Pairs Of Sequences Research Articles

Identifying ADGRG1 as a specific marker for tumor-reactive T cells in acute myeloid leukemia

Besides chemotherapy and hematopoietic stem cell transplantation (HSCT), autologous T cells can also serve as a new treatment approach for AML patients. However, the features of tumor-reactive T cells and their distinctive markers still lack full description. To evaluate the characteristics of tumor-reactive T cells, we collected bone marrow (BM) T cells from newly diagnosed AML patients with RUNX1::RUNX1T1 as examples for paired single-cell RNA sequencing and single-cell V(D)J sequencing. Based on the STARTRAC-like algorithm, we defined bystander T cells and tumor-reactive T cells. Compared with bystander T cells, tumor-reactive T cells presented as senescent-like cytotoxic terminally differentiated T cells (Temra) with upregulated NK-related markers. Additionally, we found ADGRG1 could serve as the specific marker of CD8+ T tumor-reactive T cell and validated it through the Runx1Runx1t1/+; Mx1-Cre mouse model. In chimeric antigen receptor (CAR)-T and target cell system, ADGRG1 was selectively upregulated upon antigen-TCR encounter. Moreover, ADGRG1+CD8+ T cells released a higher level of IFN-γ and showed higher cell-killing ability when exposed to matched AML blasts. Together, our findings depict the single-cell profile of tumor-reactive T cells in AML BM and propose that ADGRG1 can act as an indicator of T cell tumor reactivity in AML, which may be further harnessed for adoptive cell therapy and tumor-reactive TCR enrichment.

Convex combinations of some convergent sequences

We consider the convex combinations , of a pair of sequences of real numbers and such that , converging to , and study the location of the limit inside the intervals , for every or for sufficiently large . We also investigate the same problem for the case of two corresponding sequences converging to . Among other results, we prove some, a bit, unexpected ones. Namely, for each , we determine the exact index at which the sequence changes the monotonicity, and we also determine the type of the monotonicity. A number of interesting remarks are also presented.

Phylogeography of a herbal Pinellia ternata reveals repeated range expansions and inter/postglacial recolonization routes on the fragmented distribution pattern in China.

Most plant phylogeographic studies in China have focused on the importance of genetic divergence and where should the shelter be located. Little attention has been paid to range expansion and recolonization routes in this region. In this study, two cpDNA fragments (psbK-psbI and trnL-F), two pairs of nuclear gene sequences (ITS and ETS), and nine pairs of SSR molecular markers were used, combined with Bayesian Skyline Plot method, gene barrier analysis, and species distribution models to explore the phylogeographical pattern, potential expansion routes and population dynamic history of Pinellia ternata from 22 population. The results showed that phylogeograhical pattern and genetic structure for P. ternata are effected by environmental heterogeneity and climate fluctuation, and it can be divided into two groups (Southwest group, Central and Eastern group) and thus there are at least two glacial refugia in China. Three expanding routes within groups were explored to contribute to the phylogeogrephic pattern of P. ternata based on the geographical distribution and network analysis of haplotypes. In a word, our study reveals repeated range expansions and inter/postglacial recolonization routes on the fragmented distribution pattern in China and resolves the refugia distributing in China and has also certain reference value for the protection of the medicinal plant P. ternata.

Antibody-SGM, a Score-Based Generative Model for Antibody Heavy-Chain Design.

Traditional computational methods for antibody design involved random mutagenesis followed by energy function assessment for candidate selection. Recently, diffusion models have garnered considerable attention as cutting-edge generative models, lauded for their remarkable performance. However, these methods often focus solely on the backbone or sequence, resulting in the incomplete depiction of the overall structure and necessitating additional techniques to predict the missing component. This study presents Antibody-SGM, an innovative joint structure-sequence diffusion model that addresses the limitations of existing protein backbone generation models. Unlike previous models, Antibody-SGM successfully integrates sequence-specific attributes and functional properties into the generation process. Our methodology generates full-atom native-like antibody heavy chains by refining the generation to create valid pairs of sequences and structures, starting with random sequences and structural properties. The versatility of our method is demonstrated through various applications, including the design of full-atom antibodies, antigen-specific CDR design, antibody heavy chains optimization, validation with Alphafold3, and the identification of crucial antibody sequences and structural features. Antibody-SGM also optimizes protein function through active inpainting learning, allowing simultaneous sequence and structure optimization. These improvements demonstrate the promise of our strategy for protein engineering and significantly increase the power of protein design models.

Novel ERBB2 Variant Potentially Associated with Resistance against Anti-HER2 Monoclonal Antibody-Based Therapy in ERBB2-Amplified Metastatic Colorectal Cancer.

HER2-targeted therapies in ERBB2-amplified metastatic colorectal cancer (mCRC) are effective; however, a notable portion of patients do not respond to treatment, and secondary resistance occurs in most patients receiving these treatments. The purpose of this study was to investigate determinants of treatment efficacy and resistance in patients with ERBB2-amplified mCRC who received HER2-targeted therapy by analyzing multiomics data. We investigated genomic data from a nationwide large cancer genomic screening project, the SCRUM-Japan project. We analyzed paired genome and transcriptome data of tissue and genomic data of ctDNA collected pre- and postprogression in patients enrolled in the related trial, TRIUMPH, in ERBB2-amplified mCRC. In 155 patients with ERBB2-amplified solid tumors who received HER2-targeted therapy based on the SCRUM-Japan project, the objective response rate was 50%, 51%, and 35% in ERBB2 wild-type, variant of unknown significance, and pathogenic variant groups, respectively. In the paired genome and transcriptome data analyses in TRIUMPH, we identified the novel splicing-associated variant c.644-66_-2del in one of the 11 patients with paired whole-exome sequencing and whole-transcriptome sequencing data sets, which lacks the binding domain of pertuzumab, in progressed metastatic tumor as a variant with potential pathogenicity. The time-course ctDNA analysis detected c.644-66_-2del as an acquired variant. This study highlighted the importance of ERBB2 genomic status when evaluating the efficacy of HER2-targeted therapies in ERBB2-amplified mCRC. The identification of a novel splicing-associated variant may provide insights into potential mechanisms of treatment resistance. Furthermore, we demonstrated the utility of ctDNA to follow the acquired genomic status of mCRC tumors.

Novel antibody language model accelerates IgG screening and design for broad-spectrum antiviral therapy.

Therapeutic antibodies have become one of the most influential therapeutics in modern medicine to fight against infectious pathogens, cancer, and many other diseases. However, experimental screening for highly efficacious targeting antibodies is labor-intensive and of high cost, which is exacerbated by evolving antigen targets under selective pressure such as fast-mutating viral variants. As a proof-of-concept, we developed a machine learning-assisted antibody generation pipeline AbGen that greatly accelerates the screening and re-design of immunoglobulins G (IgGs) against a broad spectrum of SARS-CoV-2 coronavirus variant strains. Our AbGen centers around a novel antibody language model (AbLM) that is pretrained on 12 million generic protein domain sequences and fine-tuned on 4,000+ paired VH-VL sequences, with IgG-specific CDR-masking and VH-VL cross-attention. AbLM provides a latent space of IgG sequence embeddings for AbGen, including (a) landscapes of IgGs' activities in neutralizing the wild-type virus are analyzed through structure prediction for IgG and IgG-antigen (viral protein spike's receptor binding domain, RBD) interactions; and (b) landscapes of IgGs' susceptibility in neutralizing variant viruses are predicted through Gaussian process regression, despite that as few as 14 clinical antibodies' responses to variants of concern are available. The AbGen pipeline was applied to over 1300 IgG sequences we collected from RBD-binding B cells of convalescent patients. With experimental validations, AbGen efficiently prioritized IgG candidates against a broad spectrum of viral variants (wildtype, Delta, and Omicron), preventing the infection of host cells in vitro and hACE2 transgenic mice in vivo . Compared to other existing protein language models that require 10-100 times more model parameters, AbLM improved the precision from around 50% to 75% to predict IgGs with low variant susceptibility. Furthermore, AbGen enables structure-based computational protein redesign for selected IgG clones with single amino acid substitutions at the RBD-binding interface that doubled the IgG blockade efficacy for one of the severe, therapy-resistant strains - Delta (B.1.617). Our work expedites applications of artificial intelligence in antibody screen and re- design combining data-driven protein language models and Kriging for antibody sequence analysis and activity prediction, in synergy with physics-driven protein docking and design for antibody-antigen interface analyses and functional optimization.

We are doing it wrong: Putting homology before phylogeny in cyanobacterial taxonomy.

The rapid expansion of whole genome sequencing in bacterial taxonomy has revealed deep evolutionary relationships and speciation signals, but assembly methods often miss true nucleotide diversity in the ribosomal operons. Though it lacks sufficient phylogenetic signal at the species level, the 16S ribosomal RNA gene is still much used in bacterial taxonomy. In cyanobacterial taxonomy, comparisons of 16S-23S Internal Transcribed Spacer (ITS) regions are used to bridge this information gap. Although ITS rRNA region analyses are routinely being used to identify species, researchers often do not identify orthologous operons, which leads to improper comparisons. No method for delineating orthologous operon copies from paralogous ones has been established. A new method for recognizing orthologous ribosomal operons by quantifying the conserved paired nucleotides in a helical domain of the ITS, has been developed. The D1' Index quantifies differences in the ratio of pyrimidines to purines in paired nucleotide sequences of this helix. Comparing 111 operon sequences from 89 strains of Brasilonema, four orthologous operon types were identified. Plotting D1' Index values against the length of helices produced clear separation of orthologs. Most orthologous operons in this study were observed both with and without tRNA genes present. We hypothesize that genomic rearrangement, not gene duplication, is responsible for the variation among orthologs. This new method will allow cyanobacterial taxonomists to utilize ITS rRNA region data more correctly, preventing erroneous taxonomic hypotheses. Moreover, this work could assist genomicists in identifying and preserving evident sequence variability in ribosomal operons, which is an important proxy for evolution in prokaryotes.

Randomised study of a new inline respiratory function monitor (Juno) to improve mask seal and delivered ventilation with neonatal manikins

BackgroundRespiratory function monitors (RFMs) have been used extensively in manikin and infant studies yet have not become the standard of training. We report the outcomes of a new portable, lightweight...

Comparison of clinical selection-based genetic testing with phenotype-agnostic extensive germline sequencing to diagnose genetic predisposition in children with cancer: a prospective diagnostic study

Germline data have become widely available in paediatric oncology since the introduction of paired tumour-germline sequencing. To guide best practice in cancer predisposition syndrome (CPS) diagnostics, we aimed to assess the diagnostic yield of extensive germline analysis compared with clinical selection-based genetic testing among all children with cancer. In this prospective diagnostic study, all children (aged 0-19 years) with newly diagnosed neoplasms treated in the Netherlands national centre, the Princess Máxima Center for Pediatric Oncology (Utrecht, Netherlands), between June 1, 2020, and July 31, 2022, were offered two approaches to identify CPSs. In a phenotype-driven approach, paediatric oncologists used the McGill Interactive Pediatric OncoGenetic Guidelines tool to select children for referral to a clinical geneticist, and for genetic testing. In a phenotype-agnostic approach, CPS gene panel sequencing (143 genes) was offered to all children. In children declining the research CPS gene panel, 49 CPS genes were still analysed as part of routine diagnostics by the pathologist. Children with a causative CPS identified before neoplasm diagnosis were excluded. The primary objective was to compare the number and type of patients diagnosed with a CPS between the two approaches. 1052 children were eligible for this study, of whom 733 (70%) completed both the phenotype-driven approach and received phenotype-agnostic CPS gene panel sequencing (143 genes n=600; 49 genes n=133). In 53 children, a CPS was identified: 14 (26%) were diagnosed by the phenotype-driven approach only, 22 (42%) by CPS gene sequencing only, and 17 (32%) by both approaches. In 27 (51%) of the 53 children, the identified CPS was considered causative for the child's neoplasm. Only one (4%) of the 27 causative CPSs was missed by the phenotype-driven approach and was identified solely by phenotype-agnostic CPS gene sequencing. In 26 (49%) children, a CPS with uncertain causality was identified, including 14 adult-onset CPSs. The CPSs with uncertain causality were mainly detected by the phenotype-agnostic approach (21 [81%] of 26). Phenotype-driven genetic testing and phenotype-agnostic CPS gene panel sequencing were complementary. The phenotype-driven approach identified the most causative CPSs. CPS gene panel sequencing identified additional CPSs, many of those with uncertain causality, but some with clinical utility. We advise clinical evaluation for CPSs in all children with neoplasms. Phenotype-agnostic testing of all CPS genes is preferably conducted only in research settings and should be paired with counseling. Stichting Kinderen Kankervrij.

Enterobacter adelaidei sp. nov. Isolation of an extensively drug resistant strain from hospital wastewater in Australia and the global distribution of the species

BackgroundEnterobacter species are included among the normal human gut microflora and persist in a diverse range of other environmental niches. They have become important opportunistic nosocomial pathogens known to harbour plasmid-mediated multi-class antimicrobial resistance (AMR) determinants. Global AMR surveillance of Enterobacterales isolates shows the genus is second to Klebsiella in terms of frequency of carbapenem resistance. Enterobacter taxonomy is confusing and standard species identification methods are largely inaccurate or insufficient. There are currently 27 named species and a total of 46 taxa in the genus distinguishable via average nucleotide identity (ANI) calculation between pairs of genomic sequences. Here we describe an Enterobacter strain, ECC3473, isolated from the wastewater of an Australian hospital whose species could not be determined by standard methods nor by ribosomal RNA gene multi-locus typing. AimTo characterise ECC3473 in terms of phenotypic and genotypic antimicrobial resistance, biochemical characteristics and taxonomy as well as to determine the global distribution of the novel species to which it belongs. MethodsStandard broth dilution and disk diffusion were used to determine phenotypic AMR. The strain’s complete genome, including plasmids, was obtained following long- and short read sequencing and a novel long/short read hybrid assembly and polishing, and the genomic basis of AMR was determined. Phylogenomic analysis and quantitative measures of relatedness (ANI, digital DNA-DNA hybridisation, and difference in G+C content) were used to study the taxonomic relationship between ECC3473 and Enterobacter type-strains. NCBI and PubMLST databases and the literature were searched for additional members of the novel species to determine its global distribution. ResultsECC3473 is one of 21 strains isolated globally belonging to a novel Enterobacter species for which the name, Enterobacter adelaidei sp. nov. is proposed. The novel species was found to be resilient in its capacity to persist in contaminated water and adaptable in its ability to accumulate multiple transmissible AMR determinants. ConclusionE. adelaidei sp. nov. may become increasingly important to the dissemination of AMR.

Developing a Paired Whole Genome Sequencing Service for Children With Cancer

BackgroundThe uniqueness of paired (tumor and germline) whole genome sequencing (PWGS) in cancer diagnosis and management lies in not just its ability to uncover oncogenic drivers and potential treatment targets but also on the identification of underlying cancer predisposition syndromes, which has significant implications for the patient and their family. AimsThis is a descriptive article highlighting the processes taken by our team to incorporate PWGS into routine National Health Service (NHS) clinical care for children with cancer. The main aim of this article is to share our experience with other centers that may wish to set up similar services and set the stage for future quantitative/qualitative research. MethodsThis article is further supported by an audit focusing on children in whom an underlying cancer predisposition was confirmed. ResultsThe audit highlights the success of the program to date, with 100% of families identified as being at risk of a cancer predisposition syndrome being offered referral to clinical genetics and 100% of at-risk first-degree relatives being offered predictive counseling and testing. Areas requiring improvement included discussion of reproductive options as only six out of nine families (67%) had a documented discussion. ConclusionsIncorporation of the audit recommendations will improve our service, and sharing of our experience will hopefully encourage more pediatric oncology services to introduce PWGS into routine clinical care and reduce inequity of access. Further work is required to assess the long-term cancer risk reduction and establish the psychosocial impact of PWGS for the child and family.

Visual sequence encoding is modulated by music schematic structure and familiarity.

Music is omnipresent in daily life and may interact with critical cognitive processes including memory. Despite music's presence during diverse daily activities including studying, commuting, or working, existing literature has yielded mixed results as to whether music improves or impairs memory for information experienced in parallel. To elucidate how music memory and its predictive structure modulate the encoding of novel information, we developed a cross-modal sequence learning task during which participants acquired sequences of abstract shapes accompanied with paired music. Our goal was to investigate whether familiar and structurally regular music could provide a "temporal schema" (rooted in the organized and hierarchical structure of music) to enhance the acquisition of parallel temporally-ordered visual information. Results revealed a complex interplay between music familiarity and music structural regularity in learning paired visual sequences. Notably, compared to a control condition, listening to well-learned, regularly-structured music (music with high predictability) significantly facilitated visual sequence encoding, yielding quicker learning and retrieval speed. Conversely, learned but irregular music (where music memory violated musical syntax) significantly impaired sequence encoding. While those findings supported our mechanistic framework, intriguingly, unlearned irregular music-characterized by the lowest predictability-also demonstrated memory enhancement. In conclusion, this study demonstrates that concurrent music can modulate visual sequence learning, and the effect varies depending on the interaction between both music familiarity and regularity, offering insights into potential applications for enhancing human memory.

MoPPIt: De Novo Generation of Motif-Specific Binders with Protein Language Models.

The ability to precisely target specific motifs on disease-related proteins, whether conserved epitopes on viral proteins, intrinsically disordered regions within transcription factors, or breakpoint junctions in fusion oncoproteins, is essential for modulating their function while minimizing off-target effects. Current methods struggle to achieve this specificity without reliable structural information. In this work, we introduce a motif-specific PPI targeting algorithm, moPPIt, for de novo generation of motif-specific peptide binders from the target protein sequence alone. At the core of moPPIt is BindEvaluator, a transformer-based model that interpolates protein language model embeddings of two proteins via a series of multi-headed self-attention blocks, with a key focus on local motif features. Trained on over 510,000 annotated PPIs, BindEvaluator accurately predicts target binding sites given protein-protein sequence pairs with a test AUC > 0.94, improving to AUC > 0.96 when fine-tuned on peptide-protein pairs. By combining BindEvaluator with our PepMLM peptide generator and genetic algorithm-based optimization, moPPIt generates peptides that bind specifically to user-defined residues on target proteins. We demonstrate moPPIt's efficacy in computationally designing binders to specific motifs, first on targets with known binding peptides and then extending to structured and disordered targets with no known binders. In total, moPPIt serves as a powerful tool for developing highly specific peptide therapeutics without relying on target structure or structure-dependent latent spaces.

Tone-syllable synchrony in Mandarin: New evidence and implications

Recent research has shown evidence based on a minimal contrast paradigm that consonants and vowels are articulatorily synchronized at the onset of the syllable. What remains less clear is the laryngeal dimension of the syllable, for which evidence of tone synchrony with the consonant-vowel syllable has been circumstantial. The present study assesses the precise tone-vowel alignment in Mandarin Chinese by applying the minimal contrast paradigm. The vowel onset is determined by detecting divergence points of F2 trajectories between a pair of disyllabic sequences with two contrasting vowels, and the onsets of tones are determined by detecting divergence points of f0 trajectories in contrasting disyllabic tone pairs, using generalized additive mixed models (GAMMs). The alignment of the divergence-determined vowel and tone onsets is then evaluated with linear mixed effect models (LMEMs) and their synchrony is validated with Bayes factors. The results indicate that tone and vowel onsets are fully synchronized. There is therefore evidence for strict alignment of consonant, vowel and tone as hypothesized in the synchronization model of the syllable. Also, with the newly established tone onset, the previously reported ‘anticipatory raising’ effect of tone now appears to occur within rather than before the articulatory syllable. Implications of these findings will be discussed.

Unraveling the role of physicochemical differences in predicting protein-protein interactions.

The ability to accurately predict protein-protein interactions is critically important for understanding major cellular processes. However, current experimental and computational approaches for identifying them are technically very challenging and still have limited success. We propose a new computational method for predicting protein-protein interactions using only primary sequence information. It utilizes the concept of physicochemical similarity to determine which interactions will most likely occur. In our approach, the physicochemical features of proteins are extracted using bioinformatics tools for different organisms. Then they are utilized in a machine-learning method to identify successful protein-protein interactions via correlation analysis. It was found that the most important property that correlates most with the protein-protein interactions for all studied organisms is dipeptide amino acid composition (the frequency of specific amino acid pairs in a protein sequence). While current approaches often overlook the specificity of protein-protein interactions with different organisms, our method yields context-specific features that determine protein-protein interactions. The analysis is specifically applied to the bacterial two-component system that includes histidine kinase and transcriptional response regulators, as well as to the barnase-barstar complex, demonstrating the method's versatility across different biological systems. Our approach can be applied to predict protein-protein interactions in any biological system, providing an important tool for investigating complex biological processes' mechanisms.

Challenges in using DNA barcodes for authentication of Sida species

The Indian system of medicine’s “Ayurvedic pharmacopeia of India (API)” recommends the use of Sida cordifolia Linn (root), Sida cordata (Burm.f.) Borss.Waalk. (aerial part), Sida rhombifolia Linn. (root) and Abutilon indicum (Linn.) Sw. (root) in drug preparations of Bala, Nagabala, Mahabala and Atibala respectively. Moreover many Sida sp. are being used in China, South East Asia, Africa and South America in their traditional healthcare systems. It is a taxonomically complex genus often difficult to authenticate from dried/chopped herbal market samples. Many Sida sequences from the NCBI database, including published reports, were highly suspect and were redesignated into species groups during phylogenetic clustering. Among the four loci studied, ITS2 region was identified as the best for the Sida species identification followed by trnH-psbA. The trnH-psbA phylogeny however fails to differentiate between (1) S. beddomei and S. cordata, (2) S. alnifolia and S. scabrida, (3) S. cordifolia and S. fryxellii that formed monophyletic clusters. The average evolutionary divergence over Sequence Pairs within each species group for ITS2 locus ranged from 0.000 to 0.009 (Average=0.0021), while average Interspecific distance between species was 0.1175 making them ideal for authentication of Sida species. The matK and rbcL is recommended as a back-up loci for identifying intergeneric adulterants in case, the ITS2 or trnH-psbA amplification fails. The present study identified two market samples as adulterant species; (1) S. alnifolia and (2) a mixture of S. acuta and S. alnifolia/S.scabrida. The study provides a roadmap for Ayurvedic/herbal industry to utilize DNA barcoding for authentication of Sida species. At the same time the presence of “Unknown Sida group” highlights the need for further research to accurately classify and identify all Sida species at the phylogenetic level, utilizing the DNA barcode sequences to thoroughly understand the diversity and evolution of the Sida genus.

Biomarker Analyses Investigating Disease Biology and Associations with Outcomes in the JAVELIN Merkel 200 Trial of Avelumab in Metastatic Merkel Cell Carcinoma.

Avelumab (anti-PD-L1) became the first approved treatment for metastatic Merkel cell carcinoma (mMCC) based on results from the phase II JAVELIN Merkel 200 trial. In this study, we report exploratory biomarker analyses from the trial. Patients with mMCC (n = 88) with or without prior first-line chemotherapy received avelumab 10 mg/kg every 2 weeks. We conducted analyses on somatic mutations, mutational signatures, and tumor mutational burden using paired whole-exome sequencing. Additionally, we examined gene and gene set expression, immune content from RNA sequencing profiles, as well as tumor PD-L1 and CD8 statuses from IHC and CD8 status from digital pathology. Tumors positive for Merkel cell polyomavirus (MCPyV) were characterized by an absence of driver mutations and a low tumor mutational burden, consistent with previous studies. A novel MCPyV-specific host gene expression signature was identified. MCPyV+ tumors had increased levels of immunosuppressive M2 macrophages in the tumor microenvironment, which seemed to correlate with PD-L1 expression; high CD8+ T-cell density in these tumors did not predict response to avelumab. Conversely, in patients with MCPyV- tumors, higher CD8+ T-cell density seemed to be associated with response to avelumab. Mutations in several genes were associated with treatment outcomes. Compared with tumors sampled before chemotherapy, tumors sampled after chemotherapy had downregulated gene signatures for immune responses, including reduced expression of IFNγ-related pathways. Levels of activated dendritic cells in responding patients were higher in patients assessed after versus before chemotherapy. Exploratory analyses provide insights into mMCC biology and potential associations with response to avelumab. Chemotherapy seems to negatively modulate the immune microenvironment.

Misexpression of inactive genes in whole blood is associated with nearby rare structural variants

Gene misexpression is the aberrant transcription of a gene in a context where it is usually inactive. Despite its known pathological consequences in specific rare diseases, we have a limited understanding of its wider prevalence and mechanisms in humans. To address this, we analyzed gene misexpression in 4,568 whole-blood bulk RNA sequencing samples from INTERVAL study blood donors. We found that while individual misexpression events occur rarely, in aggregate they were found in almost all samples and a third of inactive protein-coding genes. Using 2,821 paired whole-genome and RNA sequencing samples, we identified that misexpression events are enriched in cis for rare structural variants. We established putative mechanisms through which a subset of SVs lead to gene misexpression, including transcriptional readthrough, transcript fusions, and gene inversion. Overall, we develop misexpression as a type of transcriptomic outlier analysis and extend our understanding of the variety of mechanisms by which genetic variants can influence gene expression.

Introduction and impact of routine whole genome sequencing in the diagnosis and management of sarcoma

BackgroundSarcomas are diverse neoplasms with highly variable histological appearances in which diagnosis is often challenging and management options for metastatic/unresectable disease limited. Many sarcomas have distinctive molecular alterations, but the range of alterations is large, variable in type and rapidly increasing, meaning that testing by limited panels is unable to capture the broad spectrum of clinically pertinent genomic drivers required. Paired whole genome sequencing (WGS) in contrast allows comprehensive assessment of small variants, copy number and structural variants along with mutational signature analysis and germline testing.MethodsIntroduction of WGS as a diagnostic standard for all eligible patients with known or suspected soft tissue sarcoma over a 2-year period at a soft tissue sarcoma treatment centre.ResultsWGS resulted in a refinement in the diagnosis in 37% of cases, identification of a target for personalised therapy in 33% of cases, and a germline alteration in 4% of cases.ConclusionIntroduction of WGS poses logistical and training challenges, but offers significant benefits to this group of patients.

Mesomelia-synostoses syndrome: contiguous deletion syndrome, SULF1 haploinsufficiency or enhancer adoption?

BackgroundMesomelia-Synostoses Syndrome (MSS)(OMIM 600,383) is a rare autosomal dominant disorder characterized by mesomelic limb shortening, acral synostoses and multiple congenital malformations which is described as a contiguous deletion syndrome involving the two genes SULF1 and SLCO5A1. The study of apparently balanced chromosomal rearrangements (BCRs) is a cytogenetic strategy used to identify candidate genes associated with Mendelian diseases or abnormal phenotypes. With the improved development of genomic technologies, new methods refine this search, allowing better delineation of breakpoints as well as more accurate genotype-phenotype correlation.Case presentationWe present a boy with a global development deficit, delayed speech development and an ASD (Asperger) family history, with an apparently balanced “de novo” reciprocal translocation [t(1;8)(p32.2;q13)dn]. The cytogenetic molecular study identified a likely pathogenic deletion of 21 kb in the 15q12 region, while mate pair sequencing identified gene-truncations at both the 1p32.2 and 8q13 translocation breakpoints.ConclusionsThe identification of a pathogenic alteration on 15q12 involving GABRA5 was likely the main cause of the ASD-phenotype. Importantly, the chr8 translocation breakpoint truncating SLCO5A1 exclude SLCO5A1 as a candidate for MSS, leaving SULF1 as the primary candidate. However, the deletions observed in MSS remove a topological associated domain (TAD) boundary separating SULF1 and SLCO5A1. Hence, Mesomelia-Synostoses syndrome is either caused by haploinsufficiency of SULF1 or ectopic enhancer effects where skeletal/chrondrogenic SULF1 enhancers drive excopic expression of developmental genes in adjacent TADs including PRDM14, NCOA2 and/or EYA1.