Using a novel method to sequence large numbers of sperm genomes, researchers have generated new insights into meiotic diversity among gametes. As reported in this week's Nature, the technique, dubbed Sperm-seq, involves decondensing tightly compacted sperm nuclei by mimicking the unpacking process used by eggs, then encapsulating the sperm DNA with barcoding beads. Newly developed computational methods are then used to determine the chromosomal phase of the sequence variants of each donor and to infer the ploidy and crossovers of each chromosome in each cell. In the study, Sperm-seq was applied to 31,228 human sperm genomes from 20 donors, revealing 813,122 chromosome crossovers and 787 aneuploid chromosomes. Other findings include aneuploidy rates ranging from 0.01 to 0.05 aneuploidies per gamete among the donors, as well as many genomic anomalies that could not be explained by simple nondisjunction. GenomeWeb has more on this, here.
While deep targeted sequencing holds great potential for cancer care, the technology is limited in low-burden disease due to low tumor fraction and the small number of cell-free DNA in circulation. Reasoning that breadth may supplant depth of sequencing for sensitive detection of low-burden cancer, a team led by investigators from the New York Genome Center developed a tumor-informed detection approach for the minimal residual disease (MRD) setting — called MRDetect — that uses genome-wide mutational integration to enable accurate and sensitive circulating tumor DNA detection in fractions as low as 10-5. This whole-genome sequencing approach, the scientists write in Nature Medicine, enables dynamic tumor burden tracking and postoperative residual disease detection associated with adverse outcome.
To overcome experimental and statistical limitations that hamper the sensitivity and throughput of genetic screens that use transcriptomics as a readout, researchers from the European Molecular Biology Laboratory have developed a technique for focusing single-cell RNA-seq coverage on genes of interest. This, they write in Nature Methods, increases the sensitivity and scale of genetic screens by orders of magnitude. Called targeted Perturb-seq, or TAP-seq, the method allows routine analysis of thousands of CRISPR-mediated perturbations within a single experiment, detects weak effects and lowly expressed genes, and decreases sequencing requirements by up to 50-fold. The scientists use TAP-seq to generate perturbation-based enhancer-target gene maps for 1,778 enhancers within 2.5 percent of the human genome and show that the method can identify cell subtypes with only 100 sequencing reads per cell.