Aims:

To execute a thorough analysis on evidence of selection acting on a suite of developmental, lifecourse and ageing-related genes.

Hypotheses:

This is an exploratory analysis and we are not testing any pre-defined hypotheses per se.

Methods:

We would like to use ALSPAC GWAS and imputed data as part of a project investigating the evolution of certain genes linked with development (LIN28B and KCNJ2) and ageing diseases (APOE), as well as other genes of interest in TLD's thesis (CHRNA5, SERPINA1). We will use various established approaches to conduct a rounded analysis for each genic region concerning whether there is evidence that selection has acted. We then plan to use the information gained from the selection detection phase, in addition to data from the 1000 Genomes Project, to model the action of selection via simulation approaches and tailor-made, informed, hypothetical selection models, to gain further insight into the values of key parameters. The selection detection stage will include calculation of haplotype-based statistics (e.g. iHS (Voight et al. (2006))) and the use of likelihood-based methods (Nielsen et al.(2009)), in addition to comparative population statistics (using 1000 Genomes data). Other selection detection methods may be incorporated as the analysis evolves. We request all genetic data for each named gene within 5mb of the gene start position, all genetic data between the gene start and stop positions, and all data within 5mb of the gene end position. (These surrounding regions may also harbour interesting signatures of selection). It is important to understand the mechanisms of selection acting on a locus. For example, in the case of APOE this has been studied in depth in the literature for the E2/3/4 haplotype (Fullerton et al.(2000), Drenos and Kirkwood (2010)). As yet, there is not a definitive conclusion for the evolutionary history of these alleles. We hope that by combining all available methods from the literature and by implementing these methods on a combination of different data sets, we will reach a more concrete conclusion for the APOE gene. In addition, we would like to use the information produced from the selection detection phase to run different models of selection for these genes and use Approximate Bayesian Computation methodology (Itan et al. (2009)) to calibrate the models with parameter estimations.

We would like to run this analysis (selection detection + model selection) on a suite of different genes which have been associated with developmental phenotypes (LIN28B - age at menarche (Perry et al(2009)), KCNJ2 - age at first tooth eruption (Pillas et al.(2010))) and ageing phenotypes (APOE - Alzheimer Disease), in addition to two genes with implications across the lifecourse (CHRNA5 - nicotine dependence, SERPINA1 - alpha 1-antitrypsin deficiency). The Proximal 14q32.1 SERPIN subcluster, for example, has been studied for evidence of selection (Seixas et al.(2007)) previously. The authors found evidence to suggest that a deletion in SERPINA2 has been positively selected in Africans. Despite having been studied in the past, we would still like to consider selection in and around SERPINA1 as our proposed work could benefit from larger sample sizes and the incorporation of other selection detection techniques, in addition to the benefits of using 1000 Genomes datasets. Additionally, we would like to computationally model selection signals to gain further insight. We would eventually like to execute a high level comparison of positive selection acting on early-acting versus late-acting traits (e.g. LIN28B/KCNJ2 vs APOE).

Note: exposure/outcome/confounding variables are not defined in this project

References

Stephanie M. Fullerton, et al., Apolipoprotein E Variation at the Sequence Haplotype Level: Implications for the Origin and Maintenance of a Major Human Polymorphism. American journal of human genetics,2000. 67(4): p. 881-900

Fotios Drenos and Thomas B. L. Kirkwood, Selection on Alleles Affecting Human Longevity and Late-Life Disease: The Example of Apolipoprotein E. PLoS ONE, 2010. 5(4): p. e10022.

Benjamin F. Voight, et al., A Map of Recent Positive Selection in the Human Genome. PLoS Biol, 2006. 4(3): p. e72.

Rasmus Nielsen, et al., Genomic scans for selective sweeps using SNP data. Genome Research, 2005. 15(11): p. 1566-1575.

Yuval Itan, et al., The Origins of Lactase Persistence in Europe. PLoS Comput Biol, 2009. 5(8): p. e1000491.

John R. B. Perry, et al., Meta-analysis of genome-wide association data identifies two loci influencing age at menarche. Nat Genet, 2009. 41(6): p. 648-650.John R. B. Perry, et al., Meta-analysis of genome-wide association data identifies two loci influencing age at menarche. Nat Genet, 2009. 41(6): p. 648-650.

Demetris Pillas, et al., Genome-Wide Association Study Reveals Multiple Loci Associated with Primary Tooth Development during Infancy. PLoS Genet, 2010. 6(2): p. e1000856

Susana Seixas, et al., Sequence Diversity at the Proximal 14q32.1 SERPIN Subcluster: Evidence for Natural Selection Favoring the Pseudogenization of SERPINA2. Molecular Biology and Evolution, 2007. 24(2): p. 587-598.