Functional and transcriptomic readouts with human iPSC-derived neural models: MEA and RNA-seq in practice

Resume:
An introduction will be provided on how defined human iPSC-derived neurons and glial cells can be used to generate high-quality functional and transcriptomic data. Practical approaches for applying multi-electrode arrays (MEA) to measure network activity, as well as bulk and single-cell RNA sequencing to quantify gene expression and molecular signatures in neural models of health and disease, will be discussed.
The session will address experimental setup considerations, workflows, and principles for data interpretation, illustrating how functional phenotypes and transcriptomic data can be integrated to build a more complete understanding of human neural biology.
Learning objectives:

• How to establish iPSC-derived neural cultures suitable for MEA and RNA-seq experiments.
• Key MEA parameters: plating, culture maintenance, signal stability, and approaches for extracting functional network metrics.
• When to choose bulk vs single-cell RNA-seq and how to match the method to the research question.
• A reproducible bulk RNA-seq workflow (nf-core/rnaseq with Salmon), from QC to differential expression with DESeq2.
• How PCA, volcano plots, and heatmaps are used to assess data quality and interpret biological changes.
• Examples of how transcriptomics is applied at bit.bio to benchmark wild-type cells and verify manufacturing consistency.

Followed by an open discussion.

Interested individuals can register for the event through the following link.

Bio:
Luke Foulser, MSc, is our Field Applications Scientist at bit.bio, and he provides expert guidance and technical support on ioCells to our customers. His professional expertise centers on the characterization of iPSC-derived neurons, including the assessment of their electrophysiological functionality using techniques such as MEA. Previously, Luke gained valuable research experience as a Research Assistant at the Wellcome Sanger Institute, where he managed projects involving neural stem cells and iPSC differentiation.

Val Yianni, PhD, is a Senior computational Biologist at bit.bio, with a strong background in molecular genetics and stem cell biology. His research interests centers on stem cell maintenance, regulation, and lineage specification, using advanced techniques such as single-cell RNA sequencing, transcriptomics, epigenomics, and bioinformatic approaches. Previously, Dr. Yianni has held several academic roles at King's College London, where he contributed to numerous peer-reviewed publications.
 

Certificates of attendance will be provided upon request at cimus.xestion [at] usc.es (cimus[dot]xestion[at]usc[dot]es). Please do not forget to enter your name and surname in the printout given during the lecture.