Accurate identification of structural variations from cancer samples.

Structural variations (SVs) are commonly found in cancer genomes. They can cause gene amplification, deletion and fusion, among other functional consequences. With an average read length of hundreds of kilobases, nano-channel-based optical DNA mapping is powerful in detecting large SVs. However, existing SV calling methods are not tailored for cancer samples, which have special properties such as mixed cell types and sub-clones. Here we propose the Cancer Optical Mapping for detecting Structural Variations (COMSV) method that is specifically designed for cancer samples. It shows high sensitivity and specificity in benchmark comparisons. Applying to cancer cell lines and patient samples, COMSV identifies hundreds of novel SVs per sample.

MaXLinker: Proteome-wide Cross-link Identifications with High Specificity and Sensitivity.

Protein-protein interactions play a vital role in nearly all cellular functions. Hence, understanding their interaction patterns and three-dimensional structural conformations can provide crucial insights about various biological processes and underlying molecular mechanisms for many disease phenotypes. Cross-linking mass spectrometry (XL-MS) has the unique capability to detect protein-protein interactions at a large scale along with spatial constraints between interaction partners. The inception of MS-cleavable cross-linkers enabled the MS2-MS3 XL-MS acquisition strategy that provides cross-link information from both MS2 and MS3 level. However, the current cross-link search algorithm available for MS2-MS3 strategy follows a "MS2-centric" approach and suffers from a high rate of mis-identified cross-links. We demonstrate the problem using two new quality assessment metrics ["fraction of mis-identifications" (FMI) and "fraction of interprotein cross-links from known interactions" (FKI)]. We then address this problem, by designing a novel "MS3-centric" approach for cross-link identification and implementing it as a search engine named MaXLinker. MaXLinker outperforms the currently popular search engine with a lower mis-identification rate, and higher sensitivity and specificity. Moreover, we performed human proteome-wide cross-linking mass spectrometry using K562 cells. Employing MaXLinker, we identified a comprehensive set of 9319 unique cross-links at 1% false discovery rate, comprising 8051 intraprotein and 1268 interprotein cross-links. Finally, we experimentally validated the quality of a large number of novel interactions identified in our study, providing a conclusive evidence for MaXLinker's robust performance.

A reference-grade wild soybean genome.

Efficient crop improvement depends on the application of accurate genetic information contained in diverse germplasm resources. Here we report a reference-grade genome of wild soybean accession W05, with a final assembled genome size of 1013.2 Mb and a contig N50 of 3.3 Mb. The analytical power of the W05 genome is demonstrated by several examples. First, we identify an inversion at the locus determining seed coat color during domestication. Second, a translocation event between chromosomes 11 and 13 of some genotypes is shown to interfere with the assignment of QTLs. Third, we find a region containing copy number variations of the Kunitz trypsin inhibitor (KTI) genes. Such findings illustrate the power of this assembly in the analysis of large structural variations in soybean germplasm collections. The wild soybean genome assembly has wide applications in comparative genomic and evolutionary studies, as well as in crop breeding and improvement programs.