Towards reliable detection of introgression in the presence of among-species rate variation.

The role of interspecific hybridization has recently seen increasing attention, especially in the context of diversification dynamics. Genomic research has now made it abundantly clear that both hybridization and introgression - the exchange of genetic material through hybridization and backcrossing - are far more common than previously thought. Besides cases of ongoing or recent genetic exchange between taxa, an increasing number of studies report "ancient introgression" - referring to results of hybridization that took place in the distant past. However, it is not clear whether commonly used methods for the detection of introgression are applicable to such old systems, given that most of these methods were originally developed for analyses at the level of populations and recently diverged species, affected by recent or ongoing genetic exchange. In particular, the assumption of constant evolutionary rates, which is implicit in many commonly used approaches, is more likely to be violated as evolutionary divergence increases. To test the limitations of introgression detection methods when being applied to old systems, we simulated thousands of genomic datasets under a wide range of settings, with varying degrees of among-species rate variation and introgression. Using these simulated datasets, we showed that some commonly applied statistical methods, including the D-statistic and certain tests based on sets of local phylogenetic trees, can produce false-positive signals of introgression between divergent taxa that have different rates of evolution. These misleading signals are caused by the presence of homoplasies occurring at different rates in different lineages. To distinguish between the patterns caused by rate variation and genuine introgression, we developed a new test that is based on the expected clustering of introgressed sites along the genome, and implemented this test in the program Dsuite.

Uncovering ghost introgression through genomic analysis of a distinct eastern Asian hickory species.

Ghost introgression, or the transfer of genetic material from extinct or unsampled lineages to sampled species, has attracted much attention. However, conclusive evidence for ghost introgression, especially in plant species, remains scarce. Here, we newly assembled chromosome-level genomes for both Carya sinensis and Carya cathayensis, and additionally re-sequenced the whole genomes of 43 C. sinensis individuals as well as 11 individuals representing 11 diploid hickory species. These genomic datasets were used to investigate the reticulation and bifurcation patterns within the genus Carya (Juglandaceae), with a particular focus on the beaked hickory C. sinensis. By combining the D-statistic and BPP methods, we obtained compelling evidence that supports the occurrence of ghost introgression in C. sinensis from an extinct ancestral hickory lineage. This conclusion was reinforced through the phylogenetic network analysis and a genome scan method VolcanoFinder, the latter of which can detect signatures of adaptive introgression from unknown donors. Our results not only dispel certain misconceptions about the phylogenetic history of C. sinensis but also further refine our understanding of Carya's biogeography via divergence estimates. Moreover, the successful integration of the D-statistic and BPP methods demonstrates their efficacy in facilitating a more precise identification of introgression types.

Summary Tests of Introgression Are Highly Sensitive to Rate Variation Across Lineages.

The evolutionary implications and frequency of hybridization and introgression are increasingly being recognized across the tree of life. To detect hybridization from multi-locus and genome-wide sequence data, a popular class of methods are based on summary statistics from subsets of 3 or 4 taxa. However, these methods often carry the assumption of a constant substitution rate across lineages and genes, which is commonly violated in many groups. In this work, we quantify the effects of rate variation on the D test (also known as ABBA-BABA test), the D3 test, and HyDe. All 3 tests are used widely across a range of taxonomic groups, in part because they are very fast to compute. We consider rate variation across species lineages, across genes, their lineage-by-gene interaction, and rate variation across gene-tree edges. We simulated species networks according to a birth-death-hybridization process, so as to capture a range of realistic species phylogenies. For all 3 methods tested, we found a marked increase in the false discovery of reticulation (type-1 error rate) when there is rate variation across species lineages. The D3 test was the most sensitive, with around 80% type-1 error, such that D3 appears to more sensitive to a departure from the clock than to the presence of reticulation. For all 3 tests, the power to detect hybridization events decreased as the number of hybridization events increased, indicating that multiple hybridization events can obscure one another if they occur within a small subset of taxa. Our study highlights the need to consider rate variation when using site-based summary statistics, and points to the advantages of methods that do not require assumptions on evolutionary rates across lineages or across genes.

A Novel SARS-CoV-2 Viral Sequence Bioinformatic Pipeline Has Found Genetic Evidence That the Viral 3' Untranslated Region (UTR) Is Evolving and Generating Increased Viral Diversity.

An unprecedented amount of SARS-CoV-2 sequencing has been performed, however, novel bioinformatic tools to cope with and process these large datasets is needed. Here, we have devised a bioinformatic pipeline that inputs SARS-CoV-2 genome sequencing in FASTA/FASTQ format and outputs a single Variant Calling Format file that can be processed to obtain variant annotations and perform downstream population genetic testing. As proof of concept, we have analyzed over 229,000 SARS-CoV-2 viral sequences up until November 30, 2020. We have identified over 39,000 variants worldwide with increased polymorphisms, spanning the ORF3a gene as well as the 3' untranslated (UTR) regions, specifically in the conserved stem loop region of SARS-CoV-2 which is accumulating greater observed viral diversity relative to chance variation. Our analysis pipeline has also discovered the existence of SARS-CoV-2 hypermutation with low frequency (less than in 2% of genomes) likely arising through host immune responses and not due to sequencing errors. Among annotated non-sense variants with a population frequency over 1%, recurrent inactivation of the ORF8 gene was found. This was found to be present in the newly identified B.1.1.7 SARS-CoV-2 lineage that originated in the United Kingdom. Almost all VOC-containing genomes possess one stop codon in ORF8 gene (Q27∗), however, 13% of these genomes also contains another stop codon (K68∗), suggesting that ORF8 loss does not interfere with SARS-CoV-2 spread and may play a role in its increased virulence. We have developed this computational pipeline to assist researchers in the rapid analysis and characterization of SARS-CoV-2 variation.

Dsuite - Fast D-statistics and related admixture evidence from VCF files.

Patterson's D, also known as the ABBA-BABA statistic, and related statistics such as the f4 -ratio, are commonly used to assess evidence of gene flow between populations or closely related species. Currently available implementations often require custom file formats, implement only small subsets of the available statistics, and are impractical to evaluate all gene flow hypotheses across data sets with many populations or species due to computational inefficiencies. Here, we present a new software package Dsuite, an efficient implementation allowing genome scale calculations of the D and f4 -ratio statistics across all combinations of tens or hundreds of populations or species directly from a variant call format (VCF) file. Our program also implements statistics suited for application to genomic windows, providing evidence of whether introgression is confined to specific loci, and it can also aid in interpretation of a system of f4 -ratio results with the use of the "f-branch" method. Dsuite is available at https://github.com/millanek/Dsuite, is straightforward to use, substantially more computationally efficient than comparable programs, and provides a convenient suite of tools and statistics, including some not previously available in any software package. Thus, Dsuite facilitates the assessment of evidence for gene flow, especially across larger genomic data sets.

RADseq data reveal ancient, but not pervasive, introgression between Californian tree and scrub oak species (Quercus sect. Quercus: Fagaceae).

A long-term debate in evolutionary biology is the extent to which reproductive isolation is a necessary element of speciation. Hybridizing plants in general are cited as evidence against this notion, and oaks specifically have been used as the classic example of species maintenance without reproductive isolation. Here, we use thousands of SNPs generated by RAD sequencing to describe the phylogeny of a set of sympatric white oak species in California and then test whether these species exhibit pervasive interspecific gene exchange. Using RAD sequencing, we first constructed a phylogeny of ten oak species found in California. Our phylogeny revealed that seven scrub oak taxa occur within one clade that diverged from a common ancestor with Q. lobata, that they comprise two subclades, and they are not monophyletic but include the widespread tree oak Q. douglasii. Next, we searched for genomic patterns of allele sharing consistent with gene flow between long-divergent tree oaks with scrub oaks. Specifically, we utilized the D-statistic as well as model-based inference to compare the signature of shared alleles between two focal tree species (Q. lobata and Q. engelmannii) with multiple scrub species within the two subclades. We found that introgression is not equally pervasive between sympatric tree and scrub oak species. Instead, gene flow commonly occurs from scrub oaks to recently sympatric Q. engelmannii, but less so from scrub oaks to long-sympatric Q. lobata. This case study illustrates the influence of ancient introgression and impact of reproductive isolating mechanisms in preventing indiscriminate interspecific gene exchange.

Unraveling historical introgression and resolving phylogenetic discord within Catostomus (Osteichthys: Catostomidae).

BACKGROUND: Porous species boundaries can be a source of conflicting hypotheses, particularly when coupled with variable data and/or methodological approaches. Their impacts can often be magnified when non-model organisms with complex histories of reticulation are investigated. One such example is the genus Catostomus (Osteichthys, Catostomidae), a freshwater fish clade with conflicting morphological and mitochondrial phylogenies. The former is hypothesized as reflecting the presence of admixed genotypes within morphologically distinct lineages, whereas the latter is interpreted as the presence of distinct morphologies that emerged multiple times through convergent evolution. We tested these hypotheses using multiple methods, to including multispecies coalescent and concatenated approaches. Patterson's D-statistic was applied to resolve potential discord, examine introgression, and test the putative hybrid origin of two species. We also applied naïve binning to explore potential effects of concatenation. RESULTS: We employed 14,007 loci generated from ddRAD sequencing of 184 individuals to derive the first highly supported nuclear phylogeny for Catostomus. Our phylogenomic analyses largely agreed with a morphological interpretation,with the exception of the placement of Xyrauchen texanus, which differs from both morphological and mitochondrial phylogenies. Additionally, our evaluation of the putative hybrid species C. columbianus revealed a lack introgression and instead matched the mitochondrial phylogeny. Furthermore, D-statistic tests clarified all discrepancies based solely on mitochondrial data, with agreement among topologies derived from concatenation and multispecies coalescent approaches. Extensive historic introgression was detected across six species-pairs. Potential endemism in the Virgin and Little Colorado Rivers was also apparent, and the former genus Pantosteus was derived as monophyletic, save for C. columbianus. CONCLUSIONS: Complex reticulated histories detected herein support the hypothesis that introgression was responsible for conflicts that occurred within the mitochondrial phylogeny, and explains discrepancies found between it and previous morphological phylogenies. Additionally, the hybrid origin of C. columbianus was refuted, but with the caveat that more fine-grain sampling is still needed. Our diverse phylogenomic approaches provided largely concordant results, with naïve binning useful in exploring the single conflict. Considerable diversity was found within Catostomus across southwestern North America, with two drainages [Virgin River (UT) and Little Colorado River (AZ)] reflecting unique composition.

Neanderthal and Denisovan ancestry in Papuans: A functional study.

Sequencing of complete nuclear genomes of Neanderthal and Denisovan stimulated studies about their relationship with modern humans demonstrating, in particular, that DNA alleles from both Neanderthal and Denisovan genomes are present in genomes of modern humans. The Papuan genome is a unique object because it contains both Neanderthal and Denisovan alleles. Here, we have shown that the Papuan genomes contain different gene functional groups inherited from each of the ancient people. The Papuan genomes demonstrate a relative prevalence of Neanderthal alleles in genes responsible for the regulation of transcription and neurogenesis. The enrichment of specific functional groups with Denisovan alleles is less pronounced; these groups are responsible for bone and tissue remodeling. This analysis shows that introgression of alleles from Neanderthals and Denisovans to Papuans occurred independently and retention of these alleles may carry specific adaptive advantages.

Gene flow analysis method, the D-statistic, is robust in a wide parameter space.

BACKGROUND: We evaluated the sensitivity of the D-statistic, a parsimony-like method widely used to detect gene flow between closely related species. This method has been applied to a variety of taxa with a wide range of divergence times. However, its parameter space and thus its applicability to a wide taxonomic range has not been systematically studied. Divergence time, population size, time of gene flow, distance of outgroup and number of loci were examined in a sensitivity analysis. RESULT: The sensitivity study shows that the primary determinant of the D-statistic is the relative population size, i.e. the population size scaled by the number of generations since divergence. This is consistent with the fact that the main confounding factor in gene flow detection is incomplete lineage sorting by diluting the signal. The sensitivity of the D-statistic is also affected by the direction of gene flow, size and number of loci. In addition, we examined the ability of the f-statistics, [Formula: see text] and [Formula: see text], to estimate the fraction of a genome affected by gene flow; while these statistics are difficult to implement to practical questions in biology due to lack of knowledge of when the gene flow happened, they can be used to compare datasets with identical or similar demographic background. CONCLUSIONS: The D-statistic, as a method to detect gene flow, is robust against a wide range of genetic distances (divergence times) but it is sensitive to population size. The D-statistic should only be applied with critical reservation to taxa where population sizes are large relative to branch lengths in generations.

Powerful Inference with the D-Statistic on Low-Coverage Whole-Genome Data.

The detection of ancient gene flow between human populations is an important issue in population genetics. A common tool for detecting ancient admixture events is the D-statistic. The D-statistic is based on the hypothesis of a genetic relationship that involves four populations, whose correctness is assessed by evaluating specific coincidences of alleles between the groups. When working with high-throughput sequencing data, calling genotypes accurately is not always possible; therefore, the D-statistic currently samples a single base from the reads of one individual per population. This implies ignoring much of the information in the data, an issue especially striking in the case of ancient genomes. We provide a significant improvement to overcome the problems of the D-statistic by considering all reads from multiple individuals in each population. We also apply type-specific error correction to combat the problems of sequencing errors, and show a way to correct for introgression from an external population that is not part of the supposed genetic relationship, and how this leads to an estimate of the admixture rate. We prove that the D-statistic is approximated by a standard normal distribution. Furthermore, we show that our method outperforms the traditional D-statistic in detecting admixtures. The power gain is most pronounced for low and medium sequencing depth (1-10×), and performances are as good as with perfectly called genotypes at a sequencing depth of 2×. We show the reliability of error correction in scenarios with simulated errors and ancient data, and correct for introgression in known scenarios to estimate the admixture rates.

A history of hybrids? Genomic patterns of introgression in the True Geese.

BACKGROUND: The impacts of hybridization on the process of speciation are manifold, leading to distinct patterns across the genome. Genetic differentiation accumulates in certain genomic regions, while divergence is hampered in other regions by homogenizing gene flow, resulting in a heterogeneous genomic landscape. A consequence of this heterogeneity is that genomes are mosaics of different gene histories that can be compared to unravel complex speciation and hybridization events. However, incomplete lineage sorting (often the outcome of rapid speciation) can result in similar patterns. New statistical techniques, such as the D-statistic and hybridization networks, can be applied to disentangle the contributions of hybridization and incomplete lineage sorting. We unravel patterns of hybridization and incomplete lineage sorting during and after the diversification of the True Geese (family Anatidae, tribe Anserini, genera Anser and Branta) using an exon-based hybridization network approach and taking advantage of discordant gene tree histories by re-sequencing all taxa of this clade. In addition, we determine the timing of introgression and reconstruct historical effective population sizes for all goose species to infer which demographic or biogeographic factors might explain the observed patterns of introgression. RESULTS: We find indications for ancient interspecific gene flow during the diversification of the True Geese and were able to pinpoint several putative hybridization events. Specifically, in the genus Branta, both the ancestor of the White-cheeked Geese (Hawaiian Goose, Canada Goose, Cackling Goose and Barnacle Goose) and the ancestor of the Brent Goose hybridized with Red-breasted Goose. One hybridization network suggests a hybrid origin for the Red-breasted Goose, but this scenario seems unlikely and it not supported by the D-statistic analysis. The complex, highly reticulated evolutionary history of the genus Anser hampered the estimation of ancient hybridization events by means of hybridization networks. The reconstruction of historical effective population sizes shows that most species showed a steady increase during the Pliocene and Pleistocene. These large effective population sizes might have facilitated contact between diverging goose species, resulting in the establishment of hybrid zones and consequent gene flow. CONCLUSIONS: Our analyses suggest that the evolutionary history of the True Geese is influenced by introgressive hybridization. The approach that we have used, based on genome-wide phylogenetic incongruence and network analyses, will be a useful procedure to reconstruct the complex evolutionary histories of many naturally hybridizing species groups.

Hybrid origin of European Vipers (Vipera magnifica and Vipera orlovi) from the Caucasus determined using genomic scale DNA markers.

BACKGROUND: Studying patterns of introgression can illuminate the role of hybridization in speciation, and help guide decisions relevant to the conservation of rare taxa. Vipera magnifica and Vipera orlovi are small vipers that have high conservation status due to their rarity and restricted distributions in an area of the Caucasus region where two other related species are present - V. kaznakovi and V. renardi. Despite numerous observations of hybridization between different species of small vipers, and the potential of a hybrid origin for V. magnifica and V. orlovi based on their distribution with respect to V. kaznakovi and V. renardi, hypotheses of a hybrid origin have not been formally tested. Here we generate genomic-scale data by performing next generation sequencing of double digest restriction-site associated DNA libraries, and use these multilocus data to test whether these two species are of hybrid origin. RESULTS: We generated over nine hundred loci for 38 specimens of six taxa, and analysed the dataset using Bayesian clustering and multivariate methods, as well as Patterson D-statistics, which can distinguish between incomplete lineage sorting and introgression as explanations for shared polymorphism. The results demonstrate a pattern of historical admixture in the two purported hybrids that is consistent with past gene flow from V. renardi into V. kaznakovi. The average admixture proportion in individuals was low (6.39 %) in the case of V. magnifica, but was higher in V. orlovi (19.02 %). We also show that the specific individual samples used in D-statistic tests can have a significant impact on inferences regarding the magnitude of introgression, suggesting the importance of including multiple individuals in these analyses. CONCLUSIONS: Our results support the conclusion that both V. orlovi and V. magnifica had formed through a hybridization event between V. kaznakovi and V. renardi. Given a low proportion of admixture and absence of clear ecological and morphological differences V. magnifica should be treated as a marginal population of V. kaznakovi. Further studies that include analyses of ecological segregation of V. orlovi from parental taxa and search for evolutionary consequences of hybridisation would clarify if V. orlovi is a distinct hybrid species. Until this we recommend preserving the current taxonomy and protection status of V. orlovi.

Phylogenetic exploration of commonly used medicinal plants in South Africa.

The rapid growth rate of human population, along with the public health crisis encountered in many regions, particularly in developing world, creates an urgent need for the discovery of alternative drugs. Because medicinal plants are not distributed randomly across lineages, it has been suggested that phylogeny along with traditional knowledge of plant uses can guide the identification of new medicinally useful plants. In this study, we combined different statistical approaches to test for phylogenetic signal in 33 categories of plant uses in South Africa. Depending on the null models considered, we found evidence for signal in up to 45% of plant use categories, indicating the need for multiple tests combination to maximize the chance of discovering new medicinal plants when applying a phylogenetic comparative approach. Furthermore, although there was no signal in the diversity of medicinal uses-that is, total number of medicinal uses recorded for each plant-our results indicate that taxa that are evolutionarily closely related have significantly more uses than those that are evolutionarily isolated. Our study therefore provides additional support to the body of the literature that advocates for the inclusion of phylogeny in bioscreening medicinal flora for the discovery of alternative medicines.

Genotyping-by-sequencing as a tool to infer phylogeny and ancestral hybridization: a case study in Carex (Cyperaceae).

Determining phylogenetic relationships among very closely related species has remained a challenge for evolutionary biologists due to interlocus phylogenetic discordance and the difficulty of obtaining variable markers. Here, we used a Genotyping-by-Sequencing (GBS) approach to sample a reduced representation genomic data set and infer the phylogeny of seven closely related species in the genus Carex (Cyperaceae). Past attempts to reconstruct phylogenetic relationships among these species produced conflicting and poorly-supported results. We inferred a robust phylogeny based on >3000 GBS loci and >1300 SNPs (with a minimum sequence depth within individuals of 10) using maximum likelihood and Bayesian inference. We also tested for historical introgression using the D-statistic test. We compared these analyses with partitioned RAD analysis, which is designed to identify suboptimal trees reflecting secondary phylogenetic signal that may be obscured by the dominant signal in the data. Phylogenetic analyses yielded fully resolved trees with high support. We found two main clades, one grouping Carex scoparia populations and C. waponahkikensis, and a second clade grouping C. longii, C. vexans, C. suberecta and C. albolutescens. We detected marginally significant signals of introgression between C. scoparia and C. suberecta or C. albolutescens, and we rejected a hybrid origin hypothesis for C. waponahkikensis. Our results demonstrate the power of NGS data sets for resolving some of the most difficult phylogenetic challenges where traditional phylogenetic markers have failed.

Analysis and meta-analysis of single-case designs with a standardized mean difference statistic: a primer and applications.

This article presents a d-statistic for single-case designs that is in the same metric as the d-statistic used in between-subjects designs such as randomized experiments and offers some reasons why such a statistic would be useful in SCD research. The d has a formal statistical development, is accompanied by appropriate power analyses, and can be estimated using user-friendly SPSS macros. We discuss both advantages and disadvantages of d compared to other approaches such as previous d-statistics, overlap statistics, and multilevel modeling. It requires at least three cases for computation and assumes normally distributed outcomes and stationarity, assumptions that are discussed in some detail. We also show how to test these assumptions. The core of the article then demonstrates in depth how to compute d for one study, including estimation of the autocorrelation and the ratio of between case variance to total variance (between case plus within case variance), how to compute power using a macro, and how to use the d to conduct a meta-analysis of studies using single-case designs in the free program R, including syntax in an appendix. This syntax includes how to read data, compute fixed and random effect average effect sizes, prepare a forest plot and a cumulative meta-analysis, estimate various influence statistics to identify studies contributing to heterogeneity and effect size, and do various kinds of publication bias analyses. This d may prove useful for both the analysis and meta-analysis of data from SCDs.

Neandertal admixture in Eurasia confirmed by maximum-likelihood analysis of three genomes.

Although there has been much interest in estimating histories of divergence and admixture from genomic data, it has proved difficult to distinguish recent admixture from long-term structure in the ancestral population. Thus, recent genome-wide analyses based on summary statistics have sparked controversy about the possibility of interbreeding between Neandertals and modern humans in Eurasia. Here we derive the probability of full mutational configurations in nonrecombining sequence blocks under both admixture and ancestral structure scenarios. Dividing the genome into short blocks gives an efficient way to compute maximum-likelihood estimates of parameters. We apply this likelihood scheme to triplets of human and Neandertal genomes and compare the relative support for a model of admixture from Neandertals into Eurasian populations after their expansion out of Africa against a history of persistent structure in their common ancestral population in Africa. Our analysis allows us to conclusively reject a model of ancestral structure in Africa and instead reveals strong support for Neandertal admixture in Eurasia at a higher rate (3.4-7.3%) than suggested previously. Using analysis and simulations we show that our inference is more powerful than previous summary statistics and robust to realistic levels of recombination.

A d-statistic for single-case designs that is equivalent to the usual between-groups d-statistic.

We describe a standardised mean difference statistic (d) for single-case designs that is equivalent to the usual d in between-groups experiments. We show how it can be used to summarise treatment effects over cases within a study, to do power analyses in planning new studies and grant proposals, and to meta-analyse effects across studies of the same question. We discuss limitations of this d-statistic, and possible remedies to them. Even so, this d-statistic is better founded statistically than other effect size measures for single-case design, and unlike many general linear model approaches such as multilevel modelling or generalised additive models, it produces a standardised effect size that can be integrated over studies with different outcome measures. SPSS macros for both effect size computation and power analysis are available.