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Mills, Ryan Edward

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Mills

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Ryan Edward

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Mills, Ryan Edward
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    Extensive Genetic Diversity and Substructuring Among Zebrafish Strains Revealed through Copy Number Variant Analysis
    (Proceedings of the National Academy of Sciences, 2012) Brown, Kim H.; Dobrinski, Kimberly P.; Lee, Arthur S.; Gokcumen, Omer; Mills, Ryan Edward; Shi, Xinghua; Chong, Wilson W. S.; Chen, Jin Yun Helen; Yoo, Paulo; David, Sthuthi; Peterson, Samuel M.; Raj, Towfique; Choy, Kwong Wai; Stranger, Barbara Elaine; Williamson, Robin E.; Zon, Leonard; Freeman, Jennifer L.; Lee, Charles
    Copy number variants (CNVs) represent a substantial source of genomic variation in vertebrates and have been associated with numerous human diseases. Despite this, the extent of CNVs in the zebrafish, an important model for human disease, remains unknown. Using 80 zebrafish genomes, representing three commonly used laboratory strains and one native population, we constructed a genome-wide, high-resolution CNV map for the zebrafish comprising 6,080 CNV elements and encompassing 14.6% of the zebrafish reference genome. This amount of copy number variation is four times that previously observed in other vertebrates, including humans. Moreover, 69% of the CNV elements exhibited strain specificity, with the highest number observed for Tubingen. This variation likely arose, in part, from Tubingen's large founding size and composite population origin. Additional population genetic studies also provided important insight into the origins and substructure of these commonly used laboratory strains. This extensive variation among and within zebrafish strains may have functional effects that impact phenotype and, if not properly addressed, such extensive levels of germ-line variation and population substructure in this commonly used model organism can potentially confound studies intended for translation to human diseases.
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    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, Ilya
    The 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.
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    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, Jane
    Genomic 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.