Pairs Of Sequences Research Articles

Discontiguous recurrences of IDH-wildtype glioblastoma share a common origin with the initial tumor and are frequently hypermutated

Glioblastoma is the deadliest primary brain tumor, largely due to inevitable recurrence of the disease after treatment. While most recurrences are local, patients rarely present with a new discontiguous focus of glioblastoma. Little is currently known about the genetic profile of discontiguous recurrences. In our institutional database, we identified 22 patients with targeted exome sequencing of pairs of initial and recurrent IDH-wildtype glioblastoma. Recurrences were classified as contiguous or discontiguous based on the presence or absence of T2 FLAIR signal connection to the initial site of disease on MRI. Exome analysis revealed shared driver and passenger mutations between discontiguous recurrences and initial tumors, supporting a common origin. Discontiguous recurrences were more likely to be hypermutated compared to contiguous recurrences (p = 0.038). Analysis of 2 glioblastoma cases with discontiguous recurrence at a collaborating institution also exhibited hypermutation. In conclusion, discontiguous glioblastoma recurrences share a common origin with the initial tumor and are more likely to be hypermutated than contiguous recurrences.

Quantitative Analysis of Hepatitis D Virus Using gRNA-Sensitive Semiconducting Polymer Dots.

Hepatitis D virus (HDV) significantly influences the progression of liver diseases. Through clinical observations and database analyses, it has been established that patients coinfected with HDV and hepatitis B virus (HBV) experience accelerated progression toward cirrhosis, hepatocellular carcinoma (HCC), and liver failure compared to those infected solely with HBV. A higher viral load correlates with increased replicative activity, enhanced infectivity, and more severe disease manifestations. In this study, we use HDV gRNA-sensitive semiconducting polymer dots (Pdots) as the nanoprobes for the quantitative analysis of HDV copy number variations. The surface of the Pdots is engineered with a clamp design that includes a pair of reporter sequences, protection sequences, and capture sequences tailored to the conserved sequence length of the HDV genome. The capture sequence, comprising leading and trailing chains, specifically binds to the gRNA of the target virus. The protection sequence shields the Pdots from external interference, while the reporter sequence detects the presence of target gRNA through the degradation of fluorescent dye Cy5.5dt. We demonstrate the effectiveness of this assay in a stably transfected cell line derived from HepG2-HDV cells and its translational application in clinical samples from patients. Additionally, this nanobiosensor can accurately detect gRNA at femtomolar (fM) levels, a sensitivity unachievable by previously reported methods. This novel virus quantification system offers significant potential for clinical and virological applications, enhancing screening, early diagnosis, and personalized treatment strategies.

Regularities of the theory of quasi-geodesic mappings of special parabolic spaces

We study quasi-geodesic mappings (QGM) of generalized-recurrent-parabolic spaces f: (Vn, gij, Fih) → (V'n, g'ij, Fih). QGM can be of two types: general and canonical. This article examines the QGM of the general type. Earlier, we considered the fundamental questions of the theory of QGM of generalized-recurrent-parabolic spaces. We proved theorems that allow for any generalized-recurrent-parabolic space (Vn, gij, Fih) to either find all spaces (V'n, g'_{ij}, Fih) on which Vn admits QGM of the general form, or prove that there are no such spaces. In this article, we constructed a Γ-transformation that makes it possible to obtain from a pair of generalized-recurrent-parabolic spaces that are in a quasi-geodesic mapping, an infinite sequence of pairs of other generalized-recurrent-parabolic spaces, which are also in a quasi-geodesic mapping.

Return of Clinically Actionable Pharmacogenetic Results From Molecular Tumor Board DNA Sequencing Data: Workflow and Estimated Costs.

Pharmacogenetic testing can prevent severe toxicities from several oncology drug therapies; it also has the potential to improve the outcomes from supportive care drugs. Paired tumor and germline sequencing is increasingly common in oncology practice; these include sequencing of pharmacogenes, but the germline pharmacogenetic variants are rarely included in the clinical reports, despite many being clinically actionable. We established an informatics workflow to evaluate the clinical sequencing results for pharmacogenetic variants. We used the Aldy computational tool, which we have previously shown to determine the variant alleles in 14 pharmacogenes in clinical sequencing data with >99% accuracy, to identify pharmacogenetic variants in the clinical whole exome sequencing from our molecular tumor board. Patients with genetic variants that are clinically actionable for their individual therapy programs, including both treatment and supportive care, are referred to a clinical pharmacogenetics testing laboratory for confirmation. Through an evaluation of our weekly informatics workflow, we determined it took approximately 3.25 hours to complete the analysis of the sequencing data from approximately 20 patients. Using a United States pharmacist's median salary, we estimated the incremental added cost of the process to be only ~$15 per patient. This adds only a minor increase to the patient's cost of testing and has the potential to improve the safety and efficacy of their treatment.

Estimating evolutionary and demographic parameters via ARG-derived IBD.

Inference of evolutionary and demographic parameters from a sample of genome sequences often proceeds by first inferring identical-by-descent (IBD) genome segments. By exploiting efficient data encoding based on the ancestral recombination graph (ARG), we obtain three major advantages over current approaches: (i) no need to impose a length threshold on IBD segments, (ii) IBD can be defined without the hard-to-verify requirement of no recombination, and (iii) computation time can be reduced with little loss of statistical efficiency using only the IBD segments from a set of sequence pairs that scales linearly with sample size. We first demonstrate powerful inferences when true IBD information is available from simulated data. For IBD inferred from real data, we propose an approximate Bayesian computation inference algorithm and use it to show that even poorly-inferred short IBD segments can improve estimation. Our mutation-rate estimator achieves precision similar to a previously-published method despite a 4 000-fold reduction in data used for inference, and we identify significant differences between human populations. Computational cost limits model complexity in our approach, but we are able to incorporate unknown nuisance parameters and model misspecification, still finding improved parameter inference.

Almost Two-Valued Periodic Golay Sequence Pairs Derived From the Legendre Symbol

Almost Two-Valued Periodic Golay Sequence Pairs Derived From the Legendre Symbol

Genomic profiling reveals SMARCA4 mutations are associated with shorter overall and intracranial progression free survival in melanoma brain metastasis patients.

Melanoma brain metastases (MBMs) are a common, lethal complication of metastatic melanoma. Despite improvements in treatments, subsets of MBM patients experience rapid decline, and few prognostic biomarkers have been identified. An improved understanding of the molecular features specifically associated with MBM overall survival (OS) and intracranial progression free survival (PFS) could facilitate the development of more effective clinical management strategies. We established an initial cohort of 102 MBMs, 970 unmatched melanoma extracranial metastases (ECMs), and 569 unmatched melanoma primaries with available targeted exome sequencing data covering 182 genes and a validation cohort of 50 MBMs with SMARCA4 genomically profiled. Kaplan-Meier analysis, log-rank test, and Cox proportional hazards model were used to evaluate associations between pathogenic genomic alterations and OS and intracranial PFS. We evaluated 14 MBMs and 19 ECMs with paired RNA sequencing and whole exome sequencing data to identify genotype-transcriptome correlations. Of 43 genes significantly mutated amongst MBMs, only pathogenic mutations in SMARCA4 significantly associated with shorter OS and intracranial PFS on univariable and multivariable analyses in MBM patients but not from first ECM or primary tumor diagnosis. SMARCA4 mutations significantly associated with enrichment of oxidative phosphorylation (OXPHOS) and depletion of immune signaling gene sets. Pathogenic SMARCA4 mutations independently predict an association with shorter OS and intracranial PFS in MBM patients and associate with expression of pathways known to mediate melanoma virulence. These findings add to our understanding of MBM pathogenesis and suggest their potential use as prognostic biomarkers and possible therapeutic opportunities.

Assembly and comparative analysis of the complete mitogenome of Rubus chingii var. suavissimus, an exceptional berry plant possessing sweet leaves

Rubus chingii var. suavissimus is a special berry plant of Rubus in the Rosaceae family. Its leaves contain high-sweetness, low-calorie, and non-toxic sweet ingredients, known as rubusoside. As a medicine and food biofunctional plant, it is a combination of “tea, sugar, and medicine.” In this study, the complete mitogenome of R. chingii var. suavissimus was successfully assembled and annotated based on PacBio HiFi sequencing technology. The mitogenome of R. chingii var. suavissimus was a typical master circle structure, spanning 432,483 bp and containing 34 unique protein-coding genes (PCGs), 20 tRNAs, and 3 rRNAs. The majority of these PCGs was subjected to purifying selection, and only one gene (ccmB) showed sign of positive selection. The mitogenome of R. chingii var. suavissimus contained a large number of repeats, and the homogeneous fragments transferring between plastid genome and mitogenome, with a total of 55 pairs of mitochondrial plastid sequences (MTPTs), and the total size was 56,913 bp. Comparative analysis showed that the non-coding region in the mitogenome of R. chingii var. suavissimus had undergone frequent rearrangements during evolution, but the coding region was still highly conserved. Furthermore, the maximum likelihood and Bayesian inference phylogenetic trees were reconstructed of 10 shared PCGs in 36 plant species. The topological structures of two phylogenetic trees were consistent with the APG IV classification system and had high support rates. In general, this study clarifies the mitogenome of R. chingii var. suavissimus and provides valuable insights into the genetic evolution of the Rosaceae family.

Predictive Modeling of Gene Expression and Localization of DNA Binding Site Using Deep Convolutional Neural Networks.

Despite the sequencing revolution, large swaths of the genomes sequenced to date lack any information about the arrangement of transcription factor binding sites on regulatory DNA. Massively Parallel Reporter Assays (MPRAs) have the potential to dramatically accelerate our genomic annotations by making it possible to measure the gene expression levels driven by thousands of mutational variants of a regulatory region. However, the interpretation of such data often assumes that each base pair in a regulatory sequence contributes independently to gene expression. To enable the analysis of this data in a manner that accounts for possible correlations between distant bases along a regulatory sequence, we developed the Deep learning Adaptable Regulatory Sequence Identifier (DARSI). This convolutional neural network leverages MPRA data to predict gene expression levels directly from raw regulatory DNA sequences. By harnessing this predictive capacity, DARSI systematically identifies transcription factor binding sites within regulatory regions at single-base pair resolution. To validate its predictions, we benchmarked DARSI against curated databases, confirming its accuracy in predicting transcription factor binding sites. Additionally, DARSI predicted novel unmapped binding sites, paving the way for future experimental efforts to confirm the existence of these binding sites and to identify the transcription factors that target those sites. Thus, by automating and improving the annotation of regulatory regions, DARSI generates experimentally actionable predictions that can feed iterations of the theory-experiment cycle aimed at reaching a predictive understanding of transcriptional control.

Rational gluing in edge replacement systems

In this paper, we prove the rationality of the gluing relation of edge replacement systems, which were introduced for studying rearrangement groups of fractals. More precisely, we describe an algorithmic procedure for building a finite state automaton that recognizes pairs of equivalent sequences that are glued in the fractal. This fits in recent interest toward the rationality of gluing relations on totally disconnected compact metrizable spaces.

MMETHANE: interpretable AI for predicting host status from microbial composition and metabolomics data.

Metabolite production, consumption, and exchange are intimately involved with host health and disease, as well as being key drivers of host-microbiome interactions. Despite the increasing prevalence of datasets that jointly measure microbiome composition and metabolites, computational tools for linking these data to the status of the host remain limited. To address these limitations, we developed MMETHANE, an open-source software package that implements a purpose-built deep learning model for predicting host status from paired microbial sequencing and metabolomic data. MMETHANE incorporates prior biological knowledge, including phylogenetic and chemical relationships, and is intrinsically interpretable, outputting an English-language set of rules that explains its decisions. Using a compendium of six datasets with paired microbial composition and metabolomics measurements, we showed that MMETHANE always performed at least on par with existing methods, including blackbox machine learning techniques, and outperformed other methods on >80% of the datasets evaluated. We additionally demonstrated through two cases studies analyzing inflammatory bowel disease gut microbiome datasets that MMETHANE uncovers biologically meaningful links between microbes, metabolites, and disease status.

DiffPaSS-high-performance differentiable pairing of protein sequences using soft scores.

Identifying interacting partners from two sets of protein sequences has important applications in computational biology. Interacting partners share similarities across species due to their common evolutionary history, and feature correlations in amino acid usage due to the need to maintain complementary interaction interfaces. Thus, the problem of finding interacting pairs can be formulated as searching for a pairing of sequences that maximizes a sequence similarity or a coevolution score. Several methods have been developed to address this problem, applying different approximate optimization methods to different scores. We introduce Differentiable Pairing using Soft Scores (DiffPaSS), a differentiable framework for flexible, fast, and hyperparameter-free optimization for pairing interacting biological sequences, which can be applied to a wide variety of scores. We apply it to a benchmark prokaryotic dataset, using mutual information and neighbor graph alignment scores. DiffPaSS outperforms existing algorithms for optimizing the same scores. We demonstrate the usefulness of our paired alignments for the prediction of protein complex structure. DiffPaSS does not require sequences to be aligned, and we also apply it to nonaligned sequences from T-cell receptors. A PyTorch implementation and installable Python package are available at https://github.com/Bitbol-Lab/DiffPaSS.

Large scale paired antibody language models.

Antibodies are proteins produced by the immune system that can identify and neutralise a wide variety of antigens with high specificity and affinity, and constitute the most successful class of biotherapeutics. With the advent of next-generation sequencing, billions of antibody sequences have been collected in recent years, though their application in the design of better therapeutics has been constrained by the sheer volume and complexity of the data. To address this challenge, we present IgBert and IgT5, the best performing antibody-specific language models developed to date which can consistently handle both paired and unpaired variable region sequences as input. These models are trained comprehensively using the more than two billion unpaired sequences and two million paired sequences of light and heavy chains present in the Observed Antibody Space dataset. We show that our models outperform existing antibody and protein language models on a diverse range of design and regression tasks relevant to antibody engineering. This advancement marks a significant leap forward in leveraging machine learning, large scale data sets and high-performance computing for enhancing antibody design for therapeutic development.

A new species of Myxobolus (Cnidaria: Myxosporea: Myxobolidae) from the gills of the green sunfish, Lepomis cyanellus (Perciformes: Centrarchidae), from the Ouachita River Drainage of Western Arkansas.

Forty-two species of myxozoans, including 31 species of Myxobolus Bütschli, 1882, have been described from centrarchid fishes. One species, the green sunfish (Lepomis cyanellus), has been reported to host at least three species of Myxobolus. Between March 2023 and June 2024, 42 L. cyanellus were collected from watersheds in Montgomery and Polk counties, Arkansas, and their gills, gallbladders, urinary bladders, fins, integument, other major organs, and musculature were examined for myxozoans. Two (5%) L. cyanellus from Polk County were found to harbor a new species of Myxobolus infecting the gill lamellae. A qualitative and quantitative morphological description was based on formalin-fixed preserved plasmodia and myxospores. Plasmodia of Myxobolus polkensis n. sp. are 133 µm long × 123 µm wide, and myxospores are 19.8 µm long × 6.5 µm wide, with two narrowly pyriform unequal polar capsules, one usually longer (9.2 µm) than the other (8.5 µm). Molecular data consisted of a 2,025 base pair sequence of the partial small subunit rRNA gene (SSU). Variably sized, polysporic plasmodia were randomly distributed throughout the gill lamellae in intralamellar locations. Large plasmodia displaced adjacent lamellae inducing mild epithelial proliferation but minimal inflammatory changes. Phylogenetic analysis revealed that M. polkensis n. sp. is a member of a clade of myxozoan species that predominately infect centrarchids from North America. This is the fourth report of a Myxobolus from L. cyanellus but the first report of a species infecting the gill lamellae. This article was registered in the Official Register of Zoological Nomenclature (ZooBank) as urn:lsid:zoobank.org:pub:E9BA08E0-0A7E-487B-80AE-C5C723DBB661.

Resolving the chromatin impact of mosaic variants with targeted Fiber-seq.

Accurately quantifying the functional consequences of noncoding mosaic variants requires the pairing of DNA sequences with both accessible and closed chromatin architectures along individual DNA molecules-a pairing that cannot be achieved using traditional fragmentation-based chromatin assays. We demonstrate that targeted single-molecule chromatin fiber sequencing (Fiber-seq) achieves this, permitting single-molecule, long-read genomic, and epigenomic profiling across targeted >100 kb loci with ∼10-fold enrichment over untargeted sequencing. Targeted Fiber-seq reveals that pathogenic expansions of the DMPK CTG repeat that underlie Myotonic Dystrophy 1 are characterized by somatic instability and disruption of multiple nearby regulatory elements, both of which are repeat length-dependent. Furthermore, we reveal that therapeutic adenine base editing of the segmentally duplicated γ-globin (HBG1/HBG2) promoters in primary human hematopoietic cells induced toward an erythroblast lineage increases the accessibility of the HBG1 promoter as well as neighboring regulatory elements. Overall, we find that these non-protein coding mosaic variants can have complex impacts on chromatin architectures, including extending beyond the regulatory element harboring the variant.

Gene and Its Promoter Cloning, and Functional Validation of JmSOC1 Revealed Its Role in Promoting Early Flowering and the Interaction with the JmSVP Protein.

Juglans mandshurica, a notable woody oil tree species, possesses both fruit and timber value. However, the complete heterodichogamous flowering mechanism in this species remains elusive. SUPPRESSOR OF OVEREXPRESSION OF CONSTANS1 (SOC1) is a crucial regulator of flower bud development in Arabidopsis thaliana. In this study, we cloned the coding DNA sequence (CDS) of the JmSOC1 gene, revealing a 705 base pair (bp) sequence that encodes a protein of 234 amino acids. The JmSOC1 protein contains a highly conserved MADS-box domain, indicating its role as a transcription factor, and is predominantly localized in the nucleus. The JmSOC1 gene expressed the highest in flower buds. The peak expression level of JmSOC1 during the physiological differentiation phase occurred earlier in male flower buds of protandry (MPD) on April 10th compared to female flower buds of protandry (FPD) on April 14th; similarly, the peak expression in female flower buds of protogyny (FPG) on April 2nd preceded that in male flower buds of protogyny (MPG) on April 14th. This may be the primary reason for the earlier differentiation of the male flowers in protandry individuals and the female flowers in protogyny individuals. Overexpression of JmSOC1 in wild-type A. thaliana resulted in earlier flowering, accompanied by an upregulation of key flowering-related genes such as LEAFY (LFY), APETALA1 (AP1), and FLOWERING LOCUS T (FT). To further explore the function of JmSOC1, a 782 bp promoter sequence of JmSOC1 gene was cloned, which has been verified to have promoter activity by GUS staining. Furthermore, the interaction between the JmSOC1 gene promoter and its upstream regulatory protein JmSVP was verified using a yeast one-hybrid. These results offer valuable insights into the molecular mechanisms underpinning the promotion of early flowering in J. mandshurica and hold promise for laying a theoretical foundation for the flowering regulation network of this species.

Molecular features of the serological IgG repertoire elicited by egg-based, cell-based, or recombinant haemagglutinin-based seasonal influenza vaccines: a comparative, prospective, observational, cohort study

Egg-based inactivated quadrivalent seasonal influenza vaccine (eIIV4), cell culture-based inactivated quadrivalent seasonal influenzavaccine (ccIIV4), and recombinant haemagglutinin (HA)-based quadrivalent seasonal influenza vaccine(RIV4) have been licensed for use in the USA. In this study, we used antigen-specific serum proteomics analysis to assess how the molecular composition and qualities of the serological antibody repertoires differ after seasonal influenza immunisation by each of the three vaccines and how different vaccination platforms affect the HA binding affinity and breadth of the serum antibodies that comprise the polyclonal response. In this comparative, prospective, observational cohort study, we included female US health-care personnel (mean age 47·6years [SD 8]) who received a single dose of RIV4, eIIV4, or ccIIV4 during the 2018-19influenza season at Baylor Scott & White Health (Temple, TX, USA). Eligible individuals were selected based on comparable day 28serum microneutralisation titres and similar vaccination history. Laboratory investigators were blinded to assignment untiltesting was completed. The preplanned exploratory endpoints were assessed by deconvoluting the serological repertoire specific to A/Singapore/INFIMH-16-0019/2016 (H3N2) HA before (day 0) and after (day 28) immunisation using bottom-up liquid chromatography-mass spectrometry proteomics (referred to as Ig-Seq) and natively paired variable heavy chain-variable light chain high-throughput B-cell receptor sequencing (referred to as BCR-Seq). Features of the antigen-specific serological repertoire at day 0and day 28for the three vaccine groups were compared. Antibodies identified with high confidence in sera were recombinantly expressed and characterised in depth to determine the binding affinity and breadth to time-ordered H3 HA proteins. During September and October of the 2018-19influenza season, 15individuals were recruited and assigned to receive RIV4 (n=5), eIIV4 (n=5), or ccIIV4 (n=5). For all three cohorts, the serum antibody repertoire was dominated by back-boosted antibody lineages (median 98% [95% CI 88-99]) that were present in the serum before vaccination. Although vaccine platform-dependent differences were not evident in the repertoire diversity, somatic hypermutation, or heavy chain complementarity determining region 3biochemical features, antibodies boosted by RIV4 showed substantially higher binding affinity to the vaccine H3/HA (median half-maximal effective concentration [EC50] to A/Singapore/INFIMH-16-0019/2016 HA: 0·037μg/mL [95% CI 0·012-0·12] for RIV4; 4·43μg/mL [0·030-100·0] for eIIV4; and 18·50μg/mL [0·99-100·0] μg/mL for ccIIV4) and also the HAs from contemporary H3N2 strains than did those elicited by eIIV4 or ccIIV4 (median EC50 to A/Texas/50/2012 HA: 0·037μg/mL [0·017-0·32] for RIV4; 1·10μg/mL [0·045-100] for eIIV4; and 12·6μg/mL [1·8-100] for ccIIV4). Comparison of B-cell receptor sequencing repertoires on day 7showed that eIIV4 increased the median frequency of canonical egg glycan-targeting Bcells (0·20% [95% CI 0·067-0·37] for eIIV4; 0·058% [0·050-0·11] for RIV4; and 0·035% [0-0·062] for ccIIV4), whereas RIV4 vaccination decreased the median frequency of B-cell receptors displaying stereotypical features associated with membrane proximal anchor-targeting antibodies (0·062% [95% CI 0-0·084] for RIV4; 0·12% [0·066-0·16] for eIIV4; and 0·18% [0·016-0·20] for ccIIV4). In exploratory analysis, we characterised the structure of a highly abundant monoclonal antibody that binds to both group 1and 2HAs and recognises the HA trimer interface, despite its sequence resembling the stereotypical sequence motif found in membrane-proximal anchor binding antibodies. Although all three licensed seasonal influenza vaccines elicit serological antibody repertoires with indistinguishable features shaped by heavy imprinting, the RIV4 vaccine selectively boosts higher affinity monoclonal antibodies to contemporary strains and elicits greater serum binding potency and breadth, possibly as a consequence of the multivalent structural features of the HA immunogen in this vaccine formulation. Collectively, our findings show advantages of RIV4 vaccines and more generally highlight the benefits of multivalent HA immunogens in promoting higher affinity serum antibody responses. Centers for Disease Control and Prevention, National Institutes of Health, and Bill & Melinda Gates Foundation.

AntiBody Sequence Database.

Antibodies play a crucial role in the humoral immune response against health threats, such as viral infections. Although the theoretical number of human immunoglobulins is well over a trillion, the total number of unique antibody protein sequences accessible in databases is much lower than the number found in a single individual. Training AI (Artificial Intelligence) models, for exampleto assist in developing serodiagnoses or antibody-based therapies, requires building datasets according to strict criteria to include as many standardized antibody sequences as possible. However, the available sequences are scattered across partially redundant databases, making it difficult to compile them into single non-redundant datasets. Here, we introduce ABSD (AntiBody Sequence Database, https://absd.pasteur.cloud), which contains data from major publicly available resources, creating the largest standardized, automatically updated and non-redundant source of public antibody sequences. This user-friendly and open website enables users to generate lists of antibodies based on selected criteria and download the unique sequence pairs of their variable regions.

Genome-wide maps of highly-similar intrachromosomal repeats that can mediate ectopic recombination in three human genome assemblies.

Repeated sequences spread throughout the genome play important roles in shaping the structure of chromosomes and facilitating the generation of new genomic variation through structural rearrangements. Several mechanisms of structural variation formation use shared nucleotide similarity between repeated sequences as substrate for ectopic recombination. We performed genome-wide analyses of direct and inverted intrachromosomal repeated sequence pairs with >200bp and >80% sequence identity in three human genome assemblies, GRCh37, GRCh38, and the T2T-CHM13 alternate assembly. Overall, the composition and distribution of direct and inverted repeats identified was similar among the three assemblies involving 13-15% of the haploid genome, with an increased, albeit not significant, number of repeated sequences in T2T-CHM13. Interestingly, the majority of repeated sequences are below 1 Kb in length with a median of 84.2% identity, highlighting the potential relevance of smaller, less identical repeats, such as Alu-Alu pairs, for ectopic recombination. We cross-referenced the identified repeated sequences with protein-coding genes to identify those at risk for being involved in genomic disorders. Olfactory receptors and immune response genes were enriched among those impacted. We have produced a catalog of highly-identical directly and inversely oriented intrachromosomal repeated sequences across the currently three most widely used human genome assemblies. Bioinformatic analyses of these sequences and their contribution to genome architecture can reveal regions that are susceptible to genomic instability. Understanding how their architectural genomic features such as identity, length, and distance can lead to genomic rearrangements can provide further insights into the molecular mechanisms leading to genomic disorders and genome evolution.

Doppler resilient MIMO radar waveform design from zero correlation zone complementary sequence pairs

The aperiodic auto-correlation sum of Golay complementary pair (GCP) is zero at all non-zero delay, which makes Golay complementary pair have good performance in radar systems. In the literature, GCPs have been widely used in single user (or single antenna) radar system in which waveforms with only good auto-correlation are considered. While in the multi-user (or MIMO) scenario, radar waveforms with both good auto-correlation and cross-correlation are desired to eliminate mutual interference in target detection. To address this issue, constructions of waveforms with both good auto-ambiguity property and cross-ambiguity property are proposed based on zero correlation zone complementary pair (ZCP) sets. The simulation results show that the proposed waveform set perform as well as Golay complementary waveforms in target detection.