Lecture

Single-cell Temporal-Omics: Inference of Transcriptional Dynamics

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In course

BIO-221: Cell and developmental biology for engineers

Students will learn essentials of cell and developmental biology with an engineering mind set, with an emphasis on animal systems and quantitative approaches. ...

Description

This lecture by the instructor on Single-cell Temporal-Omics focuses on inferring transcriptional dynamics from snapshot data. The content covers concepts such as phase space representation of complex systems, localization of cells in gene expression space, studying dynamics through pseudo-time analysis, and the interpretation of RNA velocity in RNA metabolism. The lecture also delves into the challenges of interpreting pseudotime algorithms, differentiation processes, and the dynamics of mRNA lifecycle. Various algorithms and models for analyzing single-cell data are discussed, along with the extension of steady-state models and the interpretation of velocity arrows in high-dimensional space.

Instructors (2)

Pierre Gönczy

Pierre Gönczy obtained his PhD from The Rockefeller University (New York, USA) in 1995 and joined the laboratory of Tony Hyman at the EMBL (Heidelberg, Germany) as a postdoctoral fellow in 1996. He started his own laboratory at ISREC in 2000. In 2005, he became Associate Professor at the EPFL School of Life Sciences, and was promoted Full Professor in 2009.

Andrew Charles Oates

After an undergraduate degree in Biochemistry at the University of Adelaide with Honours in Robert Saint’s lab, Andrew Oates received his Ph.D. at the Ludwig Institute for Cancer Research and the University of Melbourne in the lab of Andrew Wilks. His postdoctoral time was at Princeton University and the University of Chicago in the lab of Robert Ho, where his studies on the segmentation clock in zebrafish began in 1998. In 2003 he moved to Germany and started his group at the Max Planck Institute for Molecular Cell Biology and Genetics in Dresden. In 2012 he accepted a position at University College London as Professor of vertebrate developmental genetics and moved his group to the MRC-National Institute for Medical Research at Mill Hill in London. From April 2015, he became a member of the Francis Crick Institute in London. In September 2016, he joined École polytechnique fédéral de Lausanne (EPFL) in Switzerland as a Professor, where he is the head of the Timing, Oscillation, Patterns Laboratory. From April 2018 he served as Director of the Institute of Bioengineering, and from January 2021 became the Dean of the School of Life Sciences. The Timing, Oscillation, Patterns Laboratory is composed of biologists, engineers, and physicists using molecular genetics, quantitative imaging, and theoretical analysis to study a population of coupled genetic oscillators in the vertebrate embryo termed the segmentation clock. This system drives the rhythmic, sequential, and precise formation of embryonic body segments, exhibiting rich spatial and temporal phenomena spanning from molecular to tissue scales.

Official source

Related concepts (29)

Gene expression profiling

In the field of molecular biology, gene expression profiling is the measurement of the activity (the expression) of thousands of genes at once, to create a global picture of cellular function. These profiles can, for example, distinguish between cells that are actively dividing, or show how the cells react to a particular treatment. Many experiments of this sort measure an entire genome simultaneously, that is, every gene present in a particular cell. Several transcriptomics technologies can be used to generate the necessary data to analyse.

Dimensionality reduction

Dimensionality reduction, or dimension reduction, is the transformation of data from a high-dimensional space into a low-dimensional space so that the low-dimensional representation retains some meaningful properties of the original data, ideally close to its intrinsic dimension. Working in high-dimensional spaces can be undesirable for many reasons; raw data are often sparse as a consequence of the curse of dimensionality, and analyzing the data is usually computationally intractable (hard to control or deal with).

Regulation of gene expression

Regulation of gene expression, or gene regulation, includes a wide range of mechanisms that are used by cells to increase or decrease the production of specific gene products (protein or RNA). Sophisticated programs of gene expression are widely observed in biology, for example to trigger developmental pathways, respond to environmental stimuli, or adapt to new food sources. Virtually any step of gene expression can be modulated, from transcriptional initiation, to RNA processing, and to the post-translational modification of a protein.

RNA polymerase II

RNA polymerase II (RNAP II and Pol II) is a multiprotein complex that transcribes DNA into precursors of messenger RNA (mRNA) and most small nuclear RNA (snRNA) and microRNA. It is one of the three RNAP enzymes found in the nucleus of eukaryotic cells. A 550 kDa complex of 12 subunits, RNAP II is the most studied type of RNA polymerase. A wide range of transcription factors are required for it to bind to upstream gene promoters and begin transcription.

Serial analysis of gene expression

Serial Analysis of Gene Expression (SAGE) is a transcriptomic technique used by molecular biologists to produce a snapshot of the messenger RNA population in a sample of interest in the form of small tags that correspond to fragments of those transcripts. Several variants have been developed since, most notably a more robust version, LongSAGE, RL-SAGE and the most recent SuperSAGE. Many of these have improved the technique with the capture of longer tags, enabling more confident identification of a source gene.

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