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Science Papers Describe Approach to Track Genetic Interactions, Sample Prep for Single-Cell Sequencing More

A method that combines CRISPR interference with barcoded expression reporter sequencing to generate phenotypic profiles for tracking genetic interactions is reported in Science this week. Using the approach, called CiBER-seq, its developers at the University of California, Berkeley linked a library of CRISPR guide RNAs to their individual phenotypic consequences using pooled sequencing in yeast, fully recapitulating the integrated stress response pathway in the model organism. "CiBER-seq produces comprehensive phenotypic profiles that offer insights into gene function and regulation," the scientists write. Because the key components of the method "translate into nearly any organism, we anticipate many biological insights will arise from broad application of our approach."

A new sample preparation platform for single-cell whole-genome sequencing is presented in Science Advances this week. Called Digital-WGS, the approach uses digital microfluidics to streamline parallel nanoliter-volume single-cell multiple displacement amplification (MDA), boosting single-cell isolation efficiency and improve whole-genome amplification. The technology's developers at Xiamen University used it to perform a range of single-cell nanoliter-volume MDA reactions and show that it outperforms existing MDA methods. "This approach is also scalable and universal for any chemistry of single-cell analysis, holding great promise for broader applications of single-cell genomics," they write.

Using RNA sequencing to profile circulating, cell-free messenger RNA (cf-mRNA) of 126 Alzheimer's disease patients and age-matched healthy controls, scientists from the biotech firm Molecular Stethoscope have identified a number of genes dysregulated in the disease. As reported in Science Advances this week, the team uncovered gene transcripts differentially present in plasma of patients with Alzheimer's disease, as well as genes correlated with the severity of dementia, including ones enriched in disease-linked biological processes such as synaptic dysfunction, mitochondrial dysfunction, and inflammation. The investigators also used differentially expressed genes to categorize pathological subtypes among those with Alzheimer's disease and built classifiers that robustly discriminate controls from patients. The findings highlight cf-mRNA profiling as "a potential tool to noninvasively characterize diseases such as Alzheimer's disease," and suggest integrated analysis of cf-mRNA profiling with clinical information could be used for improved patient management and therapeutic target identification, the study's authors write.