Understanding genetic variability: exploring large-scale copy number variants through non-invasive prenatal testing in European populations

Large-scale copy number variants (CNVs) are structural alterations in the genome that involve the duplication or deletion of DNA segments, contributing to genetic diversity and playing a crucial role in the evolution and development of various diseases and disorders, as they can lead to the dosage imbalance of one or more genes. Massively parallel sequencing (MPS) has revolutionized the field of genetic analysis and contributed significantly to routine clinical diagnosis and screening. It offers a precise method for detecting CNVs with exceptional accuracy. In this context, a non-invasive prenatal test (NIPT) based on the sequencing of cell-free DNA (cfDNA) from pregnant women's plasma using a low-coverage whole genome MPS (WGS) approach represents a valuable source for population studies. Here, we analyzed genomic data of 12,732 pregnant women from the Slovak (9,230), Czech (1,583), and Hungarian (1,919) populations. We identified 5,062 CNVs ranging from 200 kbp and described their basic characteristics and differences between the subject populations. Our results suggest that re-analysis of sequencing data from routine WGS assays has the potential to obtain large-scale CNV population frequencies, which are not well known and may provide valuable information to support the classification and interpretation of this type of genetic variation. Furthermore, this could contribute to expanding knowledge about the central European genome without investing in additional laboratory work, as NIPTs are a relatively widely used screening method.

Evaluation and limitations of different approaches among COVID-19 fatal cases using whole-exome sequencing data

BACKGROUND

COVID-19 caused by the SARS-CoV-2 infection may result in various disease symptoms and severity, ranging from asymptomatic, through mildly symptomatic, up to very severe and even fatal cases. Although environmental, clinical, and social factors play important roles in both susceptibility to the SARS-CoV-2 infection and progress of COVID-19 disease, it is becoming evident that both pathogen and host genetic factors are important too. In this study, we report findings from whole-exome sequencing (WES) of 27 individuals who died due to COVID-19, especially focusing on frequencies of DNA variants in genes previously associated with the SARS-CoV-2 infection and the severity of COVID-19.

RESULTS

We selected the risk DNA variants/alleles or target genes using four different approaches: 1) aggregated GWAS results from the GWAS Catalog; 2) selected publications from PubMed; 3) the aggregated results of the Host Genetics Initiative database; and 4) a commercial DNA variant annotation/interpretation tool providing its own knowledgebase. We divided these variants/genes into those reported to influence the susceptibility to the SARS-CoV-2 infection and those influencing the severity of COVID-19. Based on the above, we compared the frequencies of alleles found in the fatal COVID-19 cases to the frequencies identified in two population control datasets (non-Finnish European population from the gnomAD database and genomic frequencies specific for the Slovak population from our own database). When compared to both control population datasets, our analyses indicated a trend of higher frequencies of severe COVID-19 associated risk alleles among fatal COVID-19 cases. This trend reached statistical significance specifically when using the HGI-derived variant list. We also analysed other approaches to WES data evaluation, demonstrating its utility as well as limitations.

CONCLUSIONS

Although our results proved the likely involvement of host genetic factors pointed out by previous studies looking into severity of COVID-19 disease, careful considerations of the molecular-testing strategies and the evaluated genomic positions may have a strong impact on the utility of genomic testing.

Gentisate and 3-oxoadipate pathways in the yeast Candida parapsilosis: identification and functional analysis of the genes coding for 3-hydroxybenzoate 6-hydroxylase and 4-hydroxybenzoate 1-hydroxylase

The pathogenic yeast Candida parapsilosis degrades various hydroxy derivatives of benzenes and benzoates by the gentisate and 3-oxoadipate pathways. We identified the genes MNX1, MNX2, MNX3, GDX1, HDX1 and FPH1 that code for enzymes involved in these pathways in the complete genome sequence of C. parapsilosis. Next, we demonstrated that MNX1, MNX2, MNX3 and GDX1 are inducible and transcriptionally controlled by hydroxyaromatic substrates present in cultivation media. Our results indicate that MNX1 and MNX2 code for flavoprotein monooxygenases catalysing the first steps in the 3-oxoadipate and gentisate pathways, respectively (i.e. 4-hydroxybenzoate 1-hydroxylase and 3-hydroxybenzoate 6-hydroxylase). Moreover, we found that the two pathways differ by their intracellular localization. The enzymes of the 3-oxoadipate pathway, Mnx1p and Mnx3p, localize predominantly in the cytosol. In contrast, intracellular localization of the components of the gentisate pathway, Mnx2p and Gdx1p, depends on the substrate in the cultivation medium. In cells growing on glucose these proteins localize in the cytosol, whereas in media containing hydroxyaromatic compounds they associate with mitochondria. Finally, we showed that the overexpression of MNX1 or MNX2 increases the tolerance of C. parapsilosis cells to the antifungal drug terbinafine.