KmerKeys: a web resource for searching indexed genome assemblies and variants.

K-mers are short DNA sequences that are used for genome sequence analysis. Applications that use k-mers include genome assembly and alignment. However, the wider bioinformatic use of these short sequences has challenges related to the massive scale of genomic sequence data. A single human genome assembly has billions of k-mers. As a result, the computational requirements for analyzing k-mer information is enormous, particularly when involving complete genome assemblies. To address these issues, we developed a new indexing data structure based on a hash table tuned for the lookup of short sequence keys. This web application, referred to as KmerKeys, provides performant, rapid query speeds for cloud computation on genome assemblies. We enable fuzzy as well as exact sequence searches of assemblies. To enable robust and speedy performance, the website implements cache-friendly hash tables, memory mapping and massive parallel processing. Our method employs a scalable and efficient data structure that can be used to jointly index and search a large collection of human genome assembly information. One can include variant databases and their associated metadata such as the gnomAD population variant catalogue. This feature enables the incorporation of future genomic information into sequencing analysis. KmerKeys is freely accessible at https://kmerkeys.dgi-stanford.org.

Implementation of Nanopore sequencing as a pragmatic workflow for copy number variant confirmation in the clinic.

BACKGROUND: Diagnosis of rare genetic diseases can be a long, expensive and complex process, involving an array of tests in the hope of obtaining an actionable result. Long-read sequencing platforms offer the opportunity to make definitive molecular diagnoses using a single assay capable of detecting variants, characterizing methylation patterns, resolving complex rearrangements, and assigning findings to long-range haplotypes. Here, we demonstrate the clinical utility of Nanopore long-read sequencing by validating a confirmatory test for copy number variants (CNVs) in neurodevelopmental disorders and illustrate the broader applications of this platform to assess genomic features with significant clinical implications. METHODS: We used adaptive sampling on the Oxford Nanopore platform to sequence 25 genomic DNA samples and 5 blood samples collected from patients with known or false-positive copy number changes originally detected using short-read sequencing. Across the 30 samples (a total of 50 with replicates), we assayed 35 known unique CNVs (a total of 55 with replicates) and one false-positive CNV, ranging in size from 40 kb to 155 Mb, and assessed the presence or absence of suspected CNVs using normalized read depth. RESULTS: Across 50 samples (including replicates) sequenced on individual MinION flow cells, we achieved an average on-target mean depth of 9.5X and an average on-target read length of 4805 bp. Using a custom read depth-based analysis, we successfully confirmed the presence of all 55 known CNVs (including replicates) and the absence of one false-positive CNV. Using the same CNV-targeted data, we compared genotypes of single nucleotide variant loci to verify that no sample mix-ups occurred between assays. For one case, we also used methylation detection and phasing to investigate the parental origin of a 15q11.2-q13 duplication with implications for clinical prognosis. CONCLUSIONS: We present an assay that efficiently targets genomic regions to confirm clinically relevant CNVs with a concordance rate of 100%. Furthermore, we demonstrate how integration of genotype, methylation, and phasing data from the Nanopore sequencing platform can potentially simplify and shorten the diagnostic odyssey.

Comprehensive, integrated, and phased whole-genome analysis of the primary ENCODE cell line K562.

K562 is widely used in biomedical research. It is one of three tier-one cell lines of ENCODE and also most commonly used for large-scale CRISPR/Cas9 screens. Although its functional genomic and epigenomic characteristics have been extensively studied, its genome sequence and genomic structural features have never been comprehensively analyzed. Such information is essential for the correct interpretation and understanding of the vast troves of existing functional genomics and epigenomics data for K562. We performed and integrated deep-coverage whole-genome (short-insert), mate-pair, and linked-read sequencing as well as karyotyping and array CGH analysis to identify a wide spectrum of genome characteristics in K562: copy numbers (CN) of aneuploid chromosome segments at high-resolution, SNVs and indels (both corrected for CN in aneuploid regions), loss of heterozygosity, megabase-scale phased haplotypes often spanning entire chromosome arms, structural variants (SVs), including small and large-scale complex SVs and nonreference retrotransposon insertions. Many SVs were phased, assembled, and experimentally validated. We identified multiple allele-specific deletions and duplications within the tumor suppressor gene FHIT Taking aneuploidy into account, we reanalyzed K562 RNA-seq and whole-genome bisulfite sequencing data for allele-specific expression and allele-specific DNA methylation. We also show examples of how deeper insights into regulatory complexity are gained by integrating genomic variant information and structural context with functional genomics and epigenomics data. Furthermore, using K562 haplotype information, we produced an allele-specific CRISPR targeting map. This comprehensive whole-genome analysis serves as a resource for future studies that utilize K562 as well as a framework for the analysis of other cancer genomes.

The sleep-deprived human brain.

How does a lack of sleep affect our brains? In contrast to the benefits of sleep, frameworks exploring the impact of sleep loss are relatively lacking. Importantly, the effects of sleep deprivation (SD) do not simply reflect the absence of sleep and the benefits attributed to it; rather, they reflect the consequences of several additional factors, including extended wakefulness. With a focus on neuroimaging studies, we review the consequences of SD on attention and working memory, positive and negative emotion, and hippocampal learning. We explore how this evidence informs our mechanistic understanding of the known changes in cognition and emotion associated with SD, and the insights it provides regarding clinical conditions associated with sleep disruption.

Single-cell RNA-Seq of follicular lymphoma reveals malignant B-cell types and coexpression of T-cell immune checkpoints.

Follicular lymphoma (FL) is a low-grade B-cell malignancy that transforms into a highly aggressive and lethal disease at a rate of 2% per year. Perfect isolation of the malignant B-cell population from a surgical biopsy is a significant challenge, masking important FL biology, such as immune checkpoint coexpression patterns. To resolve the underlying transcriptional networks of follicular B-cell lymphomas, we analyzed the transcriptomes of 34 188 cells derived from 6 primary FL tumors. For each tumor, we identified normal immune subpopulations and malignant B cells, based on gene expression. We used multicolor flow cytometry analysis of the same tumors to confirm our assignments of cellular lineages and validate our predictions of expressed proteins. Comparison of gene expression between matched malignant and normal B cells from the same patient revealed tumor-specific features. Malignant B cells exhibited restricted immunoglobulin (Ig) light chain expression (either Igκ or Igλ), as well the expected upregulation of the BCL2 gene, but also downregulation of the FCER2, CD52, and major histocompatibility complex class II genes. By analyzing thousands of individual cells per patient tumor, we identified the mosaic of malignant B-cell subclones that coexist within a FL and examined the characteristics of tumor-infiltrating T cells. We identified genes coexpressed with immune checkpoint molecules, such as CEBPA and B2M in regulatory T (Treg) cells, providing a better understanding of the gene networks involved in immune regulation. In summary, parallel measurement of single-cell expression in thousands of tumor cells and tumor-infiltrating lymphocytes can be used to obtain a systems-level view of the tumor microenvironment and identify new avenues for therapeutic development.

Targeted short read sequencing and assembly of re-arrangements and candidate gene loci provide megabase diplotypes.

The human genome is composed of two haplotypes, otherwise called diplotypes, which denote phased polymorphisms and structural variations (SVs) that are derived from both parents. Diplotypes place genetic variants in the context of cis-related variants from a diploid genome. As a result, they provide valuable information about hereditary transmission, context of SV, regulation of gene expression and other features which are informative for understanding human genetics. Successful diplotyping with short read whole genome sequencing generally requires either a large population or parent-child trio samples. To overcome these limitations, we developed a targeted sequencing method for generating megabase (Mb)-scale haplotypes with short reads. One selects specific 0.1-0.2 Mb high molecular weight DNA targets with custom-designed Cas9-guide RNA complexes followed by sequencing with barcoded linked reads. To test this approach, we designed three assays, targeting the BRCA1 gene, the entire 4-Mb major histocompatibility complex locus and 18 well-characterized SVs, respectively. Using an integrated alignment- and assembly-based approach, we generated comprehensive variant diplotypes spanning the entirety of the targeted loci and characterized SVs with exact breakpoints. Our results were comparable in quality to long read sequencing.

Haplotype-resolved and integrated genome analysis of the cancer cell line HepG2.

HepG2 is one of the most widely used human cancer cell lines in biomedical research and one of the main cell lines of ENCODE. Although the functional genomic and epigenomic characteristics of HepG2 are extensively studied, its genome sequence has never been comprehensively analyzed and higher order genomic structural features are largely unknown. The high degree of aneuploidy in HepG2 renders traditional genome variant analysis methods challenging and partially ineffective. Correct and complete interpretation of the extensive functional genomics data from HepG2 requires an understanding of the cell line's genome sequence and genome structure. Using a variety of sequencing and analysis methods, we identified a wide spectrum of genome characteristics in HepG2: copy numbers of chromosomal segments at high resolution, SNVs and Indels (corrected for aneuploidy), regions with loss of heterozygosity, phased haplotypes extending to entire chromosome arms, retrotransposon insertions and structural variants (SVs) including complex and somatic genomic rearrangements. A large number of SVs were phased, sequence assembled and experimentally validated. We re-analyzed published HepG2 datasets for allele-specific expression and DNA methylation and assembled an allele-specific CRISPR/Cas9 targeting map. We demonstrate how deeper insights into genomic regulatory complexity are gained by adopting a genome-integrated framework.

Exploring the spatiotemporal genetic heterogeneity in metastatic lung adenocarcinoma using a nuclei flow-sorting approach.

Variable tumor cellularity can limit sensitivity and precision in comparative genomics because differences in tumor content can result in misclassifying truncal mutations as region-specific private mutations in stroma-rich regions, especially when studying tissue specimens of mediocre tumor cellularity such as lung adenocarcinomas (LUADs). To address this issue, we refined a nuclei flow-sorting approach by sorting nuclei based on ploidy and the LUAD lineage marker thyroid transcription factor 1 and applied this method to investigate genome-wide somatic copy number aberrations (SCNAs) and mutations of 409 cancer genes in 39 tumor populations obtained from 16 primary tumors and 21 matched metastases. This approach increased the mean tumor purity from 54% (range 7-89%) of unsorted material to 92% (range 79-99%) after sorting. Despite this rise in tumor purity, we detected limited genetic heterogeneity between primary tumors and their metastases. In fact, 88% of SCNAs and 80% of mutations were propagated from primary tumors to metastases and low allele frequency mutations accounted for much of the mutational heterogeneity. Even though the presence of SCNAs indicated a history of chromosomal instability (CIN) in all tumors, metastases did not have more SCNAs than primary tumors. Moreover, tumors with biallelic TP53 or ATM mutations had high numbers of SCNAs, yet they were associated with a low interlesional genetic heterogeneity. The results of our study thus provide evidence that most macroevolutionary events occur in primary tumors before metastatic dissemination and advocate for a limited degree of CIN over time and space in this cohort of LUADs. Sampling of primary tumors thus may suffice to detect most mutations and SCNAs. In addition, metastases but not primary tumors had seeded additional metastases in three of four patients; this provides a genomic rational for surgical treatment of such oligometastatic LUADs. Copyright © 2018 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

Chromosome-scale mega-haplotypes enable digital karyotyping of cancer aneuploidy.

Genomic instability is a frequently occurring feature of cancer that involves large-scale structural alterations. These somatic changes in chromosome structure include duplication of entire chromosome arms and aneuploidy where chromosomes are duplicated beyond normal diploid content. However, the accurate determination of aneuploidy events in cancer genomes is a challenge. Recent advances in sequencing technology allow the characterization of haplotypes that extend megabases along the human genome using high molecular weight (HMW) DNA. For this study, we employed a library preparation method in which sequence reads have barcodes linked to single HMW DNA molecules. Barcode-linked reads are used to generate extended haplotypes on the order of megabases. We developed a method that leverages haplotypes to identify chromosomal segmental alterations in cancer and uses this information to join haplotypes together, thus extending the range of phased variants. With this approach, we identified mega-haplotypes that encompass entire chromosome arms. We characterized the chromosomal arm changes and aneuploidy events in a manner that offers similar information as a traditional karyotype but with the benefit of DNA sequence resolution. We applied this approach to characterize aneuploidy and chromosomal alterations from a series of primary colorectal cancers.

Sex, Sleep Deprivation, and the Anxious Brain.

Insufficient sleep is a known trigger of anxiety. Nevertheless, not everyone experiences these effects to the same extent. One determining factor is sex, wherein women experience a greater anxiogenic impact in response to sleep loss than men. However, the underlying brain mechanism(s) governing this sleep-loss-induced anxiety increase, including the markedly different reaction in women and men, is unclear. Here, we tested the hypothesis that structural brain morphology in a discrete network of emotion-relevant regions represents one such explanatory factor. Healthy participants were assessed across sleep-rested and sleep-deprived conditions, with brain structure quantified using gray matter volume measures. Sleep loss triggered greater levels of anxiety in women compared with men. Reduced gray matter volume in the anterior insula and lateral orbitofrontal cortex predicted the anxiogenic impact of sleep loss in women, yet predicted resilience in men, and did so with high discrimination accuracy. In contrast, gray matter volume in ventromedial prefrontal cortex predicted the anxiogenic impact of sleep loss in both men and women. Structural human brain morphology therefore appears to represent one mechanistic pathway (and possible biomarker) determining anxiety vulnerability to sleep loss-a discovery that may help explain the higher prevalence of sleep disruption and anxiety in women.

Human Hippocampal Structure: A Novel Biomarker Predicting Mnemonic Vulnerability to, and Recovery from, Sleep Deprivation.

Sleep deprivation impairs the formation of new memories. However, marked interindividual variability exists in the degree to which sleep loss compromises learning, the mechanistic reasons for which are unclear. Furthermore, which physiological sleep processes restore learning ability following sleep deprivation are similarly unknown. Here, we demonstrate that the structural morphology of human hippocampal subfields represents one factor determining vulnerability (and conversely, resilience) to the impact of sleep deprivation on memory formation. Moreover, this same measure of brain morphology was further associated with the quality of nonrapid eye movement slow wave oscillations during recovery sleep, and by way of such activity, determined the success of memory restoration. Such findings provide a novel human biomarker of cognitive susceptibility to, and recovery from, sleep deprivation. Moreover, this metric may be of special predictive utility for professions in which memory function is paramount yet insufficient sleep is pervasive (e.g., aviation, military, and medicine).

Sleep Deprivation Impairs the Human Central and Peripheral Nervous System Discrimination of Social Threat.

Facial expressions represent one of the most salient cues in our environment. They communicate the affective state and intent of an individual and, if interpreted correctly, adaptively influence the behavior of others in return. Processing of such affective stimuli is known to require reciprocal signaling between central viscerosensory brain regions and peripheral-autonomic body systems, culminating in accurate emotion discrimination. Despite emerging links between sleep and affective regulation, the impact of sleep loss on the discrimination of complex social emotions within and between the CNS and PNS remains unknown. Here, we demonstrate in humans that sleep deprivation impairs both viscerosensory brain (anterior insula, anterior cingulate cortex, amygdala) and autonomic-cardiac discrimination of threatening from affiliative facial cues. Moreover, sleep deprivation significantly degrades the normally reciprocal associations between these central and peripheral emotion-signaling systems, most prominent at the level of cardiac-amygdala coupling. In addition, REM sleep physiology across the sleep-rested night significantly predicts the next-day success of emotional discrimination within this viscerosensory network across individuals, suggesting a role for REM sleep in affective brain recalibration. Together, these findings establish that sleep deprivation compromises the faithful signaling of, and the "embodied" reciprocity between, viscerosensory brain and peripheral autonomic body processing of complex social signals. Such impairments hold ecological relevance in professional contexts in which the need for accurate interpretation of social cues is paramount yet insufficient sleep is pervasive.

A Genetic Polymorphism of the Human Dopamine Transporter Determines the Impact of Sleep Deprivation on Brain Responses to Rewards and Punishments.

Despite an emerging link between alterations in motivated behavior and a lack of sleep, the impact of sleep deprivation on human brain mechanisms of reward and punishment remain largely unknown, as does the role of trait dopamine activity in modulating such effects in the mesolimbic system. Combining fMRI with an established incentive paradigm and individual genotyping, here, we test the hypothesis that trait differences in the human dopamine transporter (DAT) gene-associated with altered synaptic dopamine signalling-govern the impact of sleep deprivation on neural sensitivity to impending monetary gains and losses. Consistent with this framework, markedly different striatal reward responses were observed following sleep loss depending on the DAT functional polymorphisms. Only participants carrying a copy of the nine-repeat DAT allele-linked to higher phasic dopamine activity-expressed amplified striatal response during anticipation of monetary gain following sleep deprivation. Moreover, participants homozygous for the ten-repeat DAT allele-linked to lower phasic dopamine activity-selectively demonstrated an increase in sensitivity to monetary loss within anterior insula following sleep loss. Together, these data reveal a mechanistic dependency on human of trait dopaminergic function in determining the interaction between sleep deprivation and neural processing of rewards and punishments. Such findings have clinical implications in disorders where the DAT genetic polymorphism presents a known risk factor with comorbid sleep disruption, including attention hyperactive deficit disorder and substance abuse.

Genotype status of the dopamine-related catechol-O-methyltransferase (COMT) gene corresponds with desirability of "unhealthy" foods.

The role of dopamine is extensively documented in weight regulation and food intake in both animal models and humans. Yet the role of dopamine has not been well studied in individual differences for food desirability. Genotype status of the dopamine-related catechol-O-methyltransferase (COMT) gene has been shown to influence dopamine levels, with greater COMT enzymatic activity in val/val individuals corresponding to greater degradation of dopamine. Decreased dopamine has been associated with poorer cognitive control and diminished goal-directed behavior in various behavioral paradigms. Additionally, dopaminergic-rich regions such as the frontal cortex and dorsal striatum have been shown to be important for supporting food-related decision-making. However, the role of dopamine, as assessed by COMT genotype status, in food desirability has not been fully explored. Therefore, we utilized an individual's COMT genotype status (n = 61) and investigated food desirability based on self-rated "healthy" and "unhealthy" food perceptions. Here we found val/val individuals (n = 19) have greater desirability for self-rated "unhealthy" food items, but not self-rated "healthy" food items, as compared to val/met (n = 24) and met/met (n = 18) individuals (p < 0.005). Utilizing an objective health measure for the food items, we also found val/val and val/met individuals have greater desirability for objectively defined "unhealthy" food items, as compared to met/met individuals (p < 0.01). This work further substantiates the role of dopamine in food-related behaviors and more specifically in relationship to food desirability for "unhealthy" food items.

Tired and apprehensive: anxiety amplifies the impact of sleep loss on aversive brain anticipation.

Anticipation is an adaptive process, aiding preparatory responses to potentially threatening events. However, excessive anticipatory responding and associated hyper-reactivity in the amygdala and insula are integral to anxiety disorders. Despite the co-occurrence of sleep disruption and anxiety disorders, the impact of sleep loss on affective anticipatory brain mechanisms, and the interaction with anxiety, remains unknown. Here, we demonstrate that sleep loss amplifies preemptive responding in the amygdala and anterior insula during affective anticipation in humans, especially for cues with high predictive certainty. Furthermore, trait anxiety significantly determined the degree of such neural vulnerability to sleep loss: individuals with highest trait anxiety showed the greatest increase in anticipatory insula activity when sleep deprived. Together, these data support a neuropathological model in which sleep disruption may contribute to the maintenance and/or exacerbation of anxiety through its impact on anticipatory brain function. They further raise the therapeutic possibility that targeted sleep restoration in anxiety may ameliorate excessive anticipatory responding and associated clinical symptomatology.

Control of nucleus accumbens activity with neurofeedback.

The nucleus accumbens (NAcc) plays critical roles in healthy motivation and learning, as well as in psychiatric disorders (including schizophrenia and attention deficit hyperactivity disorder). Thus, techniques that confer control of NAcc activity might inspire new therapeutic interventions. By providing second-to-second temporal resolution of activity in small subcortical regions, functional magnetic resonance imaging (fMRI) can resolve online changes in NAcc activity, which can then be presented as "neurofeedback." In an fMRI-based neurofeedback experiment designed to elicit NAcc activity, we found that subjects could increase their own NAcc activity, and that display of neurofeedback significantly enhanced their ability to do so. Subjects were not as capable of decreasing their NAcc activity, however, and enhanced control did not persist after subsequent removal of neurofeedback. Further analyses suggested that individuals who recruited positive aroused affect were better able to increase NAcc activity in response to neurofeedback, and that NAcc neurofeedback also elicited functionally correlated activity in the medial prefrontal cortex. Together, these findings suggest that humans can modulate their own NAcc activity and that fMRI-based neurofeedback may augment their efforts. The observed association between positive arousal and effective NAcc control further supports an anticipatory affect account of NAcc function.

Concurrent agonism of adenosine A2B and glucocorticoid receptors in human airway epithelial cells cooperatively induces genes with anti-inflammatory potential: a novel approach to treat chronic obstructive pulmonary disease.

Chronic obstructive pulmonary disease (COPD) is a neutrophilic inflammatory disorder that is weakly responsive to glucocorticoids. Identification of ways to enhance the anti-inflammatory activity of glucocorticoids is, therefore, a major research objective. Adenosine receptor agonists that target the A2B-receptor subtype are efficacious in several cell-based assays and preclinical models of inflammation. Accordingly, the present study was designed to determine if a selective A2B-receptor agonist, 2-[6-amino-3,5-dicyano-4-[4-(cyclopropylmethoxy)phenyl]pyridin-2-ylsulphanyl]acetamide (Bay 60-6583), and a glucocorticoid, dexamethasone, in combination display putative anti-inflammatory activity that is superior to either drug alone. In BEAS-2B human airway epithelial cells stably transfected with cAMP-response element (CRE) and glucocorticoid response element (GRE) reporter constructs, Bay 60-6583 promoted CRE-dependent transcription and enhanced GRE-dependent transcription by an adenosine A2B-receptor-mediated mechanism that was associated with cAMP formation and abolished by an inhibitor of cAMP-dependent protein kinase. Analysis of the concentration-response relationship that described the enhancement of GRE-dependent transcription showed that Bay 60-6583 increased the magnitude of response without affecting the potency of dexamethasone. Bay 60-6583 and dexamethasone also induced a panel of genes that, collectively, could have benefit in COPD. These were categorized into genes that were induced in a positive cooperative manner (RGS2, p57(kip2)), an additive manner (TTP, BRL-1), or by Bay 60-6583 (CD200, CRISPLD2, SOCS3) or dexamethasone (GILZ) only. Thus, the gene induction "fingerprints" produced by Bay 60-6583 and dexamethasone, alone and in combination, were distinct. Collectively, through their actions on gene expression, an adenosine A2B-receptor agonist and a glucocorticoid administered together may have utility in the treatment of inflammatory disorders that respond suboptimally to glucocorticoids as a monotherapy.

The Iterative Mindset Method: a neuroscientific theoretical approach for sustainable behavior change and weight-loss in digital medicine.

With the growing prevalence of chronic conditions driving 85% of all healthcare costs, digital health offers a promising opportunity to reverse disease and improve health at-scale. The healthcare industry's predominant approach to behavior change is performance-based with a focus on goals and tracking. This has not reversed the epidemic of chronic diseases and also can harm chronically ill and vulnerable patients via perceived failure-induced loss of motivation. Still nascent, the digital health industry is uniquely positioned to adopt and scale new and better behavior change approaches. In this paper, we present the theoretical foundation and initial findings of a neuroscience-based behavior change approach-what we call the Iterative Mindset MethodTM. We discuss its promise, as a potentially more effective, neuroscience-based approach to changing health behaviors long-term, particularly in vulnerable populations. We conclude with avenues for future research.

Population bottleneck associated with but likely preceded the recent evolution of self-fertilization in a coastal dune plant.

Evolution of self-fertilization may be initiated by a historical population bottleneck, which should diagnostically reduce lineage-wide genetic variation. However, selfing can also strongly reduce genetic variation after it evolves. Distinguishing process from pattern is less problematic if mating system divergence is recent and geographically simple. Dramatically reduced diversity is associated with the transition from outcrossing to selfing in the Pacific coastal endemic Abronia umbellata that includes large-flowered, self-incompatible populations (var. umbellata) south of San Francisco Bay and small-flowered, autogamous populations (var. breviflora) to the north. Compared to umbellata, synonymous nucleotide diversity across 10 single-copy nuclear genes was reduced by 94% within individual populations and 90% across the whole selfing breviflora lineage, which contained no unique polymorphisms. The geographic pattern of genetic variation is consistent with a single origin of selfing that occurred recently (7-28 kya). These results are best explained by a historical bottleneck, but the two most northerly umbellata populations also contained little variation and clustered with selfing populations, suggesting that substantial diversity loss preceded the origin of selfing. A bottleneck may have set the stage for the eventual evolution of selfing by purging genetic load that prevents the spread of selfing.

Pan-conserved segment tags identify ultra-conserved sequences across assemblies in the human pangenome.

The human pangenome, a new reference sequence, addresses many limitations of the current GRCh38 reference. The first release is based on 94 high-quality haploid assemblies from individuals with diverse backgrounds. We employed a k-mer indexing strategy for comparative analysis across multiple assemblies, including the pangenome reference, GRCh38, and CHM13, a telomere-to-telomere reference assembly. Our k-mer indexing approach enabled us to identify a valuable collection of universally conserved sequences across all assemblies, referred to as "pan-conserved segment tags" (PSTs). By examining intervals between these segments, we discerned highly conserved genomic segments and those with structurally related polymorphisms. We found 60,764 polymorphic intervals with unique geo-ethnic features in the pangenome reference. In this study, we utilized ultra-conserved sequences (PSTs) to forge a link between human pangenome assemblies and reference genomes. This methodology enables the examination of any sequence of interest within the pangenome, using the reference genome as a comparative framework.