It was a rapid pre-analysis and test that based on PNAS in 2026 and Sci. Adv in 2023 papers.

Introduce

it aims to test whether p.nat phylogenetic signal reported in previous studies is robust across multiple windows size. Due to the time and confidentiality, i will not show the specific species name.

Reproduce Method

1.genome selection：

7 species：Chromesome_level with appropriate scaffold

2.HAlign-G Alignment

HAlign-G tools were used to this 7-sp alignment, although it will not deal properly for the repeats element which will be considered for structure variations.

3.The different sizes of window tree

Then i made different sizes of window trees, including 10kb,20kb,50kb and 100kb. The top-3 topologies of them were consist of the same.

4.The chrY phylogeny

Because my genomes can't get a effective length of alignment in chrY. I have to use the chrY alignment get a species tree by caster-site.
the tree is same as the top-1 topology.

5.Mitochondrial phylogeny

I used 13-PCGs extracted by mitos to construct a concatnetated tree with MACSE in mitochondrial coding mode. In general, the tree is same as the top-1 tree. However, Some new research, recently, show a differet result in whole mitochondrial phylogeny in these species, so i need to check my results carefully.

6.MCMCtree for the divergence time estimation

for the divergent time estimation, I concatenated the 1500 windows from the three top topology as the input for the MCMCtree tool. it show a situation that consist with the current evidences.

7.ABBA-BABA Dfoil and QuIBL

I observed that ABBA-BABA, Dfoil, QuIBL consistently suggest the p.spp show a introgression pattern .This pattern contradicts our expectations based on the p.nat. Possible reasons include ILS, Reference bias, and the limitation of pre-analysis.

Brief AI summary and evaluate

Taken together, these analyses provide a broadly consistent phylogenetic signal across genomic compartments, but several limitations—particularly alignment quality in repetitive regions and discordant mitochondrial signals—require cautious interpretation.

AI comments

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