The aims of the present study were to assess (1) the parental origin of trisomy 21 and the stage in which nondisjunction occurs and (2) the relationship between altered genetic recombination and maternal age as risk factors for trisomy 21. The study included 102 cases with Down syndrome from the Croatian population. Genotyping analyses were performed by polymerase chain reaction using 11 short tandem repeat markers along chromosome 21q. The vast majority of trisomy 21 was of maternal origin (93%), followed by paternal (5%) and mitotic origin (2%). The frequencies of maternal meiotic I (MI) and meiotic II errors were 86% and 14%, respectively. The highest proportion of cases with zero recombination was observed among those with maternal MI derived trisomy 21. A higher proportion of telomeric exchanges were presented in cases with maternal MI errors and cases with young mothers, although these findings were not statistically significant. The present study is the first report examining parental origin and altered genetic recombination as a risk factor for trisomy 21 in a Croatian population. The results support that trisomy 21 has a universal genetic etiology across different human populations.

Balanced chromosome abnormalities (BCAs) occur at a high frequency in healthy and diseased individuals, but cost-efficient strategies to identify BCAs and evaluate whether they contribute to a phenotype have not yet become widespread. Here we apply genome-wide mate-pair library sequencing to characterize structural variation in a patient with unclear neurodevelopmental disease (NDD) and complex de novo BCAs at the karyotype level. Nucleotide-level characterization of the clinically described BCA breakpoints revealed disruption of at least three NDD candidate genes (LINC00299, NUP205, PSMD14) that gave rise to abnormal mRNAs and could be assumed as disease-causing. However, unbiased genome-wide analysis of the sequencing data for cryptic structural variation was key to reveal an additional submicroscopic inversion that truncates the schizophrenia- and bipolar disorder-associated brain transcription factor ZNF804A as an equally likely NDD-driving gene. Deep sequencing of fluorescent-sorted wild-type and derivative chromosomes confirmed the clinically undetected BCA. Moreover, deep sequencing further validated a high accuracy of mate-pair library sequencing to detect structural variants larger than 10 kB, proposing that this approach is powerful for clinical-grade genome-wide structural variant detection. Our study supports previous evidence for a role of ZNF804A in NDD and highlights the need for a more comprehensive assessment of structural variation in karyotypically abnormal individuals and patients with neurocognitive disease to avoid diagnostic deception.

The purpose of this study was to determine prevalence of Chlamydia trachomatis (Ct) urogenital infection and its serotype distribution from clinical samples in north-eastern Croatia. During a 3-year period, 2,379 urogenital samples were analyzed by real-time polymerase chain reaction (A group), while 4,846 genital swabs were analyzed by direct fluorescent antibody test (B group). 132 Ct positive specimens were genotyped by omp1 gene sequencing. The prevalence rate of Ct was 3.2 % in A and 1 % in B group. The most prevalent chlamydial genotype was E (44 %), followed by F (33 %), K (11.5 %), G (8 %), J/UW (5.3 %), D-IC (4.4 %), D-B120 (1.8 %), and B/IU, J/IU, Ia/IU (0.9 % each) serotypes. Single-nucleotide polymorphisms (SNPs) of omp1 gene were detected in E, K, and G serotypes. Some of these SNPs (C/T at position 272 and G/A at position 813 in E strain; C/T at position 884 in D strain) might represent novel omp1 variants.

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Organoids generated from human pluripotent stem cells provide experimental systems to study development and disease, but quantitative measurements across different spatial scales and molecular modalities are lacking. In this study, we generated multiplexed protein maps over a retinal organoid time course and primary adult human retinal tissue. We developed a toolkit to visualize progenitor and neuron location, the spatial arrangements of extracellular and subcellular components and global patterning in each organoid and primary tissue. In addition, we generated a single-cell transcriptome and chromatin accessibility timecourse dataset and inferred a gene regulatory network underlying organoid development. We integrated genomic data with spatially segmented nuclei into a multimodal atlas to explore organoid patterning and retinal ganglion cell (RGC) spatial neighborhoods, highlighting pathways involved in RGC cell death and showing that mosaic genetic perturbations in retinal organoids provide insight into cell fate regulation.