Laurent C. Francioli
Utrecht University
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Publication
Featured researches published by Laurent C. Francioli.
Nature Genetics | 2015
Laurent C. Francioli; Paz Polak; Amnon Koren; Androniki Menelaou; Sung Chun; Ivo Renkens; Cornelia M. van Duijn; Morris A. Swertz; Cisca Wijmenga; Gert-Jan B. van Ommen; P. Eline Slagboom; Dorret I. Boomsma; Kai Ye; Victor Guryev; Peter F. Arndt; Wigard P. Kloosterman; Paul I. W. de Bakker; Shamil R. Sunyaev
Mutations create variation in the population, fuel evolution and cause genetic diseases. Current knowledge about de novo mutations is incomplete and mostly indirect. Here we analyze 11,020 de novo mutations from the whole genomes of 250 families. We show that de novo mutations in the offspring of older fathers are not only more numerous but also occur more frequently in early-replicating, genic regions. Functional regions exhibit higher mutation rates due to CpG dinucleotides and show signatures of transcription-coupled repair, whereas mutation clusters with a unique signature point to a new mutational mechanism. Mutation and recombination rates independently associate with nucleotide diversity, and regional variation in human-chimpanzee divergence is only partly explained by heterogeneity in mutation rate. Finally, we provide a genome-wide mutation rate map for medical and population genetics applications. Our results provide new insights and refine long-standing hypotheses about human mutagenesis.
European Journal of Human Genetics | 2014
Dorret I. Boomsma; Cisca Wijmenga; Eline Slagboom; Morris A. Swertz; Lennart C. Karssen; Abdel Abdellaoui; Kai Ye; Victor Guryev; Martijn Vermaat; Freerk van Dijk; Laurent C. Francioli; Jouke-Jan Hottenga; Jeroen F. J. Laros; Qibin Li; Yingrui Li; Hongzhi Cao; Ruoyan Chen; Yuanping Du; Ning Li; Sujie Cao; Jessica van Setten; Androniki Menelaou; Sara L. Pulit; Jayne Y. Hehir-Kwa; Marian Beekman; Clara C. Elbers; Heorhiy Byelas; Anton J. M. de Craen; Patrick Deelen; Martijn Dijkstra
Within the Netherlands a national network of biobanks has been established (Biobanking and Biomolecular Research Infrastructure-Netherlands (BBMRI-NL)) as a national node of the European BBMRI. One of the aims of BBMRI-NL is to enrich biobanks with different types of molecular and phenotype data. Here, we describe the Genome of the Netherlands (GoNL), one of the projects within BBMRI-NL. GoNL is a whole-genome-sequencing project in a representative sample consisting of 250 trio-families from all provinces in the Netherlands, which aims to characterize DNA sequence variation in the Dutch population. The parent–offspring trios include adult individuals ranging in age from 19 to 87 years (mean=53 years; SD=16 years) from birth cohorts 1910–1994. Sequencing was done on blood-derived DNA from uncultured cells and accomplished coverage was 14–15x. The family-based design represents a unique resource to assess the frequency of regional variants, accurately reconstruct haplotypes by family-based phasing, characterize short indels and complex structural variants, and establish the rate of de novo mutational events. GoNL will also serve as a reference panel for imputation in the available genome-wide association studies in Dutch and other cohorts to refine association signals and uncover population-specific variants. GoNL will create a catalog of human genetic variation in this sample that is uniquely characterized with respect to micro-geographic location and a wide range of phenotypes. The resource will be made available to the research and medical community to guide the interpretation of sequencing projects. The present paper summarizes the global characteristics of the project.
European Journal of Human Genetics | 2014
Patrick Deelen; Androniki Menelaou; Elisabeth M. van Leeuwen; Alexandros Kanterakis; Freerk van Dijk; Carolina Medina-Gomez; Laurent C. Francioli; J ouke; Jan Hottenga; Lennart C. Karssen; Karol Estrada; Eskil Kreiner-Møller; Fernando Rivadeneira; Jessica van Setten; Javier Gutierrez-Achury; Lude Franke; David van Enckevort; Martijn Dijkstra; Heorhiy Byelas; Paul I. W. de Bakker; Cisca Wijmenga; Morris A. Swertz
Although genome-wide association studies (GWAS) have identified many common variants associated with complex traits, low-frequency and rare variants have not been interrogated in a comprehensive manner. Imputation from dense reference panels, such as the 1000 Genomes Project (1000G), enables testing of ungenotyped variants for association. Here we present the results of imputation using a large, new population-specific panel: the Genome of The Netherlands (GoNL). We benchmarked the performance of the 1000G and GoNL reference sets by comparing imputation genotypes with ‘true’ genotypes typed on ImmunoChip in three European populations (Dutch, British, and Italian). GoNL showed significant improvement in the imputation quality for rare variants (MAF 0.05–0.5%) compared with 1000G. In Dutch samples, the mean observed Pearson correlation, r2, increased from 0.61 to 0.71. We also saw improved imputation accuracy for other European populations (in the British samples, r2 improved from 0.58 to 0.65, and in the Italians from 0.43 to 0.47). A combined reference set comprising 1000G and GoNL improved the imputation of rare variants even further. The Italian samples benefitted the most from this combined reference (the mean r2 increased from 0.47 to 0.50). We conclude that the creation of a large population-specific reference is advantageous for imputing rare variants and that a combined reference panel across multiple populations yields the best imputation results.
Genome Research | 2015
Wigard P. Kloosterman; Laurent C. Francioli; Tobias Marschall; Jayne Y. Hehir-Kwa; Abdel Abdellaoui; Eric-Wubbo Lameijer; Matthijs Moed; Vyacheslav Koval; Ivo Renkens; Markus J. van Roosmalen; Pascal P. Arp; Lennart C. Karssen; Bradley P. Coe; Robert E. Handsaker; E. Suchiman; Edwin Cuppen; Djie Tjwan Thung; Mitch McVey; Michael C. Wendl; Cornelia M. van Duijn; Morris A. Swertz; Gert-Jan B. van Ommen; P. Eline Slagboom; Dorret I. Boomsma; Alexander Schönhuth; Evan E. Eichler; Victor Guryev
Small insertions and deletions (indels) and large structural variations (SVs) are major contributors to human genetic diversity and disease. However, mutation rates and characteristics of de novo indels and SVs in the general population have remained largely unexplored. We report 332 validated de novo structural changes identified in whole genomes of 250 families, including complex indels, retrotransposon insertions, and interchromosomal events. These data indicate a mutation rate of 2.94 indels (1-20 bp) and 0.16 SVs (>20 bp) per generation. De novo structural changes affect on average 4.1 kbp of genomic sequence and 29 coding bases per generation, which is 91 and 52 times more nucleotides than de novo substitutions, respectively. This contrasts with the equal genomic footprint of inherited SVs and substitutions. An excess of structural changes originated on paternal haplotypes. Additionally, we observed a nonuniform distribution of de novo SVs across offspring. These results reveal the importance of different mutational mechanisms to changes in human genome structure across generations.
Human Molecular Genetics | 2014
Jonas Kuiper; Jessica van Setten; Stephan Ripke; Ruben van 't Slot; Flip Mulder; Tom Missotten; G. Seerp Baarsma; Laurent C. Francioli; Sara L. Pulit; Carolien G.F. de Kovel; Ninette H. ten Dam-van Loon; Anneke I. den Hollander; Paulien I. Huis in het Veld; Carel B. Hoyng; Miguel Cordero-Coma; Javier Martin; Victor Llorenç; Bharti Arya; Dhanes Thomas; Steven C. Bakker; Roel A. Ophoff; Aniki Rothova; Paul I. W. de Bakker; Tuna Mutis; Bobby P. C. Koeleman
Birdshot chorioretinopathy (BSCR) is a rare form of autoimmune uveitis that can lead to severe visual impairment. Intriguingly, >95% of cases carry the HLA-A29 allele, which defines the strongest documented HLA association for a human disease. We have conducted a genome-wide association study in 96 Dutch and 27 Spanish cases, and 398 unrelated Dutch and 380 Spanish controls. Fine-mapping the primary MHC association through high-resolution imputation at classical HLA loci, identified HLA-A*29:02 as the principal MHC association (odds ratio (OR) = 157.5, 95% CI 91.6-272.6, P = 6.6 × 10(-74)). We also identified two novel susceptibility loci at 5q15 near ERAP2 (rs7705093; OR = 2.3, 95% CI 1.7-3.1, for the T allele, P = 8.6 × 10(-8)) and at 14q32.31 in the TECPR2 gene (rs150571175; OR = 6.1, 95% CI 3.2-11.7, for the A allele, P = 3.2 × 10(-8)). The association near ERAP2 was confirmed in an independent British case-control samples (combined meta-analysis P = 1.7 × 10(-9)). Functional analyses revealed that the risk allele of the polymorphism near ERAP2 is strongly associated with high mRNA and protein expression of ERAP2 in B cells. This study further defined an extremely strong MHC risk component in BSCR, and detected evidence for a novel disease mechanism that affects peptide processing in the endoplasmic reticulum.
PLOS Genetics | 2013
Adam Kiezun; Sara L. Pulit; Laurent C. Francioli; Freerk van Dijk; Morris A. Swertz; Dorret I. Boomsma; Cornelia M. van Duijn; P. Eline Slagboom; G.J.B. van Ommen; Cisca Wijmenga; Paul I. W. de Bakker; Shamil R. Sunyaev
Large-scale population sequencing studies provide a complete picture of human genetic variation within the studied populations. A key challenge is to identify, among the myriad alleles, those variants that have an effect on molecular function, phenotypes, and reproductive fitness. Most non-neutral variation consists of deleterious alleles segregating at low population frequency due to incessant mutation. To date, studies characterizing selection against deleterious alleles have been based on allele frequency (testing for a relative excess of rare alleles) or ratio of polymorphism to divergence (testing for a relative increase in the number of polymorphic alleles). Here, starting from Maruyamas theoretical prediction (Maruyama T (1974), Am J Hum Genet USA 6:669–673) that a (slightly) deleterious allele is, on average, younger than a neutral allele segregating at the same frequency, we devised an approach to characterize selection based on allelic age. Unlike existing methods, it compares sets of neutral and deleterious sequence variants at the same allele frequency. When applied to human sequence data from the Genome of the Netherlands Project, our approach distinguishes low-frequency coding non-synonymous variants from synonymous and non-coding variants at the same allele frequency and discriminates between sets of variants independently predicted to be benign or damaging for protein structure and function. The results confirm the abundance of slightly deleterious coding variation in humans.
American Journal of Human Genetics | 2015
Pier Francesco Palamara; Laurent C. Francioli; Peter R. Wilton; Giulio Genovese; Alexander Gusev; Hilary Finucane; Sriram Sankararaman; Shamil R. Sunyaev; Paul I. W. de Bakker; John Wakeley; Itsik Pe’er; Alkes L. Price
The rate at which human genomes mutate is a central biological parameter that has many implications for our ability to understand demographic and evolutionary phenomena. We present a method for inferring mutation and gene-conversion rates by using the number of sequence differences observed in identical-by-descent (IBD) segments together with a reconstructed model of recent population-size history. This approach is robust to, and can quantify, the presence of substantial genotyping error, as validated in coalescent simulations. We applied the method to 498 trio-phased sequenced Dutch individuals and inferred a point mutation rate of 1.66 × 10(-8) per base per generation and a rate of 1.26 × 10(-9) for <20 bp indels. By quantifying how estimates varied as a function of allele frequency, we inferred the probability that a site is involved in non-crossover gene conversion as 5.99 × 10(-6). We found that recombination does not have observable mutagenic effects after gene conversion is accounted for and that local gene-conversion rates reflect recombination rates. We detected a strong enrichment of recent deleterious variation among mismatching variants found within IBD regions and observed summary statistics of local sharing of IBD segments to closely match previously proposed metrics of background selection; however, we found no significant effects of selection on our mutation-rate estimates. We detected no evidence of strong variation of mutation rates in a number of genomic annotations obtained from several recent studies. Our analysis suggests that a mutation-rate estimate higher than that reported by recent pedigree-based studies should be adopted in the context of DNA-based demographic reconstruction.
Photochemistry and Photobiology | 2011
David Vernez; Antoine Milon; Laurent C. Francioli; Jean-Luc Bulliard; Laurent Vuilleumier; Laurent Moccozet
Exposure to solar ultraviolet (UV) light is the main causative factor for skin cancer. UV exposure depends on environmental and individual factors. Individual exposure data remain scarce and development of alternative assessment methods is greatly needed. We developed a model simulating human exposure to solar UV. The model predicts the dose and distribution of UV exposure received on the basis of ground irradiation and morphological data. Standard 3D computer graphics techniques were adapted to develop a rendering engine that estimates the solar exposure of a virtual manikin depicted as a triangle mesh surface. The amount of solar energy received by each triangle was calculated, taking into account reflected, direct and diffuse radiation, and shading from other body parts. Dosimetric measurements (n = 54) were conducted in field conditions using a foam manikin as surrogate for an exposed individual. Dosimetric results were compared to the model predictions. The model predicted exposure to solar UV adequately. The symmetric mean absolute percentage error was 13%. Half of the predictions were within 17% range of the measurements. This model provides a tool to assess outdoor occupational and recreational UV exposures, without necessitating time‐consuming individual dosimetry, with numerous potential uses in skin cancer prevention and research.
Nature Communications | 2016
Jayne Y. Hehir-Kwa; Tobias Marschall; Wigard P. Kloosterman; Laurent C. Francioli; Jasmijn A. Baaijens; Louis J. Dijkstra; Abdel Abdellaoui; Vyacheslav Koval; Djie Tjwan Thung; René Wardenaar; Ivo Renkens; Bradley P. Coe; Patrick Deelen; Joep de Ligt; Eric-Wubbo Lameijer; Freerk van Dijk; Fereydoun Hormozdiari; Jasper Bovenberg; Anton J. M. de Craen; Marian Beekman; Albert Hofman; Gonneke Willemsen; Bruce H. R. Wolffenbuttel; Mathieu Platteel; Yuanping Du; Ruoyan Chen; Hongzhi Cao; Rui Cao; Yushen Sun; Jeremy Sujie Cao
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.
Nature Communications | 2015
Elisabeth M. van Leeuwen; Lennart C. Karssen; Joris Deelen; Aaron Isaacs; Carolina Medina-Gomez; Hamdi Mbarek; Alexandros Kanterakis; Stella Trompet; Iris Postmus; Niek Verweij; David van Enckevort; Jennifer E. Huffman; Charles C. White; Mary F. Feitosa; Traci M. Bartz; Ani Manichaikul; Peter K. Joshi; Gina M. Peloso; Patrick Deelen; Freerk van Dijk; Gonneke Willemsen; Eco J. de Geus; Yuri Milaneschi; Laurent C. Francioli; Androniki Menelaou; Sara L. Pulit; Fernando Rivadeneira; Albert Hofman; Ben A. Oostra; Oscar H. Franco
Variants associated with blood lipid levels may be population-specific. To identify low-frequency variants associated with this phenotype, population-specific reference panels may be used. Here we impute nine large Dutch biobanks (~35,000 samples) with the population-specific reference panel created by the Genome of the Netherlands Project and perform association testing with blood lipid levels. We report the discovery of five novel associations at four loci (P value <6.61 × 10−4), including a rare missense variant in ABCA6 (rs77542162, p.Cys1359Arg, frequency 0.034), which is predicted to be deleterious. The frequency of this ABCA6 variant is 3.65-fold increased in the Dutch and its effect (βLDL-C=0.135, βTC=0.140) is estimated to be very similar to those observed for single variants in well-known lipid genes, such as LDLR.