Biology subjects

Pang, X.-X.

Publications and source records attributed to Pang, X.-X..

7 recordsLinked to original sources

bioRxiv2026

D-plus: Beyond the D-statistic -- Accurate Detection and Characterization of Introgression Despite Among-Lineage Rate Variation

Ubiquitous in phylogenomic and population-genomic introgression work, the D-statistic has fallen victim to its own success. Its reliability is compromised by two major confounding factors: among-lineage substitution rate heterogeneity, which generates spurious signals of introgression, and unsampled "ghost" lineages, which mislead the characterization of introgression by erroneously attributing ghost ancestry to extant species. Here, we developed D-plus, a maximum-likelihood tool that explicitly accounts for both confounding factors to unpack the sources of significant D-statistic signals. Simulations demonstrate that D-plus effectively mitigates false introgression calls under among-lineage rate variation. Meanwhile, it retains high sensitivity for genuine introgression signals and correctly assigns detected signals to introgression involving ghost lineages, or solely between extant non-sister lineages, or a combination of the two. Our D-plus re-analysis of phylogenomic data from Jaltomata (Solanaceae) overturns prior interpretations of significant D-statistic signals, which were conventionally regarded as evidence for recurrent non-sister introgression. Instead, our results favor alternative explanations invoking artefacts driven by lineage-specific rate heterogeneity as well as two ghost introgression events. Collectively, D-plus addresses major methodological limitations inherent to traditional D-statistic analyses and enables accurate detection and characterization of introgression events.

bioinformatics↗

bioRxiv2026

Hybrid speciation and ghost ancestry shape the Anopheles gambiae species complex

Speciation within reticulate radiations can involve both lineage divergence and hybrid lineage formation, yet recurrent introgression obscures both histories. In the Anopheles gambiae complex, gene-family presence-absence data yielded a species tree favored over four sequence-derived alternatives by network-model comparison. D-BPP analyses recovered seven reticulation events, including multiple ghost-lineage contributions, and supported a ghost-mediated hybrid origin of A. merus. Simulations showed that sampled-parent hybrid origin generates temporal convergence between reticulation and lineage formation when analyzed under an ordinary introgression model; this signature supported hybrid speciation in A. gambiae. Loci with contrasting parental affinities contained olfactory and cuticular genes with potential roles in prezygotic isolation. Together, these results resolve species relationships and identify candidate genomic mechanisms through which hybridization may have contributed to reproductive isolation.

evolutionary biology↗

bioRxiv2025

Synergizing Bayesian and Heuristic Approaches: D-BPP Uncovers Ghost Introgression in Panthera and Thuja

Hybridization involving extinct or unsampled ("ghost") lineages profoundly influences species evolutionary histories, but detecting such introgression remains methodologically challenging. We introduce D-BPP, a novel framework that integrates the heuristic D-statistic (or ABBA-BABA test) with Bayesian phylogenomic inference (implemented in BPP) to efficiently infer phylogenetic networks. In D-BPP, we first employ the D-statistic to rapidly identify candidate introgression events on a predefined binary species tree; then we leverage the Bayesian test in BPP to rigorously validate these candidates and sequentially add them to the species tree, retaining only those events with strong statistical support. If the species tree is ambiguous, D-BPP identifies the most probable tree by evaluating competing topologies through Bayesian model comparison of their corresponding introgression models. Critically, our framework excels at detecting ghost introgression, which is often unidentifiable or overlooked by existing methods-- whether heuristic or full-likelihood. Applied to genomic datasets from Panthera (big cats) and Thuja (conifers), D-BPP uncovered previously undetected ghost introgression events in both clades, underscoring the pervasive role ghost lineages have played across diverse taxa. By uniquely combining the computational efficiency of heuristic D-statistics with the robust statistical rigor of full-likelihood Bayesian inference, D-BPP deciphers complex hybridization patterns obscured by conventional methods, providing a powerful tool for accurately reconstructing phylogenetic networks.

evolutionary biology↗

bioRxiv2025

Detecting Introgression in Shallow Phylogenies: How Minor Molecular Clock Deviations Lead to Major Inference Errors

Recent theoretical and algorithmic advances in introgression detection, coupled with the growing availability of genome-scale data, have highlighted the widespread occurrence of interspecific gene flow across the tree of life. However, current methods largely depend on the molecular clock assumption--a questionable premise given empirical evidence of substitution rate variation across lineages. While such rate heterogeneity is known to compromise gene flow detection among divergent lineages, its impact on closely related taxa at shallow evolutionary timescales remains poorly understood, likely because these taxa are often assumed to adhere to a molecular clock. To address this gap, we combine theoretical analyses and simulations to evaluate the robustness of widely used site-pattern methods (D-statistic and HyDe) to rate variation across phylogenetic timescales. Our results demonstrate that both methods exhibit high sensitivity to even minor deviations from the molecular clock at shallow timescales, complementing previous findings at deeper scales. Specifically, in young phylogenies (with an age of 3x105 generations) with small population sizes, weak (17% difference) and moderate (33% difference) rate variation can inflate false-positive rates up to 35% and 100%, respectively, when using site-pattern counts from a 500Mb genome. Employing a more distant outgroup intensifies these spurious signals. Our study demonstrates that summary tests for introgression are pervasively vulnerable to minor rate variations and underscores the critical need for advanced methodologies to disentangle genuine introgression from false signals generated by rate heterogeneity.

evolutionary biology↗

bioRxiv2024

A Cautionary Note on Using STRUCTURE to Detect Hybridization in a Phylogenetic Context

Population genetic clustering methods are widely used to detect hybridization events between closely related populations within species, as well as between deeply diverged lineages across phylogenetic time-scales, although their strengths and limitations in the latter cases remain poorly explored. This study presents the first systematic evaluation of the performance of the most popular population clustering method, STRUCTURE, under a variety of cross-species hybridization scenarios, including hybrid speciation, as well as introgression involving ghost (i.e., extinct or unsampled) lineages or otherwise. Our simulations demonstrate that STRUCTURE performs well in identifying hybrids and their parental donors only when admixture happens very recently between sampled extant lineages. However, STRUCTURE generally fails to detect signals of admixture when hybridization occurs in deep time or when gene flow stems from ghost lineages. We find that symmetrical parental contribution in cases of hybrid speciation will often be revealed as extremely asymmetrical in STRUCTURE, especially when the admixture event occurred more than some time ago. Our results suggest that population-genetic clustering methods may be very inefficient for detecting either ancient or ghost admixtures, partly explaining why ghost introgression has escaped the attention of evolutionary biologists until recently.

evolutionary biology↗

bioRxiv2023

Uncovering Ghost Introgression Through Genomic Analysis of a Distinct East Asian Hickory Species

Although the possibility of introgression from ghost lineages (all unsampled extant and extinct taxa) is now widely recognized, detecting and characterizing ghost introgression remains a challenge. Here, we propose a combined use of the popular D-statistic method, which tests for the presence of introgression, and the full-likelihood method BPP, which determines which of the possible gene-flow scenarios, including ghost introgression, is truly responsible. We illustrate the utility of this approach by investigating the reticulation and bifurcation history of the genus Carya (Juglandaceae), including the beaked hickory Carya sinensis. To achieve this goal, we generated two chromosome-level reference genomes respectively for C. sinensis and C. cathayensis. Furthermore, we re-sequenced the whole genomes of 43 individuals from C. sinensis and one individual from each of the 11 diploid species of Carya. The latter dataset with one individual per species is used to reconstruct the phylogenetic networks and estimate the divergence time of Carya. Our results unambiguously demonstrate the presence of ghost introgression from an extinct lineage into the beaked hickory, dispelling certain misconceptions about the phylogenetic history of C. sinensis. We also discuss the profound implications of ghost introgression into C. sinensis for the historical biogeography of hickory species. [BPP; Carya; D-statistic; gene flow; ghost introgression]

evolutionary biology↗

bioRxiv2023

Detection of Ghost Introgression from Phylogenomic Data Requires a Full-Likelihood Approach

AO_SCPLOWBSTRACTC_SCPLOWIn recent years, the study of hybridization and introgression has made significant progress, with ghost introgression - the transfer of genetic material from extinct or unsampled lineages to extant species - emerging as a key area for research. Accurately identifying ghost introgression, however, presents a challenge. To address this issue, we focused on simple cases involving three species with a known phylogenetic tree. Using mathematical analyses and simulations, we evaluated the performance of popular phylogenetic methods, including HyDe and PhyloNet/MPL, and the full-likelihood method, Bayesian Phylogenetics and Phylogeography (BPP), in detecting ghost introgression. Our findings suggest that heuristic approaches relying on site patterns or gene tree topologies struggle to differentiate ghost introgression from introgression between sampled non-sister species, frequently leading to incorrect identification of donor and recipient species. The full-likelihood method BPP using multilocus sequence alignments, by contrast, is capable of detecting ghost introgression in phylogenomic datasets. We analyzed a real-world phylogenomic dataset of 14 species of Jaltomata (Solanaceae) to showcase the potential of full-likelihood methods for accurate inference of introgression.

evolutionary biology↗