Human Genome Sequence Research Articles

Alterations of the gut microbiome in HIV infection highlight human anelloviruses as potential predictors of immune recovery

BackgroundHIV-1 infection is characterized by a massive depletion of mucosal CD4 T cells that triggers a cascade of events ultimately linking gut microbial dysbiosis to HIV-1 disease progression and pathogenesis. The association between HIV infection and the enteric virome composition is less characterized, although viruses are an essential component of the gut ecosystem. Here, we performed a cross-sectional analysis of the fecal viral (eukaryotic viruses and bacteriophages) and bacterial microbiome in people with HIV (PWH) and in HIV-negative individuals. To gain further insight into the association between the gut microbiome composition, HIV-associated immunodeficiency, and immune recovery, we carried out a longitudinal study including 14 PWH who initiated antiretroviral therapy (ART) and were followed for 24 months with samplings performed at baseline (before ART) and at 2, 6, 12, and 24 months post-ART initiation.ResultsOur data revealed a striking expansion in the abundance and prevalence of several human virus genomic sequences (Anelloviridae, Adenoviridae, and Papillomaviridae) in stool samples of PWH with severe immunodeficiency (CD4 < 200). We also noted a decreased abundance of sequences belonging to two plant viruses from the Tobamovirus genus, a reduction in bacterial alpha diversity, and a decrease in Inoviridae bacteriophage sequences. Short-term ART (24 months) was linked to a significant decrease in human Anelloviridae sequences. Remarkably, the detection of Anellovirus sequences at baseline independently predicted poor immune recovery, as did low CD4 T cell counts. The bacterial and bacteriophage populations were unique to each PWH with individualized trajectories; we found no discernable pattern of clustering after 24 months on ART.ConclusionAdvanced HIV-1 infection was associated with marked alterations in the virome composition, in particular a remarkable expansion of human anelloviruses, with a gradual restoration after ART initiation. In addition to CD4 T cell counts, anellovirus sequence detection might be useful to predict and monitor immune recovery. This study confirms data on the bacteriome and expands our knowledge on the viral component of the gut microbiome in HIV-1 infection.3oR8qDfXoWY9s_P5ES648YVideo

A-238 Lyophilized Bead Multiplex Assays for CT/NG/TV Detection

Abstract Background Chlamydia trachomatis (CT), Neisseria gonorrhoeae (NG), and Trichomonas vaginalis (TV) cause the three most prevalent sexually transmitted infectious diseases in developed countries, contributing to approximately 300 million new infections worldwide, annually. Due to the challenges of culturing and using immunoassays to detect these pathogens, DNA-based molecular tests have been instrumental, and current trends in molecular testing for CT/NG/TV have moved toward point-of-care tests. Lyophilization provides benefits required for point-of-care tests, such as ambient storage, extended shelf life, simplified downstream workflow, and variable formats. A lyophilized-bead format enables an assay to be placed in sealed consumables and stored at room temperature for up to two years. An additional consideration is the need for endogenous and exogenous controls. Exogenous in-process controls can be used to validate the performance of workflows culminating in a qPCR reaction and provide flexibility to test developers. An ideal exogenous in-process control is nonhomologous to human or human pathogen genome sequences and does not align with primers or probes designed for pathogen detection. The objective of the current study was to develop a lyophilized-bead-format assay containing an ideal exogenous control and establish whether it is a valid option for the accurate detection of CT, NG, and TV. Methods A synthetic DNA control containing targets for CT/NG/TV/RNase P (RP)/exogenous control was used to establish an analytical LOD by qPCR. The 5-plex assay, lyophilized in beads, was hydrated and tested for linearity over an 8-log range of the synthetic DNA control. Further, the qPCR lyophilized bead with assay was tested with a proficiency sample by extracting DNA from ZeptoMetrix NATtrol CT/NG/TV Positive Control and spiking-in the exogenous DNA control. qPCR was performed on the extracted DNA and human cDNA. Results The analytical LOD for the control DNA was determined to be 5 copies/reaction. Additionally, linearity was observed by qPCR over an 8-log range of the synthetic DNA control for all five targets in multiplex with good efficiencies and R2 values. Finally, all targets were amplified and detected by qPCR using DNA extracted from ZeptoMetrix NATtrol CT/NG/TV Positive Control with spiked-in exogenous DNA control. The detection of the exogenous sequence in the qPCR multiplex reaction indicated the extraction was successful. Conclusions We have developed a multiplex qPCR assay in lyophilized-bead format that can identify infectious agents, such as CT/NG/TV, in a single reaction. We have included RP as a human host control, plus an exogenous in-process control, for a total of 5-plex in separate fluorescent channels. We have shown that our lyophilized beads with assay produce a positive qPCR result when combined with a proficiency sample.

Sensor systems of KEAP1 uniquely detecting oxidative and electrophilic stresses separately In vivo

In the KEAP1-NRF2 stress response system, KEAP1 acts as a sensor for oxidative and electrophilic stresses through formation of S–S bond and C–S bond, respectively. Of the many questions left related to the sensor activity, following three appear important; whether these KEAP1 sensor systems are operating in vivo, whether oxidative and electrophilic stresses are sensed by the similar or distinct systems, and how KEAP1 equips highly sensitive mechanisms detecting oxidative and electrophilic stresses in vivo. To address these questions, we conducted a series of analyses utilizing KEAP1-cysteine substitution mutant mice, conditional selenocysteine-tRNA (Trsp) knockout mice, and human cohort whole genome sequence (WGS) data. Firstly, the Trsp-knockout provokes severe deficiency of selenoproteins and compensatory activation of NRF2. However, mice lacking homozygously a pair of critical oxidative stress sensor cysteine residues of KEAP1 fail to activate NRF2 in the Trsp-knockout livers. Secondly, this study provides evidence for the differential utilization of KEAP1 sensors for oxidative and electrophilic stresses in vivo. Thirdly, theoretical calculations show that the KEAP1 dimer equips quite sensitive sensor machinery in which modification of a single molecule of KEAP1 within the dimer is sufficient to affect the activity. WGS examinations of rare variants identified seven non-synonymous variants in the oxidative stress sensors in human KEAP1, while no variant was found in electrophilic sensor cysteine residues, supporting the fail-safe nature of the KEAP1 oxidative stress sensor activity. These results provide valuable information for our understanding how mammals respond to oxidative and electrophilic stresses efficiently.

Beyond the Human Genome Project: The Age of Complete Human Genome Sequences and Pangenome References.

The Human Genome Project was an enormous accomplishment, providing a foundation for countless explorations into the genetics and genomics of the human species. Yet for many years, the human genome reference sequence remained incomplete and lacked representation of human genetic diversity. Recently, two major advances have emerged to address these shortcomings: complete gap-free human genome sequences, such as the one developed by the Telomere-to-Telomere Consortium, and high-quality pangenomes, such as the one developed by the Human Pangenome Reference Consortium. Facilitated by advances in long-read DNA sequencing and genome assembly algorithms, complete human genome sequences resolve regions that have been historically difficult to sequence, including centromeres, telomeres, and segmental duplications. In parallel, pangenomes capture the extensive genetic diversity across populations worldwide. Together, these advances usher in a new era of genomics research, enhancing the accuracy of genomic analysis, paving the path for precision medicine, and contributing to deeper insights into human biology.

Enhancing recognition and interpretation of functional phenotypic sequences through fine-tuning pre-trained genomic models

BackgroundDecoding human genomic sequences requires comprehensive analysis of DNA sequence functionality. Through computational and experimental approaches, researchers have studied the genotype-phenotype relationship and generate important datasets that help unravel complicated genetic blueprints. Thus, the recently developed artificial intelligence methods can be used to interpret the functions of those DNA sequences.MethodsThis study explores the use of deep learning, particularly pre-trained genomic models like DNA_bert_6 and human_gpt2-v1, in interpreting and representing human genome sequences. Initially, we meticulously constructed multiple datasets linking genotypes and phenotypes to fine-tune those models for precise DNA sequence classification. Additionally, we evaluate the influence of sequence length on classification results and analyze the impact of feature extraction in the hidden layers of our model using the HERV dataset. To enhance our understanding of phenotype-specific patterns recognized by the model, we perform enrichment, pathogenicity and conservation analyzes of specific motifs in the human endogenous retrovirus (HERV) sequence with high average local representation weight (ALRW) scores.ResultsWe have constructed multiple genotype-phenotype datasets displaying commendable classification performance in comparison with random genomic sequences, particularly in the HERV dataset, which achieved binary and multi-classification accuracies and F1 values exceeding 0.935 and 0.888, respectively. Notably, the fine-tuning of the HERV dataset not only improved our ability to identify and distinguish diverse information types within DNA sequences but also successfully identified specific motifs associated with neurological disorders and cancers in regions with high ALRW scores. Subsequent analysis of these motifs shed light on the adaptive responses of species to environmental pressures and their co-evolution with pathogens.ConclusionsThese findings highlight the potential of pre-trained genomic models in learning DNA sequence representations, particularly when utilizing the HERV dataset, and provide valuable insights for future research endeavors. This study represents an innovative strategy that combines pre-trained genomic model representations with classical methods for analyzing the functionality of genome sequences, thereby promoting cross-fertilization between genomics and artificial intelligence.

The receptor VLDLR binds Eastern Equine Encephalitis virus through multiple distinct modes

Eastern Equine Encephalitis virus (EEEV) is an alphavirus that can cause severe diseases in infected humans. The very low-density lipoprotein receptor (VLDLR) was recently identified as a receptor of EEEV. Herein, we performed cryo-electron microscopy structural and biochemistry studies on the specific interactions between EEEV and VLDLR. Our results show that VLDLR binds EEEV at three different sites A, B and C through its membrane-distal LDLR class A (LA) repeats. Site A is located in the cleft in between the E1-E2 heterodimers. Site B is located near the connecting β ribbon of E2 and is in proximity to site A, while site C is on the domain B of E2. The binding of VLDLR LAs to EEEV is in complex modes, including the LA1-2 and LA3-5 mediated two major modes. Disruption of the LA1-2 mediated binding significantly affect the cell attachment of EEEV. However, the mutation W132G of VLDLR impairs the binding of LA3, drives the switch of the binding modes, and significantly enhances the attachment of EEEV to the cell. The W132G variant of VLDLR could be identified in human genome and SNP sequences, implying that people with similar mutations in VLDLR may be highly susceptible to EEEV infection.

Assessment of the evidence yield for the calibrated PP3/BP4 computational recommendations

Purpose: To investigate the number of rare missense variants observed in human genome sequences by ACMG/AMP PP3/BP4 evidence strength, following the ClinGen-calibrated PP3/BP4 computational recommendations. MethodsMissense variants from the genome sequences of 300 probands from the Rare Genomes Project with suspected rare disease were analyzed using computational prediction tools that were able to reach PP3_Strong and BP4_Moderate evidence strengths (BayesDel, MutPred2, REVEL, and VEST4). The numbers of variants at each evidence strength were analyzed across disease-associated genes and genome-wide. ResultsFrom a median of 75.5 rare (≤1% allele frequency) missense variants in disease-associated genes per proband, a median of one reached PP3_Strong, 3-5 PP3_Moderate, and 3-5 PP3_Supporting. Most were allocated BP4 evidence (median 41-49 per proband) or were indeterminate (median 17.5-19 per proband). Extending the analysis to all protein-coding genes genome-wide, the number of variants reaching PP3_Strong score thresholds increased approximately 2.6-fold compared with disease-associated genes, with a median per proband of 1-3 PP3_Strong, 8-16 PP3_Moderate, and 10-17 PP3_Supporting. ConclusionA small number of variants per proband reached PP3_Strong and PP3_Moderate in 3424 disease-associated genes. Although not the intended use of the recommendations, this was also observed genome-wide. Use of PP3/BP4 evidence as recommended from calibrated computational prediction tools in the clinical diagnostic laboratory is unlikely to inappropriately contribute to the classification of an excessive number of variants as pathogenic or likely pathogenic by ACMG/AMP rules.

Enhancing SNV identification in whole-genome sequencing data through the incorporation of known genetic variants into the minimap2 index

MotivationAlignment of reads to a reference genome sequence is one of the key steps in the analysis of human whole-genome sequencing data obtained through Next-generation sequencing (NGS) technologies. The quality of the subsequent steps of the analysis, such as the results of clinical interpretation of genetic variants or the results of a genome-wide association study, depends on the correct identification of the position of the read as a result of its alignment. The amount of human NGS whole-genome sequencing data is constantly growing. There are a number of human genome sequencing projects worldwide that have resulted in the creation of large-scale databases of genetic variants of sequenced human genomes. Such information about known genetic variants can be used to improve the quality of alignment at the read alignment stage when analysing sequencing data obtained for a new individual, for example, by creating a genomic graph. While existing methods for aligning reads to a linear reference genome have high alignment speed, methods for aligning reads to a genomic graph have greater accuracy in variable regions of the genome. The development of a read alignment method that takes into account known genetic variants in the linear reference sequence index allows combining the advantages of both sets of methods.ResultsIn this paper, we present the minimap2_index_modifier tool, which enables the construction of a modified index of a reference genome using known single nucleotide variants and insertions/deletions (indels) specific to a given human population. The use of the modified minimap2 index improves variant calling quality without modifying the bioinformatics pipeline and without significant additional computational overhead. Using the PrecisionFDA Truth Challenge V2 benchmark data (for HG002 short-read data aligned to the GRCh38 linear reference (GCA_000001405.15) with parameters k = 27 and w = 14) it was demonstrated that the number of false negative genetic variants decreased by more than 9500, and the number of false positives decreased by more than 7000 when modifying the index with genetic variants from the Human Pangenome Reference Consortium.

Computational identification of ultra-conserved elements in the human genome: a hypothesis on homologous DNA pairing.

Thousands of prolonged sequences of human ultra-conserved non-coding elements (UCNEs) share only one common feature: peculiarities in the unique composition of their dinucleotides. Here we investigate whether the numerous weak signals emanating from these dinucleotide arrangements can be used for computational identification of UCNEs within the human genome. For this purpose, we analyzed 4272 UCNE sequences, encompassing 1 393 448 nucleotides, alongside equally sized control samples of randomly selected human genomic sequences. Our research identified nine different features of dinucleotide arrangements that enable differentiation of UCNEs from the rest of the genome. We employed these nine features, implementing three Machine Learning techniques - Support Vector Machine, Random Forest, and Artificial Neural Networks - to classify UCNEs, achieving an accuracy rate of 82-84%, with specific conditions allowing for over 90% accuracy. Notably, the strongest feature for UCNE identification was the frequency ratio between GpC dinucleotides and the sum of GpG and CpC dinucleotides. Additionally, we investigated the entire pool of 31 046 SNPs located within UCNEs for their representation in the ClinVar database, which catalogs human SNPs with known phenotypic effects. The presence of UCNE-associated SNPs in ClinVar aligns with the expectation of a random distribution, emphasizing the enigmatic nature of UCNE phenotypic manifestation.

Beyond Meta-Omics: Functional Genomics in Future Marine Microbiome Research.

When President Bill Clinton and Francis Collins, then the director of the National Human Genome Research Institute, celebrated the near completion of the human genome sequence at the White House in the summer of 2000, it is unlikely that they or anyone else could have predicted the blossoming of meta-omics in the following two decades and their applications in modern human microbiome and environmental microbiome research. This transformation was enabled by the development of high-throughput sequencing technologies and sophisticated computational biology tools and bioinformatics software packages. Today, environmental meta-omics has undoubtedly revolutionized our understanding of ocean ecosystems, providing the genetic blueprint of oceanic microscopic organisms. In this review, I discuss the importance of functional genomics in future marine microbiome research and advocate a position for a gene-centric, bottom-up approach in modern oceanography. I propose that a synthesis of multidimensional approaches is required for a better understanding of the true functionality of the marine microbiome.

From Sanger to genome sequencing - an overview of DNA sequencing technologies

There is no technique that would make a greater contribution to the development of genetics, molecular biology and medicine than DNA sequencing. For many years, the method based on enzymatic DNA synthesis developed by Frederic Sanger was the gold standard in this area. At the end of the 20th century, there was a dynamic development of next-generation sequencing (NGS) technologies, which ended the era of single gene analysis and initiated the era of genome sequencing. Despite fierce competition, one NGS technology has practically completely dominated the global market. In the article, we present our own review of DNA sequencing methods, starting from the Sanger method to high-throughput second- and third-generation sequencing technologies, with particular emphasis on those that have achieved commercial success. We present their short history, principles of operation, technical possibilities, applications and limitations. In the summary, we reveal how much human genome sequencing costs at the current stage of the genomic revolution and outline the prospects for further development of genomics.

Sequencing and characterization of human bocavirus genomes from patients diagnosed in Southern France between 2017 and 2022.

The diversity and evolution of the genomes of human bocavirus (HBoV), which causes respiratory diseases, have been scarcely studied. Here, we aimed to obtain and characterize HBoV genomes from patients's nasopharyngeal samples collected between 2017 and 2022 period (5 years and 7 months). Next-generation sequencing (NGS) used Illumina technology after having implemented using GEMI an in-house multiplex PCR amplification strategy. Genomes were assembled and analyzed with CLC Genomics, Mafft, BioEdit, MeV, Nextclade, MEGA, and iTol. A total of 213 genomes were obtained. Phylogeny classified them all as of Bocavirus 1 (HBoV1) species. Five HBoV1 genotypic clusters determined by hierarchical clustering analysis of 27 variable genome positions were scattered over the study period although with differences in yearly prevalence. A total of 167 amino acid substitutions were detected. Besides, coinfection was observed for 52% of the samples, rhinoviruses then adenoviruses (HAdVs) being the most common viruses. Principal component analysis showed that HBoV1 genotypic cluster α tended to be correlated with HAdV co-infection. Subsequent HAdV typing for HBoV1-positive samples and negative controls demonstrated that HAdVC species predominated but HAdVB was that significantly HBoV1-associated. Overall, we described here the first HBoV1 genomes sequenced for France. HBoV1 and HAdVB association deserves further investigation.

FAIR compliant database development for human microbiome data samples.

Sharing microbiome data among researchers fosters new innovations and reduces cost for research. Practically, this means that the (meta)data will have to be standardized, transparent and readily available for researchers. The microbiome data and associated metadata will then be described with regards to composition and origin, in order to maximize the possibilities for application in various contexts of research. Here, we propose a set of tools and protocols to develop a real-time FAIR (Findable. Accessible, Interoperable and Reusable) compliant database for the handling and storage of human microbiome and host-associated data. The conflicts arising from privacy laws with respect to metadata, possible human genome sequences in the metagenome shotgun data and FAIR implementations are discussed. Alternate pathways for achieving compliance in such conflicts are analyzed. Sample traceable and sensitive microbiome data, such as DNA sequences or geolocalized metadata are identified, and the role of the GDPR (General Data Protection Regulation) data regulations are considered. For the construction of the database, procedures have been realized to make data FAIR compliant, while preserving privacy of the participants providing the data. An open-source development platform, Supabase, was used to implement the microbiome database. Researchers can deploy this real-time database to access, upload, download and interact with human microbiome data in a FAIR complaint manner. In addition, a large language model (LLM) powered by ChatGPT is developed and deployed to enable knowledge dissemination and non-expert usage of the database.

Challenges to Precision Public Health in Nigeria

With the waves of evolution in genomics and genomics technology, the 21st century has experienced a surge in human and pathogen genome sequencing both at the clinical and public health care levels. These latest efforts have led to what is commonly referred to as "precision public health," which is a multidisciplinary field that incorporates genomics, artificial intelligence (AI), and big data to help predict the healthcare outcomes of an individual and improve the general population's health. To individualize healthcare at the clinical and public health levels, research efforts have seen the emergence and utilization of technology in the management of healthcare. Despite precision public health being ascribed as a highly promising tool that could help provide solutions to many public health problems in developed societies, how this turns out in developing nations is yet to be established. This study applied an analytical cross-sectional study design and aimed at assessing challenges and enablers of PPH in Nigeria using genomic surveillance with an objective of understanding the challenges, establishing the influence of data integration methods on the attainment of PPH, the influence of health equity on the attainment of PPH and identifying the influence of health policies. The empirical literature review and cross-sectional study design were used with SPSS 23, and the visualization of data was done using the Microsoft Excel 2019 software. The study findings illustrated that more than 52% of the respondents have heard about precision public health, with 56.4% of the respondents disagreeing with the equitable distribution of technological infrastructure to support data management. A high proportion of the respondents agree that the government can implement PPH in Nigeria. However, a slightly higher proportion of the respondents (46.2%) disagreed on the role of the private sector in establishing PPH across private health facilities and the need for political goodwill to support the implementation of PPH in Nigeria. In conclusion, PPH can help improve disease prevention strategies, treatment, and control efforts if appropriately implemented, and the study recommends a need for African studies to aggregate, analyze, visualize, and make available high quality for PPH to be more effective than traditional public health.

A comparison of methods for detecting DNA methylation from long-read sequencing of human genomes

BackgroundLong-read sequencing can enable the detection of base modifications, such as CpG methylation, in single molecules of DNA. The most commonly used methods for long-read sequencing are nanopore developed by Oxford Nanopore Technologies (ONT) and single molecule real-time (SMRT) sequencing developed by Pacific Bioscience (PacBio). In this study, we systematically compare the performance of CpG methylation detection from long-read sequencing.ResultsWe demonstrate that CpG methylation detection from 7179 nanopore-sequenced DNA samples is highly accurate and consistent with 132 oxidative bisulfite-sequenced (oxBS) samples, isolated from the same blood draws. We introduce quality filters for CpGs that further enhance the accuracy of CpG methylation detection from nanopore-sequenced DNA, while removing at most 30% of CpGs. We evaluate the per-site performance of CpG methylation detection across different genomic features and CpG methylation rates and demonstrate how the latest R10.4 flowcell chemistry and base-calling algorithms improve methylation detection from nanopore sequencing. Additionally, we show how the methylation detection of 50 SMRT-sequenced genomes compares to nanopore sequencing and oxBS.ConclusionsThis study provides the first systematic comparison of CpG methylation detection tools for long-read sequencing methods. We compare two commonly used computational methods for the detection of CpG methylation in a large number of nanopore genomes, including samples sequenced using the latest R10.4 nanopore flowcell chemistry and 50 SMRT sequenced samples. We provide insights into the strengths and limitations of each sequencing method as well as recommendations for standardization and evaluation of tools designed for genome-scale modified base detection using long-read sequencing.

Nanopore sequencing with T2T-CHM13 for accurate detection and preventing the transmission of structural rearrangements in highly repetitive heterochromatin regions in human embryos.

Structural rearrangements in highly repetitive heterochromatin regions can result in miscarriage or foetal malformations; however, detecting and preventing the transmission of these rearrangements has been challenging. Recently, the completion of sequencing of the complete human genome (T2T-CHM13) has made it possible to accurately characterise structural rearrangements in these regions. We developed a method based on T2T-CHM13 and nanopore sequencing to detect and block structural rearrangements in highly repetitive heterochromatin sequences. T2T-CHM13-based "Mapping Allele with Resolved Carrier Status" was performed for couples who carry structural rearrangements in heterochromatin regions. Using nanopore sequencing and the T2T-CHM13 reference genome, the precise breakpoints of inversions and translocations close to the centromere were detected and haplotypes were constructed using flanking single-nucleotide polymorphisms (SNPs). Haplotype linkage analysis was then performed by comparing consistent parental SNPs with embryonic SNPs to determine whether the embryos carried hereditary inversions or balanced translocations. Based on copy number variation and haplotype linkage analysis, we transplanted normal embryos, which were further verified by an amniotic fluid test. To validate this approach, we used nanopore sequencing of families with inversions and reciprocal translocations close to the centromere. Using the T2T-CHM13 reference genome, we accurately detected inversions and translocations in centromeres, constructed haplotypes and prevented the transmission of structural rearrangements in the offspring. This study represents the first successful application of T2T-CHM13 in human reproduction and provides a feasible protocol for detecting and preventing the transmission of structural rearrangements of heterochromatin in embryos.

Expanding the DNA editing toolbox: Novel lambda integrase variants targeting microalgal and human genome sequences.

Recombinase enzymes are extremely efficient at integrating very large DNA fragments into target genomes. However, intrinsic sequence specificities curtail their use to DNA sequences with sufficient homology to endogenous target motifs. Extensive engineering is therefore required to broaden applicability and robustness. Here, we describe the directed evolution of novel lambda integrase variants capable of editing exogenous target sequences identified in the diatom Phaeodactylum tricornutum and the algae Nannochloropsis oceanica. These microorganisms hold great promise as conduits for green biomanufacturing and carbon sequestration. The evolved enzyme variants show >1000-fold switch in specificity towards the non-natural target sites when assayed in vitro. A single-copy target motif in the human genome with homology to the Nannochloropsis oceanica site can also be efficiently targeted using an engineered integrase, both in vitro and in human cells. The developed integrase variants represent useful additions to the DNA editing toolbox, with particular application for targeted genomic insertion of large DNA cargos.

Gene replacement-Alzheimer's disease (GR-AD): Modeling the genetics of human dementias in mice.

Genetic studies conducted over the past four decades have provided us with a detailed catalog of genes that play critical roles in the etiology of Alzheimer's disease (AD) and related dementias (ADRDs). Despite this progress, as a field we have had only limited success in incorporating this rich complexity of human AD/ADRD genetics findings into our animal models of these diseases. Our primary goal for the gene replacement (GR)-AD project is to develop mouse lines that model the genetics of AD/ADRD as closely as possible. To do this, we are generating mouse lines in which the genes of interest are precisely and completely replaced in the mouse genome by their full human orthologs. Each model set consists of a control line with a wild-type human allele and variant lines that precisely match the human genomic sequence in the control line except for a high-impact pathogenic mutation or risk variant.

A whole-genome shotgun approach to human reference genome sequencing.

A whole-genome shotgun approach to human reference genome sequencing.

Viral and host small RNA transcriptome analysis of SARS-CoV-1 and SARS-CoV-2-infected human cells reveals novel viral short RNAs

RNA viruses have been shown to express various short RNAs, some of which have regulatory roles during replication, transcription, and translation of viral genomes. However, short viral RNAs generated from SARS-CoV-1 and SARS-CoV-2 genomic RNAs remained largely unexplored, possibly due limitations of the widely used library preparation methods for small RNA deep sequencing and corresponding data processing. By analyzing publicly available small RNA sequencing datasets, we observed that human Calu-3 cells infected by SARS-CoV-1 or SARS-CoV-2 accumulate multiple previously unreported short viral RNAs. In addition, we verified the presence of the five most abundant SARS-CoV-2 short viral RNAs in SARS-CoV-2-infected human lung adenocarcinoma cells by quantitative PCR. Interestingly, the copy number of the observed SARS-CoV-2 short viral RNAs dramatically exceeded the expression of previously reported viral microRNAs in the same cells. We hypothesize that the reported SARS-CoV-2 short viral RNAs could serve as biomarkers for early infection stages due to their high abundance. Furthermore, unlike SARS-CoV-1, the SARS-CoV-2 infection induced significant (Benjamini-Hochberg-corrected p-value <0.05) deregulation of Y-RNA, transfer RNA, vault RNA, as well as more than 300 endogenous short RNAs that aligned predominantly to human protein-coding and long noncoding RNA transcripts. In particular, more than 20-fold upregulation of reads derived from Y-RNA (and several transfer RNAs) have been documented in RNA-seq datasets from SARS-CoV-2 infected cells. Finally, a significant proportion of short RNAs derived from full-length viral genomes also aligned to various human genome (hg38) sequences, suggesting opportunities to investigate regulatory roles of short viral RNAs during infection. Further characterization of the small RNA landscape of both viral and host genomes is clearly warranted to improve our understanding of molecular events related to infection and to design more efficient strategies for therapeutic interventions as well as early diagnosis.