Anti-bias training for (sc)RNA-seq: experimental and computational approaches to improve precision

Davies, P. S. W.; Jones, Molly Morgan; Liu, Juntai; Hebenstreit, Daniel

doi:10.1093/bib/bbab148

Cited by 10 publications

(8 citation statements)

References 142 publications

(177 reference statements)

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“…A cell is defined as having >500 features (genes) detected. Transcriptome coverage is known to be less extensive in scRNA-seq, with a bias towards detecting longer and more highly expressed transcripts ( Macosko et al, 2015 ; Phipson et al, 2017 ; Davies et al, 2021 ). A low-expressing cell or one expressing short transcripts such as transcription factors (TFs), then, could be erroneously removed from analysis as an artifact.…”

Section: Resultsmentioning

confidence: 99%

Comparative Toxicotranscriptomics of Single Cell RNA-Seq and Conventional RNA-Seq in TCDD-Exposed Testicular Tissue

et al. 2022

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In this report, we compare the outcomes and limitations of two methods of transcriptomic inquiry on adult zebrafish testes exposed to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) during sexual differentiation: conventional or bulk RNA-seq (bulk-seq) and single cell RNA sequencing (scRNA-seq) data. scRNA-seq has emerged as a valuable tool for uncovering cell type-specific transcriptome dynamics which exist in heterogeneous tissue. Our lab previously showed the toxicological value of the scRNA-seq pipeline to characterize the sequelae of TCDD exposure in testes, demonstrating that loss of spermatids and spermatozoa, but not other cell types, contributed to the pathology of infertility in adult male zebrafish exposed during sexual differentiation. To investigate the potential for technical artifacts in scRNA-seq such as cell dissociation effects and reduced transcriptome coverage, we compared bulk-sequenced and scRNA-seq-paired samples from control and TCDD-exposed samples to understand what is gained and lost in scRNA-seq vs bulk-seq, both transcriptomically and toxicologically. We hypothesized that the testes may be sensitive to tissue disruption as they contain multiple cell types under constant division and/or maturation, and that TCDD exposure may mediate the extent of sensitivity. Thus, we sought to understand the extent to which this dissociation impacts the toxicological value of data returned from scRNA-seq. We confirm that the required dissociation of individual cells from intact tissue has a significant impact on gene expression, affecting gene pathways with the potential to confound toxicogenomics studies on exposures if findings are not well-controlled and well-situated in context. Additionally, a common scRNA-seq method using cDNA amplified from the 3’ end of mRNA under-detects low-expressing transcripts including transcription factors. We confirm this, and show TCDD-related genes may be overlooked by scRNA-seq, however, this under-detection effect is not mediated by TCDD exposure. Even so, scRNA-seq generally extracted toxicologically relevant information better than the bulk-seq method in the present study. This report aims to inform future experimental design for transcriptomic investigation in the growing field of toxicogenomics by demonstrating the differential information extracted from sequencing cells—despite being from the same tissue and exposure scheme—is influenced by the specific protocol used, with implications for the interpretation of exposure-induced risk.

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Section: Resultsmentioning

confidence: 99%

Comparative Toxicotranscriptomics of Single Cell RNA-Seq and Conventional RNA-Seq in TCDD-Exposed Testicular Tissue

et al. 2022

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“…Sun and Zhang [57] used allele-specific expressions in diploid cells and intrinsic and extrinsic noise decomposition to study the genetic factors affecting gene expression noise. We also note that more detailed mechanistic models of RNA-sequencing protocols can help to explain more of the technical noise and biases in the data [14, 64, 65, 66, 67].…”

Section: Discussionmentioning

confidence: 99%

Modelling capture efficiency of single cell RNA-sequencing data improves inference of transcriptome-wide burst kinetics

Tang

Jørgensen

Marguerat

et al. 2023

Preprint

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Gene expression is characterised by stochastic bursts of transcription that occur at brief and random periods of promoter activity. The kinetics of gene expression burstiness differs across the genome and is dependent on the promoter sequence, among other factors. Single-cell RNA sequencing (scRNA-seq) has made it possible to quantify the cell-to-cell variability in transcription at a global genome-wide level. However, scRNA-seq data is prone to technical variability, including low and variable capture efficiency of transcripts from individual cells. Here, we propose a novel mathematical theory for the observed variability in scRNA-seq data. Our method captures burst kinetics and variability in both cell size and capture efficiency, which allows us to propose several likelihood-based and simulation-based methods for the inference of burst kinetics from scRNA-seq data. Using both synthetic and real data, we show that the simulation-based methods provide an accurate, robust and flexible tool for inferring burst kinetics from scRNA-seq data. In particular, in supervised manner, a simulation-based inference method based on neural networks proves to be accurate and useful in application to both allele and non-allele specific scRNA-seq data.

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Section: Platelet Rnas Are Informative On the Cancer Diagnostics Journeymentioning

confidence: 99%

“…[142] However, in the validation phase, the insufficient Se and precision of RNA-seq for specific genes might lead to biased results, whereas quantitative PCR with a rigorous stepwise process or digital PCR could provide precise and quantitative data. [103,[143][144][145][146] [104] SNORD55 qRT-PCR 91 189 Se = 91.2%, Sp = 49.7%, AUC = 0.784 Best [101] 1000 genes RNA-seq 53 53 Se = 81.3%, Sp = 75.5%, AUC = 0.890 Lung cancer…”

Section: Myeloproliferative Neoplasmsmentioning

confidence: 99%

A narrative review for platelets and their RNAs in cancers: New concepts and clinical perspectives

Xiang

Xiang²,

Zhang

et al. 2022

Medicine

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Recent years have witnessed a growing body of evidence suggesting that platelets are involved in several stages of the metastatic process via direct or indirect interactions with cancer cells, contributing to the progression of neoplastic malignancies. Cancer cells can dynamically exchange components with platelets in and out of blood vessels, and directly phagocytose platelets to hijack their proteome, transcriptome, and secretome, or be remotely regulated by metabolites or microparticles released by platelets, resulting in phenotypic, genetic, and functional modifications. Moreover, platelet interactions with stromal and immune cells in the tumor microenvironment lead to alterations in their components, including the ribonucleic acid (RNA) profile, and complicate the impact of platelets on cancers. A deeper understanding of the roles of platelets and their RNAs in cancer will contribute to the development of anticancer strategies and the optimization of clinical management. Encouragingly, advances in high-throughput sequencing, bioinformatics data analysis, and machine learning have allowed scientists to explore the potential of platelet RNAs for cancer diagnosis, prognosis, and guiding treatment. However, the clinical application of this technique remains controversial and requires larger, multicenter studies with standardized protocols. Here, we integrate the latest evidence to provide a broader insight into the role of platelets in cancer progression and management, and propose standardized recommendations for the clinical utility of platelet RNAs to facilitate translation and benefit patients.

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Anti-bias training for (sc)RNA-seq: experimental and computational approaches to improve precision

Cited by 10 publications

References 142 publications

Comparative Toxicotranscriptomics of Single Cell RNA-Seq and Conventional RNA-Seq in TCDD-Exposed Testicular Tissue

Comparative Toxicotranscriptomics of Single Cell RNA-Seq and Conventional RNA-Seq in TCDD-Exposed Testicular Tissue

Modelling capture efficiency of single cell RNA-sequencing data improves inference of transcriptome-wide burst kinetics

A narrative review for platelets and their RNAs in cancers: New concepts and clinical perspectives

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