The Gene Curation Coalition: A global effort to harmonize gene-disease evidence resources

PURPOSE: Several groups and resources provide information that pertains to the validity of gene-disease relationships used in genomic medicine and research; however, universal standards and terminologies to define the evidence base for the role of a gene in disease, and a single harmonized resource were lacking. To tackle this issue, the Gene Curation Coalition (GenCC) was formed. METHODS: The GenCC drafted harmonized definitions for differing levels of gene-disease validity based on existing resources, and performed a modified Delphi survey with three rounds to narrow the list of terms. The GenCC also developed a unified database to display curated gene-disease validity assertions from its members. RESULTS: Based on 241 survey responses from the genetics community, a consensus term set was chosen for grading gene-disease validity and database submissions. As of December 2021, the database contains 15,241 gene-disease assertions on 4,569 unique genes from 12 submitters. When comparing submissions to the database from distinct sources, conflicts in assertions of gene-disease validity ranged from 5.3% to 13.4%. CONCLUSION: Terminology standardization, sharing of gene-disease validity classifications, and resolution of curation conflicts will facilitate collaborations across international curation efforts and in turn, improve consistency in genetic testing and variant interpretation.

Identification of evolutionary relationships and DNA markers in the medicinally important genus Fritillaria based on chloroplast genomics

The genus Fritillaria has attracted great attention because of its medicinal and ornamental values. At least three reasons, including the accurate discrimination between various Fritillaria species, protection and sustainable development of rare Fritillaria resources as well as understanding of relationship of some perplexing species, have prompted phylogenetic analyses and development of molecular markers for Fritillaria species. Here we determined the complete chloroplast (CP) genomes for F. unibracteata, F. przewalskii, F. delavayi, and F. sinica through Illumina sequencing, followed by de novo assembly. The lengths of the genomes ranged from 151,076 in F. unibracteata to 152,043 in F. przewalskii. Those CP genomes displayed a typical quadripartite structure, all including a pair of inverted repeats (26,078 to 26,355 bp) separated by the large single-copy (81,383 to 81,804 bp) and small single-copy (17,537 to 17,569 bp) regions. Fritillaria przewalskii, F. delavayi, and F. sinica equivalently encoded 133 unique genes consisting of 38 transfer RNA genes, eight ribosomal RNA genes, and 87 protein coding genes, whereas F. unibracteata contained 132 unique genes due to absence of the rps16 gene. Subsequently, comparative analysis of the complete CP genomes revealed that ycf1, trnL, trnF, ndhD, trnN-trnR, trnE-trnT, trnN, psbM-trnD, atpI, and rps19 to be useful molecular markers in taxonomic studies owning to their interspecies variations. Based on the comprehensive CP genome data collected from 53 species in Fritillaria and Lilium genera, a phylogenomic study was carried out with three Cardiocrinum species and five Amana species as outgroups. The results of the phylogenetic analysis showed that Fritillaria was a sister to Lilium, and the interspecies relationships within subgenus Fritillaria were well resolved. Furthermore, phylogenetic analysis based on the CP genome was proved to be a promising method in selecting potential novel medicinal resources to substitute current medicinal species that are on the verge of extinction.

The identification of gene signatures in patients with extranodal NK/T-cell lymphoma from a pair of twins

Background There is no unified treatment standard for patients with extranodal NK/T-cell lymphoma (ENKTL). Cancer neoantigens are the result of somatic mutations and cancer-specific. Increased number of somatic mutations are associated with anti-cancer effects. Screening out ENKTL-specific neoantigens on the surface of cancer cells relies on the understanding of ENKTL mutation patterns. Hence, it is imperative to identify ENKTL-specific genes for ENKTL diagnosis, the discovery of tumor-specific neoantigens and the development of novel therapeutic strategies. We investigated the gene signatures of ENKTL patients. Methods We collected the peripheral blood of a pair of twins for sequencing to identify unique variant genes. One of the twins is diagnosed with ENKTL. Seventy samples were analyzed by Robust Multi-array Analysis (RMA). Two methods (elastic net and Support Vector Machine-Recursive Feature Elimination) were used to select unique genes. Next, we performed functional enrichment analysis and pathway enrichment analysis. Then, we conducted single-sample gene set enrichment analysis of immune infiltration and validated the expression of the screened markers with limma packages. Results We screened out 126 unique variant genes. Among them, 11 unique genes were selected by the combination of elastic net and Support Vector Machine-Recursive Feature Elimination. Subsequently, GO and KEGG analysis indicated the biological function of identified unique genes. GSEA indicated five immunity-related pathways with high signature scores. In patients with ENKTL and the group with high signature scores, a proportion of functional immune cells are all of great infiltration. We finally found that CDC27, ZNF141, FCGR2C and NES were four significantly differential genes in ENKTL patients. ZNF141, FCGR2C and NES were upregulated in patients with ENKTL, while CDC27 was significantly downregulated. Conclusion We identified four ENKTL markers (ZNF141, FCGR2C, NES and CDC27) in patients with extranodal NK/T-cell lymphoma.

RNA-seq driven expression and enrichment analysis to investigate CVD genes with associated phenotypes among high-risk heart failure patients

Background Heart failure (HF) is one of the most common complications of cardiovascular diseases (CVDs) and among the leading causes of death in the US. Many other CVDs can lead to increased mortality as well. Investigating the genetic epidemiology and susceptibility to CVDs is a central focus of cardiology and biomedical life sciences. Several studies have explored expression of key CVD genes specially in HF, yet new targets and biomarkers for early diagnosis are still missing to support personalized treatment. Lack of gender-specific cardiac biomarker thresholds in men and women may be the reason for CVD underdiagnosis in women, and potentially increased morbidity and mortality as a result, or conversely, an overdiagnosis in men. In this context, it is important to analyze the expression and enrichment of genes with associated phenotypes and disease-causing variants among high-risk CVD populations. Methods We performed RNA sequencing focusing on key CVD genes with a great number of genetic associations to HF. Peripheral blood samples were collected from a broad age range of adult male and female CVD patients. These patients were clinically diagnosed with CVDs and CMS/HCC HF, as well as including cardiomyopathy, hypertension, obesity, diabetes, asthma, high cholesterol, hernia, chronic kidney, joint pain, dizziness and giddiness, osteopenia of multiple sites, chest pain, osteoarthritis, and other diseases. Results We report RNA-seq driven case–control study to analyze patterns of expression in genes and differentiating the pathways, which differ between healthy and diseased patients. Our in-depth gene expression and enrichment analysis of RNA-seq data from patients with mostly HF and other CVDs on differentially expressed genes and CVD annotated genes revealed 4,885 differentially expressed genes (DEGs) and regulation of 41 genes known for HF and 23 genes related to other CVDs, with 15 DEGs as significantly expressed including four genes already known (FLNA, CST3, LGALS3, and HBA1) for HF and CVDs with the enrichment of many pathways. Furthermore, gender and ethnic group specific analysis showed shared and unique genes between the genders, and among different races. Broadening the scope of the results in clinical settings, we have linked the CVD genes with ICD codes. Conclusions Many pathways were found to be enriched, and gender-specific analysis showed shared and unique genes between the genders. Additional testing of these genes may lead to the development of new clinical tools to improve diagnosis and prognosis of CVD patients.

Common Gene Expression Signature of B-Cells of Waldenström Macroglobulinemia (WM) and IgM Monoclonal Gammopathies of Undetermined Significance (IgM MGUS) Compared to Healthy Subjects

We performed a comparative gene expression profiling (GEP) study on B-cells and plasma cells of Waldenström Macroglobulinemia (WM), IgM monoclonal gammopathies of undetermined significance (IgMMGUS), and normal individuals (CTRLs) to identify GEP changes as reliable predictors of progression of IgMMGUS to WM. We analyzed bone marrow B-cells and plasma cells from 36 WM patients, 13 IgMMGUS subjects, and 7 CTRLs by Affymetrix microarray, respectively (Table 1). GEP experiments were performed on the CD19+ and CD138+ cells using GeneChip-HGU133 Plus 2.0. Data were preprocessed and normalized by Robust Multi-Array Average and ComBat. Selection of the different expressed genes was performed separately for CD19+ and CD138+ cells, using Significance Analysis of Microarrays (SAM) on the 3 groups and a false discovery rate threshold of 5%, followed, for significance comparisons, by a pair-wise SAM test corrected for multiple testing. We focused on the comparison of the CD19+ cells of WM vs. IgMMGUS vs. CTRLs which highlighted 2038 unique genes whereas the same comparison of the CD138+ cells determined 29 unique genes (Trojani et.al. Cancers 2021). Among the 2038 DEGs, 115 genes were grouped in KEGG pathways involved in Wnt-signaling, BCR-signaling, calcium signaling, hematopoietic cell antigens, cell adhesion, adherens junctions, coagulation cascade, platelet activation, cytokine receptor, and signaling pathways responsible for cell cycle, apoptosis, and survival. Interestingly, most of the 115 DEGs in B-cells were different expressed in WM vs. IgMMGUS and CTRLs. Only 9/115 DEGs were significantly different expressed in WM vs. CTRLs and in IgMMGUS vs. CTRLs, but no significant expression changes were noted between WM and IgMMGUS (Table 2). To further inspect the similarities and the differences among WM and IgMMGUS, we computed the Euclidean pair-wise distance between subjects and, using this distance as weight, constructed a minimum spanning tree (MST) (Figure 1). Considerably, four probesets identified ADRB2 (transmembrane Beta adrenergic receptor) which was up regulated in WM and IgMMGUS compared to CTRLs. The over expression of ADRB2 was also demonstrated in Mantle Cell Lymphoma cell lines and in Diffuse large B-cell lymphoma (DLBCL) lymphocytes compared to normal B-cells (doi10.1016/j.cellsig.2017.08.002), and in most malignancies (doi10.1007/s11033-021-06250-y) . As far as we know, ADAM23 (ADAM Metallopeptidase Domain23) has not been found in WM, whereas we suggest its possible role in WM patients with Sjogren's syndrome (SS). ADAM23 plays a role in the peripheral neuropathy by controlling the activity of potassium channels in SS (doi10.1007/s10067-016-3499-z). Some authors found that sensory/motor neuropathies were associated with MGUS patients (doi10.1017/s0317167100011483). We strongly believe that the down regulation of ADAM23 in WM and IgMMGUS has a good chance to be associated with clinical neuropathy in WM and IgMMGUS. RASGRP3 (RAS Guanyl Releasing Protein3) and PIK3AP1 (Phosphoinositide 3 Kinase Adaptor Protein1) play crucial roles in BCR signaling pathway: PIK3AP1 activates the PI3K-Akt signaling while RASGRP3 stimulates MAPK signaling pathway. The deregulation of LEF1 (Lymphoid Enhancer Binding Factor1) and genes of Wnt-pathway were previously demonstrated in B-cell disorders and multiple myeloma (doi10.1007/s00277-017-3207-3, doi10.1016/j.pathol.2019.09.009). According to these studies, we showed the under expression of LEF1 in WM and IgMMGUS compared to CTRLs. We identified the down regulation of EZH2 (Enhancer Of Zeste2 Polycomb Repressive Complex2Subunit) in WM and IgMMGUS compared to CTRLs. EZH2 is involved in Follicular lymphoma and DLBCL (doi10.1080/2162402X.2017.1321184). CDHR3 (Cadherin Related Family Member3), CHEK1 (Checkpoint Kinase1), and HIST1H1B (Histone-H1.5) were over expressed in CTRLs compared to IgMMGUS and WM. In conclusion, the common gene-set in WM and IgMMGUS could suggest two-hit hypothesis. First, the gene-set could play a role in the risk of progression of IgMMGUS to WM. Until now, all the IgMMGUS subjects have not been transformed in WM or other NHL, but they have been monitored every 6 months, and their possible transformation to lymphoma could highlight new insights. The second hypothesis suggests their involvement in the biological processes of leukemogenesis in WM and IgMMGUS which will be further investigated. Figure 1 Figure 1. Disclosures Tedeschi: AbbVie: Honoraria, Speakers Bureau; AstraZeneca: Honoraria, Speakers Bureau; Beigene: Honoraria, Speakers Bureau; Janssen: Honoraria, Speakers Bureau.

Diagnostic testing laboratories are valuable partners for disease gene discovery: 5-year experience with GeneMatcher

Clinical and research laboratories extensively use exome sequencing due to its high diagnostic rates, cost savings, impact on clinical management, and efficacy for disease gene discovery. While the rates of disease gene discovery have steadily increased, only ~16% of genes in the genome have confirmed disease associations. Here we describe our diagnostic laboratory’s disease gene discovery and ongoing data-sharing efforts with GeneMatcher. In total, we submitted 246 candidates from 243 unique genes to GeneMatcher, of which 45.93% are now clinically characterized. Submissions with at least one case meeting our candidate genes reporting criteria were significantly more likely to be characterized as of October 2021 compared to genes with no candidates meeting our reporting criteria (p=0.025). We reported relevant findings related to these gene-disease associations for 480 probands. In 219 (45.63%) instances, these results were reclassifications after an initial candidate gene (uncertain) or negative report. Since 2013, we have co-authored 105 publications focused on delineating gene-disease associations. Diagnostic laboratories are pivotal for disease gene discovery efforts and can screen phenotypes based on genotype matches, contact clinicians of relevant cases, and issue proactive reclassification reports. GeneMatcher is a critical resource in these efforts.

Genome of Serratia plymuthica UBCF_13, Insight into diverse unique traits

Background: Whole genome sequencing is become an essential tool to explore potential of microorganism and evolutionary study. The Serratia plymuthica UBCF_13 is one of phylloplane associated plant bacteria showing antifungal activity. For that reason, its complete genome information is necessary to enhance its potential as biocontrol against plant pathogenic fungal. Here, we report the genome sequence of Serratia plymuthica UBCF_13 to understand the molecular mechanism regarding its biocontrol ability. Methods: Continuous short reads were attained from Illumina sequencing runs and reads 150 bp were merged into a single dataset. Pan-genome based method was used to identify core-genome of S. plymuthica species and unique gene in UBCF_13. Results: Assambled Illumina reads of S. plymuthica strain UBCF_13 genome was produced a 5.46 Mb circular genome sequence. It was found 3321 genes belong to the core-genome sheared by the 18 strains evaluated. The UBCF_13 genome harbor 485 unique genes, where 300 of them only can be found in this strain Conclusions: The sequence of UBCF_13 genome sequence data will contribute for further exploration of the potential of S. plymuthica UBCF_13 as bacteria producing antibiotic.

Contribution of Environmental Constituents in the Genomic Disruption of Cytokeratins

Cytokeratins are keratinous protein and assist cells to reduce mechanical stress on the intracytoplasmic layer of epithelial tissue. There are several unspecified mutations in the epithelial layer that may induces by environmental mutagens and pathogens. The unspecified mutations in the epithelium surface also disrupt biology of skin at multiple different levels and cause innate keratinizing disorders. These serve as a root generator of neurohormones and neuropeptides which mainly partake in the disruption. Generally, all 54 unique genes of human keratin partake in mutations and cause cutaneous tissue fragility, skin hypertrophic, and malignant transformation. In this chapter, unspecific factors that involved in the pathogenesis of skin diseases and the ways by which such keratin changes might harness to alleviate different skin conditions are also included. Consequently, the contribution of environmental changes in the frontier of mutations or misregulations of the cytokeratin genes, is also cited here.

Lifespan-Associated Gene Expression Signatures of Recombinant BXD Mice Implicates Coro7 and Set in Longevity

Although genetic approaches have identified key genes and pathways that promote longevity, systems-level approaches are less utilized. Here, we took advantage of the wealth of omics data characterizing the BXD family of mice. We associated transcript and peptide levels across five tissues from both female and male BXD isogenic lines with their median lifespan. We identified over 5000 genes that showed a longevity correlation in a given tissue. Surprisingly, we found less than 1% overlap among longevity-correlating genes across tissues and sex. These 1% shared genes consist of 51 genes, of which 13 have been shown to alter lifespan. Only two genes -Coro7 and Set- showed a longevity correlation in all tissues and in both sexes. While differential regulation of aging across tissues and sex has been reported, our systems-level analysis reveals two unique genes that may promote healthy aging in unique sex- and tissue-agnostic manner.

Analysis of merged whole blood transcriptomic datasets to identify circulating molecular biomarkers of feed efficiency in growing pigs

Background Improving feed efficiency (FE) is an important goal due to its economic and environmental significance for farm animal production. The FE phenotype is complex and based on the measurements of the individual feed consumption and average daily gain during a test period, which is costly and time-consuming. The identification of reliable predictors of FE is a strategy to reduce phenotyping efforts. Results Gene expression data of the whole blood from three independent experiments were combined and analyzed by machine learning algorithms to propose molecular biomarkers of FE traits in growing pigs. These datasets included Large White pigs from two lines divergently selected for residual feed intake (RFI), a measure of net FE, and in which individual feed conversion ratio (FCR) and blood microarray data were available. Merging the three datasets allowed considering FCR values (Mean = 2.85; Min = 1.92; Max = 5.00) for a total of n = 148 pigs, with a large range of body weight (15 to 115 kg) and different test period duration (2 to 9 weeks). Random forest (RF) and gradient tree boosting (GTB) were applied on the whole blood transcripts (26,687 annotated molecular probes) to identify the most important variables for binary classification on RFI groups and a quantitative prediction of FCR, respectively. The dataset was split into learning (n = 74) and validation sets (n = 74). With iterative steps for variable selection, about three hundred’s (328 to 391) molecular probes participating in various biological pathways, were identified as important predictors of RFI or FCR. With the GTB algorithm, simpler models were proposed combining 34 expressed unique genes to classify pigs into RFI groups (100% of success), and 25 expressed unique genes to predict FCR values (R2 = 0.80, RMSE = 8%). The accuracy performance of RF models was slightly lower in classification and markedly lower in regression. Conclusion From small subsets of genes expressed in the whole blood, it is possible to predict the binary class and the individual value of feed efficiency. These predictive models offer good perspectives to identify animals with higher feed efficiency in precision farming applications.