A scalable, fully automated process for construction of sequence-ready human exome targeted capture libraries

Genome targeting methods enable cost-effective capture of specific subsets of the genome for sequencing. We present here an automated, highly scalable method for carrying out the Solution Hybrid Selection capture approach that provides a dramatic increase in scale and throughput of sequence-ready libraries produced. Significant process improvements and a series of in-process quality control checkpoints are also added. These process improvements can also be used in a manual version of the protocol

Mutations causing medullary cystic kidney disease type 1 (MCKD1) lie in a large VNTR in MUC1 missed by massively parallel sequencing

While genetic lesions responsible for some Mendelian disorders can be rapidly discovered through massively parallel sequencing (MPS) of whole genomes or exomes, not all diseases readily yield to such efforts. We describe the illustrative case of the simple Mendelian disorder medullary cystic kidney disease type 1 (MCKD1), mapped more than a decade ago to a 2-Mb region on chromosome 1. Ultimately, only by cloning, capillary sequencing, and de novo assembly, we found that each of six MCKD1 families harbors an equivalent, but apparently independently arising, mutation in sequence dramatically underrepresented in MPS data: the insertion of a single C in one copy (but a different copy in each family) of the repeat unit comprising the extremely long (~1.5-5 kb), GC-rich (>80%), coding VNTR in the mucin 1 gene. The results provide a cautionary tale about the challenges in identifying genes responsible for Mendelian, let alone more complex, disorders through MPS

Whole exome sequencing of circulating tumor cells provides a window into metastatic prostate cancer

Comprehensive analyses of cancer genomes promise to inform prognoses and precise cancer treatments. A major barrier, however, is inaccessibility of metastatic tissue. A potential solution is to characterize circulating tumor cells (CTCs), but this requires overcoming the challenges of isolating rare cells and sequencing low-input material. Here we report an integrated process to isolate, qualify and sequence whole exomes of CTCs with high fidelity, using a census-based sequencing strategy. Power calculations suggest that mapping of >99.995% of the standard exome is possible in CTCs. We validated our process in two prostate cancer patients including one for whom we sequenced CTCs, a lymph node metastasis and nine cores of the primary tumor. Fifty-one of 73 CTC mutations (70%) were observed in matched tissue. Moreover, we identified 10 early-trunk and 56 metastatic-trunk mutations in the non-CTC tumor samples and found 90% and 73% of these, respectively, in CTC exomes. This study establishes a foundation for CTC genomics in the clinic

Mutations causing medullary cystic kidney disease type 1 (MCKD1) lie in a large VNTR in MUC1 missed by massively parallel sequencing

While genetic lesions responsible for some Mendelian disorders can be rapidly discovered through massively parallel sequencing (MPS) of whole genomes or exomes, not all diseases readily yield to such efforts. We describe the illustrative case of the simple Mendelian disorder medullary cystic kidney disease type 1 (MCKD1), mapped more than a decade ago to a 2-Mb region on chromosome 1. Ultimately, only by cloning, capillary sequencing, and de novo assembly, we found that each of six MCKD1 families harbors an equivalent, but apparently independently arising, mutation in sequence dramatically underrepresented in MPS data: the insertion of a single C in one copy (but a different copy in each family) of the repeat unit comprising the extremely long (~1.5-5 kb), GC-rich (>80%), coding VNTR in the mucin 1 gene. The results provide a cautionary tale about the challenges in identifying genes responsible for Mendelian, let alone more complex, disorders through MPS

Mutations causing medullary cystic kidney disease type 1 lie in a large VNTR in MUC1 missed by massively parallel sequencing

Although genetic lesions responsible for some mendelian disorders can be rapidly discovered through massively parallel sequencing of whole genomes or exomes, not all diseases readily yield to such efforts. We describe the illustrative case of the simple mendelian disorder medullary cystic kidney disease type 1 (MCKD1), mapped more than a decade ago to a 2-Mb region on chromosome 1. Ultimately, only by cloning, capillary sequencing and de novo assembly did we find that each of six families with MCKD1 harbors an equivalent but apparently independently arising mutation in sequence markedly under-represented in massively parallel sequencing data: the insertion of a single cytosine in one copy (but a different copy in each family) of the repeat unit comprising the extremely long (~1.5–5 kb), GC-rich (>80%) coding variable-number tandem repeat (VNTR) sequence in the MUC1 gene encoding mucin 1. These results provide a cautionary tale about the challenges in identifying the genes responsible for mendelian, let alone more complex, disorders through massively parallel sequencing.National Institutes of Health (U.S.) (Intramural Research Program)National Human Genome Research Institute (U.S.)Charles University (program UNCE 204011)Charles University (program PRVOUK-P24/LF1/3)Czech Republic. Ministry of Education, Youth, and Sports (grant NT13116-4/2012)Czech Republic. Ministry of Health (grant NT13116-4/2012)Czech Republic. Ministry of Health (grant LH12015)National Institutes of Health (U.S.) (Harvard Digestive Diseases Center, grant DK34854

Using viral load and epidemic dynamics to optimize pooled testing in resource-constrained settings

Virological testing is central to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) containment, but many settings face severe limitations on testing. Group testing offers a way to increase throughput by testing pools of combined samples; however, most proposed designs have not yet addressed key concerns over sensitivity loss and implementation feasibility. Here, we combined a mathematical model of epidemic spread and empirically derived viral kinetics for SARS-CoV-2 infections to identify pooling designs that are robust to changes in prevalence and to ratify sensitivity losses against the time course of individual infections. We show that prevalence can be accurately estimated across a broad range, from 0.02 to 20%, using only a few dozen pooled tests and using up to 400 times fewer tests than would be needed for individual identification. We then exhaustively evaluated the ability of different pooling designs to maximize the number of detected infections under various resource constraints, finding that simple pooling designs can identify up to 20 times as many true positives as individual testing with a given budget. Crucially, we confirmed that our theoretical results can be translated into practice using pooled human nasopharyngeal specimens by accurately estimating a 1% prevalence among 2304 samples using only 48 tests and through pooled sample identification in a panel of 960 samples. Our results show that accounting for variation in sampled viral loads provides a nuanced picture of how pooling affects sensitivity to detect infections. Using simple, practical group testing designs can vastly increase surveillance capabilities in resource-limited settings.National Institute of General Medical Sciences (Grant U54GM088558

Development and Validation of a Mass Spectrometry–Based Assay for the Molecular Diagnosis of Mucin-1 Kidney Disease

Mucin-1 kidney disease, previously described as medullary cystic kidney disease type 1 (MCKD1, OMIM 174000), is an autosomal dominant tubulointerstitial kidney disease recently shown to be caused by a single-base insertion within the variable number tandem repeat region of the MUC1 gene. Because of variable age of disease onset and often subtle signs and symptoms, clinical diagnosis of mucin-1 kidney disease and differentiation from other forms of hereditary kidney disease have been difficult. The causal insertion resides in a variable number tandem repeat region with high GC content, which has made detection by standard next-generation sequencing impossible to date. The inherently difficult nature of this mutation required an alternative method for routine detection and clinical diagnosis of the disease. We therefore developed and validated a mass spectrometry–based probe extension assay with a series of internal controls to detect the insertion event using 24 previously characterized positive samples from patients with mucin-1 kidney disease and 24 control samples known to be wild type for the variant. Validation results indicate an accurate and reliable test for clinically establishing the molecular diagnosis of mucin-1 kidney disease with 100% sensitivity and specificity across 275 tests called.Carlos Slim Foundation. Slim Initiative for Genomic Medicin

EGFR Variant Heterogeneity in Glioblastoma Resolved through Single-Nucleus Sequencing

Glioblastomas (GBM) with EGFR amplification represent approximately 50% of newly diagnosed cases, and recent studies have revealed frequent coexistence of multiple EGFR aberrations within the same tumor, which has implications for mutation cooperation and treatment resistance. However, bulk tumor sequencing studies cannot resolve the patterns of how the multiple EGFR aberrations coexist with other mutations within single tumor cells. Here, we applied a population-based single-cell whole-genome sequencing methodology to characterize genomic heterogeneity in EGFR-amplified glioblastomas. Our analysis effectively identified clonal events, including a novel translocation of a super enhancer to the TERT promoter, as well as subclonal LOH and multiple EGFR mutational variants within tumors. Correlating the EGFR mutations onto the cellular hierarchy revealed that EGFR truncation variants (EGFRvII and EGFR carboxyl-terminal deletions) identified in the bulk tumor segregate into nonoverlapping subclonal populations. In vitro and in vivo functional studies show that EGFRvII is oncogenic and sensitive to EGFR inhibitors currently in clinical trials. Thus, the association between diverse activating mutations in EGFR and other subclonal mutations within a single tumor supports an intrinsic mechanism for proliferative and clonal diversification with broad implications in resistance to treatment. Significance: We developed a novel single-cell sequencing methodology capable of identifying unique, nonoverlapping subclonal alterations from archived frozen clinical specimens. Using GBM as an example, we validated our method to successfully define tumor cell subpopulations containing distinct genetic and treatment resistance profiles and potentially mutually cooperative combinations of alterations in EGFR and other genes.Dana-Farber/Harvard Cancer Center (MIT Bridge Project Fund)National Brain Tumor Societ