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Genotype imputation has become a standard procedure prior genome-wide association studies (GWASs). For common and low-frequency variants, genotype imputation can be performed sufficiently accurately with publicly available and ethnically heterogeneous reference datasets like 1000 Genomes Project (1000G) and Haplotype Reference Consortium panels. However, the imputation of rare variants has been shown to be significantly more accurate when ethnically matched reference panel is used. Even more, greater genetic similarity between reference panel and target samples facilitates the detection of rare (or even population-specific) causal variants. Notwithstanding, the genome-wide downstream consequences and differences of using ethnically mixed and matched reference panels have not been yet comprehensively explored.We determined and quantified these differences by performing several comparative evaluations of the discovery-driven analysis scenarios. A variant-wise GWAS was performed on seven complex diseases and body mass index by using genome-wide genotype data of ∼37,000 Estonians imputed with ethnically mixed 1000G and ethnically matched imputation reference panels. Although several previously reported common (minor allele frequency; MAF > 5%) variant associations were replicated in both resulting imputed datasets, no major differences were observed among the genome-wide significant findings or in the fine-mapping effort. In the analysis of rare (MAF < 1%) coding variants, 46 significantly associated genes were identified in the ethnically matched imputed data as compared to four genes in the 1000G panel based imputed data. All resulting genes were consequently studied in the UK Biobank data.These associations provide a solid example of how rare variants can be efficiently analysed to discover novel, potentially functional genetic variants in relevant phenotypes. Furthermore, our work serves as proof of a cost-efficient study design, demonstrating that the usage of ethnically matched imputation reference panels can enable substantially improved imputation of rare variants, facilitating novel high-confidence findings in rare variant GWAS scans.Author summaryOver the last decade, genome-wide association studies (GWASs) have been widely used for detecting genetic biomarkers in a wide range of traits. Typically, GWASs are carried out using chip-based genotyping data, which are then combined with a more densely genotyped reference panel to infer untyped genetic variants in chip-typed individuals. The latter method is called genotype imputation and its accuracy depends on multiple factors. Publicly available and ethnically heterogeneous imputation reference panels (IRPs) such as 1000 Genomes Project (1000G) are sufficiently accurate for imputation of common and low-frequency variants, but custom ethnically matched IRPs outperform these in case of rare variants. In this work, we systematically compare downstream association analysis effects on eight complex traits in ∼37,000 Estonians imputed with ethnically mixed and ethnically matched IRPs. We do not observe major differences in the single variant analysis, where both imputed datasets replicate previously reported significant loci. But in the gene-based analysis of rare protein-coding variants we show that ethnically matched panel clearly outperforms 1000G panel based imputation, providing 10-fold increase in significant gene-trait associations. Our study demonstrates empirically that imputed data based on ethnically matched panel is very promising for rare variant analysis – it captures more population-specific variants and makes it possible to efficiently identify novel findings.

Isolated populations with enrichment of variants due to recent population bottlenecks provide a powerful resource for identifying disease-associated genetic variants and genes. As a model of an isolate population, we sequenced the genomes of 1463 Finnish individuals as part of the Sequencing Initiative Suomi (SISu) Project. We compared the genomic profiles of the 1463 Finns to a sample of 1463 British individuals that were sequenced in parallel as part of the UK10K Project. Whereas there were no major differences in the allele frequency of common variants, a significant depletion of variants in the rare frequency spectrum was observed in Finns when comparing the two populations. On the other hand, we observed >2.1 million variants that were twice as frequent among Finns compared with Britons and 800 000 variants that were more than 10 times more frequent in Finns. Furthermore, in Finns we observed a relative proportional enrichment of variants in the minor allele frequency range between 2 and 5% (P

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.

ObjectiveThe study aimed to validate a whole-genome sequencing-based NIPT method and our newly developed NIPTmer analysis software with the potential to integrate the pipeline into prenatal clinical care in Estonia.MethodIn total, 447 maternal blood samples were included to the study. Analysis pipeline involved whole-genome library preparation and massively parallel sequencing on Illumina NextSeq 500. Aneuploidy status was determined with NIPTmer software, which is based on counting pre-defined per-chromosome sets of unique k-mers from raw sequencing data. To estimate fetal fraction (FF) from total cell-free DNA SeqFF was implemented.ResultsNIPTmer software allowed to identify correctly all samples of non-mosaic T21 (15/15), T18 (9/9) and T13 (4/4) cases. However, one mosaic T18 remained undetected. Six false positive results were observed, including three for T18 (specificity 99.3%) and three for T13 (specificity 99.3%). FF < 4% (2.8-3.99%) was estimated in eight samples, including two samples with T13 and T18. Despite low FF, these two samples were determined as aneuploid with NIPTmer software.ConclusionOur NIPT analysis pipeline proved to perform efficiently in detecting common fetal aneuploidies T21, T18 and T13 and is feasible for implementation into clinical service in Estonia.

Nordic Exome Variant Catalogue is a web tool to browse human genomic aggregation data from Nordic cohorts. This allows viewing, querying, comparison, filtering and sorting the data in graphical user interface. The main end users are researchers and clinicians studying genetic variance in genes of interest.

Background The biological mechanisms of headache chronification are poorly understood. We aimed to identify changes in DNA methylation associated with the transformation from episodic to chronic headache. Methods Participants were recruited from the population-based Norwegian HUNT Study. Thirty-six female headache patients who transformed from episodic to chronic headache between baseline and follow-up 11 years later were matched against 35 controls with episodic headache. DNA methylation was quantified at 485,000 CpG sites, and changes in methylation level at these sites were compared between cases and controls by linear regression analysis. Data were analyzed in two stages (Stages 1 and 2) and in a combined meta-analysis. Results None of the top 20 CpG sites identified in Stage 1 replicated in Stage 2 after multiple testing correction. In the combined meta-analysis the strongest associated CpG sites were related to SH2D5 and NPTX2, two brain-expressed genes involved in the regulation of synaptic plasticity. Functional enrichment analysis pointed to processes including calcium ion binding and estrogen receptor pathways. Conclusion In this first genome-wide study of DNA methylation in headache chronification several potentially implicated loci and processes were identified. The study exemplifies the use of prospectively collected population cohorts to search for epigenetic mechanisms of disease.

It has long been observed that complex traits, including migraine, often aggregate in families, but the underlying genetic architecture behind this is not well understood. Two competing hypotheses exist, emphasizing either rare or common genetic variation. More specifically, familial aggregation could be predominantly explained by rare, penetrant variants that segregate according to Mendelian inheritance or rather by the sufficient polygenic accumulation of many common variants, each with an individually small effect. Some combination of both common and rare variation could also contribute towards a spectrum of disease risk.We investigated this in a collection of 8,319 individuals across 1,589 migraine families from Finland. Family members were individually diagnosed by a migraine-specific questionnaire with either migraine without aura (MO, ICHD-3 code 1.1, n=2,357), migraine with typical aura (ICHD- 3 code 1.2.1, n=2,420), hemiplegic migraine (HM, ICHD-3 code 1.2.3, n=540), or no migraine (n=3,002). For comparison, we used population-based migraine cases (n=1,101) and controls (n=13,369) from the FINRISK study. The disease status of FINRISK individuals was assigned based on health registry data from outpatient clinics and/or prescription medication. All individuals were genotyped on the Illumina® CoreExome or PsychArray chip platforms and imputed to a Finnish reference panel of 6,962 haplotypes. Polygenic risk scores (PRS), representing the common variant burden in each individual, were calculated using weights from the most recent large-scale genome-wide association study of migraine. To account for family structure in our analyses, we used a mixed-model approach, adjusting for the genetic relationship matrix as a random effect.We found a significantly higher common variant burden in familial cases of migraine (for all subtypes, measured by the odds ratio [OR] per standard deviation [SD] increase in PRS; OR = 1.76, 95% CI = 1.71-1.81, P = 1.7×10−109) compared to cases from a population cohort (OR = 1.32, 95% CI = 1.25-1.38, P = 7.2×10−17) when using the population controls as a reference group. The highest enrichment was observed for HM (OR = 1.96, 95% CI = 1.86-2.07, P = 8.7×10−36) and migraine with typical aura (OR = 1.85, 95% CI = 1.79-1.91, P = 1.4×10−86) but enrichment was also present for MO (OR = 1.57, 95% CI = 1.51-1.63, P = 1.1×10−48). Comparing within cases, there was no significant difference in common variant burden between the migraine with aura subtypes, HM and migraine with typical aura (OR = 1.09, 95% CI = 0.99-1.19, P = 0.09), but both showed significantly higher enrichment compared to MO (OR = 1.28, 95% CI = 1.17-1.38, P = 7.3×10−7, and OR = 1.17, 95% CI = 1.11-1.23, P = 4.62×10−5, respectively). Additionally, we found that higher common variant burden corresponded to earlier age of headache onset (OR per SD increase in PRS for 3,631 cases with onset before 20 years old compared to 1,686 cases with onset later than 20 years old; OR = 1.11, 95% CI = 1.05-1.18, P = 8.3×10−4). FINRISK population cases identified from national health registry data were found to have lower common variant burden in comparison to the familial migraine cases (OR = 1.32, 95% CI = 1.25-1.38, P = 6.8×10−17), unless the individuals had attended both a specialist clinic and also received prophylactic migraine treatment (OR = 1.70, 95% CI = 1.53-1.88, P = 3.9×10−9). Finally, although rare variants have been suggested as the primary cause for familial hemiplegic migraine (FHM), we found only four out of 45 sequenced FHM families (8.9%) with a pathogenic mutation in one of the known risk genes.In summary, our results demonstrate a substantial contribution of common polygenic variation to familial aggregation in migraine, comparable to both controls and that observed in migraine cases from a population cohort. The findings also suggest that individuals with migraine aura symptoms (either typical aura, which is mostly visual, or rare motor aura) tend to have higher common variant burden on average supporting the polygenic model also in these migraine subtypes.

Recurrent miscarriage (RM) is a multifactorial disorder with acknowledged genetic heritability that affects ∼3% of couples aiming at childbirth. As copy number variants (CNVs) have been shown to contribute to reproductive disease susceptibility, we aimed to describe genome-wide profile of CNVs and identify common rearrangements modulating risk to RM. Genome-wide screening of Estonian RM patients and fertile controls identified excessive cumulative burden of CNVs (5.4 and 6.1 Mb per genome) in two RM cases possibly increasing their individual disease risk. Functional profiling of all rearranged genes within RM study group revealed significant enrichment of loci related to innate immunity and immunoregulatory pathways essential for immune tolerance at fetomaternal interface. As a major finding, we report a multicopy duplication (61.6 kb) at 5p13.3 conferring increased maternal risk to RM in Estonia and Denmark (meta-analysis, n = 309/205, odds ratio = 4.82, P = 0.012). Comparison to Estonian population-based cohort (total, n = 1000) confirmed the risk for Estonian female cases (P = 7.9 × 10(-4) ). Datasets of four cohorts from the Database of Genomic Variants (total, n = 5,846 subjects) exhibited similar low duplication prevalence worldwide (0.7%-1.2%) compared to RM cases of this study (6.6%-7.5%). The CNV disrupts PDZD2 and GOLPH3 genes predominantly expressed in placenta and it may represent a novel risk factor for pregnancy complications.

Transcriptome profiling of 57 endometrial receptivity genes specifies the menstrual cycle phase of endometrial samples.

Hyperlipidemia, particularly high LDL-C or TG, is the most important heritable risk factor for coronary artery disease (CAD). Its most severe form, monogenic familial hypercholesterolemia (FH) increases CAD risk more than expected from a single LDL-C measurement, likely due to lifelong cumulative

Inherited alleles account for most of the genetic risk for schizophrenia. However, new (de novo) mutations, in the form of large chromosomal copy number changes, occur in a small fraction of cases and disproportionally disrupt genes encoding postsynaptic proteins. Here we show that small de novo mutations, affecting one or a few nucleotides, are overrepresented among glutamatergic postsynaptic proteins comprising activity-regulated cytoskeleton-associated protein (ARC) and N-methyl-d-aspartate receptor (NMDAR) complexes. Mutations are additionally enriched in proteins that interact with these complexes to modulate synaptic strength, namely proteins regulating actin filament dynamics and those whose messenger RNAs are targets of fragile X mental retardation protein (FMRP). Genes affected by mutations in schizophrenia overlap those mutated in autism and intellectual disability, as do mutation-enriched synaptic pathways. Aligning our findings with a parallel case-control study, we demonstrate reproducible insights into aetiological mechanisms for schizophrenia and reveal pathophysiology shared with other neurodevelopmental disorders.

DNA methylation is an important mechanism by which gene transcription and hence cellular function are regulated. Here, we provide detailed functional genome-wide methylome maps of 5 primary peripheral blood leukocyte subsets including T cells, B cells, monocytes/macrophages, and neutrophils obtained from healthy individuals. A comparison of these methylomes revealed highly specific cell-lineage and cell-subset methylation profiles. DNA hypomethylation is known to be permissive for gene expression and we identified cell-subset-specific hypomethylated regions (HMRs) that strongly correlate with gene transcription levels suggesting these HMRs may regulate corresponding cell functions. Single-nucleotide polymorphisms associated with immune-mediated disease in genome-wide association studies preferentially localized to these cell-specific regulatory HMRs, offering insight into pathogenesis by highlighting cell subsets in which specific epigenetic changes may drive disease. Our data provide a valuable reference tool for researchers aiming to investigate the role of DNA methylation in regulating primary leukocyte function in health and immune-mediated disease.

Genetic variants affecting hematopoiesis can influence commonly measured blood cell traits. To identify factors that affect hematopoiesis, we performed association studies for blood cell traits in the population-based Estonian Biobank using high coverage whole genome sequencing (WGS) in 2,284 samples and SNP genotyping in an additional ~17,000 samples. Our analyses identified 17 associations across 14 blood cell traits. Integration of WGS-based fine-mapping and complementary epigenomic data sets provided evidence for causal mechanisms at several loci, including at a novel basophil count-associated locus near the master hematopoietic transcription factor CEBPA. The fine-mapped variant at this basophil count association near CEBPA overlapped an enhancer active in common myeloid progenitors and influenced its activity. In situ perturbation of this enhancer by CRISPR/Cas9 mutagenesis in hematopoietic stem and progenitor cells demonstrated that it is necessary for and specifically regulates CEBPA expression during basophil differentiation. We additionally identified basophil count-associated variation at another more pleiotropic myeloid enhancer near GATA2, highlighting regulatory mechanisms for ordered expression of master hematopoietic regulators during lineage specification. Our study illustrates how population-based genetic studies can provide key insights into poorly understood cell differentiation processes of considerable physiologic relevance.

Genetic imputation is a cost-efficient way to improve the power and resolution of genome-wide association (GWA) studies. Current publicly accessible imputation reference panels accurately predict genotypes for common variants with minor allele frequency (MAF)≥5% and low-frequency variants (0.5≤MAF

Isolated populations with enrichment of variants due to recent population bottlenecks provide a powerful resource for identifying disease-associated genetic variants and genes. As a model of an isolate population, we sequenced the genomes of 1463 Finnish individuals as part of the Sequencing Initiative Suomi (SISu) Project. We compared the genomic profiles of the 1463 Finns to a sample of 1463 British individuals that were sequenced in parallel as part of the UK10K Project. Whereas there were no major differences in the allele frequency of common variants, a significant depletion of variants in the rare frequency spectrum was observed in Finns when comparing the two populations. On the other hand, we observed >2.1 million variants that were twice as frequent among Finns compared to Britons and 800,000 variants that were more than 10 times more frequent in Finns. Furthermore, in Finns we observed a relative proportional enrichment of variants in the minor allele frequency range between 2 - 5% (p < 2.2×10−16). When stratified by their functional annotations, loss-of-function (LoF) variants showed the highest proportional enrichment in Finns (p = 0.0291). In the noncoding part of the genome, variants in conserved regions (p = 0.002) and promoters (p = 0.01) were also significantly enriched in the Finnish samples. These functional categories represent the highest a priori power for downstream association studies of rare variants using population isolates.

Sequencing the coding regions, the exome, of the human genome is one of the major current strategies to identify low frequency and rare variants associated with human disease traits. So far, the most widely used commercial exome capture reagents have mainly targeted the consensus coding sequence (CCDS) database. We report the design of an extended set of targets for capturing the complete human exome, based on annotation from the GENCODE consortium. The extended set covers an additional 5594 genes and 10.3 Mb compared with the current CCDS-based sets. The additional regions include potential disease genes previously inaccessible to exome resequencing studies, such as 43 genes linked to ion channel activity and 70 genes linked to protein kinase activity. In total, the new GENCODE exome set developed here covers 47.9 Mb and performed well in sequence capture experiments. In the sample set used in this study, we identified over 5000 SNP variants more in the GENCODE exome target (24%) than in the CCDS-based exome sequencing.

Migraine is a debilitating neurological disorder affecting around 1 in 7 people worldwide, but its molecular mechanisms remain poorly understood. Some debate exists over whether migraine is a disease of vascular dysfunction, or a result of neuronal dysfunction with secondary vascular changes. Genome-wide association (GWA) studies have thus far identified 13 independent loci associated with migraine. To identify new susceptibility loci, we performed the largest genetic study of migraine to date, comprising 59,674 cases and 316,078 controls from 22 GWA studies. We identified 45 independent single nucleotide polymorphisms (SNPs) significantly associated with migraine risk (P < 5 x 10-8) that map to 38 distinct genomic loci, including 28 loci not previously reported and the first locus identified on chromosome X. Furthermore, a subset analysis for migraine without aura (MO) identified seven of the same loci as from the full sample, whereas no loci reached genome-wide significance in the migraine with aura (MA) subset. In subsequent computational analyzes, the identified loci showed enrichment for genes expressed in vascular and smooth muscle tissues, consistent with a predominant theory of migraine that highlights vascular etiologies.

Exome sequencing studies in complex diseases are challenged by the allelic heterogeneity, large number and modest effect sizes of associated variants on disease risk and the presence of large numbers of neutral variants, even in phenotypically relevant genes. Isolated populations with recent bottlenecks offer advantages for studying rare variants in complex diseases as they have deleterious variants that are present at higher frequencies as well as a substantial reduction in rare neutral variation. To explore the potential of the Finnish founder population for studying low-frequency (0.5–5%) variants in complex diseases, we compared exome sequence data on 3,000 Finns to the same number of non-Finnish Europeans and discovered that, despite having fewer variable sites overall, the average Finn has more low-frequency loss-of-function variants and complete gene knockouts. We then used several well-characterized Finnish population cohorts to study the phenotypic effects of 83 enriched loss-of-function variants across 60 phenotypes in 36,262 Finns. Using a deep set of quantitative traits collected on these cohorts, we show 5 associations (p, National Institutes of Health (U.S.) (NIH RC2 HL-102925)

Migraine is the most common brain disorder, affecting approximately 14% of the adult population, but its molecular mechanisms are poorly understood. We report the results of a meta-analysis across 29 genome-wide association studies, including a total of 23,285 individuals with migraine (cases) and 95,425 population-matched controls. We identified 12 loci associated with migraine susceptibility (P

Migraine is a debilitating neurological disorder affecting around 1 in 7 people worldwide, but its molecular mechanisms remain poorly understood. Some debate exists over whether migraine is a disease of vascular dysfunction or a result of neuronal dysfunction with secondary vascular changes. Genome-wide association (GWA) studies have thus far identified 13 independent loci associated with migraine. To identify new susceptibility loci, we performed the largest genetic study of migraine to date, comprising 59,674 cases and 316,078 controls from 22 GWA studies. We identified 44 independent single nucleotide polymorphisms (SNPs) significantly associated with migraine risk (P < 5 × 10−8) that map to 38 distinct genomic loci, including 28 loci not previously reported and the first locus identified on chromosome X. In subsequent computational analyses, the identified loci showed enrichment for genes expressed in vascular and smooth muscle tissues, consistent with a predominant theory of migraine that highlights vascular etiologies.

background: De novo somatic copy number aberrations (SCNAs) in eutopic and ectopic endometria are thought to be involved in the pathogenesis of endometriosis. In this study we used, for the first time, high-density single nucleotide polymorphism-array technology for accurate detection of SCNAs, inherited DNA copy number variations (CNVs) and copy-neutral loss of heterozygosity (cn-LOH) patterns in patients with endometriosis. methods: The Illumina HumanOmniExpress array was used to detect de novo somatic genomic alterations in eutopic and ectopic endometria from 11 women (eight with Stage I – II endometriosis and three with Stage III –IV endometriosis) by comparatively analysing DNA from peripheral blood, eutopic endometrium and a pure population of endometriotic cells harvested from endometriotic lesions by laser capture microdissection (LCM). The frequency of the CNV in 3p14.1 from blood DNA of 187 endometriosis patients (94 with Stage I –II endometriosis and 93 with Stage III –IV endometriosis) and 171 healthy women from the Estonian general population was evaluated. results: Analysis of array data showed that LCM DNA can be used successfully for detection of genetic changes as all inherited CNVs were identified in all tissues studied. No unique SCNAs or cases of cn-LOH were found in either eutopic or ectopic endometrium when compared with blood DNA. The frequency of the deletion allele in 3p14.1 did not differ between studied groups. conclusions: In the present study no endometriosis-specific SCNAs or regions of cn-LOH in eutopic or ectopic endometrium were found. Nevertheless, as we studied only 17 endometriotic tissues derived from 11 patients we cannot entirely exclude the occurrence of rare SCNAs. Based on our results we suggest that molecular mechanisms other than chromosomal rearrangements most likely underlie the onset and progression of endometriosis.

Background We present a comprehensive technological solution for bacterial diagnostics using tmRNA as a marker molecule. A robust probe design algorithm for microbial detection microarray is implemented. The probes were evaluated for specificity and, combined with NASBA (Nucleic Acid Sequence Based Amplification) amplification, for sensitivity. Results We developed a new web-based program SLICSel for the design of hybridization probes, based on nearest-neighbor thermodynamic modeling. A SLICSel minimum binding energy difference criterion of 4 kcal/mol was sufficient to design of Streptococcus pneumoniae tmRNA specific microarray probes. With lower binding energy difference criteria, additional hybridization specificity tests on the microarray were needed to eliminate non-specific probes. Using SLICSel designed microarray probes and NASBA we were able to detect S. pneumoniae tmRNA from a series of total RNA dilutions equivalent to the RNA content of 0.1-10 CFU. Conclusions The described technological solution and both its separate components SLICSel and NASBA-microarray technology independently are applicative for many different areas of microbial diagnostics.

Obesity has become a major worldwide challenge to public health, owing to an interaction between the Western 'obesogenic' environment and a strong genetic contribution. Recent extensive genome-wide association studies (GWASs) have identified numerous single nucleotide polymorphisms associated with obesity, but these loci together account for only a small fraction of the known heritable component. Thus, the 'common disease, common variant' hypothesis is increasingly coming under challenge. Here we report a highly penetrant form of obesity, initially observed in 31 subjects who were heterozygous for deletions of at least 593 kilobases at 16p11.2 and whose ascertainment included cognitive deficits. Nineteen similar deletions were identified from GWAS data in 16,053 individuals from eight European cohorts. These deletions were absent from healthy non-obese controls and accounted for 0.7% of our morbid obesity cases (body mass index (BMI) >or= 40 kg m(-2) or BMI standard deviation score >or= 4; P = 6.4 x 10(-8), odds ratio 43.0), demonstrating the potential importance in common disease of rare variants with strong effects. This highlights a promising strategy for identifying missing heritability in obesity and other complex traits: cohorts with extreme phenotypes are likely to be enriched for rare variants, thereby improving power for their discovery. Subsequent analysis of the loci so identified may well reveal additional rare variants that further contribute to the missing heritability, as recently reported for SIM1 (ref. 3). The most productive approach may therefore be to combine the 'power of the extreme' in small, well-phenotyped cohorts, with targeted follow-up in case-control and population cohorts.

We compared six DNA extraction methods for obtaining DNA from whole blood and saliva for use in multiplex polymerase chain reaction (PCR) assays. The aim was to evaluate saliva sampling as an alternative to blood sampling to obtain DNA for molecular diagnostics, genetic genealogy, and research purposes. The DNA quantity, DNA purity (A(260/280)), PCR inhibition ratio, and mitochondrial DNA/genomic DNA ratio were measured to compare the extraction methods. The different extraction methods resulted in variable DNA quantity and purity, but there were no significant differences in the efficiency of multiplex PCR and oligomicroarray signals after single-base extension on the arrayed primer extension 2 (APEX-2).

Background Here we present a novel promising microbial diagnostic method that combines the sensitivity of Nucleic Acid Sequence Based Amplification (NASBA) with the high information content of microarray technology for the detection of bacterial tmRNA molecules. The NASBA protocol was modified to include aminoallyl-UTP (aaUTP) molecules that were incorporated into nascent RNA during the NASBA reaction. Post-amplification labeling with fluorescent dye was carried out subsequently and tmRNA hybridization signal intensities were measured using microarray technology. Significant optimization of the labeled NASBA protocol was required to maintain the required sensitivity of the reactions. Results Two different aaUTP salts were evaluated and optimum final concentrations were identified for both. The final 2 mM concentration of aaUTP Li-salt in NASBA reaction resulted in highest microarray signals overall, being twice as high as the strongest signals with 1 mM aaUTP Na-salt. Conclusion We have successfully demonstrated efficient combination of NASBA amplification technology with microarray based hybridization detection. The method is applicative for many different areas of microbial diagnostics including environmental monitoring, bio threat detection, industrial process monitoring and clinical microbiology.

Human identification systems such as criminal databases, forensic DNA testing and genetic genealogy require reliable and cost-effective genotyping of autosomal, mitochondrial and Y chromosome markers from different biological materials, including venous blood and saliva. Although many such assays are available, few systems are capable of simultaneously detecting all three targets in a single reaction. Employing the APEX-2 principle, we have characterized a novel 124-plex assay, using specific primer extension, universal primer amplification and single base extension on an oligonucleotide array. The assay has been designed for simultaneous genotyping of SNPs from the single copy loci (46 autosomal and 29 Y chromosomal markers) side by side with SNPs from the mitochondrial genome (49 markers) that appears in up to thousands of copies per cell in certain tissue types. All the autosomal SNPs (from the SNPforID Consortium) included in the multiplex assay are unlinked and are distributed widely across autosomes, enabling genetic fingerprints to be distinguished. Mitochondrial DNA and Y chromosome polymorphisms that define haplogroups common in European populations are included to allow for maternity and paternity testing and for the analysis of genetic genealogies. After assay optimization we estimated the accuracy (99.83%) and call rate (99.66%) of the protocol on 17 mother–father–child/ children families and five internal control DNAs. In addition, 79 unrelated Estonian and Swedish DNA samples were genotyped and the accuracy of mtDNA and Y chromosome haplogroup inference by the multiplex method was assessed using conventional genotyping methods and direct sequencing.

High-throughput genome-wide screening methods to detect subtle genomic imbalances are extremely important for diagnostic genetics and genomics. Here, we provide a detailed protocol for a microarray-based technique, applying the principle of multiplex amplifiable probe hybridization (MAPH). Methodology and software have been developed for designing unique PCR-amplifiable sequences (400-600 bp) covering any genomic region of interest. These sequences are amplified, cloned and spotted onto arrays (targets). A mixture of the same sequences (probes) is hybridized to genomic DNA immobilized on a membrane. Bound probes are recovered and quantitatively amplified by PCR, labeled and hybridized to the array. The procedure can be completed in 4-5 working days, excluding microarray preparation. Unlike array-comparative genomic hybridization (array-CGH), test DNA of specifically reduced complexity is hybridized to an array of identical small amplifiable target sequences, resulting in increased hybridization specificity and higher potential for increasing resolution. Array-MAPH can be used for detection of small-scale copy-number changes in complex genomes, leading to genotype-phenotype correlations and the discovery of new genes.

Contains fulltext : 53054.pdf (Publisher’s version ) (Closed access) The rapid advancement of high-resolution DNA copy number assessment methods revealed the significant contribution of submicroscopic genetic imbalances to abnormal phenotypes, including mental retardation. In order to detect submicroscopic genetic imbalances, we have screened 20 families with X-linked mental retardation (XLMR) using a chromosome X-specific array-MAPH platform with median resolution of 238kb. Among the 20 families, 18 were experimental, as they were not previously screened with any microarray method, and two were blind controls with known aberrations, as they were previously screened by array-CGH. This study presents the first clinical application of chromosome X-specific array-MAPH methodology. The screening of 20 affected males from 20 unrelated XLMR families resulted in the detection of an unknown deletion, spanning a region of 7-23kb. Family studies and population screening demonstrated that the detected deletion is an unknown rare copy number variant. One of the control samples, carrying approximately 6-Mb duplication was correctly identified, moreover it was found to be interrupted by a previously unknown 19kb region of normal copy number. The second control 50kb deletion was not identified, as this particular region was not covered by array-MAPH probes. This study demonstrates that the chromosome X-specific array-MAPH platform is a valuable tool for screening patients with XLMR, or other X-linked disorders, and emerges the need for introducing new high-resolution screening methods for the detection of genetic imbalances.

Array-based genome-wide screening methods were recently introduced to clinical practice in order to detect small genomic imbalances that may cause severe genetic disorders. The continuous advancement of such methods plays an extremely important role in diagnostic genetics and medical genomics. We have modified and adapted the original multiplex amplifiable probe hybridization (MAPH) to a novel microarray format providing an important new diagnostic tool for detection of small size copy-number changes in any locus of human genome. Here, we describe the new array-MAPH diagnostic method and show proof of concept through fabrication, interrogation and validation of a human chromosome X-specific array. We have developed new bioinformatic tools and methodology for designing and producing amplifiable hybridization probes (200–600 bp) for array-MAPH. We designed 558 chromosome X-specific probes with median spacing 238 kb and 107 autosomal probes, which were spotted onto microarrays. DNA samples from normal individuals and patients with known and unknown chromosome X aberrations were analyzed for validation. Array-MAPH detected exactly the same deletions and duplications in blind studies, as well as other unknown small size deletions showing its accuracy and sensitivity. All results were confirmed by fluorescence in situ hybridization and probe-specific PCR. Array-MAPH is a new microarray-based diagnostic tool for the detection of small-scale copy-number changes in complex genomes, which may be useful for genotype–phenotype correlations, identification of new genes, studying genetic variation and provision of genetic services.

Targeted next-generation sequencing (NGS) methods have become essential in medical research and diagnostics. In addition to NGS sensitivity and high-throughput capacity, precise biomolecule counting based on unique molecular identifier (UMI) has potential to increase biomolecule detection accuracy. Although UMIs are widely used in basic research its introduction to clinical assays is still in progress. Here, we present a robust and cost-effective TAC-seq (Targeted Allele Counting by sequencing) method that uses UMIs to estimate the original molecule counts of mRNAs, microRNAs, and cell-free DNA. We applied TAC-seq in three different clinical applications and compared the results with standard NGS. RNA samples extracted from human endometrial biopsies were analyzed using previously described 57 mRNA-based receptivity biomarkers and 49 selected microRNAs at different expression levels. Cell-free DNA aneuploidy testing was based on cell line (47,XX, +21) genomic DNA. TAC-seq mRNA profiling showed identical clustering results to transcriptome RNA sequencing, and microRNA detection demonstrated significant reduction in amplification bias, allowing to determine minor expression changes between different samples that remained undetermined by standard NGS. The mimicking experiment for cell-free DNA fetal aneuploidy analysis showed that TAC-seq can be applied to count highly fragmented DNA, detecting significant (p = 7.6 × 10−4) excess of chromosome 21 molecules at 10% fetal fraction level. Based on three proof-of-principle applications we demonstrate that TAC-seq is an accurate and highly potential biomarker profiling method for advanced medical research and diagnostics., Biomarkers: Sequencing technique offers accurate RNA or DNA count A new method for counting individual RNA or DNA molecules could help with biomarker analyses across a range of robust clinical applications. A team led by Kaarel Krjutškov from the Competence Center on Health Technologies in Tartu, Estonia, developed a system called TAC-seq (Targeted Allele Counting by sequencing) that tags RNA transcripts or DNA molecules with strings of random nucleotides, called unique molecular identifiers, to accurately quantify their numbers despite biases introduced by amplification ahead of sequencing. As a proof of principle, the researchers tested the ability of TAC-seq to detect biomarkers important for reproductive medicine. In endometrial biopsies, TAC-seq offered an accurate profile on levels of messenger RNAs and microRNAs linked to a woman’s chance of reproductive success. Proof of principle Down syndrome trisomy detection was carry out using simulated cell-free DNA testing, mimicking non-invasive prenatal genetic testing (NIPT).

Background The hybridization of synthetic Streptococcus pneumoniae tmRNA on a detection microarray is slow at 34°C resulting in low signal intensities. Results We demonstrate that adding specific DNA helper oligonucleotides (chaperones) to the hybridization buffer increases the signal strength at a given temperature and thus makes the specific detection of Streptococcus pneumoniae tmRNA more sensitive. No loss of specificity was observed at low temperatures compared to hybridization at 46°C. The effect of the chaperones can be explained by disruption of the strong secondary and tertiary structure of the target RNA by the selective hybridization of helper molecules. The amplification of the hybridization signal strength by chaperones is not necessarily local; we observed increased signal intensities in both local and distant regions of the target molecule. Conclusions The sensitivity of the detection of tmRNA at low temperature can be increased by chaperone oligonucleotides. Due to the complexity of RNA secondary and tertiary structures the effect of any individual chaperone is currently not predictable.

Käesoleva töö eesmärk oli leida ja kalibreerida arvutuslik metoodika loote rakuvaba DNA fraktsiooni määramiseks raseda naise vereproovis. Tegemist on rakendusliku teadusuuringuga, mis on eeltingimuseks NIPT testi usaldusväärseks rakendamiseks tervishoiusüsteemis. NIPT on kõige täpsem ja kaasaegsem mitteinvasiivne loote sünnieelne kromosoomihaiguste sõeluuring, mis põhineb madala katvusega täisgenoomi sekveneerimisandmete analüüsil. Metoodika võimaldab määrata loote rakuvaba DNA hulka raseda naise vereproovis nii poiss- kui ka tüdruklootele, mis on vajalik, et iga raseduse rakuvaba DNA analüüsi tulemus oleks usaldusväärne ja arstile ning patsiendile edastatud tulemus tõene. Käesolevas töös kasutati madala katvusega üle-genoomsetest Illumina platvormiga läbiviidud sekveneerimise katsetest saadud 416 Eesti päritolu naise NIPT proove, et välja töötada Y-kromosoomi põhine loote rakuvaba DNA hulga määramine poiss-loodetele. Välja töötatud Y-kromosoomi põhist meetodit kasutati SeqFF arvutusliku metoodika valideerimiseks Eesti NIPT proovidel. SeqFF rakendamine Eesti NIPT proovidel võimaldab määrata loote rakuvaba DNA hulka nii poiss- kui ka tüdrukloodetel. Väljatöötatud algoritm on integreeritud Eestis pakutavasse NIPT täppismeditsiini teenusesse NIPTIFY., The aim of this thesis was to find and 'calibrate' computational methodology for estimating the proportion of cell-free fetal DNA (cffDNA) in pregnant women’s blood sample. This work was done as part of an applied research project aimed to develop a whole genome sequencing (WGS) based non-invasive prenatal testing (NIPT) medical screening test. NIPT is the most up-to-date, accurate and easily applied (non-invasive) prenatal screening method to detect fetal aneuploidies (for example trisomy 21, that causes Down syndrome) with high confidence and already during the first trimester of pregnancy. Commonly, NIPT is based on the low coverage WGS data, generated by the means of Illumina or some another platform technology. Computational tools used for aneuploidy detection can also estimate the proportion of cffDNA in maternal blood for both male and female fetus pregnancies. Fetal fraction calculation is a prerequisite to assure the technical credibility of NIPT screening test. In the current study, low coverage cell-free whole genome sequencing data from 416 pregnant women were used to develop a chromosome Y based estimator for the proportion of cffDNA in male-fetus pregnancy cases. Next, the chromosome Y based estimator was used to validate the credibility of SeqFF computational method with Estonian NIPT samples. This developed approach using SeqFF method on Estonian NIPT samples enables to estimate the proportion of cffDNA in both male and female fetus pregnancies. The SeqFF method is now integrated into the NIPT computation workflow service, validated and in daily practical use as part of the NIPTIFY® screening test.