SC vs SN

Single cell RNA sequencing has revolutionized biomedical research, however it can only be applied to fresh tissues that can be effectively dissociated into intact single cells. Frozen material such as biobanked disease cohorts is cannot be dissociated, and many diseases result in highly fibrotic or stressed cells that do not survive dissociation. To rectify this issue, many disease samples are processed using single nucleus RNA sequencing which extracts nuclei directly from tissue without requiring dissociation. However, many systematic and cell-type specific differences between single-cell and single-nucleus RNA sequencing have been observed in individual tissues, hampering efforts to compare the two. What are the differences between the RNA captured by these technologies? How can we computationally correct for them? Can we learn about post-transcriptional regulation by examining cell-type specific differences?

Ambient RNA Removal

During the process of tissue dissociation many cells are damaged or destroyed releasing their RNA content into the buffer that surrounds the surviving single cells. This RNA is known as 'ambient RNA' and contaminates all cells of the sample with RNA that does not belong to the captured cell. Variabililty in this contamination confounds comparisons of diseased and normal samples leading to false-positive results. Ambient RNA is a main contributor to between sample variability which causes problems when combining samples and reduces statistical power to detect differences. Ambient RNA may also cause errors in somatic variant calling when inferring tumour evolution. How do we estimate the effect of this contamination? Which tools are effective in removing it? How can we improve ambient RNA removal?

Inferring cell-cell interactions

Cells are constantly sensing and responding to their extracellular environment and nearby cells. This 'tissue microenvironment' has proven critical to the survival and proliferation of many tumours, and the progression vs resolution of inflammation-associated diseases. Recent developments in single-cell RNA sequencing enable the full characterisation tissue microenvironment in healthy and diseased tissue. However, unravelling the specific protein, signalling and metabolic interactions that regulate and maintain tissue-specific microenvironments has proven challenging due to the sparsity of single-cell RNA sequencing detection rates and paucity of characterized signalling pathways. How can we use high-throughput data to infer signalling interactions? How do we integrate single-cell RNA sequencing data with high-resolution proteomic or metabolomic data?

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Primary Sclerosing Cholangitis

Primary Sclerosing Cholangitis (PSC) is a chronic and progressive disease of the bile ducts in the liver. The bile ducts become inflammed and constricted causing bile to become trapped inside the liver causing toxicity and fibrosis of hepatic tissues. It's causes are unknown, and cases progress over years until liver failure or cancer at which point transplant is performed. However, even after transplant PSC may return in up to 40% of cases. PSC is typically diagnosed around middle age, but can be found in teenagers and children at lower incidience. Together with the MacParland Lab at UHN, we are examining single-cell, single-nucleus and spatial transcriptomics of PSC with the goal to unravel the complex immune interactions which contribute to this disease that could be targets for novel treatments.

Billiary Atresia

Billiary Atresia (BA) is a devastating pre- and peri-natal liver disease where the bile ducts which connect the liver to the gallbladder and intestines become inflammed or fail to develop properly preventing bile from leaving the liver. Bile causes toxicity to hepatic tissues typically leading to liver failure and transplant within a few years. BA is the most common cause of liver transplant in children. Current treatment is limited to surgery to by-pass the extra-hepatic bile duct and restore bile flow to the intestines. The causes of BA are unknown, despite its congenital development it is no inherited and there have been no genetic associations found. We are working with the Taylor group at Northwestern University to use spatial transcriptomics to elucidate the spatial organization of immune populations within BA livers and changes in hepatic metabolism which may underly this disease.

Atherosclerosis

Atherosclerosis is a chronic health condition associated with higher changes of stroke and heart attacks. It is characterized by the development of fatty-lesions within blood vessels that contain dysfunctional macrophages, macromolecular debris, and transformed endothelial cells. These lesions reduce bloodflow which can damage tissues, can trigger the formation of blood clots, rupture releasing toxic debris into the bloodstream. Atherosclerosis has multiple known evironmental (dietary) and genetic risk factors. We are working with the Boffa group at the Robarts Research Institute to examine the synergy between genetic risk factors on the development of atherosclerotic plaques in a rodent model.

Soft Tissue Sarcoma

Soft tissue sarcoma (STS) is a rare but deadly cancer. These tumours are large (multiple 2-10 cm diameter) fast growing and highly heterogeneous. Treatment involves surgical resection often accompanied by radiation and/or chemotherapy, and in some cases amputation of the affected limb. Despite these treatments rates of recurrence and metastasis are high (~50%), with lung as the most frequent site of metastasis. In collaboration with the sarcoma clinical group in Toronto, we will combine whole exome sequencing with single-cell and spatial transcriptomics to elucidate the transcriptional and genetic heterogeneity of STS and examine mechanisms of resistance, recurrence, and metastasis.

Alzheimers

Alzheimers disease (AD) is an aging-related degenerative neurological disease. It is relatively common and represented a billion dollar burden on society. Alzheimers disease is characterized by the build up of amyloid-beta plaques in the brains of suffers as well as inflammation, stress and neuronal death. The underlying cause of AD is poorly understood, but studies have suggested a strong association with mitochondrial dysfunction related to APOE. We are working together with the Prado group at the Robarts Research Institute to elucidate the role of different AD-associated genetic mutations on different cell-types in a humanized mouse model using single-nucleus RNA sequencing.

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Publications

Full Publication List

Single-Cell, Single-Nucleus, and Spatial RNA Sequencing of the Human Liver Identifies Cholangiocyte and Mesenchymal Heterogeneity (2021) TS Andrews, J Atif, JC Liu, CT Perciani, XZ Ma, C Thoeni, M Slyper, ... Hepatology Communications

Tutorial: guidelines for annotating single-cell transcriptomic maps using automated and manual methods (2021) ZA Clarke, TS Andrews, J Atif, D Pouyabahar, BT Innes, SA MacParland, ... Nature protocols 16 (6), 2749-2764

Tutorial: guidelines for the computational analysis of single-cell RNA sequencing data (2021) TS Andrews, VY Kiselev, D McCarthy, M Hemberg Nature protocols 16 (1), 1-9

EmptyDrops: distinguishing cells from empty droplets in droplet-based single-cell RNA sequencing data (2019) ATL Lun, S Riesenfeld, T Andrews, T Gomes, JC Marioni Genome biology 20 (1), 1-9

The Malaria Cell Atlas: Single parasite transcriptomes across the complete Plasmodium life cycle (2019) VM Howick, AJC Russell, T Andrews, H Heaton, AJ Reid, K Natarajan, ... Science 365 (6455), eaaw2619

M3Drop: dropout-based feature selection for scRNASeq (2019) TS Andrews, M Hemberg Bioinformatics 35 (16), 2865-2867

Statistical Methods for Single-Cell RNA-Sequencing (2019) TS Andrews, V Yu. Kiselev, M Hemberg Handbook of Statistical Genomics: Two Volume Set, 735-20
Single-cell transcriptomics reveals a new dynamical function of transcription factors during embryonic hematopoiesis (2018) I Bergiers, T Andrews, ÖV Bölükbasi, A Buness, E Janosz, ... Elife 7, e29312

False signals induced by single-cell imputation (2018) TS Andrews, M Hemberg F1000Research 7

The clustering of functionally related genes contributes to CNV-mediated disease (2015) T Andrews, F Honti, R Pfundt, N De Leeuw, J Hehir-Kwa, ... Genome research 25 (6), 802-813

Gene networks underlying convergent and pleiotropic phenotypes in a large and systematically-phenotyped cohort with heterogeneous developmental disorders (2015) T Andrews, S Meader, A Vulto-van Silfhout, A Taylor, J Steinberg, ... PLoS genetics 11 (3), e1005012

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Tallulah Andrews, DPhil

Dr. Tallulah Andrews is an Assistant Professor in the Department of Biochemistry at the University of Western Ontario. Her group focuses on the integration of biological imaging and multiple -omics technologies to understand the structure of diseased tissues. She is a long-term member of the Human Cell Atlas developing computational tools for single-cell RNAseq data while a post-doc at the Wellcome Sanger Institute in Cambridge, UK and analyzing the Healthy Liver atlas in the MacParland group at UHN Research. She holds a PhD from the University of Oxford where she used systems biology approaches to identify biological pathways underlying rare genetic diseases.

Boris Tchatchoua Ngassam

Boris Tchatchoua Ngassam is a PhD student in the Collaborative Specialization in Machine Learning in Health and Biomedical Sciences, working on building machine learning models to extract biologically relevant features from spatial transcriptomics data to improve the identification and understanding of diseased tissue. He has a MSc. from the University of Milan.

Sunny Pang

Sunny Pang is a MSc student in Biochemistry. He is working on building a pipeline for the analysis of pooled mouse atherosclerosis scRNAseq data, and a meta-analysis of EMT and endothelial-immune interactions across mouse and human atherosclerosis.

Siraj Elzagallaai

Siraj Elzagallaai is a MSc student studying bioinformatics at Western University under Dr. Andrews, working on an integration method for spatial transcriptomics data. He has always had a passion working with computers as well as studying genetics. After finishing his undergraduate degree in HSP genetics, he wanted to study bioinformatics which articulates both these fields.

Jack Peplinski

Jack Peplinski is in his fourth year of a dual degree program in software engineering and business. He has previously received two NSCERC Undergraduate Summer Research Awards and performed research about using augmented reality in civil engineering and open source application development for developing countries. Jack is interested in exploring how humans’ essential need for healthcare can be met with software's scalability. Jack is working on inferring the cell-cycle in single-cell RNAseq data.

Bryan Lung

Bryan is a 4th year HSP student studying medical cell biology, he is an Undergraduate Summer Research Fellow in the Andrews Lab. His research interest involves determining the relationship between disease, injury, and embryogenesis in macrophages by analyzing single-cell datasets. In his spare time, he enjoys making music, exercising, and traveling the world!

Alex Tse

Alex is a former research assistant for the team. He has previously worked as a data analyst for BMO finical group and the AIA group, responsible for data mapping and writing programs to manage data. Alex is currently studying in University of Waterloo, pursing his bachelor of computer science.

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