Set Of Human Genes Research Articles

A robust estimation of exon expression to identify alternative spliced genes applied to human tissues and cancer samples.

BackgroundAccurate analysis of whole-gene expression and individual-exon expression is essential to characterize different transcript isoforms and identify alternative splicing events in human genes. One of the omic technologies widely used in many studies on human samples are the exon-specific expression microarray platforms.ResultsSince there are not many validated comparative analyses to identify specific splicing events using data derived from these types of platforms, we have developed an algorithm (called ESLiM) to detect significant changes in exon use, and applied it to a reference dataset of 270 human genes that show alternative expression in different tissues. We compared the results with three other methodological approaches and provided the R source code to be applied elsewhere. The genes positively detected by these analyses also provide a verified subset of human genes that present tissue-regulated isoforms. Furthermore, we performed a validation analysis on human patient samples comparing two different subtypes of acute myeloid leukemia (AML) and we experimentally validated the splicing in several selected genes that showed exons with highly significant signal change.ConclusionsThe comparative analyses with other methods using a fair set of human genes that show alternative splicing and the validation on clinical samples demonstrate that the proposed novel algorithm is a reliable tool for detecting differential splicing in exon-level expression data.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-879) contains supplementary material, which is available to authorized users.

Inter-species pathway perturbation prediction via data-driven detection of functional homology

Experiments in animal models are often conducted to infer how humans will respond to stimuli by assuming that the same biological pathways will be affected in both organisms. The limitations of this assumption were tested in the IMPROVER Species Translation Challenge, where 52 stimuli were applied to both human and rat cells and perturbed pathways were identified. In the Inter-species Pathway Perturbation Prediction sub-challenge, multiple teams proposed methods to use rat transcription data from 26 stimuli to predict human gene set and pathway activity under the same perturbations. Submissions were evaluated using three performance metrics on data from the remaining 26 stimuli. We present two approaches, ranked second in this challenge, that do not rely on sequence-based orthology between rat and human genes to translate pathway perturbation state but instead identify transcriptional response orthologs across a set of training conditions. The translation from rat to human accomplished by these so-called direct methods is not dependent on the particular analysis method used to identify perturbed gene sets. In contrast, machine learning-based methods require performing a pathway analysis initially and then mapping the pathway activity between organisms. Unlike most machine learning approaches, direct methods can be used to predict the activation of a human pathway for a new (test) stimuli, even when that pathway was never activated by a training stimuli. Gene expression data are available from ArrayExpress (accession E-MTAB-2091), while software implementations are available from http://bioinformaticsprb.med.wayne.edu?p=50 and http://goo.gl/hJny3h. christoph.hafemeister@nyu.edu or atarca@med.wayne.edu. Supplementary data are available at Bioinformatics online.

A comprehensive analysis of piRNAs from adult human testis and their relationship with genes and mobile elements.

BackgroundPiwi-interacting RNAs (piRNAs) are a recently discovered class of small non-coding RNAs whose best-understood function is to repress mobile element (ME) activity in animal germline. To date, nearly all piRNA studies have been conducted in model organisms and little is known about piRNA diversity, target specificity and biological function in human.ResultsHere we performed high-throughput sequencing of piRNAs from three human adult testis samples. We found that more than 81% of the ~17 million putative piRNAs mapped to ~6,000 piRNA-producing genomic clusters using a relaxed definition of clusters. A set of human protein-coding genes produces a relatively large amount of putative piRNAs from their 3’UTRs, and are significantly enriched for certain biological processes, suggestive of non-random sampling by the piRNA biogenesis machinery. Up to 16% of putative piRNAs mapped to a few hundred annotated long non-coding RNA (lncRNA) genes, suggesting that some lncRNA genes can act as piRNA precursors. Among major ME families, young families of LTR and endogenous retroviruses have a greater association with putative piRNAs than other MEs. In addition, piRNAs preferentially mapped to specific regions in the consensus sequences of several ME (sub)families and some piRNA mapping peaks showed patterns consistent with the “ping-pong” cycle of piRNA targeting and amplification.ConclusionsOverall our data provide a comprehensive analysis and improved annotation of human piRNAs in adult human testes and shed new light into the relationship of piRNAs with protein-coding genes, lncRNAs, and mobile genetic elements in human.Electronic supplementary materialThe online version of this article (doi:10.1186/1471-2164-15-545) contains supplementary material, which is available to authorized users.

The abundance of antibiotic resistance genes in human guts has correlation to the consumption of antibiotics in animal

Increasing evidence has accumulated to support that the human gut is a reservoir for antibiotic resistance genes. We previously identified more than 1000 genes displaying high similarity with known antibiotic resistance genes in the human gut gene set generated from the Chinese, Danish, and Spanish populations. Here, first, we add our new understanding of antibiotic resistance genes in the US and the Japanese populations; next, we describe the structure of a vancomycin-resistant operon in a Danish sample; and finally, we provide discussions on the correlation of the abundance of resistance genes in human gut with the antibiotic consumption in human medicine and in animal husbandry. These results, combined with those we published previously, provide comprehensive insights into the antibiotic resistance genes in the human gut microbiota at a population level.

Partitioning the Human Transcriptome Using HKera, a Novel Classifier of Housekeeping and Tissue-Specific Genes

High-throughput transcriptomic experiments have made it possible to classify genes that are ubiquitously expressed as housekeeping (HK) genes and those expressed only in selective tissues as tissue-specific (TS) genes. Although partitioning a transcriptome into HK and TS genes is conceptually problematic owing to the lack of precise definitions and gene expression profile criteria for the two, information whether a gene is an HK or a TS gene can provide an initial clue to its cellular and/or functional role. Consequently, the development of new and novel HK (TS) classification methods has been a topic of considerable interest in post-genomics research. Here, we report such a development. Our method, called HKera, differs from the others by utilizing a novel property of HK genes that we have previously uncovered, namely that the ranking order of their expression levels, as opposed to the expression levels themselves, tends to be preserved from one tissue to another. Evaluated against multiple benchmark sets of human HK genes, including one recently derived from second generation sequencing data, HKera was shown to perform significantly better than five other classifiers that use different methodologies. An enrichment analysis of pathway and gene ontology annotations showed that HKera-predicted HK and TS genes have distinct functional roles and, together, cover most of the ontology categories. These results show that HKera is a good transcriptome partitioner that can be used to search for, and obtain useful expression and functional information for, novel HK (TS) genes.

JEPETTO: a Cytoscape plugin for gene set enrichment and topological analysis based on interaction networks

Summary: JEPETTO (Java Enrichment of Pathways Extended To TOpology) is a Cytoscape 3.x plugin performing integrative human gene set analysis. It identifies functional associations between genes and known cellular pathways, and processes using protein interaction networks and topological analysis. The plugin integrates information from three separate web servers we published previously, specializing in enrichment analysis, pathways expansion and topological matching. This integration substantially simplifies the analysis of user gene sets and the interpretation of the results. We demonstrate the utility of the JEPETTO plugin on a set of misregulated genes associated with Alzheimer’s disease.Availability: Source code and binaries are freely available for download at http://apps.cytoscape.org/apps/jepetto, implemented in Java and multi-platform. Installable directly via Cytoscape plugin manager. Released under the GNU General Public Licence.Contact: jepetto.plugin@gmail.comSupplementary information: Supplementary data are available at Bioinformatics online.

Genes with Aberrant Expression in Murine Preneoplastic Intestine Show Epigenetic and Expression Changes in Normal Mucosa of Colon Cancer Patients

An understanding of early genetic/epigenetic changes in colorectal cancer would aid in diagnosis and prognosis. To identify these changes in human preneoplastic tissue, we first studied our mouse model in which Mthfr⁺/⁻ BALB/c mice fed folate-deficient diets develop intestinal tumors in contrast to Mthfr⁺/⁺ BALB/c mice fed control diets. Transcriptome profiling was performed in normal intestine from mice with low or high tumor susceptibility. We identified 12 upregulated and 51 downregulated genes in tumor-prone mice. Affected pathways included retinoid acid synthesis, lipid and glucose metabolism, apoptosis and inflammation. We compared murine candidates from this microarray analysis, and murine candidates from an earlier strain-based comparison, with a set of human genes that we had identified in previous methylome profiling of normal human colonic mucosa, from colorectal cancer patients and controls. From the extensive list of human methylome candidates, our approach uncovered five orthologous genes that had shown changes in murine expression profiles (PDK4, SPRR1A, SPRR2A, NR1H4, and PYCARD). The human orthologs were assayed by bisulfite-pyrosequencing for methylation at 14 CpGs. All CpGs exhibited significant methylation differences in normal mucosa between colorectal cancer patients and controls; expression differences for these genes were also observed. PYCARD and NR1H4 methylation differences showed promise as markers for presence of polyps in controls. We conclude that common pathways are disturbed in preneoplastic intestine in our animal model and morphologically normal mucosa of patients with colorectal cancer, and present an initial version of a DNA methylation-based signature for human preneoplastic colon.

From Genome Sequencing to Bedside

To summarize excellent current research in the field of Bioinformatics and Translational Informatics with application in the health domain and evidence-based medicine. We provide a synopsis of the articles selected for the IMIA Yearbook 2013, from which we attempt to derive a synthetic overview of current and future activities in the field. Three steps of selection were performed by querying PubMed and Web of Science. A first set of 5,549 articles was refined into a second set of 1,272 articles from which 15 articles were retained for peer-review. The selection and evaluation process of this Yearbook's section on Bioinformatics and Translational Informatics yielded four excellent articles regarding the Human Genome and Medicine. Exploiting genomic data depends on having the appropriate reference annotation available. In the first article, the goal of the GENCODE Consortium is to produce and publish The GENCODE human reference gene set. As a result it is composed by merged manual and automatic annotations, which are frequently updated from public experimental databases. The quality of genome sequencing is platform-dependant. In the second article, a generic database independent from the sequencing technologies, Huvariome, can help to identify errors and inconsistencies in sequencing. To understand complex diseases of patients it will be of great importance to detect rare gene variants. This is the aim of the third study. Finally, in the last article, the plasma's DNA of healthy individual and patients suffering from cancer is compared. The current research activities attest to the continuous convergence of Bioinformatics and Medical Informatics for clinical practice. For instance, a direct use of high throughput sequencing technologies for patients could aid the diagnosis of complex diseases (such as cancer) without invasive surgery (such as biopsy) but only with blood analysis. However, ongoing genomic tests will generate massive amounts of data and will imply new trends in the near future: "Big Data" and smart health management.

Genomics analysis of potassium channel genes in songbirds reveals molecular specializations of brain circuits for the maintenance and production of learned vocalizations

BackgroundA fundamental question in molecular neurobiology is how genes that determine basic neuronal properties shape the functional organization of brain circuits underlying complex learned behaviors. Given the growing availability of complete vertebrate genomes, comparative genomics represents a promising approach to address this question. Here we used genomics and molecular approaches to study how ion channel genes influence the properties of the brain circuitry that regulates birdsong, a learned vocal behavior with important similarities to human speech acquisition. We focused on potassium (K-)Channels, which are major determinants of neuronal cell excitability.Starting with the human gene set of K-Channels, we used cross-species mRNA/protein alignments, and syntenic analysis to define the full complement of orthologs, paralogs, allelic variants, as well as novel loci not previously predicted in the genome of zebra finch (Taeniopygia guttata). We also compared protein coding domains in chicken and zebra finch orthologs to identify genes under positive selective pressure, and those that contained lineage-specific insertions/deletions in functional domains. Finally, we conducted comprehensive in situ hybridizations to determine the extent of brain expression, and identify K-Channel gene enrichments in nuclei of the avian song system.ResultsWe identified 107 K-Channel finch genes, including 6 novel genes common to non-mammalian vertebrate lineages. Twenty human genes are absent in songbirds, birds, or sauropsids, or unique to mammals, suggesting K-Channel properties may be lineage-specific. We also identified specific family members with insertions/deletions and/or high dN/dS ratios compared to chicken, a non-vocal learner. In situ hybridization revealed that while most K-Channel genes are broadly expressed in the brain, a subset is selectively expressed in song nuclei, representing molecular specializations of the vocal circuitry.ConclusionsTogether, these findings shed new light on genes that may regulate biophysical and excitable properties of the song circuitry, identify potential targets for the manipulation of the song system, and reveal genomic specializations that may relate to the emergence of vocal learning and associated brain areas in birds.

Functional analysis of human cancer-associated genes and their association with the testes and epididymis

Human cancer-associated UniGene sets (NCBI GeneBank) provide a platform for identifying differentially-expressed genes in human cancers. The present study identified and characterized a set of human cancer-associated genes using the Digital Differential Display (DDD) and functional analysis tools. A total of 1,904 genes were differentially expressed in 15 cancer types, including genes that had been previously shown to be specific in certain human cancers. A total of 274 genes were uniquely expressed in certain cancer types, including 37 genes that were highly expressed in the human testes and epididymis. These genes mainly functioned as ribosomal proteins, enzymes, receptors, secretory proteins and cell adhesion molecules. The most common domains that were encoded by the cancer-associated genes were those of cytochrome P450 CYP2D6, serpin and apolipoprotein A-I. A further gene ontology (GO) enrichment analysis revealed seven major functional clusters, which corresponded to the enriched pathways involved in cancer. The present study provides a source of cancer-associated genes and their functions. The results provide new insights into cancer biology and the involvement of highly-expressed epididymal genes in cancer biomarkers.

Human interactome resource and gene set linkage analysis for the functional interpretation of biologically meaningful gene sets

A molecular interaction network can be viewed as a network in which genes with related functions are connected. Therefore, at a systems level, connections between individual genes in a molecular interaction network can be used to infer the collective functional linkages between biologically meaningful gene sets. We present the human interactome resource and the gene set linkage analysis (GSLA) tool for the functional interpretation of biologically meaningful gene sets observed in experiments. GSLA determines whether an observed gene set has significant functional linkages to established biological processes. When an observed gene set is not enriched by known biological processes, traditional enrichment-based interpretation methods cannot produce functional insights, but GSLA can still evaluate whether those genes work in concert to regulate specific biological processes, thereby suggesting the functional implications of the observed gene set. The quality of human interactome resource and the utility of GSLA are illustrated with multiple assessments. http://www.cls.zju.edu.cn/hir/

Comparative RNA-seq analysis in the unsequenced axolotl: the oncogene burst highlights early gene expression in the blastema.

The salamander has the remarkable ability to regenerate its limb after amputation. Cells at the site of amputation form a blastema and then proliferate and differentiate to regrow the limb. To better understand this process, we performed deep RNA sequencing of the blastema over a time course in the axolotl, a species whose genome has not been sequenced. Using a novel comparative approach to analyzing RNA-seq data, we characterized the transcriptional dynamics of the regenerating axolotl limb with respect to the human gene set. This approach involved de novo assembly of axolotl transcripts, RNA-seq transcript quantification without a reference genome, and transformation of abundances from axolotl contigs to human genes. We found a prominent burst in oncogene expression during the first day and blastemal/limb bud genes peaking at 7 to 14 days. In addition, we found that limb patterning genes, SALL genes, and genes involved in angiogenesis, wound healing, defense/immunity, and bone development are enriched during blastema formation and development. Finally, we identified a category of genes with no prior literature support for limb regeneration that are candidates for further evaluation based on their expression pattern during the regenerative process.

Understanding cellular function and disease with comparative pathway analysis

Pathway analysis is important in interpreting the functional implications of high-throughput experimental results, but robust comparison across platforms and species is problematic. A new approach, Pathprinting, provides a cross-platform, cross-species comparative analysis of pathway expression signatures. This method calculates pathway-level statistics from gene expression across nearly 180,000 microarrays in the Gene Expression Omnibus. Pathprinting can accurately retrieve phenotypically similar samples and identify sets of human and mouse genes that are prognostic in cancer.See related Research paper, http://genomemedicine.com/content/5/7/68

Pathway Analysis of ChIP-Seq-Based NRF1 Target Genes Suggests a Logical Hypothesis of their Involvement in the Pathogenesis of Neurodegenerative Diseases

Nuclear respiratory factor 1 (NRF1) serves as a transcription factor that activates the expression of a wide range of nuclear genes essential for mitochondrial biogenesis and function, including mitochondrial respiratory complex subunits, heme biosynthetic enzymes, and regulatory factors involved in the replication and transcription of mitochondrial DNA. Increasing evidence indicates that mitochondrial function is severely compromised in the brains of aging-related neurodegenerative diseases. To identify the comprehensive set of human NRF1 target genes potentially relevant to the pathogenesis of neurodegenerative diseases, we analyzed the NRF1 chromatin immunoprecipitation followed by deep sequencing (ChIP-Seq) dataset retrieved from the Encyclopedia of DNA Elements (ENCODE) project. Overall, we identified 2,470 highly stringent ChIP-Seq peaks on protein-coding genes in SK-N-SH human neuroblastoma cells. They were accumulated in the proximal promoter regions with an existence of the NRF1-binding consensus sequence. The set of ChIP-Seq-based NRF1 target genes included known NRF1 targets such as EIF2S1, EIF2S2, CYCS, FMR1, FXR2, E2F6, CD47, and TOMM34. By pathway analysis, the molecules located in the core pathways related to mitochondrial respiratory function were determined to be highly enriched in NRF1 target genes. Furthermore, we found that NRF1 target genes play a pivotal role in regulation of extra-mitochondrial biological processes, including RNA metabolism, splicing, cell cycle, DNA damage repair, protein translation initiation, and ubiquitin-mediated protein degradation. We identified a panel of neurodegenerative disease-related genes, such as PARK2 (Parkin), PARK6 (Pink1), PARK7 (DJ-1), and PAELR (GPR37) for Parkinson’s disease, as well as PSENEN (Pen2) and MAPT (tau) for Alzheimer’s disease, as previously unrecognized NRF1 targets. These results suggest a logical hypothesis that aberrant regulation of NRF1 and its targets might contribute to the pathogenesis of human neurodegenerative diseases via perturbation of diverse mitochondrial and extra-mitochondrial functions.

Human disease locus discovery and mapping to molecular pathways through phylogenetic profiling

Genes with common profiles of the presence and absence in disparate genomes tend to function in the same pathway. By mapping all human genes into about 1000 clusters of genes with similar patterns of conservation across eukaryotic phylogeny, we determined that sets of genes associated with particular diseases have similar phylogenetic profiles. By focusing on those human phylogenetic gene clusters that significantly overlap some of the thousands of human gene sets defined by their coexpression or annotation to pathways or other molecular attributes, we reveal the evolutionary map that connects molecular pathways and human diseases. The other genes in the phylogenetic clusters enriched for particular known disease genes or molecular pathways identify candidate genes for roles in those same disorders and pathways. Focusing on proteins coevolved with the microphthalmia-associated transcription factor (MITF), we identified the Notch pathway suppressor of hairless (RBP-Jk/SuH) transcription factor, and showed that RBP-Jk functions as an MITF cofactor.

Objective assessment of cancer genes for drug discovery

Selecting the best targets is a key challenge for drug discovery, and achieving this effectively, efficiently and systematically is particularly important for prioritizing candidates from the sizeable lists of potential therapeutic targets that are now emerging from large-scale multi-omics initiatives, such as those in oncology. Here, we describe an objective, systematic, multifaceted computational assessment of biological and chemical space that can be applied to any human gene set to prioritize targets for therapeutic exploration. We use this approach to evaluate an exemplar set of 479 cancer-associated genes, reveal the tension between biological relevance and chemical tractability, and describe major gaps in available knowledge that could be addressed to aid objective decision-making. We also propose drug repurposing opportunities and identify potentially druggable cancer-associated proteins that have been poorly explored with regard to the discovery of small-molecule modulators, despite their biological relevance.

Systems-level approaches reveal conservation of trans-regulated genes in the rat and genetic determinants of blood pressure in humans

Human genome-wide association studies (GWAS) of hypertension identified only few susceptibility loci with large effect that were replicated across populations. The vast majority of genes detected by GWAS has small effect and the regulatory mechanisms through which these genetic variants cause disease remain mostly unclear. Here, we used comparative genomics between human and an established rat model of hypertension to explore the transcriptional mechanisms mediating the effect of genes identified in 15 hypertension GWAS. Time series analysis of radiotelemetric blood pressure (BP) was performed to assess 11 parameters of BP variation in recombinant inbred strains derived from the spontaneously hypertensive rat. BP data were integrated with ∼27 000 expression quantative trait loci (eQTLs) mapped across seven tissues, detecting >8000 significant associations between eQTL genes and BP variation in the rat. We then compiled a large catalogue of human genes from GWAS of hypertension and identified a subset of 2292 rat-human orthologous genes. Expression levels for 795 (34%) of these genes correlated with BP variation across rat tissues: 51 genes were cis-regulated, whereas 459 were trans-regulated and enriched for 'calcium signalling pathway' (P = 9.6 × 10(-6)) and 'ion channel' genes (P = 3.5 × 10(-7)), which are important determinants of hypertension. We identified 158 clusters of trans-eQTLs, annotated the underlying 'master regulator' genes and found significant over-representation in the human hypertension gene set (enrichment P = 5 × 10(-4)). We showed extensive conservation of trans-regulated genes and their master regulators between rat and human hypertension. These findings reveal that small-effect genes associated with hypertension by human GWAS are likely to exert their action through coordinate regulation of pathogenic pathways.

Correlates Between Host and Viral Transcriptional Program Associated with Different Oncolytic Vaccinia Virus Isolates

Vaccinia virus (VACV) has emerged as an attractive tool in oncolytic virotherapy. VACV replication efficiency plays a crucial role in the therapeutic outcome. However, little is known about the influence of host factors on viral replication efficiency and permissiveness of a host cell line to infection and oncolysis. In this study, replication of the attenuated VACV GLV-1h68 strain and three wild-type VACV isolates was determined in two autologous human melanoma cell lines (888-MEL and 1936-MEL). Host gene expression and viral gene expression in infected cells were evaluated via respective expression array platforms. Microarray analyses followed by sequential statistical approaches characterized human genes that change specifically due to virus infection. Viral gene transcription correlated with viral replication in a time-dependent manner. A set of human genes revealed strong correlations with the respective viral gene expression. Finally we identified a set of human genes with possible predictive value for viral replication in an independent dataset. The results demonstrate a probable correlation between viral replication, early gene expression, and the respective host response, and thus a possible involvement of human host factors in viral early replication. The characterization of human target genes that influence viral replication could help answer the question of host cell permissiveness to oncolytic virotherapy and provide important information for the development of novel recombinant vaccinia viruses with improved features to enhance replication rate and hence trigger therapeutic outcome.

Colon cancer associated genes exhibit signatures of positive selection at functionally significant positions

BackgroundCancer, much like most human disease, is routinely studied by utilizing model organisms. Of these model organisms, mice are often dominant. However, our assumptions of functional equivalence fail to consider the opportunity for divergence conferred by ~180 Million Years (MY) of independent evolution between these species. For a given set of human disease related genes, it is therefore important to determine if functional equivalency has been retained between species. In this study we test the hypothesis that cancer associated genes have different patterns of substitution akin to adaptive evolution in different mammal lineages.ResultsOur analysis of the current literature and colon cancer databases identified 22 genes exhibiting colon cancer associated germline mutations. We identified orthologs for these 22 genes across a set of high coverage (>6X) vertebrate genomes. Analysis of these orthologous datasets revealed significant levels of positive selection. Evidence of lineage-specific positive selection was identified in 14 genes in both ancestral and extant lineages. Lineage-specific positive selection was detected in the ancestral Euarchontoglires and Hominidae lineages for STK11, in the ancestral primate lineage for CDH1, in the ancestral Murinae lineage for both SDHC and MSH6 genes and the ancestral Muridae lineage for TSC1.ConclusionIdentifying positive selection in the Primate, Hominidae, Muridae and Murinae lineages suggests an ancestral functional shift in these genes between the rodent and primate lineages. Analyses such as this, combining evolutionary theory and predictions - along with medically relevant data, can thus provide us with important clues for modeling human diseases.

A simple method for analyzing exome sequencing data shows distinct levels of nonsynonymous variation for human immune and nervous system genes.

To measure the strength of natural selection that acts upon single nucleotide variants (SNVs) in a set of human genes, we calculate the ratio between nonsynonymous SNVs (nsSNVs) per nonsynonymous site and synonymous SNVs (sSNVs) per synonymous site. We transform this ratio with a respective factor f that corrects for the bias of synonymous sites towards transitions in the genetic code and different mutation rates for transitions and transversions. This method approximates the relative density of nsSNVs (rdnsv) in comparison with the neutral expectation as inferred from the density of sSNVs. Using SNVs from a diploid genome and 200 exomes, we apply our method to immune system genes (ISGs), nervous system genes (NSGs), randomly sampled genes (RSGs), and gene ontology annotated genes. The estimate of rdnsv in an individual exome is around 20% for NSGs and 30–40% for ISGs and RSGs. This smaller rdnsv of NSGs indicates overall stronger purifying selection. To quantify the relative shift of nsSNVs towards rare variants, we next fit a linear regression model to the estimates of rdnsv over different SNV allele frequency bins. The obtained regression models show a negative slope for NSGs, ISGs and RSGs, supporting an influence of purifying selection on the frequency spectrum of segregating nsSNVs. The y-intercept of the model predicts rdnsv for an allele frequency close to 0. This parameter can be interpreted as the proportion of nonsynonymous sites where mutations are tolerated to segregate with an allele frequency notably greater than 0 in the population, given the performed normalization of the observed nsSNV to sSNV ratio. A smaller y-intercept is displayed by NSGs, indicating more nonsynonymous sites under strong negative selection. This predicts more monogenically inherited or de-novo mutation diseases that affect the nervous system.