New dryocosmus giraud species associated with cyclobalanopsis and non-quercus host plants from the eastern palaearctic (hymenoptera, cynipidae, cynipini)

Volume: 53Start Page: 77End Page: 16

Network structure and taxonomic composition of tritrophic communities of Fagaceae, cynipid gallwasps and parasitoids in Sichuan, China

A key question in insect community ecology is whether parasitoid assemblages are structured by the food plants of their herbivore hosts. Tritrophic communities centred on oak-feeding cynipid gallwasps are one of the best-studied tritrophic insect communities. Previous work suggests that host plant identity is a much stronger predictor of oak–cynipid interactions than of cynipid–parasitoid interactions. However, these relationships have not been formally quantified. We reason that the potential for ‘bottom-up’ effects should increase with host plant phylogenetic diversity. We, therefore, generated quantified interaction network data for previously unstudied tritrophic cynipid communities in Sichuan, China, where, in addition to Quercus, cynipid host plants include Castanea, Castanopsis and Lithocarpus. We characterise these communities taxonomically and compare the extent to which host plant taxonomy predicts plant–herbivore and plant–parasitoid associations. We sampled 42,620 cynipid galls of 176 morphotypes from 23 host plant species, yielding over 4500 specimens of 64 parasitoid morphospecies. Many parasitoids were identifiable to chalcidoid taxa present in other Holarctic oak cynipid communities, with the addition of Cynipencyrtus (Cynipencyrtidae). As elsewhere, Sichuan parasitoid assemblages were dominated by generalists. Gallwasp–plant interaction networks were significantly more modular than parasitoid–plant association networks. Gallwasps were significantly more specialised to host plants (i.e. had higher mean d' values) than parasitoids. Parasitoid assemblages nevertheless showed significant plant-associated beta diversity, with a dominant turnover component. We summarise parallels between our study and other Fagaceae-associated cynipid communities and discuss our findings in light of the processes thought to structure tritrophic interactions centred on endophytic insect herbivores

Network structure and taxonomic composition of tritrophic communities of Fagaceae, cynipid gallwasps and parasitoids in Sichuan, China

A key question in insect community ecology is whether parasitoid assemblages are structured by the food plants of their herbivore hosts. Tritrophic communities centred on oak‐feeding cynipid gallwasps are one of the best‐studied tritrophic insect communities. Previous work suggests that host plant identity is a much stronger predictor of oak–cynipid interactions than of cynipid–parasitoid interactions. However, these relationships have not been formally quantified. We reason that the potential for ‘bottom‐up’ effects should increase with host plant phylogenetic diversity. We, therefore, generated quantified interaction network data for previously unstudied tritrophic cynipid communities in Sichuan, China, where, in addition to Quercus, cynipid host plants include Castanea, Castanopsis and Lithocarpus. We characterise these communities taxonomically and compare the extent to which host plant taxonomy predicts plant–herbivore and plant–parasitoid associations. We sampled 42,620 cynipid galls of 176 morphotypes from 23 host plant species, yielding over 4500 specimens of 64 parasitoid morphospecies. Many parasitoids were identifiable to chalcidoid taxa present in other Holarctic oak cynipid communities, with the addition of Cynipencyrtus (Cynipencyrtidae). As elsewhere, Sichuan parasitoid assemblages were dominated by generalists. Gallwasp–plant interaction networks were significantly more modular than parasitoid–plant association networks. Gallwasps were significantly more specialised to host plants (i.e. had higher mean d' values) than parasitoids. Parasitoid assemblages nevertheless showed significant plant‐associated beta diversity, with a dominant turnover component. We summarise parallels between our study and other Fagaceae‐associated cynipid communities and discuss our findings in light of the processes thought to structure tritrophic interactions centred on endophytic insect herbivores

Network structure and taxonomic composition of tritrophic communities of Fagaceae, cynipid gallwasps and parasitoids in Sichuan, China

A key question in insect community ecology is whether parasitoid assemblages are structured by the food plants of their herbivore hosts. Tritrophic communities centred on oak‐feeding cynipid gallwasps are one of the best‐studied tritrophic insect communities. Previous work suggests that host plant identity is a much stronger predictor of oak–cynipid interactions than of cynipid–parasitoid interactions. However, these relationships have not been formally quantified. We reason that the potential for ‘bottom‐up’ effects should increase with host plant phylogenetic diversity. We, therefore, generated quantified interaction network data for previously unstudied tritrophic cynipid communities in Sichuan, China, where, in addition to Quercus, cynipid host plants include Castanea, Castanopsis and Lithocarpus. We characterise these communities taxonomically and compare the extent to which host plant taxonomy predicts plant–herbivore and plant–parasitoid associations. We sampled 42,620 cynipid galls of 176 morphotypes from 23 host plant species, yielding over 4500 specimens of 64 parasitoid morphospecies. Many parasitoids were identifiable to chalcidoid taxa present in other Holarctic oak cynipid communities, with the addition of Cynipencyrtus (Cynipencyrtidae). As elsewhere, Sichuan parasitoid assemblages were dominated by generalists. Gallwasp–plant interaction networks were significantly more modular than parasitoid–plant association networks. Gallwasps were significantly more specialised to host plants (i.e. had higher mean d' values) than parasitoids. Parasitoid assemblages nevertheless showed significant plant‐associated beta diversity, with a dominant turnover component. We summarise parallels between our study and other Fagaceae‐associated cynipid communities and discuss our findings in light of the processes thought to structure tritrophic interactions centred on endophytic insect herbivores

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment

Enhanced Statistical Tests for GWAS in Admixed Populations: Assessment using African Americans from CARe and a Breast Cancer Consortium

While genome-wide association studies (GWAS) have primarily examined populations of European ancestry, more recent studies often involve additional populations, including admixed populations such as African Americans and Latinos. In admixed populations, linkage disequilibrium (LD) exists both at a fine scale in ancestral populations and at a coarse scale (admixture-LD) due to chromosomal segments of distinct ancestry. Disease association statistics in admixed populations have previously considered SNP association (LD mapping) or admixture association (mapping by admixture-LD), but not both. Here, we introduce a new statistical framework for combining SNP and admixture association in case-control studies, as well as methods for local ancestry-aware imputation. We illustrate the gain in statistical power achieved by these methods by analyzing data of 6,209 unrelated African Americans from the CARe project genotyped on the Affymetrix 6.0 chip, in conjunction with both simulated and real phenotypes, as well as by analyzing the FGFR2 locus using breast cancer GWAS data from 5,761 African-American women. We show that, at typed SNPs, our method yields an 8% increase in statistical power for finding disease risk loci compared to the power achieved by standard methods in case-control studies. At imputed SNPs, we observe an 11% increase in statistical power for mapping disease loci when our local ancestry-aware imputation framework and the new scoring statistic are jointly employed. Finally, we show that our method increases statistical power in regions harboring the causal SNP in the case when the causal SNP is untyped and cannot be imputed. Our methods and our publicly available software are broadly applicable to GWAS in admixed populations