Array Automated Assembly, Phase 2

The baseline process sequence using nontextured square wafers was integrated. Difficulties encountered include: (1) replacement of the N-250 spray on diffusion source with PX-10 source; and (2) modification of the firing for printed silver and aluminum contracts is required to accommodate the change of wafer size and shape. Results indicate that the cells processed through the entire process sequence except laser scribe and spray on AR coating indicate the process sequence is feasible. Greater cell conversion efficiency is presented

Blood RNA analysis can increase clinical diagnostic rate and resolve variants of uncertain significance

Purpose: Diagnosis of genetic disorders is hampered by large numbers of variants of uncertain significance (VUSs) identified through next-generation sequencing. Many such variants may disrupt normal RNA splicing. We examined effects on splicing of a large cohort of clinically identified variants and compared performance of bioinformatic splicing prediction tools commonly used in diagnostic laboratories. Methods: Two hundred fifty-seven variants (coding and noncoding) were referred for analysis across three laboratories. Blood RNA samples underwent targeted reverse transcription polymerase chain reaction (RT-PCR) analysis with Sanger sequencing of PCR products and agarose gel electrophoresis. Seventeen samples also underwent transcriptome-wide RNA sequencing with targeted splicing analysis based on Sashimi plot visualization. Bioinformatic splicing predictions were obtained using Alamut, HSF 3.1, and SpliceAI software. Results: Eighty-five variants (33%) were associated with abnormal splicing. The most frequent abnormality was upstream exon skipping (39/85 variants), which was most often associated with splice donor region variants. SpliceAI had greatest accuracy in predicting splicing abnormalities (0.91) and outperformed other tools in sensitivity and specificity. Conclusion: Splicing analysis of blood RNA identifies diagnostically important splicing abnormalities and clarifies functional effects of a significant proportion of VUSs. Bioinformatic predictions are improving but still make significant errors. RNA analysis should therefore be routinely considered in genetic disease diagnostics.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.This research was funded by National Institute for Health Research (NIHR) and the NewLife Foundation. The Baralle lab is supported by NIHR Research Professorship to D.B. (RP-2016-07-011).published version, accepted version (6 month embargo), submitted versio

Molecular differences between ductal carcinoma in situ and adjacent invasive breast carcinoma: a multiplex ligation-dependent probe amplification study

Ductal carcinoma in situ (DCIS) accounts for approximately 20% of mammographically detected breast cancers. Although DCIS is generally highly curable, some women with DCIS will develop life-threatening invasive breast cancer, but the determinants of progression to infiltrating ductal cancer (IDC) are largely unknown. In the current study, we used multiplex ligation-dependent probe amplification (MLPA), a multiplex PCR-based test, to compare copy numbers of 21 breast cancer related genes between laser-microdissected DCIS and adjacent IDC lesions in 39 patients. Genes included in this study were ESR1, EGFR, FGFR1, ADAM9, IKBKB, PRDM14, MTDH, MYC, CCND1, EMSY, CDH1, TRAF4, CPD, MED1, HER2, CDC6, TOP2A, MAPT, BIRC5, CCNE1 and AURKA

“Halal fiction” and the limits of postsecularism: Criticism, critique, and the Muslim in Leila Aboulela’s Minaret

This article examines Leila Aboulela’s 2005 novel Minaret, considering the extent to which it can be seen as an example of a postsecular text. The work has been praised by some as one of the most cogent attempts to communicate a life of Islamic faith in the English language novel form. Others have expressed concern about what they perceive as its apparent endorsement of submissiveness and a secondary status for women, along with its silence on some of the more thorny political issues facing Islam in the modern world. I argue that both these readings are shaped by the current “market” for Muslim novels, which places on such texts the onus of being “authentically representative”. Moreover, while apparently underwriting claims to authenticity, Aboulela’s technique of unvarnished realism requires of the reader the kind of suspension of disbelief in the metaphysical that appears to run contrary to the secular trajectory of the English literary novel in the last 300 years. I take issue with binarist versions of the postsecular thesis that equate the post-Enlightenment West with relentless desacralization and the “Islamic world” with a persistent collectivist and spiritual outlook, and suggest that we pay more attention to fundamental narrative elements which recur across the supposed West/East divide. Historically simplistic understandings of the secularization of culture — followed in the last few years by a postsecular turn — misrepresent the actual evolution of the novel. The “religious” persists, albeit transmuted into symbolic schema and themes of material or emotional redemption. I end by arguing for the renewed relevance of the kind of analysis of literary “archetypes” suggested by Northrop Frye, albeit disentangled from its specifically Christian resonances and infused by more attention to cultural cross-pollination. It is this type of approach that seems more accurately to account for the peculiarities of Aboulela’s fiction

A systematic analysis of splicing variants identifies new diagnoses in the 100,000 Genomes Project

Background Genomic variants which disrupt splicing are a major cause of rare genetic diseases. However, variants which lie outside of the canonical splice sites are difficult to interpret clinically. Improving the clinical interpretation of non-canonical splicing variants offers a major opportunity to uplift diagnostic yields from whole genome sequencing data. Methods Here, we examine the landscape of splicing variants in whole-genome sequencing data from 38,688 individuals in the 100,000 Genomes Project and assess the contribution of non-canonical splicing variants to rare genetic diseases. We use a variant-level constraint metric (the mutability-adjusted proportion of singletons) to identify constrained functional variant classes near exon–intron junctions and at putative splicing branchpoints. To identify new diagnoses for individuals with unsolved rare diseases in the 100,000 Genomes Project, we identified individuals with de novo single-nucleotide variants near exon–intron boundaries and at putative splicing branchpoints in known disease genes. We identified candidate diagnostic variants through manual phenotype matching and confirmed new molecular diagnoses through clinical variant interpretation and functional RNA studies. Results We show that near-splice positions and splicing branchpoints are highly constrained by purifying selection and harbour potentially damaging non-coding variants which are amenable to systematic analysis in sequencing data. From 258 de novo splicing variants in known rare disease genes, we identify 35 new likely diagnoses in probands with an unsolved rare disease. To date, we have confirmed a new diagnosis for six individuals, including four in whom RNA studies were performed. Conclusions Overall, we demonstrate the clinical value of examining non-canonical splicing variants in individuals with unsolved rare diseases

Genomic rearrangements in BRCA1 and BRCA2: A literature review

Women with mutations in the breast cancer genes BRCA1 or BRCA2 have an increased lifetime risk of developing breast, ovarian and other BRCA-associated cancers. However, the number of detected germline mutations in families with hereditary breast and ovarian cancer (HBOC) syndrome is lower than expected based upon genetic linkage data. Undetected deleterious mutations in the BRCA genes in some high-risk families are due to the presence of intragenic rearrangements such as deletions, duplications or insertions that span whole exons. This article reviews the molecular aspects of BRCA1 and BRCA2 rearrangements and their frequency among different populations. An overview of the techniques used to screen for large rearrangements in BRCA1 and BRCA2 is also presented. The detection of rearrangements in BRCA genes, especially BRCA1, offers a promising outlook for mutation screening in clinical practice, particularly in HBOC families that test negative for a germline mutation assessed by traditional methods

Clinical and pathological characteristics of Chinese patients with BRCA related breast cancer

Breast cancers related to BRCA mutations are associated with particular biological features. Here we report the clinical and pathological characteristics of breast cancer in Chinese women with and without BRCA mutations and of carriers of BRCA1 mutations compared to BRCA2 mutations. Two hundred and 26 high-risk Hong Kong Chinese women were tested for BRCA mutations, medical information was obtained from medical records, and risk and demographic information was obtained from personal interviews. In this cohort, 28 (12.4%) women were BRCA mutation carriers and among these carriers, 39.3% were BRCA1 and 60.7% were BRCA2 mutations. Mutation carriers were more likely to have a familial history of breast and ovarian cancer, high-grade cancers, and triple negative (TN) cancers. Prevalence of TN was 48.3% in BRCA carriers and 25.6% in non-carriers and was 67.7% in BRCA1 and 35.3% in BRCA2 carriers. Estrogen receptor (ER) negative cancer was significantly associated with BRCA1 mutations, especially in those under 40 years of age. BRCA-related breast cancer in this Chinese population is associated with family history and adverse pathological/prognostic features, with BRCA2 mutations being more prevalent but BRCA1 carriers having more aggressive and TN cancers. Compared to Caucasian populations, prevalence of BRCA2 mutations and TN cancer in BRCA2 mutation carriers in Chinese population are elevated

Finding Diagnostically Useful Patterns in Quantitative Phenotypic Data.

Trio-based whole-exome sequence (WES) data have established confident genetic diagnoses in ∼40% of previously undiagnosed individuals recruited to the Deciphering Developmental Disorders (DDD) study. Here we aim to use the breadth of phenotypic information recorded in DDD to augment diagnosis and disease variant discovery in probands. Median Euclidean distances (mEuD) were employed as a simple measure of similarity of quantitative phenotypic data within sets of ≥10 individuals with plausibly causative de novo mutations (DNM) in 28 different developmental disorder genes. 13/28 (46.4%) showed significant similarity for growth or developmental milestone metrics, 10/28 (35.7%) showed similarity in HPO term usage, and 12/28 (43%) showed no phenotypic similarity. Pairwise comparisons of individuals with high-impact inherited variants to the 32 individuals with causative DNM in ANKRD11 using only growth z-scores highlighted 5 likely causative inherited variants and two unrecognized DNM resulting in an 18% diagnostic uplift for this gene. Using an independent approach, naive Bayes classification of growth and developmental data produced reasonably discriminative models for the 24 DNM genes with sufficiently complete data. An unsupervised naive Bayes classification of 6,993 probands with WES data and sufficient phenotypic information defined 23 in silico syndromes (ISSs) and was used to test a "phenotype first" approach to the discovery of causative genotypes using WES variants strictly filtered on allele frequency, mutation consequence, and evidence of constraint in humans. This highlighted heterozygous de novo nonsynonymous variants in SPTBN2 as causative in three DDD probands

Prioritization of genes driving congenital phenotypes of patients with de novo genomic structural variants

Background:Genomic structural variants (SVs) can affect many genes and regulatory elements. Therefore, the molecular mechanisms driving the phenotypes of patients carrying de novo SVs are frequently unknown. Methods:We applied a combination of systematic experimental and bioinformatic methods to improve the molecular diagnosis of 39 patients with multiple congenital abnormalities and/or intellectual disability harboring apparent de novo SVs, most with an inconclusive diagnosis after regular genetic testing. Results: In 7 of these cases (18%), whole-genome sequencing analysis revealed disease-relevant complexities of the SVs missed in routine microarray-based analyses. We developed a computational tool to predict the effects on genes directly affected by SVs and on genes indirectly affected likely due to the changes in chromatin organization and impact on regulatory mechanisms. By combining these functional predictions with extensive phenotype information, candidate driver genes were identified in 16/39 (41%) patients. In 8 cases, evidence was found for the involvement of multiple candidate drivers contributing to different parts of the phenotypes. Subsequently, we applied this computational method to two cohorts containing a total of 379 patients with previously detected and classified de novo SVs and identified candidate driver genes in 189 cases (50%), including 40 cases whose SVs were previously not classified as pathogenic. Pathogenic position effects were predicted in 28% of all studied cases with balanced SVs and in 11% of the cases with copy number variants. Conclusions:These results demonstrate an integrated computational and experimental approach to predict driver genes based on analyses of WGS data with phenotype association and chromatin organization datasets. These analyses nominate new pathogenic loci and have strong potential to improve the molecular diagnosis of patients with de novo SVs