We propose the Model-based Analysis of Genome-wide CRISPR/Cas9 Knockout (MAGeCK) method for prioritizing single-guide RNAs, genes and pathways in genome-scale CRISPR/Cas9 knockout screens. MAGeCK demonstrates better performance compared with existing methods, identifies both positively and negatively selected genes simultaneously, and reports robust results across different experimental conditions. Using public datasets, MAGeCK identified novel essential genes and pathways, including EGFR in vemurafenib-treated A375 cells harboring a BRAF mutation. MAGeCK also detected cell type-specific essential genes, including BCR and ABL1, in KBM7 cells bearing a BCR-ABL fusion, and IGF1R in HL-60 cells, which depends on the insulin signaling pathway for proliferation.

Knowledge of the structure of gene expression is essential for mammalian transcriptomics research. We analyzed a collection of more than one million porcine expressed sequence tags (ESTs), of which two-thirds were generated in the Sino-Danish Pig Genome Project and one-third are from public databases. The Sino-Danish ESTs were generated from one normalized and 97 non-normalized cDNA libraries representing 35 different tissues and three developmental stages.

High-throughput CRISPR screens have shown great promise in functional genomics. We present MAGeCK-VISPR, a comprehensive quality control (QC), analysis, and visualization workflow for CRISPR screens. MAGeCK-VISPR defines a set of QC measures to assess the quality of an experiment, and includes a maximum-likelihood algorithm to call essential genes simultaneously under multiple conditions. The algorithm uses a generalized linear model to deconvolute different effects, and employs expectation-maximization to iteratively estimate sgRNA knockout efficiency and gene essentiality. MAGeCK-VISPR also includes VISPR, a framework for the interactive visualization and exploration of QC and analysis results. MAGeCK-VISPR is freely available at http://bitbucket.org/liulab/mageck-vispr .

A specific 3-dimensional intrachromosomal architecture of core stem cell factor genes is required to reprogram a somatic cell into pluripotency. As little is known about the epigenetic readers that orchestrate this architectural remodeling, we used a novel chromatin RNA in situ reverse transcription sequencing (CRIST-seq) approach to profile long noncoding RNAs (lncRNAs) in the Oct4 promoter.

DNA methylation is a heritable epigenetic mark, enabling stable but reversible gene repression. In mammalian cells, DNA methyltransferases (DNMTs) are responsible for modifying cytosine to 5-methylcytosine (5mC), which can be further oxidized by the TET dioxygenases to ultimately cause DNA demethylation. However, the genome-wide cooperation and functions of these two families of proteins, especially at large under-methylated regions, called canyons, remain largely unknown.