Divergence-Based Introgression Polarization

Selection Shapes the Genomic Landscape of Introgressed Ancestry in a Pair of Sympatric Sea Urchin Species

A growing number of recent studies have demonstrated that introgression is common across the tree of life. However, we still have a limited understanding of the fate and fitness consequence of introgressed variation at the whole-genome scale across diverse taxonomic groups. Here, we implemented a phylogenetic hidden Markov model to identify and characterize introgressed genomic regions in a pair of well-diverged, nonsister sea urchin species: Strongylocentrotus pallidus and Strongylocentrotus droebachiensis. Despite the old age of introgression, a sizable fraction of the genome (1% to 5%) exhibited introgressed ancestry, including numerous genes showing signals of historical positive selection that may represent cases of adaptive introgression. One striking result was the overrepresentation of hyalin genes in the identified introgressed regions despite observing considerable overall evidence of selection against introgression. There was a negative correlation between introgression and chromosome gene density, and two chromosomes were observed with considerably reduced introgression. Relative to the nonintrogressed genome-wide background, introgressed regions had significantly reduced nucleotide divergence (dXY) and overlapped fewer protein-coding genes, coding bases, and genes with a history of positive selection. Additionally, genes residing within introgressed regions showed slower rates of evolution (dN, dS, dN/dS) than random samples of genes without introgressed ancestry. Overall, our findings are consistent with widespread selection against introgressed ancestry across the genome and suggest that slowly evolving, low-divergence genomic regions are more likely to move between species and avoid negative selection following hybridization and introgression.

Genome sequencing reveals evidence of adaptive variation in the genus Zea

Maize is a globally valuable commodity and one of the most extensively studied genetic model organisms. However, we know surprisingly little about the extent and potential utility of the genetic variation found in wild relatives of maize. Here, we characterize a high-density genomic variation map from 744 genomes encompassing maize and all wild taxa of the genus Zea, identifying over 70 million single-nucleotide polymorphisms. The variation map reveals evidence of selection within taxa displaying novel adaptations. We focus on adaptive alleles in highland teosinte and temperate maize, highlighting the key role of flowering-time-related pathways in their adaptation. To show the utility of variants in these data, we generate mutant alleles for two flowering-time candidate genes. This work provides an extensive sampling of the genetic diversity of Zea, resolving questions on evolution and identifying adaptive variants for direct use in modern breeding.

Ghost lineages can invalidate or even reverse findings regarding gene flow

Introgression, endosymbiosis, and gene transfer, i.e., horizontal gene flow (HGF), are primordial sources of innovation in all domains of life. Our knowledge on HGF relies on detection methods that exploit some of its signatures left on extant genomes. One of them is the effect of HGF on branch lengths of constructed phylogenies. This signature has been formalized in statistical tests for HGF detection and used for example to detect massive adaptive gene flows in malaria vectors or to order evolutionary events involved in eukaryogenesis. However, these studies rely on the assumption that ghost lineages (all unsampled extant and extinct taxa) have little influence. We demonstrate here with simulations and data reanalysis that when considering the more realistic condition that unsampled taxa are legion compared to sampled ones, the conclusion of these studies become unfounded or even reversed. This illustrates the necessity to recognize the existence of ghosts in evolutionary studies.

Phylogenomic approaches to detecting and characterizing introgression

Phylogenomics has revealed the remarkable frequency with which introgression occurs across the tree of life. These discoveries have been enabled by the rapid growth of methods designed to detect and characterize introgression from whole-genome sequencing data. A large class of phylogenomic methods makes use of data across species to infer and characterize introgression based on expectations from the multispecies coalescent. These methods range from simple tests, such as the D-statistic, to model-based approaches for inferring phylogenetic networks. Here, we provide a detailed overview of the various signals that different modes of introgression are expected leave in the genome, and how current methods are designed to detect them. We discuss the strengths and pitfalls of these approaches and identify areas for future development, highlighting the different signals of introgression, and the power of each method to detect them. We conclude with a discussion of current challenges in inferring introgression and how they could potentially be addressed.

Chromosome-scale inference of hybrid speciation and admixture with convolutional neural networks

Inferring the frequency and mode of hybridization among closely related organisms is an important step for understanding the process of speciation and can help to uncover reticulated patterns of phylogeny more generally. Phylogenomic methods to test for the presence of hybridization come in many varieties and typically operate by leveraging expected patterns of genealogical discordance in the absence of hybridization. An important assumption made by these tests is that the data (genes or SNPs) are independent given the species tree. However, when the data are closely linked, it is especially important to consider their nonindependence. Recently, deep learning techniques such as convolutional neural networks (CNNs) have been used to perform population genetic inferences with linked SNPs coded as binary images. Here, we use CNNs for selecting among candidate hybridization scenarios using the tree topology (((P1 , P2 ), P3 ), Out) and a matrix of pairwise nucleotide divergence (dXY ) calculated in windows across the genome. Using coalescent simulations to train and independently test a neural network showed that our method, HyDe-CNN, was able to accurately perform model selection for hybridization scenarios across a wide breath of parameter space. We then used HyDe-CNN to test models of admixture in Heliconius butterflies, as well as comparing it to phylogeny-based introgression statistics. Given the flexibility of our approach, the dropping cost of long-read sequencing and the continued improvement of CNN architectures, we anticipate that inferences of hybridization using deep learning methods like ours will help researchers to better understand patterns of admixture in their study organisms.

Biased Gene Retention in the Face of Introgression Obscures Species Relationships

Phylogenomic analyses are recovering previously hidden histories of hybridization, revealing the genomic consequences of these events on the architecture of extant genomes. We applied phylogenomic techniques and several complementary statistical tests to show that introgressive hybridization appears to have occurred between close relatives of Arabidopsis, resulting in cytonuclear discordance and impacting our understanding of species relationships in the group. The composition of introgressed and retained genes indicates that selection against incompatible cytonuclear and nuclear-nuclear interactions likely acted during introgression, whereas linkage also contributed to genome composition through the retention of ancient haplotype blocks. We also applied divergence-based tests to determine the species branching order and distinguish donor from recipient lineages. Surprisingly, these analyses suggest that cytonuclear discordance arose via extensive nuclear, rather than cytoplasmic, introgression. If true, this would mean that most of the nuclear genome was displaced during introgression whereas only a small proportion of native alleles were retained.