Person: Grossman, Sharon
Loading...
Email Address
AA Acceptance Date
Birth Date
Research Projects
Organizational Units
Job Title
Last Name
Grossman
First Name
Sharon
Name
Grossman, Sharon
7 results
Search Results
Now showing 1 - 7 of 7
Publication Genome-Wide Scans Provide Evidence for Positive Selection of Genes Implicated in Lassa Fever(The Royal Society, 2012) Andersen, Kristian G; Shylakhter, Ilya; Tabrizi, Shervin; Grossman, Sharon; Happi, Christian; Sabeti, PardisRapidly evolving viruses and other pathogens can have an immense impact on human evolution as natural selection acts to increase the prevalence of genetic variants providing resistance to disease. With the emergence of large datasets of human genetic variation, we can search for signatures of natural selection in the human genome driven by such disease-causing microorganisms. Based on this approach, we have previously hypothesized that Lassa virus (LASV) may have been a driver of natural selection in West African populations where Lassa haemorrhagic fever is endemic. In this study, we provide further evidence for this notion. By applying tests for selection to genome-wide data from the International Haplotype Map Consortium and the 1000 Genomes Consortium, we demonstrate evidence for positive selection in LARGE and interleukin 21 (IL21), two genes implicated in LASV infectivity and immunity. We further localized the signals of selection, using the recently developed composite of multiple signals method, to introns and putative regulatory regions of those genes. Our results suggest that natural selection may have targeted variants giving rise to alternative splicing or differential gene expression of LARGE and IL21. Overall, our study supports the hypothesis that selective pressures imposed by LASV may have led to the emergence of particular alleles conferring resistance to Lassa fever, and opens up new avenues of research pursuit.Publication A Map of Human Genome Variation from Population Scale Sequencing(Nature Publishing Group, 2010) Altshuler, David; Lander, Eric; Ambrogio, Lauren; Bloom, Toby; Cibulskis, Kristian; Fennell, Tim J.; Gabriel, Stacey B.; Jaffe, David B.; Shefler, Erica; Sougnez, Carrie L.; Lee, Charles; Mills, Ryan Edward; Shi, Xinghua; Daly, Mark; DePristo, Mark A.; Ball, Aaron D.; Banks, Eric; Browning, Brian L.; Garimella, Kiran V.; Grossman, Sharon; Handsaker, Robert; Hanna, Matt; Hartl, Chris; Kernytsky, Andrew M.; Korn, Joshua M.; Li, Heng; Maguire, Jared R.; McCarroll, Steven; Nemesh, James C.; McKenna, Aaron; Philippakis, Anthony Andrew; Poplin, Ryan E.; Price, Alkes; Rivas, Manuel A.; Sabeti, Pardis; Schaffner, Stephen; Shlyakhter, IlyaThe 1000 Genomes Project aims to provide a deep characterization of human genome sequence variation as a foundation for investigating the relationship between genotype and phenotype. Here we present results of the pilot phase of the project, designed to develop and compare different strategies for genome-wide sequencing with high-throughput platforms. We undertook three projects: low-coverage whole-genome sequencing of 179 individuals from four populations; high-coverage sequencing of two mother–father–child trios; and exon-targeted sequencing of 697 individuals from seven populations. We describe the location, allele frequency and local haplotype structure of approximately 15 million single nucleotide polymorphisms, 1 million short insertions and deletions, and 20,000 structural variants, most of which were previously undescribed. We show that, because we have catalogued the vast majority of common variation, over 95% of the currently accessible variants found in any individual are present in this data set. On average, each person is found to carry approximately 250 to 300 loss-of-function variants in annotated genes and 50 to 100 variants previously implicated in inherited disorders. We demonstrate how these results can be used to inform association and functional studies. From the two trios, we directly estimate the rate of de novo germline base substitution mutations to be approximately \(10^{−8}\) per base pair per generation. We explore the data with regard to signatures of natural selection, and identify a marked reduction of genetic variation in the neighbourhood of genes, due to selection at linked sites. These methods and public data will support the next phase of human genetic research.Publication A Composite of Multiple Signals Distinguishes Causal Variants in Regions of Positive Selection(American Association for Advancement of Science, 2010) Shylakhter, Ilya; Karlsson, Elinor K; Byrne, Elizabeth; Morales, Shannon; Frieden, Gabriel; Hostetter, Elizabeth; Angelino, Elaine Lee; Garber, Manuel; Zuk, Or; Lander, Eric; Schaffner, Stephen; Sabeti, Pardis; Grossman, SharonThe human genome contains hundreds of regions whose patterns of genetic variation indicate recent positive natural selection, yet for most the underlying gene and the advantageous mutation remain unknown. We developed a method, composite of multiple signals (CMS), that combines tests for multiple signals of selection and increases resolution by up to 100-fold. By applying CMS to candidate regions from the International Haplotype Map, we localized population-specific selective signals to 55 kilobases (median), identifying known and novel causal variants. CMS can not just identify individual loci but implicates precise variants selected by evolution.Publication Mapping Copy Number Variation by Population Scale Genome Sequencing(Nature Publishing Group, 2011) Mills, Ryan Edward; Handsaker, Robert; Korn, Joshua; Nemesh, James; Shi, Xinghua; Lee, Charles; McCarroll, Steven; Altshuler, David; Gabriel, Stacey B.; Lander, Eric; Ambrogio, Lauren; Bloom, Toby; Cibulskis, Kristian; Fennell, Tim J.; Jaffe, David B.; Shefler, Erica; Sougnez, Carrie L.; Daly, Mark; DePristo, Mark A.; Ball, Aaron D.; Banks, Eric; Browning, Brian L.; Garimella, Kiran V.; Grossman, Sharon; Hanna, Matt; Hartl, Chris; Kernytsky, Andrew M.; Li, Heng; Maguire, Jared R.; McKenna, Aaron; Philippakis, Anthony Andrew; Poplin, Ryan E.; Price, Alkes; Rivas, Manuel A.; Sabeti, Pardis; Schaffner, Stephen; Shlyakhter, Ilya; Wilkinson, JaneGenomic structural variants (SVs) are abundant in humans, differing from other forms of variation in extent, origin and functional impact. Despite progress in SV characterization, the nucleotide resolution architecture of most SVs remains unknown. We constructed a map of unbalanced SVs (that is, copy number variants) based on whole genome DNA sequencing data from 185 human genomes, integrating evidence from complementary SV discovery approaches with extensive experimental validations. Our map encompassed 22,025 deletions and 6,000 additional SVs, including insertions and tandem duplications. Most SVs (53%) were mapped to nucleotide resolution, which facilitated analysing their origin and functional impact. We examined numerous whole and partial gene deletions with a genotyping approach and observed a depletion of gene disruptions amongst high frequency deletions. Furthermore, we observed differences in the size spectra of SVs originating from distinct formation mechanisms, and constructed a map of SV hotspots formed by common mechanisms. Our analytical framework and SV map serves as a resource for sequencing-based association studies.Publication Identification and Functional Validation of the Novel Antimalarial Resistance Locus PF10_0355 in Plasmodium falciparum(Public Library of Science, 2011) Van tyne, Daria; Park, Daniel John; Schaffner, Stephen; Neafsey, Daniel; Angelino, Elaine Lee; Cortese, Joseph F.; Barnes, Kayla G.; Rosen, David M.; Lukens, Amanda; Daniels, Rachel; Milner, Danny; Johnson, Charles A.; Shlyakhter, Ilya; Grossman, Sharon; Becker, Justin S.; Yamins, Daniel Louis Kanef; Karlsson, Elinor K; Ndiaye, Daouda; Sarr, Ousmane; Mboup, Souleymane; Happi, Christian; Furlotte, Nicholas A.; Eskin, Eleazar; Kang, Hyun Min; Hartl, Daniel; Birren, Bruce W.; Wiegand, Roger; Lander, Eric; Wirth, Dyann; Volkman, Sarah; Sabeti, PardisThe Plasmodium falciparum parasite's ability to adapt to environmental pressures, such as the human immune system and antimalarial drugs, makes malaria an enduring burden to public health. Understanding the genetic basis of these adaptations is critical to intervening successfully against malaria. To that end, we created a high-density genotyping array that assays over 17,000 single nucleotide polymorphisms (~1 SNP/kb), and applied it to 57 culture-adapted parasites from three continents. We characterized genome-wide genetic diversity within and between populations and identified numerous loci with signals of natural selection, suggesting their role in recent adaptation. In addition, we performed a genome-wide association study (GWAS), searching for loci correlated with resistance to thirteen antimalarials; we detected both known and novel resistance loci, including a new halofantrine resistance locus, PF10_0355. Through functional testing we demonstrated that PF10_0355 overexpression decreases sensitivity to halofantrine, mefloquine, and lumefantrine, but not to structurally unrelated antimalarials, and that increased gene copy number mediates resistance. Our GWAS and follow-on functional validation demonstrate the potential of genome-wide studies to elucidate functionally important loci in the malaria parasite genome.Publication Ancient and Recent Adaptive Evolution of Primate Non-Homologous End Joining Genes(Public Library of Science, 2010) Demogines, Ann; East, Alysia M.; Lee, Ji-Hoon; Grossman, Sharon; Sabeti, Pardis; Paull, Tanya T.; Sawyer, Sara L.In human cells, DNA double-strand breaks are repaired primarily by the non-homologous end joining (NHEJ) pathway. Given their critical nature, we expected NHEJ proteins to be evolutionarily conserved, with relatively little sequence change over time. Here, we report that while critical domains of these proteins are conserved as expected, the sequence of NHEJ proteins has also been shaped by recurrent positive selection, leading to rapid sequence evolution in other protein domains. In order to characterize the molecular evolution of the human NHEJ pathway, we generated large simian primate sequence datasets for NHEJ genes. Codon-based models of gene evolution yielded statistical support for the recurrent positive selection of five NHEJ genes during primate evolution: XRCC4, NBS1, Artemis, POLλ, and CtIP. Analysis of human polymorphism data using the composite of multiple signals (CMS) test revealed that XRCC4 has also been subjected to positive selection in modern humans. Crystal structures are available for XRCC4, Nbs1, and Polλ; and residues under positive selection fall exclusively on the surfaces of these proteins. Despite the positive selection of such residues, biochemical experiments with variants of one positively selected site in Nbs1 confirm that functions necessary for DNA repair and checkpoint signaling have been conserved. However, many viruses interact with the proteins of the NHEJ pathway as part of their infectious lifecycle. We propose that an ongoing evolutionary arms race between viruses and NHEJ genes may be driving the surprisingly rapid evolution of these critical genes.Publication Activity-by-Contact model of enhancer specificity from thousands of CRISPR perturbations(Cold Spring Harbor Laboratory, 2019-01-26) Fulco, Charles P.; Nasser, Joseph; Jones, Thouis; Munson, Glen; Bergman, Drew T.; Subramanian, Vidya; Grossman, Sharon; Anyoha, Rockwell; Doughty, Benjamin; Patwardhan, Tejal A.; Nguyen, Tung H.; Kane, Michael; Perez, Elizabeth; Durand, Neva C.; Lareau, Caleb; Stamenova, Elena K.; Aiden, Erez Lieberman; Lander, Eric; Engreitz, JesseMammalian genomes harbor millions of noncoding elements called enhancers that quantitatively regulate gene expression, but it remains unclear which enhancers regulate which genes. Here we describe an experimental approach, based on CRISPR interference, RNA FISH, and flow cytometry (CRISPRi-FlowFISH), to perturb enhancers in the genome, and apply it to test >3,000 potential regulatory enhancer-gene connections across multiple genomic loci. A simple equation based on a mechanistic model for enhancer function performed remarkably well at predicting the complex patterns of regulatory connections we observe in our CRISPR dataset. This Activity-by-Contact (ABC) model involves multiplying measures of enhancer activity and enhancer-promoter 3D contacts, and can predict enhancer-gene connections in a given cell type based on chromatin state maps. Together, CRISPRi-FlowFISH and the ABC model provide a systematic approach to map and predict which enhancers regulate which genes, and will help to interpret the functions of the thousands of disease risk variants in the noncoding genome.