Pairs Of Sequences Research Articles

The symmetric 2-adic complexity of Tang-Gong interleaved sequences from Legendre sequence pair

The symmetric 2-adic complexity of Tang-Gong interleaved sequences from Legendre sequence pair

Comparative Analyses of the Complete Mitogenomes of Two Oxyria Species (Polygonaceae) Provide Insights into Understanding the Mitogenome Evolution Within the Family

Oxyria (Polygonaceae) is a small genus only comprising two species, Oxyria digyna and O. sinensis. Both species have well-documented usage in Chinese herbal medicine. We sequenced and assembled the complete mitogenomes of these two species and conducted a comparative analysis of the mitogenomes within Polygonaceae. Both O. digyna and O. sinensis displayed distinctive multi-branched conformations, consisting of one linear and one circular molecule. These two species shared similar gene compositions and exhibited distinct codon preferences, with mononucleotides as the most abundant type of simple sequence repeats. In the mitogenome of O. sinensis, a pair of long forward repeat sequences can mediate the division of molecule 1 into two sub-genomic circular molecules. Homologous sequence analysis revealed the occurrence of gene transfer between the chloroplast and mitochondrial genomes within Oxyria species. Additionally, a substantial number of homologous collinear blocks with varied arrangements were observed across different Polygonaceae species. Phylogenetic analysis suggested that mitogenome genes can serve as reliable markers for constructing phylogenetic relationships within Polygonaceae. Comparative analysis of eight species revealed Polygonaceae mitogenomes exhibited variability in gene presence, and most protein-coding genes (PCGs) have undergone negative selection. Overall, our study provided a comprehensive overview of the structural, functional, and evolutionary characteristics of the Polygonaceae mitogenomes.

Enzyme-Assisted Fluorescence Biosensor Based on Circular Single-Stranded DNA Without Group Modification for MicroRNA Detection

Fluorescent biosensor, which has the characteristics of high sensitivity, specificity, and low cost, can be directly detected in physiological fluids such as blood and serum. Therefore, the development of fluorescence sensor platforms for miRNA detection has a positive effect on the prevention and treatment of various diseases. In this paper, miR-34a was selected as a biological indicator of Alzheimer’s disease (AD). We designed a circular single-stranded DNA (CSSD) biosensor, which uses two unmodified single-stranded DNA (ssDNA) with complementary ends, DNAa and DNAb, to form CSSD by DNA sequence pairing to improve thermal stability and achieve signal amplification. At the same time, CSSD can react with miR-34a, and then the DNA of the DNA–RNA chain is hydrolyzed by duplex-specific nuclease (DSN enzyme). Finally, miR-34a is released to partake in the subsequent step, thus realizing cycle amplification. By evaluating the change in fluorescence signal under the optimized conditions, we discovered that this approach exhibits impressive sensitivity, with a detection threshold reaching as low as 0.36 nM. This surpasses the performance of numerous preceding miRNA detection biosensors. Furthermore, the system displays excellent detection capabilities even in intricate settings like serum, showcasing a strong ability to differentiate and choose effectively. In summary, this is a signal-off fluorescent biosensor, which realizes the purpose of double amplification of biosensor signal by using CSSD and enzyme assistance so that it can be used as a valuable tool for early diagnosis of diseases.

Paired single-cell RNA sequencing and T cell receptor sequencing reveals both pro- and anti-inflammatory roles of T cells in patients with calcific aortic valve disease

Abstract Background Calcified aortic valve disease (CAVD) is a chronic unresolvable inflammatory disorder that affects 25% of adults over 65 years old, leading to aortic stenosis, heart failure, and death [1]. Since the molecular mechanisms of its pathogenesis are not well understood, therapies to treat root causes of the disease remain to be developed, with valve replacement as the major intervention strategy currently. Increasing evidence indicates that substantial T cells infiltrate in the aortic valve during calcification, and clonal expanded CD8+ T cells have been identified in the calcificed aortic valve by bulk T cell receptor (TCR) repertoire sequencing [2]. Purpose To decipher T cell heterogenity and understand the precise mechanisms of T cell subsets involving CAVD progression as a basis for novel therapeutic targets. Methods In Cohort 1, we collected aortic valves from CAVD (n=3) and healthy (n=2) patients for single-cell RNA sequencing (scRNA-seq). In Cohort 2, we performed paired scRNA-seq and TCR sequencing (scTCR-seq) on aortic valves obtained from CAVD (n=3) and healthy (n=3) patients to evaluate both gene expression and clonality. Pathway enrichment analysis and cell-cell interaction analysis elucidated the function of T cells in the calcificied valves. Immunohistochemistry and fluorescence-activated cell sorting were recruited to verify the key findings. Results scRNA-seq demonstrated a conversion from anti-inflammatory regulatory T (Treg) cells towards pro-inflammatory T helper 17 (Th17) cells in the calcificied aortic valve. Paired scRNA-seq and scTCR-seq revealed CAVD-related signaling pathways (osteoclast differentiation, NOD-like receptor signaling pathways, IL-17 signaling pathways) significantly upregulated in highly expanded CD8+ T cells in the calcified valve, with upregulation of pro-inflammatory mediators such as IFNG, CCL4 and CCL5, suggesting pro-inflammation functions in clonally expanded T cells. Moreover, we characterized tissue-resident memory T cells, which resembled similar transcriptome and TCR clonality as exhausted T cells in calcified valves. These cells up-regulated anti-inflammation-related transcriptomes but their cellular fraction decreased in calcified valves, implying anti-inflammatory functions of these tissue-resident memory and exhausted T cells. Conclusion This study elucidates transcriptomic and immune profiling of T cells in the calcified aortic valve, therefore shedding light on the pathophysiological mechanisms underlying aortic valve calcification from the novel perspective of tissue-specific T lymphocytes, providing promising targets for immune checkpoint-based therapeutic interventions.

Overloading And unpacKing (OAK) - droplet-based combinatorial indexing for ultra-high throughput single-cell multiomic profiling

Multiomic profiling of single cells by sequencing is a powerful technique for investigating cellular diversity. Existing droplet-based microfluidic methods produce many cell-free droplets, underutilizing bead barcodes and reagents. Combinatorial indexing on microplates is more efficient for barcoding but labor-intensive. Here we present Overloading And unpacKing (OAK), which uses a droplet-based barcoding system for initial compartmentalization followed by a second aliquoting round to achieve combinatorial indexing. We demonstrate OAK’s versatility with single-cell RNA sequencing as well as paired single-nucleus RNA sequencing and accessible chromatin profiling. We further showcase OAK’s performance on complex samples, including differentiated bronchial epithelial cells and primary retinal tissue. Finally, we examine transcriptomic responses of over 400,000 melanoma cells to a RAF inhibitor, belvarafenib, discovering a rare resistant cell population (0.12%). OAK’s ultra-high throughput, broad compatibility, high sensitivity, and simplified procedures make it a powerful tool for large-scale molecular analysis, even for rare cells.

The brain hierarchically represents the past and future during multistep anticipation

Memory for temporal structure enables both planning of future events and retrospection of past events. We investigated how the brain flexibly represents extended temporal sequences into the past and future during anticipation. Participants learned sequences of environments in immersive virtual reality. Pairs of sequences had the same environments in a different order, enabling context-specific learning. During fMRI, participants anticipated upcoming environments multiple steps into the future in a given sequence. Temporal structure was represented in the hippocampus and across higher-order visual regions (1) bidirectionally, with graded representations into the past and future and (2) hierarchically, with further events into the past and future represented in successively more anterior brain regions. In hippocampus, these bidirectional representations were context-specific, and suppression of far-away environments predicted response time costs in anticipation. Together, this work sheds light on how we flexibly represent sequential structure to enable planning over multiple timescales.

The complete mitochondrial genome of Castanopsis carlesii and Castanea henryi reveals the rearrangement and size differences of mitochondrial DNA molecules

BackgroundCastanopsis carlesii is a dominant tree species in subtropical evergreen broad-leaved forests and holds significant ecological value. It serves as an excellent timber tree species and raw material for cultivating edible fungi. Henry Chinquapin (Castanea henryi) wood is known for its hardness and resistance to water and moisture, making it an exceptional timber species. Additionally, its fruit has a sweet and fruity taste, making it a valuable food source. However, the mitogenomes of these species have not been previously reported. To gain a better understanding of them, this study successfully assembled high-quality mitogenomes of C. carlesii and Ca. henryi for the first time.ResultsOur research reveals that the mitochondrial DNA (mtDNA) of C. carlesii exhibits a unique multi-branched conformation, while Ca. henryi primarily exists in the form of two independent molecules that can be further divided into three independent molecules through one pair of long repetitive sequences. The size of the mitogenomes of C. carlesii and Ca. henryi are 592,702 bp and 379,929 bp respectively, which are currently the largest and smallest Fagaceae mitogenomes recorded thus far. The primary factor influencing mitogenome size is dispersed repeats. Comparison with published mitogenomes from closely related species highlights differences in size, gene loss patterns, codon usage preferences, repetitive sequences, as well as mitochondrial plastid DNA segments (MTPTs).ConclusionsOur study enhances the understanding of mitogenome structure and evolution in Fagaceae, laying a crucial foundation for future research on cell respiration, disease resistance, and other traits in this family.

Optical manipulation of spin states in ultracold magnetic atoms via an inner-shell hz transition

Lanthanides, like erbium and dysprosium, have emerged as powerful platforms for quantum-gas research due to their diverse properties, including a significant large spin manifold in their absolute ground state. However, effectively exploiting the spin richness necessitates precise manipulation of spin populations, a challenge yet to be fully addressed in this class of atomic species. In this work, we present an all-optical method for deterministically controlling the spin composition of a dipolar bosonic erbium gas, based on a clocklike transition in the telecom window at 1299nm. The atoms can be prepared in just a few tens of microseconds in any spin-state composition using a sequence of Rabi-pulse pairs, selectively coupling Zeeman sublevels of the ground state with those of the long-lived clocklike state. Finally, we demonstrate that this transition can also be used to create spin-selective light shifts, thus fully suppressing spin-exchange collisions. These experimental results unlock exciting possibilities for implementing advanced spin models in isolated, clean, and fully controllable lattice systems. Published by the American Physical Society 2024

Ultrasensitive detection of circulating tumor DNA using a CRISPR/Cas9 nickase-driven 3D DNA walker based on a COF-AuNPs sensing platform.

Aelectrochemical biosensor was designedutilizing a CRISPR Cas9n-driven DNA walker combined with gold-nanosphere-like covalent organic frameworks (COFs-AuNPs) to detect breast cancer markers (PIK3CA E545K ctDNA). The DNA walker probe is activated only in the presence of circulating tumor deoxyribonucleic acid(ctDNA), binding to a support probe to form a double strand that is then specifically cleaved by the Cas9n/sgRNA complex. This cleavage produces numerous DNA fragments for signal amplification. The COF-AuNPs as electrode materials facilitate electronic transfer and provide additional active sites for the immobilization of nucleic acid probes. This setup achieves a detection limit of 1.76 aM, demonstrating high sensitivity. Additionally, Cas9n improves the specificity of the sensor, accurately distinguishing a pair of base-mismatched sequences, and reducing the occurrence of false positives. Overall, the sensor exhibits excellent selectivity, reproducibility, and potential for early diagnosis of breast cancer.

Single-Cell Antigen Receptor Sequencing in Pigs with Influenza.

Understanding the pulmonary adaptive immune system of pigs is important as respiratory pathogens present a major challenge for swine producers and pigs are increasingly used to model human pulmonary diseases. Single-cell RNA sequencing (scRNAseq) has accelerated the characterization of cellular phenotypes in the pig respiratory tract under both healthy and diseased conditions. However, combining scRNAseq with recovery of paired T cell receptor (TCR) α and β chains as well as B cell receptor (BCR) heavy and light chains to interrogate their repertoires has not to our knowledge been demonstrated for pigs. Here, we developed primers to enrich porcine TCR α and β chains along with BCR κ and λ light chains and IgM, IgA, and IgG heavy chains that are compatible with the 10x Genomics VDJ sequencing protocol. Using these pig-specific assays, we sequenced the T and B cell receptors of cryopreserved lung cells from CD1D -expressing and -deficient pigs after one or two infections with influenza A virus (IAV) to examine whether natural killer T (NKT) cells alter pulmonary TCR and BCR repertoire selection. We also performed paired single-cell RNA and receptor sequencing of FACS-sorted T cells longitudinally sampled from the lungs of IAV-vaccinated and -infected pigs to track clonal expansion in response to IAV exposure. All pigs presented highly diverse repertoires. Pigs re-exposed to influenza antigens from either vaccination or infection exhibited higher numbers of expanded CD4 and CD8 T cell clonotypes with activated phenotypes, suggesting potential IAV reactive T cell populations. Our results demonstrate the utility of high throughput single-cell TCR and BCR sequencing in pigs.

Concordance in the estimation of tumor percentage in non-small cell lung cancer using digital pathology

The incorporation of digital pathology in clinical practice will require the training of pathologists in digital skills. Our study aimed to assess the reliability among pathologists in determining tumor percentage in whole slide images (WSI) of non-small cell lung cancer (NSCLC) using digital image analysis, and study how the results correlate with the molecular findings. Pathologists from nine centers were trained to quantify epithelial tumor cells, tumor-associated stromal cells, and non-neoplastic cells from NSCLC WSI using QuPath. Then, we conducted two consecutive ring trials. In the first trial, analyzing four WSI, reliability between pathologists in the assessment of tumor cell percentage was poor (intraclass correlation coefficient (ICC) 0.09). After performing the first ring trial pathologists received feedback. The second trial, comprising 10 WSI with paired next-generation sequencing results, also showed poor reliability (ICC 0.24). Cases near the recommended 20% visual threshold for molecular techniques exhibited higher values with digital analysis. In the second ring trial reliability slightly improved and human errors were reduced from 5.6% to 1.25%. Most discrepancies arose from subjective tasks, such as the annotation process, suggesting potential improvement with future artificial intelligence solutions.

Crispr-SGRU: Prediction of CRISPR/Cas9 Off-Target Activities with Mismatches and Indels Using Stacked BiGRU

CRISPR/Cas9 is a popular genome editing technology, yet its clinical application is hindered by off-target effects. Many deep learning-based methods are available for off-target prediction. However, few can predict off-target activities with insertions or deletions (indels) between single guide RNA and DNA sequence pairs. Additionally, the analysis of off-target data is challenged due to a data imbalance issue. Moreover, the prediction accuracy and interpretability remain to be improved. Here, we introduce a deep learning-based framework, named Crispr-SGRU, to predict off-target activities with mismatches and indels. This model is based on Inception and stacked BiGRU. It adopts a dice loss function to solve the inherent imbalance issue. Experimental results show our model outperforms existing methods for off-target prediction in terms of accuracy and robustness. Finally, we study the interpretability of this model through Deep SHAP and teacher–student-based knowledge distillation, and find it can provide meaningful explanations for sequence patterns regarding off-target activity.

The Complete Chloroplast Genome of Meconopsis simplicifolia and Its Genetic Comparison to Other Meconopsis Species.

Background: Chloroplasts, due to their high conservation and lack of recombination, serve as important genetic resources for the classification and evolutionary analysis of closely related species that are difficult to distinguish based on their morphological features. Meconopsis simplicifolia (M. simplicifolia), an endangered herb within the Meconopsis genus, has demonstrated therapeutic potential in treating various diseases. However, the highly polymorphic morphology of this species poses a challenge for accurate identification. Methods: In this study, the complete chloroplast genome of M. simplicifolia was sequenced and assembled using Illumina sequencing technology. Simple sequence repeats (SSRs) and repetitive sequences were characterized. In addition, a comparative analysis was conducted with the chloroplast genomes of six other Meconopsis species. Results: The chloroplast genome of M. simplicifolia has a quadripartite circular structure with a total length of 152,772 bp. It consists of a large single-copy region of 83,824 bp and a small single-copy region of 17,646 bp, separated by a pair of inverted repeat sequences (IRa and IRb, 25,651 bp). The genome contains 131 genes, 33 SSRs, and 27 long repetitive sequences. Comparative analysis with six other chloroplast genomes of Meconopsis revealed that M. simplicifolia is closely related to M. betonicifolia and that the rpl2 (ribosomal protein L2) gene in the IRb region has been deleted. This deletion is of significant importance for future taxonomic studies of M. simplicifolia. Conclusions: This study provides a valuable reference for the identification of M. simplicifolia and contributes to a deeper understanding of the phylogeny and evolution of the Meconopsis genus.

Enhancing subjective spaciousness for stereo reproduction in car-size acoustical enclosures based on audio signal decorrelation

Audio signal decorrelation has been used for enhancing the spaciousness of auditory source width (ASW) in a stereo reproduction. However, the acoustic environment in car-size acoustical enclosures is quite different from that in a home theater or listening room. Due to the small cabin size and the substantial presence of absorptive surfaces, the reproduced sound field in car-size acoustical enclosures is characterized by the interior mode region up to some hundreds or one thousand hertz and fast decay of pressure at higher frequencies which could affect the perceived performance of audio signal decorrelation. Therefore, the present work evaluates the effect of reflections in an acoustical enclosure model with car-size on the ASW enhanced by decorrelated audio signals, which reproduced by a standard stereo system. The decorrelation algorithm is handled by all-pass filters sets based on a pair of reciprocal maximal length sequence (MLS). Last, a subjective assessment experiment of ASW validates that appropriate decorrelation method can improve perceived spaciousness for sound reproduction in car-size acoustical enclosures.

Learning placement order for constructive floorplanning

Floorplanning is an early and essential task of physical design. Recently, there has been a surge in the application of learning-based methods to tackle floorplanning problem. A prevalent approach involves training a reinforcement learning (RL) agent to sequentially place blocks on a chip canvas. However, existing methods mainly focus on learning block placement, relying on heuristic rules for placement order determination. In contrast to previous approaches, we propose an RL-based method to determine the placement order. Based on block features and states, an agent is trained to select the block for placement. Once a block is selected, we enumerate all potential relative positions captured by sequence pairs and select the optimal placement. After establishing the layout topology, we further optimize wirelength through linear programming. Experimental results demonstrate the effectiveness of our proposed method. On the original-outline MCNC benchmarks, our method achieves a notable 25.2% average improvement in wirelength compared to a recent learning-based method. Additionally, when applied to rescaled-outline benchmarks from MCNC and GSRC, our method outperforms state-of-the-art results, resulting in an average wirelength reduction of 12.5%.

Prediction and functional interpretation of inter-chromosomal genome architecture from DNA sequence with TwinC.

Three-dimensional nuclear DNA architecture comprises well-studied intra-chromosomal (cis) folding and less characterized inter-chromosomal (trans) interfaces. Current predictive models of 3D genome folding can effectively infer pairwise cis-chromatin interactions from the primary DNA sequence but generally ignore trans contacts. There is an unmet need for robust models of trans-genome organization that provide insights into their underlying principles and functional relevance. We present TwinC, an interpretable convolutional neural network model that reliably predicts trans contacts measurable through genome-wide chromatin conformation capture (Hi-C). TwinC uses a paired sequence design from replicate Hi-C experiments to learn single base pair relevance in trans interactions across two stretches of DNA. The method achieves high predictive accuracy (AUROC=0.80) on a cross-chromosomal test set from Hi-C experiments in heart tissue. Mechanistically, the neural network learns the importance of compartments, chromatin accessibility, clustered transcription factor binding and G-quadruplexes in forming trans contacts. In summary, TwinC models and interprets trans genome architecture, shedding light on this poorly understood aspect of gene regulation.

TIRTL-seq: Deep, quantitative, and affordable paired TCR repertoire sequencing.

α/β T cells are key players in adaptive immunity. The specificity of T cells is determined by the sequences of the hypervariable T cell receptor (TCR) α and β chains. Although bulk TCR sequencing offers a cost-effective approach for in-depth TCR repertoire profiling, it does not provide chain pairings, which are essential for determining T cell specificity. In contrast, single-cell TCR sequencing technologies produce paired chain data, but are limited in throughput to thousands of cells and are cost-prohibitive for cohort-scale studies. Here, we present TIRTL-seq (Throughput-Intensive Rapid TCR Library sequencing), a novel approach that generates ready-to-sequence TCR libraries from live cells in less than 7 hours. The protocol is optimized for use with non-contact liquid handlers in an automation-friendly 384-well plate format. Reaction volume miniaturization reduces library preparation costs to <$0.50 per well. The core principle of TIRTL-seq is the parallel generation of hundreds of libraries providing multiple biological replicates from a single sample that allows precise inference of both frequencies of individual clones and TCR chain pairings from well-occurrence patterns. We demonstrate scalability of our approach up to 1 million unique paired αβTCR clonotypes corresponding to over 30 million T cells per sample at a cost of less than $2000. For a sample of 10 million cells the cost is ~$200. We benchmarked TIRTL-seq against state-of-the-art 5'RACE bulk TCR-seq and 10x Genomics Chromium technologies on longitudinal samples. We show that TIRTL-seq is able to quantitatively identify expanding and contracting clonotypes between timepoints while providing accurate TCR chain pairings, including distinct temporal dynamics of SARS-CoV-2-specific and EBV-specific CD8+ T cell responses after infection. While clonal expansion was followed by sharp contraction for SARS-CoV-2 specific TCRs, EBV-specific TCRs remained stable once established. The sequences of both α and β TCR chains are essential for determining T cell specificity. As the field moves towards greater applications in diagnostics and immunotherapy that rely on TCR specificity, we anticipate that our scalable paired TCR sequencing methodology will be instrumental for collecting large paired-chain datasets and ultimately extracting therapeutically relevant information from the TCR repertoire.

Abstract C117: Integrative multi-omics profiling in patients of African descent diagnosed with prostate cancer reveals distinct tumor-promoting immunosuppressive niches at a single-cell level and spatial resolution

Abstract In the United States and globally, prostate cancer (PCa) mortality rates are the highest among men of African descent. 24% of the disparities in PCa remains even when controlled for access to care and stage at presentation. Moreover, the tumor microenvironment plays an essential role in tumor progression, aggressiveness, therapeutic response, and patient outcomes. Additionally, the association of the genomic findings with patient ancestry and other characteristics, such as tumor biology and transcriptomic alterations, remains poorly understood. Here, we performed a multi-Omics approach (N=447) to unravel the complexity of tumor heterogeneity and understand disease progression &amp; distinct tumor biology influenced by genetic ancestry. We performed Whole Exome (Normal/tumor paired) Sequencing matched with Methyl Seq and Whole transcriptomic Sequencing for three datasets of our African, African American Men (AAM), and European Men (EAM). Additionally, we ran Spatial NanoString high-plex GeoMx-DSP for a total of 118 treatment-naive PCa patients (around 500 ROIs). Simultaneously, we added matched whole transcriptome Sequencing for these patients. The cohort comprised 87 AAM, 3 unknown, and 28 EAM self-reported individuals. To verify the self-reported race, the genomic ancestry was qualified using genotype and Admixture analysis. To further validate differentially expressed genes at the protein level, we performed multi-plex histological staining of 40 markers to determine the spatial resolution and neighborhood clustering within the tumor and the microenvironment. In parallel, we performed scMultiOmics sequencing (scRNA &amp; scATAC-Seq) at a single-cell resolution (6000 cells/sample at 25K reads per cell) from an additional 12 patients (9 AAM &amp; 3 EAM). We reconstructed a 3D model of the distinct tumor microenvironment at subcellular resolution using serially sectioned hematoxylin and eosin- stained tissue sections (CODA technology). Our results demonstrate that patients who self-report as AAM or Nigerian are assigned to high African (&amp;gt; 70%) Ancestry with either Yoruba (Nigeria) and/or Bantu subpopulation in the Sub-Saharan area. Additionally, high African Ancestry patients are diagnosed at a younger age and show advanced pathology stages compared to patients with European Ancestry. AAM of Yoruba descent expresses significantly higher immune-inflammatory signatures (STAT/IFNG-signaling pathway) compared to the Nigerian-Yoruba subpopulation. Our scRNA-Seq analysis shows that AAM has suppressive myeloid cells infiltrate within the tumor cells. The infiltrations of these cells change with age, Gleason Grade, and pathology stage. Moreover, AAM-tumor cells (scATAC-Seq) have increased open Chromatin accessibility with STAT motifs enrichment (p-value;0.0001), which could be the driver regulators of the immune-suppressive signature as well as influence the upregulation of STAT/IFNG signature within African Ancestry patients. Our study provides new insight into how genetic ancestry impacts immune signatures in AAM/African and contributes to PCa racial disparities. Citation Format: Isra Elhussin, Ezra Baraban1, Ashley Kiemen, Tamara L Lotan, Cathy Handy Marshall, Emmanuel Antonarakis, Moray J Campbell, Melissa Davis, Michael Dixon, Isaac Kim, Stefan Ambs, Rick Kittles, Adam B Murphy, Clayton Yates. Integrative multi-omics profiling in patients of African descent diagnosed with prostate cancer reveals distinct tumor-promoting immunosuppressive niches at a single-cell level and spatial resolution [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr C117.

A content analysis of parents' reflections on pathogenic and uncertain pediatric oncology germline sequencing results.

Germline genomic sequencing is increasingly integrated into pediatric cancer care, with pathogenic cancer-predisposing variants identified among 5-18% of affected children and variants of uncertain significance (VUS) in up to 70%. Given the potential medical implications for children and their families, parents' psychosocial responses to learning results are important to understand. Parents of children with cancer who learned their children's germline pathogenic or VUS results following paired tumor and germline genomic sequencing described their cognitive and affective responses to results in an open-ended write-in question after disclosure (M = 10 months post-disclosure; range = 1-28). Responses were coded and categorized using content analysis, then compared across results using chi-square and Fisher's exact test. Parents of children with pathogenic (n = 9), VUS (n = 52), and pathogenic plus VUS results (n = 9) described negative emotions, positive reactions, mixed emotions (i.e., positive and negative emotions), and neutral reactions. Negative emotions were described significantly more frequently with pathogenic results than VUS only (χ2 = 5.19; p = .02), with peace of mind and empowerment only described for those with VUS. Parents also described approach(es) to coping (e.g., faith, plan of action) and reactions specific to the uncertainty of VUS (e.g., disappointment at no explanation for cancer etiology). A subset with VUS described decreasing worry/distress with increased understanding of results, whereas others displayed misconceptions regarding VUS. Screening for emotional adjustment is warranted for parents of children with cancer receiving pathogenic germline results, and screening for understanding is warranted with VUS. Findings highlight the importance of pre-and posttest genetic counseling.

Local adaptation can cause both peaks and troughs in nucleotide diversity within populations.

The amount of standing variation present within populations is a fundamental quantity of interest in population genetics, commonly represented by calculating the average number of differences between pairs of nucleotide sequences (nucleotide diversity, π). It is well understood that both background and positive selection can cause reductions in nucleotide diversity, but less clear how local adaptation affects it. Depending on the assumptions and parameters, some theoretical studies have emphasized how local adaptation can reduce nucleotide diversity, while others have shown that it can increase it. Here, we explore how local adaptation shapes genome-wide patterns in within-population nucleotide diversity, extending previous work to study the effects of polygenic adaptation, genotypic redundancy, and population structure. We show that local adaptation produces two very different patterns depending on the relative strengths of migration and selection, either markedly decreasing or increasing within-population diversity at linked sites at equilibrium. At low migration, regions of depleted diversity can extend large distances from the causal locus, with substantially more diversity eroded than expected with background selection. With higher migration, peaks occur over much smaller genomic distances but with much larger magnitude changes in diversity. Across spatially extended environmental gradients, both patterns can be found within a single species, with increases in diversity at the center of the range and decreases towards the periphery. Our results demonstrate that there is no universal diagnostic signature of local adaptation based on within-population nucleotide diversity, so it will not be broadly useful for explaining increased FST. However, given that neither background nor positive selection inflate diversity, when peaks are found they suggest local adaptation may be acting on a causal allele in the region.