journal article·2025-10Open access

Patterns and Processes of Genomic Evolution Inferred From the Ten Smallest Vertebrate Genomes

Kaiqiang Liu, Qian Wang, Ning Wang, Lingfeng Meng, Shuo Li, Hong‐Yan Wang, Yuyan Liu, Qian Liu, Yangqing Zhang, Lucas B. Doretto, Mengqi Zhang, Yating Qin, Shanshan Pan, Shenglei Han, Weijing Li, Shanshan Liu, Fengtao Gao, Axel Meyer, Jussi Taipale, Guangyi Fan, Manfred Schartl, Jilin Zhang, Changwei Shao

Advanced Science· Volume 12· Issue 38

Abstract

Abstract Pufferfish exhibit the smallest vertebrate genomes, making them ideal models for investigating evolutionary patterns and processes that affect genome size. While the Takifugu rubripes genome was fully sequenced two decades ago, key evolutionary drivers remain elusive. We sequenced 10 pufferfish genomes and generated 35 transcriptomes and 13 methylomes to understand genomic evolutionary mechanisms. Comparative genomics revealed that transposable element suppression—rather than lineage‐specific conserved element loss—primarily underlies genome compaction. This is mediated by reductions in transposon‐associated enzymes that limit transposable element propagation and modify DNA repair mechanisms that promote genomic streamlining. Based on resolved phylogeny among nine Takifugu , it is found that introgression drives speciation of T. niphobles and T. oblongus , while long‐term linked selection dominates divergence in other species. Positive selection analyses highlighted mechanotransduction pathway genes (integrins, ion channel transport) that are functionally convergent with mammalian lung cell mechanisms, potentially supporting inflation‐based anti‐predatory strategies. Additionally, positive selection variants in genes that control lineage‐specific skin patterning and coloration, which are either selected for or are rewired in regulatory processes, might suggest a role for pigmentation during the rapid speciation of this lineage. This findings shed light on mechanisms enabling extreme vertebrate genome compaction and provide insights for genome engineering applications.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Genomics and Phylogenetic Studies · Chromosomal and Genetic Variations · Genetic diversity and population structure

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

State Key Laboratory of Mariculture Biobreeding and Sustainable Goods Yellow Sea Fisheries Research Institute Chinese Academy of Fishery Sciences Qingdao Shandong 266071 China

Laboratory for Marine Fisheries Science and Food Production Processes Qingdao Marine Science and Technology Center Qingdao Shandong 266237 China

Department of Biophysics and Biochemistry Karolinska Institute Stockholm 17177 Sweden

BGI‐Qingdao BGI‐Shenzhen Qingdao Shandong 266555 China

BGI‐Shenzhen Shenzhen Guangdong 518083 China

Weifang Municipal Key Laboratory of Fishery Resources Development & Comprehensive Utilization College of Biology and Oceanography Weifang University Weifang 261053 China

Department of Biology University of Konstanz 78457 Konstanz Germany

CAS Key Laboratory of Tropical Marine Bio‐Resources and Ecology South China Sea Institute of Oceanology Chinese Academy of Sciences Guangzhou 510301 China

Museum of Comparative Zoology Harvard University Cambridge MA 02138 USA

Department of Biochemistry University of Cambridge Cambridge CB2 1QW U.K

Developmental Biochemistry Biozentrum University of Würzburg 97074 Würzburg Germany

Tung Biomedical Sciences Centre City University of Hong Kong Hong Kong S.A.R 999077 China

Department of Precision Diagnostic and Therapeutic Technology The City University of Hong Kong Shenzhen Futian Research Institute Shenzhen 518053 China

Department of Biomedical Sciences City University of Hong Kong Hong Kong S.A.R 999077 China

References (74)

Show source-provided references
1. 10.1086/68085010.1086/680850 ↗
2. 10.1073/pnas.211563511810.1073/pnas.2115635118 ↗
3. 10.1016/j.tree.2019.02.00810.1016/j.tree.2019.02.008 ↗
4. 10.1126/science.107210410.1126/science.1072104 ↗
5. 10.1093/molbev/msn28310.1093/molbev/msn283 ↗
6. 10.1016/j.chemosphere.2022.13496210.1016/j.chemosphere.2022.134962 ↗
7. 10.1111/j.1558-5646.1997.tb02438.x10.1111/j.1558-5646.1997.tb02438.x ↗
8. 10.2307/144675810.2307/1446758 ↗
9. 10.1038/s41597-019-0195-210.1038/s41597-019-0195-2 ↗
10. 10.1111/1755-0998.1313210.1111/1755-0998.13132 ↗
11. 10.1038/s41597-023-01937-210.1038/s41597-023-01937-2 ↗
12. 10.1038/s41597-019-0279-z10.1038/s41597-019-0279-z ↗
13. 10.1007/s00227-020-03705-x10.1007/s00227-020-03705-x ↗
14. 10.1073/pnas.040811810110.1073/pnas.0408118101 ↗
15. 10.1073/pnas.211960211910.1073/pnas.2119602119 ↗
16. 10.1126/sciadv.aaw667110.1126/sciadv.aaw6671 ↗
17. 10.1126/science.abq425710.1126/science.abq4257 ↗
18. 10.1016/j.cell.2016.09.02810.1016/j.cell.2016.09.028 ↗
19. 10.1093/biolinnean/blab09910.1093/biolinnean/blab099 ↗
20. 10.1093/sysbio/syac05110.1093/sysbio/syac051 ↗
21. 10.1038/nature0541910.1038/nature05419 ↗
22. 10.1093/gbe/evac05110.1093/gbe/evac051 ↗
23. 10.1038/347550a010.1038/347550a0 ↗
24. 10.1038/s41586-020-2930-410.1038/s41586-020-2930-4 ↗
25. Kratochwil C. F. · Science · 362 · 45710.1126/science.aao6809 ↗
26. 10.1073/pnas.96.9.510710.1073/pnas.96.9.5107 ↗
27. 10.1146/annurev.es.25.110194.00255510.1146/annurev.es.25.110194.002555 ↗
28. 10.1007/s10577-017-9570-z10.1007/s10577-017-9570-z ↗
29. 10.1186/1471-2164-10-4710.1186/1471-2164-10-47 ↗
30. 10.1073/pnas.220976611910.1073/pnas.2209766119 ↗
31. 10.1111/mec.1479410.1111/mec.14794 ↗
32. 10.1038/ng.352610.1038/ng.3526 ↗
33. 10.7554/eLife.2390710.7554/eLife.23907 ↗
34. 10.1111/j.1469-185X.2012.00240.x10.1111/j.1469-185X.2012.00240.x ↗
35. 10.1186/1471-2105-9-32210.1186/1471-2105-9-322 ↗
36. 10.3389/fgene.2021.62560010.3389/fgene.2021.625600 ↗
37. 10.1152/ajpregu.2000.279.3.R75610.1152/ajpregu.2000.279.3.R756 ↗
38. 10.3389/fphys.2021.83491610.3389/fphys.2021.834916 ↗
39. 10.1002/hep.2358610.1002/hep.23586 ↗
40. 10.1111/bph.1474910.1111/bph.14749 ↗
41. 10.1186/s12931-019-0973-610.1186/s12931-019-0973-6 ↗
42. 10.1093/molbev/msx14310.1093/molbev/msx143 ↗
43. 10.1111/j.1365-294X.2004.02211.x10.1111/j.1365-294X.2004.02211.x ↗
44. 10.1038/nature0473810.1038/nature04738 ↗
45. 10.1016/j.cbpb.2022.11077910.1016/j.cbpb.2022.110779 ↗
46. 10.1074/jbc.M115.65727010.1074/jbc.M115.657270 ↗
47. 10.1098/rspb.2019.158810.1098/rspb.2019.1588 ↗
48. 10.1111/raq.1258310.1111/raq.12583 ↗
49. 10.1038/s41467-021-27685-810.1038/s41467-021-27685-8 ↗
50. 10.1073/pnas.192179111710.1073/pnas.1921791117 ↗
51. 10.1038/s41586-023-06327-710.1038/s41586-023-06327-7 ↗
52. 10.1111/jeb.1211210.1111/jeb.12112 ↗
53. 10.1007/s00227-017-3120-210.1007/s00227-017-3120-2 ↗
54. 10.1016/0012-821X(96)00109-410.1016/0012-821X(96)00109-4 ↗
55. 10.1029/2007GL02988510.1029/2007GL029885 ↗
56. 10.1016/j.cell.2022.03.03410.1016/j.cell.2022.03.034 ↗
57. 10.1371/journal.pbio.100222410.1371/journal.pbio.1002224 ↗
58. 10.1098/rsos.17035110.1098/rsos.170351 ↗
59. 10.1038/s41586-020-2845-010.1038/s41586-020-2845-0 ↗
60. 10.1126/science.aaw209010.1126/science.aaw2090 ↗
61. 10.1371/journal.pgen.100615710.1371/journal.pgen.1006157 ↗
62. M.Tarailo‐Graovac N.Chen Curr. Protoc. Bioinforma.2009 Chapter 4 4.10.1.
63. 10.1159/00008497910.1159/000084979 ↗
64. 10.1073/pnas.192104611710.1073/pnas.1921046117 ↗
65. 10.1093/nar/gkm28610.1093/nar/gkm286 ↗
66. 10.1093/nar/27.2.57310.1093/nar/27.2.573 ↗
67. 10.1101/gr.186550410.1101/gr.1865504 ↗
68. 10.1093/nar/gkl20010.1093/nar/gkl200 ↗
69. 10.1038/nprot.2016.09510.1038/nprot.2016.095 ↗
70. 10.1038/s41467-017-02525-w10.1038/s41467-017-02525-w ↗
71. 10.1093/bioinformatics/bty63110.1093/bioinformatics/bty631 ↗
72. 10.1093/bioinformatics/btaa102210.1093/bioinformatics/btaa1022 ↗
73. 10.1093/molbev/msm08810.1093/molbev/msm088 ↗
74. 10.1038/s41586-023-05752-y10.1038/s41586-023-05752-y ↗