Whole-exome sequencing (WES) is used to selectively sequence all exons of protein-coding genes. WES is considered as a cost-effective and direct approach for identifying phenotype-associated variants in protein-coding regions and is as such situated between the traditional Sanger sequencing and whole genome sequencing (WGS). While WES is already widely used as a clinical tool in human and medical genetics, its use in veterinary medicine is currently restricted to research purposes. In this article, we aimed to provide baseline performance characteristics of a WES design to assess its suitability with future applications in veterinary clinical genetics in mind.

To assess the potential of WES in a clinical setting for dogs, 49 canine samples underwent capture, sequencing and analysis for the presence of 352 known phenotype-associated variants. The sequencing performance was compared for three types of variants, based on their size and location: single nucleotide variants (SNVs) inside exons, larger indel variants (≤20 bp) inside exons and intronic variants.

On average, 85 % and 82 % of the exonic SNPs and larger variants were sequenced at a sequencing depth of ≥ 10x in the 49 samples, respectively. In the best performing sample, 94 % of the exonic SNPs were covered at least 10x, whereas in the worst performing sample, still 71 % of the exonic SNPs had an average sequencing depth of more than 10x.

To our knowledge, this is the first report that describes the performance of a research-intended WES design if it would be used in clinical genetics. This study found that WES demonstrated high efficacy in detecting variants located within target regions, including those that were not initially included in the design. However, the performance varied across different variants. The next steps would be the development of improved designs and settings to ameliorate the results.

To investigate the exome sequencing (ES) detection rate among fetuses with congenital anomalies and describe the rates in the setting of multiple versus isolated anomalies, perinatal autopsy, and family history of a previously affected child.

A single-center retrospective chart review was conducted on 397 anomalous fetuses that underwent ES from May 2012 through December 2023. Medical record review included demographics, imaging, and genetic testing.

The overall ES diagnostic rate was 34.3%. The rate of diagnosis was 31.6% in fetuses with a single anomaly and 42.6% in fetuses with 4 or more major organ systems involved. Of the fetuses with a single anomaly, lymphatic, craniofacial, skeletal, and neurological anomalies had the highest diagnostic rate on ES. 38.6% of deceased fetuses who underwent autopsy had a genetic diagnosis. Additionally, families who had a previously affected child had a 45.5% diagnostic rate.

ES is an important tool that should be offered in pregnancies affected with congenital abnormalities or at the time of fetal demise or termination. The diagnostic rate of ES in the prenatal setting is also highly dependent on comprehensive phenotyping. With diagnostic ES results, reproductive technology and testing options are available in subsequent pregnancies.

Exome sequencing has been established as a fundamental tool in genetic diagnostics. It may also provide information about variants in genes unrelated to the primary purpose, so-called secondary findings. Especially, diagnoses of unnoticed inborn cardiac diseases are of high clinical relevance due to therapeutic options in context of prevention of sudden cardiac death.

Exome data of 9962 individuals was analysed for relevant cardiogenetic findings. Genes were selected according to ACMG recommendations for secondary findings (v.3.1). First, a filter for (likely) pathogenic variants, published in the ClinVar database, was used. Second, exome data was screened for loss of function (LoF) variants in genes in which LoF is a known disease pathomechanism. All variants were evaluated by geneticists regarding their pathogenicity.

Pathogenic or likely pathogenic variants were identified in 136 different individuals (136/9962, 1.4%), with the Low-Density Lipoprotein Receptor gene (LDLR, 24/136, 17.6%) and the Titin gene (TTN, 24/136, 17.6%), being the most frequently affected ones. 31.6% (43/136) of the identified variants had been reported beforehand, while 47.1% (64/136) had not been reported. The remaining cases (29/136, 21.3%) were part of research projects with no written reports. In 26.5% (36/136), the finding would have been missed, if only index patients and not their parents had been screened for secondary findings in case of trio ES.

As demonstrated in our study, at least one or two out of one hundred people are likely to carry a pathogenic cardiogenetic variant. Counselling geneticist and clinicians need to be aware of these findings in exome and genome sequencing. Informed consent of the patient regarding the report of secondary findings should absolutely be obtained beforehand.

Alcohol use disorder (AUD) is a leading cause of death and disability worldwide. There has been substantial progress in identifying genetic variants that underlie AUD. However, whole-exome sequencing studies of AUD have been hampered by the lack of available samples.

We analyzed whole-exome sequencing data of 4530 samples from the Yale-Penn cohort and 469,835 samples from the UK Biobank, which represent an unprecedented resource for exploring the contribution of coding variants in AUD. After quality control, 1750 African-ancestry (1142 cases) and 2039 European-ancestry (1420 cases) samples from the Yale-Penn and 6142 African-ancestry (130 cases), 415,617 European-ancestry (12,861‬ cases), and 4607 South Asian (130 cases) samples from the UK Biobank cohorts were included in the analyses.

We confirmed the well-known functional variant rs1229984 in ADH1B (p = 4.88 × 10-31) and several other variants in ADH1C. Gene-based collapsing tests that considered the high allelic heterogeneity revealed the previously unreported genes CNST (p = 1.19 × 10-6), attributable to rare variants with allele frequency < 0.001, and IFIT5 (p = 3.74 × 10-6), driven by the burden of both common and rare loss-of-function and missense variants.

This study extends our understanding of the genetic architecture of AUD by providing insights into the contribution of rare coding variants, separately and convergently with common variants in AUD.

Increasing evidence supports the involvement of inborn errors of immunity in severe infections, but little is known about the prevalence of these genetic defects in children with sepsis. Due to the limited understanding of the molecular and immunological mechanisms driving sepsis, genetic testing is rarely used in routine diagnostics to identify genetic susceptibility to the condition. We performed a prospective observational study on previously healthy children hospitalized for severe infections, including sepsis. Patients underwent immunophenotyping and whole-exome sequencing, followed by in silico analysis to identify potentially causal variants. We assembled a cohort of 194 previously healthy children, including 149 (77%) patients with severe infection and 45 (23%) with sepsis. Our cohort was marked by a high frequency of respiratory tract infections (35%), bloodstream infections (20%), and central nervous system infections (16%). The genetic investigation identified 28 potentially causal variants, 18 (64%) are classified as variants with uncertain significance, and 10 (36%) are likely pathogenic variants. Of 45 patients with sepsis, 6 (13%) had potentially causal genetic variants. Similarly, 22/149 (15%) patients with severe infection presented potentially causal genetic variants. Whole-exome sequencing predicted the impairment of various immune mechanistic pathways such as immune dysregulation defects, antibody deficiencies, and combined immunodeficiencies (18% each). We found no clear association between genetic variants and the studied parameters: organ failure, microbe identification, immunoglobulin levels, and lymphocyte subset numbers. Although whole-exome sequencing is a valuable tool for detecting inborn errors of immunity underlying sepsis and unexplained severe infections, it could be selectively recommended for patients with a strong clinical suspicion of genetic abnormalities, balancing its diagnostic value with its cost and complexity.

Skeletal dysplasia (SD) represents a series of highly heterogeneous congenital genetic diseases affecting the human skeletal system. Refined genetic diagnosis is helpful for the accurate diagnosis and prognosis evaluation of SDs.

In this study, we recruited 26 cases of SD and analyzed them with a designed sequential genetic detection. Chromosome karyotyping, microarray analysis (CMA), and whole exome sequencing (WES) techniques are performed as needed. Sanger sequencing and fluorescent quantitative PCR (QF-PCR) were used as validation methods.

A total of 16 cases (61.5%, 16/26) received positive results at various levels of testing, including one trisomy 18, four copy number variations (CNVs), and 11 sequence variations. Additionally, four novel SD-related sequence mutations were detected in this study.

Our findings provide conclusive evidence for genetic counseling of corresponding families and expand the mutation spectrum of SD. In addition, this study demonstrates that a strategy sequentially including various genetic techniques contributes to the diagnosis of highly heterogeneous genetic disorders such as SD.

The revolutionary progress in development of next-generation sequencing (NGS) technologies has made it possible to deliver accurate genomic information in a timely manner. Over the past several years, NGS has transformed biomedical and clinical research and found its application in the field of personalized medicine. Here we discuss the rise of personalized medicine and the history of NGS. We discuss current applications and uses of NGS in medicine, including infectious diseases, oncology, genomic medicine, and dermatology. We provide a brief discussion of selected studies where NGS was used to respond to wide variety of questions in biomedical research and clinical medicine. Finally, we discuss the challenges of implementing NGS into routine clinical use.

Variant detection from long-read genome sequencing (lrGS) has proven to be more accurate and comprehensive than variant detection from short-read genome sequencing (srGS). However, the rate at which lrGS can increase molecular diagnostic yield for rare disease is not yet precisely characterized. We performed lrGS using Pacific Biosciences "HiFi" technology on 96 short-read-negative probands with rare diseases that were suspected to be genetic. We generated hg38-aligned variants and de novo phased genome assemblies, and subsequently annotated, filtered, and curated variants using clinical standards. New disease-relevant or potentially relevant genetic findings were identified in 16/96 (16.7%) probands, nine of which (8/96, ∼9.4%) harbored pathogenic or likely pathogenic variants. Nine probands (∼9.4%) had variants that were accurately called in both srGS and lrGS and represent changes to clinical interpretation, mostly from recently published gene-disease associations. Seven cases included variants that were only correctly interpreted in lrGS, including copy-number variants (CNVs), an inversion, a mobile element insertion, two low-complexity repeat expansions, and a 1 bp deletion. While evidence for each of these variants is, in retrospect, visible in srGS, they were either not called within srGS data, were represented by calls with incorrect sizes or structures, or failed quality control and filtration. Thus, while reanalysis of older srGS data clearly increases diagnostic yield, we find that lrGS allows for substantial additional yield (7/96, 7.3%) beyond srGS. We anticipate that as lrGS analysis improves, and as lrGS data sets grow allowing for better variant-frequency annotation, the additional lrGS-only rare disease yield will grow over time.

Amino acids are the building blocks of proteins and enzymes which are essential for life. Understanding amino acid usage offers insights into protein function and molecular mechanisms underlying life histories. However, genome-wide patterns of amino acid usage across domains of life remain poorly understood. Here, we analysed the proteomes of 5590 species across four domains and found that only a few amino acids are consistently the most and least used. This differential usage results in lower amino acid usage diversity at the most and least frequent ranks, creating a ubiquitous inverted U-shape pattern of amino acid diversity and rank which we call an 'edge effect' across proteomes and domains of life. This effect likely stems from protein secondary structural constraints, not the evolutionary chronology of amino acid incorporation into the genetic code, highlighting the functional rather than evolutionary influences on amino acid usage. We also tested other contemporary hypotheses regarding amino acid usage in proteomes and found that amino acid usage varies across life's domains and is only weakly influenced by growth temperature. Our findings reveal a novel and pervasive amino acid usage pattern across genomes with the potential to help us probe deep evolutionary relationships and advance synthetic biology.

Dihydroorotate dehydrogenase (DHODH) catalyzes the fourth enzymatic reaction of the pyrimidine biosynthesis pathway. Miller syndrome, also known as postaxial acrofacial dysostosis, is caused by biallelic pathogenic variants in DHODH. We present a patient with a relatively mild skeletal phenotype carrying a novel variant of unknown significance in DHODH: c.829G > A, p.(D277N), in combination with a known variant, c.403C > T, p.(R135C). We functionally characterized the DHODH variant D277N in comparison to a very recently reported, but functionally uncharacterized variant P43L, that was found in a patient with more pronounced Miller syndrome features. Because both cases share the same DHODH variant R135C, we aimed to study the effect on enzyme activity of the two variants D277N and P43L to determine pathogenicity and possibly a genotype-phenotype relationship on the R135C background. We found a significant reduction in enzyme activity for both variants. The variant P43L showed a more pronounced loss of function in all assays compatible with other pathogenic variants reported in Miller, whereas the D277N variant showed milder changes that could reflect the mild phenotypic features in our patient. Yet due to a lack of a known threshold of residual enzyme activity to determine pathogenicity, this needs to be confirmed in further studies.

Autosomal recessive coding variants are well-known causes of rare disorders. We quantified the contribution of these variants to developmental disorders in a large, ancestrally diverse cohort comprising 29,745 trios, of whom 20.4% had genetically inferred non-European ancestries. The estimated fraction of patients attributable to exome-wide autosomal recessive coding variants ranged from ~2-19% across genetically inferred ancestry groups and was significantly correlated with average autozygosity. Established autosomal recessive developmental disorder-associated (ARDD) genes explained 84.0% of the total autosomal recessive coding burden, and 34.4% of the burden in these established genes was explained by variants not already reported as pathogenic in ClinVar. Statistical analyses identified two novel ARDD genes: KBTBD2 and ZDHHC16. This study expands our understanding of the genetic architecture of developmental disorders across diverse genetically inferred ancestry groups and suggests that improving strategies for interpreting missense variants in known ARDD genes may help diagnose more patients than discovering the remaining genes.

This review examines the complexities of Type 2 Diabetes Mellitus (T2DM), focusing on the critical role of integrating omics technologies with traditional experimental methods. It underscores the advancements in understanding the genetic diversity of T2DM and emphasizes the evolution towards personalized treatment modalities. The paper analyzes a variety of omics approaches, including genomics, methylation, transcriptomics, proteomics, metabolomics, and intestinal microbiomics, delineating their substantial contributions to deciphering the multifaceted mechanisms underlying T2DM. Furthermore, the review highlights the indispensable role of non-omics experimental techniques in comprehending and managing T2DM, advocating for their integration in the development of tailored medicine and precision treatment strategies. By identifying existing research gaps and suggesting future research trajectories, the review underscores the necessity for a comprehensive, multidisciplinary approach. This approach synergistically combines clinical insights with cutting-edge biotechnologies, aiming to refine the management and therapeutic interventions of T2DM, and ultimately enhancing patient outcomes. This synthesis of knowledge and methodologies paves the way for innovative advancements in T2DM research, fostering a deeper understanding and more effective treatment of this complex condition.

Diamond-Blackfan anemia syndrome (DBA) is a ribosomopathy associated with loss-of-function variants in more than 20 ribosomal protein (RP) genes. Here, we report the genetic, functional, and biochemical dissection of 2 multigenerational pedigrees with variants in RPL17, a large ribosomal subunit protein-encoding gene. Affected individuals had clinical features and erythroid proliferation defects consistent with DBA. Further, RPL17/uL22 depletion resulted in anemia and micrognathia in zebrafish larvae, and in vivo complementation studies indicated that RPL17 variants were pathogenic. Lymphoblastoid cell lines (LCLs) derived from patients displayed a ribosomal RNA maturation defect reflecting haploinsufficiency of RPL17. The proteins encoded by RPL17 variants were not incorporated into ribosomes, but 10%-20% of 60S ribosomal subunits contained a short form of 5.8S rRNA (5.8SC), a species that is marginal in normal cells. These atypical 60S subunits were actively engaged in translation. Ribosome profiling showed changes of the translational profile, but those are similar to LCLs bearing RPS19 variants. These results link an additional RP gene to DBA. They show that ribosomes can be modified substantially by RPL17 haploinsufficiency but support the paradigm that translation alterations in DBA are primarily related to insufficient ribosome production rather than to changes in ribosome structure or composition.

The identification of structural variants (SVs) in genomic data represents an ongoing challenge because of difficulties in reliable SV calling leading to reduced sensitivity and specificity. We prepared high-quality DNA from 9 parent-child trios, who had previously undergone short-read whole-genome sequencing (Illumina platform) as part of the Genomics England 100,000 Genomes Project. We reanalysed the genomes using both Bionano optical genome mapping (OGM; 8 probands and one trio) and Nanopore long-read sequencing (Oxford Nanopore Technologies [ONT] platform; all samples). To establish a "truth" dataset, we asked whether rare proband SV calls (n = 234) made by the Bionano Access (version 1.6.1)/Solve software (version 3.6.1_11162020) could be verified by individual visualisation using the Integrative Genomics Viewer with either or both of the Illumina and ONT raw sequence. Of these, 222 calls were verified, indicating that Bionano OGM calls have high precision (positive predictive value 95%). We then asked what proportion of the 222 true Bionano SVs had been identified by SV callers in the other two datasets. In the Illumina dataset, sensitivity varied according to variant type, being high for deletions (115/134; 86%) but poor for insertions (13/58; 22%). In the ONT dataset, sensitivity was generally poor using the original Sniffles variant caller (48% overall) but improved substantially with use of Sniffles2 (36/40; 90% and 17/23; 74% for deletions and insertions, respectively). In summary, we show that the precision of OGM is very high. In addition, when applying the Sniffles2 caller, the sensitivity of SV calling using ONT long-read sequence data outperforms Illumina sequencing for most SV types.

Facial dysostosis syndromes (FDS) are rare congenital conditions impacting facial development, often leading to diverse craniofacial abnormalities. This study addresses the scarcity of evidence on these syndromes about optimal diagnostic and treatment practices. To overcome this scarcity, European experts from ERN CRANIO collaborated to develop a clinical consensus statement through the Delphi consensus method. A systematic search of Embase, MEDLINE/PubMed, Cochrane, and Web of Science databases was conducted until February 2023. The quality of evidence was evaluated using various tools depending on the study design. Statements were subsequently formed based on literature and expert opinion, followed by a Delphi process with expert health care providers and patient representatives. In total, 92 experts from various specialties and three patient representatives were involved in the Delphi process. Over 3 voting rounds, consensus was achieved on 92 (46.9%), 58 (59.2%), and 19 (70.4%) statements, respectively. These statements cover the topics of general care; craniofacial reconstruction; the eyes and lacrimal system; upper airway management; genetics; hearing; speech; growth, feeding, and swallowing; dental treatment and orthodontics; extracranial anomalies; and psychology and cognition. The current clinical consensus statement provides valuable insights into optimal diagnostic and treatment practices and identifies key research opportunities for FDS. This consensus statement represents a significant advancement in FDS care, underlining the commitment of health care professionals to improve the understanding and management of these rare syndromes in Europe.

Diagnosing genetic disorders requires extensive manual curation and interpretation of candidate variants, a labor-intensive task even for trained geneticists. Although artificial intelligence (AI) shows promise in aiding these diagnoses, existing AI tools have only achieved moderate success for primary diagnosis.

AI-MARRVEL (AIM) uses a random-forest machine-learning classifier trained on over 3.5 million variants from thousands of diagnosed cases. AIM additionally incorporates expert-engineered features into training to recapitulate the intricate decision-making processes in molecular diagnosis. The online version of AIM is available at https://ai.marrvel.org. To evaluate AIM, we benchmarked it with diagnosed patients from three independent cohorts.

AIM improved the rate of accurate genetic diagnosis, doubling the number of solved cases as compared with benchmarked methods, across three distinct real-world cohorts. To better identify diagnosable cases from the unsolved pools accumulated over time, we designed a confidence metric on which AIM achieved a precision rate of 98% and identified 57% of diagnosable cases out of a collection of 871 cases. Furthermore, AIM's performance improved after being fine-tuned for targeted settings including recessive disorders and trio analysis. Finally, AIM demonstrated potential for novel disease gene discovery by correctly predicting two newly reported disease genes from the Undiagnosed Diseases Network.

AIM achieved superior accuracy compared with existing methods for genetic diagnosis. We anticipate that this tool may aid in primary diagnosis, reanalysis of unsolved cases, and the discovery of novel disease genes. (Funded by the NIH Common Fund and others.).

Alcohol use disorder (AUD) is a leading cause of death and disability worldwide. There has been substantial progress in identifying genetic variants underlying AUD. However, there are few whole-exome sequencing (WES) studies of AUD. We analyzed WES of 4,530 samples from the Yale-Penn cohort and 469,835 samples from the UK Biobank (UKB). After quality control, 1,420 AUD cases and 619 controls of European ancestry (EUR) and 1,142 cases and 608 controls of African ancestry (AFR) from Yale-Penn were retained for subsequent analyses. WES data from 415,617 EUR samples (12,861 cases), 6,142 AFR samples (130 cases) and 4,607 South Asian (SAS) samples (130 cases) from UKB were also analyzed. Single-variant association analysis identified the well-known functional variant rs1229984 in ADH1B ( P =4.88×10 -31 ) and several other common variants in ADH1C . Gene-based tests identified ADH1B ( P =1.00×10 -31 ), ADH1C ( P =5.23×10 -7 ), CNST ( P =1.19×10 -6 ), and IFIT5 (3.74×10 -6 ). This study extends our understanding of the genetic basis of AUD.

Migraine is a severe, debilitating neurovascular disorder. Hemiplegic migraine (HM) is a rare and debilitating neurological condition with a strong genetic basis. Sequencing technologies have improved the diagnosis and our understanding of the molecular pathophysiology of HM. Linkage analysis and sequencing studies in HM families have identified pathogenic variants in ion channels and related genes, including CACNA1A, ATP1A2, and SCN1A, that cause HM. However, approximately 75% of HM patients are negative for these mutations, indicating there are other genes involved in disease causation. In this review, we explored our current understanding of the genetics of HM. The evidence presented herein summarises the current knowledge of the genetics of HM, which can be expanded further to explain the remaining heritability of this debilitating condition. Innovative bioinformatics and computational strategies to cover the entire genetic spectrum of HM are also discussed in this review.

Variant detection from long-read genome sequencing (lrGS) has proven to be considerably more accurate and comprehensive than variant detection from short-read genome sequencing (srGS). However, the rate at which lrGS can increase molecular diagnostic yield for rare disease is not yet precisely characterized. We performed lrGS using Pacific Biosciences "HiFi" technology on 96 short-read-negative probands with rare disease that were suspected to be genetic. We generated hg38-aligned variants and de novo phased genome assemblies, and subsequently annotated, filtered, and curated variants using clinical standards. New disease-relevant or potentially relevant genetic findings were identified in 16/96 (16.7%) probands, eight of which (8/96, 8.33%) harbored pathogenic or likely pathogenic variants. Newly identified variants were visible in both srGS and lrGS in nine probands (~9.4%) and resulted from changes to interpretation mostly from recent gene-disease association discoveries. Seven cases included variants that were only interpretable in lrGS, including copy-number variants, an inversion, a mobile element insertion, two low-complexity repeat expansions, and a 1 bp deletion. While evidence for each of these variants is, in retrospect, visible in srGS, they were either: not called within srGS data, were represented by calls with incorrect sizes or structures, or failed quality-control and filtration. Thus, while reanalysis of older data clearly increases diagnostic yield, we find that lrGS allows for substantial additional yield (7/96, 7.3%) beyond srGS. We anticipate that as lrGS analysis improves, and as lrGS datasets grow allowing for better variant frequency annotation, the additional lrGS-only rare disease yield will grow over time.

The number of human disease genes has dramatically increased over the past decade, largely fueled by ongoing advances in sequencing technologies. In parallel, the number of available clinical genetic tests has also increased, including the utilization of exome sequencing for undiagnosed diseases. Although most clinical sequencing tests have been centered on enrichment-based multigene panels and exome sequencing, the continued improvements in performance and throughput of genome sequencing suggest that this technology is emerging as a potential platform for routine clinical genetic testing. A notable advantage is a single workflow with the opportunity to reflexively interrogate content as clinically indicated; however, challenges with implementing routine clinical genome sequencing still remain. This review is centered on evaluating the applications of genome sequencing as a single platform for clinical constitutional genetic testing, including its potential utility for diagnostic testing, carrier screening, cytogenomic molecular karyotyping, prenatal testing, mitochondrial genome interrogation, and pharmacogenomic and polygenic risk score testing.

The revolutionary progress in development of next-generation sequencing (NGS) technologies has made it possible to deliver accurate genomic information in a timely manner. Over the past several years, NGS has transformed biomedical and clinical research and found its application in the field of personalized medicine. Here we discuss the rise of personalized medicine and the history of NGS. We discuss current applications and uses of NGS in medicine, including infectious diseases, oncology, genomic medicine, and dermatology. We provide a brief discussion of selected studies where NGS was used to respond to wide variety of questions in biomedical research and clinical medicine. Finally, we discuss the challenges of implementing NGS into routine clinical use.

To assess telomere silencing 1-like (DOTIL) gene expression within gastric cancer (GC) tissues as well as its function of promoting cancer stem cell (CSC)-mediated epithelial-mesenchymal switching, tissue samples from 8 patients each in 3 stages (normal, low-grade intraepithelial neoplasia (LGIN), as well as early gastric carcinoma (EGC)) were collected for whole-exome sequencing, which revealed differentially expressed genes (DEGs). The DEGs and their prognostic value were verified through TCGA and GTEx analyses. We also verified the role of DOT1L in EGC development. We collected samples from three patients each with LGIN and EGC for single-cell sequencing. We conducted single-cell transcriptomic analysis, DEG analysis, cell‒cell interaction analysis, and pseudotime analysis using R language. Sites and levels of DOT1L, CD44 and DOT1L expression were verified by IF. We found 703 deleterious mutation sites in the LGIN group and 389 deleterious mutation sites in the EGC group. The LGIN as well as EGC categories exhibited increased levels of DOT1L expression compared to the standard category (P<0.05) in TCGA and GTEx. DOT1L also correlated significantly with TMB (P=8.45E-06), MSI (P=0.001), and tumor proliferation index (P=7.17E-09) in the TCGA and GTEx datasets. In single cells, we found that DOT1L promotes CD44 expression via the Wnt/β-catenin signaling pathway and the development for stemness properties within GC. In addition, we found that DOT1L, CD44 and CTNNB1 colocalize and correlate positively. In conclusion, one important CSC regulator in GC, DOT1L may be crucial in coordinating the expression of genes specific to a certain lineage during MSC development.

Phenotype-guided gene prioritizers have proved a highly efficient approach to identifying causal genes for Mendelian diseases. In our previous study, we preliminarily evaluated the performance of ten prioritizers. However, all the selected software was run based on default settings and singleton mode. With a large-scale family dataset from Deciphering Developmental Disorders (DDD) project (N = 305) and an in-house trio cohort (N = 152), the four optimal performers in our prior study including Exomiser, PhenIX, AMELIE, and LIRCIAL were further assessed through parameter optimization and/or the utilization of trio mode. The in-depth assessment revealed high diagnostic yields of the four prioritizers with refined preferences, each alone or together: (1) 83.3-91.8% of the causal genes were presented among the first ten candidates in the final ranking lists of the four tools; (2) Over 97.7% of the causal genes were successfully captured within the top 50 by either of the four software. Exomiser did best in directly hitting the target (ranking the causal gene at the very top) while LIRICAL displayed a predominant overall detection capability. Besides, cases affected by low-penetrance and high-frequency pathogenic variants were found misjudged during the automated prioritization process. The discovery of the limitations shed light on the specific directions of future enhancement for causal-gene ranking tools.

The genetic background of neonatal encephalopathy (NE) is complicated and early diagnosis is beneficial to optimizing therapeutic strategy for patients.

NE Patients with unclear etiology received regular clinical tests including ammonia test, metabolic screening test, amplitude-integrated electroencephalographic (aEEG) monitoring, brain Magnetic Resonance Imaging (MRI) scanning, and genetic test. The protein structure change was predicted using Dynamut2 and RoseTTAFold.

15 out of a total of 113 NE Patients were detected with newly reported pathogenic variants. In this sub-cohort, (1) seizure was the primary initial symptoms; (2) four patients had abnormal metabolic screening results, and two of them were also diagnosed with excessive blood ammonia concentration; (3) the brain MRI results were irregular in three infants and the brain waves were of moderate-severe abnormality in about a half of the patients. The novel pathogenic variants discovered in this study belonged to 12 genes, and seven of them were predicted to introduce a premature translation termination. In-silicon predictions showed that four variants were destructive to the protein structure of KCNQ2.

Our study expands the mutation spectrum of genes associated with NE and introduces new evidence for molecular diagnosis in this newborn illness.

Purines and pyrimidines are essential components as they are the building blocks of vital molecules, such as nucleic acids, coenzymes, signalling molecules, as well as energy transfer molecules. Purine and pyrimidine metabolism defects are characterised by abnormal concentrations of purines, pyrimidines and/or their metabolites in cells or body fluids. This phenomenon is due to a decreased or an increased activity of enzymes involved in this metabolism and has been reported in humans for over 60 years. This review provides an overview of neurological presentations of inborn errors of purine and pyrimidine metabolism. These conditions can lead to psychomotor retardation, epilepsy, hypotonia, or microcephaly; sensory involvement, such as deafness and visual disturbances; multiple malformations, as well as muscular symptoms. Clinical signs are often nonspecific and thus overlooked, but some diseases are treatable and early diagnosis may improve the child's future. Although these metabolic hereditary diseases are rare, they are most probably under-diagnosed. When confronted with suggestive clinical or laboratory signs, clinicians should prescribe genetic testing in association with a biochemical screening including thorough purine and pyrimidine metabolites analysis and/or specific enzyme evaluation. This is most likely going to increase the number of confirmed patients.

Cancer genome sequencing consortiums have recently catalogued an abundance of somatic mutations, across a wide range of human cancers, in the chromatin-modifying enzymes that regulate gene expression. Defining the molecular mechanisms underlying the potentially oncogenic functions of these epigenetic mutations could serve as the basis for precision medicine approaches to cancer therapy. MLL4 encoded by the KMT2D gene highly mutated in a large number of human cancers, is a key histone lysine monomethyltransferase within the Complex of Proteins Associated with Set1 (COMPASS) family that regulates gene expression through enhancer function, potentially functioning as a tumor suppressor. We report that the KMT2D mutations which cause MLL4 protein truncation also alter MLL4's subcellular localization, resulting in loss-of-function in the nucleus and gain-of-function in the cytoplasm. We demonstrate that isogenic correction of KMT2D truncation mutation rescues the aberrant localization phenotype and restores multiple regulatory functions of MLL4, including COMPASS integrity/stabilization, histone H3K4 mono-methylation, enhancer activation, and therefore transcriptional regulation. Moreover, isogenic correction diminishes the sensitivity of KMT2D-mutated cancer cells to targeted metabolic inhibition. Using immunohistochemistry, we identified that cytoplasmic MLL4 is unique to the tissue of bladder cancer patients with KMT2D truncation mutations. Using a preclinical carcinogen model of bladder cancer in mouse, we demonstrate that truncated cytoplasmic MLL4 predicts response to targeted metabolic inhibition therapy for bladder cancer and could be developed as a biomarker for KMT2D-mutated cancers. We also highlight the broader potential for prognosis, patient stratification and treatment decision-making based on KMT2D mutation status in MLL4 truncation-relevant diseases, including human cancers and Kabuki Syndrome.

During the neonatal period, many genetic disorders present and contribute to neonatal morbidity and mortality. Genomic medicine-the use of genomic information in clinical care- has the potential to significantly reduce morbidity and mortality in the neonatal period and improve outcomes for this population. Diagnostic genomic testing for symptomatic newborns, especially rapid testing, has been shown to be feasible and have diagnostic and clinical utility, particularly in the short-term. Ongoing studies are assessing the feasibility and utility, including personal utility, of implementation in diverse populations. Genomic screening for asymptomatic newborns has also been studied, and the acceptability and feasibility of such an approach remains an active area of investigation. Emerging precision therapies, with examples even at the "n-of-1" level, highlight the promise of precision diagnostics to lead to early intervention and improve outcomes. To sustainably implement genomic medicine in neonatal care in an ethical, effective, and equitable manner, we need to ensure access to genetics and genomics knowledge, access to genomic tests, which is currently limited by payors, feasible processes for ordering these tests, and access to follow up in the clinical and research realms. Future studies will provide further insight into enablers and barriers to optimize implementation strategies.

Bardet-Biedl syndrome (BBS) is an archetypal ciliopathy caused by dysfunction of primary cilia. BBS affects multiple tissues, including the kidney, eye and hypothalamic satiety response. Understanding pan-tissue mechanisms of pathogenesis versus those which are tissue-specific, as well as gauging their associated inter-individual variation owing to genetic background and stochastic processes, is of paramount importance in syndromology. The BBSome is a membrane-trafficking and intraflagellar transport (IFT) adaptor protein complex formed by eight BBS proteins, including BBS1, which is the most commonly mutated gene in BBS. To investigate disease pathogenesis, we generated a series of clonal renal collecting duct IMCD3 cell lines carrying defined biallelic nonsense or frameshift mutations in Bbs1, as well as a panel of matching wild-type CRISPR control clones. Using a phenotypic screen and an unbiased multi-omics approach, we note significant clonal variability for all assays, emphasising the importance of analysing panels of genetically defined clones. Our results suggest that BBS1 is required for the suppression of mesenchymal cell identities as the IMCD3 cell passage number increases. This was associated with a failure to express epithelial cell markers and tight junction formation, which was variable amongst clones. Transcriptomic analysis of hypothalamic preparations from BBS mutant mice, as well as BBS patient fibroblasts, suggested that dysregulation of epithelial-to-mesenchymal transition (EMT) genes is a general predisposing feature of BBS across tissues. Collectively, this work suggests that the dynamic stability of the BBSome is essential for the suppression of mesenchymal cell identities as epithelial cells differentiate.

Artificial intelligence (AI) has been used in many areas of medicine, and recently large language models (LLMs) have shown potential utility for clinical applications. However, since we do not know if the use of LLMs can accelerate the pace of genetic discovery, we used data generated from mouse genetic models to investigate this possibility. We examined whether a recently developed specialized LLM (Med-PaLM 2) could analyze sets of candidate genes generated from analysis of murine models of biomedical traits. In response to free-text input, Med-PaLM 2 correctly identified the murine genes that contained experimentally verified causative genetic factors for six biomedical traits, which included susceptibility to diabetes and cataracts. Med-PaLM 2 was also able to analyze a list of genes with high impact alleles, which were identified by comparative analysis of murine genomic sequence data, and it identified a causative murine genetic factor for spontaneous hearing loss. Based upon this Med-PaLM 2 finding, a novel bigenic model for susceptibility to spontaneous hearing loss was developed. These results demonstrate Med-PaLM 2 can analyze gene-phenotype relationships and generate novel hypotheses, which can facilitate genetic discovery.

Next-generation sequencing (NGS) has revolutionized the field of genomics and is rapidly transforming clinical diagnosis and precision medicine. This advanced sequencing technology enables the rapid and cost-effective analysis of large-scale genomic data, allowing comprehensive exploration of the genetic landscape of diseases. In clinical diagnosis, NGS has proven to be a powerful tool for identifying disease-causing variants, enabling accurate and early detection of genetic disorders. Additionally, NGS facilitates the identification of novel disease-associated genes and variants, aiding in the development of targeted therapies and personalized treatment strategies. NGS greatly benefits precision medicine by enhancing our understanding of disease mechanisms and enabling the identification of specific molecular markers for disease subtypes, thus enabling tailored medical interventions based on individual characteristics. Furthermore, NGS contributes to the development of non-invasive diagnostic approaches, such as liquid biopsies, which can monitor disease progression and treatment response. The potential of NGS in clinical diagnosis and precision medicine is vast, yet challenges persist in data analysis, interpretation, and protocol standardization. This review highlights NGS applications in disease diagnosis, prognosis, and personalized treatment strategies, while also addressing challenges and future prospects in fully harnessing genomic potential within clinical practice.

Exome and genome sequencing have rapidly transitioned from research methods to widely used clinical tests for diagnosing rare genetic diseases. We sought to synthesize the topics covered and appraise the development processes of clinical guidance documents generated by genetics professional organizations.

We conducted a scoping review of guidance documents published since 2010, systematically identified in peer-reviewed and gray literature, using established methods and reporting guidelines. We coded verbatim recommendations by topic using content analysis and critically appraised documents using the Appraisal of Guidelines Research and Evaluation (AGREE) II tool.

We identified 30 guidance documents produced by 8 organizations (2012-2022), yielding 611 recommendations covering 21 topics. The most common topic related to findings beyond the primary testing indication. Mean AGREE II scores were low across all 6 quality domains; scores for items related to rigor of development were among the lowest. More recently published documents generally received higher scores.

Guidance documents included a broad range of recommendations but were of low quality, particularly in their rigor of development. Developers should consider using tools such as AGREE II and basing recommendations on living knowledge syntheses to improve guidance development in this evolving space.

Pathogenic mutations in EVC or EVC2 gene can lead to Ellis-van Creveld (EvC) syndrome, which is a rare autosomal recessive skeletal dysplasia disorder. This study aimed to determine pathogenic gene variations associated with EvC syndrome in fetuses showing ultrasound anomalies.

A 32-year-old pregnant woman from Quanzhou, China was investigated. In her pregnancy examination, the fetus exhibited multiple fetal malformations, including a narrow thorax, short limbs, postaxial polydactyly, cardiac malformations, and separation of double renal pelvis. Karyotype, chromosomal microarray analysis and whole exome sequencing were performed for prenatal genetic etiology analysis.

Chromosome abnormalities and copy number variants were not observed in the fetus using karyotype and chromosomal microarray analysis. Using whole exome sequencing, two compound heterozygous variants NM_147127.5:c.[2484G>A(p.Trp828Ter)];[871-2_894del] in EVC2 gene were identified in the fetus as pathogenic variants inherited from parents.

The study is the first to identify two rare compound variants in EVC2 gene in a Chinese family using whole exome sequencing. The application of whole-exome sequencing would be helpful in fetal etiological diagnosis with ultrasound anomalies.

Molecular diagnostics is a cornerstone of modern precision medicine, broadly understood as tailoring an individual's treatment, follow-up, and care based on molecular data. In rare diseases (RDs), molecular diagnoses reveal valuable information about the cause of symptoms, disease progression, familial risk, and in certain cases, unlock access to targeted therapies. Due to decreasing DNA sequencing costs, genome sequencing (GS) is emerging as the primary method for precision diagnostics in RDs. Several ongoing European initiatives for precision medicine have chosen GS as their method of choice. Recent research supports the role for GS as first-line genetic investigation in individuals with suspected RD, due to its improved diagnostic yield compared to other methods. Moreover, GS can detect a broad range of genetic aberrations including those in noncoding regions, producing comprehensive data that can be periodically reanalyzed for years to come when further evidence emerges. Indeed, targeted drug development and repurposing of medicines can be accelerated as more individuals with RDs receive a molecular diagnosis. Multidisciplinary teams in which clinical specialists collaborate with geneticists, genomics education of professionals and the public, and dialogue with patient advocacy groups are essential elements for the integration of precision medicine into clinical practice worldwide. It is also paramount that large research projects share genetic data and leverage novel technologies to fully diagnose individuals with RDs. In conclusion, GS increases diagnostic yields and is a crucial step toward precision medicine for RDs. Its clinical implementation will enable better patient management, unlock targeted therapies, and guide the development of innovative treatments.

Orofacial clefting is considered one of the commonest birth defects worldwide. It presents as cleft lip only, isolated cleft palate or cleft lip and palate. The condition has a diverse genetic background influenced by gene-gene and gene-environment interaction, resulting in two main types, syndromic and nonsyndromic orofacial clefts. Orofacial clefts lead to significant physiological difficulties that affect feeding, speech and language development and other developmental aspects, which results in an increased social and financial burden on the affected individuals and their families. The management of cleft lip and palate is solely based on following a multidisciplinary team approach. In this narrative review article, we briefly summarize the different genetic causes of orofacial clefts and discuss some of the common syndromes and the approach to the management of orofacial clefts.

Oral clefts and ectrodactyly are common, heterogeneous birth defects. We performed whole-exome sequencing (WES) analysis in a Syrian family. The proband presented with both orofacial clefting and ectrodactyly but not ectodermal dysplasia as typically seen in ectrodactyly, ectodermal dysplasia, and cleft lip/palate syndrome-3. A paternal uncle with only an oral cleft was deceased and unavailable for analysis.

Variant annotation, Mendelian inconsistencies, and novel variants in known cleft genes were examined. Candidate variants were validated using Sanger sequencing, and pathogenicity assessed by knocking out the tp63 gene in zebrafish to evaluate its role during zebrafish development.

Twenty-eight candidate de novo events were identified, one of which is in a known oral cleft and ectrodactyly gene, TP63 (c.956G > T, p.Arg319Leu), and confirmed by Sanger sequencing.

TP63 mutations are associated with multiple autosomal dominant orofacial clefting and limb malformation disorders. The p.Arg319Leu mutation seen in this patient is de novo but also novel. Two known mutations in the same codon (c.956G > A, p.(Arg319His; rs121908839, c.955C > T), p.Arg319Cys) cause ectrodactyly, providing evidence that mutating this codon is deleterious. While this TP63 mutation is the best candidate for the patient's clinical presentation, whether it is responsible for the entire phenotype is unclear. Generation and characterization of tp63 knockout zebrafish showed necrosis and rupture of the head at 3 days post-fertilization (dpf). The embryonic phenotype could not be rescued by injection of zebrafish or human messenger RNA (mRNA). Further functional analysis is needed to determine what proportion of the phenotype is due to this mutation.