A Massively Parallel Pipeline to Clone DNA Variants and Examine Molecular Phenotypes of Human Disease Mutations

Abstract

Understanding the functional relevance of DNA variants is essential for all exome and genome sequencing projects. However, current mutagenesis cloning protocols require Sanger sequencing, and thus are prohibitively costly and labor-intensive. We describe a massively-parallel site-directed mutagenesis approach, “Clone-seq”, leveraging next-generation sequencing to rapidly and cost-effectively generate a large number of mutant alleles. Using Clone-seq, we further develop a comparative interactome-scanning pipeline integrating high-throughput GFP, yeast two-hybrid (Y2H), and mass spectrometry assays to systematically evaluate the functional impact of mutations on protein stability and interactions. We use this pipeline to show that disease mutations on protein-protein interaction interfaces are significantly more likely than those away from interfaces to disrupt corresponding interactions. We also find that mutation pairs with similar molecular phenotypes in terms of both protein stability and interactions are significantly more likely to cause the same disease than those with different molecular phenotypes, validating the in vivo biological relevance of our high-throughput GFP and Y2H assays, and indicating that both assays can be used to determine candidate disease mutations in the future. The general scheme of our experimental pipeline can be readily expanded to other types of interactome-mapping methods to comprehensively evaluate the functional relevance of all DNA variants, including those in non-coding regions.

A Proteome-wide Fission Yeast Interactome Reveals Network Evolution Principles from Yeasts to Human

“…This shows that even among conserved interactions, only a few key alterations at important binding sites can make the cross-species interactions incompatible and the interactions coevolved. Thus, these sites are critical to protein binding and subsequent function, and changes at these sites alter protein interactions in a manner analogous to a single amino acid change disrupting protein interactions in human disease (Wang et al, 2012; Wei et al, 2014). …”

“…Gain or loss of these interactions within an organism can modulate protein functions and disease states (Sahni et al, 2015; Wei et al, 2014). The importance of protein interactions to our understanding of fundamental biological processes has spurred the mapping of protein interactome networks for several organisms (Arabidopsis Interactome Mapping Consortium, 2011; Giot et al, 2003; Rolland et al, 2014; Stelzl et al, 2005; Yu et al, 2008).…”

Diagnostic use of Massively Parallel Sequencing in Neuromuscular Diseases: Towards an Integrated Diagnosis

“…To increase the benefit of MPS in a diagnosis setting, improvement in bioinformatics, storage of data and interpretation of variants are areas that require further resource development, as well as expanded and multidisciplinary databases and analysis pipelines and tools, and increased training for biologists and clinicians. High throughput assay to assess RNA integrity [55] and protein function have been described [43] and should be further developed for functional validation of genetic variants.…”

“…Such complementary analyses were required to reach a diagnostic conclusion for 115 out of 442 patients (26%) enrolled in 7 studies presented in Table 1. More detailed functional analyses may be required for potential mutations that were not yet reported as pathogenic and can benefit from high throughput wet bench pipelines, for example to test the impact of variants on protein stability, localisation and interaction [43], or to correlate with phenotypes in animal models as zebrafish [44]. …”

Base-resolution stratification of cancer mutations using functional variomics

“…1). To this end, a number of deep mutagenesis technologies have emerged in recent years, including PFunkel 11 , deep mutational scanning 12,13 , Clone-seq 14 and most recently, Gateway-mediated functional variomics 15 . These strategies are all coupled with next-generation sequencing.…”