Building, benchmarking, and exploring perturbative maps of transcriptional and morphological data.

The continued scaling of genetic perturbation technologies combined with high-dimensional assays such as cellular microscopy and RNA-sequencing has enabled genome-scale reverse-genetics experiments that go beyond single-endpoint measurements of growth or lethality. Datasets emerging from these experiments can be combined to construct perturbative "maps of biology", in which readouts from various manipulations (e.g.

High-resolution genome-wide mapping of chromosome-arm-scale truncations induced by CRISPR-Cas9 editing.

Clustered regularly interspaced short palindromic repeats (CRISPR)-CRISPR-associated protein 9 (Cas9) is a powerful tool for introducing targeted mutations in DNA, but recent studies have shown that it can have unintended effects such as structural changes. However, these studies have not yet looked genome wide or across data types. Here we performed a phenotypic CRISPR-Cas9 scan targeting 17,065 genes in primary human cells, revealing a 'proximity bias' in which CRISPR knockouts show unexpected similarities to unrelated genes on the same chromosome arm.

Computational model for predicting experimental RNA and DNA nearest-neighbor free energy rankings.

Hydrogen-bonding, intrastrand base-stacking, and interstrand base-stacking energies were calculated for RNA and DNA dimers at the MP2(full)/6-311G** level of theory. Standard A-form RNA and B-form DNA geometries from average fiber diffraction data were employed for all base monomer and dimer geometries, and all dimer binding energies were obtained via single-point calculations. The effects of water solvation were considered using the PCM model.