was isolated using the PAXgene Blood RNA kit (Qiagen Inc., Germantown, MD). The nCounter analysis system (Nanostring Inc., Seattle, WA) was used to measure expression of 25 genes related to inflammation and oxidative stress. Gene expression levels were logarithmically (base 2) transformed to approximate a normal distribution, so 1 unit higher represents doubling of the expression. Average cumulative sitting rest BP exposure was calculated (N=2,823) as the time weighted average across ≥5 BP measurements among 9 CARDIA exams with ≥1 measurement in each of Set 1 Years 0, 2, 5, 7; Set 2 Years 10, 15; and Set 3 Years 20, 25, 30. We added 10 mmHg to the systolic BP and 5 mmHg to the diastolic BP at visits in which antihypertensive medications were used. Linear regression estimated associations between dependent variables cumulative systolic and diastolic BP and each of the 25 gene expression levels, adjusting for age, race, sex, clinic, and year 25 body mass index. Hypertension at year 25 was defined as BP >140/90 mmHg or taking antihypertensive medications and pre-hypertension at year 25 was defined as BP between 121-139/81-90 mmHg, not taking antihypertensive medications. Unconditional logistic regression models were used to estimate the cross sectional association between hypertension and gene expression after adjusting for the covariates mentioned above. Results: The mean ± standard deviation for cumulative systolic BP was 113±11 mm Hg and for cumulative diastolic BP was 72±8 mmHg. NADH Dehydrogenase [Ubiquinone] 1 Beta Subcomplex Subunit 3 ( NDUFB3) , a mitochondrial gene involved in the electron transport chain was significantly associated with both cumulative systolic (β=1.549; p<0.0001) and diastolic BP measures (β=1.281 mmHg/1 log 2 unit of expression; p<0.0001), even after Bonferroni correction. Other genes had weaker signals. Consistent with these observations, hypertension (n=898) at year 25 (OR: 1.737; p<0.001) and pre-hypertension (n=1,127) at year 25 (OR:1.288; p=0.005) were also associated with increased NDUFB3 expression. Conclusions: Expression of the NDUFB3 gene, an element of oxidative stress, was associated with BP assessed throughout young adult and middle age and with concurrent hypertension.

A reverse transcriptase-polymerase chain reaction assay for gene expression studies at the single cell level

Plant Science ◽  
1996 ◽  
Vol 114 (1) ◽  
pp. 93-99 ◽  
Author(s):  
Jean Richert ◽  
Erhard Kranz ◽  
Horst Lörz ◽  
Thomas Dresselhaus
Keyword(s):  
Gene Expression ◽  
Polymerase Chain Reaction ◽  
Single Cell ◽  
Polymerase Chain Reaction Assay ◽  
Single Cell Level ◽  
Cell Level ◽  
Chain Reaction ◽  
Expression Studies ◽  
Polymerase Chain ◽  
Gene Expression Studies
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