Annotation Pipeline Research Articles

FA-nf: A Functional Annotation Pipeline for Proteins from Non-Model Organisms Implemented in Nextflow

Functional annotation allows adding biologically relevant information to predicted features in genomic sequences, and it is, therefore, an important procedure of any de novo genome sequencing project. It is also useful for proofreading and improving gene structural annotation. Here, we introduce FA-nf, a pipeline implemented in Nextflow, a versatile computational workflow management engine. The pipeline integrates different annotation approaches, such as NCBI BLAST+, DIAMOND, InterProScan, and KEGG. It starts from a protein sequence FASTA file and, optionally, a structural annotation file in GFF format, and produces several files, such as GO assignments, output summaries of the abovementioned programs and final annotation reports. The pipeline can be broken easily into smaller processes for the purpose of parallelization and easily deployed in a Linux computational environment, thanks to software containerization, thus helping to ensure full reproducibility.

Converting Biomedical Text Annotated Resources into FAIR Research Objects with an Open Science Platform

Today, there are excellent resources for the semantic annotation of biomedical text. These resources span from ontologies, tools for NLP, annotators, and web services. Most of these are available either in the form of open source components (i.e., MetaMap) or as web services that offer free access (i.e., Whatizit). In order to use these resources in automatic text annotation pipelines, researchers face significant technical challenges. For open-source tools, the challenges include the setting up of the computational environment, the resolution of dependencies, as well as the compilation and installation of the software. For web services, the challenge is implementing clients to undertake communication with the respective web APIs. Even resources that are available as Docker containers (i.e., NCBO annotator) require significant technical skills for installation and setup. This work deals with the task of creating ready-to-install and run Research Objects (ROs) for a large collection of components in biomedical text analysis. These components include (a) tools such as cTAKES, NOBLE Coder, MetaMap, NCBO annotator, BeCAS, and Neji; (b) ontologies from BioPortal, NCBI BioSystems, and Open Biomedical Ontologies; and (c) text corpora such as BC4GO, Mantra Gold Standard Corpus, and the COVID-19 Open Research Dataset. We make these resources available in OpenBio.eu, an open-science RO repository and workflow management system. All ROs can be searched, shared, edited, downloaded, commented on, and rated. We also demonstrate how one can easily connect these ROs to form a large variety of text annotation pipelines.

De novo whole-genome assembly of Chrysanthemum makinoi, a key wild chrysanthemum.

Chrysanthemum is among the top 10 cut, potted, and perennial garden flowers in the world. Despite this, to date, only the genomes of two wild diploid chrysanthemums have been sequenced and assembled. Here, we present the most complete and contiguous chrysanthemum de novo assembly published so far, as well as a corresponding ab initio annotation. The cultivated hexaploid varieties are thought to originate from a hybrid of wild chrysanthemums, among which the diploid Chrysanthemum makinoi has been mentioned. Using a combination of Oxford Nanopore long reads, Pacific Biosciences long reads, Illumina short reads, Dovetail sequences, and a genetic map, we assembled 3.1 Gb of its sequence into nine pseudochromosomes, with an N50 of 330 Mb and a BUSCO complete score of 92.1%. Our ab initio annotation pipeline predicted 95,074 genes and marked 80.0% of the genome as repetitive. This genome assembly of C. makinoi provides an important step forward in understanding the chrysanthemum genome, evolution, and history.

Genomic and phylogenetic analysis of a multidrug-resistant mcr-1-carrying Klebsiella pneumoniae recovered from a urinary tract infection in China

The emergence and dissemination of colistin-resistant Enterobacterales has become a major global public-health threat. Here we investigated the genomic and phylogenetic characteristics of a multidrug-resistant Klebsiella pneumoniae strain (KP4823) carrying the mcr-1 gene recovered from a urinary tract infection in China. Antimicrobial susceptibility of K. pneumoniae KP4823 was determined by broth microdilution. Whole genomic DNA was extracted and sequenced using Oxford Nanopore MinION and Illumina NovaSeq 6000 platforms. Hybrid assembly with long and short reads was performed using Unicycler, and the genome was annotated using the NCBI Prokaryotic Genome Annotation Pipeline (PGAP). The sequence type (ST), capsular type, and antimicrobial resistance and virulence genes were identified from the genome sequence. Core genome multilocus sequence typing (cgMLST) analysis was performed by BacWGSTdb 2.0 server. Klebsiella pneumoniae KP4823 was resistant to colistin, ceftazidime, cefepime, cefotaxime, fosfomycin and aztreonam. The complete genome sequence of KP4823 consists of five contigs comprising 5 445 519 bp, including one chromosome and four plasmids. The isolate was assigned to ST101 with capsular serotype KL106. Several antimicrobial resistance genes were identified, including the colistin resistance gene mcr-1, which was located on a 34 685-bp IncX4 plasmid. The closest relative of K. pneumoniae KP4823 was another ST101 isolate (08EU827) recovered from Sweden in 2008, which differed by 191 cgMLST loci. Our study reports the genome sequence of a multidrug-resistant mcr-1-carrying K. pneumoniae in China. These data may help to understand the antimicrobial resistance mechanisms, genomic features and transmission dynamics of colistin resistance in clinical settings.

P-063: Pathogenic germline variants in hereditary cancer genes in patients with Multiple Myeloma

<h3>Background</h3> GWAS have identified common SNPs & rare high-penetrance variants that explain ~16% of the estimated heritability of multiple myeloma (MM)(PMID 30213928). Pathogenic/likely-pathogenic germline variants (PGV) in hereditary cancer genes (HCG) are common in adult cancer pts (~8%), but prevalence in MM is not known. The aim of our study is to investigate the occurrence of PGV in newly-diagnosed MM (NDMM) and describe clinical characteristics & outcomes of carriers. <h3>Methods</h3> We analyzed MMRF CoMMpass data & identified 895 NDMM pts with whole-exome sequencing of germline DNA. We used the clinical annotation pipeline from Sema4, a CLIA/CAP certified genetic testing laboratory, to identify pts with PGV according to ACMG variant classification guidelines. We compared clinical characteristics & disease phenotypes of PGV carriers vs non-carriers. We used Chi-Square and Fisher's Exact tests to assess statistical significance. <h3>Results</h3> We identified 83 PGV in 31 distinct HCG in 79 (8.8%) of 895 NDMM pts (83% European ancestry). Most PGV involved DNA damage repair (DDR) genes (78%), & homologous recombination (HR) genes were the most commonly mutated (34%). PGV in CHEK2 were most common (n=10,1.1% of all MM pts). 2 pts carried PGV in TP53, & 6 pts had mismatch repair (MMR) gene defects (1:149). MM pts with family history (FH) of hematologic malignancy (HM) in a 1st or 2nd-degree relative were more likely to carry PGV (22 vs 7.6%,OR=3.3,p<0.001), an association that remained significant in multivariate analysis (MVA) (OR=4.1,p<0.001). CHEK2 variants were leading drivers of this correlation (OR 18,adjusted p<0.01), & especially protein-truncating founder variant c.1100delC. Likelihood of MM dx before age 40 was significantly higher in PGV carriers (6.3 vs 1.8%,OR=3.7,p=0.025). 25% of those <40y/o carried PGV, but none of these were in DDR-HR genes, a notable difference with other age groups (0 vs 41%,p=0.02). 2/6 MMR PGV were detected in pts <40y/o. In univariate analysis, DDR-PGV carriers had a significant PFS1 advantage (median 52 vs 35 months,p=0.008) & a non-significant OS advantage (p=0.08). PFS1 difference remained significant in MVA adjusting for age, ISS stage, high-risk cytogenetics, treatment type & transplant status (OR 0.65,95% CI 0.44-0.97,p=0.03). <h3>Conclusions</h3> PGV in HCG were common (8.8%) in this large cohort of NDMM pts of predominantly European ancestry, especially in those with FH of HM (1:4, with high prevalence of CHEK2 variants), and in those <40y/o (1:4). Routine screening in high-prevalence subgroups may be warranted, as carriers can benefit from counseling & enrollment in early cancer detection programs. We observed a clinically & statistically significant PFS1 advantage in PGV carriers, possibly due to increased sensitivity to MM therapies, a well-described phenomenon in other cancers (PMID 33158305). Prospective validation of these findings is needed to better understand prognostic & therapeutic implications of PGV in MM.

Genome assembly and annotation of the tambaqui (Colossoma macropomum): an emblematic fish of the Amazon River Basin.

Colossoma macropomum, known as "tambaqui", is the largest Characiformes fish in the Amazon River Basin and a leading species in Brazilian aquaculture and fisheries. Good quality meat and excellent adaptability to culture systems are some of its remarkable farming features. To support studies into the genetics and genomics of the tambaqui, we have produced the first high-quality genome for the species. We combined Illumina and PacBio sequencing technologies to generate a reference genome, assembled with 39× coverage of long reads and polished to a consensus quality value (QV) of 36 with 130× coverage of short reads. The genome was assembled into 1269 scaffolds (a total of 1,221,847,006 bases), with a scaffold N50 size of 40Mb, where 93% of all assembled bases were placed in the largest 54 scaffolds corresponding to the diploid karyotype of the tambaqui. Furthermore, the NCBI Annotation Pipeline annotated genes, pseudogenes, and non-coding transcripts using the RefSeq database as evidence, guaranteeing a high-quality annotation. A Genome Data Viewer for the tambaqui was produced, which will benefit groups interested in exploring the unique genomic features of the species. The availability of a highly accurate genome assembly for tambaqui provides the foundation for the discovery of novel ecological and evolutionary insights, and is a helpful resource for aquaculture.

SRCP: a comprehensive pipeline for accurate annotation and quantification of circRNAs

Here we describe a new integrative approach for accurate annotation and quantification of circRNAs named Short Read circRNA Pipeline (SRCP). Our strategy involves two steps: annotation of validated circRNAs followed by a quantification step. We show that SRCP is more sensitive than other individual pipelines and allows for more comprehensive quantification of a larger number of differentially expressed circRNAs. To facilitate the use of SRCP, we generate a comprehensive collection of validated circRNAs in five different organisms, including humans. We then utilize our approach and identify a subset of circRNAs bound to the miRNA-effector protein AGO2 in human brain samples.

Metagenomic Insights Into the Microbial Iron Cycle of Subseafloor Habitats

Microbial iron cycling influences the flux of major nutrients in the environment (e.g., through the adsorptive capacity of iron oxides) and includes biotically induced iron oxidation and reduction processes. The ecological extent of microbial iron cycling is not well understood, even with increased sequencing efforts, in part due to limitations in gene annotation pipelines and limitations in experimental studies linking phenotype to genotype. This is particularly true for the marine subseafloor, which remains undersampled, but represents the largest contiguous habitat on Earth. To address this limitation, we used FeGenie, a database and bioinformatics tool that identifies microbial iron cycling genes and enables the development of testable hypotheses on the biogeochemical cycling of iron. Herein, we survey the microbial iron cycle in diverse subseafloor habitats, including sediment-buried crustal aquifers, as well as surficial and deep sediments. We inferred the genetic potential for iron redox cycling in 32 of the 46 metagenomes included in our analysis, demonstrating the prevalence of these activities across underexplored subseafloor ecosystems. We show that while some processes (e.g., iron uptake and storage, siderophore transport potential, and iron gene regulation) are near-universal, others (e.g., iron reduction/oxidation, siderophore synthesis, and magnetosome formation) are dependent on local redox and nutrient status. Additionally, we detected niche-specific differences in strategies used for dissimilatory iron reduction, suggesting that geochemical constraints likely play an important role in dictating the dominant mechanisms for iron cycling. Overall, our survey advances the known distribution, magnitude, and potential ecological impact of microbe-mediated iron cycling and utilization in sub-benthic ecosystems.

Characterisation of blaNDM-5 and blaKPC-2 co-occurrence in K64-ST11 carbapenem-resistant Klebsiella pneumoniae

The aim of this study was to characterise the co-occurrence of blaKPC and blaNDM in a K64-ST11 carbapenem-resistant Klebsiella pneumoniae strain. Antimicrobial susceptibility was determined by the disk diffusion method. Whole-genome sequencing was performed using Illumina MiSeq and PacBio II sequencers. High-quality reads were de novo assembled using the SOAPdenovo package. Genome annotation was performed using the NCBI Prokaryotic Genome Annotation Pipeline (PGAP), and genome characteristics were analysed using bioinformatics methods. Klebsiella pneumoniae strain KPWX136 was resistant to most of the tested antibiotics, being susceptible only to polymyxin B and tigecycline. The genome of strain KPWX136 is composed of a single chromosome (5 473 976 bp) and six plasmids including pA (191 359 bp), pB (134 972 bp), pC (117 844 bp), pD (87 095 bp), pE (11 970 bp) and pF (5596 bp). Complete sequence analysis revealed the resistome of isolate KPWX136, which included blaKPC-2 and blaNDM-5 together with 23 other resistance genes, of which 6 resistance genes were located on the chromosome and 19 on plasmids. Virulome analysis showed that KPWX136 carried a large number of virulence-associated genes. Meanwhile, 26 genomic islands and 6 prophages were predicted within the genome. Genetic characterisation of K. pneumoniae KPWX136 co-harbouring blaNDM-5 and blaKPC-2 showed that it carried not only 25 resistance genes and a large number virulence factors but also various mobile genetic elements (MGEs) such as plasmids and genomic islands. Therefore, we must be alert to the transmission of resistance genes and virulence determinants via MGEs.

Comparison of High-Resolution Fourier Transform Mass Spectrometry Platforms for Putative Metabolite Annotation.

Fourier transform ion cyclotron resonance (FT-ICR) and Orbitrap mass spectrometry (MS) are among the highest-performing analytical platforms used in metabolomics. Non-targeted metabolomics experiments, however, yield extremely complex datasets that make metabolite annotation very challenging and sometimes impossible. The high-resolution accurate mass measurements of the leading MS platforms greatly facilitate this process by reducing mass errors and spectral overlaps. When high resolution is combined with relative isotopic abundance (RIA) measurements, heuristic rules, and constraints during searches, the number of candidate elemental formula(s) can be significantly reduced. Here, we evaluate the performance of Orbitrap ID-X and 12T solariX FT-ICR mass spectrometers in terms of mass accuracy and RIA measurements and how these factors affect the assignment of the correct elemental formulas in the metabolite annotation pipeline. Quality of the mass measurements was evaluated under various experimental conditions (resolution: 120, 240, 500 K; automatic gain control: 5 × 104, 1 × 105, 5 × 105) for the Orbitrap MS platform. High average mass accuracy (<1 ppm for UPLC-Orbitrap MS and <0.2 ppm for direct infusion FT-ICR MS) was achieved and allowed the assignment of correct elemental formulas for over 90% (m/z 75-466) of the 104 investigated metabolites. 13C1 and 18O1 RIA measurements further improved annotation certainty by reducing the number of candidates. Overall, our study provides a systematic evaluation for two leading Fourier transform (FT)-based MS platforms utilized in metabolite annotation and provides the basis for applying these, individually or in combination, to metabolomics studies of biological systems.

Workflows for Rapid Functional Annotation of Diverse Arthropod Genomes.

Simple SummaryGenomic technologies are accumulating information about genes faster than ever before, and sequencing initiatives, such as the Earth BioGenome Project, i5k, and Ag100Pest Initiative, are expected to increase this rate of acquisition. However, if genomic sequencing is to be used for the improvement of human health, agriculture, and our understanding of biological systems, it is necessary to identify genes and understand how they contribute to biological outcomes. While there are several well-established workflows for assembling genomic sequences and identifying genes, understanding gene function is essential to create actionable knowledge. Moreover, this functional annotation process must be easily accessible and provide information at a genomic scale to keep up with new sequence data. We report a well-defined workflow for rapid functional annotation of whole proteomes to produce Gene Ontology and pathways information. We test this workflow on a diverse set of arthropod genomes and compare it to common arthropod reference genomes. The workflow we described is freely and publicly available via a web interface on CyVerse or as biocontainers that can be deployed scalably on local computing systems.Genome sequencing of a diverse array of arthropod genomes is already underway, and these genomes will be used to study human health, agriculture, biodiversity, and ecology. These new genomes are intended to serve as community resources and provide the foundational information required to apply ‘omics technologies to a more diverse set of species. However, biologists require genome annotation to use these genomes and derive a better understanding of complex biological systems. Genome annotation incorporates two related, but distinct, processes: Demarcating genes and other elements present in genome sequences (structural annotation); and associating a function with genetic elements (functional annotation). While there are well-established and freely available workflows for structural annotation of gene identification in newly assembled genomes, workflows for providing the functional annotation required to support functional genomics studies are less well understood. Genome-scale functional annotation is required for functional modeling (enrichment, networks, etc.). A first-pass genome-wide functional annotation effort can rapidly identify under-represented gene sets for focused community annotation efforts. We present an open-source, open access, and containerized pipeline for genome-scale functional annotation of insect proteomes and apply it to various arthropod species. We show that the performance of the predictions is consistent across a set of arthropod genomes with varying assembly and annotation quality.

The Arabidopsis PeptideAtlas: Harnessing worldwide proteomics data to create a comprehensive community proteomics resource

We developed a resource, the Arabidopsis PeptideAtlas (www.peptideatlas.org/builds/arabidopsis/), to solve central questions about the Arabidopsis thaliana proteome, such as the significance of protein splice forms and post-translational modifications (PTMs), or simply to obtain reliable information about specific proteins. PeptideAtlas is based on published mass spectrometry (MS) data collected through ProteomeXchange and reanalyzed through a uniform processing and metadata annotation pipeline. All matched MS-derived peptide data are linked to spectral, technical, and biological metadata. Nearly 40 million out of ∼143 million MS/MS (tandem MS) spectra were matched to the reference genome Araport11, identifying ∼0.5 million unique peptides and 17,858 uniquely identified proteins (only isoform per gene) at the highest confidence level (false discovery rate 0.0004; 2 non-nested peptides ≥9 amino acid each), assigned canonical proteins, and 3,543 lower-confidence proteins. Physicochemical protein properties were evaluated for targeted identification of unobserved proteins. Additional proteins and isoforms currently not in Araport11 were identified that were generated from pseudogenes, alternative start, stops, and/or splice variants, and small Open Reading Frames; these features should be considered when updating the Arabidopsis genome. Phosphorylation can be inspected through a sophisticated PTM viewer. PeptideAtlas is integrated with community resources including TAIR, tracks in JBrowse, PPDB, and UniProtKB. Subsequent PeptideAtlas builds will incorporate millions more MS/MS data.

Diversity in the composition of the accessory genome of Mexican Pseudomonas aeruginosa strains.

Pseudomonas aeruginosa is an important opportunistic pathogen especially in nosocomial infections due to its easy adaptation to different environments; this characteristic is due to the great genetic diversity that presents its genome. In addition, it is considered a pathogen of critical priority due to the high antimicrobial resistance. The aim of this study was to characterize the mobile genetic elements present in the chromosome of six Mexican P. aeruginosa strains isolated from adults with pneumonia and children with bacteremia. The genomic DNA of six P. aeruginosa strains were isolated and sequenced using PacBio RS-II platform. They were annotated using Prokaryotic Genome Annotation Pipeline and manually curated and analyzed for the presence of mobile genetic elements, antibiotic resistances genes, efflux pumps and virulence factors using several bioinformatics programs and databases. The global analysis of the strains chromosomes showed a novel chromosomal rearrangement in two strains, possibly mediated by subsequent recombination and inversion events. They have a high content of mobile genetic elements: 21 genomic islands, four new islets, four different integrative conjugative elements, 28 different prophages, one CRISPR-Cas arrangements, and one class 1 integron. The acquisition of antimicrobials resistance genes into these elements are in concordance with their phenotype of multi-drug resistance. The accessory genome increased the ability of the strains to adapt or survive to the hospital environment, promote genomic plasticity and chromosomal rearrangements, which may affect the expression or functionality of the gene and might influence the clinical outcome, having an impact on the treatment.

Transcriptome annotation in the cloud: complexity, best practices and cost

BACKGROUND The NIH Science and Technology Research Infrastructure for Discovery, Experimentation, and Sustainability (STRIDES) initiative provides NIH-funded researchers cost-effective access to commercial cloud providers, such as Amazon Web Services (AWS) and Google Cloud Platform (GCP). These cloud providers represent an alternative for the execution of large computational biology experiments like transcriptome annotation, which is a complex analytical process that requires the interrogation of multiple biological databases with several advanced computational tools. The core components of annotation pipelines published since 2012 are BLAST sequence alignments using annotated databases of both nucleotide or protein sequences almost exclusively with networked on-premises compute systems. FINDINGS We compare multiple BLAST sequence alignments using AWS and GCP. We prepared several Jupyter Notebooks with all the code required to submit computing jobs to the batch system on each cloud provider. We consider the consequence of the number of query transcripts in input files and the effect on cost and processing time. We tested compute instances with 16, 32, and 64 vCPUs on each cloud provider. Four classes of timing results were collected: the total run time, the time for transferring the BLAST databases to the instance local solid-state disk drive, the time to execute the CWL script, and the time for the creation, set-up, and release of an instance. This study aims to establish an estimate of the cost and compute time needed for the execution of multiple BLAST runs in a cloud environment. CONCLUSIONS We demonstrate that public cloud providers are a practical alternative for the execution of advanced computational biology experiments at low cost. Using our cloud recipes, the BLAST alignments required to annotate a transcriptome with ∼500,000 transcripts can be processed in <2 hours with a compute cost of ∼$200-$250. In our opinion, for BLAST-based workflows, the choice of cloud platform is not dependent on the workflow but, rather, on the specific details and requirements of the cloud provider. These choices include the accessibility for institutional use, the technical knowledge required for effective use of the platform services, and the availability of open source frameworks such as APIs to deploy the workflow.

Genomic characterisation of multidrug-resistant Bacillus toyonensis strain 4HC1 isolated from marine plastic in Norway

Bacillus toyonensis is widespread in nature. Multidrug-resistant B. toyonensis strain 4HC1 was isolated from polyethylene submerged in the water column near a beach in Øygarden, Norway. We analysed the whole genome sequence of strain 4HC1 in order to understand the genetic basis of the observed phenotypic antibiotic resistance. Whole-genome sequencing of B. toyonensis strain 4HC1 was performed on Illumina MiSeq platform using 2×300 bp chemistry. The genome sequence was assembled using SPAdes v.3.13.0 and was annotated using the NCBI Prokaryotic Genome Annotation Pipeline (PGAP). The draft genome of strain 4HC1 is 6 156 259 bp (133 contigs) in size with a GC content of 34.95%. The genome comprises 6089 protein-coding genes, 86 tRNAs and 24 rRNAs. Strain 4HC1 is resistant to cefotaxime, trimethoprim and ampicillin and carries various antibiotic resistance genes (ARGs), including several β-lactamases, aminoglycoside 6-adenylyltransferase, a TetM family tetracycline resistance gene, two different tetracycline efflux pumps, and a bleomycin resistance gene. Several virulence genes including genes involved in immune evasion, iron acquisition and toxins were also detected in strain 4HC1. The draft genome sequence of B. toyonensis strain 4HC1 released here shows the presence of various ARGs and virulence genes in a multidrug-resistant strain isolated from marine plastic.

Genomic analysis of Leuconostoc citreum TR116 with metabolic reconstruction and the effects of fructose on gene expression for mannitol production

The species Leuconostoc citreum is often isolated from grain and vegetable fermentations such as sourdough, sauerkraut and kimchi. Lc. citreum has seen an increase in its use as a starter culture for various fermentations and food applications. The strain Lc. citreum TR116 has been applied previously in this laboratory aimed at sugar depletion through metabolism resulting in the reduction of fructose to mannitol, a polyol considered as a sweet carbohydrate. Besides reducing sugar, TR116 showed flavour modulating characteristics and contributes to the extension of microbial shelf life. In order to obtain a better understanding of this strain and to fully use its set of abilities, the genome of Lc. citreum TR116 was sequenced using the Illumina MiSeq, assembly with SPAdes and annotated by the Prokaryotic Genome Annotation Pipeline. Metabolic reconstruction was employed to elucidate carbohydrate, organic acid and amino acid metabolism in the strain. Of particular interest was the gene expression analysis ascertained the influence of fructose on the genes mdh and manX involved in the uptake of fructose and its conversion to mannitol. This investigation, the first in Lc. citreum, illustrates the metabolic processes involved in fermentation used by this strain and demonstrates that in the presence of fructose, expression of the genes mdh and manX is increased. The resulting transparency of the skill set of TR116 contributes highly to future functionalisation of food systems and food ingredients.

Abstract 868: Heritable cancer mutations in multiple myeloma

Abstract Background: Epidemiologic studies have shown familial aggregations of multiple myeloma (MM) and other hematologic malignancies, but little is known about heritable genetic susceptibilities in these patients. The purpose of this study is to investigate the prevalence of known germline cancer-predisposing mutations (CPM) in patients with multiple myeloma (MM). Methods: We analyzed a set of 895 newly diagnosed MM patients from the Multiple Myeloma Research Foundation (MMRF) CoMMpass registry for whom whole-exome sequencing of germline DNA data was available. We used the clinical annotation pipeline from Sema4, a CLIA- and CAP-certified genetic testing laboratory, in a research context, to identify patients with pathogenic or likely pathogenic CPM according to ACMG variant classification guidelines, and compared their characteristics against those without CPM. Statistical significance was assessed using the Chi-Square and Fisher's Exact tests and defined as a two-sided p value &amp;lt;0.05. Results: We identified 83 germline CPM in 31 distinct genes in 79 (8.8%) of 895 patients. Homologous recombination (HR) pathway gene mutations were the most common (n = 38, 46%), with CHEK2 being the most frequently mutated gene (n = 10, 12%). Notably, the number of mismatch repair (MMR) gene defects was considerably higher (n = 6, 1:149) than the estimated prevalence in the general population. CPM carriers were significantly more likely to be diagnosed with MM before age 40 (6.3% vs 1.8%, p = 0.025) and to have a family history (FH) of MM or leukemia (16.4% vs 6.3%, p = 0.01) than those without a CPM. Likelihood of having a FH of any malignancy was also significantly higher in the CPM group (70.9% vs 54.5%, p = 0.028). Interestingly, common CHEK2 founder mutations were observed at a much higher rate in patients with a FH of MM or leukemia (8.7% vs 0.68%, p = 0.0013). Conclusions: Our results suggest that a significant proportion of patients with MM carry germline cancer-predisposing mutations, especially those diagnosed at a very young age (&amp;lt;40 years old), and those with a family history of MM or leukemia. The observation that 6 out of 895 patients with MM had pathogenic MMR variants suggests that MM may be a previously unsuspected component of Lynch syndrome. Common CHEK2 founder mutations were strikingly frequent in patients with a FH of MM, suggesting that FH modifies the penetrance of these variants in MM predisposition, as has been observed for other cancers. Citation Format: Santiago Thibaud, Aaron Etra, Ryan Subaran, Zachry Soens, Scott Newman, Rong Chen, Ajai Chari, Hearn J. Cho, Sundar Jagannath, Deepu Madduri, David T. Melnekoff, Shambavi Richard, Joshua Richter, Larysa Sanchez, Alessandro Lagana, Samir Parekh, Kenan Onel. Heritable cancer mutations in multiple myeloma [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 868.

LNA -Gapmer Antisense Oligonucleotides Targeting the Oncogenic Lncrna MALAT1 Trigger Anti-Multiple Myeloma Activity By Proteasome Blockade

Dysregulation of non-coding RNAs is emerging as a common feature of human cancer. While short non-coding RNAs have been extensively investigated in multiple myeloma (MM), the biological role and the therapeutic significance of aberrantly expressed long non-coding RNAs (lncRNAs) are yet undetermined. A proprietary custom annotation pipeline of microarray data on lncRNA expression in different plasma cell (PC) dyscrasias, including 20 MGUS, 33 smoldering MM, 170 MM, 36 PC leukemia patients and 9 healthy donors, revealed high expression of MALAT1 in MM PCs. On this finding, we investigated the functional significance of MALAT1 by using novel 16-mer LNA gapmeR synthetic ASOs, that trigger selective RNAse-H dependent degradation of MALAT1. LNA-gapmeR ASOs targeting MALAT1 inhibited proliferation and clonogenicity of MM cell lines (n=7) and patient PCs (n=5), triggering ER-stress response and apoptosis, even in the presence of bone marrow stromal cells, while sparing healthy peripheral blood mononuclear cells. Conversely, MALAT1-enforced expression by lentiviral vectors enhanced cell proliferation and migration, reverted the effect of anti-MALAT1 ASOs and activated major oncogenic signal transduction pathways, such as AKT and MAPK. In vivo, i.p. administration of anti-MALAT1 gapmeRs inhibited the growth of human MM xenografts, with no evidence of organ toxicity. Microarray gene expression profiling indicated that MALAT1 depletion downregulated genes encoding for 20S proteasome β-subunits, as evidenced by gene set enrichment analysis (GSEA).Down-modulation of PSMβ2/4/5/7 mRNA and protein by anti-MALAT1 ASOs was confirmed by qPCR and Western blot respectively, and was associated to reduced trypsine-, chymotrypsine- and caspase-like proteasome activities and to the accumulation of polyubiquitylated proteins. Mechanistically, we demonstrated that proteasome inhibition upon MALAT1 knock-down was due to downmodulation of the major transcriptional activators of proteasome gene expression NRF1 and NRF2. At the same time, NRF1 was found to bind to and transactivate MALAT1 promoter, as demonstrated by chromatin immunoprecipitation and reporter assays, thus establishing a positive feedback-loop with MALAT1. Intriguingly, this loop was overactivated in bortezomib-resistant MM cells. Collectively, our findings highlight an unprecedented role of the lncRNA MALAT1 in the regulation of the proteasome machinery, and provide the first preclinical rationale for using ASO therapeutics targeting dysregulated lncRNAs for MM treatment. DisclosuresNo relevant conflicts of interest to declare.

Lantern: an integrative repository of functional annotations for lncRNAs in the human genome

BackgroundWith advancements in omics technologies, the range of biological processes where long non-coding RNAs (lncRNAs) are involved, is expanding extensively, thereby generating the need to develop lncRNA annotation resources. Although, there are a plethora of resources for annotating genes, despite the extensive corpus of lncRNA literature, the available resources with lncRNA ontology annotations are rare.ResultsWe present a lncRNA annotation extractor and repository (Lantern), developed using PubMed’s abstract retrieval engine and NCBO’s recommender annotation system. Lantern’s annotations were benchmarked against lncRNAdb’s manually curated free text. Benchmarking analysis suggested that Lantern has a recall of 0.62 against lncRNAdb for 182 lncRNAs and precision of 0.8. Additionally, we also annotated lncRNAs with multiple omics annotations, including predicted cis-regulatory TFs, interactions with RBPs, tissue-specific expression profiles, protein co-expression networks, coding potential, sub-cellular localization, and SNPs for ~ 11,000 lncRNAs in the human genome, providing a one-stop dynamic visualization platform.ConclusionsLantern integrates a novel, accurate semi-automatic ontology annotation engine derived annotations combined with a variety of multi-omics annotations for lncRNAs, to provide a central web resource for dissecting the functional dynamics of long non-coding RNAs and to facilitate future hypothesis-driven experiments. The annotation pipeline and a web resource with current annotations for human lncRNAs are freely available on sysbio.lab.iupui.edu/lantern.

A workflow to identify novel proteins based on the direct mapping of peptide-spectrum-matches to genomic locations

BackgroundSmall Proteins have received increasing attention in recent years. They have in particular been implicated as signals contributing to the coordination of bacterial communities. In genome annotations they are often missing or hidden among large numbers of hypothetical proteins because genome annotation pipelines often exclude short open reading frames or over-predict hypothetical proteins based on simple models. The validation of novel proteins, and in particular of small proteins (sProteins), therefore requires additional evidence. Proteogenomics is considered the gold standard for this purpose. It extends beyond established annotations and includes all possible open reading frames (ORFs) as potential sources of peptides, thus allowing the discovery of novel, unannotated proteins. Typically this results in large numbers of putative novel small proteins fraught with large fractions of false-positive predictions.ResultsWe observe that number and quality of the peptide-spectrum matches (PSMs) that map to a candidate ORF can be highly informative for the purpose of distinguishing proteins from spurious ORF annotations. We report here on a workflow that aggregates PSM quality information and local context into simple descriptors and reliably separates likely proteins from the large pool of false-positive, i.e., most likely untranslated ORFs. We investigated the artificial gut microbiome model SIHUMIx, comprising eight different species, for which we validate 5114 proteins that have previously been annotated only as hypothetical ORFs. In addition, we identified 37 non-annotated protein candidates for which we found evidence at the proteomic and transcriptomic level. Half (19) of these candidates have close functional homologs in other species. Another 12 candidates have homologs designated as hypothetical proteins in other species. The remaining six candidates are short (< 100 AA) and are most likely bona fide novel proteins.ConclusionsThe aggregation of PSM quality information for predicted ORFs provides a robust and efficient method to identify novel proteins in proteomics data. The workflow is in particular capable of identifying small proteins and frameshift variants. Since PSMs are explicitly mapped to genomic locations, it furthermore facilitates the integration of transcriptomics data and other sources of genome-level information.