Genome-wide association analyses (GWAS) have proved an effective tool for exploring the biology of complex traits, with many new loci being identified. However, it is also clear that much of the genetic variation underlying complex traits remains to be detected – the so called missing heritability. The limited proportion of complex trait variance identified in GWAS reflects the limited power of single SNP analyses to detect either rare causative alleles or those of small effect.
We have recently developed a method to estimate the variance contributed by sequential short regions of the genome to the total trait variation using information on relationships between individuals based on local SNP data. We use this local relationship to estimate the heritability that is associated with each region (the regional heritability) of the genome, representing the integrated effects of both common and rare variants in that region, and serves to localise the responsible loci. We have shown that regional heritability estimates are correlated with results from genome-wide association analysis but capture more of the genetic variance segregating in the population and identify additional trait loci.
However, these analyses can potentially be made more powerful by using information from haplotypes of genetic markers. These should be even more effective at inferring relationships between distantly related individuals than the current approach and so will have more power to detect genetic effects.
The current project is aimed at combining our current advances in mapping methodology with those in the field of haplotype inference to develop methods that are even more effective at locating missing heritability of complex traits. The methods will be explored and optimised using simulated data and then evaluated on several different populations
We have recently developed a method which uses information on relationships between individuals based on local SNP data to estimate the heritability of specific regions (the regional heritability) of the genome, and it represents the integrated effects of both common and rare variants in that region. Previously, we showed that this method capture more of the genetic variance segregating in the population than standard GWAS studies.
The current project is to further develop the regional heritability mapping method by incorporating information of haplotype to make it even more effective at locating missing heritability of complex traits. The improved method will be optimised using simulated data and then evaluated on several different populations.
We have proposed and developed several approaches to use haplotype information to calculate regional relationships between individuals
We have tested these approaches using simulations, and the general results suggest that they seem more robust to
|Effective start/end date||1/01/12 → 31/12/14|