Phylogenomics reveals patterns of ancient hybridization and differential diversification that contribute to phylogenetic conflict in willows, poplars, and close relatives.

Despite the economic, ecological, and scientific importance of the genera Salix L. (willows) and Populus L. (poplars, cottonwoods, and aspens) Salicaceae, we know little about the sources of differences in species diversity between the genera and of the phylogenetic conflict that often confounds estimating phylogenetic trees. Salix subgenera and sections, in particular, have been difficult to classify, with one recent attempt termed a "spectacular failure" due to a speculated radiation of the subgenera Vetrix and Chamaetia. Here, we use targeted sequence capture to understand the evolutionary history of this portion of the Salicaceae plant family. Our phylogenetic hypothesis was based on 787 gene regions and identified extensive phylogenetic conflict among genes. Our analysis supported some previously described subgeneric relationships and confirmed the polyphyly of others. Using an fbranch analysis, we identified several cases of hybridization in deep branches of the phylogeny, which likely contributed to discordance among gene trees. In addition, we identified a rapid increase in diversification rate near the origination of the Vetrix-Chamaetia clade in Salix. This region of the tree coincided with several nodes that lacked strong statistical support, indicating a possible increase in incomplete lineage sorting due to rapid diversification. The extraordinary level of both recent and ancient hybridization in both Salix and Populus have played important roles in the diversification and diversity in these two genera.

A Genomically and Clinically Annotated Patient-Derived Xenograft Resource for Preclinical Research in Non-Small Cell Lung Cancer.

Patient-derived xenograft (PDX) models are an effective preclinical in vivo platform for testing the efficacy of novel drugs and drug combinations for cancer therapeutics. Here we describe a repository of 79 genomically and clinically annotated lung cancer PDXs available from The Jackson Laboratory that have been extensively characterized for histopathologic features, mutational profiles, gene expression, and copy-number aberrations. Most of the PDXs are models of non-small cell lung cancer (NSCLC), including 37 lung adenocarcinoma (LUAD) and 33 lung squamous cell carcinoma (LUSC) models. Other lung cancer models in the repository include four small cell carcinomas, two large cell neuroendocrine carcinomas, two adenosquamous carcinomas, and one pleomorphic carcinoma. Models with both de novo and acquired resistance to targeted therapies with tyrosine kinase inhibitors are available in the collection. The genomic profiles of the LUAD and LUSC PDX models are consistent with those observed in patient tumors from The Cancer Genome Atlas and previously characterized gene expression-based molecular subtypes. Clinically relevant mutations identified in the original patient tumors were confirmed in engrafted PDX tumors. Treatment studies performed in a subset of the models recapitulated the responses expected on the basis of the observed genomic profiles. These models therefore serve as a valuable preclinical platform for translational cancer research. SIGNIFICANCE: Patient-derived xenografts of lung cancer retain key features observed in the originating patient tumors and show expected responses to treatment with standard-of-care agents, providing experimentally tractable and reproducible models for preclinical investigations.

PDXNet portal: patient-derived Xenograft model, data, workflow and tool discovery.

We created the PDX Network (PDXNet) portal (https://portal.pdxnetwork.org/) to centralize access to the National Cancer Institute-funded PDXNet consortium resources, to facilitate collaboration among researchers and to make these data easily available for research. The portal includes sections for resources, analysis results, metrics for PDXNet activities, data processing protocols and training materials for processing PDX data. Currently, the portal contains PDXNet model information and data resources from 334 new models across 33 cancer types. Tissue samples of these models were deposited in the NCI's Patient-Derived Model Repository (PDMR) for public access. These models have 2134 associated sequencing files from 873 samples across 308 patients, which are hosted on the Cancer Genomics Cloud powered by Seven Bridges and the NCI Cancer Data Service for long-term storage and access with dbGaP permissions. The portal includes results from freely available, robust, validated and standardized analysis workflows on PDXNet sequencing files and PDMR data (3857 samples from 629 patients across 85 disease types). The PDXNet portal is continuously updated with new data and is of significant utility to the cancer research community as it provides a centralized location for PDXNet resources, which support multi-agent treatment studies, determination of sensitivity and resistance mechanisms, and preclinical trials.

A targeted sequence capture array for phylogenetics and population genomics in the Salicaceae.

PREMISE: The family Salicaceae has proved taxonomically challenging, especially in the genus Salix, which is speciose and features frequent hybridization and polyploidy. Past efforts to reconstruct the phylogeny with molecular barcodes have failed to resolve the species relationships of many sections of the genus. METHODS: We used the wealth of sequence data in the family to design sequence capture probes to target regions of 300-1200 bp of exonic regions of 972 genes. RESULTS: We recovered sequence data for nearly all of the targeted genes in three species of Populus and three species of Salix. We present a species tree, discuss concordance among gene trees, and present population genomic summary statistics for these loci. CONCLUSIONS: Our sequence capture array has extremely high capture efficiency within the genera Populus and Salix, resulting in abundant phylogenetic information. Additionally, these loci show promise for population genomic studies.