Reference Genome Assembly of Marmota marmota

Applied Genomics 2025 – University of Bologna

Table of Contents

• Repository Structure
• Introduction
• Aim of the Project
• Material and Methods
• Estimated Cost
• Results
• Discussion
• Conclusion
• References
• Author

Repository Structure

The repository is organized into two main sections:

• project/ → contains the Applied Genomics final project:

  • REPORT_AG_NATALE_SOFIA.pdf (full report)
  • Reference Genome Assembly of Marmota marmota Reveals Molecular Bases of Hibernation and Life at High Altitude.pptx (PowerPoint)

• teaching-materials/ → lecture notes, transcripts and study resources from the Applied Genomics course.

• figures/ → figures and graphical materials generated or used in the project.

Introduction

The Alpine marmot (Marmota marmota) is an alpine rodent adapted to chronic hypoxia at high altitude and to prolonged hibernation with strong metabolic suppression.
Its dual lifestyle makes it an ideal model to study how vertebrate genomes regulate energy balance, stress resistance, and circannual physiology.
A reference genome is crucial to integrate population-level and functional genomic data, with implications for both evolutionary biology and conservation.

Aim of the Project

To generate a chromosome-scale reference genome of M. marmota using a hybrid sequencing strategy (PacBio HiFi, Illumina, Hi-C), and to integrate it with:

• Population genomics across an altitudinal gradient,
• Functional assays (RNA-seq, ATAC-seq, ChIP-seq, WGBS),
• Comparative genomics to detect conserved vs. marmot-specific adaptations.

Material and Methods

• Sample collection: Active and hibernating marmots sampled in the Stelvio National Park.
• Genome sequencing: PacBio HiFi long reads, Illumina NovaSeq short reads, Hi-C scaffolding.
• Assembly & annotation: Hifiasm, Pilon, AUGUSTUS, RepeatMasker, BUSCO.
• Population genomics: Pool-seq (80 pools from 10 populations), BWA-MEM, bcftools, π, θ, F_ST, Tajima’s D.
• Functional assays:
  • RNA-seq (STAR, DESeq2, GO/KEGG enrichment),
  • ATAC-seq & H3K27ac ChIP-seq (chromatin accessibility & enhancers),
  • WGBS (Bismark, methylKit) for DNA methylation.
• Comparative analyses: Orthologous gene families, annotation (eggNOG), synteny (MCScanX), adaptive evolution (dN/dS).

Figure: Overview of the methodological pipeline from genome sequencing to integrative analyses.

Estimated Cost

Category	Details	Estimated Cost (€)
Sample collection & DNA	Fieldwork & logistics, consumables, cold chain, permits	73,000
Reference genome	PacBio HiFi, Illumina, Hi-C sequencing	30,100
Population genomics	Pool-seq (80 pools, libraries, sequencing)	20,000
Functional assays	RNA-seq, ATAC-seq, ChIP-seq, WGBS	40,400
Personnel	Technician (18 mo, 37,500), Postdoc (24 mo, 70,000)	115,500
Genome assembly & quality control	Storage & computing	15,000
Total		294,000

Results

Expected outcomes:

• A high-quality reference genome (scaffold N50 > 50 Mb, BUSCO >95%).
• Population variation: reduced nucleotide diversity at altitude, high F_ST at candidate loci.
• Transcriptome profiling: DEGs enriched in lipid metabolism, thermogenesis, circadian rhythm.
• Chromatin assays: active enhancers and promoters with state-dependent activity.
• DNA methylation: DMRs overlapping metabolic and hypoxia-related genes.
• Comparative genomics: lineage-specific expansions and adaptive signatures in marmot-specific genes.

Discussion

The integrative design combines ecological realism (altitude + hibernation) with molecular resolution (multi-omics + population genomics).

Strengths:

• Reference genome anchors all analyses.
• Multi-omics validation ensures robust identification of adaptive loci.
• Comparative framework distinguishes conserved vs. species-specific adaptations.

Limitations:

• Hybrid assemblies may miss complex regions.
• Functional predictions need experimental validation.
• Geographic scope limited to Stelvio National Park.

Conclusion

This project establishes the Alpine marmot as a reference model for studying mammalian adaptation to chronic hypoxia and prolonged hibernation.
It provides a transferable pipeline for non-model species, with applications in:

• Biomedical research (metabolic suppression, ischemia tolerance),
• Conservation (genomic markers of climate resilience).

This project establishes the Alpine marmot as a genomic reference model for adaptation studies, bridging ecology, evolution, and biomedicine.

References

• Gossmann, T. I., & Ralser, M. (2020). Marmota marmota. Trends in Genetics, 36(5), 383–384. https://doi.org/10.1016/j.tig.2020.01.006
• Ortmann, S., & Heldmaier, G. (2000). Regulation of body temperature and energy requirements of hibernating alpine marmots. Am J Physiol Regul Integr Comp Physiol, 278(3), R698–R704. https://doi.org/10.1152/ajpregu.2000.278.3.R698
• Theodoridis, S., et al. (2020). Evolutionary history and past climate change shape genetic diversity in mammals. Nature Communications, 11, 2557. https://doi.org/10.1038/s41467-020-16449-5
• Rhoads, A., & Au, K. F. (2015). PacBio sequencing and its applications. Genomics, Proteomics & Bioinformatics, 13(5), 278–289. https://doi.org/10.1016/j.gpb.2015.08.002
• Modi, A., Vai, S., Caramelli, D., & Lari, M. (2021). The Illumina sequencing protocol and the NovaSeq 6000 system. Methods Mol Biol, 2242, 15–42. https://doi.org/10.1007/978-1-0716-1099-2_2
• Seppey, M., Manni, M., & Zdobnov, E. M. (2019). BUSCO: assessing genome assembly and annotation completeness. Methods Mol Biol, 1962, 227–245. https://doi.org/10.1007/978-1-4939-9173-0_14

Author

Sofia Natale
MSc in Bioinformatics – University of Bologna
Contact: sofia.natale@studio.unibo.it