2023
DOI: 10.1002/ece3.10435
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Ghost introgression facilitates genomic divergence of a sympatric cryptic lineage in Cycas revoluta

Jui‐Tse Chang,
Koh Nakamura,
Chien‐Ti Chao
et al.

Abstract: A cryptic lineage is a genetically diverged but morphologically unrecognized variant of a known species. Clarifying cryptic lineage evolution is essential for quantifying species diversity. In sympatric cryptic lineage divergence compared with allopatric divergence, the forces of divergent selection and mating patterns override geographical isolation. Introgression, by supplying preadapted or neutral standing genetic variations, can promote sympatric cryptic lineage divergence via selection. However, most stud… Show more

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Cited by 1 publication
(2 citation statements)
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References 123 publications
(142 reference statements)
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“…Phylogenetic network methods that accommodate both ILS and hybridization, such as PhyloNet (Wen et al 2018) and SNaQ (Solís-Lemus and Ané 2016), are suitable choices for identifying hybridization and introgression in general, despite their limitations in differentiating different types of introgression (Pang and Zhang 2024). More powerful model-based population genetic approaches have been developed and widely applied for the purpose of detecting and quantifying ghost introgression (Ru et al 2018;Ding et al 2022;Chang et al 2023;Pawar et al 2023;Yamahira et al 2023;Kato et al 2024). In this context, full-likelihood methods such as G-PhoCS (Gronau et al 2011), IMa3 (Hey et al 2018, and BPP (Flouri et al 2020;Flouri et al 2023) hold great promise because they make full use of information in multilocus sequences.…”
Section: Recommendations For Empirical Studiesmentioning
confidence: 99%
See 1 more Smart Citation
“…Phylogenetic network methods that accommodate both ILS and hybridization, such as PhyloNet (Wen et al 2018) and SNaQ (Solís-Lemus and Ané 2016), are suitable choices for identifying hybridization and introgression in general, despite their limitations in differentiating different types of introgression (Pang and Zhang 2024). More powerful model-based population genetic approaches have been developed and widely applied for the purpose of detecting and quantifying ghost introgression (Ru et al 2018;Ding et al 2022;Chang et al 2023;Pawar et al 2023;Yamahira et al 2023;Kato et al 2024). In this context, full-likelihood methods such as G-PhoCS (Gronau et al 2011), IMa3 (Hey et al 2018, and BPP (Flouri et al 2020;Flouri et al 2023) hold great promise because they make full use of information in multilocus sequences.…”
Section: Recommendations For Empirical Studiesmentioning
confidence: 99%
“…Evolutionary studies are often constrained to a limited subset of species due to many lineages becoming either extinct or unsampled because of technical constraints or their irrelevance to the research question (Ottenburghs 2020;Tricou et al 2022aTricou et al , 2022b. The phenomenon of 'ghost introgression', which refers to introgression from extinct or unsampled lineages to the sampled species, is widely acknowledged and has been uncovered in a growing number of plants (e.g., Ru et al 2018;Li M. et al 2021;Ding et al 2022;Chang et al 2023;Tiley et al 2023) and animals (Sankararaman et al 2014;Ai et al 2015;Kuhlwilm et al 2019;Wang et al 2020;Rocha et al 2022;Pawar et al 2023;Yamahira et al 2023;Kato et al 2024). Intuitively, the involvement of ghost lineages in a gene flow event inevitably leads to a loss of information for hybridization detection, thereby negatively affecting admixture inference.…”
mentioning
confidence: 99%