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Single cell transcriptomics of a living fossil brain

Single cell transcriptomics of a living fossil brain

Supervisor: Dr Èlia Benito-Gutiérrez

Project summary:

The evolutionary origin of the vertebrate brain is still uncertain. This is due principally to the lack of unambiguous homologues of key vertebrate brain parts in invertebrate chordates. These invertebrate chordates include tunicates and amphioxus, with the latter possessing the oldest extant tubular brain. Recent advances in amphioxus husbandry, sequencing and imaging technologies have made the oldest tubular brain available in the lab for experimentation and visualisation. This will enable investigation of the neuronal cell type repertoire and organisation of the amphioxus brain at a single cell level. Considering that amphioxus might be the only living representative of the ancestral chordate brain, we propose to characterise cell types within the amphioxus brain. With this we expect to define the primordial neuronal types that provide the basis for building up brains as complex as the human ones.

What the student will be doing:

The project will start by developing a protocol to obtain cell suspensions of living brain cells from amphioxus. Using the latest Single Cell Sequencing Technology these cells will be sorted and sequenced individually. There will be the opportunity of assembling and annotating full single-cell transcriptomes to a reference already available in the lab. From these transcriptomes the top neuronal identifiers for each of the brain cells will be cloned and analysed by in situ hybridisation. This will allow to map back the transcriptome data generated into the real brain. This mapping will be done by imaging the hybridised brains with confocal or light-sheet microscopy. These images will then be used to reconstruct the amphioxus brain in 3D with integrated expression data.


1. Scialdone A, Tanaka Y, Jawaid W, Moignard V, Wilson NK, Macaulay IC, Marioni JC, Göttgens B. Resolving early mesoderm diversification through single-cell expression profiling. Nature. 2016. 535(7611): 289-93.

2. Achim K, Pettit JB, Saraiva LR, Gavriouchkina D, Larsson T, Arendt D, Marioni JC. High-throughput spatial mapping of single-cell RNA-seq data to tissue of origin. Nat Biotechnol. 2015. 33(5): 503-9.