A fast and flexible statistical model for large-scale population genotype data: applications to inferring missing genotypes and haplotypic phase

We present a statistical model for patterns of genetic variation in samples of unrelated individuals from natural populations. This model is based on the idea that, over short regions, haplotypes in a population tend to cluster into groups of similar haplotypes. To capture the fact that, because of recombination, this clustering tends to be local in nature, our model allows cluster memberships to change continuously along the chromosome according to a hidden Markov model. This approach is flexible, allowing for both "block-like" patterns of linkage disequilibrium (LD) and gradual decline in LD with distance. The resulting model is also fast and, as a result, is practicable for large data sets (e.g., thousands of individuals typed at hundreds of thousands of markers). We illustrate the utility of the model by applying it to dense single-nucleotide-polymorphism genotype data for the tasks of imputing missing genotypes and estimating haplotypic phase. For imputing missing genotypes, methods based on this model are as accurate or more accurate than existing methods. For haplotype estimation, the point estimates are slightly less accurate than those from the best existing methods (e.g., for unrelated Centre d'Etude du Polymorphisme Humain individuals from the HapMap project, switch error was 0.055 for our method vs. 0.051 for PHASE) but require a small fraction of the computational cost. In addition, we demonstrate that the model accurately reflects uncertainty in its estimates, in that probabilities computed using the model are approximately well calibrated. The methods described in this article are implemented in a software package, fastPHASE, which is available from the Stephens Lab Web site.     

A revised model for AMP-activated protein kinase structure: The alpha-subunit binds to both the beta- and gamma-subunits although there is no direct binding between the beta- and gamma-subunits

The 5'-AMP-activated protein kinase (AMPK) is a master sensor for cellular metabolic energy state. It is activated by a high AMP/ATP ratio and leads to metabolic changes that conserve energy and utilize alternative cellular fuel sources. The kinase is composed of a heterotrimeric protein complex containing a catalytic alpha-subunit, an AMP-binding gamma-subunit, and a scaffolding beta-subunit thought to bind directly both the alpha- and gamma-subunits. Here, we use coimmunoprecipitation of proteins in transiently transfected cells to show that the alpha2-subunit binds directly not only to the beta-subunit, confirming previous work, but also to the gamma1-subunit. Deletion analysis of the alpha2-subunit reveals that the C-terminal 386-552 residues are sufficient to bind to the beta-subunit. The gamma1-subunit binds directly to the alpha2-subunit at two interaction sites, one within the catalytic domain consisting of alpha2 amino acids 1-312 and a second within residues 386-552. Binding of the alpha2 and the gamma1-subunits was not affected by 400 mum AMP or ATP. Furthermore, we show that the beta-subunit C terminus is essential for binding to the alpha2-subunit but, in contrast to previous work, the beta-subunit does not bind directly to the gamma1-subunit. Taken together, this study presents a new model for AMPK heterotrimer structure where through its C terminus the beta-subunit binds to the alpha-subunit that, in turn, binds to the gamma-subunit. There is no direct interaction between the beta- and gamma-subunits.