Detecting sample swaps in diverse NGS data types using linkage disequilibrium.

As the number of genomics datasets grows rapidly, sample mislabeling has become a high stakes issue. We present CrosscheckFingerprints (Crosscheck), a tool for quantifying sample-relatedness and detecting incorrectly paired sequencing datasets from different donors. Crosscheck outperforms similar methods and is effective even when data are sparse or from different assays. Application of Crosscheck to 8851 ENCODE ChIP-, RNA-, and DNase-seq datasets enabled us to identify and correct dozens of mislabeled samples and ambiguous metadata annotations, representing ~1% of ENCODE datasets.

Development of a gene-editing approach to restore vision loss in Leber congenital amaurosis type 10.

Leber congenital amaurosis type 10 is a severe retinal dystrophy caused by mutations in the CEP290 gene1,2. We developed EDIT-101, a candidate genome-editing therapeutic, to remove the aberrant splice donor created by the IVS26 mutation in the CEP290 gene and restore normal CEP290 expression. Key to this therapeutic, we identified a pair of Staphylococcus aureus Cas9 guide RNAs that were highly active and specific to the human CEP290 target sequence. In vitro experiments in human cells and retinal explants demonstrated the molecular mechanism of action and nuclease specificity. Subretinal delivery of EDIT-101 in humanized CEP290 mice showed rapid and sustained CEP290 gene editing. A comparable surrogate non-human primate (NHP) vector also achieved productive editing of the NHP CEP290 gene at levels that met the target therapeutic threshold, and demonstrated the ability of CRISPR/Cas9 to edit somatic primate cells in vivo. These results support further development of EDIT-101 for LCA10 and additional CRISPR-based medicines for other inherited retinal disorders.

A framework for variation discovery and genotyping using next-generation DNA sequencing data.

Recent advances in sequencing technology make it possible to comprehensively catalog genetic variation in population samples, creating a foundation for understanding human disease, ancestry and evolution. The amounts of raw data produced are prodigious, and many computational steps are required to translate this output into high-quality variant calls. We present a unified analytic framework to discover and genotype variation among multiple samples simultaneously that achieves sensitive and specific results across five sequencing technologies and three distinct, canonical experimental designs. Our process includes (i) initial read mapping; (ii) local realignment around indels; (iii) base quality score recalibration; (iv) SNP discovery and genotyping to find all potential variants; and (v) machine learning to separate true segregating variation from machine artifacts common to next-generation sequencing technologies. We here discuss the application of these tools, instantiated in the Genome Analysis Toolkit, to deep whole-genome, whole-exome capture and multi-sample low-pass (∼4×) 1000 Genomes Project datasets.

Subtype-specific genomic alterations define new targets for soft-tissue sarcoma therapy.

Soft-tissue sarcomas, which result in approximately 10,700 diagnoses and 3,800 deaths per year in the United States, show remarkable histologic diversity, with more than 50 recognized subtypes. However, knowledge of their genomic alterations is limited. We describe an integrative analysis of DNA sequence, copy number and mRNA expression in 207 samples encompassing seven major subtypes. Frequently mutated genes included TP53 (17% of pleomorphic liposarcomas), NF1 (10.5% of myxofibrosarcomas and 8% of pleomorphic liposarcomas) and PIK3CA (18% of myxoid/round-cell liposarcomas, or MRCs). PIK3CA mutations in MRCs were associated with Akt activation and poor clinical outcomes. In myxofibrosarcomas and pleomorphic liposarcomas, we found both point mutations and genomic deletions affecting the tumor suppressor NF1. Finally, we found that short hairpin RNA (shRNA)-based knockdown of several genes amplified in dedifferentiated liposarcoma, including CDK4 and YEATS4, decreased cell proliferation. Our study yields a detailed map of molecular alterations across diverse sarcoma subtypes and suggests potential subtype-specific targets for therapy.