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Abstract Background Infectious Salmon Anaemia Virus (ISAV) is an Orthomixovirus that represents a large problem for salmonid aquaculture worldwide. Current prevention and treatment methods are only partially effective. Genetic selection and genome engineering have the potential to develop ISAV resistant salmon stocks. Both strategies can benefit from an improved understanding of the genomic regulation of ISAV pathogenesis. Here, we used single-cell RNA sequencing of an Atlantic salmon cell line to provide the first high dimensional insight into the transcriptional landscape that underpins host-virus interaction during early ISAV infection. Results Salmon head kidney (SHK-1) cells were single-cell RNA sequenced at 24, 48 and 96 h post-ISAV challenge. At 24 h post infection, cells showed expression signatures consistent with viral entry, with genes such as PI3K, FAK or JNK being upregulated relative to uninfected cells. At 48 and 96 h, infected cells showed a clear anti-viral response, characterised by the expression of IFNA2 or IRF2. Uninfected bystander cells at 48 and 96 h also showed clear transcriptional differences, potentially suggesting paracrine signalling from infected cells. These bystander cells expressed pathways such as mRNA sensing, RNA degradation, ubiquitination or proteasome; and up-regulation of mitochondrial ribosome genes also seemed to play a role in the host response to the infection. Correlation between viral and host genes revealed novel genes potentially key for this fish-virus interaction. Conclusions This study has increased our understanding of the cellular response of Atlantic salmon during ISAV infection and revealed host-virus interactions at the cellular level. Our results highlight various potential key genes in this host-virus interaction, which can be manipulated in future functional studies to increase the resistance of Atlantic salmon to ISAV.

Background: Infectious Salmon Anaemia Virus (ISAV) is an Orthomixovirus that represents a large problem for salmonid aquaculture worldwide. Current prevention and treatment methods are only partially effective. Genetic selection and genome engineering have the potential to develop ISAV resistant salmon stocks. Both strategies can benefit from an improved understanding of the genomic regulation of ISAV pathogenesis. Here, we used single-cell RNA sequencing of an Atlantic salmon cell line to provide the first high dimensional insight into the transcriptional landscape that underpins host-virus interaction during early ISAV infection. Results: Salmon head kidney (SHK-1) cells were single-cell RNA sequenced at 24, 48 and 96 h post-ISAV challenge. At 24 h post infection, cells showed expression signatures consistent with viral entry, with genes such as PI3K, FAK or JNK being upregulated relative to uninfected cells. At 48 and 96 h, infected cells showed a clear anti-viral response, characterised by the expression of IFNA2 or IRF2. Uninfected bystander cells at 48 and 96 h also showed clear transcriptional differences, potentially suggesting paracrine signalling from infected cells. These bystander cells expressed pathways such as mRNA sensing, RNA degradation, ubiquitination or proteasome; and up-regulation of mitochondrial ribosome genes also seemed to play a role in the host response to the infection. Correlation between viral and host genes revealed novel genes potentially key for this fish-virus interaction. Conclusions: This study has increased our understanding of the cellular response of Atlantic salmon during ISAV infection and revealed host-virus interactions at the cellular level. Our results highlight various potential key genes in this host-virus interaction, which can be manipulated in future functional studies to increase the resistance of Atlantic salmon to ISAV. [ABSTRACT FROM AUTHOR]

Abstract Background Single-cell RNA sequencing (scRNA-seq) has led to remarkable progress in our understanding of tissue heterogeneity in health and disease. Recently, the need for scRNA-seq sample fixation has emerged in many scenarios, such as when samples need long-term transportation, or when experiments need to be temporally synchronized. Methanol fixation is a simple and gentle method that has been routinely applied in scRNA-sEq. Yet, concerns remain that fixation may result in biases which may change the RNA-seq outcome. Results We adapted an existing methanol fixation protocol and performed scRNA-seq on both live and methanol fixed cells. Analyses of the results show methanol fixation can faithfully preserve biological related signals, while the discrepancy caused by fixation is subtle and relevant to library construction methods. By grouping transcripts based on their lengths and GC content, we find that transcripts with different features are affected by fixation to different degrees in full-length sequencing data, while the effect is alleviated in Drop-seq result. Conclusions Our deep analysis reveals the effects of methanol fixation on sample RNA integrity and elucidates the potential consequences of using fixation in various scRNA-seq experiment designs.

Abstract Background CCCTC-Binding Factor (CTCF), also known as 11-zinc finger protein, participates in many cellular processes, including insulator activity, transcriptional regulation and organization of chromatin architecture. Based on single cell flow cytometry and single cell RNA-FISH analyses, our previous study showed that deletion of CTCF binding site led to a significantly increase of cellular variation of its target gene. However, the effect of CTCF on genome-wide landscape of cell-to-cell variation remains unclear. Results We knocked down CTCF in EL4 cells using shRNA, and conducted single cell RNA-seq on both wild type (WT) cells and CTCF-Knockdown (CTCF-KD) cells using Fluidigm C1 system. Principal component analysis of single cell RNA-seq data showed that WT and CTCF-KD cells concentrated in two different clusters on PC1, indicating that gene expression profiles of WT and CTCF-KD cells were systematically different. Interestingly, GO terms including regulation of transcription, DNA binding, zinc finger and transcription factor binding were significantly enriched in CTCF-KD-specific highly variable genes, implying tissue-specific genes such as transcription factors were highly sensitive to CTCF level. The dysregulation of transcription factors potentially explains why knockdown of CTCF leads to systematic change of gene expression. In contrast, housekeeping genes such as rRNA processing, DNA repair and tRNA processing were significantly enriched in WT-specific highly variable genes, potentially due to a higher cellular variation of cell activity in WT cells compared to CTCF-KD cells. We further found that cellular variation-increased genes were significantly enriched in down-regulated genes, indicating CTCF knockdown simultaneously reduced the expression levels and increased the expression noise of its regulated genes. Conclusions To our knowledge, this is the first attempt to explore genome-wide landscape of cellular variation after CTCF knockdown. Our study not only advances our understanding of CTCF function in maintaining gene expression and reducing expression noise, but also provides a framework for examining gene function.

Background: Single-cell RNA sequencing (scRNA-seq) has led to remarkable progress in our understanding of tissue heterogeneity in health and disease. Recently, the need for scRNA-seq sample fixation has emerged in many scenarios, such as when samples need long-term transportation, or when experiments need to be temporally synchronized. Methanol fixation is a simple and gentle method that has been routinely applied in scRNA-sEq. Yet, concerns remain that fixation may result in biases which may change the RNA-seq outcome. Results: We adapted an existing methanol fixation protocol and performed scRNA-seq on both live and methanol fixed cells. Analyses of the results show methanol fixation can faithfully preserve biological related signals, while the discrepancy caused by fixation is subtle and relevant to library construction methods. By grouping transcripts based on their lengths and GC content, we find that transcripts with different features are affected by fixation to different degrees in full-length sequencing data, while the effect is alleviated in Drop-seq result. Conclusions: Our deep analysis reveals the effects of methanol fixation on sample RNA integrity and elucidates the potential consequences of using fixation in various scRNA-seq experiment designs. [ABSTRACT FROM AUTHOR]

Abstract Background Single cell transcriptomics is critical for understanding cellular heterogeneity and identification of novel cell types. Leveraging the recent advances in single cell RNA sequencing (scRNA-Seq) technology requires novel unsupervised clustering algorithms that are robust to high levels of technical and biological noise and scale to datasets of millions of cells. Results We present novel computational approaches for clustering scRNA-seq data based on the Term Frequency - Inverse Document Frequency (TF-IDF) transformation that has been successfully used in the field of text analysis. Conclusions Empirical experimental results show that TF-IDF methods consistently outperform commonly used scRNA-Seq clustering approaches.

Background: CCCTC-Binding Factor (CTCF), also known as 11-zinc finger protein, participates in many cellular processes, including insulator activity, transcriptional regulation and organization of chromatin architecture. Based on single cell flow cytometry and single cell RNA-FISH analyses, our previous study showed that deletion of CTCF binding site led to a significantly increase of cellular variation of its target gene. However, the effect of CTCF on genome-wide landscape of cell-to-cell variation remains unclear. Results: We knocked down CTCF in EL4 cells using shRNA, and conducted single cell RNA-seq on both wild type (WT) cells and CTCF-Knockdown (CTCF-KD) cells using Fluidigm C1 system. Principal component analysis of single cell RNA-seq data showed that WT and CTCF-KD cells concentrated in two different clusters on PC1, indicating that gene expression profiles of WT and CTCF-KD cells were systematically different. Interestingly, GO terms including regulation of transcription, DNA binding, zinc finger and transcription factor binding were significantly enriched in CTCF-KD-specific highly variable genes, implying tissue-specific genes such as transcription factors were highly sensitive to CTCF level. The dysregulation of transcription factors potentially explains why knockdown of CTCF leads to systematic change of gene expression. In contrast, housekeeping genes such as rRNA processing, DNA repair and tRNA processing were significantly enriched in WT-specific highly variable genes, potentially due to a higher cellular variation of cell activity in WT cells compared to CTCF-KD cells. We further found that cellular variation-increased genes were significantly enriched in down-regulated genes, indicating CTCF knockdown simultaneously reduced the expression levels and increased the expression noise of its regulated genes. Conclusions: To our knowledge, this is the first attempt to explore genome-wide landscape of cellular variation after CTCF knockdown. Our study not only advances our understanding of CTCF function in maintaining gene expression and reducing expression noise, but also provides a framework for examining gene function. [ABSTRACT FROM AUTHOR]

Background: Single cell transcriptomics is critical for understanding cellular heterogeneity and identification of novel cell types. Leveraging the recent advances in single cell RNA sequencing (scRNA-Seq) technology requires novel unsupervised clustering algorithms that are robust to high levels of technical and biological noise and scale to datasets of millions of cells. Results: We present novel computational approaches for clustering scRNA-seq data based on the Term Frequency - Inverse Document Frequency (TF-IDF) transformation that has been successfully used in the field of text analysis. Conclusions: Empirical experimental results show that TF-IDF methods consistently outperform commonly used scRNA-Seq clustering approaches. [ABSTRACT FROM AUTHOR]