Discovery Of Genetic Variants Research Articles

Clinical-grade whole genome sequencing-based haplarithmisis enables all forms of preimplantation genetic testing

High-throughput sequencing technologies have increasingly led to discovery of disease-causing genetic variants, primarily in postnatal multi-cell DNA samples. However, applying these technologies to preimplantation genetic testing (PGT) in nuclear or mitochondrial DNA from single or few-cells biopsied from in vitro fertilised (IVF) embryos is challenging. PGT aims to select IVF embryos without genetic abnormalities. Although genotyping-by-sequencing (GBS)-based haplotyping methods enabled PGT for monogenic disorders (PGT-M), structural rearrangements (PGT-SR), and aneuploidies (PGT-A), they are labour intensive, only partially cover the genome and are troublesome for difficult loci and consanguineous couples. Here, we devise a simple, scalable and universal whole genome sequencing haplarithmisis-based approach enabling all forms of PGT in a single assay. In a comparison to state-of-the-art GBS-based PGT for nuclear DNA, shallow sequencing-based PGT, and PCR-based PGT for mitochondrial DNA, our approach alleviates technical limitations by decreasing whole genome amplification artifacts by 68.4%, increasing breadth of coverage by at least 4-fold, and reducing wet-lab turn-around-time by ~2.5-fold. Importantly, this method enables trio-based PGT-A for aneuploidy origin, an approach we coin PGT-AO, detects translocation breakpoints, and nuclear and mitochondrial single nucleotide variants and indels in base-resolution.

Metadata-guided feature disentanglement for functional genomics.

With the development of high-throughput technologies, genomics datasets rapidly grow in size, including functional genomics data. This has allowed the training of large Deep Learning (DL) models to predict epigenetic readouts, such as protein binding or histone modifications, from genome sequences. However, large dataset sizes come at a price of data consistency, often aggregating results from a large number of studies, conducted under varying experimental conditions. While data from large-scale consortia are useful as they allow studying the effects of different biological conditions, they can also contain unwanted biases from confounding experimental factors. Here, we introduce Metadata-guided Feature Disentanglement (MFD)-an approach that allows disentangling biologically relevant features from potential technical biases. MFD incorporates target metadata into model training, by conditioning weights of the model output layer on different experimental factors. It then separates the factors into disjoint groups and enforces independence of the corresponding feature subspaces with an adversarially learned penalty. We show that the metadata-driven disentanglement approach allows for better model introspection, by connecting latent features to experimental factors, without compromising, or even improving performance in downstream tasks, such as enhancer prediction, or genetic variant discovery. The code will be made available at https://github.com/HealthML/MFD.

Applying an ELSI lens to real-world data and novel genomic insights for personalized mental healthcare.

Improving the understanding of the complex relationship between genetic predispositions, environmental influences, and sociocultural factors in the development and progression of mental illness is crucial for optimizing treatment efficacy and addressing longstanding health disparities. This paper discusses the ethical, legal, and social implications (ELSI) of recent advancements in biomedical research, particularly in genome-wide association studies (GWAS), phenome-wide association studies (PheWAS), and genome-wide environment interaction studies (GWEIS). Despite recent scientific progresses, challenges such as inadequate study methodology (e.g., correlational studies) and lack of diversity within study samples persist. Recent discoveries of several genetic variants of diseases, could augment and improve, or even challenge, existing understanding of the onset and management of mental illness. Leveraging real-world data (RWD), including electronic health record data (EHRs) focused on social determinant of health alongside biobank data, offers further opportunities to enhance the understanding of gene-environment interactions and inform efforts for reducing disparities in mental healthcare. Increased knowledge can support timely, holistic, evidence-based, and personalized care. Addressing ELSI considerations and maximizing the use of RWD is essential for advancing ethical and inclusive psychiatric genetics research, ultimately improving patient outcomes and promoting equitable access to evidence-based treatments.

Monogenic interferon-mediated diseases: novel phenotype and genotype characteristics from a Saudi population.

IFN-mediated diseases are mendelian innate immunodysregulatory disorders that present early in life with fevers, sterile organ inflammation, and a high type-I IFN-response gene signature in peripheral blood cells. To date, monumental discoveries of novel genetic variants with various phenotypic features have been recognised. We aimed to describe the genotype and phenotype findings in Saudi children diagnosed with autoinflammatory interferonopathy and to report novel findings. This is a descriptive retrospective cohort study of children with genetically confirmed type I interferonopathies. Medical records were reviewed for demographic, family history, clinical and laboratory data. All patients underwent genetic testing. A total of 20 patients (11 females) were included in the study. Sixteen patients (80%) presented within the first 2 years. The median age of disease onset was 0.87 years (IQR: 0.5-2) and the median age of diagnosis was 4.5 years (IQR: 2-7.5). The rates of consanguinity and family history of affected members were high (88% and 47%, respectively). Among the cohort of patients, whole exome sequencing was conducted for 15 patients. Three patients underwent targeted gene tests, and 2 patients had a leukoencephalopathy genetic panel. Eight patients were diagnosed with Aicardi-Goutières syndrome, attributed to variants in the RNASEH2A, RNASEH2C, and IFIH1 genes. Additionally, 2 patients were identified with STING-associated vasculopathy with onset in infancy linked to the TMEM173 variant. One patient exhibited chronic atypical neutrophilic dermatosis with lipodystrophy and elevated temperature due to PSMB8, and another patient had DNase II. Moreover, 8 patients presented with rare interferonopathy conditions, including three with ISG15, 3 with ZNFX1, 1 with the SOCS1 variant, and 1 the STAT1 variant. Of 12 variants, six (50%) found to have novel genetic variants. The most frequent features were fever (75%), neurology (70%), mucocutaneous (60%), gastrointestinal (50%), and pulmonary (50%). Hypogammaglobinaemia and recurrent infections were seen in (45%) and (20%), respectively. Fifteen patients (75%) had elevated inflammatory markers. The majority of patients received intensive treatment, including corticosteroids, JAK inhibitors, IVIG, and various immunosuppressive agents. Despite these interventions, a partial response to treatment was observed, and cumulative disease damage primarily manifested as growth failure and developmental delay. Our findings support the previous reports; early-onset fever, neurology, and respiratory features should raise the suspicion of interferonopathies. However, there is eminent evidence of phenotypic variability. Our data also expanded the spectrum of clinical findings in relation to novel genetic variants.

O-057 Newly identified female mutations causing failed fertilization

Abstract Over the past decade, advancements in next-generation sequencing technology, alongside reduced costs, and the rising demand for infertility medical care, have resulted in the discovery of new genes and genetic variants linked to infertility conditions. Phenotypes of ICSI failure, such as oocyte maturation arrest (OMA), fertilization failure (FF) and embryo developmental arrest (EDA), can now be attributed to male or female genetic causes. This represents a transformative shift in patient treatment, allowing the identification of some cases previously classified as unexplained infertility, thereby reducing patient stress. Moreover, it facilitates personalized treatment recommendations, as well as paves the way for the exploration of novel treatment options, thus expanding research opportunities. This talk will review the genetic causes of FF following ICSI, with the main focus on the newly identified female causes, as well as give an update on current diagnostic tests and treatment options for this infertility condition. FF after ICSI still occurs in 1-3% of ICSI cycles, primarily due to oocyte activation deficiency (OAD). Defects in the male PLCζ protein, responsible of inducing calcium oscillations during oocyte activation, have long been known as the leading cause of OAD. Recent discoveries have identified genetic variants in the male genes ACTL7A, ACTL9 and IQCN, which also reduce PLCζ protein content in sperm cells and thus, contribute to FF after ICSI. Additionally, for the first time in 2018, mutations in a female gene (WEE2) crucial for oocyte activation were identified. WEE2 is an oocyte kinase that acts downstream the calcium release during fertilization. Interestingly, genetic variants in other female genes, such as PATL2, TUBB8 and CDC20 associated mainly to OMA and TLE6 and NLRP5 associated mainly to EDA, have also been described to cause failed fertilization in some patients. Determining whether the deficiency lies in sperm- or oocyte-related genes is crucial for tailoring the most effective treatment for FF after ICSI. For sperm-related factors, assisted oocyte activation (AOA), which consists in the artificial induction of calcium oscillations using calcium ionophores, has proven highly beneficial. However, most patients with oocyte-factors do not benefit from AOA (e.g. patients with WEE2 variants). In this regard, wild-type cRNA injection of the defected protein has been shown to rescue fertilization. A more generalist approach, such as maternal spindle transfer, which consists in replacing poor-quality oocyte cytoplasm with healthy cytoplasm from a donor oocyte, represents a potential treatment for these patients, as recently demonstrated in infertile females with repeated IVF failures. Nevertheless, further research into the safety of these procedures is needed before clinical application, and for now, gamete donation should be considered when facing female-related FF.

Clinical Impact of Telomere Length Testing for Interstitial Lung Disease

BackgroundShortened telomere length (TL) is a genomic risk factor for fibrotic interstitial lung disease (ILD), but its role in clinical management is unknown. Research QuestionWhat is the clinical impact of TL testing on the management of ILD? Study Design and MethodsPatients were evaluated in the Columbia University ILD clinic and underwent CLIA-certified TL testing by flow cytometry and fluorescence in-situ hybridization (FlowFISH) as part of clinical management. Short TL was defined as below the 10th age-adjusted percentile for either granulocytes or lymphocytes by FlowFISH. Patients were offered genetic counseling and testing if they had short TL or a family history of ILD. FlowFISH TL was compared against research qPCR TL measurement. ResultsA total of 108 patients underwent TL testing, including those with clinical features of short telomere syndrome such as familial pulmonary fibrosis (50%) or extrapulmonary manifestations in the patient (25%) or a relative (41%). The overall prevalence of short TL was 46% and was similar across clinical ILD diagnoses. The number of short telomere clinical features was independently associated with detecting short TL (OR 2.00, 95% CI [1.27, 3.32]). TL testing led to clinical management changes for 35 (32%) patients, most commonly resulting in reduction or avoidance of immunosuppression. Of the patients who underwent genetic testing (n=34), a positive or candidate diagnostic finding in telomere-related genes was identified in 10 (29%) patients. Inclusion of TL testing below the 1st percentile helped reclassify 8 of 9 variants of uncertain significance (VUS) into actionable findings. The qPCR test correlated with FlowFISH, but age-adjusted percentile cutoffs may not be equivalent between the two assays. InterpretationIncorporating TL testing in ILD impacted clinical management and led to the discovery of new actionable genetic variants.

Case-Case Genome-Wide Analyses Identify Subtype-Informative Variants That Confer Risk for Breast Cancer.

Breast cancer includes several subtypes with distinct characteristic biological, pathologic, and clinical features. Elucidating subtype-specific genetic etiology could provide insights into the heterogeneity of breast cancer to facilitate the development of improved prevention and treatment approaches. In this study, we conducted pairwise case-case comparisons among five breast cancer subtypes by applying a case-case genome-wide association study (CC-GWAS) approach to summary statistics data of the Breast Cancer Association Consortium. The approach identified 13 statistically significant loci and eight suggestive loci, the majority of which were identified from comparisons between triple-negative breast cancer (TNBC) and luminal A breast cancer. Associations of lead variants in 12 loci remained statistically significant after accounting for previously reported breast cancer susceptibility variants, among which, two were genome-wide significant. Fine mapping implicated putative functional/causal variants and risk genes at several loci, e.g., 3q26.31/TNFSF10, 8q22.3/NACAP1/GRHL2, and 8q23.3/LINC00536/TRPS1, for TNBC as compared with luminal cancer. Functional investigation further identified rs16867605 at 8q22.3 as a SNP that modulates the enhancer activity of GRHL2. Subtype-informative polygenic risk scores (PRS) were derived, and patients with a high subtype-informative PRS had an up to two-fold increased risk of being diagnosed with TNBC instead of luminal cancers. The CC-GWAS PRS remained statistically significant after adjusting for TNBC PRS derived from traditional case-control GWAS in The Cancer Genome Atlas and the African Ancestry Breast Cancer Genetic Consortium. The CC-GWAS PRS was also associated with overall survival and disease-specific survival among patients with breast cancer. Overall, these findings have advanced our understanding of the genetic etiology of breast cancer subtypes, particularly for TNBC. Significance: The discovery of subtype-informative genetic risk variants for breast cancer advances our understanding of the etiologic heterogeneity of breast cancer, which could accelerate the identification of targets and personalized strategies for prevention and treatment.

Prediction of adverse drug reactions due to genetic predisposition using deep neural networks.

Drug development is a long and costly process, often limited by the toxicity and adverse drug reactions (ADRs) caused by drug candidates. Even on the market, some drugs can cause strong ADRs that can vary depending on an individual polymorphism. The development of Genome-wide association studies (GWAS) allowed the discovery of genetic variants of interest that may cause these effects. In this study, the objective was to investigate a deep learning approach to predict genetic variations potentially related to ADRs. We used single nucleotide polymorphisms (SNPs) information from dbSNP to create a network based on ADR-drug-target-mutations and extracted matrixes of interaction to build deep Neural Networks (DNN) models. Considering only information about mutations known to impact drug efficacy and drug safety from PharmGKB and drug adverse reactions based on the MedDRA System Organ Classes (SOCs), these DNN models reached a balanced accuracy of 0.61 in average. Including molecular fingerprints representing structural features of the drugs did not improve the performance of the models. To our knowledge, this is the first model that exploits DNN to predict ADR-drug-target-mutations. Although some improvements are suggested, these models can be of interest to analyze multiple compounds over all of the genes and polymorphisms information accessible and thus pave the way in precision medicine.

Genetic association analysis of human median voice pitch identifies a common locus for tonal and non-tonal languages

The genetic influence on human vocal pitch in tonal and non-tonal languages remains largely unknown. In tonal languages, such as Mandarin Chinese, pitch changes differentiate word meanings, whereas in non-tonal languages, such as Icelandic, pitch is used to convey intonation. We addressed this question by searching for genetic associations with interindividual variation in median pitch in a Chinese major depression case-control cohort and compared our results with a genome-wide association study from Iceland. The same genetic variant, rs11046212-T in an intron of the ABCC9 gene, was one of the most strongly associated loci with median pitch in both samples. Our meta-analysis revealed four genome-wide significant hits, including two novel associations. The discovery of genetic variants influencing vocal pitch across both tonal and non-tonal languages suggests the possibility of a common genetic contribution to the human vocal system shared in two distinct populations with languages that differ in tonality (Icelandic and Mandarin).

Regulation of human microglial gene expression and function via RNAase-H active antisense oligonucleotides in vivo in Alzheimer’s disease

BackgroundMicroglia play important roles in maintaining brain homeostasis and neurodegeneration. The discovery of genetic variants in genes predominately or exclusively expressed in myeloid cells, such as Apolipoprotein E (APOE) and triggering receptor expressed on myeloid cells 2 (TREM2), as the strongest risk factors for Alzheimer’s disease (AD) highlights the importance of microglial biology in the brain. The sequence, structure and function of several microglial proteins are poorly conserved across species, which has hampered the development of strategies aiming to modulate the expression of specific microglial genes. One way to target APOE and TREM2 is to modulate their expression using antisense oligonucleotides (ASOs).MethodsIn this study, we identified, produced, and tested novel, selective and potent ASOs for human APOE and TREM2. We used a combination of in vitro iPSC-microglia models, as well as microglial xenotransplanted mice to provide proof of activity in human microglial in vivo.ResultsWe proved their efficacy in human iPSC microglia in vitro, as well as their pharmacological activity in vivo in a xenografted microglia model. We demonstrate ASOs targeting human microglia can modify their transcriptional profile and their response to amyloid-β plaques in vivo in a model of AD.ConclusionsThis study is the first proof-of-concept that human microglial can be modulated using ASOs in a dose-dependent manner to manipulate microglia phenotypes and response to neurodegeneration in vivo.

Large-Scale Cytochrome C Oxidase Subunit I Gene Data Analysis for the Development of a Multiplex Polymerase Chain Reaction Test Capable of Identifying Biting Midge Vector Species and Haplotypes (Diptera: Ceratopogonidae) of the Culicoides Subgenus Avaritia Fox, 1955.

The emergence of culicoid-transmitted bluetongue and Schmallenberg viruses in several European countries demonstrated the ability of indigenous biting midge species to transmit pathogens. Entomologic research programs identified members of the Obsoletus Group (Culicoides subgenus Avaritia) as keyplayers in disease epidemiology in Europe. However, morphological identification of potential vectors is challenging due to the recent discovery of new genetic variants (haplotypes) of C. obsoletus sensu stricto (s.s.), forming distinct clades. In this study, 4422 GenBank entries of the mitochondrial cytochrome c oxidase subunit I (COI) gene of subgenus Avaritia members of the genus Culicoides were analyzed to develop a conventional multiplex PCR, capable of detecting all vector species and clades of the Western Palearctic in this subgenus. Numerous GenBank entries incorrectly assigned to a species were identified, analyzed and reassigned. The results suggest that the three C. obsoletus clades represent independent species, whereas C. montanus should rather be regarded as a genetic variant of C. obsoletus s.s. Based on these findings, specific primers were designed and validated with DNA material from field-caught biting midges which achieved very high diagnostic sensitivity (100%) when compared to an established reference PCR (82.6%).

Lessons Learned from Translating Genome Sequencing to Clinical Routine: Understanding the Accuracy of a Diagnostic Pipeline.

The potential of genome sequencing (GS), which allows detection of almost all types of genetic variation across nearly the entire genome of an individual, greatly expands the possibility for diagnosing genetic disorders. The opportunities provided with this single test are enticing to researchers and clinicians worldwide for human genetic research as well as clinical application. Multiple studies have highlighted the advantages of GS for genetic variant discovery, emphasizing its added value for routine clinical use. We have implemented GS as first-line genetic testing for patients with rare diseases. Here, we report on our experiences in establishing GS as a reliable diagnostic method for almost all types of genetic disorders, from validating diagnostic accuracy of sequencing pipelines to clinical implementation in routine practice.

Glaucoma pharmacogenetics. Role in neuroprotection

Glaucoma is a blinding disease that can occur at all ages, with Mendelian inheritance typical for the rare early onset disease (before age 40) and complex inheritance evident in common adult‐onset forms of disease. Genetic and genomic studies, including genome‐wide association studies (GWAS) have identified new genetic variants contributing to glaucoma in the last years. Genes correlating with glaucoma risk may involve: ocular development, intraocular pressure, trabecular meshwork function or some of them are directly related to optic nerve susceptibility such as retinal ganglion cell membranes, mitochondrial function, reactive oxygen species production and management, and mechanisms controlling apoptosis. These findings are providing new insights into the underlying molecular mechanisms responsible for glaucoma that could eventually lead to novel gene‐based therapies, including strategies for neuroprotection.We present our study about the genetic analysis of a cohort of Spanish patients with primary open‐angle glaucoma to determine the contribution of rare variants associated with this disease through next generation sequencing (NGS) glaucoma gene panel, as a future method of diagnosis and early treatment. We found some rare variants associated with optic disk parameters and function in some families with high and normal tension glaucoma with allelic frequencies significantly higher than the frequency in the general population by NGS. Those rare variants are located in SIX6, CARD10, MFN1, OPTN, and WDR36 glaucoma‐related genes.These risk variants have been associated to the alteration of retinal ganglion cells through different mechanisms, thereby increasing the risk of glaucoma‐associated vision loss.The discovery of new genetic variants associated with augmented susceptibility of the optic nerve may in the future open the door to designing new neuroprotection gene therapies aimed at repairing damaged genes or providing them through different vectors.

NetPRISBI‐AD: Network‐based Polygenic Risk Scoring model with Brain Imaging for Alzheimer’s Disease

AbstractBackgroundThe amount of gray matter can measure the structural characteristics of the brain, and the deterioration of brain function can be evaluated accordingly. In particular, the lower the amount of gray matter in areas involved in memory, the lower the cognitive function, eventually affecting the onset of dementia, such as Alzheimer’s disease (AD). Although there are various factors for changes in gray matter volume, genetic factors are also closely related. In addition, genetic factors are not only independently involved in biological activities, but also have complex interactions.MethodIn this study, we construct a SNP network that reflects interactions between SNPs and propose a model that can predict the risk score for AD and the gray matter volume of the brain by region from the SNP network. First, in the SNP network, interactions between SNPs are measured as similarities based on the linkage disequilibrium score. Then, the proposed method constructs a regression model to predict brain volume and risk scores for AD using feature propagation, which is conducted to refine existing genetic variant information.ResultThe proposed method was applied to data including both genetic and brain imaging information among UK Biobank (UKBB; 8,273 cases and 25,353 controls, total 33,626 participants) and Alzheimer’s Disease Neuroimaging Initiative (ADNI; 202 cases and 720 controls, total 922 participants) data. The results were cross‐validated from the two datasets and compared with other models including the conventional polygenic risk score with pruning and thresholding (PRS‐PT) model. Compared to the other methods, the proposed method showed outstanding performance and the discovery of genetic variants and brain regions affecting Alzheimer’s disease.ConclusionWe proposed the framework for predicting the volume of the brain with refined features of SNP that reflects the interactions between elements. The results revealed that genetic relations and inferring brain volumes are crucial for enhancing AD risk prediction. Furthermore, through the proposed method, it is expected that understanding and interpreting the phased mechanism of the onset of AD through brain lesions from genetic variants will be possible.

Assessment of multi-trait analysis of GWAS (MTAG) for discovery of novel genetic variants and mechanistic insight in common cardiovascular diseases

Abstract Background Variability in cardiovascular conditions is partly explained by common genomic variation identifiable by genome-wide association studies (GWAS). Genetic substrate may overlap in certain entities, this being quantified by genetic correlation. We aimed to leverage multi-trait analysis of GWAS (MTAG), (1) which boosts statistical power by joint analysis of genetically correlated traits, to improve genetic loci discovery in 3 common cardiovascular diseases: atrial fibrillation (AF), coronary artery disease (CAD), and heart failure (HF). Methods and Results Cardiovascular phenotypes with available GWAS summary statistics most correlated with the disease of interest were analysed jointly by MTAG (workflow depicted in Figure 1). These included body mass index and HF for AF (2); HF, LDL-cholesterol, and systolic blood pressure for CAD (3); and AF, CAD, and dilated cardiomyopathy for HF (4). MTAG increased statistical power for all 3 disease GWAS and allowed the identification of 19 new genomic loci for AF, 89 for CAD and 52 for HF (at a GWAS significance level P<5x10-8) (Figure 2). New loci were defined as not previously identified in the single trait original GWAS. Consistently, 19/19, 85/89 and 48/52 of new loci reached nominal significance (P<0.05) in the original studies; and 37%, 44% and 36% of new loci have been associated with AF, CAD and HF in GWAS and phenome wide association studies (PheWAS) in independent cohorts. MTAG summary statistics annotation and functional analysis integrated the distance to the canonical transcriptional start site, chromatin interaction experiments, quantitative molecular phenotype trait experiments and in silico functional prediction through OpenTargets Genetics. MAGMA gene-set functional analysis of the new MTAG results showed 87, 27 and 24 significant associated pathways to AF, CAD and HF respectively. Among the top associations, cardiac depolarization, repolarization, and muscle contraction in AF; macromolecular complex remodeling, triglyceride, chylomicron and LDL metabolism in CAD; and muscle structure, tissue development and RNA transcription initiation in HF. Among novel relevant genes in AF, SRR on chromosome 16 is involved in central nervous system development through regulation of NMDA receptors. This locus has been previously associated with QRS in another GWAS and SRR is related to reduction in heart rate variability and AF enhancement in rats. In CAD, RSPO3 and JAG1 genes, on chromosomes 6 and 20 respectively, have a relevant role in angiogenesis, where RSPO3 is a crucial regulator of coronary artery formation in the developing heart. Conclusions MTAG allows the discovery of new trait-specific loci involved in the pathogenesis of AF, CAD, and HF congruent with the mechanisms of each disease and consistent with independent external cohort PheWAS and GWAS. Thus, MTAG is an interesting tool to unravel relevant mechanisms and potential therapeutic targets in common cardiovascular diseases.

Next-Generation Sequencing to Study the DNA Interaction.

Next-generation sequencing (NGS) has transformed genomics by allowing researchers to sequence DNA and RNA at highest speed, accuracy, and cost-effectiveness. Researchers investigate DNA interactions with the help next-generation sequencing with a great deal of information. Over the last decade, NGS technologies have advanced significantly, with the development of several platforms, including Illumina, PacBio, and Oxford Nanopore, each offering distinct advantages and uses. The use of next-generation sequencing (NGS) has aided in the discovery of genetic variations, gene expression patterns, and epigenetic modifications connected with a variety of diseases, including cancer, neurological disorders, and infectious diseases. By identifying these regions, we can control the expression of genes, cellular signaling pathways, and other key biological processes. NGS is an effective method for researching DNA interactions that has completely transformed the area of genomics. NGS has also played an important part in personalized medicine, enabling the discovery of disease-causing mutations and the creation of targeted medicines. Finally, NGS has transformed the field of genomics, resulting in new discoveries and applications in medicine, environmental sciences, and other fields.

Integrating non-mammalian model organisms in the diagnosis of rare genetic diseases in humans.

Next-generation sequencing technology has rapidly accelerated the discovery of genetic variants of interest in individuals with rare diseases. However, showing that these variants are causative of the disease in question is complex and may require functional studies. Use of non-mammalian model organisms - mainly fruitflies (Drosophila melanogaster), nematode worms (Caenorhabditis elegans) and zebrafish (Danio rerio) - enables the rapid and cost-effective assessment of the effects of gene variants, which can then be validated in mammalian model organisms such as mice and in human cells. By probing mechanisms of gene action and identifying interacting genes and proteins in vivo, recent studies in these non-mammalian model organisms have facilitated the diagnosis of numerous genetic diseases and have enabled the screening and identification of therapeutic options for patients. Studies in non-mammalian model organisms have also shown that the biological processes underlying rare diseases can provide insight into more common mechanisms of disease and the biological functions of genes. Here, we discuss the opportunities afforded by non-mammalian model organisms, focusing on flies, worms and fish, and provide examples of their use in the diagnosis of rare genetic diseases.

Actionability of unanticipated monogenic disease risks in newborn genomic screening: Findings from the BabySeq Project

Newborn genomic sequencing (NBSeq) to screen for medically important genetic information is of considerable interest but data characterizing the actionability of such findings, and the downstream medical efforts in response to discovery of unanticipated genetic risk variants, are lacking. From a clinical trial of comprehensive exome sequencing in 127 apparently healthy infants and 32 infants in intensive care, we previously identified 17 infants (10.7%) with unanticipated monogenic disease risks (uMDRs). In this analysis, we assessed actionability for each of these uMDRs with a modified ClinGen actionability semiquantitative metric (CASQM) and created radar plots representing degrees of penetrance of the condition, severity of the condition, effectiveness of intervention, and tolerability of intervention. In addition, we followed each of these infants for 3-5 years after disclosure and tracked the medical actions prompted by these findings. All 17 uMDR findings were scored as moderately or highly actionable on the CASQM (mean 9, range: 7-11 on a 0-12 scale) and several distinctive visual patterns emerged on the radar plots. In three infants, uMDRs revealed unsuspected genetic etiologies for existing phenotypes, and in the remaining 14 infants, uMDRs provided risk stratification for future medical surveillance. In 13 infants, uMDRs prompted screening for at-risk family members, three of whom underwent cancer-risk-reducing surgeries. Although assessments of clinical utility and cost-effectiveness will require larger datasets, these findings suggest that large-scale comprehensive sequencing of newborns will reveal numerous actionable uMDRs and precipitate substantial, and in some cases lifesaving, downstream medical care in newborns and their family members.

RNA-Seq-based discovery of genetic variants and allele-specific expression of two layer lines and broiler chicken.

Recent advances in the selective breeding of broilers and layers have made poultry production one of the fastest-growing industries. In this study, a transcriptome variant calling approach from RNA-seq data was used to determine population diversity between broilers and layers. In total, 200 individuals were analyzed from three different chicken populations (Lohmann Brown (LB), n = 90), Lohmann Selected Leghorn (LSL, n = 89), and Broiler (BR, n = 21). The raw RNA-sequencing reads were pre-processed, quality control checked, mapped to the reference genome, and made compatible with Genome Analysis ToolKit for variant detection. Subsequently, pairwise fixation index (F ST) analysis was performed between broilers and layers. Numerous candidate genes were identified, that were associated with growth, development, metabolism, immunity, and other economically significant traits. Finally, allele-specific expression (ASE) analysis was performed in the gut mucosa of LB and LSL strains at 10, 16, 24, 30, and 60 weeks of age. At different ages, the two-layer strains showed significantly different allele-specific expressions in the gut mucosa, and changes in allelic imbalance were observed across the entire lifespan. Most ASE genes are involved in energy metabolism, including sirtuin signaling pathways, oxidative phosphorylation, and mitochondrial dysfunction. A high number of ASE genes were found during the peak of laying, which were particularly enriched in cholesterol biosynthesis. These findings indicate that genetic architecture as well as biological processes driving particular demands relate to metabolic and nutritional requirements during the laying period shape allelic heterogeneity. These processes are considerably affected by breeding and management, whereby elucidating allele-specific gene regulation is an essential step towards deciphering the genotype to phenotype map or functional diversity between the chicken populations. Additionally, we observed that several genes showing significant allelic imbalance also colocalized with the top 1% of genes identified by the FST approach, suggesting a fixation of genes in cis-regulatory elements.

The impact of heme oxygenase-2 on pharmacological research: A bibliometric analysis and beyond.

Heme oxygenase (HO-2) is an enzyme mainly involved in the physiologic turnover of heme and intracellular gas sensing, and it is very abundant in the brain, testes, kidneys and vessels. Since 1990, when HO-2 was discovered, the scientific community has underestimated the role of this protein in health and disease, as attested by the small amount of articles published and citations received. One of the reason that have contributed to the lack of interest in HO-2 was the difficulty in upregulating or inhibiting this enzyme. However, over the last 10years, novel HO-2 agonists and antagonists have been synthesized, and the availability of these pharmacological tools should increase the appeal of HO-2 as drug target. In particular, these agonists and antagonists could help explain some controversial aspects, such as the neuroprotective versus neurotoxic roles of HO-2 in cerebrovascular diseases. Furthermore, the discovery of HO-2 genetic variants and their involvement in Parkinson's disease, in particular in males, opens new avenues for pharmacogenetic studies in gender medicine.