TY - JOUR T1 - A general approach for haplotype phasing across the full spectrum of relatedness. JF - PLoS Genet Y1 - 2014 A1 - O'Connell, Jared A1 - Gurdasani, Deepti A1 - Delaneau, Olivier A1 - Pirastu, Nicola A1 - Ulivi, Sheila A1 - Cocca, Massimiliano A1 - Traglia, Michela A1 - Huang, Jie A1 - Huffman, Jennifer E A1 - Rudan, Igor A1 - McQuillan, Ruth A1 - Fraser, Ross M A1 - Campbell, Harry A1 - Polasek, Ozren A1 - Asiki, Gershim A1 - Ekoru, Kenneth A1 - Hayward, Caroline A1 - Wright, Alan F A1 - Vitart, Veronique A1 - Navarro, Pau A1 - Zagury, Jean-Francois A1 - Wilson, James F A1 - Toniolo, Daniela A1 - Gasparini, Paolo A1 - Soranzo, Nicole A1 - Sandhu, Manjinder S A1 - Marchini, Jonathan KW - Chromosome Mapping KW - Cohort Effect KW - Family KW - Genotype KW - Haplotypes KW - Humans KW - Models, Genetic KW - Pedigree KW - Phenotype KW - Recombination, Genetic AB -

Many existing cohorts contain a range of relatedness between genotyped individuals, either by design or by chance. Haplotype estimation in such cohorts is a central step in many downstream analyses. Using genotypes from six cohorts from isolated populations and two cohorts from non-isolated populations, we have investigated the performance of different phasing methods designed for nominally 'unrelated' individuals. We find that SHAPEIT2 produces much lower switch error rates in all cohorts compared to other methods, including those designed specifically for isolated populations. In particular, when large amounts of IBD sharing is present, SHAPEIT2 infers close to perfect haplotypes. Based on these results we have developed a general strategy for phasing cohorts with any level of implicit or explicit relatedness between individuals. First SHAPEIT2 is run ignoring all explicit family information. We then apply a novel HMM method (duoHMM) to combine the SHAPEIT2 haplotypes with any family information to infer the inheritance pattern of each meiosis at all sites across each chromosome. This allows the correction of switch errors, detection of recombination events and genotyping errors. We show that the method detects numbers of recombination events that align very well with expectations based on genetic maps, and that it infers far fewer spurious recombination events than Merlin. The method can also detect genotyping errors and infer recombination events in otherwise uninformative families, such as trios and duos. The detected recombination events can be used in association scans for recombination phenotypes. The method provides a simple and unified approach to haplotype estimation, that will be of interest to researchers in the fields of human, animal and plant genetics.

VL - 10 IS - 4 U1 - http://www.ncbi.nlm.nih.gov/pubmed/24743097?dopt=Abstract ER - TY - JOUR T1 - Evidence of inbreeding depression on human height. JF - PLoS Genet Y1 - 2012 A1 - McQuillan, Ruth A1 - Eklund, Niina A1 - Pirastu, Nicola A1 - Kuningas, Maris A1 - McEvoy, Brian P A1 - Esko, Tõnu A1 - Corre, Tanguy A1 - Davies, Gail A1 - Kaakinen, Marika A1 - Lyytikäinen, Leo-Pekka A1 - Kristiansson, Kati A1 - Havulinna, Aki S A1 - Gögele, Martin A1 - Vitart, Veronique A1 - Tenesa, Albert A1 - Aulchenko, Yurii A1 - Hayward, Caroline A1 - Johansson, Åsa A1 - Boban, Mladen A1 - Ulivi, Sheila A1 - Robino, Antonietta A1 - Boraska, Vesna A1 - Igl, Wilmar A1 - Wild, Sarah H A1 - Zgaga, Lina A1 - Amin, Najaf A1 - Theodoratou, Evropi A1 - Polasek, Ozren A1 - Girotto, Giorgia A1 - Lopez, Lorna M A1 - Sala, Cinzia A1 - Lahti, Jari A1 - Laatikainen, Tiina A1 - Prokopenko, Inga A1 - Kals, Mart A1 - Viikari, Jorma A1 - Yang, Jian A1 - Pouta, Anneli A1 - Estrada, Karol A1 - Hofman, Albert A1 - Freimer, Nelson A1 - Martin, Nicholas G A1 - Kähönen, Mika A1 - Milani, Lili A1 - Heliövaara, Markku A1 - Vartiainen, Erkki A1 - Räikkönen, Katri A1 - Masciullo, Corrado A1 - Starr, John M A1 - Hicks, Andrew A A1 - Esposito, Laura A1 - Kolcic, Ivana A1 - Farrington, Susan M A1 - Oostra, Ben A1 - Zemunik, Tatijana A1 - Campbell, Harry A1 - Kirin, Mirna A1 - Pehlic, Marina A1 - Faletra, Flavio A1 - Porteous, David A1 - Pistis, Giorgio A1 - Widen, Elisabeth A1 - Salomaa, Veikko A1 - Koskinen, Seppo A1 - Fischer, Krista A1 - Lehtimäki, Terho A1 - Heath, Andrew A1 - McCarthy, Mark I A1 - Rivadeneira, Fernando A1 - Montgomery, Grant W A1 - Tiemeier, Henning A1 - Hartikainen, Anna-Liisa A1 - Madden, Pamela A F A1 - d'Adamo, Pio A1 - Hastie, Nicholas D A1 - Gyllensten, Ulf A1 - Wright, Alan F A1 - van Duijn, Cornelia M A1 - Dunlop, Malcolm A1 - Rudan, Igor A1 - Gasparini, Paolo A1 - Pramstaller, Peter P A1 - Deary, Ian J A1 - Toniolo, Daniela A1 - Eriksson, Johan G A1 - Jula, Antti A1 - Raitakari, Olli T A1 - Metspalu, Andres A1 - Perola, Markus A1 - Järvelin, Marjo-Riitta A1 - Uitterlinden, André A1 - Visscher, Peter M A1 - Wilson, James F KW - Adult KW - Aged KW - Body Height KW - Consanguinity KW - Databases, Genetic KW - Family KW - Female KW - Genes, Recessive KW - Genetic Heterogeneity KW - Genome-Wide Association Study KW - Homozygote KW - Humans KW - Male KW - Middle Aged KW - Polymorphism, Single Nucleotide KW - Quantitative Trait, Heritable AB -

Stature is a classical and highly heritable complex trait, with 80%-90% of variation explained by genetic factors. In recent years, genome-wide association studies (GWAS) have successfully identified many common additive variants influencing human height; however, little attention has been given to the potential role of recessive genetic effects. Here, we investigated genome-wide recessive effects by an analysis of inbreeding depression on adult height in over 35,000 people from 21 different population samples. We found a highly significant inverse association between height and genome-wide homozygosity, equivalent to a height reduction of up to 3 cm in the offspring of first cousins compared with the offspring of unrelated individuals, an effect which remained after controlling for the effects of socio-economic status, an important confounder (χ(2) = 83.89, df = 1; p = 5.2 × 10(-20)). There was, however, a high degree of heterogeneity among populations: whereas the direction of the effect was consistent across most population samples, the effect size differed significantly among populations. It is likely that this reflects true biological heterogeneity: whether or not an effect can be observed will depend on both the variance in homozygosity in the population and the chance inheritance of individual recessive genotypes. These results predict that multiple, rare, recessive variants influence human height. Although this exploratory work focuses on height alone, the methodology developed is generally applicable to heritable quantitative traits (QT), paving the way for an investigation into inbreeding effects, and therefore genetic architecture, on a range of QT of biomedical importance.

VL - 8 IS - 7 U1 - http://www.ncbi.nlm.nih.gov/pubmed/22829771?dopt=Abstract ER -