Data from: Phylogenetic comparative methods on phylogenetic networks with reticulations

The goal of Phylogenetic Comparative Methods (PCMs) is to study the
distribution of quantitative traits among related species. The observed
traits are often seen as the result of a Brownian Motion (BM) along the
branches of a phylogenetic tree. Reticulation events such as
hybridization, gene flow or horizontal gene transfer, can substantially
affect a species' traits, but are not modeled by a tree. Phylogenetic
networks have been designed to represent reticulate evolution. As they
become available for downstream analyses, new models of trait evolution
are needed, applicable to networks. One natural extension of the BM is to
use a weighted average model for the trait of a hybrid, at a reticulation
point. We develop here an efficient recursive algorithm to compute the
phylogenetic variance matrix of a trait on a network, in only one preorder
traversal of the network. We then extend the standard PCM tools to this
new framework, including phylogenetic regression with covariates (or
phylogenetic ANOVA), ancestral trait reconstruction, and Pagel's λ
test of phylogenetic signal. The trait of a hybrid is sometimes outside of
the range of its two parents, for instance because of hybrid vigor or
hybrid depression. These two phenomena are rather commonly observed in
present-day hybrids. Transgressive evolution can be modeled as a shift in
the trait value following a reticulation point. We develop a general
framework to handle such shifts, and take advantage of the phylogenetic
regression view of the problem to design statistical tests for ancestral
transgressive evolution in the evolutionary history of a group of species.
We study the power of these tests in several scenarios, and show that
recent events have indeed the strongest impact on the trait distribution
of present-day taxa. We apply those methods to a dataset of Xiphophorus
fishes, to confirm and complete previous analysis in this group. All the
methods developed here are available in the Julia package PhyloNetworks.

系统发育比较方法（Phylogenetic Comparative Methods, PCMs）的核心目标是探究近缘物种间数量性状的分布规律。观测得到的性状通常被视作沿系统发育树分支开展的布朗运动（Brownian Motion, BM）的结果。诸如杂交、基因流或水平基因转移等网状进化事件，可对物种性状产生显著影响，但传统系统发育树无法对这类事件进行建模。系统发育网络正是为表征网状进化而设计的工具。随着这类网络可用于下游分析，亟需适配于网络结构的全新性状进化模型。对布朗运动模型的一项自然拓展，是在网状进化节点处为杂种性状采用加权平均模型。本文提出一种高效的递归算法，仅需对系统发育网络进行一次前序遍历，即可计算得到性状在网络上的系统发育方差-协方差矩阵。随后，我们将标准的系统发育比较方法工具拓展至这一新框架中，涵盖带协变量的系统发育回归（或系统发育方差分析）、祖先性状重建，以及用于检测系统发育信号的Pagel’s λ检验。杂种的性状有时会超出其双亲的性状范围，例如因杂种优势或杂种衰退所致——这两种现象在现存杂种中相当常见。超亲进化可被建模为网状进化节点后发生的性状值偏移。我们构建了一套可处理这类偏移的通用框架，并借助该问题的系统发育回归视角，设计出用于检测物种类群演化历史中祖先超亲进化的统计检验方法。我们在多种场景下检验了这些检验方法的效力，并证实近期发生的网状进化事件对现存类群的性状分布影响最为显著。我们将所提出的方法应用于剑尾鱼属（Xiphophorus）鱼类数据集，以验证并完善该类群此前的相关分析。本文开发的所有方法均可通过Julia包PhyloNetworks获取使用。