Methods and strategies for gene structure curation in WormBase

The Caenorhabditis elegans genome sequence was published over a decade ago; this was the first published genome of a multi-cellular organism and now the WormBase project has had a decade of experience in curating this genome's sequence and gene structures. In one of its roles as a central repository for nematode biology, WormBase continues to refine the gene structure annotations using sequence similarity and other computational methods, as well as information from the literature- and community-submitted annotations. We describe the various methods of gene structure curation that have been tried by WormBase and the problems associated with each of them. We also describe the current strategy for gene structure curation, and introduce the WormBase ‘curation tool’, which integrates different data sources in order to identify new and correct gene structures

Ownership and control in a competitive industry

We study a differentiated product market in which an investor initially owns a controlling stake in one of two competing firms and may acquire a non-controlling or a controlling stake in a competitor, either directly using her own assets, or indirectly via the controlled firm. While industry profits are maximized within a symmetric two product monopoly, the investor attains this only in exceptional cases. Instead, she sometimes acquires a noncontrolling stake. Or she invests asymmetrically rather than pursuing a full takeover if she acquires a controlling one. Generally, she invests indirectly if she only wants to affect the product market outcome, and directly if acquiring shares is profitable per se. --differentiated products,separation of ownership and control,private benefits of control

Comparative Functional Analysis of the Caenorhabditis elegans and Drosophila melanogaster Proteomes

The nematode Caenorhabditis elegans is a popular model system in genetics, not least because a majority of human disease genes are conserved in C. elegans. To generate a comprehensive inventory of its expressed proteome, we performed extensive shotgun proteomics and identified more than half of all predicted C. elegans proteins. This allowed us to confirm and extend genome annotations, characterize the role of operons in C. elegans, and semiquantitatively infer abundance levels for thousands of proteins. Furthermore, for the first time to our knowledge, we were able to compare two animal proteomes (C. elegans and Drosophila melanogaster). We found that the abundances of orthologous proteins in metazoans correlate remarkably well, better than protein abundance versus transcript abundance within each organism or transcript abundances across organisms; this suggests that changes in transcript abundance may have been partially offset during evolution by opposing changes in protein abundance

EpiDiP/NanoDiP: a versatile unsupervised machine learning edge computing platform for epigenomic tumour diagnostics.

DNA methylation analysis based on supervised machine learning algorithms with static reference data, allowing diagnostic tumour typing with unprecedented precision, has quickly become a new standard of care. Whereas genome-wide diagnostic methylation profiling is mostly performed on microarrays, an increasing number of institutions additionally employ nanopore sequencing as a faster alternative. In addition, methylation-specific parallel sequencing can generate methylation and genomic copy number data. Given these diverse approaches to methylation profiling, to date, there is no single tool that allows (1) classification and interpretation of microarray, nanopore and parallel sequencing data, (2) direct control of nanopore sequencers, and (3) the integration of microarray-based methylation reference data. Furthermore, no software capable of entirely running in routine diagnostic laboratory environments lacking high-performance computing and network infrastructure exists. To overcome these shortcomings, we present EpiDiP/NanoDiP as an open-source DNA methylation and copy number profiling suite, which has been benchmarked against an established supervised machine learning approach using in-house routine diagnostics data obtained between 2019 and 2021. Running locally on portable, cost- and energy-saving system-on-chip as well as gpGPU-augmented edge computing devices, NanoDiP works in offline mode, ensuring data privacy. It does not require the rigid training data annotation of supervised approaches. Furthermore, NanoDiP is the core of our public, free-of-charge EpiDiP web service which enables comparative methylation data analysis against an extensive reference data collection. We envision this versatile platform as a useful resource not only for neuropathologists and surgical pathologists but also for the tumour epigenetics research community. In daily diagnostic routine, analysis of native, unfixed biopsies by NanoDiP delivers molecular tumour classification in an intraoperative time frame

A subset of pediatric-type thalamic gliomas share a distinct DNA methylation profile, H3K27me3 loss and frequent alteration of EGFR

Background: Malignant astrocytic gliomas in children show a remarkable biological and clinical diversity. Small in-frame insertions or missense mutations in the epidermal growth factor receptor gene (EGFR) have recently been identified in a distinct subset of pediatric-type bithalamic gliomas with a unique DNA methylation pattern. Methods: Here, we investigated an epigenetically homogeneous cohort of malignant gliomas (n = 58) distinct from other subtypes and enriched for pediatric cases and thalamic location, in comparison with this recently identified subtype of pediatric bithalamic gliomas. Results EGFR gene amplification was detected in 16/58 (27%) tumors, and missense mutations or small in-frame insertions in EGFR were found in 20/30 tumors with available sequencing data (67%; 5 of them co-occurring with EGFR amplification). Additionally, 8 of the 30 tumors (27%) harbored an H3.1 or H3.3 K27M mutation (6 of them with a concomitant EGFR alteration). All tumors tested showed loss of H3K27me3 staining, with evidence of overexpression of the EZH inhibitory protein (EZHIP) in the H3 wildtype cases. Although some tumors indeed showed a bithalamic growth pattern, a significant proportion of tumors occurred in the unilateral thalamus or in other (predominantly midline) locations. Conclusions: Our findings present a distinct molecular class of pediatric-type malignant gliomas largely overlapping with the recently reported bithalamic gliomas characterized by EGFR alteration, but additionally showing a broader spectrum of EGFR alterations and tumor localization. Global H3K27me3 loss in this group appears to be mediated by either H3 K27 mutation or EZHIP overexpression. EGFR inhibition may represent a potential therapeutic strategy in these highly aggressive gliomas

Genetic Variation Shapes Protein Networks Mainly through Non-transcriptional Mechanisms

Variation in the levels of co-regulated proteins that function within networks in an outbred yeast population is not driven by variation in the corresponding transcripts