RNA parmak izi hücre değişimlerini olası nedenleriyle eşleştiriyor

Single-cell methods can describe changes in gene activity with great detail, yet a changed cell does not reveal by itself what caused the change. Researchers at the New York Genome Center, New York University and Columbia University developed RNA fingerprinting to address that problem. The computational method compares an unfamiliar RNA pattern with large reference collections in which scientists have deliberately disrupted genes, applied drugs or exposed cells to immune signals. It separates ordinary variation among cells from the response that may matter, then weighs the evidence for several possible matches instead of forcing a single answer when the data remain unclear. In one test, profiles from cells treated with BCR-ABL inhibitors matched the BCR gene among thousands of candidate perturbations. The method also indicated that two compounds described as selective HDAC6 inhibitors produced broader effects at higher doses. In mice reinfected with influenza, it distinguished immune-cell responses that conventional single-cell analysis had missed. The software is open source, offering researchers hypotheses to test rather than final clinical conclusions.