Severe congenital lactic acidosis and hypertrophic cardiomyopathy caused by an intronic variant in NDUFB7.

Mutations in structural subunits and assembly factors of complex I of the oxidative phosphorylation system constitute the most common cause of mitochondrial respiratory chain defects. Such mutations can present a wide range of clinical manifestations, varying from mild deficiencies to severe, lethal disorders. We describe a patient presenting intrauterine growth restriction and anemia, which displayed postpartum hypertrophic cardiomyopathy, lactic acidosis, encephalopathy, and a severe complex I defect with fatal outcome. Whole genome sequencing revealed an intronic biallelic mutation in the NDUFB7 gene (c.113-10C>G) and splicing pattern alterations in NDUFB7 messenger RNA were confirmed by RNA Sequencing. The detected variant resulted in a significant reduction of the NDUFB7 protein and reduced complex I activity. Complementation studies with expression of wild-type NDUFB7 in patient fibroblasts normalized complex I function. Here we report a case with a primary complex I defect due to a homozygous mutation in an intron region of the NDUFB7 gene.

Automation of Spatial Transcriptomics library preparation to enable rapid and robust insights into spatial organization of tissues.

BACKGROUND: Interest in studying the spatial distribution of gene expression in tissues is rapidly increasing. Spatial Transcriptomics is a novel sequencing-based technology that generates high-throughput information on the distribution, heterogeneity and co-expression of cells in tissues. Unfortunately, manual preparation of high-quality sequencing libraries is time-consuming and subject to technical variability due to human error during manual pipetting, which results in sample swapping and the accidental introduction of batch effects. All these factors complicate the production and interpretation of biological datasets. RESULTS: We have integrated an Agilent Bravo Automated Liquid Handling Platform into the Spatial Transcriptomics workflow. Compared to the previously reported Magnatrix 8000+ automated protocol, this approach increases the number of samples processed per run, reduces sample preparation time by 35%, and minimizes batch effects between samples. The new approach is also shown to be highly accurate and almost completely free from technical variability between prepared samples. CONCLUSIONS: The new automated Spatial Transcriptomics protocol using the Agilent Bravo Automated Liquid Handling Platform rapidly generates high-quality Spatial Transcriptomics libraries. Given the wide use of the Agilent Bravo Automated Liquid Handling Platform in research laboratories and facilities, this will allow many researchers to quickly create robust Spatial Transcriptomics libraries.

Comprehensive RNA sequencing of healthy human endometrium at two time points of the menstrual cycle.

Endometrial receptivity is crucial for implantation and establishment of a normal pregnancy. The shift from proliferative to receptive endometrium is still far from being understood. In this paper, we comprehensively present the transcriptome of the human endometrium by comparing endometrial biopsies from proliferative phase with consecutive biopsies 7-9 days after ovulation. The results show a clear difference in expression between the two time points using both total and small RNA sequencing. A total of 3,297 messenger RNAs (mRNAs), 516 long noncoding RNAs (lncRNAs), and 102 small noncoding RNAs were identified as statistically differentially expressed between the two time points. We show a thorough description of the change in mRNA between the two time points and display lncRNAs, small nucleolar RNAs, and small nuclear RNAs not previously reported in the healthy human endometrium. In conclusion, this paper reports in detail the shift in RNA expression from the proliferative to receptive endometrium.

Nanopore arrays in a silicon membrane for parallel single-molecule detection: DNA translocation.

Optical nanopore sensing offers great potential in single-molecule detection, genotyping, or DNA sequencing for high-throughput applications. However, one of the bottle-necks for fluorophore-based biomolecule sensing is the lack of an optically optimized membrane with a large array of nanopores, which has large pore-to-pore distance, small variation in pore size and low background photoluminescence (PL). Here, we demonstrate parallel detection of single-fluorophore-labeled DNA strands (450 bps) translocating through an array of silicon nanopores that fulfills the above-mentioned requirements for optical sensing. The nanopore array was fabricated using electron beam lithography and anisotropic etching followed by electrochemical etching resulting in pore diameters down to ∼7 nm. The DNA translocation measurements were performed in a conventional wide-field microscope tailored for effective background PL control. The individual nanopore diameter was found to have a substantial effect on the translocation velocity, where smaller openings slow the translocation enough for the event to be clearly detectable in the fluorescence. Our results demonstrate that a uniform silicon nanopore array combined with wide-field optical detection is a promising alternative with which to realize massively-parallel single-molecule detection.

Integration of whole genome sequencing into a healthcare setting: high diagnostic rates across multiple clinical entities in 3219 rare disease patients.

BACKGROUND: We report the findings from 4437 individuals (3219 patients and 1218 relatives) who have been analyzed by whole genome sequencing (WGS) at the Genomic Medicine Center Karolinska-Rare Diseases (GMCK-RD) since mid-2015. GMCK-RD represents a long-term collaborative initiative between Karolinska University Hospital and Science for Life Laboratory to establish advanced, genomics-based diagnostics in the Stockholm healthcare setting. METHODS: Our analysis covers detection and interpretation of SNVs, INDELs, uniparental disomy, CNVs, balanced structural variants, and short tandem repeat expansions. Visualization of results for clinical interpretation is carried out in Scout-a custom-developed decision support system. Results from both singleton (84%) and trio/family (16%) analyses are reported. Variant interpretation is done by 15 expert teams at the hospital involving staff from three clinics. For patients with complex phenotypes, data is shared between the teams. RESULTS: Overall, 40% of the patients received a molecular diagnosis ranging from 19 to 54% for specific disease groups. There was heterogeneity regarding causative genes (n = 754) with some of the most common ones being COL2A1 (n = 12; skeletal dysplasia), SCN1A (n = 8; epilepsy), and TNFRSF13B (n = 4; inborn errors of immunity). Some causative variants were recurrent, including previously known founder mutations, some novel mutations, and recurrent de novo mutations. Overall, GMCK-RD has resulted in a large number of patients receiving specific molecular diagnoses. Furthermore, negative cases have been included in research studies that have resulted in the discovery of 17 published, novel disease-causing genes. To facilitate the discovery of new disease genes, GMCK-RD has joined international data sharing initiatives, including ClinVar, UDNI, Beacon, and MatchMaker Exchange. CONCLUSIONS: Clinical WGS at GMCK-RD has provided molecular diagnoses to over 1200 individuals with a broad range of rare diseases. Consolidation and spread of this clinical-academic partnership will enable large-scale national collaboration.

Gene expression profiling of periodontitis-affected gingival tissue by spatial transcriptomics.

Periodontitis is a highly prevalent chronic inflammatory disease of the periodontium, leading ultimately to tooth loss. In order to characterize the gene expression of periodontitis-affected gingival tissue, we have here simultaneously quantified and localized gene expression in periodontal tissue using spatial transcriptomics, combining RNA sequencing with histological analysis. Our analyses revealed distinct clusters of gene expression, which were identified to correspond to epithelium, inflamed areas of connective tissue, and non-inflamed areas of connective tissue. Moreover, 92 genes were identified as significantly up-regulated in inflamed areas of the gingival connective tissue compared to non-inflamed tissue. Among these, immunoglobulin lambda-like polypeptide 5 (IGLL5), signal sequence receptor subunit 4 (SSR4), marginal zone B and B1 cell specific protein (MZB1), and X-box binding protein 1 (XBP1) were the four most highly up-regulated genes. These genes were also verified as significantly higher expressed in gingival tissue of patients with periodontitis compared to healthy controls, using reverse transcription quantitative polymerase chain reaction. Moreover, the protein expressions of up-regulated genes were verified in gingival biopsies by immunohistochemistry. In summary, in this study, we report distinct gene expression signatures within periodontitis-affected gingival tissue, as well as specific genes that are up-regulated in inflamed areas compared to non-inflamed areas of gingival tissue. The results obtained from this study may add novel information on the genes and cell types contributing to pathogenesis of the chronic inflammatory disease periodontitis.

An automated approach to prepare tissue-derived spatially barcoded RNA-sequencing libraries.

Sequencing the nucleic acid content of individual cells or specific biological samples is becoming increasingly common. This drives the need for robust, scalable and automated library preparation protocols. Furthermore, an increased understanding of tissue heterogeneity has lead to the development of several unique sequencing protocols that aim to retain or infer spatial context. In this study, a protocol for retaining spatial information of transcripts has been adapted to run on a robotic workstation. The method spatial transcriptomics is evaluated in terms of robustness and variability through the preparation of reference RNA, as well as through preparation and sequencing of six replicate sections of a gingival tissue biopsy from a patient with periodontitis. The results are reduced technical variability between replicates and a higher throughput, processing four times more samples with less than a third of the hands on time, compared to the standard protocol.

Endonuclease specificity and sequence dependence of type IIS restriction enzymes.

Restriction enzymes that recognize specific sequences but cleave unknown sequence outside the recognition site are extensively utilized tools in molecular biology. Despite this, systematic functional categorization of cleavage performance has largely been lacking. We established a simple and automatable model system to assay cleavage distance variation (termed slippage) and the sequence dependence thereof. We coupled this to massively parallel sequencing in order to provide sensitive and accurate measurement. With this system 14 enzymes were assayed (AcuI, BbvI, BpmI, BpuEI, BseRI, BsgI, Eco57I, Eco57MI, EcoP15I, FauI, FokI, GsuI, MmeI and SmuI). We report significant variation of slippage ranging from 1-54%, variations in sequence context dependence, as well as variation between isoschizomers. We believe this largely overlooked property of enzymes with shifted cleavage would benefit from further large scale classification and engineering efforts seeking to improve performance. The gained insights of in-vitro performance may also aid the in-vivo understanding of these enzymes.