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Trichoptera (caddisflies) play an essential role in freshwater ecosystems; for instance, larvae process organic material from the water and are food for a variety of predators. Knowledge on the genomic diversity of caddisflies can facilitate comparative and phylogenetic studies thereby allowing scientists to better understand the evolutionary history of caddisflies. While Trichoptera are the most diverse aquatic insect order, they remain poorly represented in terms of genomic resources. To date, all long-read based genomes have been sequenced from individuals in the retreat-making suborder, Annulipalpia, leaving ∼275 Ma of evolution without high-quality genomic resources. Here, we report the first long-read based de novo genome assemblies of two tube case-making Trichoptera from the suborder Integripalpia, Agrypnia vestita Walker and Hesperophylax magnus Banks. We find that these tube case-making caddisflies have genome sizes that are at least three-fold larger than those of currently sequenced annulipalpian genomes and that this pattern is at least partly driven by major expansion of repetitive elements. In H. magnus, long interspersed nuclear elements (LINEs) alone exceed the entire genome size of some annulipalpian counterparts suggesting that caddisflies have high potential as a model for understanding genome size evolution in diverse insect lineages.

Trichoptera (caddisflies) play an essential role in freshwater ecosystems; for instance, larvae process organic material from the water and are food for a variety of predators. Knowledge on the genomic diversity of caddisflies can facilitate comparative and phylogenetic studies thereby allowing scientists to better understand the evolutionary history of caddisflies. While Trichoptera are the most diverse aquatic insect order, they remain poorly represented in terms of genomic resources. To date, all long-read based genomes have been sequenced from individuals in the retreat-making suborder, Annulipalpia, leaving ∼275 Ma of evolution without high-quality genomic resources. Here, we report the first long-read based de novo genome assemblies of two tube case-making Trichoptera from the suborder Integripalpia, Agrypnia vestita Walker and Hesperophylax magnus Banks. We find that these tube case-making caddisflies have genome sizes that are at least three-fold larger than those of currently sequenced annulipalpian genomes and that this pattern is at least partly driven by major expansion of repetitive elements. In H. magnus, long interspersed nuclear elements (LINEs) alone exceed the entire genome size of some annulipalpian counterparts suggesting that caddisflies have high potential as a model for understanding genome size evolution in diverse insect lineages.SignificanceThere is a lack of genomic resources for aquatic insects. So far, only three high-quality genomes have been assembled, all from individuals in the retreat-making suborder Annulipalpia. In this article, we report the first high-quality genomes of two case-making species from the suborder Integripalpia, which are essential for studying genomic diversity across this ecologically diverse insect order. Our research reveals larger genome sizes in the tube case-makers (suborder Integripalpia, infraorder Phryganides), accompanied by a disproportionate increase of repetitive DNA. This suggests that genome size is at least partly driven by a major expansion of repetitive elements. Our work shows that caddisflies have high potential as a model for understanding how genomic diversity might be linked to functional diversification and forms the basis for detailed studies on genome size evolution in caddisflies.Data depositionThis project has been deposited at NCBI under the Bioproject ID: PRJNA668166

Shotgun proteomics is essential for protein identification and quantification in biomedical research, but protein isoform characterization is inhibited by the extensive number of peptides shared across proteins, hindering our understanding of protein isoform regulation and their roles in normal and disease biology. We systematically assess the challenge and opportunities of shotgun proteomics-based protein isoform characterization using in silico and experimental data, and then present SEPepQuant, a graph theory-based approach to enable isoform characterization. Using published data from one induced pluripotent stem cell study and two human hepatocellular carcinoma studies, we demonstrate the ability of SEPepQuant in addressing the key limitations of existing methods, providing more comprehensive proteome characterization, identifying hundreds of isoform-level regulation events, and facilitating streamlined crossstudy comparisons. Our analysis provides solid evidence to support a widespread role of protein isoform regulation in normal and disease processes, and SEPepQuant has broad applications to biological and translational research.

A growing number of datasets characterize tumors with quantitative proteomic and genomic data. These emerging datasets are typically specific to a single cancer type. However, analysis of proteogenomic patterns across multiple cancer types allows us to identify common mechanisms in the function of cancer, as well as mechanisms that are unique to specific cancer types. Here we present how a Python data API from the NCI's CPTAC program bridges the gap between different cancer datasets to facilitate pancancer analysis. While we have previously presented this API as a general model for data dissemination, we have yet to display the specific pancancer applications of the tool. Several key aspects of its design optimize its use from a pancancer point of view, including parsing data to a single consistent format for all datasets, and automatically managed data updates for each dataset. Our analyses demonstrate the efficacy of our data model for generalizing an analysis pipeline, applying it to multiple cancer types, and comparing the results. This enables unique discoveries that characterize the overall proteogenomic landscape of cancer. Citation Format: Caleb M. Lindgren, Chelsie Minor, Lindsey K. Olsen, Brittany Henderson, CPTAC Investigators, Samuel H. Payne. Data distribution for easy pancancer analysis [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 251.

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