Khavari Lab Methodologies

Laboratory efforts employ a diverse set of methodologies, including methods that were either originally developed or collaboratively refined in the lab [methods noted below link to relevant lab publications].

Tissue and disease modeling methods in the lab are used to study cancer, monogenic human disease, and stem cell differentiation and include genetically defined human organoid and xenograft models as well as mouse knockout and transgenic mouse models.

Genome profiling methods used in the lab include ATAC-seq, ChIP-seq, Hi-C, capture Hi-C, and HiChIP as well as DNA-seq, including whole genome sequencing (WGS) and exome sequencing.

Single-cell methods used in the lab include single-cell RNA-seq and single-cell ATAC-seq as well as single-cell methods that incorporate CRISPR with sequencing, including Perturb-RNA-seq and Perturb-ATAC-seq.

Proteomic methods in the lab include proximity proteomics (BioID), cross-linking mass spectrometry, microscale thermophoresis (MST), and DNA protein interaction detection (DAPID).

Genetics methods in the lab include CRISPRi and CRISPR knockout screening, massively parallel reporter assays (MPRA), high efficiency gene editing in primary cells, and genetic rescue experiments.

Informatics efforts in the lab encompass network analysis and machine learning and involve innovation of lab-developed pipelines for the analysis of high dimensional multiomics datasets, including those derived by RNA-seq, DNA-seq, RIA-seq, Perturb-ATAC-seq, HiChIP, RPM, mass spectrometry, ChIP-seq, and CLIP-seq.

Cell biology methods in the lab include confocal and super-resolution microscopy, cellular fractionation, and live-cell imaging.

RNA-focused methods in the lab are used to study noncoding RNAs, including snoRNAs and lncRNAs and include RNA interaction detection (RIA), RNA-protein microrrays (RPM), non-radioactive irCLIP-seq, easyCLIP, and RNA protein interaction detection (RAPID) in living cells.