The cancer-risk variant frequency among Polish population reported by the first national whole-genome sequencing study.

Introduction: Population-based cancer screening has raised many controversies in recent years, not only regarding the costs but also regarding the ethical nature and issues related to variant interpretation. Nowadays, genetic cancer screening standards are different in every country and usually encompass only individuals with a personal or family history of relevant cancer. Methods: Here we performed a broad genetic screening for cancer-related rare germline variants on population data from the Thousand Polish Genomes database based on 1076 Polish unrelated individuals that underwent whole genome sequencing (WGS). Results: We identified 19 551 rare variants in 806 genes related to oncological diseases, among them 89% have been located in non-coding regions. The combined BRCA1/BRCA2 pathogenic/likely pathogenic according to ClinVar allele frequency in the unselected population of 1076 Poles was 0.42%, corresponding to nine carriers. Discussion: Altogether, on the population level, we found especially problematic the assessment of the pathogenicity of variants and the relation of ACMG guidelines to the population frequency. Some of the variants may be overinterpreted as disease-causing due to their rarity or lack of annotation in the databases. On the other hand, some relevant variants may have been overseen given that there is little pooled population whole genome data on oncology. Before population WGS screening will become a standard, further studies are needed to assess the frequency of the variants suspected to be pathogenic on the population level and with reporting of likely benign variants.

Better safe than sorry-Whole-genome sequencing indicates that missense variants are significant in susceptibility to COVID-19.

Undoubtedly, genetic factors play an important role in susceptibility and resistance to COVID-19. In this study, we conducted the GWAS analysis. Out of 15,489,173 SNPs, we identified 18,191 significant SNPs for severe and 11,799 SNPs for resistant phenotype, showing that a great number of loci were significant in different COVID-19 representations. The majority of variants were synonymous (60.56% for severe, 58.46% for resistant phenotype) or located in introns (55.77% for severe, 59.83% for resistant phenotype). We identified the most significant SNPs for a severe outcome (in AJAP1 intron) and for COVID resistance (in FIG4 intron). We found no missense variants with a potential causal function on resistance to COVID-19; however, two missense variants were determined as significant a severe phenotype (in PM20D1 and LRP4 exons). None of the aforementioned SNPs and missense variants found in this study have been previously associated with COVID-19.

Population WGS-based spinal muscular atrophy carrier screening in a cohort of 1076 healthy Polish individuals.

Spinal muscular atrophy is a severe neuromuscular disorder with an autosomal recessive inheritance pattern. The disease-causing gene is SMN1, and its paralogue, SMN2, is a disease course modifier. Both genes SMN1 and SMN2 show over 99.9% sequence identity and a high rate of crossing over in the genomic region. Due to this reason, SMN1/SMN2 is usually excluded from the whole-genome sequencing (WGS) analysis and investigated with traditional methods, such as MLPA and qPCR. Recently, novel bioinformatic algorithms dedicated to analyzing this particular genomic region have been developed. Here, we analyze the SMN1/SMN2 genomic region with a dedicated program, SMNCopyNumberCaller. We report a similar prevalence of SMN1 gene deletion carrier status (1 per 41 people) to published data from the Polish population (1 per 35 people). Additionally, SMNCopyNumberCaller can identify SMN2 CNVs and SMN2Δ7-8 present in 153 healthy Polish individuals. Two other programs for the CNV analysis in standard genomic regions were not able to provide reliable results. Using WGS-based tools for SMN1/2 genomic region analysis is not only an efficient method in terms of time but will also enable more complex analysis such screening for markers related with a silent carrier status and identification of further genetic modifiers. Although still an experimental method, soon WGS-based SMN1/SMN2 carrier identification may become a standard method for patients screened with WGS for other purposes.

Case report: The cardio-facio-cutaneous syndrome due to a novel germline mutation in MAP2K1: A multifaceted disease with immunodeficiency and short stature.

Cardio-facio-cutaneous syndrome (CFCS) belongs to the group of RASopathies, clinical disorders defined by disruptions in the RAS/MAPK signaling pathway. It is caused by heterozygous gain-of-function germline mutations in genes encoding protein kinases: BRAF, MAP2K1 (MEK1), MAP2K2 (MEK2), and in the GTPase-encoding gene KRAS. CFCS is characterized by craniofacial dysmorphic features, congenital heart defects, severe malnutrition, proportionate short stature, anomalies within the structure of skin and hair, and psychomotor disability. The pathophysiology of growth impairment is multifactorial with feeding difficulties, growth hormone deficiency, and insensitivity. Immunodeficiency has not been hitherto reported as an integral part of CFCS yet an increased activation of the RAS/MAPK signaling pathway may contribute to explaining the causal relationship between RASopathy and the dysfunctions within the B and T lymph cell compartments resulting in a deficiency in T cell costimulation and B cell maturation with impaired class switch recombination, somatic hypermutation, and high-affinity antibody production. We report on a boy born prematurely at 32 WGA, with the perinatal period complicated by pneumonia, respiratory distress syndrome, and valvular pulmonary stenosis. The boy suffered from recurrent pneumonia, obstructive bronchitis, sepsis, urinary tract infection, and recurrent fevers. He presented with severe hypotrophy, psychomotor disability, short stature, craniofacial dysmorphism, dental hypoplasia, sparse hair, and cryptorchidism. Whole genome sequencing showed a novel heterozygous pathogenic germline missense variant: c.364A > G; p.Asn122Asp in the MAP2K1 gene, supporting the diagnosis of CFCS. The immunological workup revealed hypogammaglobulinemia, IgG subclass, and specific antibody deficiency accompanied by decreased numbers of T helper cells and naive and memory B cells. Replacement immunoglobulin therapy with timely antibiotic prophylaxis were instituted. At the age of six years, growth hormone deficiency was diagnosed and the rGH therapy was started. The ever-increasing progress in genetic studies contributes to establishing the definitive CFCS diagnosis and sheds the light on the interrelated genotype-phenotype heterogeneity of RASopathies. Herein, we add new phenotypic features of predominating humoral immunodeficiency to the symptomatology of CFCS with a novel mutation in MAP2K1. While CFCS is a multifaceted disease, increased pediatricians' awareness is needed to prevent the delay in diagnostics and therapeutic interventions.

DBFE: distribution-based feature extraction from structural variants in whole-genome data.

MOTIVATION: Whole-genome sequencing has revolutionized biosciences by providing tools for constructing complete DNA sequences of individuals. With entire genomes at hand, scientists can pinpoint DNA fragments responsible for oncogenesis and predict patient responses to cancer treatments. Machine learning plays a paramount role in this process. However, the sheer volume of whole-genome data makes it difficult to encode the characteristics of genomic variants as features for learning algorithms. RESULTS: In this article, we propose three feature extraction methods that facilitate classifier learning from sets of genomic variants. The core contributions of this work include: (i) strategies for determining features using variant length binning, clustering and density estimation; (ii) a programing library for automating distribution-based feature extraction in machine learning pipelines. The proposed methods have been validated on five real-world datasets using four different classification algorithms and a clustering approach. Experiments on genomes of 219 ovarian, 61 lung and 929 breast cancer patients show that the proposed approaches automatically identify genomic biomarkers associated with cancer subtypes and clinical response to oncological treatment. Finally, we show that the extracted features can be used alongside unsupervised learning methods to analyze genomic samples. AVAILABILITY AND IMPLEMENTATION: The source code of the presented algorithms and reproducible experimental scripts are available on Github at https://github.com/MNMdiagnostics/dbfe. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Beyond GWAS-Could Genetic Differentiation within the Allograft Rejection Pathway Shape Natural Immunity to COVID-19?

COVID-19 infections pose a serious global health concern so it is crucial to identify the biomarkers for the susceptibility to and resistance against this disease that could help in a rapid risk assessment and reliable decisions being made on patients' treatment and their potential hospitalisation. Several studies investigated the factors associated with severe COVID-19 outcomes that can be either environmental, population based, or genetic. It was demonstrated that the genetics of the host plays an important role in the various immune responses and, therefore, there are different clinical presentations of COVID-19 infection. In this study, we aimed to use variant descriptive statistics from GWAS (Genome-Wide Association Study) and variant genomic annotations to identify metabolic pathways that are associated with a severe COVID-19 infection as well as pathways related to resistance to COVID-19. For this purpose, we applied a custom-designed mixed linear model implemented into custom-written software. Our analysis of more than 12.5 million SNPs did not indicate any pathway that was significant for a severe COVID-19 infection. However, the Allograft rejection pathway (hsa05330) was significant (p = 0.01087) for resistance to the infection. The majority of the 27 SNP marking genes constituting the Allograft rejection pathway were located on chromosome 6 (19 SNPs) and the remainder were mapped to chromosomes 2, 3, 10, 12, 20, and X. This pathway comprises several immune system components crucial for the self versus non-self recognition, but also the components of antiviral immunity. Our study demonstrated that not only single variants are important for resistance to COVID-19, but also the cumulative impact of several SNPs within the same pathway matters.

The Thousand Polish Genomes-A Database of Polish Variant Allele Frequencies.

Although Slavic populations account for over 4.5% of world inhabitants, no centralised, open-source reference database of genetic variation of any Slavic population exists to date. Such data are crucial for clinical genetics, biomedical research, as well as archeological and historical studies. The Polish population, which is homogenous and sedentary in its nature but influenced by many migrations of the past, is unique and could serve as a genetic reference for the Slavic nations. In this study, we analysed whole genomes of 1222 Poles to identify and genotype a wide spectrum of genomic variation, such as small and structural variants, runs of homozygosity, mitochondrial haplogroups, and de novo variants. Common variant analyses showed that the Polish cohort is highly homogenous and shares ancestry with other European populations. In rare variant analyses, we identified 32 autosomal-recessive genes with significantly different frequencies of pathogenic alleles in the Polish population as compared to the non-Finish Europeans, including C2, TGM5, NUP93, C19orf12, and PROP1. The allele frequencies for small and structural variants, calculated for 1076 unrelated individuals, are released publicly as The Thousand Polish Genomes database, and will contribute to the worldwide genomic resources available to researchers and clinicians.

Validation of HER2 Status in Whole Genome Sequencing Data of Breast Cancers with the Ploidy-Corrected Copy Number Approach.

BACKGROUND AND OBJECTIVE: Human epidermal growth factor receptor 2 (HER2) protein overexpression is one of the most significant biomarkers for breast cancer diagnostics, treatment prediction, and prognostics. The high accessibility of HER2 inhibitors in routine clinical practice directly translates into the diagnostic need for precise and robust marker identification. Even though multigene next-generation sequencing methodologies have slowly taken over the field of single-biomarker molecular tests, the copy number alterations such as amplification of the HER2-coding ERBB2 gene are hard to validate on next-generation sequencing platforms as they are characterized by chromosomal structural heterogeneity, polysomy, and genomic context of ploidy. In our study, we tested the approach of using whole genome sequencing instead of next-generation sequencing panels to determine HER2 status in the clinical set-up. METHODS: We used a large dataset of 876 patients with breast cancer whole genomes with curated clinical data and an additional set of 551 patients' external genomic data. We used the decision-tree-based algorithm for optimization of the diagnostic tool for HER2 status assessment by whole genome sequencing. RESULTS: The most efficient approach to assess HER2 status in whole genome sequencing data was the ploidy-corrected copy number, utilizing ERBB2 copy number and mean tumor ploidy. The classifier achieved sensitivity of 91.18% and specificity of 98.69% on the internal validation dataset and 89.86% and 96.06% on the external data, which is similar to other next-generation sequencing methods, currently tested in the clinic. CONCLUSIONS: We provide evidence that the HER2 status may be reliably determined by whole genome sequencing and is applicable across different laboratory protocols and pipelines. We suggest using the ploidy-corrected copy number for diagnostic purposes.

Analysis of Single Nucleotide Variants (SNVs) Induced by Passages of Equine Influenza Virus H3N8 in Embryonated Chicken Eggs.

Vaccination is an effective method for the prevention of influenza virus infection. Many manufacturers use embryonated chicken eggs (ECE) for the propagation of vaccine strains. However, the adaptation of viral strains during subsequent passages can lead to additional virus evolution and lower effectiveness of the resulting vaccines. In our study, we analyzed the distribution of single nucleotide variants (SNVs) of equine influenza virus (EIV) during passaging in ECE. Viral RNA from passage 0 (nasal swabs), passage 2 and 5 was sequenced using next generation technology. In total, 50 SNVs with an occurrence frequency above 2% were observed, 29 of which resulted in amino acid changes. The highest variability was found in passage 2, with the most variable segment being IV encoding hemagglutinin (HA). Three variants, HA (W222G), PB2 (A377E) and PA (R531K), had clearly increased frequency with the subsequent passages, becoming dominant. None of the five nonsynonymous HA variants directly affected the major antigenic sites; however, S227P was previously reported to influence the antigenicity of EIV. Our results suggest that although host-specific adaptation was observed in low passages of EIV in ECE, it should not pose a significant risk to influenza vaccine efficacy.