Unearthing modes of climatic adaptation in underground storage organs across Liliales

The evolution of major innovations in life history strategies (how organisms gather and store energy and reproduce) is a primary theme of biodiversity research. In one remarkable example of a life history innovation, certain plants --- geophytes --- retreat underground using underground storage organs (USOs), and thus survive extended periods of unfavorable conditions. Geophytes have evolved multiple times independently across all major vascular plant lineages. Even within closely related lineages, however, geophytes show impressive variation in the morphological modifications (i.e. 'types' of USOs) that allow them to survive underground. With all this variation, it is unclear to what extent geophytes with different USO morphologies have converged in climatic niche, or have evolved distinct niches. To test this hypothesis, we extended existing phylogenetic comparative method approaches to test for links between hierarchical discrete traits and adaptation to environmental variation. We inferred a phylogeny of 621 species of Liliales and used the phylogeny and analysis pipeline to test the relationship between underground morphologies and different adaptive optima of climate seasonality. Contrary to expectation, plants with the same USO type do not share climatic niches more than expected by chance, with the exception of root morphology, where modified roots are associated with lower temperature seasonality. These findings suggest that root tubers may be adaptations to different climatic conditions than other types of USOs. Thus, the tissue type and developmental origin of the structure may influence the way it mediates ecological relationships and draws into question the appropriateness of ascribing broad ecological patterns uniformly across geophytes. This work provides a new framework for testing adaptive hypotheses and for linking ecological patterns across morphologically varying taxa.

A multivariate phylogenetic comparative method incorporating a flexible function between discrete and continuous traits

One major challenge of using the phylogenetic comparative method (PCM) is the analysis of the evolution of interrelated continuous and discrete traits in a single multivariate statistical framework. In addition, more intricate parameters such as branch-specific directional selection have rarely been integrated into such multivariate PCM frameworks. Here, originally motivated to analyze the complex evolutionary trajectories of group size (continuous variable) and social systems (discrete variable) in African subterranean rodents, we develop a flexible approach using approximate Bayesian computation (ABC). Specifically, our multivariate ABC-PCM method allows the user to flexibly model an underlying latent evolutionary function between continuous and discrete traits. The ABC-PCM also simultaneously incorporates complex evolutionary parameters such as branch-specific selection. This study highlights the flexibility of ABC-PCMs in analyzing the evolution of phenotypic traits interrelated in a complex manner.

An improved tree-based statistical method for genome-wide association study

In genetic studies, quantitative traits are found possibly associated with genetic data. Due to advanced sequencing technology, many methods have been proposed in genome wide association study (GWAS) to search the single nucleotide polymorphism (SNP) associated with the traits. Currently several methods that account for the evolutionary relatedness among individuals were developed. When comparing with conventional methods without evolutionary relatedness among individuals, tree based methods are found to have better performance when the population structure increases. In this work, we extend a couple of methods in previous studies by varying the magnitude of relatedness. The magnitude of relatedness of the evolutionary history is controlled by an Ornstein-Uhlenbeck (OU) process through its parameters. Our method combines a pertinent process and phylogenetic comparative method where the incorporated evolutionary history is built by SNP data. We perform simulation as well as analyze drosophila longevity data set.

An improved tree-based statistical method for genome-wide association study

In genetic studies, quantitative traits are found possibly associated with genetic data. Due to advanced sequencing technology, many methods have been proposed in genome wide association study (GWAS) to search the single nucleotide polymorphism (SNP) associated with the traits. Currently several methods that account for the evolutionary relatedness among individuals were developed. When comparing with conventional methods without evolutionary relatedness among individuals, tree based methods are found to have better performance when the population structure increases. In this work, we extend a couple of methods in previous studies by varying the magnitude of relatedness. The magnitude of relatedness of the evolutionary history is controlled by an Ornstein-Uhlenbeck (OU) process through its parameters. Our method combines a pertinent process and phylogenetic comparative method where the incorporated evolutionary history is built by SNP data. We perform simulation as well as analyze drosophila longevity data set.

An improved tree-based statistical method for genome-wide association study

In genetic studies, quantitative traits are found possibly associated with genetic data. Due to advanced sequencing technology, many methods have been proposed in genome wide association study (GWAS) to search the single nucleotide polymorphism (SNP) associated with the traits. Currently several methods that account for the evolutionary relatedness among individuals were developed. When comparing with conventional methods without evolutionary relatedness among individuals, tree based methods are found to have better performance when the population structure increases. In this work, we extend a couple of methods in previous studies by varying the magnitude of relatedness. The magnitude of relatedness of the evolutionary history is controlled by an Ornstein-Uhlenbeck (OU) process through its parameters. Our method combines a pertinent process and phylogenetic comparative method where the incorporated evolutionary history is built by SNP data. We perform simulation as well as analyze drosophila longevity data set.