Optimized ancestral state reconstruction using Sankoff parsimony

A geographic history of human genetic ancestry

Describing the distribution of genetic variation across individuals is a fundamental goal of population genetics. In humans, traditional approaches for describing population genetic variation often rely on discrete genetic ancestry labels, which, despite their utility, can obscure the complex, multi-faceted nature of human genetic history. These labels risk oversimplifying ancestry by ignoring its temporal depth and geographic continuity, and may therefore conflate notions of race, ethnicity, geography, and genetic ancestry. Here, we present a method that capitalizes on the rich genealogical information encoded in genomic tree sequences to infer the geographic locations of the shared ancestors of a sample of sequenced individuals. We use this method to infer the geographic history of genetic ancestry of a set of human genomes sampled from Europe, Asia, and Africa, accurately recovering major population movements on those continents. Our findings demonstrate the importance of defining the spatial-temporal context of genetic ancestry to describing human genetic variation and caution against the oversimplified interpretations of genetic data prevalent in contemporary discussions of race and ancestry.

B cell phylogenetics in the single cell era

The widespread availability of single-cell RNA sequencing (scRNA-seq) has led to the development of new methods for understanding immune responses. Single-cell transcriptome data can now be paired with B cell receptor (BCR) sequences. However, RNA from BCRs cannot be analyzed like most other genes because BCRs are genetically diverse within individuals. In humans, BCRs are shaped through recombination followed by mutation and selection for antigen binding. As these processes co-occur with cell division, B cells can be studied using phylogenetic trees representing the mutations within a clone. B cell trees can link experimental timepoints, tissues, or cellular subtypes. Here, we review the current state and potential of how B cell phylogenetics can be combined with single-cell data to understand immune responses.

Determining Significant Correlation Between Pairs of Extant Characters in a Small Parsimony Framework

When studying the evolutionary relationships among a set of species, the principle of parsimony states that a relationship involving the fewest number of evolutionary events is likely the correct one. Due to its simplicity, this principle was formalized in the context of computational evolutionary biology decades ago by, for example, Fitch and Sankoff. Because the parsimony framework does not require a model of evolution, unlike maximum likelihood or Bayesian approaches, it is often a good starting point when no reasonable estimate of such a model is available. In this work, we devise a method for determining if pairs of discrete characters are significantly correlated across all most parsimonious reconstructions, given a set of species on these characters, and an evolutionary tree. The first step of this method is to use Sankoff's algorithm to compute all most parsimonious assignments of ancestral states (of each character) to the internal nodes of the phylogeny. Correlation between a pair of evolutionary events (e.g., absent to present) for a pair of characters is then determined by the (co-) occurrence patterns between the sets of their respective ancestral assignments. The probability of obtaining a correlation this extreme (or more) under a null hypothesis where the events happen randomly on the evolutionary tree is then used to assess the significance of this correlation. We implement this method: parcours (PARsimonious CO-occURrenceS) and use it to identify significantly correlated evolution among vocalizations and morphological characters in the Felidae family.

TNT version 1.5, including a full implementation of phylogenetic morphometrics

Version 1.5 of the computer program TNT completely integrates landmark data into phylogenetic analysis. Landmark data consist of coordinates (in two or three dimensions) for the terminal taxa; TNT reconstructs shapes for the internal nodes such that the difference between ancestor and descendant shapes for all tree branches sums up to a minimum; this sum is used as tree score. Landmark data can be analysed alone or in combination with standard characters; all the applicable commands and options in TNT can be used transparently after reading a landmark data set. The program continues implementing all the types of analyses in former versions, including discrete and continuous characters (which can now be read at any scale, and automatically rescaled by TNT). Using algorithms described in this paper, searches for landmark data can be made tens to hundreds of times faster than it was possible before (from T to 3T times faster, where T is the number of taxa), thus making phylogenetic analysis of landmarks feasible even on standard personal computers.

The histone modification H3K27me3 is retained after gene duplication and correlates with conserved noncoding sequences in Arabidopsis

The histone modification H3K27me3 is involved in repression of transcription and plays a crucial role in developmental transitions in both animals and plants. It is deposited by PRC2 (Polycomb repressive complex 2), a conserved protein complex. In Arabidopsis thaliana, H3K27me3 is found at 15% of all genes. These tend to encode transcription factors and other regulators important for development. However, it is not known how PRC2 is recruited to target loci nor how this set of target genes arose during Arabidopsis evolution. To resolve the latter, we integrated A. thaliana gene families with five independent genome-wide H3K27me3 data sets. Gene families were either significantly enriched or depleted of H3K27me3, showing a strong impact of shared ancestry to H3K27me3 distribution. To quantify this, we performed ancestral state reconstruction of H3K27me3 on phylogenetic trees of gene families. The set of H3K27me3-marked genes changed less than expected by chance, suggesting that H3K27me3 was retained after gene duplication. This retention suggests that the PRC2-recruiting signal could be encoded in the DNA and also conserved among certain duplicated genes. Indeed, H3K27me3-marked genes were overrepresented among paralogs sharing conserved noncoding sequences (CNSs) that are enriched with transcription factor binding sites. The association of upstream CNSs with H3K27me3-marked genes represents the first genome-wide connection between H3K27me3 and potential regulatory elements in plants. Thus, we propose that CNSs likely function as part of the PRC2 recruitment in plants.

Gene network biological validity based on gene-gene interaction relevance

In recent years, gene networks have become one of the most useful tools for modeling biological processes. Many inference gene network algorithms have been developed as techniques for extracting knowledge from gene expression data. Ensuring the reliability of the inferred gene relationships is a crucial task in any study in order to prove that the algorithms used are precise. Usually, this validation process can be carried out using prior biological knowledge. The metabolic pathways stored in KEGG are one of the most widely used knowledgeable sources for analyzing relationships between genes. This paper introduces a new methodology, GeneNetVal, to assess the biological validity of gene networks based on the relevance of the gene-gene interactions stored in KEGG metabolic pathways. Hence, a complete KEGG pathway conversion into a gene association network and a new matching distance based on gene-gene interaction relevance are proposed. The performance of GeneNetVal was established with three different experiments. Firstly, our proposal is tested in a comparative ROC analysis. Secondly, a randomness study is presented to show the behavior of GeneNetVal when the noise is increased in the input network. Finally, the ability of GeneNetVal to detect biological functionality of the network is shown.

Analysis on the reconstruction accuracy of the Fitch method for inferring ancestral states

Background

As one of the most widely used parsimony methods for ancestral reconstruction, the Fitch method minimizes the total number of hypothetical substitutions along all branches of a tree to explain the evolution of a character. Due to the extensive usage of this method, it has become a scientific endeavor in recent years to study the reconstruction accuracies of the Fitch method. However, most studies are restricted to 2-state evolutionary models and a study for higher-state models is needed since DNA sequences take the format of 4-state series and protein sequences even have 20 states.

Results

In this paper, the ambiguous and unambiguous reconstruction accuracy of the Fitch method are studied for N-state evolutionary models. Given an arbitrary phylogenetic tree, a recurrence system is first presented to calculate iteratively the two accuracies. As complete binary tree and comb-shaped tree are the two extremal evolutionary tree topologies according to balance, we focus on the reconstruction accuracies on these two topologies and analyze their asymptotic properties. Then, 1000 Yule trees with 1024 leaves are generated and analyzed to simulate real evolutionary scenarios. It is known that more taxa not necessarily increase the reconstruction accuracies under 2-state models. The result under N-state models is also tested.

Conclusions

In a large tree with many leaves, the reconstruction accuracies of using all taxa are sometimes less than those of using a leaf subset under N-state models. For complete binary trees, there always exists an equilibrium interval [a, b] of conservation probability, in which the limiting ambiguous reconstruction accuracy equals to the probability of randomly picking a state. The value b decreases with the increase of the number of states, and it seems to converge. When the conservation probability is greater than b, the reconstruction accuracies of the Fitch method increase rapidly. The reconstruction accuracies on 1000 simulated Yule trees also exhibit similar behaviors. For comb-shaped trees, the limiting reconstruction accuracies of using all taxa are always less than or equal to those of using the nearest root-to-leaf path when the conservation probability is not less than 1N. As a result, more taxa are suggested for ancestral reconstruction when the tree topology is balanced and the sequences are highly similar, and a few taxa close to the root are recommended otherwise.