Camera Component for the ESTCube-2 Mission Control System

ESTCube-2 on teine Eesti Tudengisatelliidi Programmi satelliidi projekt. Sellepeamiseks uurimisülesandeks on plasma piduri tehnoloogia testimine maa orbiidil. Projekti riistvara ja tarkvara arendavad üliõpilased. Arendamisel on tarkvara nimega missiooni juhtimissüsteem, mis aitaks satelliiti pärast orbiidile saatmist jälgida ja juhtida. Süsteem koosneb mitmest osast ja rakendustest, mis on mikroteenuste arhitektuuri sees ühendatud. Käesoleva lõputöö autor kirjeldab väljakutseid, mis on seotud satelliidi piltide kuvamisega kaasaegses veebirakenduses, analüüsib võimalikke lahendusi ja annab ülevaate tarkvaraprototüübi arenduse protsessist.ESTCube-2 is the second satellite project of the Estonian Student Satellite Programme. Its main scientific mission is to test the plasma break technology on the low Earth orbit. The hardware and the software for the project are developed by students. Computer software called Mission Control System is being developed to monitor and control the satellite after launch. The system consists of multiple components and applications connected in a microservice architecture. This paper focuses on the research and development process of the Mission Control System camera component. The author describes challenges related to displaying the satellite images in a modern web application, analyses possible solutions and provides an overview of the software prototype implementation

Sünnieelne mitteinvasiivne geneetiline sõeluuring – võidukäik ja puudujäägid

Paljudes Euroopa maades on sünnieelne kromosoomhaiguste sõeluuring riiklikult korraldatud: rasedatele pakutakse vereseerumi markerite määramist ning loote ultraheliuuringuid. Uus alternatiivne meetod kromosoomhaigusega loodet kandva rasedate riskirühma selgitamiseks on NIPT ehk loote mitteinvasiivne sünnieelne geneetiline testimine (Non-Invasive Prenatal genetic Testing), mille on Ameerika Ämmaemandate ja Naistearstide Kolleegium ning mitmed Euroopa riigid heaks kiitnud suure riskiga rasedate sõeltestina. Artiklis on antud ülevaade NIPT olemusest, eelistest, puudustest, eetilistest aspektidest ning erinevatest saadaolevatest testidest.Eesti Arst 2016; 95(9):582–58

Systematic evaluation of NIPT aneuploidy detection software tools with clinically validated NIPT samples

Non-invasive prenatal testing (NIPT) is a powerful screening method for fetal aneuploidy detection, relying on laboratory and computational analysis of cell-free DNA. Although several published computational NIPT analysis tools are available, no prior comprehensive, head-to-head accuracy comparison of the various tools has been published. Here, we compared the outcome accuracies obtained for clinically validated samples with five commonly used computational NIPT aneuploidy analysis tools (WisecondorX, NIPTeR, NIPTmer, RAPIDR, and GIPseq) across various sequencing depths (coverage) and fetal DNA fractions. The sample set included cases of fetal trisomy 21 (Down syndrome), trisomy 18 (Edwards syndrome), and trisomy 13 (Patau syndrome). We determined that all of the compared tools were considerably affected by lower sequencing depths, such that increasing proportions of undetected trisomy cases (false negatives) were observed as the sequencing depth decreased. We summarised our benchmarking results and highlighted the advantages and disadvantages of each computational NIPT software. To conclude, trisomy detection for lower coverage NIPT samples (e.g. 2.5M reads per sample) is technically possible but can, with some NIPT tools, produce troubling rates of inaccurate trisomy detection, especially in low-FF samples.Author summaryNon-invasive prenatal testing analysis relies on computational algorithms that are used for inferring chromosomal aneuploidies, such as chromosome 21 triploidy in the case of Down syndrome. However, the performance of these algorithms has not been compared on the same clinically validated data. Here we conducted a head-to-head comparison of WGS-based NIPT aneuploidy detection tools. Our findings indicate that at and below 2.5M reads per sample, the least accurate algorithm would miss detection of almost a third of trisomy cases. Furthermore, we describe and quantify a previously undocumented aneuploidy risk uncertainty that is mainly relevant in cases of very low sequencing coverage (at and below 1.25M reads per sample) and could, in the worst-case scenario, lead to a false negative rate of 245 undetected trisomies per 1,000 trisomy cases. Our findings underscore the importance of the informed selection of NIPT software tools in combination with sequencing coverage, which directly impacts NIPT sequencing cost and accuracy

Identification of fetal unmodified and 5-hydroxymethylated CG sites in maternal cell-free DNA for non-invasive prenatal testing

BackgroundMassively parallel sequencing of maternal cell-free DNA (cfDNA) is widely used to test fetal genetic abnormalities in non-invasive prenatal testing (NIPT). However, sequencing-based approaches are still of high cost. Building upon previous knowledge that placenta, the main source of fetal circulating DNA, is hypomethylated in comparison to maternal tissue counterparts of cfDNA, we propose that targeting either unmodified or 5-hydroxymethylated CG sites specifically enriches fetal genetic material and reduces numbers of required analytical sequencing reads thereby decreasing cost of a test.MethodsWe employed uTOPseq and hmTOP-seq approaches which combine covalent derivatization of unmodified or hydroxymethylated CG sites, respectively, with next generation sequencing, or quantitative real-time PCR.ResultsWe detected increased 5-hydroxymethylcytosine (5hmC) levels in fetal chorionic villi (CV) tissue samples as compared with peripheral blood. Using our previously developed uTOP-seq and hmTOP-seq approaches we obtained whole-genome uCG and 5hmCG maps of 10 CV tissue and 38 cfDNA samples in total. Our results indicated that, in contrast to conventional whole genome sequencing, such epigenomic analysis highly specifically enriches fetal DNA fragments from maternal cfDNA. While both our approaches yielded 100% accuracy in detecting Down syndrome in fetuses, hmTOP-seq maintained such accuracy at ultra-low sequencing depths using only one million reads. We identified 2164 and 1589 placenta-specific differentially modified and 5-hydroxymethylated regions, respectively, in chromosome 21, as well as 3490 and 2002 Down syndrome-specific differentially modified and 5-hydroxymethylated regions, respectively, that can be used as biomarkers for identification of Down syndrome or other epigenetic diseases of a fetus.ConclusionsuTOP-seq and hmTOP-seq approaches provide a cost-efficient and sensitive epigenetic analysis of fetal abnormalities in maternal cfDNA. The results demonstrated that T21 fetuses contain a perturbed epigenome and also indicated that fetal cfDNA might originate from fetal tissues other than placental chorionic villi. Robust covalent derivatization followed by targeted analysis of fetal DNA by sequencing or qPCR presents an attractive strategy that could help achieve superior sensitivity and specificity in prenatal diagnostics.Peer reviewe

Computational framework for targeted high-coverage sequencing based NIPT

Non-invasive prenatal testing (NIPT) enables accurate detection of fetal chromosomal trisomies. The majority of publicly available computational methods for sequencing-based NIPT analyses rely on low-coverage whole-genome sequencing (WGS) data and are not applicable for targeted high-coverage sequencing data from cell-free DNA samples. Here, we present a novel computational framework for a targeted high-coverage sequencing-based NIPT analysis. The developed framework uses a hidden Markov model (HMM) in conjunction with a supplemental machine learning model, such as decision tree (DT) or support vector machine (SVM), to detect fetal trisomy and parental origin of additional fetal chromosomes. These models were developed using simulated datasets covering a wide range of biologically relevant scenarios with various chromosomal quantities, parental origins of extra chromosomes, fetal DNA fractions, and sequencing read depths. Developed models were tested on simulated and experimental targeted sequencing datasets. Consequently, we determined the functional feasibility and limitations of each proposed approach and demonstrated that read count-based HMM achieved the best overall classification accuracy of 0.89 for detecting fetal euploidies and trisomies on simulated dataset. Furthermore, we show that by using the DT and SVM on the HMM classification results, it was possible to increase the final trisomy classification accuracy to 0.98 and 0.99, respectively. We demonstrate that read count and allelic ratio-based models can achieve a high accuracy (up to 0.98) for detecting fetal trisomy even if the fetal fraction is as low as 2%. Currently, existing commercial NIPT analysis requires at least 4% of fetal fraction, which can be possibly a challenge in case of early gestational age (35 kg/m2). More accurate detection can be achieved at higher sequencing depth using HMM in conjunction with supplemental models, which significantly improve the trisomy detection especially in borderline scenarios (e.g., very low fetal fraction) and enables to perform NIPT even earlier than 10 weeks of pregnancy.Peer reviewe

Endometrial receptivity revisited: endometrial transcriptome adjusted for tissue cellular heterogeneity

STUDY QUESTION Does cellular composition of the endometrial biopsy affect the gene expression profile of endometrial whole-tissue samples? SUMMARY ANSWER The differences in epithelial and stromal cell proportions in endometrial biopsies modify the whole-tissue gene expression profiles and affect the results of differential expression analyses. WHAT IS ALREADY KNOWN Each cell type has its unique gene expression profile. The proportions of epithelial and stromal cells vary in endometrial tissue during the menstrual cycle, along with individual and technical variation due to the method and tools used to obtain the tissue biopsy. STUDY DESIGN, SIZE, DURATION Using cell-population specific transcriptome data and computational deconvolution approach, we estimated the epithelial and stromal cell proportions in whole-tissue biopsies taken during early secretory and mid-secretory phases. The estimated cellular proportions were used as covariates in whole-tissue differential gene expression analysis. Endometrial transcriptomes before and after deconvolution were compared and analysed in biological context. PARTICIPANTS/MATERIAL, SETTING, METHODS Paired early- and mid-secretory endometrial biopsies were obtained from 35 healthy, regularly cycling, fertile volunteers, aged 23–36 years, and analysed by RNA sequencing. Differential gene expression analysis was performed using two approaches. In one of them, computational deconvolution was applied as an intermediate step to adjust for the proportions of epithelial and stromal cells in the endometrial biopsy. The results were then compared to conventional differential expression analysis. Ten paired endometrial samples were analysed with qPCR to validate the results. MAIN RESULTS AND THE ROLE OF CHANCE The estimated average proportions of stromal and epithelial cells in early secretory phase were 65% and 35%, and during mid-secretory phase, 46% and 54%, respectively, correlating well with the results of histological evaluation (r = 0.88, P = 1.1 × 10−6). Endometrial tissue transcriptomic analysis showed that approximately 26% of transcripts (n = 946) differentially expressed in receptive endometrium in cell-type unadjusted analysis also remain differentially expressed after adjustment for biopsy cellular composition. However, the other 74% (n = 2645) become statistically non-significant after adjustment for biopsy cellular composition, underlining the impact of tissue heterogeneity on differential expression analysis. The results suggest new mechanisms involved in endometrial maturation, involving genes like LINC01320, SLC8A1 and GGTA1P, described for the first time in context of endometrial receptivity. LARGE-SCALE DATA The RNA-seq data presented in this study is deposited in the Gene Expression Omnibus database with accession number GSE98386. LIMITATIONS REASONS FOR CAUTION Only dominant endometrial cell types were considered in gene expression profile deconvolution; however, other less frequent endometrial cell types also contribute to the whole-tissue gene expression profile. WIDER IMPLICATIONS OF THE FINDINGS The better understanding of molecular processes during transition from pre-receptive to receptive endometrium serves to improve the effectiveness and personalization of assisted reproduction protocols. Biopsy cellular composition should be taken into account in future endometrial ‘omics’ studies, where tissue heterogeneity could potentially influence the results. STUDY FUNDING/COMPETING INTEREST(S) This study was funded by: Estonian Ministry of Education and Research (grant IUT34-16); Enterprise Estonia (EU48695); the EU-FP7 Eurostars program (NOTED, EU41564); the EU-FP7 Marie Curie Industry-Academia Partnerships and Pathways (SARM, EU324509); Horizon 2020 innovation program (WIDENLIFE, EU692065); MSCA-RISE-2015 project MOMENDO (No 691058) and the Miguel Servet Program Type I of Instituto de Salud Carlos III (CP13/00038); Spanish Ministry of Economy, Industry and Competitiveness (MINECO) and European Regional Development Fund (FEDER): grants RYC-2016-21199 and ENDORE SAF2017-87526. Authors confirm no competing interests

Creating basis for introducing non‐invasive prenatal testing in the Estonian public health setting

Objective The study aimed to validate a whole‐genome sequencing‐based NIPT laboratory method and our recently developed NIPTmer aneuploidy detection software with the potential to integrate the pipeline into prenatal clinical care in Estonia. Method In total, 424 maternal blood samples were included. Analysis pipeline involved cell‐free DNA extraction, library preparation and massively parallel sequencing on Illumina platform. Aneuploidies were determined with NIPTmer software, which is based on counting pre‐defined per‐chromosome sets of unique k‐mers from sequencing raw data. SeqFF was implemented to estimate cell‐free fetal DNA (cffDNA) fraction. Results NIPTmer identified correctly all samples of non‐mosaic trisomy 21 (T21, 15/15), T18 (9/9), T13 (4/4) and monosomy X (4/4) cases, with the 100% sensitivity. However, one mosaic T18 remained undetected. Six false‐positive (FP) results were observed (FP rate of 1.5%, 6/398), including three for T18 (specificity 99.3%) and three for T13 (specificity 99.3%). The level of cffDNA of <4% was estimated in eight samples, including one sample with T13 and T18. Despite low cffDNA level, these two samples were determined as aneuploid. Conclusion We believe that the developed NIPT method can successfully be used as a universal primary screening test in combination with ultrasound scan for the first trimester fetal examination

Highly Parallel and Short-Acting Amplification with Locus-Specific Primers to Detect Single Nucleotide Polymorphisms by the DigiTag2 Assay

The DigiTag2 assay enables analysis of a set of 96 SNPs using Kapa 2GFast HotStart DNA polymerase with a new protocol that has a total running time of about 7 hours, which is 6 hours shorter than the previous protocol. Quality parameters (conversion rate, call rate, reproducibility and concordance) were at the same levels as when genotype calls were acquired using the previous protocol. Multiplex PCR with 192 pairs of locus-specific primers was available for target preparation in the DigiTag2 assay without the optimization of reaction conditions, and quality parameters had the same levels as those acquired with 96-plex PCR. The locus-specific primers were able to achieve sufficient (concentration of target amplicon ≥5 nM) and specific (concentration of unexpected amplicons <2 nM) amplification within 2 hours, were also able to achieve detectable amplifications even when working in a 96-plex or 192-plex form. The improved DigiTag2 assay will be an efficient platform for screening an intermediate number of SNPs (tens to hundreds of sites) in the replication analysis after genome-wide association study. Moreover, highly parallel and short-acting amplification with locus-specific primers may thus facilitate widespread application to other PCR-based assays

The human long non-coding RNA gene RMRP has pleiotropic effects and regulates cell-cycle progression at G2

RMRP was the first non-coding nuclear RNA gene implicated in a disease. Its mutations cause cartilage-hair hypoplasia (CHH), an autosomal recessive skeletal dysplasia with growth failure, immunodeficiency, and a high risk for malignancies. This study aimed to gain further insight into the role of RNA Component of Mitochondrial RNA Processing Endoribonuclease (RMRP) in cellular physiology and disease pathogenesis. We combined transcriptome analysis with single-cell analysis using fibroblasts from CHH patients and healthy controls. To directly assess cell cycle progression, we followed CHH fibroblasts by pulse-labeling and time-lapse microscopy. Transcriptome analysis identified 35 significantly upregulated and 130 downregulated genes in CHH fibroblasts. The downregulated genes were significantly connected to the cell cycle. Multiple other pathways, involving regulation of apoptosis, bone and cartilage formation, and lymphocyte function, were also affected, as well as PI3K-Akt signaling. Cell-cycle studies indicated that the CHH cells were delayed specifically in the passage from G2 phase to mitosis. Our findings expand the mechanistic understanding of CHH, indicate possible pathways for therapeutic intervention and add to the limited understanding of the functions of RMRP.Peer reviewe

Fibrinogen beta variants confer protection against coronary artery disease in a Greek case-control study

<p>Abstract</p> <p>Background</p> <p>Although plasma fibrinogen levels are related to cardiovascular risk, data regarding the role of fibrinogen genetic variation in myocardial infarction (MI) or coronary artery disease (CAD) etiology remain inconsistent. The purpose of the present study was to investigate the effect of <it>fibrinogen A (FGA)</it>, <it>fibrinogen B (FGB) </it>and <it>fibrinogen G (FGG) </it>gene SNPs and haplotypes on susceptibility to CAD in a homogeneous Greek population.</p> <p>Methods</p> <p>We genotyped for rs2070022, rs2070016, rs2070006 in <it>FGA </it>gene, the rs7673587, rs1800789, rs1800790, rs1800788, rs1800787, rs4681 and rs4220 in <it>FGB </it>gene and for the rs1118823, rs1800792 and rs2066865 SNPs in <it>FGG </it>gene applying an arrayed primer extension-based genotyping method (APEX-2) in a sample of CAD patients (n = 305) and controls (n = 305). Logistic regression analysis was used to calculate odds ratios (ORs) and 95% confidence intervals (CIs), before and after adjustment for potential confounders.</p> <p>Results</p> <p>None of the <it>FGA </it>and <it>FGG </it>SNPs and <it>FGA, FGB, FGG </it>and <it>FGA-FGG </it>haplotypes was associated with disease occurrence after adjustment. Nevertheless, rs1800787 and rs1800789 SNPs in <it>FGB </it>gene seem to decrease the risk of CAD, even after adjustment for potential confounders (OR = 0.42, 95%CI: 0.19-0.90, p = 0.026 and OR = 0.44, 95%CI:0.21-0.94, p = 0.039, respectively).</p> <p>Conclusions</p> <p><it>FGA </it>and <it>FGG </it>SNPs as well as <it>FGA, FGB, FGG </it>and <it>FGA-FGG </it>haplotypes do not seem to be important contributors to CAD occurrence in our sample. On the contrary, <it>FGB </it>rs1800787 and rs1800789 SNPs seem to confer protection to disease onset lowering the risk by about 50% in homozygotes for the minor alleles.</p