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The genetic architecture of skeletal convergence and sex determination in ninespine sticklebacks.

ABSTRACT: The history of life offers plentiful examples of convergent evolution, the independent derivation of similar phenotypes in distinct lineages. The emergence of convergent phenotypes among closely related lineages (frequently termed "parallel" evolution) is often assumed to result from changes in similar genes or developmental pathways, but the genetic origins of convergence remains poorly understood. Ninespine (Pungitius pungitius) and threespine (Gasterosteus aculeatus) stickleback fish provide many examples of convergent evolution of adaptive phenotypes, both within and between genera. The genetic architecture of several important traits is now known for threespine sticklebacks; thus, ninespine sticklebacks provide a unique opportunity to critically test whether similar or different chromosome regions control similar phenotypes in these lineages. We have generated the first genome-wide linkage map for ninespine sticklebacks and used quantitative trait locus mapping to identify chromosome regions controlling several skeletal traits and sex determination. In ninespine sticklebacks, these traits mapped to chromosome regions not previously known to control the corresponding traits in threespine sticklebacks. Therefore, convergent morphological evolution in these related, but independent, vertebrate lineages might have different genetic origins. Comparative genetics in sticklebacks provides an exciting opportunity to study the mechanisms controlling similar phenotypic changes in different animal groups.

SUBMITTER: Shapiro MD

PROVIDER: S-EPMC2735127 | biostudies-literature | 2009 Jul

REPOSITORIES: biostudies-literature

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The genetic architecture of skeletal convergence and sex determination in ninespine sticklebacks.

Shapiro Michael D MD Summers Brian R BR Balabhadra Sarita S Aldenhoven Jaclyn T JT Miller Ashley L AL Cunningham Christopher B CB Bell Michael A MA Kingsley David M DM

Current biology : CB 20090604 13

The history of life offers plentiful examples of convergent evolution, the independent derivation of similar phenotypes in distinct lineages. The emergence of convergent phenotypes among closely related lineages (frequently termed "parallel" evolution) is often assumed to result from changes in similar genes or developmental pathways, but the genetic origins of convergence remains poorly understood. Ninespine (Pungitius pungitius) and threespine (Gasterosteus aculeatus) stickleback fish provide ...[more]

PMID: 19500990

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Project description:BACKGROUND:One of the fundamental problems of modern genomics is to extract the genetic architecture of a complex trait from a data set of individual genotypes and trait values. Establishing this important connection between genotype and phenotype is complicated by the large number of candidate genes, the potentially large number of causal loci, and the likely presence of some nonlinear interactions between different genes. Compressed Sensing methods obtain solutions to under-constrained systems of linear equations. These methods can be applied to the problem of determining the best model relating genotype to phenotype, and generally deliver better performance than simply regressing the phenotype against each genetic variant, one at a time. We introduce a Compressed Sensing method that can reconstruct nonlinear genetic models (i.e., including epistasis, or gene-gene interactions) from phenotype-genotype (GWAS) data. Our method uses L1-penalized regression applied to nonlinear functions of the sensing matrix. RESULTS:The computational and data resource requirements for our method are similar to those necessary for reconstruction of linear genetic models (or identification of gene-trait associations), assuming a condition of generalized sparsity, which limits the total number of gene-gene interactions. An example of a sparse nonlinear model is one in which a typical locus interacts with several or even many others, but only a small subset of all possible interactions exist. It seems plausible that most genetic architectures fall in this category. We give theoretical arguments suggesting that the method is nearly optimal in performance, and demonstrate its effectiveness on broad classes of nonlinear genetic models using simulated human genomes and the small amount of currently available real data. A phase transition (i.e., dramatic and qualitative change) in the behavior of the algorithm indicates when sufficient data is available for its successful application. CONCLUSION:Our results indicate that predictive models for many complex traits, including a variety of human disease susceptibilities (e.g., with additive heritability h (2)?0.5), can be extracted from data sets comprised of n ??100s individuals, where s is the number of distinct causal variants influencing the trait. For example, given a trait controlled by ?10 k loci, roughly a million individuals would be sufficient for application of the method.

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The genetic architecture of skeletal convergence and sex determination in ninespine sticklebacks.

Publications

The genetic architecture of skeletal convergence and sex determination in ninespine sticklebacks.

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