In Nature Biotechnology this week, Hubrecht Institute researchers describe a new approach to quantify genomic DNA and mRNA from the same cell without physically separating the two before amplification. They demonstrated that the method is as efficient as similar methods for single-cell sequencing of either genomic DNA or mRNA, and they expect it will facilitate applications ranging from the study of cancer evolution and heterogeneity to understanding the transcriptional consequences of copy number variations in healthy and diseased tissue. GenomeWeb has more on this study here.
Meanwhile, in Nature Genetics, a team led by University of Michigan scientists report the landscape of long non-coding RNAs (lncRNAs) in the human transcriptome. They curated more than 7,000 RNAs sequencing libraries from tumors, normal tissues, and cell lines from 25 independent studies, and applied ab initio assembly methodology to the dataset, which yielded a consensus human transcriptome of roughly 91,000 expressed genes. More than 68 percent of these genes were classified as lncRNAs, of which nearly 80 percent were previously unannotated. Non-parametric differential expression testing was used to prioritize lineage-specific, disease-associated lncRNA expression and revealed about 7,900 lineage- or cancer-associated lncRNA genes. The resource is expected to help uncover new details about normal biology and cancer pathogenesis, and may ultimately assist in new biomarker development.