What you see here is the average face of the average person currently living on planet earth. By averaging we lose all the little details that make us unique. Our beauty is in our difference and this is true at all levels: We are different at all scales! . From our faces, our minds, our proteins down to individual cells that make up our body even down to single molecules. National Geographic

Our beauty is in our differences Our beauty is in our difference and this is true down to level of individual cells and individual molecules.

Our beauty is in our difference and this is true down to level of individual cells and individual molecules.

Our beauty is in our difference and this is true down to level of individual cells and individual molecules.

Our beauty is in our difference and this is true down to level of individual cells and individual molecules.

Our beauty is in our difference and this is true down to level of individual cells and individual molecules.

Our beauty is in our difference and this is true down to level of individual cells and individual molecules.

Our beauty is in our difference and this is true down to level of individual cells and individual molecules.

Our beauty is in our difference and this is true down to level of individual cells and individual molecules.

Our beauty is in our difference and this is true down to level of individual cells and individual molecules.

Our beauty is in our difference and this is true down to level of individual cells and individual molecules.

School of Electronic and Electrical Engineering Single-Cell Genomics Dr Paolo Actis School of Electronic and Electrical Engineering p.actis@leeds.ac.uk @paoloactis

Single-Cell Genomics Single-cell genome sequencing: current state of the science, Nat Rev Genetics 2016 Single Cell Genomics: Advances and Future Perspectives, PLOS Genetics, 2014

Single-Cell Genomics 1. Cell Isolation

Single-Cell Genomics 1. Cell Isolation 2. Genome Amplification

Single-Cell Genomics 1. Cell Isolation 2. Genome Amplification 3. Genome Sequencing

Single-Cell Genomics 1. Cell Isolation 2. Genome Amplification 3. Genome Sequencing 4. Bioinformatics analysis

1. Cell Isolation

Cell Isolation Manual Micropipetting ✔Visual confirmation, Applicable to low number of cells ✖Low throughput, Operator Bias

Cell Isolation FACS (fluorescence activated cell sorting) ✔High Throughput , Sorting based on phenotype ✖Large amount of cells required, Putative damage to cells, Occasionally more than one cell isolated

Cell Isolation Microfluidics ✔High Throughput , highly standardized, nanoliter reaction volumes, automated with visual confirmation ✖Putative loss of cells

Cell Isolation Single nuclei sorting ✔No need to isolate whole cell, isolation form cryopreserved or fresh tissues ✖Potential loss of micronuclei

Cell Isolation Laser Capture Microdissection ✔Retains topological information of the cell, isolation form cryopreserved or fresh tissues ✖Contamination with other cells, Potential loss of cellular material

Single-Cell Nanobiopsy

Electrowetting in a nanopipette H2O DCE

Electrowetting in a nanopipette

Single-Cell Nanobiopsy

Single-Cell Nanobiopsy Actis et al, ACS Nano, 2013

RNA-Sequencing High read coverage of RNA sequencing of nanobiopsies Full length cDNA from transcripts isolated by nanobiopsy

Organelle Surgery

Single-Cell Nanobiopsy

Single-Cell Nanobiopsy

Sub-Cellular Sequencing

Sub-Cellular Sequencing

Sub-Cellular Sequencing

Ambition Nucleolar trafficking during virus infection (Ade Whitehouse, FBS) Sub-cellular Sequencing (Thierry Voet, Sanger Institute) Omics analysis (You)

2. Genome Amplification

Genome Amplification

Genome Amplification High Uniformity but High error rates

Genome Amplification

Genome Amplification Low Uniformity but Low error rates

Genome Amplification

intermediate error rates Genome Amplification High Uniformity but intermediate error rates

3. Genome Sequencing

Genome Sequencing Easy …just ask Ian Carr

4. Bioinformatics analysis

Amplification artefacts Loss of coverage Amplification artefacts

False positive True positive False Negative (locus dropout)

Single-Cell Genomics 1. Cell Isolation 2. Genome Amplification 3. Genome Sequencing 4. Bioinformatics analysis

Our beauty is in our differences Dr Paolo Actis School of Electronic and Electrical Engineering p.actis@leeds.ac.uk @paoloactis Our beauty is in our difference and this is true down to level of individual cells and individual molecules.