The 3D organization of eukaryotic chromosomes affects key processes such as gene expression, DNA replication, cell division, and response to DNA damage. The genome-wide chromosome conformation capture (Hi-C) approach can characterize the landscape of 3D genome organization by measuring interaction frequencies between all genomic regions. Hi-C protocol improvements and rapid advances in DNA sequencing power have made Hi-C useful to study diverse biological systems, not only to elucidate the role of 3D genome structure in proper cellular function, but also to characterize genomic rearrangements, assemble new genomes, and consider chromatin interactions as potential biomarkers for diseases. Yet, the Hi-C protocol is still complex and subject to variations at numerous steps that can affect the resulting data. Thus, there is still a need for better understanding and control of factors that contribute to Hi-C experiment success and data quality. Here, we evaluate recently proposed Hi-C protocol modifications as well as often overlooked variables in sample preparation and examine their effects on Hi-C data quality. We examine artifacts that can occur during Hi-C library preparation, including microhomology-based artificial template copying and chimera formation that can add noise to the downstream data. Exploring the mechanisms underlying Hi-C artifacts pinpoints steps that should be further optimized in the future. To improve the utility of Hi-C in characterizing the 3D genome of specialized populations of cells or small samples of primary tissue, we identify steps prone to DNA loss which should be considered to adapt Hi-C to lower cell numbers.

真核染色体的3D组织会影响关键过程，例如基因表达，DNA复制，细胞分裂以及对DNA损伤的反应。全基因组染色体构象捕获（Hi-C）方法可通过测量所有基因组区域之间的相互作用频率来表征3D基因组组织的格局。Hi-C协议的改进和DNA测序能力的飞速发展使Hi-C可用于研究各种生物系统，不仅阐明3D基因组结构在适当细胞功能中的作用，而且还可表征基因组重排，组装新基因组，并考虑染色质相互作用作为疾病的潜在生物标记。但是，Hi-C协议仍然很复杂，并且在许多步骤上都会发生变化，从而可能影响结果数据。因此，仍然需要更好地理解和控制有助于Hi-C实验成功和数据质量的因素。在这里，我们评估了最近提出的Hi-C协议修改以及样品制备中经常被忽略的变量，并检查了它们对Hi-C数据质量的影响。我们检查了在Hi-C库准备过程中可能发生的伪影，包括基于微同源性的人工模板复制和嵌合体形成，这些杂物会给下游数据增加噪音。探索Hi-C工件的基础机制可确定将来应进一步优化的步骤。为了提高Hi-C在表征专业细胞或初级组织小样本群体的3D基因组中的效用，我们确定了容易发生DNA丢失的步骤，应考虑将Hi-C适应于更低的细胞数量。