Search bioRxiv⌕ Search

Biology subjects

Pang, X.-X.

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

3 recordsLinked to original sources

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↗

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↗

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↗