Understanding dysfunction may require the identification of single-cell gene expression profiles of individual cells from complex tissues and organs.
Technology to drive breakthrough science
All tissues and organs are made up of a collection of diverse cell types, with some organs being markedly more complex than others. With increased age, our tissues become more heterogeneous. This change is often accompanied by increasing dysfunction caused by a variety of factors that we don’t fully understand. One approach for better understanding tissue dysfunction with age is to measure gene expression averaged from specific organs or tissues (for example, comparing gene expression of young samples to old samples). This approach averages the gene expression of all the cells together, masking potentially distinct signatures of subpopulations of cells within the tissue.
Over the past few years, there has been a revolution that has combined technologies in microfluidics, machine learning, and gene expression profiling. The combination of these diverse technologies and analytical methods enables the characterization of gene expression profiles of tens of thousands of individual cells from complex tissues and organs. Single-cell gene expression profiling allows us to identify gene expression signatures of small populations of cells within a tissue, which may yield unique insights into how tissues age or respond to age-related disease.
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