German researchers present an updated genome annotation for Aspergillus niger, a fungal species that's often tapped to produce large quantities of specific organic acids, enzymes, or other proteins. The team considered more than 150 published, array-based transcriptome datasets, putting together gene co-expression networks representing 9,579 A. niger genes. Along with gene ontology analyses informed with experimental data from other Aspergillus species, the co-expression clues helped to tease out biological roles for almost 9,300 of the A. niger genes, including genes coding for four secondary metabolite-related transcription factors assessed in more detail.
A Johns Hopkins University and University of California, Irvine, team describes a high-throughput sequencing strategy for profiling RNA structure. The approach — known as "Light Activated Structural Examination of RNA by high-throughput sequencing," or LASER-Seq — uses deep sequencing and light-activated chemical probes, the researchers say. They note that LASER-Seq compares favorably with other RNA analysis methods, and say the LASER step in the process "can be used to rapidly survey for ligand binding sites in an unbiased fashion."
Finally, researchers from the University of Colorado School of Medicine report on a transcriptome resampling-based method for delving more deeply into gene expression patterns in pooled single-cell RNA sequence libraries. "[W]e developed a strategy to physically recover the DNA molecules comprising transcriptome subsets, enabling deeper interrogation of the isolated molecules by another round of DNA sequencing," they write. When the team applied this approach to scRNA-seq libraries from blood platelet-producing megakaryocyte cells, for example, it saw a jump in both sequencing depth and in the number of gene transcripts detected in each cell.