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Francioli, Laurent

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Francioli

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Laurent

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Francioli, Laurent
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    Human genetic variation alters CRISPR-Cas9 on- and off-targeting specificity at therapeutically implicated loci
    (National Academy of Sciences, 2017) Lessard, Samuel; Francioli, Laurent; Alfoldi, Jessica; Tardif, Jean-Claude; Ellinor, Patrick; MacArthur, Daniel; Lettre, Guillaume; Orkin, Stuart; Canver, Matthew C.
    The CRISPR-Cas9 nuclease system holds enormous potential for therapeutic genome editing of a wide spectrum of diseases. Large efforts have been made to further understanding of on- and off-target activity to assist the design of CRISPR-based therapies with optimized efficacy and safety. However, current efforts have largely focused on the reference genome or the genome of cell lines to evaluate guide RNA (gRNA) efficiency, safety, and toxicity. Here, we examine the effect of human genetic variation on both on- and off-target specificity. Specifically, we utilize 7,444 whole-genome sequences to examine the effect of variants on the targeting specificity of ∼3,000 gRNAs across 30 therapeutically implicated loci. We demonstrate that human genetic variation can alter the off-target landscape genome-wide including creating and destroying protospacer adjacent motifs (PAMs). Furthermore, single-nucleotide polymorphisms (SNPs) and insertions/deletions (indels) can result in altered on-target sites and novel potent off-target sites, which can predispose patients to treatment failure and adverse effects, respectively; however, these events are rare. Taken together, these data highlight the importance of considering individual genomes for therapeutic genome-editing applications for the design and evaluation of CRISPR-based therapies to minimize risk of treatment failure and/or adverse outcomes.
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    Negative selection in humans and fruit flies involves synergistic epistasis
    (Cold Spring Harbor Laboratory, 2016-07-29) Sohail, Mashaal; Vakhrusheva, Olga A; Sul, Jae; Pulit, Sara; Francioli, Laurent; van den Berg, Leonard H; Veldink, Jan H; de Bakker, Paul; Bazykin, Georgii A; Kondrashov, Alexey S; Sunyaev, Shamil
    AbstractNegative selection against deleterious alleles produced by mutation is the most common form of natural selection, which strongly influences within-population variation and interspecific divergence. However, some fundamental properties of negative selection remain obscure. In particular, it is still not known whether deleterious alleles affect fitness independently, so that cumulative fitness loss depends exponentially on the number of deleterious alleles, or synergistically, so that each additional deleterious allele results in a larger decrease in relative fitness. Negative selection with synergistic epistasis must produce negative linkage disequilibrium between deleterious alleles, and therefore, underdispersed distribution of the number of deleterious alleles in the genome. Indeed, we detected underdispersion of the number of rare loss-of-function (LoF) alleles in eight independent datasets from modern human andDrosophila melanogasterpopulations. Thus, ongoing selection against deleterious alleles is characterized by synergistic epistasis, which can explain how human and fly populations persist despite very high genomic deleterious mutation rates.
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    A high-quality human reference panel reveals the complexity and distribution of genomic structural variants
    (Nature Publishing Group, 2016) Hehir-Kwa, Jayne Y.; Marschall, Tobias; Kloosterman, Wigard P.; Francioli, Laurent; Baaijens, Jasmijn A.; Dijkstra, Louis J.; Abdellaoui, Abdel; Koval, Vyacheslav; Thung, Djie Tjwan; Wardenaar, René; Renkens, Ivo; Coe, Bradley P.; Deelen, Patrick; de Ligt, Joep; Lameijer, Eric-Wubbo; van Dijk, Freerk; Hormozdiari, Fereydoun; Bovenberg, Jasper A.; de Craen, Anton J. M.; Beekman, Marian; Hofman, Albert; Willemsen, Gonneke; Wolffenbuttel, Bruce; Platteel, Mathieu; Du, Yuanping; Chen, Ruoyan; Cao, Hongzhi; Cao, Rui; Sun, Yushen; Cao, Jeremy Sujie; Neerincx, Pieter B. T.; Dijkstra, Martijn; Byelas, George; Kanterakis, Alexandros; Bot, Jan; Vermaat, Martijn; Laros, Jeroen F. J.; den Dunnen, Johan T.; de Knijff, Peter; Karssen, Lennart C.; van Leeuwen, Elisa M.; Amin, Najaf; Rivadeneira, Fernando; Estrada, Karol; Hottenga, Jouke-Jan; Kattenberg, V. Mathijs; van Enckevort, David; Mei, Hailiang; Santcroos, Mark; van Schaik, Barbera D. C.; Handsaker, Robert; McCarroll, Steven; Ko, Arthur; Sudmant, Peter; Nijman, Isaac J.; Uitterlinden, André G.; van Duijn, Cornelia M.; Eichler, Evan E.; de Bakker, Paul I. W.; Swertz, Morris A.; Wijmenga, Cisca; van Ommen, Gert-Jan B.; Slagboom, P. Eline; Boomsma, Dorret I.; Schönhuth, Alexander; Ye, Kai; Guryev, Victor
    Structural variation (SV) represents a major source of differences between individual human genomes and has been linked to disease phenotypes. However, the majority of studies provide neither a global view of the full spectrum of these variants nor integrate them into reference panels of genetic variation. Here, we analyse whole genome sequencing data of 769 individuals from 250 Dutch families, and provide a haplotype-resolved map of 1.9 million genome variants across 9 different variant classes, including novel forms of complex indels, and retrotransposition-mediated insertions of mobile elements and processed RNAs. A large proportion are previously under reported variants sized between 21 and 100 bp. We detect 4 megabases of novel sequence, encoding 11 new transcripts. Finally, we show 191 known, trait-associated SNPs to be in strong linkage disequilibrium with SVs and demonstrate that our panel facilitates accurate imputation of SVs in unrelated individuals.
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    A framework for the detection of de novo mutations in family-based sequencing data
    (Nature Publishing Group, 2016) Francioli, Laurent; Cretu-Stancu, Mircea; Garimella, Kiran V; Fromer, Menachem; Kloosterman, Wigard P; Wijmenga, Cisca; Investigator, Principal; Swertz, Morris A; van Duijn, Cornelia M; Boomsma, Dorret I; Slagboom, PEline; van Ommen, Gertjan B; de Bakker, Paul IW; van Dijk, Freerk; Menelaou, Androniki; Neerincx, Pieter BT; Pulit, Sara L; Deelen, Patrick; Elbers, Clara C; Francesco Palamara, Pier; Pe'er, Itsik; Abdellaoui, Abdel; van Oven, Mannis; Vermaat, Martijn; Li, Mingkun; Laros, Jeroen FJ; Stoneking, Mark; de Knijff, Peter; Kayser, Manfred; Veldink, Jan H; van den Berg, Leonard H; Byelas, Heorhiy; den Dunnen, Johan T; Dijkstra, Martijn; Amin, Najaf; van der Velde, K Joeri; Hottenga, Jouke Jan; van Setten, Jessica; van Leeuwen, Elisabeth M; Kanterakis, Alexandros; Kattenberg, Mathijs; Karssen, Lennart C; van Schaik, Barbera DC; Bot, Jan; Nijman, Isaäc J; Renkens, Ivo; van Enckevort, David; Mei, Hailiang; Koval, Vyacheslav; Estrada, Karol; Medina-Gomez, Carolina; Ye, Kai; Lameijer, Eric-Wubbo; Moed, Matthijs H; Hehir-Kwa, Jayne Y; Handsaker, Robert E; McCarroll, Steven A; Sunyaev, Shamil R; Polak, Paz; Vuzman, Dana; Sohail, Mashaal; Hormozdiari, Fereydoun; Marschall, Tobias; Schönhuth, Alexander; Guryev, Victor; Slagboom, P Eline; Beekman, Marian B; de Craen, Anton JM; Suchiman, H Eka D; Hofman, Albert; Oostra, Ben; Isaacs, Aaron; Rivadeneira, Fernando; Uitterlinden, André G; Willemsen, Gonneke; Platteel, Mathieu; Pitts, Steven J; Potluri, Shobha; Sundar, Purnima; Cox, David R; Li, Qibin; Li, Yingrui; Du, Yuanping; Chen, Ruoyan; Cao, Hongzhi; Li, Ning; Cao, Sujie; Wang, Jun; Bovenberg, Jasper A; Brandsma, Margreet; Samocha, Kaitlin E.; Neale, Benjamin; Daly, Mark; Banks, Eric; DePristo, Mark A
    Germline mutation detection from human DNA sequence data is challenging due to the rarity of such events relative to the intrinsic error rates of sequencing technologies and the uneven coverage across the genome. We developed PhaseByTransmission (PBT) to identify de novo single nucleotide variants and short insertions and deletions (indels) from sequence data collected in parent-offspring trios. We compute the joint probability of the data given the genotype likelihoods in the individual family members, the known familial relationships and a prior probability for the mutation rate. Candidate de novo mutations (DNMs) are reported along with their posterior probability, providing a systematic way to prioritize them for validation. Our tool is integrated in the Genome Analysis Toolkit and can be used together with the ReadBackedPhasing module to infer the parental origin of DNMs based on phase-informative reads. Using simulated data, we show that PBT outperforms existing tools, especially in low coverage data and on the X chromosome. We further show that PBT displays high validation rates on empirical parent-offspring sequencing data for whole-exome data from 104 trios and X-chromosome data from 249 parent-offspring families. Finally, we demonstrate an association between father's age at conception and the number of DNMs in female offspring's X chromosome, consistent with previous literature reports.