A variety of rotation projects are available including:

- Analysis of massively parallel reporter assays to identify regulatory variants

- Application of machine learning models to predict the function of non-coding genetic variants

- Analysis of single-cell gene expression and chromatin datasets

- Analysis of “Superb-seq” data consisting of single cell readouts of CRISPR edits and transcriptomes.

The Li lab has generated multiple single cell datasets of normal, perturbed, and regenerative hematopoiesis that serve as a launching pad for exploration of novel bioinformatic approaches to reveal biology relevant to understanding and treating blood disorders. Rotation projects leveraging existing high-value datasets are available for prospective graduate students.

Cul3 (Cullin 3) ubiquitin ligase is one of the genes implicated in Autism Spectrum Disorders. We generated brain organoids with Cul3 haploinsufficiency, and collected 10x multiome data on these organoids. The goal of the rotation project is to analyze these data to identify cell types, genes and chromatin states impacted by this ASD mutation. The student is required to have familiarity with single cell RNA data analyses.

Copy number variants (CNVs) represent significant risk factors for Autism Spectrum Disorders (ASD). One of the most frequent CNVs involved in ASD is a deletion or duplication of the 16p11.2 CNV locus, spanning 29 protein-coding genes. Despite the progress in linking 16p11.2 genetic changes with the phenotypic (macrocephaly and microcephaly) abnormalities in the patients and model organisms, the specific molecular pathways impacted by this CNV remain unknown. We generated 10x multiome data from brain organoids carrying 16p11.2 deletions and duplications at various time points. The goal of this rotation project is to analyze these data to discover pathways and gene regulatory networks dysregulated by the 16p11.2 CNV. The student is required to have familiarity with single cell RNA data analyses.