A repository infrastructure and data resource for reproducible quantitative mass spectrometry-based proteomics experiments is presented in Nature Methods this week. Developed by a team led by Northeastern University scientists, the resource — called MassIVE.quant — is compatible with all mass spectrometry data acquisition types and computational analysis tools. It systematically stores the intermediate output files of every tool and workflow in a way that allows the user to easily inspect, reproduce, or modify any component of the workflow, beginning with well-defined intermediate files. "MassIVE.quant provides an opportunity for large-scale deposition of heterogeneous experimental datasets and facilitates a community-wide conversation about the benefits of its use," its developers write.
A machine learning framework for the systematic, de novo reconstruction of a new kind of tumor-specific molecular interaction signaling map for cancer network analysis is described in Nature Biotechnology. The maps, proposed by a team led by Columbia University scientists, are a representation of the signaling and regulatory machinery necessary to modulate and affect the function of an oncoprotein of interest in a specific tissue context, which is equivalent to a protein's mechanism of action. According to the investigators, these maps — dubbed SigMaps — provide a "more unbiased, compact, and realistic representation of a protein's mechanism of action, compared to available network representations and algorithms." The investigators use the computational framework — called OncoSig — to generate a KRAS-specific SigMap for lung adenocarcinoma, which recapitulated published KRAS biology, identified novel synthetic lethal proteins, and established uncharacterized crosstalk with RAB/RHO family members. They also inferred SigMaps for the ten most mutated human oncoproteins and for the full repertoire of 715 proteins in the COSMIC Cancer Gene Census, demonstrating OncoSig's generalizability.
An analysis of ancient human DNA published in Nature this week reveals that Viking populations influenced the genomic makeup of multiple regions of Europe. An international team led by scientists from the University of Copenhagen sequenced the genomes of 442 humans from archeological sites across Europe and Greenland covering the Bronze Age (around 2400 BC) to the Early Modern Period (around 1600 AD). They found evidence of gene flow into Scandinavia from the south and east during the Viking period of between 750 AD and 1050 AD. The investigators also uncovered evidence showing Viking movements outside of Scandinavia including a Danish influx into England, a Swedish influx into the Baltic, and Norwegian influx into Ireland, Iceland, and Greenland. Notably, the researchers find Swedish-like and Finnish-like ancestry in the westernmost fringes of Europe and Danish-like ancestry in the east, defying modern historical groupings. "It is likely that many such individuals were from communities with mixed ancestries, thrown together by complex trading, raiding, and settling networks that crossed cultures and the continent," they write. Other discoveries include two pairs of kin in which the related individuals were excavated hundreds of miles apart from each other, illustrating the mobility of individuals during the Viking Age. Genome Web has more on this, here.