Reactivation of a developmentally silenced embryonic globin gene.

The α- and β-globin loci harbor developmentally expressed genes, which are silenced throughout post-natal life. Reactivation of these genes may offer therapeutic approaches for the hemoglobinopathies, the most common single gene disorders. Here, we address mechanisms regulating the embryonically expressed α-like globin, termed ζ-globin.

High-Throughput Genotyping of CRISPR/Cas Edited Cells in 96-Well Plates.

The emergence in recent years of DNA editing technologies-Zinc finger nucleases (ZFNs), transcription activator-like effector (TALE) guided nucleases (TALENs), clustered regularly interspaced short palindromic repeats (CRISPR)/Cas family enzymes, and Base-Editors-have greatly increased our ability to generate hundreds of edited cells carrying an array of alleles, including single-nucleotide substitutions. However, the infrequency of homology-dependent repair (HDR) in generating these substitutions in general requires the screening of large numbers of edited cells to isolate the sequence change of interest. Here we present a high-throughput method for the amplification and barcoding of edited loci in a 96-well plate format.

Fast and accurate genomic analyses using genome graphs.

The human reference genome serves as the foundation for genomics by providing a scaffold for alignment of sequencing reads, but currently only reflects a single consensus haplotype, thus impairing analysis accuracy. Here we present a graph reference genome implementation that enables read alignment across 2,800 diploid genomes encompassing 12.6 million SNPs and 4.

Sasquatch: predicting the impact of regulatory SNPs on transcription factor binding from cell- and tissue-specific DNase footprints.

In the era of genome-wide association studies (GWAS) and personalized medicine, predicting the impact of single nucleotide polymorphisms (SNPs) in regulatory elements is an important goal. Current approaches to determine the potential of regulatory SNPs depend on inadequate knowledge of cell-specific DNA binding motifs. Here, we present Sasquatch, a new computational approach that uses DNase footprint data to estimate and visualize the effects of noncoding variants on transcription factor binding.