Exonuclease combinations reduce noises in 3D genomics technologies

The shape of chromatin: insights from computational recognition of geometric patterns in Hi-C data

The three-dimensional organization of chromatin plays a crucial role in gene regulation and cellular processes like deoxyribonucleic acid (DNA) transcription, replication and repair. Hi-C and related techniques provide detailed views of spatial proximities within the nucleus. However, data analysis is challenging partially due to a lack of well-defined, underpinning mathematical frameworks. Recently, recognizing and analyzing geometric patterns in Hi-C data has emerged as a powerful approach. This review provides a summary of algorithms for automatic recognition and analysis of geometric patterns in Hi-C data and their correspondence with chromatin structure. We classify existing algorithms on the basis of the data representation and pattern recognition paradigm they make use of. Finally, we outline some of the challenges ahead and promising future directions.

Exploring the Role of Enhancer-Mediated Transcriptional Regulation in Precision Biology

The emergence of precision biology has been driven by the development of advanced technologies and techniques in high-resolution biological research systems. Enhancer-mediated transcriptional regulation, a complex network of gene expression and regulation in eukaryotes, has attracted significant attention as a promising avenue for investigating the underlying mechanisms of biological processes and diseases. To address biological problems with precision, large amounts of data, functional information, and research on the mechanisms of action of biological molecules is required to address biological problems with precision. Enhancers, including typical enhancers and super enhancers, play a crucial role in gene expression and regulation within this network. The identification and targeting of disease-associated enhancers hold the potential to advance precision medicine. In this review, we present the concepts, progress, importance, and challenges in precision biology, transcription regulation, and enhancers. Furthermore, we propose a model of transcriptional regulation for multi-enhancers and provide examples of their mechanisms in mammalian cells, thereby enhancing our understanding of how enhancers achieve precise regulation of gene expression in life processes. Precision biology holds promise in providing new tools and platforms for discovering insights into gene expression and disease occurrence, ultimately benefiting individuals and society as a whole.

An SPRI beads-based DNA purification strategy for flexibility and cost-effectiveness

BACKGROUND

Current solid-phase reversible immobilization (SPRI) beads technology is widely used in molecular biology due to its convenience for DNA manipulation. However, the high performance commercial SPRI beads have no price advantage over our method. Furthermore, the use of commercially available SPRI beads standards does not provide the flexibility required for a number of specific nucleic acid handling scenarios.

RESULTS

We report an efficient DNA purification strategy by combining home-made beads-suspension buffer with SPRI beads. The method tests the critical concentrations of polyethylene glycol (PEG) 8000 and beads to maximise recovery. And the composition of the SPRI beads DNA purification system (SDPS) was determined at 20% PEG 8000, 2 M NaCl and 16.3 mM MgCl2, and 1.25 mg/ml beads (1/8th original concentration). Then, we tested the DNA recovery of the SDPS, and the result showed that it was comparable to the control (AMPure XP beads). In the study, we have also developed an adjustment SPRI beads DNA purification system (ASDPS), the volume of ASDPS per reaction is 0.6× reaction volume (beads/samples). The performance of ASDPS is similar to SDPS and the control. But the cost of our methods is only about 1/24th of the control. To further assess its performance, we prepare the DNA-seq libraries to evaluate the yield, library quality, capture efficiency and consistency. We have compared all these results with the performance of the control and confirmed its efficiency.

CONCLUSION

We have proposed an alternative DNA purification approach with great flexibility, allowing researchers to manipulate DNA in different conditions. And ultimately, its application will benefit molecular biology research in the future.

Single-cell omics: A new direction for functional genetic research in human diseases and animal models

Over the past decade, with the development of high-throughput single-cell sequencing technology, single-cell omics has been emerged as a powerful tool to understand the molecular basis of cellular mechanisms and refine our knowledge of diverse cell states. They can reveal the heterogeneity at different genetic layers and elucidate their associations by multiple omics analysis, providing a more comprehensive genetic map of biological regulatory networks. In the post-GWAS era, the molecular biological mechanisms influencing human diseases will be further elucidated by single-cell omics. This review mainly summarizes the development and trend of single-cell omics. This involves single-cell omics technologies, single-cell multi-omics technologies, multiple omics data integration methods, applications in various human organs and diseases, classic laboratory cell lines, and animal disease models. The review will reveal some perspectives for elucidating human diseases and constructing animal models.

Application of Hi-C and other omics data analysis in human cancer and cell differentiation research

With the development of 3C (chromosome conformation capture) and its derivative technology Hi-C (High-throughput chromosome conformation capture) research, the study of the spatial structure of the genomic sequence in the nucleus helps researchers understand the functions of biological processes such as gene transcription, replication, repair, and regulation. In this paper, we first introduce the research background and purpose of Hi-C data visualization analysis. After that, we discuss the Hi-C data analysis methods from genome 3D structure, A/B compartment, TADs (topologically associated domain), and loop detection. We also discuss how to apply genome visualization technologies to the identification of chromosome feature structures. We continue with a review of correlation analysis differences among multi-omics data, and how to apply Hi-C and other omics data analysis into cancer and cell differentiation research. Finally, we summarize the various problems in joint analyses based on Hi-C and other multi-omics data. We believe this review can help researchers better understand the progress and applications of 3D genome technology.