High-coverage whole-genome sequencing of the expanded 1000 Genomes Project cohort including 602 trios.

The 1000 Genomes Project (1kGP) is the largest fully open resource of whole-genome sequencing (WGS) data consented for public distribution without access or use restrictions. The final, phase 3 release of the 1kGP included 2,504 unrelated samples from 26 populations and was based primarily on low-coverage WGS. Here, we present a high-coverage 3,202-sample WGS 1kGP resource, which now includes 602 complete trios, sequenced to a depth of 30X using Illumina. We performed single-nucleotide variant (SNV) and short insertion and deletion (INDEL) discovery and generated a comprehensive set of structural variants (SVs) by integrating multiple analytic methods through a machine learning model. We show gains in sensitivity and precision of variant calls compared to phase 3, especially among rare SNVs as well as INDELs and SVs spanning frequency spectrum. We also generated an improved reference imputation panel, making variants discovered here accessible for association studies.

A Deep Neural Network for Predicting and Engineering Alternative Polyadenylation.

Alternative polyadenylation (APA) is a major driver of transcriptome diversity in human cells. Here, we use deep learning to predict APA from DNA sequence alone. We trained our model (APARENT, APA REgression NeT) on isoform expression data from over 3 million APA reporters. APARENT's predictions are highly accurate when tasked with inferring APA in synthetic and human 3'UTRs. Visualizing features learned across all network layers reveals that APARENT recognizes sequence motifs known to recruit APA regulators, discovers previously unknown sequence determinants of 3' end processing, and integrates these features into a comprehensive, interpretable, cis-regulatory code. We apply APARENT to forward engineer functional polyadenylation signals with precisely defined cleavage position and isoform usage and validate predictions experimentally. Finally, we use APARENT to quantify the impact of genetic variants on APA. Our approach detects pathogenic variants in a wide range of disease contexts, expanding our understanding of the genetic origins of disease.

The functional impact of 1,570 individual amino acid substitutions in human OTC.

Deleterious mutations in the X-linked gene encoding ornithine transcarbamylase (OTC) cause the most common urea cycle disorder, OTC deficiency. This rare but highly actionable disease can present with severe neonatal onset in males or with later onset in either sex. Individuals with neonatal onset appear normal at birth but rapidly develop hyperammonemia, which can progress to cerebral edema, coma, and death, outcomes ameliorated by rapid diagnosis and treatment. Here, we develop a high-throughput functional assay for human OTC and individually measure the impact of 1,570 variants, 84% of all SNV-accessible missense mutations. Comparison to existing clinical significance calls, demonstrated that our assay distinguishes known benign from pathogenic variants and variants with neonatal onset from late-onset disease presentation. This functional stratification allowed us to identify score ranges corresponding to clinically relevant levels of impairment of OTC activity. Examining the results of our assay in the context of protein structure further allowed us to identify a 13 amino acid domain, the SMG loop, whose function appears to be required in human cells but not in yeast. Finally, inclusion of our data as PS3 evidence under the current ACMG guidelines, in a pilot reclassification of 34 variants with complete loss of activity, would change the classification of 22 from variants of unknown significance to clinically actionable likely pathogenic variants. These results illustrate how large-scale functional assays are especially powerful when applied to rare genetic diseases.

miniSNV: accurate and fast single nucleotide variant calling from nanopore sequencing data.

Nanopore sequence technology has demonstrated a longer read length and enabled to potentially address the limitations of short-read sequencing including long-range haplotype phasing and accurate variant calling. However, there is still room for improvement in terms of the performance of single nucleotide variant (SNV) identification and computing resource usage for the state-of-the-art approaches. In this work, we introduce miniSNV, a lightweight SNV calling algorithm that simultaneously achieves high performance and yield. miniSNV utilizes known common variants in populations as variation backgrounds and leverages read pileup, read-based phasing, and consensus generation to identify and genotype SNVs for Oxford Nanopore Technologies (ONT) long reads. Benchmarks on real and simulated ONT data under various error profiles demonstrate that miniSNV has superior sensitivity and comparable accuracy on SNV detection and runs faster with outstanding scalability and lower memory than most state-of-the-art variant callers. miniSNV is available from https://github.com/CuiMiao-HIT/miniSNV.

The repertoire of G-protein-coupled receptor variations in the Japanese population 54KJPN.

G-protein-coupled receptors (GPCRs) are the largest superfamily in the human genome and the major targets for the market drugs. Recent massive genomics studies revealed numerous natural variations in the general population. 54KJPN is the most extensive Japanese population genomics study, curating the whole genome sequences from about 54,000 individuals. Here, by analyzing 390 non-olfactory GPCR genes in the 54KJPN dataset, we annotated 25,443 missense single-nucleotide variations. Among them, we found 120 major variations that appear with an allele frequency greater than 0.5, including variations that occurred on posttranslational modification sites. Structural alignment of GPCRs using the generic numbering system in the GPCRdb reveals enrichment of alterations in the conserved arginine residue within the DRY motif, which contributes to downstream G-protein signaling. A comparison with the worldwide 1000 Genomes Project (1KGP) dataset found 23 variations that were present exclusively in the 54KJPN dataset. This study will be the basis for future pharmacogenomics studies for the Japanese population.

Post-implantation analysis of genomic variations in the progeny from developing fetus to birth.

The analysis of genomic variations in offspring after implantation has been infrequently studied. In this study, we aim to investigate the extent of de novo mutations in humans from developing fetus to birth. Using high-depth whole-genome sequencing, 443 parent-offspring trios were studied to compare the results of de novo mutations (DNMs) between different groups. The focus was on fetuses and newborns, with DNA samples obtained from the families' blood and the aspirated embryonic tissues subjected to deep sequencing. It was observed that the average number of total DNMs in the newborns group was 56.26 (54.17-58.35), which appeared to be lower than that the multifetal reduction group, which was 76.05 (69.70-82.40) (F = 2.42, P = 0.12). However, after adjusting for parental age and maternal pre-pregnancy body mass index (BMI), significant differences were found between the two groups. The analysis was further divided into single nucleotide variants (SNVs) and insertion/deletion of a small number of bases (indels), and it was discovered that the average number of de novo SNVs associated with the multifetal reduction group and the newborn group was 49.89 (45.59-54.20) and 51.09 (49.22-52.96), respectively. No significant differences were noted between the groups (F = 1.01, P = 0.32). However, a significant difference was observed for de novo indels, with a higher average number found in the multifetal reduction group compared to the newborn group (F = 194.17, P < 0.001). The average number of de novo indels among the multifetal reduction group and the newborn group was 26.26 (23.27-29.05) and 5.17 (4.82-5.52), respectively. To conclude, it has been observed that the quantity of de novo indels in the newborns experiences a significant decrease when compared to that in the aspirated embryonic tissues (7-9 weeks). This phenomenon is evident across all genomic regions, highlighting the adverse effects of de novo indels on the fetus and emphasizing the significance of embryonic implantation and intrauterine growth in human genetic selection mechanisms.

Variant Impact Predictor database (VIPdb), version 2: trends from three decades of genetic variant impact predictors.

BACKGROUND: Variant interpretation is essential for identifying patients' disease-causing genetic variants amongst the millions detected in their genomes. Hundreds of Variant Impact Predictors (VIPs), also known as Variant Effect Predictors (VEPs), have been developed for this purpose, with a variety of methodologies and goals. To facilitate the exploration of available VIP options, we have created the Variant Impact Predictor database (VIPdb). RESULTS: The Variant Impact Predictor database (VIPdb) version 2 presents a collection of VIPs developed over the past three decades, summarizing their characteristics, ClinGen calibrated scores, CAGI assessment results, publication details, access information, and citation patterns. We previously summarized 217 VIPs and their features in VIPdb in 2019. Building upon this foundation, we identified and categorized an additional 190 VIPs, resulting in a total of 407 VIPs in VIPdb version 2. The majority of the VIPs have the capacity to predict the impacts of single nucleotide variants and nonsynonymous variants. More VIPs tailored to predict the impacts of insertions and deletions have been developed since the 2010s. In contrast, relatively few VIPs are dedicated to the prediction of splicing, structural, synonymous, and regulatory variants. The increasing rate of citations to VIPs reflects the ongoing growth in their use, and the evolving trends in citations reveal development in the field and individual methods. CONCLUSIONS: VIPdb version 2 summarizes 407 VIPs and their features, potentially facilitating VIP exploration for various variant interpretation applications. VIPdb is available at  https://genomeinterpretation.org/vipdb.

HiFi long-read amplicon sequencing for full-spectrum variants of human mtDNA.

BACKGROUND: Mitochondrial diseases (MDs) can be caused by single nucleotide variants (SNVs) and structural variants (SVs) in the mitochondrial genome (mtDNA). Presently, identifying deletions in small to medium-sized fragments and accurately detecting low-percentage variants remains challenging due to the limitations of next-generation sequencing (NGS). METHODS: In this study, we integrated targeted long-range polymerase chain reaction (LR-PCR) and PacBio HiFi sequencing to analyze 34 participants, including 28 patients and 6 controls. Of these, 17 samples were subjected to both targeted LR-PCR and to compare the mtDNA variant detection efficacy. RESULTS: Among the 28 patients tested by long-read sequencing (LRS), 2 patients were found positive for the m.3243 A > G hotspot variant, and 20 patients exhibited single or multiple deletion variants with a proportion exceeding 4%. Comparison between the results of LRS and NGS revealed that both methods exhibited similar efficacy in detecting SNVs exceeding 5%. However, LRS outperformed NGS in detecting SNVs with a ratio below 5%. As for SVs, LRS identified single or multiple deletions in 13 out of 17 cases, whereas NGS only detected single deletions in 8 cases. Furthermore, deletions identified by LRS were validated by Sanger sequencing and quantified in single muscle fibers using real-time PCR. Notably, LRS also effectively and accurately identified secondary mtDNA deletions in idiopathic inflammatory myopathies (IIMs). CONCLUSIONS: LRS outperforms NGS in detecting various types of SNVs and SVs in mtDNA, including those with low frequencies. Our research is a significant advancement in medical comprehension and will provide profound insights into genetics.

MiRiQ Database: A Platform for In Silico Rice Mutant Screening.

Genetic studies using mutant resources have significantly contributed to elucidating plant gene function. Massive mutant libraries sequenced by next-generation sequencing technology facilitate mutant identification and functional analysis of genes of interest. Here, we report the creation and release of an open-access database (https://miriq.agr.kyushu-u.ac.jp/index.php), called Mutation-induced Rice in Kyushu University (MiRiQ), designed for in silico mutant screening based on a whole-genome-sequenced mutant library. This database allows any user to easily find mutants of interest without laborious efforts such as large-scale screening by PCR. The initial version of the MiRiQ database (version 1.0) harbors a total of 1.6 million single-nucleotide variants (SNVs) and InDels of 721 M1 plants that were mutagenized by N-methyl-N-nitrosourea treatment of the rice cultivar Nipponbare (Oryza sativa ssp. japonica). The SNVs were distributed among 87% of all 35,630 annotated protein-coding genes of the Nipponbare genome and were predicted to induce missense and nonsense mutations. The MiRiQ database provides built-in tools, such as a search tool by keywords and JBrowse for mutation searches. Users can request mutant seeds in the M2 or M3 generations from a request form linked to this database. We believe that the availability of a wide range of gene mutations in this database will benefit the plant science community and breeders worldwide by accelerating functional genomic research and crop improvement.

New approaches to predict the effect of co-occurring variants on protein characteristics.

Predicting the effect of a mutated gene before the onset of symptoms of genetic diseases would greatly facilitate diagnosis and potentiate early intervention. There have been myriad attempts to predict the effects of single-nucleotide variants. However, the applicability of these efforts does not scale to co-occurring variants. Furthermore, an increasing number of protein therapeutics contain co-occurring nucleotide variations, adding uncertainty during development to the safety and efficiency of these drugs. Co-occurring nucleotide variants may often have synergistic, additive, or antagonistic effects on protein attributes, further complicating the task of outcome prediction. We tested four models based on the cooperative and antagonistic effects of co-occurring variants to predict pathogenicity and effectiveness of protein therapeutics. A total of 30 attributes, including amino acid and nucleotide features, as well as existing single-variant effect prediction tools, were considered on the basis of previous studies on single-nucleotide variants. Importantly, the effects of synonymous variants, often seen in protein therapeutics, were also included in our models. We used 12 datasets of people with monogenic diseases and controls with co-occurring genetic variants to evaluate the accuracy of our models, accomplishing a degree of accuracy comparable to that of prediction tools for single-nucleotide variants. More importantly, our framework is generalizable to new, well-curated datasets of monogenic diseases and new variant scoring tools. This approach successfully assists in addressing the challenging task of predicting the effect of co-occurring variants on pathogenicity and protein effectiveness and is applicable for a wide range of protein therapeutics and genetic diseases.

Changes in intrahost genetic diversity according to lesion severity in longitudinal HPV16 samples.

Human papillomavirus type 16 (HPV16) is the most common cause of cervical cancer, but most infections are transient with lesions not progressing to cancer. There is a lack of specific biomarkers for early cancer risk stratification. This study aimed to explore the intrahost HPV16 genomic variation in longitudinal samples from HPV16-infected women with different cervical lesion severity (normal, low-grade, and high-grade). The TaME-seq deep sequencing protocol was used to generate whole genome HPV16 sequences of 102 samples collected over time from 40 individuals. Single nucleotide variants (SNVs) and intrahost SNVs (iSNVs) were identified in the viral genomes. A majority of individuals had a unique set of SNVs and these SNVs were stable over time. Overall, the number of iSNVs and APOBEC3-induced iSNVs were significantly lower in high-grade relative to normal and low-grade samples. A significant increase in the number of APOBEC3-induced iSNVs over time was observed for normal samples when compared to high-grade. Our results indicates that the lower incidence of iSNVs and APOBEC3-induced iSNVs in high-grade lesions may have implications for novel biomarkers discoveries, potentially aiding early stratification of HPV-induced cervical precancerous lesions.

Intramolecular Nucleophilic Vinylic Substitution (SNV) by Carbon Nucleophiles: Conformationally Directed Formation of Dienes from N,N'-Diallyl Ureas.

Nucleophilic vinylic substitution (SNV) by carbon nucleophiles allows the formation of vinylic C-C bonds without transition metal catalysts. In this paper, we show that tethering two alkenes together through a urea linkage can lead to the formation of a diene by an intramolecular SNV reaction. The starting materials are fully substituted N,N'-diallyl ureas; the reaction proceeds in the presence of base, and entails a cascade of deprotonations, reprotonations, and an SNV reaction of an allylic carbanion on a rare electrophile: a vinylic urea. As a result, two allylic substituents couple to form a diene, despite the fact that neither is activated towards electrophilic attack. The reaction is tolerant of significant steric bulk, and exhibits regioselectivity with unsymmetrical diallyl ureas: ß-substituted allyl groups invariably behave as nucleophiles, while electrophilic behavior may be enforced by the use of an E-vinylic urea substituent that cannot be deprotonated under the reaction conditions.

Evidence for etiologic field changes in tongue distant from tumor in patients with squamous cell carcinoma of the oral tongue.

Oral cancer is a paradigm of Slaughter's concept of field cancerization, where tumors are thought to originate within an area of cells containing genetic alterations that predispose to cancer development. The field size is unclear but may represent a large area of tissue, and the origin of mutations is also unclear. Here, we analyzed whole exome and transcriptome features in contralateral tumor-distal tongue (i.e. distant from the tumor, not tumor-adjacent) and corresponding tumor tissues of 15 patients with squamous cell carcinoma of the oral tongue. The number of point mutations ranged from 41 to 237 in tumors and from one to 78 in tumor-distal samples. Tumor-distal samples showed mainly clock-like (associated with aging) or tobacco smoking mutational signatures. Tumors additionally showed mutations that associate with cytidine deaminase AID/APOBEC enzyme activities or a UV-like signature. Importantly, no point mutations were shared between a tumor and the matched tumor-distal sample in any patient. TP53 was the most frequently mutated gene in tumors (67%), whereas a TP53 mutation was detected in only one tumor-distal sample, and this mutation was not shared with the matched tumor. Arm-level copy number variation (CNV) was found in 12 tumors, with loss of chromosome (Chr) 8p or gain of 8q being the most frequent events. Two tumor-distal samples showed a gain of Chr8, which was associated with increased expression of Chr8-located genes in these samples, although gene ontology did not show a role for these genes in oncogenic processes. In situ hybridization revealed a mixed pattern of Chr8 gain and neutral copy number in both tumor cells and adjacent nontumor epithelium in one patient. We conclude that distant field cancerization exists but does not present as tumor-related mutational events. The data are compatible with etiologic field effects, rather than classical monoclonal field cancerization theory. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

The VEGFA rs3025039 Variant Is a Risk Factor for Breast Cancer in Mexican Women.

Breast cancer (BC) is the leading cause of death from tumors in women worldwide, influenced by various factors, including genetics. The T allele of the single nucleotide variant (SNV) rs3025039 at position +936 of the VEGFA gene has been reported to affect the mRNA regulatory mechanisms, potentially altering VEGFA expression and increasing BC risk. This study aimed to investigate the association between rs3025039 and BC in Mexican women residing in Jalisco, Mexico. The study included 231 women with a confirmed diagnosis of BC and 201 healthy subjects as a reference group (RG). PCR-RFLP was employed for the genotyping of rs3025039, with the visualization of amplified products using polyacrylamide gel electrophoresis. Significant differences were observed in rs3025039 alleles and genotypes between BC cases and the RG (p = 0.0038). The frequency of the T allele and the CT genotype was higher in the BC group compared to the RG, with a significant difference (p = 0.0006). In conclusion, this research suggests that the SNV rs3025039 is associated with a higher risk of BC in Mexican women. These findings enhance our understanding of the genetic underpinnings of BC in this population, offering potential insights for future studies and interventions.

A Bioinformatics Toolkit for Next-Generation Sequencing in Clinical Oncology.

Next-generation sequencing (NGS) has taken on major importance in clinical oncology practice. With the advent of targeted therapies capable of effectively targeting specific genomic alterations in cancer patients, the development of bioinformatics processes has become crucial. Thus, bioinformatics pipelines play an essential role not only in the detection and in identification of molecular alterations obtained from NGS data but also in the analysis and interpretation of variants, making it possible to transform raw sequencing data into meaningful and clinically useful information. In this review, we aim to examine the multiple steps of a bioinformatics pipeline as used in current clinical practice, and we also provide an updated list of the necessary bioinformatics tools. This resource is intended to assist researchers and clinicians in their genetic data analyses, improving the precision and efficiency of these processes in clinical research and patient care.

Identification of Novel Genetic Risk Factors for Focal Segmental Glomerulosclerosis in Children: Results From the Chronic Kidney Disease in Children (CKiD) Cohort.

RATIONALE & OBJECTIVE: Focal segmental glomerulosclerosis (FSGS) is a major cause of pediatric nephrotic syndrome, and African Americans exhibit an increased risk for developing FSGS compared with other populations. Predisposing genetic factors have previously been described in adults. Here we performed genomic screening of primary FSGS in a pediatric African American population. STUDY DESIGN: Prospective cohort with case-control genetic association study design. SETTING & PARTICIPANTS: 140 African American children with chronic kidney disease from the Chronic Kidney Disease in Children (CKiD) cohort, including 32 cases with FSGS. PREDICTORS: Over 680,000 common single-nucleotide polymorphisms (SNPs) were tested for association. We also ran a pathway enrichment analysis and a human leucocyte antigen (HLA)-focused association study. OUTCOME: Primary biopsy-proven pediatric FSGS. ANALYTICAL APPROACH: Multivariate logistic regression models. RESULTS: The genome-wide association study revealed 169 SNPs from 14 independent loci significantly associated with FSGS (false discovery rate [FDR]<5%). We observed notable signals for genetic variants within the APOL1 (P=8.6×10-7; OR, 25.8 [95% CI, 7.1-94.0]), ALMS1 (P=1.3×10-7; 13.0% in FSGS cases vs 0% in controls), and FGFR4 (P=4.3×10-6; OR, 24.8 [95% CI, 6.3-97.7]) genes, all of which had previously been associated with adult FSGS, kidney function, or chronic kidney disease. We also highlighted novel, functionally relevant genes, including GRB2 (which encodes a slit diaphragm protein promoting podocyte structure through actin polymerization) and ITGB1 (which is linked to renal injuries). Our results suggest a major role for immune responses and antigen presentation in pediatric FSGS through (1) associations with SNPs in PTPRJ (or CD148, P=3.5×10-7), which plays a role in T-cell receptor signaling, (2) HLA-DRB1∗11:01 association (P=6.1×10-3; OR, 4.5 [95% CI, 1.5-13.0]), and (3) signaling pathway enrichment (P=1.3×10-6). LIMITATIONS: Sample size and no independent replication cohort with genomic data readily available. CONCLUSIONS: Our genetic study has identified functionally relevant risk factors and the importance of immune regulation for pediatric primary FSGS, which contributes to a better description of its molecular pathophysiological mechanisms. PLAIN-LANGUAGE SUMMARY: We assessed the genetic risk factors for primary focal segmental glomerulosclerosis (FSGS) by simultaneously testing over 680,000 genetic markers spread across the genome in 140 children, including 32 with FSGS lesions. Fourteen independent genetic regions were significantly associated with pediatric FSGS, including APOL1 and ALMS1-NAT8, which were previously found to be associated with FSGS and chronic kidney diseases in adults. Novel genes with relevant biological functions were also highlighted, such as GRB2 and FGFR4, which play a role in the kidney filtration barrier and in kidney cell differentiation, respectively. Finally, we revealed the importance of immune regulation in pediatric FSGS through associations involving cell surface proteins presenting antigens to the immune system and interacting with T-cell receptors.

A common variant close to the "tripwire" linker region of NLRP1 contributes to severe COVID-19.

OBJECTIVE AND DESIGN: The heterogeneity of response to SARS-CoV-2 infection is directly linked to the individual genetic background. Genetic variants of inflammasome-related genes have been pointed as risk factors for several inflammatory sterile and infectious disease. In the group of inflammasome receptors, NLRP1 stands out as a good novel candidate as severity factor for COVID-19 disease. METHODS: To address this question, we performed an association study of NLRP1, DPP9, CARD8, IL1B, and IL18 single nucleotide variants (SNVs) in a cohort of 945 COVID-19 patients. RESULTS: The NLRP1 p.Leu155His in the linker region, target of viral protease, was significantly associated to COVID-19 severity, which could contribute to the excessive cytokine release reported in severe cases. CONCLUSION: Inflammasome genetic background contributes to individual response to SARS-CoV-2.

Intra-host mutation rate of acute SARS-CoV-2 infection during the initial pandemic wave.

SARS-CoV-2 mutation is minimized through a proofreading function encoded by NSP-14. Most estimates of the SARS-CoV-2 mutation rate are derived from population based sequence data. Our understanding of SARS-CoV-2 evolution might be enhanced through analysis of intra-host viral mutation rates in specific populations. Viral genome analysis was performed between paired samples and mutations quantified at allele frequencies (AF) ≥ 0.25, ≥ 0.5 and ≥ 0.75. Mutation rate was determined employing F81 and JC69 evolution models and compared between isolates with (ΔNSP-14) and without (wtNSP-14) non-synonymous mutations in NSP-14 and by patient comorbidity. Forty paired samples with median interval of 13 days [IQR 8.5-20] were analyzed. The estimated mutation rate by F81 modeling was 93.6 (95%CI 90.8-96.4], 40.7 (95%CI 38.9-42.6) and 34.7 (95%CI 33.0-36.4) substitutions/genome/year at AF ≥ 0.25, ≥ 0.5, ≥ 0.75 respectively. Mutation rate in ΔNSP-14 were significantly elevated at AF ≥ 0.25 vs wtNSP-14. Patients with immune comorbidities had higher mutation rate at all allele frequencies. Intra-host SARS-CoV-2 mutation rates are substantially higher than those reported through population analysis. Virus strains with altered NSP-14 have accelerated mutation rate at low AF. Immunosuppressed patients have elevated mutation rate at all AF. Understanding intra-host virus evolution will aid in current and future pandemic modeling.

HCM-associated ALMS1 variant: Allele drop-out and frequency in Italian Sphynx cats.

Hypertrophic cardiomyopathy (HCM) is the most common cardiomyopathy in domestic cats, and some inherited variants are available for genetic testing. A variant of the Alstrom syndrome protein 1 gene (ALMS1) was recently reported to be associated with HCM in the Sphynx cat breed (A3: g.92439157G>C). Genetic screening of the variant, promoted by the Osservatorio Veterinario Italiano Cardiopatie and Genefast Laboratory, was offered to Sphynx cat owners and breeders in Italy. Genotype data were initially obtained by Sanger sequencing. In one case where the samples of a trio were available, inconsistency in the vertical transmission of the variant suggested an allele dropout (ADO) of the wt allele. A new external primer pair was designed as an alternative to the original. The larger PCR product obtained was sanger sequenced, and five novel single nucleotide variants (SNVs) not yet annotated in open-access databases were detected. Three of these SNVs were within the original primer-binding regions and were assumed to have caused ADO. The haplotype, including the ADO SNVs, was detected in two cats belonging to different lineages. To accurately genotype ALMS1 g.92439157G>C in the samples, we set up a real-time TaqMan MGB assay while avoiding all surrounding SNVs. At g.92439157G>C, for 136 Sphynx cats, g.92439157 C variant was highly widespread (freq. >0.50). The present study reports five new variants surrounding ALMS1 g.92439157G>C that must be considered when designing the test. The study also indicates the need to verify the correspondence between the g.92439157 C variant frequency and the prevalence of HCM by increasing clinical visits and follow-ups and finally to promote genetic counselling for accurate management of mating plans in Italian Sphynx cats.

Diversity and Classification of Genetic Variations in Autism Spectrum Disorder.

Autism spectrum disorder (ASD) is a neurodevelopmental condition with symptoms that affect the whole personality and all aspects of life. Although there is a high degree of heterogeneity in both its etiology and its characteristic behavioral patterns, the disorder is well-captured along the autistic triad. Currently, ASD status can be confirmed following an assessment of behavioral features, but there is a growing emphasis on conceptualizing autism as a spectrum, which allows for establishing a diagnosis based on the level of support need, free of discrete categories. Since ASD has a high genetic predominance, the number of genetic variations identified in the background of the condition is increasing exponentially as genetic testing methods are rapidly evolving. However, due to the huge amount of data to be analyzed, grouping the different DNA variations is still challenging. Therefore, in the present review, a multidimensional classification scheme was developed to accommodate most of the currently known genetic variants associated with autism. Genetic variations have been grouped according to six criteria (extent, time of onset, information content, frequency, number of genes involved, inheritance pattern), which are themselves not discrete categories, but form a coherent continuum in line with the autism spectrum approach.