Hi-C sequencing for de novo Genome Assembly

Sequencing Has Become Essential for de novo Genome Assembly

As genome projects expand across ecology, agriculture, conservation, and translational biology, assembling genomes to chromosome-scale contiguity has become a universal benchmark. Yet long-read or short-read sequencing alone rarely delivers truly complete assemblies—leaving hundreds of contigs, unresolved haplotypes, or structural errors. This is where Hi-C sequencing has become indispensable.

Hi-C provides genome-wide chromatin contact information, capturing how DNA folds in 3D inside the nucleus. Because genomic regions that are close in linear space also tend to be physically near one another, Hi-C read pairs encode long-range proximity signals that can be exploited to scaffold contigs, anchor them to chromosomes, and even phase haplotypes.

Figure 1- Example of Hi-C generated genomic interaction frequency data used to order and orient sequencing contigs into chromosomal scaffolds.

What Hi-C Adds to Genome Assembly

1. Ordering and Orienting Contigs
Hi-C data distinguishes true adjacency from assembly artifacts by quantifying interaction probability across the genome. This enables placing contigs into correct chromosome order and direction .
2. Fixing Mis-assemblies & Revealing Structural Variation
Abnormal patterns in Hi-C contact maps readily flag mis-joins or structural errors. Researchers can manually correct these issues with visualization tools like Juicebox and PretextView.
3. Anchoring to Chromosomes
Hi-C allows delineation of chromosome boundaries by identifying centromeric and telomeric patterns—essential for building chromosome-scale scaffolds.
4. Phasing Haplotypes
Hi-C reads separate haplotypes by exploiting inter- vs intra-chromosomal interaction patterns, enabling accurate maternal/paternal phasing in diploid or polyploid species.

Together, these features upgrade a fragmented contig assembly into a complete, phased, chromosome-scale reference genome (Šimková, et al., 2024)

Technical Considerations That Matter

• Tissue choice impacts library quality - Important considerations include selecting tissues with low endogenous nuclease activity and those that more easily yield high quality single cell suspensions with intact nuclei.
• Restriction enzyme choice (single enzyme vs. multi-enzyme cocktails) affects resolution and uniformity of contact maps.
• QC steps — biotin incorporation, digestion efficiency, and library fragment diversity—are critical for avoiding low-signal or biased libraries. Poor QC results indicating incomplete crosslinking, insufficient digestion, or weak biotin labeling are associated with poor contact map quality and unusable scaffolds.
• Computational scaffolding tools (3D-DNA, SALSA, YaHS, instaGRAAL, HiCExplorer, etc.) vary widely in algorithms and output quality. Correct tool selection depends heavily on the organism, ploidy level, and contig quality.

These insights highlight that while Hi-C sequencing is a powerful tool, it requires rigorous sample prep and computational validation. (Yamaguchi, et al., 2021)

Hi-C in Practice: Real Genome Projects

The value of Hi-C is illustrated directly through BMKGENE’s extensive contributions to scientific literature including, but not limited to, the following featured publications:
• Cotton Genomes – Convergence and divergence of diploid and tetraploid cotton genomes, Nature Genetics, 2024
• Cowpea Genomes – Differential selection of yield and quality traits has shaped genomic signatures of cowpea domestication and improvement, Nature Genetics, 2024
• Australian Tobacco Genome – The complete genome assembly of Nicotiana benthamiana reveals genetic and epigenetic landscape of centromeres, Nature Genetics, 2024
• Chile Pepper Genomes – Two telomere-to-telomere gapless genomes reveal insight into Capsicum evolution and capsaicinoid biosynthesis, Nature Communications, 2024
• Oyster Genome – Chromosome-level genome assembly of Suminoa oyster Crassostrea ariakensis in south China, Scientific Data, 2024

Conclusion

Hi-C has become a cornerstone technology for modern genome assembly because it bridges the gap between fragmented contig assemblies and fully realized chromosome-level genomes. Whether resolving mis-joins, phasing haplotypes, anchoring entire chromosomes, or increasing assembly confidence, Hi-C supplies the long-range information that sequencing alone cannot.

Unlock the full potential of your genome project—partner with BMKGENE and discover how our Hi-C–enhanced de novo assembly services can deliver the chromosome-scale precision that your research demands!

References

1. Li, A., Zhao, J., Dai, H., Zhao, M., Zhang, M., Wang, W., Zhang, G. and Li, L., 2024. Chromosome-level genome assembly of the Suminoe oyster Crassostrea ariakensis in south China. Scientific Data, 11(1), p.1296.
2. Šimková, H., Câmara, A.S. and Mascher, M., 2024. Hi-C techniques: from genome assemblies to transcription regulation. Journal of Experimental Botany, 75(17), pp.5357-5365.
3. Yamaguchi, K., Kadota, M., Nishimura, O., Ohishi, Y., Naito, Y. and Kuraku, S., 2021. Technical considerations in Hi‐C scaffolding and evaluation of chromosome‐scale genome assemblies. Molecular Ecology, 30(23), pp.5923-5934.
4. Li, J., Liu, Z., You, C., Qi, Z., You, J., Grover, C.E., Long, Y., Huang, X., Lu, S., Wang, Y. and Zhang, S., 2024. Convergence and divergence of diploid and tetraploid cotton genomes. Nature Genetics, 56(11), pp.2562-2573.
5. Wu, X., Hu, Z., Zhang, Y., Li, M., Liao, N., Dong, J., Wang, B., Wu, J., Wu, X., Wang, Y. and Wang, J., 2024. Differential selection of yield and quality traits has shaped genomic signatures of cowpea domestication and improvement. Nature Genetics, 56(5), pp.992-1005.
6. Chen, W., Yan, M., Chen, S., Sun, J., Wang, J., Meng, D., Li, J., Zhang, L. and Guo, L., 2024. The complete genome assembly of Nicotiana benthamiana reveals the genetic and epigenetic landscape of centromeres. Nature Plants, 10(12), pp.1928-1943.
7. Chen, W., Wang, X., Sun, J., Wang, X., Zhu, Z., Ayhan, D.H., Yi, S., Yan, M., Zhang, L., Meng, T. and Mu, Y., 2024. Two telomere-to-telomere gapless genomes reveal insights into Capsicum evolution and capsaicinoid biosynthesis. Nature Communications, 15(1), p.4295.