Malaria Cell Atlas
The Malaria Cell Atlas is an active project led by the Lawniczak lab to provide an interactive data resource of single cell transcriptomic data across the full lifecycle of malaria parasites.
Overview of MCA
Nearly half of the world’s population remains at risk for malaria with 228 million reported cases in 2018 and over 400,000 deaths. Understanding transcriptional diversity across the lifecycle under different disease settings will help in the fight to eliminate and eventually eradicate this disease.
The MCA includes data from multiple collaborative projects (more details below), and more are in the works. Currently, it includes data from our eLife, SCIENCE and NatureComms papers, which describe methods we have used and optimised to generate single cell transcriptomes for malaria parasites as well as unpublished data. Our Atlas includes single cell RNA-sequencing data covering all stages of the life cycle in both Anopheles vector and mammalian host tissues, spans both cell sorting and droplet-based scRNAseq and includes five Plasmodium species, including four human pathogens. It also includes the first single cell data from parasites isolated directly from clinical samples.
In the MCA, users can explore how genes are expressed over thousands of individual parasites from several different Plasmodium species and across all life stages. We aim for this tool to be beneficial to all malaria researchers, from those focused on particular gene families, to those developing novel drugs and vaccines.
If you have suggestions for improvement, please get in touch at firstname.lastname@example.org
Papers, collaborators, data summaries, and raw data are linked to for the MCA instalments below.
Papers & Datasets
MCA NatureComms paper: Collaborators on this instalment of the atlas, which includes SmartSeq2 data for all P. falciparum stages were Eliana Real, Virginia Howick, Farah Dahalan, Kathrin Witmer, Juliana Cudini, Clare Andradi-Brown, Mira Davidson, Sunil Kumar Dogga, and Jake Baum
MCA NatureComms raw data: https://www.ebi.ac.uk/ena/browser/view/PRJEB40487
MCA Science paper: Collaborators on this instalment of the atlas, which includes SmartSeq2 data examining the full life cycle stages of P. berghei as well as 10x studies on the asexual stages of P. falciparum, P. knowlesi, and P. berghei were Virginia Howick, Andrew Russell, Tallulah Andrews, Haynes Heaton, Adam Reid, Kedar Natarajan, Hellen Butungi, Tom Metcalf, Lisa Verzier, Julian Rayner, Matthew Berriman, Jeremy Herren, Oliver Billker, Martin Hemberg, and Arthur Talman
MCA Science raw data: https://www.ebi.ac.uk/ena/browser/view/PRJEB28169
MCA eLife paper: Collaborators on the original installment of the MCA were Adam Reid, Arthur Talman, Hayley Bennett, Ana Gomes, Christopher Illingworth, Oliver Billker, and Matthew Berriman. This presented SmartSeq2 data on P. berghei and P. falciparum blood stages.
eLife raw data: https://www.ebi.ac.uk/ena/browser/view/PRJEB19245
VISUALISE DATA <- explore how genes are expressed over thousands of individual Plasmodium parasites from across the life cycle.
DOWNLOAD DATA <- Our Github contains gene count tables for all scRNAseq data.
eLife paper <- Further information about this study.
eLife RAW DATA <- European Nucleotide Archive accession PRJEB19245
SCIENCE paper <- Further information about this study.
SCIENCE RAW DATA <- European Nucleotide Archive accession PRJEB28169
NatureComms paper <- Further information about this study.
NatureComms MCA RAW DATA <- European Nucleotide Archive accession PRJEB40487
The Malaria Cell Atlas is supported by Wellcome (WT098051) and by a Medical Research Council Career Development Award (G1100339) to Mara Lawniczak. The authors would like to thank the staff of the Illumina Bespoke Sequencing and Core Cytometry teams at the Wellcome Sanger Institute for their contribution.
Sanger Institute Contributors
The Parasite Genomics group uses comparative and functional genomics approaches to investigate the biology of helminths and protozoan parasites.
Programmes and Facilities
We are focused on using single-cell approaches: cell atlas technologies and understanding human genetics at the cellular level. The team combines ...
Human Cell Atlas
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