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Pan-evolutionary and regulatory genome architecture delineated by an integrated macro- and microsynteny approach

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Abstract

The forthcoming massive genome data generated by the Earth BioGenome Project will open up a new era of comparative genomics, for which genome synteny analysis provides an important framework. Profiling genome synteny represents an essential step in elucidating genome architecture, regulatory blocks/elements and their evolutionary history. Here we describe PanSyn, (https://github.com/yhw320/PanSyn), the most comprehensive and up-to-date genome synteny pipeline, providing step-by-step instructions and application examples to demonstrate its usage. PanSyn inherits both basic and advanced functions from existing popular tools, offering a user-friendly, highly customized approach for genome macrosynteny analysis and integrated pan-evolutionary and regulatory analysis of genome architecture, which are not yet available in public synteny software or tools. The advantages of PanSyn include: (i) advanced microsynteny analysis by functional profiling of microsynteny genes and associated regulatory elements; (ii) comprehensive macrosynteny analysis, including the inference of karyotype evolution from ancestors to extant species; and (iii) functional integration of microsynteny and macrosynteny for pan-evolutionary profiling of genome architecture and regulatory blocks, as well as integration with external functional genomics datasets from three- or four-dimensional genome and ENCODE projects. PanSyn requires basic knowledge of the Linux environment and Perl programming language and the ability to access a computer cluster, especially for large-scale genomic comparisons. Our protocol can be easily implemented by a competent graduate student or postdoc and takes several days to weeks to execute for dozens to hundreds of genomes. PanSyn provides yet the most comprehensive and powerful tool for integrated evolutionary and functional genomics.

Key points

  • PanSyn is a user-friendly pipeline that integrates popular and customized micro- and macrosynteny tools and provides access to external functional genomics datasets for comparative genomic studies.

  • Compared with alternative methods, PanSyn allows advanced microsynteny analysis of regulatory blocks, comprehensive macrosynteny analysis of karyotype evolution and integrated analysis of micro- and macrosynteny for the pan-evolutionary and functional investigation of genome architecture.

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Fig. 1: A schematic overview of PanSyn approach for comprehensive microsynteny and macrosynteny analysis.
Fig. 2: Demonstration of PanSyn-based microsynteny analysis.
Fig. 3: Demonstration of PanSyn-based macrosynteny analysis.
Fig. 4: Demonstration of integrated microsynteny and macrosynteny analysis.

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Data availability

All data analyzed within this protocol are publicly available. Demo datasets used in the procedure section and expected results are included in the PanSyn package, which are accessible at Zenodo (https://zenodo.org/records/10115240). The accession numbers for the demo datasets used in the PanSyn procedure are listed in Supplementary Table 1. Source data are provided with this paper.

Code availability

All PanSyn source codes are publicly available at the GitHub website (https://github.com/yhw320/PanSyn/tree/main/scripts) and are provided in the Supplementary Code.

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Acknowledgements

We thank all developers of useful genome comparison algorithms and tools that have been integrated in the PanSyn pipeline. We also wish to thank J. Zhang (Novogene Bioinformatics Institute) and X. Dai (University of Michigan) for assisting in the early development of macrosynteny pipeline and PanSyn protocol testing, respectively. This research is part of the ongoing M10K+ genome project that is proposed by M10K+ Consortium and targets sequencing of 10,000 molluscan genomes. We acknowledge the grant support from the Science & Technology Innovation Project of Laoshan Laboratory (LSKJ202203001, LSKJ202202804), National Natural Science Foundation of China (32130107, 32222085), National Key Research and Development Program of China (2022YFD2400301), Key R&D Project of Shandong Province (2021ZLGX03, 2022ZLGX01), the Fundamental Research Funds for the Central Universities (842341005) and Taishan Scholar Project Fund of Shandong Province of China.

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Author notes

  1. These authors contributed equally: Hongwei Yu, Yuli Li.

Authors and Affiliations

  1. Fang Zongxi Center for Marine Evo-Devo & MOE Key Laboratory of Marine Genetics and Breeding, College of Marine Life Sciences, Ocean University of China, Qingdao, China

    Hongwei Yu, Yuli Li, Wentao Han, Fuyun Liu, Yuanting Ma, Zhongqi Pu, Qifan Zeng, Lingling Zhang, Zhenmin Bao & Shi Wang

  2. Laboratory for Marine Biology and Biotechnology, Laoshan Laboratory, Qingdao, China

    Yuli Li, Lingling Zhang & Shi Wang

  3. Institute of Evolution & Marine Biodiversity, Ocean University of China, Qingdao, China

    Lisui Bao

  4. Southern Marine Science and Engineering Guangdong Laboratory, Guangzhou, China

    Zhenmin Bao & Shi Wang

  5. Key Laboratory of Tropical Aquatic Germplasm of Hainan Province, Sanya Oceanographic Institution, Ocean University of China, Sanya, China

    Zhenmin Bao & Shi Wang

  6. Laboratory for Marine Fisheries and Aquaculture, Laoshan Laboratory, Qingdao, China

    Zhenmin Bao

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Contributions

S.W. and Y.L. conceived and designed the protocol. H.Y., Y.L., W.H., L.B., F.L., Y.M. and Z.P. developed, optimized and tested the protocol. Q.Z., L.Z. and Z.B. participated in discussions and provided suggestions for protocol improvement. S.W., Y.L. and H.Y. wrote the protocol with the input from other authors.

Corresponding authors

Correspondence to Yuli Li or Shi Wang.

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The authors declare no competing interests.

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Nature Protocols thanks Steven Cannon, Xiyin Wang and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Related links

Key references using this protocol

Wang, S. et al. Nat. Ecol. Evol. 1, 120 (2017): https://doi.org/10.1038/s41559-017-0120

Han, W. et al. Nat. Ecol. Evol. 6, 1891–1906 (2022): https://doi.org/10.1038/s41559-022-01898-6

Wei, J. et al. Nucleic Acids Res. 51, D913–D923 (2023): https://doi.org/10.1093/nar/gkac944

Extended data

Extended Data Fig. 1 Extended demonstrations of microsynteny analyses.

(a) Dot plot or Circos plot visualization of polyploid plant genomes (left) and microbial genomes (right). In the dot plot, homologous gene pairs are shown as dots, and syntenic gene pairs are aligned together. In the Circos plot, lines linking two chromosomes indicate the location of microsynteny genes. (b) Microsynteny analysis of heteromorphic and homomorphic sex chromosomes in X/Y and Z/W sexual systems, respectively. Lines linking two sex chromosomes indicate the location of microsynteny genes. The location of sex-determining gene is indicated by a green line. (c) Genomic organization of plant gene clusters, which are tandemly connected in metabolic pathways. Homologous genes are represented with rectangles of the same color. Microsynteny between two species is shown with grey curves. (d) Integrative analysis of microsynteny with genomic structural variations. Oryza sativa L. indica rice varieties Minghui63 (MH63) and Zhenshan97 (ZS97) genomes are used for displaying the association of genome synteny and different structural variations (insertions/deletions or inversions).

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Extended Data Fig. 2 Computational procedure and visualization of network-based microsynteny analysis.

(a, b) Schematic overview of network-based approaches developed for microsynteny network detection and macroevolutionary history inference (see Zhao et al.108 and Robert et al.27 for detailed algorithm descriptions). (c) Network-based microsynteny analysis in 18 animal genomes. The heatmap in the top panel shows the pairwise comparisons for microsynteny conservation between any two species. The adjacent network shows several example clusters after microsynteny network clustering. The middle panel shows a binary matrix constructed by the phylogenomic profiling of all clusters, where rows represent clusters and columns represent species. The bottom panel shows the network representation of one conserved (left) and one Eutheria-specific (right) microsynteny genes.

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Extended Data Fig. 3 Functional characterization and regulatory analysis of microsynteny gene clusters.

(a) Association of microsynteny cluster with single-cell transcriptome data of Amphimedon queenslandica (left) and Trichoplax adhaerens (right), with microsynteny genes associated with cell type (top), cell lineage (middle) and co-expression pattern (bottom). (b) Identification of the conserved regulatory CNEs for the well-known pharyngeal gene cluster across four placental mammals. Blue and orange rectangles represent the positions of CNEs on chromosomes that are presented in each species (blue) or conserved across all species (orange). Pink rectangles represent the position of conserved gene cluster on the chromosome of the reference species (human Chr14). (c) Distribution and comparison of TADs around the conserved pharyngeal gene cluster in human and mouse. The chromatin interaction heatmap was generated using the 3D Genome Browser (http://3dgenome.fsm.northwestern.edu/).

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Extended Data Fig. 4 Ancestral genome reconstruction and macrosynteny analysis.

(a) Schematic overview of ancestral genome reconstruction approaches for macrosynteny analysis, which are suitable for a wide range of evolutionary distance (see Kim et al.74 and Simakov et al.75 for detailed algorithm descriptions). (b) Various visualizations of genome macrosynteny for human, chimpanzee and mouse in comparison with the deduced karyotype of the eutherian ancestor, including profiling of karyotype evolution and conservation (CI values), identification of chromosome breakage and fusion events, and genome-wide profiling of macrosynteny landscapes for both genomic DNA-based and protein-based analyses.

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Extended Data Fig. 5 Macrosynteny analysis of 34 representative species across the animal kingdom.

Macrosynteny analysis using the ancestral linkage groups represented by the ancestral genome of Nematostella vectensis is presented, with orange and blue dots representing chromosome-level and scaffold-level genomes, respectively. In the dot plots, dots represent homologous genes distributed in the chromosomes of compared species (x-axis: extant species, y-axis: bilaterian ancestor). Conserved macrosynteny blocks (with statistical significance) are indicated by red dots.

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Extended Data Fig. 6 Visualization of karyotype evolution and integration with functional genomics data.

(a) Visualization of karyotype comparison of the bilaterian ancestor with human (top) or mouse (bottom). Each color represents one of the 17 chromosomes of bilaterian ancestor. (b) Integrative analysis of karyotype and regulatory evolution in humans (top) and mice (bottom). The color density in the heatmap represents the relative number of contacts observed within chromosomes. Various epigenetic and regulatory data are collectively shown for the chromosomes under investigation. The chromatin interaction heatmap was generated using the 3D Genome Browser (http://3dgenome.fsm.northwestern.edu/).

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Extended Data Fig. 7 Schematic overview of pan-evolutionary analysis of microsynteny and macrosynteny.

(a) Recovering macrosyntenic ancient blocks from microsyntenic gene clusters in extant species. Coloured circles correspond to different OGs. The lengths of the edges in the networks are proportional to the intergenic distance. The schematic overview is adapted from the SYNPHONI pipeline27. (b) Tracing evolutionary trajectories and dynamics of gene contents and gene orders from ancestors to extant species in the aspects of gene gain and loss events and conservative transitions from macrosynteny to microsynteny.

Extended Data Fig. 8 Whole-genome distribution and three-dimensional exhibition of ancient/novel gene clusters.

(a) Distribution of Eutheria-conserved (green), Boreoeutheria-conserved (pink) and Simian-conserved (blue) microsynteny genes along the human chromosomes. (b) Three-dimensional chromosome model of human (top) and mouse (bottom), with color labeling Eutheria-conserved (left), Euarchontoglires-conserved (middle) and Simian/Glires-specific (right) microsynteny locations. Gray thick threads represent the 3D structure of the entire chromosome. 3D genome structures are visualized using the Nucleome Browser (http://www.nucleome.org).

Source data

Extended Data Fig. 9 Integrated pan-evolutionary and regulatory analysis of genome microsynteny and macrosynteny.

(a) Chromosomal distribution of macrosynteny, microsynteny and various regulatory information derived from the ENCODE project in human (left) and mouse (right). Rectangles represent conserved synteny genes (blue: macrosynteny, green: microsynteny, red: microsynteny & macrosynteny). Visualization of various associated regulatory data types is shown below. (b) Functional enrichment analysis of macrosynteny/microsynteny genes based on KEGG (top) and GO (bottom) annotation. In the bubble diagrams, the color and size of the bubbles are utilized to convey statistical information, such as the P-value and the number of overlapping genes with the pathway. In the bar charts, the enriched annotated GO terms are shown, with statistical significance indicated by the height of the bars. (c) Detailed presentation of CNEs and other regulatory information from ENCODE for the HOXA gene cluster in human and mouse. Blue and red rectangles represent the position of the HOXA gene cluster and identified CNEs on chromosomes, respectively. Various ENCODE data types are collectively shown for the chromosomal regions under investigation.

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Extended Data Table 1 Technical comparison between PanSyn and other commonly used or newly published tools
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Supplementary information

Supplementary Table 1

The sources of all the input datasets used in demonstration.

Supplementary Code 1

All PanSyn source codes and user guidance.

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Yu, H., Li, Y., Han, W. et al. Pan-evolutionary and regulatory genome architecture delineated by an integrated macro- and microsynteny approach. Nat Protoc (2024). https://doi.org/10.1038/s41596-024-00966-4

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