Abstract
Cellular heterogeneity is revolutionizing the way to study, monitor and dissect complex diseases. This has been possible with the technological and computational advances associated to single-cell genomics and epigenomics. Deeper understanding of cell-to-cell variation and its impact on tissue function will open new avenues for early disease detection, accurate diagnosis and personalized treatments, all together leading to the next generation of health care. This review focuses on the recent discoveries that single-cell genomics and epigenomics have facilitated in the context of human health. It highlights the potential of single-cell omics to further advance the development of personalized treatments and precision medicine in cancer, diabetes and chronic age-related diseases. The promise of single-cell technologies to generate new insights about the differences in function between individual cells is just emerging, and it is paving the way for identifying biomarkers and novel therapeutic targets to tackle age, complex diseases and understand the effect of life style interventions and environmental factors.
Highlights
Efforts have been made to highlight the importance of moving translational genomic findings to the clinic for the overall improvement of human health (Cho et al 2016; Regev et al 2017; Zeggini et al 2019)
To understand the finer details at the level of a singular cell, sophisticated genomic and epigenomic next-generation sequencing (NGS) technologies have increased the potential for research output immensely
Single-cell genomic approaches are changing the concept of personalized medicine from early detection to tailored treatments
Summary
Efforts have been made to highlight the importance of moving translational genomic findings to the clinic for the overall improvement of human health (Cho et al 2016; Regev et al 2017; Zeggini et al 2019). Efforts have been made to observe cell-type specific transcriptomes mapped to areas of open chromatin to define gene regulatory regions, characterize novel gene signatures and highlight transcription factors of interest pertaining to diabetes pathogenesis (Ackermann et al 2016; Bysani et al 2019; Chiou et al 2019; Rai et al 2019) Most of these studies have used the Assay for Transposase Accessible Chromatin Sequencing (ATAC-seq) technique (Buenrostro et al 2015; Lareau et al 2019) for profiling rare and common endocrine cell types. These pioneering works would potentially allow the identification of biomarkers and further personalized treatments (Huch et al 2017)
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