The duplicated genes database: identification and functional annotation of co-localised duplicated genes across genomes

Deep multiple-instance learning accurately predicts gene haploinsufficiency and deletion pathogenicity

Copy number losses (deletions) are a major contributor to the etiology of severe genetic disorders. Although haploinsufficient genes play a critical role in deletion pathogenicity, current methods for deletion pathogenicity prediction fail to integrate multiple lines of evidence for haploinsufficiency at the gene level, limiting their power to pinpoint deleterious deletions associated with genetic disorders. Here we introduce DosaCNV, a deep multiple-instance learning framework that, for the first time, models deletion pathogenicity jointly with gene haploinsufficiency. By integrating over 30 gene-level features potentially predictive of haploinsufficiency, DosaCNV shows unmatched performance in prioritizing pathogenic deletions associated with a broad spectrum of genetic disorders. Furthermore, DosaCNV outperforms existing methods in predicting gene haploinsufficiency even though it is not trained on known haploinsufficient genes. Finally, DosaCNV leverages a state-of-the-art technique to quantify the contributions of individual gene-level features to haploinsufficiency, allowing for human-understandable explanations of model predictions. Altogether, DosaCNV is a powerful computational tool for both fundamental and translational research.

IsoFrog: a reversible jump Markov Chain Monte Carlo feature selection-based method for predicting isoform functions

MOTIVATION

A single gene may yield several isoforms with different functions through alternative splicing. Continuous efforts are devoted to developing machine-learning methods to predict isoform functions. However, existing methods do not consider the relevance of each feature to specific functions and ignore the noise caused by the irrelevant features. In this case, we hypothesize that constructing a feature selection framework to extract the function-relevant features might help improve the model accuracy in isoform function prediction.

RESULTS

In this article, we present a feature selection-based approach named IsoFrog to predict isoform functions. First, IsoFrog adopts a reversible jump Markov Chain Monte Carlo (RJMCMC)-based feature selection framework to assess the feature importance to gene functions. Second, a sequential feature selection procedure is applied to select a subset of function-relevant features. This strategy screens the relevant features for the specific function while eliminating irrelevant ones, improving the effectiveness of the input features. Then, the selected features are input into our proposed method modified domain-invariant partial least squares, which prioritizes the most likely positive isoform for each positive MIG and utilizes diPLS for isoform function prediction. Tested on three datasets, our method achieves superior performance over six state-of-the-art methods, and the RJMCMC-based feature selection framework outperforms three classic feature selection methods. We expect this proposed methodology will promote the identification of isoform functions and further inspire the development of new methods.

AVAILABILITY AND IMPLEMENTATION

IsoFrog is freely available at https://github.com/genemine/IsoFrog.

Identification and characterization of aldehyde dehydrogenase (ALDH) gene superfamily in garlic and expression profiling in response to drought, salinity, and ABA

In response to biotic and abiotic stressors, aldehydes are detoxified and converted to carboxylic acids by aldehyde dehydrogenases (ALDHs), which are enzymes that use NAD+/NADP+ as cofactors. Garlic (Allium sativum L.) has not yet undergone a systematic examination of the ALDH superfamily, despite the genome sequence having been made public. In this investigation, we identified, characterized, and profiled the expression of the garlic ALDH gene family over the entire genome. The ALDH Gene Nomenclature Committee (AGNC) classification was used to classify and name the 34 ALDH genes that were discovered. Except for chromosome 8, all AsALDH genes were dispersed across the chromosomes. AsALDH genes have various localizations, according to predictions about subcellular localization. The AsALDH proteins are more varied and closely related to rice than to Arabidopsis, according to a study of conserved motifs and phylogenetic relationships. The presence of stress modulation pathways is indicated by the abundance of stress-related cis-elements in the AsALDH genes' promoter regions. Analysis of the RNA-seq data showed that AsALDHs expressed differently in various tissues and at various developmental stages. Nine AsALDHs were chosen for study using RT-qPCR, and the results revealed that the majority of the genes were upregulated in response to ABA and downregulated in response to salinity and drought. The results of this study improved our knowledge of the traits, evolutionary background, and biological functions of AsALDHs genes in growth and development.

An overview of online resources for intra-species detection of gene duplications

Gene duplication plays an important role in evolutionary mechanism, which can act as a new source of genetic material in genome evolution. However, detecting duplicate genes from genomic data can be challenging. Various bioinformatics resources have been developed to identify duplicate genes from single and/or multiple species. Here, we summarize the metrics used to measure sequence identity among gene duplicates within species, compare several computational approaches that have been used to predict gene duplicates, and review recent advancements of a Basic Local Alignment Search Tool (BLAST)-based web tool and database, allowing future researchers to easily identify intra-species gene duplications. This article is a quick reference guide for research tools used for detecting gene duplicates.

HSDatabase-a database of highly similar duplicate genes from plants, animals, and algae

Gene duplication is an important evolutionary mechanism capable of providing new genetic material, which in some instances can help organisms adapt to various environmental conditions. Recent studies, for example, have indicated that highly similar duplicate genes (HSDs) are aiding adaptation to extreme conditions via gene dosage. However, for most eukaryotic genomes HSDs remain uncharacterized, partly because they can be hard to identify and categorize efficiently and effectively. Here, we collected and curated HSDs in nuclear genomes from various model animals, land plants and algae and indexed them in an online, open-access sequence repository called HSDatabase. Currently, this database contains 117 864 curated HSDs from 40 distinct genomes; it includes statistics on the total number of HSDs per genome as well as individual HSD copy numbers/lengths and provides sequence alignments of the duplicate gene copies. HSDatabase also allows users to download sequences of gene copies, access genome browsers, and link out to other databases, such as Pfam and Kyoto Encyclopedia of Genes and Genomes. What is more, a built-in Basic Local Alignment Search Tool option is available to conveniently explore potential homologous sequences of interest within and across species. HSDatabase has a user-friendly interface and provides easy access to the source data. It can be used on its own for comparative analyses of gene duplicates or in conjunction with HSDFinder, a newly developed bioinformatics tool for identifying, annotating, categorizing and visualizing HSDs.

Database URL: http://hsdfinder.com/database/

Extrachromosomal Circular DNA from TCGA Tumors Is Generated from Common Genomic Loci, Is Characterized by Self-Homology and DNA Motifs near Circle Breakpoints

Extrachromosomal circular DNA has emerged as a frequent genomic alteration in tumors. High numbers of circular DNAs correspond to poor prognosis suggesting an important function in tumor biology. However, despite mounting evidence supporting the importance of circular DNA, little is known about their production, maintenance, or selection. To provide insight into these processes, we analyzed circular DNA elements computationally identified in 355 TCGA tumors spanning 22 tumor types. Circular DNAs originated from common genomic loci irrespective of cancer type. Genes found in circularized genomic regions were more likely to be expressed and were enriched in cancer-related pathways. Finally, in support of a model for circle generation through either a homology or microhomology-mediated process, circles exhibit homology near their breakpoint. These breakpoints are also enriched in specific DNA motifs. Our analysis supports a model where gene-containing circles emerge from common, highly transcribed regions through a homology-mediated process.

Evolutionarily conserved properties of CLCA proteins 1, 3 and 4, as revealed by phylogenetic and biochemical studies in avian homologues

Species-specific diversities are particular features of mammalian chloride channel regulator, calcium activated (CLCA) genes. In contrast to four complex gene clusters in mammals, only two CLCA genes appear to exist in chickens. CLCA2 is conserved in both, while only the galline CLCA1 (gCLCA1) displays close genetic distance to mammalian clusters 1, 3 and 4. In this study, sequence analyses and biochemical characterizations revealed that gCLCA1 as a putative avian prototype shares common protein domains and processing features with all mammalian CLCA homologues. It has a transmembrane (TM) domain in the carboxy terminal region and its mRNA and protein were detected in the alimentary canal, where the protein was localized in the apical membrane of enterocytes, similar to CLCA4. Both mammals and birds seem to have at least one TM domain containing CLCA protein with complex glycosylation in the apical membrane of enterocytes. However, some characteristic features of mammalian CLCA1 and 3 including entire protein secretion and expression in cell types other than enterocytes seem to be dispensable for chicken. Phylogenetic analyses including twelve bird species revealed that avian CLCA1 and mammalian CLCA3 form clades separate from a major branch containing mammalian CLCA1 and 4. Overall, our data suggest that gCLCA1 and mammalian CLCA clusters 1, 3 and 4 stem from a common ancestor which underwent complex gene diversification in mammals but not in birds.

HSDFinder: A BLAST-Based Strategy for Identifying Highly Similar Duplicated Genes in Eukaryotic Genomes

Gene duplication is an important evolutionary mechanism capable of providing new genetic material for adaptive and nonadaptive evolution. However, bioinformatics tools for identifying duplicate genes are often limited to the detection of paralogs in multiple species or to specific types of gene duplicates, such as retrocopies. Here, we present a user-friendly, BLAST-based web tool, called HSDFinder, which can identify, annotate, categorize, and visualize highly similar duplicate genes (HSDs) in eukaryotic nuclear genomes. HSDFinder includes an online heatmap plotting option, allowing users to compare HSDs among different species and visualize the results in different Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway functional categories. The external software requirements are BLAST, InterProScan, and KEGG. The utility of HSDFinder was tested on various model eukaryotic species, including Chlamydomonas reinhardtii, Arabidopsis thaliana, Oryza sativa, and Zea mays as well as the psychrophilic green alga Chlamydomonas sp. UWO241, and was proven to be a practical and accurate tool for gene duplication analyses. The web tool is free to use at http://hsdfinder.com. Documentation and tutorials can be found via the GitHub: https://github.com/zx0223winner/HSDFinder.

Cost-Effective Mapping of Genetic Interactions in Mammalian Cells

Comprehensive maps of genetic interactions in mammalian cells are daunting to construct because of the large number of potential interactions, ~ 2 × 10⁸ for protein coding genes. We previously used co-inheritance of distant genes from published radiation hybrid (RH) datasets to identify genetic interactions. However, it was necessary to combine six legacy datasets from four species to obtain adequate statistical power. Mapping resolution was also limited by the low density PCR genotyping. Here, we employ shallow sequencing of nascent human RH clones as an economical approach to constructing interaction maps. In this initial study, 15 clones were analyzed, enabling construction of a network with 225 genes and 2,359 interactions (FDR < 0.05). Despite its small size, the network showed significant overlap with the previous RH network and with a protein-protein interaction network. Consumables were ≲$50 per clone, showing that affordable, high quality genetic interaction maps are feasible in mammalian cells.

The molecular basis, genetic control and pleiotropic effects of local gene co-expression

Nearby genes are often expressed as a group. Yet, the prevalence, molecular mechanisms and genetic control of local gene co-expression are far from being understood. Here, by leveraging gene expression measurements across 49 human tissues and hundreds of individuals, we find that local gene co-expression occurs in 13% to 53% of genes per tissue. By integrating various molecular assays (e.g. ChIP-seq and Hi-C), we estimate the ability of several mechanisms, such as enhancer-gene interactions, in distinguishing gene pairs that are co-expressed from those that are not. Notably, we identify 32,636 expression quantitative trait loci (eQTLs) which associate with co-expressed gene pairs and often overlap enhancer regions. Due to affecting several genes, these eQTLs are more often associated with multiple human traits than other eQTLs. Our study paves the way to comprehend trait pleiotropy and functional interpretation of QTL and GWAS findings. All local gene co-expression identified here is available through a public database ( https://glcoex.unil.ch/ ).

Systematic analysis of bypass suppression of essential genes

Essential genes tend to be highly conserved across eukaryotes, but, in some cases, their critical roles can be bypassed through genetic rewiring. From a systematic analysis of 728 different essential yeast genes, we discovered that 124 (17%) were dispensable essential genes. Through whole-genome sequencing and detailed genetic analysis, we investigated the genetic interactions and genome alterations underlying bypass suppression. Dispensable essential genes often had paralogs, were enriched for genes encoding membrane-associated proteins, and were depleted for members of protein complexes. Functionally related genes frequently drove the bypass suppression interactions. These gene properties were predictive of essential gene dispensability and of specific suppressors among hundreds of genes on aneuploid chromosomes. Our findings identify yeast's core essential gene set and reveal that the properties of dispensable essential genes are conserved from yeast to human cells, correlating with human genes that display cell line-specific essentiality in the Cancer Dependency Map (DepMap) project.

JEDI: circular RNA prediction based on junction encoders and deep interaction among splice sites

Motivation

Circular RNA (circRNA) is a novel class of long non-coding RNAs that have been broadly discovered in the eukaryotic transcriptome. The circular structure arises from a non-canonical splicing process, where the donor site backspliced to an upstream acceptor site. These circRNA sequences are conserved across species. More importantly, rising evidence suggests their vital roles in gene regulation and association with diseases. As the fundamental effort toward elucidating their functions and mechanisms, several computational methods have been proposed to predict the circular structure from the primary sequence. Recently, advanced computational methods leverage deep learning to capture the relevant patterns from RNA sequences and model their interactions to facilitate the prediction. However, these methods fail to fully explore positional information of splice junctions and their deep interaction.

Results

We present a robust end-to-end framework, Junction Encoder with Deep Interaction (JEDI), for circRNA prediction using only nucleotide sequences. JEDI first leverages the attention mechanism to encode each junction site based on deep bidirectional recurrent neural networks and then presents the novel cross-attention layer to model deep interaction among these sites for backsplicing. Finally, JEDI can not only predict circRNAs but also interpret relationships among splice sites to discover backsplicing hotspots within a gene region. Experiments demonstrate JEDI significantly outperforms state-of-the-art approaches in circRNA prediction on both isoform level and gene level. Moreover, JEDI also shows promising results on zero-shot backsplicing discovery, where none of the existing approaches can achieve.

Availability and implementation

The implementation of our framework is available at https://github.com/hallogameboy/JEDI.

Supplementary information

Supplementary data are available at Bioinformatics online.

Exome variant discrepancies due to reference-genome differences

Despite release of the GRCh38 human reference genome more than seven years ago, GRCh37 remains more widely used by most research and clinical laboratories. To date, no study has quantified the impact of utilizing different reference assemblies for the identification of variants associated with rare and common diseases from large-scale exome-sequencing data. By calling variants on both the GRCh37 and GRCh38 references, we identified single-nucleotide variants (SNVs) and insertion-deletions (indels) in 1,572 exomes from participants with Mendelian diseases and their family members. We found that a total of 1.5% of SNVs and 2.0% of indels were discordant when different references were used. Notably, 76.6% of the discordant variants were clustered within discrete discordant reference patches (DISCREPs) comprising only 0.9% of loci targeted by exome sequencing. These DISCREPs were enriched for genomic elements including segmental duplications, fix patch sequences, and loci known to contain alternate haplotypes. We identified 206 genes significantly enriched for discordant variants, most of which were in DISCREPs and caused by multi-mapped reads on the reference assembly that lacked the variant call. Among these 206 genes, eight are implicated in known Mendelian diseases and 53 are associated with common phenotypes from genome-wide association studies. In addition, variant interpretations could also be influenced by the reference after lifting-over variant loci to another assembly. Overall, we identified genes and genomic loci affected by reference assembly choice, including genes associated with Mendelian disorders and complex human diseases that require careful evaluation in both research and clinical applications.

Juvenile hormone in spiders. Is this the solution to a mystery?

The juvenile hormone (JH) plays a crucial role in arthropod physiological processes, e.g., the regulation of metamorphosis, development, and reproduction (the vitellogenesis, the development of gonads, egg production). Still, data about this sesquiterpenoid hormone in spiders (Araneae) are rudimentary and equivocal. The presence of the JH or its precursors (e.g. methyl farnesoate) is not confirmed in spiders. The site of synthesis of its is still undetermined. No receptors of the JH are identified in spiders and thus, the molecular mechanism of action of this group of hormones is still unknown. Here we show by using the phylogenetic analysis and qPCR method the presence of the transcript of the enzyme catalyzing the last phase of the JH biosynthesis pathway (epox CYP15A1), the JH receptor (Met), and a possible candidate to the methyl farnesoate receptor (USP) in the various tissues and stages of ontogenesis in both sexes of spider Parasteatoda tepidariorum. Our results indicate that the juvenile hormone and/or methyl farnesoate presence is possible in the species of spider P. tepidariorum. The presence of the Ptepox CYP15A1 gene suggests that the main site of the juvenile hormone synthesis can be the integument and not the Schneider organ 2. It also seems that the juvenile hormone and/or methyl farnesoate can be hormones with biological activity due to the presence of the transcript of insect and crustacean JH/MG receptor - Met. The Ptepox CYP15A1, PtMet, and Ptusp expression are sex-, tissue-and time-specific. This study is the first report about the presence of the Ptepox CYP15A1 and PtMet transcripts in the Arachnida, which may indicate the presence of the juvenile hormone and/or methyl farnesoate in spiders.

IsoResolve: predicting splice isoform functions by integrating gene and isoform-level features with domain adaptation

MOTIVATION

High resolution annotation of gene functions is a central goal in functional genomics. A single gene may produce multiple isoforms with different functions through alternative splicing. Conventional approaches, however, consider a gene as a single entity without differentiating these functionally different isoforms. Towards understanding gene functions at higher resolution, recent efforts have focused on predicting the functions of isoforms. However, the performance of existing methods is far from satisfactory mainly because of the lack of isoform-level functional annotation.

RESULTS

We present IsoResolve, a novel approach for isoform function prediction, which leverages the information from gene function prediction models with domain adaptation (DA). IsoResolve treats gene-level and isoform-level features as source and target domains, respectively. It uses DA to project the two domains into a latent variable space in such a way that the latent variables from the two domains have similar distribution, which enables the gene domain information to be leveraged for isoform function prediction. We systematically evaluated the performance of IsoResolve in predicting functions. Compared with five state-of-the-art methods, IsoResolve achieved significantly better performance. IsoResolve was further validated by case studies of genes with isoform-level functional annotation.

AVAILABILITY AND IMPLEMENTATION

IsoResolve is freely available at https://github.com/genemine/IsoResolve.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Ancient horse genomes reveal the timing and extent of dispersals across the Bering Land Bridge

The Bering Land Bridge (BLB) last connected Eurasia and North America during the Late Pleistocene. Although the BLB would have enabled transfers of terrestrial biota in both directions, it also acted as an ecological filter whose permeability varied considerably over time. Here we explore the possible impacts of this ecological corridor on genetic diversity within, and connectivity among, populations of a once wide-ranging group, the caballine horses (Equus spp.). Using a panel of 187 mitochondrial and eight nuclear genomes recovered from present-day and extinct caballine horses sampled across the Holarctic, we found that Eurasian horse populations initially diverged from those in North America, their ancestral continent, around 1.0-0.8 million years ago. Subsequent to this split our mitochondrial DNA analysis identified two bidirectional long-range dispersals across the BLB ~875-625 and ~200-50 thousand years ago, during the Middle and Late Pleistocene. Whole genome analysis indicated low levels of gene flow between North American and Eurasian horse populations, which probably occurred as a result of these inferred dispersals. Nonetheless, mitochondrial and nuclear diversity of caballine horse populations retained strong phylogeographical structuring. Our results suggest that barriers to gene flow, currently unidentified but possibly related to habitat distribution across Beringia or ongoing evolutionary divergence, played an important role in shaping the early genetic history of caballine horses, including the ancestors of living horses within Equus ferus.

Multi-modal meta-analysis of cancer cell line omics profiles identifies ECHDC1 as a novel breast tumor suppressor

Molecular and functional profiling of cancer cell lines is subject to laboratory-specific experimental practices and data analysis protocols. The current challenge therefore is how to make an integrated use of the omics profiles of cancer cell lines for reliable biological discoveries. Here, we carried out a systematic analysis of nine types of data modalities using meta-analysis of 53 omics studies across 12 research laboratories for 2,018 cell lines. To account for a relatively low consistency observed for certain data modalities, we developed a robust data integration approach that identifies reproducible signals shared among multiple data modalities and studies. We demonstrated the power of the integrative analyses by identifying a novel driver gene, ECHDC1, with tumor suppressive role validated both in breast cancer cells and patient tumors. The multi-modal meta-analysis approach also identified synthetic lethal partners of cancer drivers, including a co-dependency of PTEN deficient endometrial cancer cells on RNA helicases.

FIREWORKS: a bottom-up approach to integrative coessentiality network analysis

Genetic coessentiality analysis, a computational approach which identifies genes sharing a common effect on cell fitness across large-scale screening datasets, has emerged as a powerful tool to identify functional relationships between human genes. However, widespread implementation of coessentiality to study individual genes and pathways is limited by systematic biases in existing coessentiality approaches and accessibility barriers for investigators without computational expertise. We created FIREWORKS, a method and interactive tool for the construction and statistical analysis of coessentiality networks centered around gene(s) provided by the user. FIREWORKS incorporates a novel bias reduction approach to reduce false discoveries, enables restriction of coessentiality analyses to custom subsets of cell lines, and integrates multiomic and drug-gene interaction datasets to investigate and target contextual gene essentiality. We demonstrate the broad utility of FIREWORKS through case vignettes investigating gene function and specialization, indirect therapeutic targeting of "undruggable" proteins, and context-specific rewiring of genetic networks.

Tissue-specific usage of transposable element-derived promoters in mouse development

BACKGROUND

Transposable elements (TEs) are a significant component of eukaryotic genomes and play essential roles in genome evolution. Mounting evidence indicates that TEs are highly transcribed in early embryo development and contribute to distinct biological functions and tissue morphology.

RESULTS

We examine the epigenetic dynamics of mouse TEs during the development of five tissues: intestine, liver, lung, stomach, and kidney. We found that TEs are associated with over 20% of open chromatin regions during development. Close to half of these accessible TEs are only activated in a single tissue and a specific developmental stage. Most accessible TEs are rodent-specific. Across these five tissues, 453 accessible TEs are found to create the transcription start sites of downstream genes in mouse, including 117 protein-coding genes and 144 lincRNA genes, 93.7% of which are mouse-specific. Species-specific TE-derived transcription start sites are found to drive the expression of tissue-specific genes and change their tissue-specific expression patterns during evolution.

CONCLUSION

Our results suggest that TE insertions increase the regulatory potential of the genome, and some TEs have been domesticated to become a crucial component of gene and regulate tissue-specific expression during mouse tissue development.

PRESM: personalized reference editor for somatic mutation discovery in cancer genomics

MOTIVATION

Accurate detection of somatic mutations is a crucial step toward understanding cancer. Various tools have been developed to detect somatic mutations from cancer genome sequencing data by mapping reads to a universal reference genome and inferring likelihoods from complex statistical models. However, read mapping is frequently obstructed by mismatches between germline and somatic mutations on a read and the reference genome. Previous attempts to develop personalized genome tools are not compatible with downstream statistical models for somatic mutation detection.

RESULTS

We present PRESM, a tool that builds personalized reference genomes by integrating germline mutations into the reference genome. The aforementioned obstacle is circumvented by using a two-step germline substitution procedure, maintaining positional fidelity using an innovative workaround. Reads derived from tumor tissue can be positioned more accurately along a personalized reference than a universal reference due to the reduced genetic distance between the subject (tumor genome) and the target (the personalized genome). Application of PRESM's personalized genome reduced false-positive (FP) somatic mutation calls by as much as 55.5%, and facilitated the discovery of a novel somatic point mutation on a germline insertion in PDE1A, a phosphodiesterase associated with melanoma. Moreover, all improvements in calling accuracy were achieved without parameter optimization, as PRESM itself is parameter-free. Hence, similar increases in read mapping and decreases in the FP rate will persist when PRESM-built genomes are applied to any user-provided dataset.

AVAILABILITY AND IMPLEMENTATION

The software is available at https://github.com/precisionomics/PRESM.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Extensive disruption of protein interactions by genetic variants across the allele frequency spectrum in human populations

Each human genome carries tens of thousands of coding variants. The extent to which this variation is functional and the mechanisms by which they exert their influence remains largely unexplored. To address this gap, we leverage the ExAC database of 60,706 human exomes to investigate experimentally the impact of 2009 missense single nucleotide variants (SNVs) across 2185 protein-protein interactions, generating interaction profiles for 4797 SNV-interaction pairs, of which 421 SNVs segregate at > 1% allele frequency in human populations. We find that interaction-disruptive SNVs are prevalent at both rare and common allele frequencies. Furthermore, these results suggest that 10.5% of missense variants carried per individual are disruptive, a higher proportion than previously reported; this indicates that each individual's genetic makeup may be significantly more complex than expected. Finally, we demonstrate that candidate disease-associated mutations can be identified through shared interaction perturbations between variants of interest and known disease mutations.

Expression profile of genes encoding allatoregulatory neuropeptides in females of the spider Parasteatoda tepidariorum (Araneae, Theridiidae)

Allatoregulatory neuropeptides are multifunctional proteins that take part in the synthesis and secretion of juvenile hormones. In insects, allatostatins are inhibitors of juvenile hormone biosynthesis in the corpora allata while allatotropins, act as stimulators. By quantitative real-time PCR, we analyzed the gene expression of allatostatin A (PtASTA), allatostatin B (PtASTB), allatostatin C (PtASTC), allatotropin (PtAT) and their receptors (PtASTA-R, PtASTB-R, PtASTC-R, PtAT-R) in various tissues in different age groups of female spiders. In the presented manuscript, the presence of allatostatin A, allatostatin C, and allatotropin are reported in females of the spider P. tepidariorum. The obtained results indicated substantial differences in gene expression levels for allatoregulatory neuropeptides and their receptors in the different tissues. Additionally, the gene expression levels also varied depending on the female age. Strong expression was observed coinciding with sexual maturation in the neuroendocrine and nervous system, and to a lower extent in the digestive tissues and ovaries. Reverse trends were observed for the expression of genes encoding the receptors of these neuropeptides. In conclusion, our study is the first hint that the site of synthesis and secretion is fulfilled by similar structures as observed in other arthropods. In addition, the results of the analysis of spider physiology give evidence that the general functions like regulation of the juvenile hormone synthesis, regulation of the digestive tract and ovaries action, control of vitellogenesis process by the neuropeptides seem to be conserved among arthropods and are the milestone to future functional studies.

FusionScan: accurate prediction of fusion genes from RNA-Seq data

Identification of fusion gene is of prominent importance in cancer research field because of their potential as carcinogenic drivers. RNA sequencing (RNA-Seq) data have been the most useful source for identification of fusion transcripts. Although a number of algorithms have been developed thus far, most programs produce too many false-positives, thus making experimental confirmation almost impossible. We still lack a reliable program that achieves high precision with reasonable recall rate. Here, we present FusionScan, a highly optimized tool for predicting fusion transcripts from RNA-Seq data. We specifically search for split reads composed of intact exons at the fusion boundaries. Using 269 known fusion cases as the reference, we have implemented various mapping and filtering strategies to remove false-positives without discarding genuine fusions. In the performance test using three cell line datasets with validated fusion cases (NCI-H660, K562, and MCF-7), FusionScan outperformed other existing programs by a considerable margin, achieving the precision and recall rates of 60% and 79%, respectively. Simulation test also demonstrated that FusionScan recovered most of true positives without producing an overwhelming number of false-positives regardless of sequencing depth and read length. The computation time was comparable to other leading tools. We also provide several curative means to help users investigate the details of fusion candidates easily. We believe that FusionScan would be a reliable, efficient and convenient program for detecting fusion transcripts that meet the requirements in the clinical and experimental community. FusionScan is freely available at http://fusionscan.ewha.ac.kr/.

Copy number variation of PR-39 cathelicidin, and identification of PR-35, a natural variant of PR-39 with reduced mammalian cytotoxicity

Proline-arginine-rich (PR)-39 is neutrophil antimicrobial peptide that has potent antimicrobial activity against a broad spectrum of microorganisms, including bacteria, fungi, and some enveloped viruses as a part of the innate immune system. We analyzed the nucleotide sequence variations of PR-39 exon 4, which is the mature peptide region responsible for antimicrobial activity, from 48 pigs of six breeds using sequence-based typing. The analysis identified four alleles including allele PR-35 with a 12-bp deletion near the N-terminus. Interestingly, 16.7% of individuals showed the presence of three alleles per individual, but only in the Berkshire and Duroc breeds. We further analyzed the genetic diversity of PR-39 for the entire genomic region of the gene from PR-39 exon 1 to the 3' untranslated region for different alleles by PCR amplification and cloning. The antimicrobial activity of chemically synthesized PR-35 was similar to that of PR-39, but the level of mammalian cell cytotoxicity was lower than the wild type. Better knowledge of the genetic diversity of PR-39 among different individuals and breeds may contribute to improved immune defense of pigs. PR-35, as a natural antimicrobial peptide variant, could be an interesting candidate for the development of peptide antibiotics.

Rapid high-resolution measurement of DNA replication timing by droplet digital PCR

Genomes are replicated in a reproducible temporal pattern. Current methods for assaying allele replication timing are time consuming and/or expensive. These include high-throughput sequencing which can be used to measure DNA copy number as a proxy for allele replication timing. Here, we use droplet digital PCR to study DNA replication timing at multiple loci in budding yeast and human cells. We establish that the method has temporal and spatial resolutions comparable to the high-throughput sequencing approaches, while being faster than alternative locus-specific methods. Furthermore, the approach is capable of allele discrimination. We apply this method to determine relative replication timing across timing transition zones in cultured human cells. Finally, multiple samples can be analysed in parallel, allowing us to rapidly screen kinetochore mutants for perturbation to centromere replication timing. Therefore, this approach is well suited to the study of locus-specific replication and the screening of cis- and trans-acting mutants to identify mechanisms that regulate local genome replication timing.

Linking autoimmunity to the origin of the adaptive immune system

In jawed vertebrates, the adaptive immune system (AIS) cooperates with the innate immune system (IIS) to protect hosts from infections. Although targeting non-self-components, the AIS also generates self-reactive antibodies which, when inadequately counter-selected, can give rise to autoimmune diseases (ADs). ADs are on the rise in western countries. Why haven’t ADs been eliminated during the evolution of a ∼500 million-year old system? And why have they become more frequent in recent decades? Self-recognition is an attribute of the phylogenetically more ancient IIS and empirical data compellingly show that some self-reactive antibodies, which are classifiable as elements of the IIS rather then the AIS, may protect from (rather than cause) ADs. Here, we propose that the IIS’s self-recognition system originally fathered the AIS and, as a consequence of this relationship, its activity is dampened in hygienic environments. Rather than a mere breakdown or failure of the mechanisms of self-tolerance, ADs might thus arise from architectural constraints.

Gene duplication can impart fragility, not robustness, in the yeast protein interaction network

The maintenance of duplicated genes is thought to protect cells from genetic perturbations, but the molecular basis of this robustness is largely unknown. By measuring the interaction of yeast proteins with their partners in wild-type cells and in cells lacking a paralog, we found that 22 out of 56 paralog pairs compensate for the lost interactions. An equivalent number of pairs exhibit the opposite behavior and require each other's presence for maintaining their interactions. These dependent paralogs generally interact physically, regulate each other's abundance, and derive from ancestral self-interacting proteins. This reveals that gene duplication may actually increase mutational fragility instead of robustness in a large number of cases.

The impact of the protein interactome on the syntenic structure of mammalian genomes

Conserved synteny denotes evolutionary preserved gene order across species. It is not well understood to which degree functional relationships between genes are preserved in syntenic blocks. Here we investigate whether protein-coding genes conserved in mammalian syntenic blocks encode gene products that serve the common functional purpose of interacting at protein level, i.e. connectivity. High connectivity among protein-protein interactions (PPIs) was only moderately associated with conserved synteny on a genome-wide scale. However, we observed a smaller subset of 3.6% of all syntenic blocks with high-confidence PPIs that had significantly higher connectivity than expected by random. Additionally, syntenic blocks with high-confidence PPIs contained significantly more chromatin loops than the remaining blocks, indicating functional preservation among these syntenic blocks. Conserved synteny is typically defined by sequence similarity. In this study, we also examined whether a functional relationship, here PPI connectivity, can identify syntenic blocks independently of orthology. While orthology-based syntenic blocks with high-confident PPIs and the connectivity-based syntenic blocks largely overlapped, the connectivity-based approach identified additional syntenic blocks that were not found by conventional sequence-based methods alone. Additionally, the connectivity-based approach enabled identification of potential orthologous genes between species. Our analyses demonstrate that subsets of syntenic blocks are associated with highly connected proteins, and that PPI connectivity can be used to detect conserved synteny even if sequence conservation drifts beyond what orthology algorithms normally can identify.

Analysis of the relationship between coexpression domains and chromatin 3D organization

Gene order is not random in eukaryotic chromosomes, and co-regulated genes tend to be clustered. The mechanisms that determine co-regulation of large regions of the genome and its connection with chromatin three-dimensional (3D) organization are still unclear however. Here we have adapted a recently described method for identifying chromatin topologically associating domains (TADs) to identify coexpression domains (which we term “CODs”). Using human normal breast and breast cancer RNA-seq data, we have identified approximately 500 CODs. CODs in the normal and breast cancer genomes share similar characteristics but differ in their gene composition. COD genes have a greater tendency to be coexpressed with genes that reside in other CODs than with non-COD genes. Such inter-COD coexpression is maintained over large chromosomal distances in the normal genome but is partially lost in the cancer genome. Analyzing the relationship between CODs and chromatin 3D organization using Hi-C contact data, we find that CODs do not correspond to TADs. In fact, intra-TAD gene coexpression is the same as random for most chromosomes. However, the contact profile is similar between gene pairs that reside either in the same COD or in coexpressed CODs. These data indicate that co-regulated genes in the genome present similar patterns of contacts irrespective of the frequency of physical chromatin contacts between them.

Prokaryotic operons normally comprise functionally related genes whose expression is coordinated. Even though operons do not exist in most eukaryotes, results from the last fifteen years indicate that gene order is nonetheless not random in eukaryotes, and that coexpressed genes tend to be grouped in the genome. We identify here about 500 coexpression domain (CODs) in normal breast tissue. Interestingly, we find that genes within CODs often are coexpressed with other genes that reside in other CODs placed very far away in the same chromosome, which is indicative of long-range inter-COD co-regulation. Furthermore, we find that coexpressed genes within CODs or within co-regulated CODs display similar three-dimensional chromatin contacts, suggesting a spatial coordination of CODs.

eDGAR: a database of Disease-Gene Associations with annotated Relationships among genes

BACKGROUND

Genetic investigations, boosted by modern sequencing techniques, allow dissecting the genetic component of different phenotypic traits. These efforts result in the compilation of lists of genes related to diseases and show that an increasing number of diseases is associated with multiple genes. Investigating functional relations among genes associated with the same disease contributes to highlighting molecular mechanisms of the pathogenesis.

RESULTS

We present eDGAR, a database collecting and organizing the data on gene/disease associations as derived from OMIM, Humsavar and ClinVar. For each disease-associated gene, eDGAR collects information on its annotation. Specifically, for lists of genes, eDGAR provides information on: i) interactions retrieved from PDB, BIOGRID and STRING; ii) co-occurrence in stable and functional structural complexes; iii) shared Gene Ontology annotations; iv) shared KEGG and REACTOME pathways; v) enriched functional annotations computed with NET-GE; vi) regulatory interactions derived from TRRUST; vii) localization on chromosomes and/or co-localisation in neighboring loci. The present release of eDGAR includes 2672 diseases, related to 3658 different genes, for a total number of 5729 gene-disease associations. 71% of the genes are linked to 621 multigenic diseases and eDGAR highlights their common GO terms, KEGG/REACTOME pathways, physical and regulatory interactions. eDGAR includes a network based enrichment method for detecting statistically significant functional terms associated to groups of genes.

CONCLUSIONS

eDGAR offers a resource to analyze disease-gene associations. In multigenic diseases genes can share physical interactions and/or co-occurrence in the same functional processes. eDGAR is freely available at: edgar.biocomp.unibo.it.

Mapping of Wnt-Frizzled interactions by multiplex CRISPR targeting of receptor gene families

Signaling pathway modules are often encoded by several closely related paralogous genes that can have redundant roles and are therefore difficult to analyze by loss-of-function analysis. A typical example is the Wnt signaling pathway, which in mammals is mediated by 19 Wnt ligands that can bind to 10 Frizzled (FZD) receptors. Although significant progress in understanding Wnt-FZD receptor interactions has been made in recent years, tools to generate systematic interaction maps have been largely lacking. Here we generated cell lines with multiplex mutant alleles of FZD1, FZD2, and FZD7 and demonstrate that these cells are unresponsive to canonical Wnt ligands. Subsequently, we performed genetic rescue experiments with combinations of FZDs and canonical Wnts to create a functional ligand–receptor interaction map. These experiments showed that whereas several Wnt ligands, such as Wnt3a, induce signaling through a broad spectrum of FZD receptors, others, such as Wnt8a, act through a restricted set of FZD genes. Together, our results map functional interactions of FZDs and 10 Wnt ligands and demonstrate how multiplex targeting by clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 can be used to systematically elucidate the functions of multigene families.—Voloshanenko, O., Gmach, P., Winter, J., Kranz, D., Boutros, M. Mapping of Wnt-Frizzled interactions by multiplex CRISPR targeting of receptor gene families.

Germline BRCA2 mutations drive prostate cancers with distinct evolutionary trajectories

Germline mutations in the BRCA2 tumour suppressor are associated with both an increased lifetime risk of developing prostate cancer (PCa) and increased risk of aggressive disease. To understand this aggression, here we profile the genomes and methylomes of localized PCa from 14 carriers of deleterious germline BRCA2 mutations (BRCA2-mutant PCa). We show that BRCA2-mutant PCa harbour increased genomic instability and a mutational profile that more closely resembles metastastic than localized disease. BRCA2-mutant PCa shows genomic and epigenomic dysregulation of the MED12L/MED12 axis, which is frequently dysregulated in metastatic castration-resistant prostate cancer (mCRPC). This dysregulation is enriched in BRCA2-mutant PCa harbouring intraductal carcinoma (IDC). Microdissection and sequencing of IDC and juxtaposed adjacent non-IDC invasive carcinoma in 10 patients demonstrates a common ancestor to both histopathologies. Overall we show that localized castration-sensitive BRCA2-mutant tumours are uniquely aggressive, due to de novo aberration in genes usually associated with metastatic disease, justifying aggressive initial treatment.

Men that carrier BRCA2 germline mutations are at risk of developing prostate cancer. Here, the authors analyse the genomes of prostate cancer from these individuals and demonstrate increased genomic instability in comparison to sporadic prostate cancer.

Genomic hallmarks of localized, non-indolent prostate cancer

Prostate tumours are highly variable in their response to therapies, but clinically available prognostic factors can explain only a fraction of this heterogeneity. Here we analysed 200 whole-genome sequences and 277 additional whole-exome sequences from localized, non-indolent prostate tumours with similar clinical risk profiles, and carried out RNA and methylation analyses in a subset. These tumours had a paucity of clinically actionable single nucleotide variants, unlike those seen in metastatic disease. Rather, a significant proportion of tumours harboured recurrent non-coding aberrations, large-scale genomic rearrangements, and alterations in which an inversion repressed transcription within its boundaries. Local hypermutation events were frequent, and correlated with specific genomic profiles. Numerous molecular aberrations were prognostic for disease recurrence, including several DNA methylation events, and a signature comprised of these aberrations outperformed well-described prognostic biomarkers. We suggest that intensified treatment of genomically aggressive localized prostate cancer may improve cure rates.

Driver gene classification reveals a substantial overrepresentation of tumor suppressors among very large chromatin-regulating proteins

Compiling a comprehensive list of cancer driver genes is imperative for oncology diagnostics and drug development. While driver genes are typically discovered by analysis of tumor genomes, infrequently mutated driver genes often evade detection due to limited sample sizes. Here, we address sample size limitations by integrating tumor genomics data with a wide spectrum of gene-specific properties to search for rare drivers, functionally classify them, and detect features characteristic of driver genes. We show that our approach, CAnceR geNe similarity-based Annotator and Finder (CARNAF), enables detection of potentially novel drivers that eluded over a dozen pan-cancer/multi-tumor type studies. In particular, feature analysis reveals a highly concentrated pool of known and putative tumor suppressors among the <1% of genes that encode very large, chromatin-regulating proteins. Thus, our study highlights the need for deeper characterization of very large, epigenetic regulators in the context of cancer causality.

A pathway-centric view of spatial proximity in the 3D nucleome across cell lines

In various contexts, spatially proximal genes have been shown to be functionally related. However, the extent to which spatial proximity of genes in a pathway contributes to the pathway's context-specific activity is not known. Leveraging Hi-C data in six human cell-lines, we show that spatial proximity of genes in a pathway is highly correlated with the pathway's context-specific expression and function. Furthermore, spatial proximity of pathway genes correlates with interactions of their protein products, and the specific pathway genes that are proximal to one another tend to occupy higher levels in the regulatory hierarchy. In addition to intra-pathway proximity, related pathways are spatially proximal to one another and housekeeping-genes tend to be proximal to several other pathways suggesting their coordinating role. Substantially extending previous works, our study reveals a pathway-centric organization of 3D-nucleome, whereby, functionally related interacting driver genes tend to be in spatial-proximity in a context-specific manner.

Enhancer Sharing Promotes Neighborhoods of Transcriptional Regulation Across Eukaryotes

Enhancers physically interact with transcriptional promoters, looping over distances that can span multiple regulatory elements. Given that enhancer-promoter (EP) interactions generally occur via common protein complexes, it is unclear whether EP pairing is predominantly deterministic or proximity guided. Here, we present cross-organismic evidence suggesting that most EP pairs are compatible, largely determined by physical proximity rather than specific interactions. By reanalyzing transcriptome datasets, we find that the transcription of gene neighbors is correlated over distances that scale with genome size. We experimentally show that nonspecific EP interactions can explain such correlation, and that EP distance acts as a scaling factor for the transcriptional influence of an enhancer. We propose that enhancer sharing is commonplace among eukaryotes, and that EP distance is an important layer of information in gene regulation.

CDROM: Classification of Duplicate gene RetentiOn Mechanisms

BACKGROUND

Gene duplication is a major source of new genes that is thought to play an important role in phenotypic innovation. Though several mechanisms have been hypothesized to drive the functional evolution and long-term retention of duplicate genes, there are currently no software tools for assessing their genome-wide contributions. Thus, the evolutionary mechanisms by which duplicate genes acquire novel functions remain unclear in a number of taxa.

RESULTS

In a recent study, researchers developed a phylogenetic approach that uses gene expression data from two species to classify the mechanisms underlying the retention of duplicate genes (Proc Natl Acad Sci USA 110:1740917414, 2013). We have implemented their classification method, as well as a more generalized method, in the R package CDROM, enabling users to apply these methods to their data and gain insights into the origin of novel biological functions after gene duplication. The CDROM R package, source code, and user manual for the R package are available for download from CRAN at https://cran.rstudio.com/web/packages/CDROM/ . Additionally, the CDROM R source code, user manual for running CDROM from the source code, and sample dataset used in this manuscript can be accessed at www.personal.psu.edu/rua15/software.html .

CONCLUSIONS

CDROM is the first software package that enables genome-wide classification of the mechanisms driving the long-term retention of duplicate genes. It is user-friendly and flexible, providing researchers with a tool for studying the functional evolution of duplicate genes in a variety of taxa.

Survey of variation in human transcription factors reveals prevalent DNA binding changes

Sequencing of exomes and genomes has revealed abundant genetic variation affecting the coding sequences of human transcription factors (TFs), but the consequences of such variation remain largely unexplored. We developed a computational, structure-based approach to evaluate TF variants for their impact on DNA binding activity and used universal protein-binding microarrays to assay sequence-specific DNA binding activity across 41 reference and 117 variant alleles found in individuals of diverse ancestries and families with Mendelian diseases. We found 77 variants in 28 genes that affect DNA binding affinity or specificity and identified thousands of rare alleles likely to alter the DNA binding activity of human sequence-specific TFs. Our results suggest that most individuals have unique repertoires of TF DNA binding activities, which may contribute to phenotypic variation.

Comparative analysis of housekeeping and tissue-selective genes in human based on network topologies and biological properties

Housekeeping genes are genes that are turned on most of the time in almost every tissue to maintain cellular functions. Tissue-selective genes are predominantly expressed in one or a few biologically relevant tissue types. Benefitting from the massive gene expression microarray data obtained over the past decades, the properties of housekeeping and tissue-selective genes can now be investigated on a large-scale manner. In this study, we analyzed the topological properties of housekeeping and tissue-selective genes in the protein-protein interaction (PPI) network. Furthermore, we compared the biological properties and amino acid usage between these two gene groups. The results indicated that there were significant differences in topological properties between housekeeping and tissue-selective genes in the PPI network, and housekeeping genes had higher centrality properties and may play important roles in the complex biological network environment. We also found that there were significant differences in multiple biological properties and many amino acid compositions. The functional genes enrichment and subcellular localizations analysis was also performed to investigate the characterization of housekeeping and tissue-selective genes. The results indicated that the two gene groups showed significant different enrichment in drug targets, disease genes and toxin targets, and located in different subcellular localizations. At last, the discriminations between the properties of two gene groups were measured by the F-score, and expression stage had the most discriminative index in all properties. These findings may elucidate the biological mechanisms for understanding housekeeping and tissue-selective genes and may contribute to better annotate housekeeping and tissue-selective genes in other organisms.

Characterization of DNA variants in the human kinome in breast cancer

Kinases play a key role in cancer biology, and serve as potential clinically useful targets for designing cancer therapies. We examined nucleic acid variations in the human kinome and several known cancer-related genes in breast cancer. DNA was extracted from fine needle biopsies of 73 primary breast cancers and 19 metastatic lesions. Targeted sequencing of 518 kinases and 68 additional cancer related genes was performed using the SOLiD sequencing platform. We detected 1561 unique, non-synonymous variants in kinase genes in the 92 cases, and 74 unique variants in 43 kinases that were predicted to have major functional impact on the protein. Three kinase groups—CMGC, STE and TKL—showed greater mutational load in metastatic compared to primary cancer samples, however, after correction for multiple testing the difference was significant only for the TKL group (P = 0.04). We also observed that a higher proportion of histologic grade 1 and 2 cases had high functional impact variants in the SCYL2 gene compared with grade 3 cases. Our findings indicate that individual breast cancers harbor a substantial number of potentially functionally important nucleotide variations in kinase genes, most of which are present in unique combinations and include both somatic and germline functional variants.

Red: an intelligent, rapid, accurate tool for detecting repeats de-novo on the genomic scale

Background

With rapid advancements in technology, the sequences of thousands of species’ genomes are becoming available. Within the sequences are repeats that comprise significant portions of genomes. Successful annotations thus require accurate discovery of repeats. As species-specific elements, repeats in newly sequenced genomes are likely to be unknown. Therefore, annotating newly sequenced genomes requires tools to discover repeats de-novo. However, the currently available de-novo tools have limitations concerning the size of the input sequence, ease of use, sensitivities to major types of repeats, consistency of performance, speed, and false positive rate.

Results

To address these limitations, I designed and developed Red, applying Machine Learning. Red is the first repeat-detection tool capable of labeling its training data and training itself automatically on an entire genome. Red is easy to install and use. It is sensitive to both transposons and simple repeats; in contrast, available tools such as RepeatScout and ReCon are sensitive to transposons, and WindowMasker to simple repeats. Red performed consistently well on seven genomes; the other tools performed well only on some genomes. Red is much faster than RepeatScout and ReCon and has a much lower false positive rate than WindowMasker. On human genes with five or more copies, Red was more specific than RepeatScout by a wide margin. When tested on genomes of unusual nucleotide compositions, Red located repeats with high sensitivities and maintained moderate false positive rates. Red outperformed the related tools on a bacterial genome. Red identified 46,405 novel repetitive segments in the human genome. Finally, Red is capable of processing assembled and unassembled genomes.

Conclusions

Red’s innovative methodology and its excellent performance on seven different genomes represent a valuable advancement in the field of repeats discovery.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-015-0654-5) contains supplementary material, which is available to authorized users.

Spatial genomic heterogeneity within localized, multifocal prostate cancer

Herein we provide a detailed molecular analysis of the spatial heterogeneity of clinically localized, multifocal prostate cancer to delineate new oncogenes or tumor suppressors. We initially determined the copy number aberration (CNA) profiles of 74 patients with index tumors of Gleason score 7. Of these, 5 patients were subjected to whole-genome sequencing using DNA quantities achievable in diagnostic biopsies, with detailed spatial sampling of 23 distinct tumor regions to assess intraprostatic heterogeneity in focal genomics. Multifocal tumors are highly heterogeneous for single-nucleotide variants (SNVs), CNAs and genomic rearrangements. We identified and validated a new recurrent amplification of MYCL, which is associated with TP53 deletion and unique profiles of DNA damage and transcriptional dysregulation. Moreover, we demonstrate divergent tumor evolution in multifocal cancer and, in some cases, tumors of independent clonal origin. These data represent the first systematic relation of intraprostatic genomic heterogeneity to predicted clinical outcome and inform the development of novel biomarkers that reflect individual prognosis.

Principles for the organization of gene-sets

A gene-set, an important concept in microarray expression analysis and systems biology, is a collection of genes and/or their products (i.e. proteins) that have some features in common. There are many different ways to construct gene-sets, but a systematic organization of these ways is lacking. Gene-sets are mainly organized ad hoc in current public-domain databases, with group header names often determined by practical reasons (such as the types of technology in obtaining the gene-sets or a balanced number of gene-sets under a header). Here we aim at providing a gene-set organization principle according to the level at which genes are connected: homology, physical map proximity, chemical interaction, biological, and phenotypic-medical levels. We also distinguish two types of connections between genes: actual connection versus sharing of a label. Actual connections denote direct biological interactions, whereas shared label connection denotes shared membership in a group. Some extensions of the framework are also addressed such as overlapping of gene-sets, modules, and the incorporation of other non-protein-coding entities such as microRNAs.

Hotspot activating PRKD1 somatic mutations in polymorphous low-grade adenocarcinomas of the salivary glands

Polymorphous low-grade adenocarcinoma (PLGA) is the second most frequent type of malignant tumor of the minor salivary glands. We identified PRKD1 hotspot mutations encoding p.Glu710Asp in 72.9% of PLGAs but not in other salivary gland tumors. Functional studies demonstrated that this kinase-activating alteration likely constitutes a driver of PLGA.

Genome-wide analysis of human hotspot intersected genes highlights the roles of meiotic recombination in evolution and disease

Background

Meiotic recombination events are not randomly located, but rather cluster at hotspot regions. Recently, the fine-scale mapping of genome-wide human recombination hotspots was performed. Here, we systematically analyzed the evolutionary and disease-associated features of hotspots that overlapped with protein-coding genes.

Results

In this study, we defined hotspot intersected genes as HI genes. We found that HI genes were prone to be located in the extracellular part and were functionally enriched in cell-to-cell communication. Tissue-specific genes and secreted protein encoding genes were overrepresented in HI genes, while housekeeping genes were underrepresented. Compared to slowly evolving housekeeping genes and random genes with lower recombination rates, HI genes evolved faster. The fact that brain and blood specific genes were overrepresented in HI genes indicates that they may be involved in the evolution of human intelligence and the immune system. We also found that genes related to disease were enriched in HI genes, especially genes with disease-associated chromosomal rearrangements. Hotspot sequence motifs were overrepresented in common sequences of HI genes and genes with disease-associated chromosomal rearrangements. We further listed repeat elements that were enriched both in hotspots and genes with disease-associated chromosomal rearrangements.

Conclusion

HI genes are evolving and may be involved in the generation of key features of human during evolution. Disease-associated genes may be by-products of meiotic recombination. In addition, hotspot sequence motifs and repeat elements showed the connection between meiotic recombination and genes with disease-associated chromosomal rearrangements at the sequence level. Our study will enable us to better understand the evolutionary and biological significance of human meiotic recombination.