Individual Human Genomes Research Articles

HaplotagLR: An efficient and configurable utility for haplotagging long reads.

Understanding the functional effects of sequence variation is crucial in genomics. Individual human genomes contain millions of variants that contribute to phenotypic variability and disease risks at the population level. Because variants rarely act in isolation, we must consider potential interactions of neighboring variants to accurately predict functional effects. We can accomplish this using haplotagging, which matches sequencing reads to their parental haplotypes using alleles observed at known heterozygous variants. However, few published tools for haplotagging exist and these share several technical and usability-related shortcomings that limit applicability, in particular a lack of insight or control over error rates, and lack of key metrics on the underlying sources of haplotagging error. Here we present HaplotagLR: a user-friendly tool that haplotags long sequencing reads based on a multinomial model and existing phased variant lists. HaplotagLR is user-configurable and includes a basic error model to control the empirical FDR in its output. We show that HaplotagLR outperforms the leading haplotagging method in simulated datasets, especially at high levels of specificity, and displays 7% greater sensitivity in haplotagging real data. HaplotagLR advances both the immediate utility of haplotagging and paves the way for further improvements to this important method.

A landscape of complex tandem repeats within individual human genomes

Markedly expanded tandem repeats (TRs) have been correlated with ~60 diseases. TR diversity has been considered a clue toward understanding missing heritability. However, haplotype-resolved long TRs remain mostly hidden or blacked out because their complex structures (TRs composed of various units and minisatellites containing >10-bp units) make them difficult to determine accurately with existing methods. Here, using a high-precision algorithm to determine complex TR structures from long, accurate reads of PacBio HiFi, an investigation of 270 Japanese control samples yields several genome-wide findings. Approximately 322,000 TRs are difficult to impute from the surrounding single-nucleotide variants. Greater genetic divergence of TR loci is significantly correlated with more events of younger replication slippage. Complex TRs are more abundant than single-unit TRs, and a tendency for complex TRs to consist of <10-bp units and single-unit TRs to be minisatellites is statistically significant at loci with ≥500-bp TRs. Of note, 8909 loci with extended TRs (>100b longer than the mode) contain several known disease-associated TRs and are considered candidates for association with disorders. Overall, complex TRs and minisatellites are found to be abundant and diverse, even in genetically small Japanese populations, yielding insights into the landscape of long TRs.

Social network position and the Conserved Transcriptional Response to Adversity in older Koreans

BackgroundSocial connections are crucial to human health and well-being. Previous research on molecular mechanisms in health has focused primarily on the individual-level perception of social connections (e.g., loneliness). This study adopted socio-centric social network analysis that includes all social ties from the entire population of interest to examine the group-level social connections and their association with a molecular genomic measure of health. MethodsUsing socio-centric (global) social network data from an entire village in Korea, we investigated how social network characteristics are related to immune cell gene expression among older adults. Blood samples were collected (N = 53, 65–79 years) and mixed effect linear model analyses were performed to examine the association between social network characteristics and Conserved Transcriptional Response to Adversity (CTRA) RNA expression patterns. ResultsSocial network positions measured by k-core score, the degree of cohesive core positions in an entire village, were significantly associated with CTRA downregulation. Such associations emerged above and beyond the effects of perceived social isolation (loneliness) and biobehavioral risk factors (smoking, alcohol, BMI, etc.). Social network size, defined as degree centrality, was also associated with reduced CTRA gene expression, but its association mimicked that of perceived social isolation (loneliness). ConclusionsThe current findings implicate community-level social network characteristics in the regulation of individual human genome function above and beyond individual-level perceptions of connectedness.

This population does not exist: learning the distribution of evolutionary histories with generative adversarial networks.

Numerous studies over the last decade have demonstrated the utility of machine learning methods when applied to population genetic tasks. More recent studies show the potential of deep-learning methods in particular, which allow researchers to approach problems without making prior assumptions about how the data should be summarized or manipulated, instead learning their own internal representation of the data in an attempt to maximize inferential accuracy. One type of deep neural network, called Generative Adversarial Networks (GANs), can even be used to generate new data, and this approach has been used to create individual artificial human genomes free from privacy concerns. In this study, we further explore the application of GANs in population genetics by designing and training a network to learn the statistical distribution of population genetic alignments (i.e. data sets consisting of sequences from an entire population sample) under several diverse evolutionary histories-the first GAN capable of performing this task. After testing multiple different neural network architectures, we report the results of a fully differentiable Deep-Convolutional Wasserstein GAN with gradient penalty that is capable of generating artificial examples of population genetic alignments that successfully mimic key aspects of the training data, including the site-frequency spectrum, differentiation between populations, and patterns of linkage disequilibrium. We demonstrate consistent training success across various evolutionary models, including models of panmictic and subdivided populations, populations at equilibrium and experiencing changes in size, and populations experiencing either no selection or positive selection of various strengths, all without the need for extensive hyperparameter tuning. Overall, our findings highlight the ability of GANs to learn and mimic population genetic data and suggest future areas where this work can be applied in population genetics research that we discuss herein.

The first gapless, reference-quality, fully annotated genome from a Southern Han Chinese individual.

We used long-read DNA sequencing to assemble the genome of a Southern Han Chinese male. We organized the sequence into chromosomes and filled in gaps using the recently completed T2T-CHM13 genome as a guide, yielding a gap-free genome, Han1, containing 3,099,707,698 bases. Using the T2T-CHM13 annotation as a reference, we mapped all genes onto the Han1 genome and identified additional gene copies, generating a total of 60,708 putative genes, of which 20,003 are protein-coding. A comprehensive comparison between the genes revealed that 235 protein-coding genes were substantially different between the individuals, with frameshifts or truncations affecting the protein-coding sequence. Most of these were heterozygous variants in which one gene copy was unaffected. This represents the first gene-level comparison between two finished, annotated individual human genomes.

DANGER analysis: risk-averse on/off-target assessment for CRISPR editing without a reference genome.

The CRISPR-Cas9 system has successfully achieved site-specific gene editing in organisms ranging from humans to bacteria. The technology efficiently generates mutants, allowing for phenotypic analysis of the on-target gene. However, some conventional studies did not investigate whether deleterious off-target effects partially affect the phenotype. Herein, we present a novel phenotypic assessment of CRISPR-mediated gene editing: Deleterious and ANticipatable Guides Evaluated by RNA-sequencing (DANGER) analysis. Using RNA-seq data, this bioinformatics pipeline can elucidate genomic on/off-target sites on mRNA-transcribed regions related to expression changes and then quantify phenotypic risk at the gene ontology term level. We demonstrated the risk-averse on/off-target assessment in RNA-seq data from gene-edited samples of human cells and zebrafish brains. Our DANGER analysis successfully detected off-target sites, and it quantitatively evaluated the potential contribution of deleterious off-targets to the transcriptome phenotypes of the edited mutants. Notably, DANGER analysis harnessed de novo transcriptome assembly to perform risk-averse on/off-target assessments without a reference genome. Thus, our resources would help assess genome editing in non-model organisms, individual human genomes, and atypical genomes from diseases and viruses. In conclusion, DANGER analysis facilitates the safer design of genome editing in all organisms with a transcriptome. The Script for the DANGER analysis pipeline is available at https://github.com/KazukiNakamae/DANGER_analysis. In addition, the software provides a tutorial on reproducing the results presented in this article on the Readme page. The Docker image of DANGER_analysis is also available at https://hub.docker.com/repository/docker/kazukinakamae/dangeranalysis/general.

Secure secondary utilization system of genomic data using quantum secure cloud

Secure storage and secondary use of individual human genome data is increasingly important for genome research and personalized medicine. Currently, it is necessary to store the whole genome sequencing information (FASTQ data), which enables detections of de novo mutations and structural variations in the analysis of hereditary diseases and cancer. Furthermore, bioinformatics tools to analyze FASTQ data are frequently updated to improve the precision and recall of detected variants. However, existing secure secondary use of data, such as multi-party computation or homomorphic encryption, can handle only a limited algorithms and usually requires huge computational resources. Here, we developed a high-performance one-stop system for large-scale genome data analysis with secure secondary use of the data by the data owner and multiple users with different levels of data access control. Our quantum secure cloud system is a distributed secure genomic data analysis system (DSGD) with a “trusted server” built on a quantum secure cloud, the information-theoretically secure Tokyo QKD Network. The trusted server will be capable of deploying and running a variety of sequencing analysis hardware, such as GPUs and FPGAs, as well as CPU-based software. We demonstrated that DSGD achieved comparable throughput with and without encryption on the trusted server Therefore, our system is ready to be installed at research institutes and hospitals that make diagnoses based on whole genome sequencing on a daily basis.

Computational study of the impact of nucleotide variations on highly conserved proteins: In the case of actin.

Sequencing of individual human genomes enables studying relationship among nucleotide variations, amino acid substitutions, effect on protein structures and diseases. Many studies have found general tendencies, for instance, that pathogenic variations tend to be found in the buried regions of the protein structures, that benign variations tend to be found on the surface of the proteins, and that variations on evolutionary conserved residues tend to be pathogenic. These tendencies were deduced from globular proteins with standard evolutionary changes in amino acid sequences. In this study, we investigated the variation distribution on actin, one of the highly conserved proteins. Many nucleotide variations and three-dimensional structures of actin have been registered in databases. By combining those data, we found that variations buried inside the protein were rather benign and variations on the surface of the protein were pathogenic. This idiosyncratic distribution of the variation impact is likely ascribed to the extensive use of the surface of the protein for protein-protein interactions in actin.

Contribution of research-based pharmaceutical companies in Germany to personalised medicine

Abstract Background The term Personlised Medicine (PM) was introduced to the public more than 20 years ago and was related to tailor-made medicines and a treatment considering the individual human genome. In the meantime, the term PM can be found with various definitions in several different contexts. Considering this, the aim of this research is to analyse the current status of PM in Germany, especially with regard to scientific articles and the pharmaceutical industry. Methods First, a systematic literature review was conducted in PubMed and Web of Science. Each search strategy was adapted to the database conditions and consisted of the search terms personalised medicine or the MeSH term precision medicine, additionally pharmaceutical industry and Germany in topic, title or abstract (the Boolean operator AND was applied). Only results in German or English with an available abstract were considered. Second, the websites of all 47 members of the German association of research-based pharmaceutical companies (vfa) were systematically screened referring to their position and communication in terms of PM. Results The literature research yielded a total of only 4 results. The scope of the papers is nanomedicine, an interview study and gene disorders. The second research part shows differences on the company websites: More than half of the companies have no relation to PM or an analysis was not possible (n = 25). Some were categorized with indirect relation (n = 3) and on 19 websites PM was communicated in different ways. Conclusions The literature research clearly shows that although PM is not a new topic and furthermore, the research of pharmaceutical companies in this area is widely required, the number of scientific articles found is very low. The screening of company websites underlines this result as only 19 of 47 companies take a position to PM here and the scope varies greatly. Nevertheless, it is necessary to examine the reasons and how Germany compares to other countries. Key messages Although introduced more than 20 years ago, the appearance of PM by German pharmaceutical companies in scientific articles is quite low. The difference in companies’ communication should be examined.

Coronaviruses caused epidemics for millennia

Inside modern human DNA lie traces of ancient coronavirus infections from many, many years ago ( Curr. Biol. 2021, DOI: 10.1016/j.cub.2021.05.067 ). Around 25,000 years ago, in fact. That’s the conclusion of a team of researchers led by David Enard of the University of Arizona. The scientists used a large database of individual human genomes known as 1000 Genomes to compare the genes coding for proteins that interact with coronaviruses, including SARS-CoV-2. They found evidence in the DNA of people whose families came from East Asia that a coronavirus epidemic raged in that region around 25,000 years ago. In addition, the virus had changed the DNA of the survivors and their descendants. After completing the computational genomic analysis, the researchers synthesized human and coronavirus proteins and confirmed that they interact, as suggested by the team’s earlier results. The researchers also identified previously unknown drug targets that they say could be

A study of transposable element-associated structural variations (TASVs) using a de novo-assembled Korean genome

Advances in next-generation sequencing (NGS) technology have made personal genome sequencing possible, and indeed, many individual human genomes have now been sequenced. Comparisons of these individual genomes have revealed substantial genomic differences between human populations as well as between individuals from closely related ethnic groups. Transposable elements (TEs) are known to be one of the major sources of these variations and act through various mechanisms, including de novo insertion, insertion-mediated deletion, and TE–TE recombination-mediated deletion. In this study, we carried out de novo whole-genome sequencing of one Korean individual (KPGP9) via multiple insert-size libraries. The de novo whole-genome assembly resulted in 31,305 scaffolds with a scaffold N50 size of 13.23 Mb. Furthermore, through computational data analysis and experimental verification, we revealed that 182 TE-associated structural variation (TASV) insertions and 89 TASV deletions contributed 64,232 bp in sequence gain and 82,772 bp in sequence loss, respectively, in the KPGP9 genome relative to the hg19 reference genome. We also verified structural differences associated with TASVs by comparative analysis with TASVs in recent genomes (AK1 and TCGA genomes) and reported their details. Here, we constructed a new Korean de novo whole-genome assembly and provide the first study, to our knowledge, focused on the identification of TASVs in an individual Korean genome. Our findings again highlight the role of TEs as a major driver of structural variations in human individual genomes.

Finding long tandem repeats in long noisy reads.

MotivationLong tandem repeat expansions of more than 1000 nt have been suggested to be associated with diseases, but remain largely unexplored in individual human genomes because read lengths have been too short. However, new long-read sequencing technologies can produce single reads of 10 000 nt or more that can span such repeat expansions, although these long reads have high error rates, of 10–20%, which complicates the detection of repetitive elements. Moreover, most traditional algorithms for finding tandem repeats are designed to find short tandem repeats ( nt) and cannot effectively handle the high error rate of long reads in a reasonable amount of time.ResultsHere, we report an efficient algorithm for solving this problem that takes advantage of the length of the repeat. Namely, a long tandem repeat has hundreds or thousands of approximate copies of the repeated unit, so despite the error rate, many short k-mers will be error-free in many copies of the unit. We exploited this characteristic to develop a method for first estimating regions that could contain a tandem repeat, by analyzing the k-mer frequency distributions of fixed-size windows across the target read, followed by an algorithm that assembles the k-mers of a putative region into the consensus repeat unit by greedily traversing a de Bruijn graph. Experimental results indicated that the proposed algorithm largely outperformed Tandem Repeats Finder, a widely used program for finding tandem repeats, in terms of sensitivity.Availability and implementation https://github.com/morisUtokyo/mTR.

Loss-of-function tolerance of enhancers in the human genome.

Previous studies have surveyed the potential impact of loss-of-function (LoF) variants and identified LoF-tolerant protein-coding genes. However, the tolerance of human genomes to losing enhancers has not yet been evaluated. Here we present the catalog of LoF-tolerant enhancers using structural variants from whole-genome sequences. Using a conservative approach, we estimate that individual human genomes possess at least 28 LoF-tolerant enhancers on average. We assessed the properties of LoF-tolerant enhancers in a unified regulatory network constructed by integrating tissue-specific enhancers and gene-gene interactions. We find that LoF-tolerant enhancers tend to be more tissue-specific and regulate fewer and more dispensable genes relative to other enhancers. They are enriched in immune-related cells while enhancers with low LoF-tolerance are enriched in kidney and brain/neuronal stem cells. We developed a supervised learning approach to predict the LoF-tolerance of all enhancers, which achieved an area under the receiver operating characteristics curve (AUROC) of 98%. We predict 3,519 more enhancers would be likely tolerant to LoF and 129 enhancers that would have low LoF-tolerance. Our predictions are supported by a known set of disease enhancers and novel deletions from PacBio sequencing. The LoF-tolerance scores provided here will serve as an important reference for disease studies.

Abstract LB-214: Imputation of single cell cancer genotypes

Abstract Recent advances in sequencing technologies and emerging single cell sequencing promise to profoundly impact cancer studies. One of the most important problems is reconstruction of history of cancer mutations. Existing methods model cells DNA as haplotypes and reconstruct perfect (or almost perfect) phylogeny of mutations from single cell DNA sequencing data. In this paper we propose to reconstruct genotypes (rather than haplotypes) which in absence of repeated and omitted mutations is equivalent to reconstruction of the mutation phylogeny. Single cell genotype reconstruction is proposed to perform in two steps - first the sequencing data are used for imputation of cell genotypes treated as individual human genomes and then the resulted genomes are fitted to perfect phylogeny by eliminating 4-gamete rule violations using integer linear programs. Our simulation results show advantage of single cell genotype imputation over existing methods. Note: This abstract was not presented at the meeting. Citation Format: Alex Zelikovsky, Igor Mandric, Pavel Skums, Ion Mandoiu, Bogdan Pasaniuc, Pramod Srivastava. Imputation of single cell cancer genotypes [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr LB-214.

Characterization of Coding/Noncoding Variants for SHROOM3 in Patients with CKD.

Background Interpreting genetic variants is one of the greatest challenges impeding analysis of rapidly increasing volumes of genomic data from patients. For example, SHROOM3 is an associated risk gene for CKD, yet causative mechanism(s) of SHROOM3 allele(s) are unknown.Methods We used our analytic pipeline that integrates genetic, computational, biochemical, CRISPR/Cas9 editing, molecular, and physiologic data to characterize coding and noncoding variants to study the human SHROOM3 risk locus for CKD.Results We identified a novel SHROOM3 transcriptional start site, which results in a shorter isoform lacking the PDZ domain and is regulated by a common noncoding sequence variant associated with CKD (rs17319721, allele frequency: 0.35). This variant disrupted allele binding to the transcription factor TCF7L2 in podocyte cell nuclear extracts and altered transcription levels of SHROOM3 in cultured cells, potentially through the loss of repressive looping between rs17319721 and the novel start site. Although common variant mechanisms are of high utility, sequencing is beginning to identify rare variants involved in disease; therefore, we used our biophysical tools to analyze an average of 112,849 individual human genome sequences for rare SHROOM3 missense variants, revealing 35 high-effect variants. The high-effect alleles include a coding variant (P1244L) previously associated with CKD (P=0.01, odds ratio=7.95; 95% CI, 1.53 to 41.46) that we find to be present in East Asian individuals at an allele frequency of 0.0027. We determined that P1244L attenuates the interaction of SHROOM3 with 14-3-3, suggesting alterations to the Hippo pathway, a known mediator of CKD.Conclusions These data demonstrate multiple new SHROOM3-dependent genetic/molecular mechanisms that likely affect CKD.

Single cell on-chip whole genome amplification via micropillar arrays for reduced amplification bias.

Single cell whole genome amplification is susceptible to amplification biases that impact the accuracy of single cell sequencing data. To address this, we have developed a microfluidic device for the isolation and purification of genomic DNA from individual cells. The device uses a micropillar array to physically capture single cells and its chromosomal DNA upon extraction. The extracted DNA is immobilized within the micropillar array in a way that allows isothermal amplification. In this system, whole genome amplification of the single cell is carried out under a continual fluid flow within the microfluidic channel. We have demonstrated the process for amplification of individual human cancer cell genomes from the HeLa cell line. By sampling select gene loci along the human genome and performing whole exome sequencing, we demonstrate improved genome coverage and reduced amplification bias compared to amplification of single cells deposited in wells by fluorescence activated cell sorting.

SNP_TATA_Comparator: genomewide landmarks for preventive personalized medicine.

Year after year, conditions, quality, and duration of human lives have been improving due to the progress of science, technology, education, and medicine, which however has a downside. Owing to improvement in children's nutrition, developmental acceleration occurs that imbalances a child's system. Because of virtual worlds of the Internet, social experience of teenagers expands and clashes with puberty of adolescents. Due to the comfort of cities, urbanization emerges and causes stress to adults because of artificial light, noise, pollution, violations of personal space, and family disruption. At old age, all these factors taken together contribute to loneliness, cancer, diabetes, drug addiction, and sporadic Alzheimer's disease, which shorten the lifespan, as reviewed in the US, 1990-2010. That is why, a person may ask oneself: "What can I do now to keep my health in my old age?" To help them, we provide this comprehensive review on predictive preventive personalized medicine. This branch of molecular medicine uses single nucleotide polymorphisms to prevent diseases on the basis of the difference between the individual and reference human genomes.

The whole genome sequences and experimentally phased haplotypes of over 100 personal genomes.

BackgroundSince the completion of the Human Genome Project in 2003, it is estimated that more than 200,000 individual whole human genomes have been sequenced. A stunning accomplishment in such a short period of time. However, most of these were sequenced without experimental haplotype data and are therefore missing an important aspect of genome biology. In addition, much of the genomic data is not available to the public and lacks phenotypic information.FindingsAs part of the Personal Genome Project, blood samples from 184 participants were collected and processed using Complete Genomics’ Long Fragment Read technology. Here, we present the experimental whole genome haplotyping and sequencing of these samples to an average read coverage depth of 100X. This is approximately three-fold higher than the read coverage applied to most whole human genome assemblies and ensures the highest quality results. Currently, 114 genomes from this dataset are freely available in the GigaDB repository and are associated with rich phenotypic data; the remaining 70 should be added in the near future as they are approved through the PGP data release process. For reproducibility analyses, 20 genomes were sequenced at least twice using independent LFR barcoded libraries. Seven genomes were also sequenced using Complete Genomics’ standard non-barcoded library process. In addition, we report 2.6 million high-quality, rare variants not previously identified in the Single Nucleotide Polymorphisms database or the 1000 Genomes Project Phase 3 data.ConclusionsThese genomes represent a unique source of haplotype and phenotype data for the scientific community and should help to expand our understanding of human genome evolution and function.Electronic supplementary materialThe online version of this article (doi:10.1186/s13742-016-0148-z) contains supplementary material, which is available to authorized users.

A high-quality human reference panel reveals the complexity and distribution of genomic structural variants.

Structural variation (SV) represents a major source of differences between individual human genomes and has been linked to disease phenotypes. However, the majority of studies provide neither a global view of the full spectrum of these variants nor integrate them into reference panels of genetic variation. Here, we analyse whole genome sequencing data of 769 individuals from 250 Dutch families, and provide a haplotype-resolved map of 1.9 million genome variants across 9 different variant classes, including novel forms of complex indels, and retrotransposition-mediated insertions of mobile elements and processed RNAs. A large proportion are previously under reported variants sized between 21 and 100 bp. We detect 4 megabases of novel sequence, encoding 11 new transcripts. Finally, we show 191 known, trait-associated SNPs to be in strong linkage disequilibrium with SVs and demonstrate that our panel facilitates accurate imputation of SVs in unrelated individuals.

Deep sequencing of 10,000 human genomes

We report on the sequencing of 10,545 human genomes at 30×-40× coverage with an emphasis on quality metrics and novel variant and sequence discovery. We find that 84% of an individual human genome can be sequenced confidently. This high-confidence region includes 91.5% of exon sequence and 95.2% of known pathogenic variant positions. We present the distribution of over 150 million single-nucleotide variants in the coding and noncoding genome. Each newly sequenced genome contributes an average of 8,579 novel variants. In addition, each genome carries on average 0.7 Mb of sequence that is not found in the main build of the hg38 reference genome. The density of this catalog of variation allowed us to construct high-resolution profiles that define genomic sites that are highly intolerant of genetic variation. These results indicate that the data generated by deep genome sequencing is of the quality necessary for clinical use.