Massive and parallel expression profiling using microarrayed single-cell sequencing.
Sanja VickovicPatrik L StåhlFredrik SalménSarantis GiatrellisJakub Orzechowski WestholmAnnelie MollbrinkJosé Fernández NavarroJoaquin CustodioMagda BienkoLesley-Ann SuttonRichard RosenquistJonas FrisénJoakim LundebergPublished in: Nature communications (2016)
Single-cell transcriptome analysis overcomes problems inherently associated with averaging gene expression measurements in bulk analysis. However, single-cell analysis is currently challenging in terms of cost, throughput and robustness. Here, we present a method enabling massive microarray-based barcoding of expression patterns in single cells, termed MASC-seq. This technology enables both imaging and high-throughput single-cell analysis, characterizing thousands of single-cell transcriptomes per day at a low cost (0.13 USD/cell), which is two orders of magnitude less than commercially available systems. Our novel approach provides data in a rapid and simple way. Therefore, MASC-seq has the potential to accelerate the study of subtle clonal dynamics and help provide critical insights into disease development and other biological processes.
Keyphrases
- single cell
- rna seq
- high throughput
- gene expression
- induced apoptosis
- mental health
- high resolution
- stem cells
- oxidative stress
- poor prognosis
- machine learning
- endoplasmic reticulum stress
- bone marrow
- binding protein
- signaling pathway
- data analysis
- human health
- photodynamic therapy
- cell cycle arrest
- genome wide identification