Human Genome Research Articles

Tracking Somatic Mutations for Lineage Reconstruction.

The human genome is composed of distinct genomic regions that are susceptible to various types of somatic mutations. Among these, Short Tandem Repeats (STRs) stand out as the most mutable genetic elements. STRs are short repetitive polymorphic sequences, predominantly situated within noncoding sectors of the genome. The intrinsic repetition characterizing these sequences makes them highly mutable in vivo. Consequently, this characteristic provides the chance to unravel the natural developmental history of human viable cells retrospectively. However, STRs also introduce stutter noise in vitro amplification, which makes their analysis challenging. Here we describe our integrated biochemical-computational platform for single-cell lineage analysis. It consists of a pipeline whose inputs are single cells and whose output is a lineage tree of input cells.

Identification and Analysis of Small Nucleolar RNAs by Real-Time Quantitative PCR.

One of the greatest scientific achievements of the twenty-first century is the completion of The Human Genome Project (HGP). Thereafter, we came to know that the human genome codes nearly 2% for making proteins and thus named as coding genes, suggesting the rest of the genome as noncoding or junk. However, research in the past two decades has shown and established that noncoding RNAs are major contributors of regulating and modulating the various function of cells as well as tissues. Noncoding RNAs can be classified as basis of their sizes in two categories, long noncoding RNAs (>200nt) and small noncoding RNAs (<200nt). Small nucleolar RNAs (snoRNAs) are part of the small noncoding RNA family and primarily reside inside the nucleus of eukaryotes. Sno RNAs can be divided into two major categories based on their distinguished structure and function; these are C/D box and HACA box snoRNAs. They participate in the posttranscriptional modifications on ribosomal RNAs (r-RNAs), transfer RNAs (t-RNAs), messenger RNAs (m-RNAs), and small nuclear RNAs (snRNAs). Sno RNAs act as guide RNAs to modify other noncoding RNAs by pseudouridylation or 2'O ribomethylation. We discussed in this protocol about one of the widely used techniques for detection and analysis of snoRNAs, i.e., real-time quantitative PCR (RT-qPCR).

When "loss-of-function" means proteostasis burden: Thinking again about coding DNA variants.

Each human genome has approximately 5 million DNA variants. Even for complete loss-of-function variants causing inherited, monogenic diseases, current understanding based on gene-specific molecular function does not adequately predict variability observed between people with identical mutations or fluctuating disease trajectories. We present a parallel paradigm for loss-of-function variants based on broader consequences to the cell when aberrant polypeptide chains of amino acids are translated from mutant RNA to generate mutated proteins. Missense variants that modify primary amino acid sequence, and nonsense/frameshift variants that generate premature termination codons (PTCs), are placed in context alongside emergent themes of chaperone binding, protein quality control capacity, and cellular adaptation to stress. Relatively stable proteostasis burdens are contrasted with rapid changes after induction of gene expression, or stress responses that suppress nonsense mediated decay (NMD) leading to higher PTC transcript levels where mutant proteins can augment cellular stress. For known disease-causal mutations, an adjunctive variant categorization system enhances clinical predictive power and precision therapeutic opportunities. Additionally, with typically more than 100 nonsense and frameshift variants, and ∼10,000 missense variants per human DNA, the paradigm focuses attention on all protein-coding DNA variants, and their potential contributions to multimorbid states beyond classically designated inherited diseases. Experimental testing in clinically relevant systems is encouraged to augment current atlases of protein expression at single-cell resolution, and high-throughput experimental data and deep-learning models that predict which amino acid substitutions generate enhanced degradative burdens. Incorporating additional dimensions such as pan-proteome competition for chaperones, and age-related loss of proteostasis capacity, should further accelerate health impacts.

Three-Dimensional Simulation of Whole-Genome Structuring Through the Transition from Anaphase to Interphase.

In order to analyze the three-dimensional genome architecture, it is important to simulate how the genome is structured through the cell cycle progression. In this chapter, we present the usage of our computation codes for simulating how the human genome is formed as the cell transforms from anaphase to interphase. We do not use the global Hi-C data as an input into the genome simulation but represent all chromosomes as linear polymers annotated by the neighboring region contact index (NCI), which classifies the A/B type of each local chromatin region. The simulated mitotic chromosomes heterogeneously expand upon entry to the G1 phase, which induces phase separation of A and B chromatin regions, establishing chromosome territories, compartments, and lamina and nucleolus associations in the interphase nucleus. When the appropriate one-dimensional chromosomal annotation is possible, using the protocol of this chapter, one can quantitatively simulate the three-dimensional genome structure and dynamics of human cells of interest.

Experience using conventional compared to ancestry-based population descriptors in clinical genomics laboratories.

Various scientific and professional groups, including the American Medical Association (AMA), American Society of Human Genetics (ASHG), American College of Medical Genetics (ACMG), and the National Academies of Sciences, Engineering, and Medicine (NASEM), have appropriately clarified that certain population descriptors, such as race and ethnicity, are social and cultural constructs with no basis in genetics. Nevertheless, these conventional population descriptors are routinely collected during the course of clinical genetic testing and may be used to interpret test results. Experts who have examined the use of population descriptors, both conventional and ancestry based, in human genetics and genomics have offered guidance on using these descriptors in research but not in clinical laboratory settings. This perspective piece is based on a decade of experience in a clinical genomics laboratory and provides insight into the relevance of conventional and ancestry-based population descriptors for clinical genetic testing, reporting, and clinical research on aggregated data. As clinicians, laboratory geneticists, genetic counselors, and researchers, we describe real-world experiences collecting conventional population descriptors in the course of clinical genetic testing and expose challenges in ensuring clarity and consistency in the use of population descriptors. Current practices in clinical genomics laboratories that are influenced by population descriptors are identified and discussed through case examples. In relation to this, we describe specific types of clinical research projects in which population descriptors were used and helped derive useful insights related to practicing and improving genomic medicine.

Human microbiome-derived peptide affects the development of experimental autoimmune encephalomyelitis via molecular mimicry.

Gut commensal microbiota has been identified as a potential environmental risk factor for multiple sclerosis (MS), and numerous studies have linked the commensal microorganism with the onset of MS. However, little is known about the mechanisms underlying the gut microbiome and host-immune system interaction. We employed bioinformatics methodologies to identify human microbial-derived peptides by analyzing their similarity to the MHC II-TCR binding patterns of self-antigens. Subsequently, we conducted a range of invitro and invivo assays to assess the encephalitogenic potential of these microbial-derived peptides. We analyzed 304,246 human microbiome genomes and 103 metagenomes collected from the MS cohort and identified 731 nonredundant analogs of myelin oligodendrocyte glycoprotein peptide 35-55 (MOG35-55). Of note, half of these analogs could bind to MHC II and interact with TCR through structural modeling of the interaction using fine-tuned AlphaFold. Among the 8 selected peptides, the peptide (P3) shows the ability to activate MOG35-55-specific CD4+ T cells invitro. Furthermore, P3 shows encephalitogenic capacity and has the potential to induce EAE in some animals. Notably, mice immunized with a combination of P3 and MOG35-55 develop severe EAE. Additionally, dendritic cells could process and present P3 to MOG35-55-specific CD4+ T cells and activate these cells. Our data suggests the potential involvement of a MOG35-55-mimic peptide derived from the gut microbiota as a molecular trigger of EAE pathogenesis. Our findings offer direct evidence of how microbes can initiate the development of EAE, suggesting a potential explanation for the correlation between certain gut microorganisms and MS prevalence. National Natural Science Foundation of China (82371350 to GY).

A brief history of the cortical thick ascending limb: a systems-biology perspective.

Here, we review key events in the accrual of knowledge about the cortical thick ascending limb (CTAL) of the kidney, starting with its initial characterization by Maurice Burg in 1973. Burg's work showed that the CTAL actively reabsorbs NaCl and that, because its water permeability is virtually zero, it can lower the luminal NaCl concentration to a "static head" level well below blood levels. This process is central to the kidney's ability to excrete dilute urine in states of high water intake. Following Burg's original observations, Greger and Schlatter, working in the 1980s, identified the membrane transport processes responsible for transepithelial NaCl transport in the CTAL. In the 1990s, several investigators identified the key transporter genes and proteins at a molecular level by cDNA cloning. The successful completion of human and mouse genome sequencing projects at the turn of the century led to the development of transcriptomic and proteomic methodologies that allowed the identification of complete transcriptomes and proteomes of CTAL cells. Knowledge accrual was enhanced by the development of differential equation-based models of transport in the CTAL in the 2010s. Here, we used a simplified mathematical model of NaCl ("salt"), urea, and water transport in the CTAL to address three key questions about CTAL function: 1) What is the mechanism of Burg's "static head" phenomenon? 2) How does the kidney compensate for the very short length of the CTALs of juxtamedullary nephrons? 3) Which of the three isoforms of the apical Na-K-2Cl cotransporter (NKCC2) dominates functionally in the CTAL?NEW & NOTEWORTHY Here, we review key events in the accrual of knowledge about the cortical thick ascending limb (CTAL) of the kidney, starting with its initial characterization by Maurice Burg in 1973, and culminating with the application of systems biology techniques including mathematical modeling.

A potential therapeutic strategy by fungal laccase targeting novel binding sites on human cytomegalovirus DNA polymerase.

Human cytomegalovirus (HCMV) is a common herpesvirus that can severely affect transplant recipients, those with AIDS, and newborns. Existing synthetic medications face limitations, including toxicity, processing issues, and viral resistance. As part of this study, the efficacy of the extracellular enzyme laccase isolated from a widely available mushroom (Pleurotus pulmonarius) was compared to that of ganciclovir, a common antiviral, used against HCMV. The study found that laccase can synergistically inhibit HCMV replication by targeting new inhibitory sites on the UL54 protein. Viral replication requires significant energy, increasing cellular respiration. The antiviral effect of laccase was linked to reduced expression of genes regulating cellular respiration, which coincided with decreased viral DNA copies. Additionally, in silico analysis has identified a novel binding site for the laccase enzyme in the C-terminal region of HCMV DNA polymerase specifically between amino acids 1004 and 1242, which effectively obstructs the binding of the essential viral replication regulatory accessory protein UL44, thereby hindering successful replication. Molecular dynamics simulations were performed under standardized conditions mimicking a cellular environment, revealing a stable protein-protein docking complex. This study may aid in developing novel antiviral strategies by utilizing laccase's target specificity to regulate host cellular pathways against Herpesviridae.

Highly-multiplex detection of plasma cell-free human papillomavirus-16 DNA in oropharyngeal carcinoma.

Plasma cell-free Human Papillomavirus DNA (cfHPVDNA) is a biomarker for oropharyngeal carcinoma. Existing diagnostics may be limited by inadequate sensitivity or high cost/complexity for longitudinal monitoring. We hypothesized that sensitive and specific plasma cfHPVDNA detection may be achieved via a highly-multiplex qPCR method. We designed and validated a single-tube one-step genotype-specific qPCR assay for detection of cfHPV16DNA in human plasma using >8,000 genomes spanning 18 genotypes. Amplicons were optimized for cfHPVDNA fragment size. The cfHPV16DNA qPCR amplicons spanned 16 % of the HPV16 genome. Amplicons were conserved in a median of 99.0 % of 3,944 genomes in silico. The 95 % lower limit of detection was 0.35 genome copies/reaction and the limit of blank was 0. Multiplexing achieved a tenfold improvement in sensitivity compared with single amplicons using in silico simulations of cfHPVDNA fragmentation, which was in close agreement with experimental observations. An assay was replicated for HPV18 with similar observations. Among 36 patients with head/neck mucosal carcinomas (26 HPV-positive, 12 HPV-negative), there was 100 % concordance with tissue HPV status and with NavDx digital PCR. Pre-treatment specimens with sub-genomic cfHPVDNA concentration were detected. False negatives were observed with single amplicons but not with this multiplexed method. Among 17 patients with post-treatment landmark specimens, there was 100 % PPV and 100 % NPV for recurrence. This assay is specific for plasma cfHPVDNA detection and prognostic for recurrence. Sub-genomic sensitivity was in close agreement with in silico simulations. The format might be more accessible than dPCR or NGS for longitudinal testing.

LncRNA Recognition-Associated CpG Island Detection and Methylation Analysis.

CpG islands (CGIs) are rare, interspersed DNA sequences, which possess a significant deviation from background genomic distribution by exhibiting patterns of GC-rich and CpG-rich sequence, the density of which provides a good classification feature for long noncoding RNA (lncRNA) promoters. By reviewing previous CpG-related studies, we consider that the transcription regulation of about half of the human genes, mostly housekeeping (HK) genes, involves CGIs, their methylation states, CpG spacing, and other chromosomal parameters. However, the precise CGI definition and positioning of CGIs within gene structures, as well as specific CGI-associated regulatory mechanisms, all remain to be elucidated at individual gene and gene family levels, together with consideration of species and lineage specificity. Although previous studies have already classified CGIs into high-CpG (HCGI), intermediate-CpG (ICGI), and low-CpG (LCGI) densities based on CpG density variation, the correlation between CGI density and gene expression regulation, such as co-regulation of CGIs and TATA-box on HK genes, is not clear. Here, we introduce such a problem-solving protocol for human genome annotation, which is based on a combination of GTEx, JBLA, and GO analysis. Next, we discuss why CGI-associated genes are most likely regulated by HCGI and tend to be HK genes; The HCGI/TATA± and LCGI/TATA± combinations show different GO enrichment, whereas the ICGI/TATA± combination is less characteristic than LCGI/TATA± based on GO enrichment analysis.

The future of personalized medicine in Saudi Arabia: Opportunities and challenges.

Personalized medicine is a healthcare approach that designs treatment plans of each patient, considering genetic, environmental, and lifestyle factors. This model leverages genomic information, advanced diagnostics, and data analytics to predict disease risk, optimize prevention strategies, and provide customized treatments. In Saudi Arabia, personalized medicine is gaining momentum, driven by the country's Vision 2030 initiative, which aims to transform the healthcare sector by integrating advanced medical technologies and improving healthcare delivery. The Kingdom has made significant strides in genomics and bioinformatics, with initiatives such as the Saudi Human Genome Program and advancements in institutions i.e.,King Faisal Specialist Hospital and Research Centre. Continued investment in research, education, and technology, alongside international collaborations, will be crucial in overcoming these challenges and realizing the full potential of personalized medicine. This review explores the current state, challenges, and future prospects of personalized medicine in Saudi Arabia, highlighting its transformative impact on healthcare delivery and patient outcomes.

Basic Epigenetic Mechanisms.

The human genome consists of 23 chromosome pairs (22 autosomes and one pair of sex chromosomes), with 46 chromosomes in a normal cell. In the interphase nucleus, the 2 m long nuclear DNA is assembled with proteins forming chromatin. The typical mammalian cell nucleus has a diameter between 5 and 15μm in which the DNA is packaged into an assortment of chromatin assemblies. The human brain has over 3000 cell types, including neurons, glial cells, oligodendrocytes, microglial, and many others. Epigenetic processes are involved in directing the organization and function of the genome of each one of the 3000 brain cell types. We refer to epigenetics as the study of changes in gene function that do not involve changes in DNA sequence. These epigenetic processes include histone modifications, DNA modifications, nuclear RNA, and transcription factors. In the interphase nucleus, the nuclear DNA is organized into different structures that are permissive or a hindrance to gene expression. In this chapter, we will review the epigenetic mechanisms that give rise to cell type-specific gene expression patterns.

Trajectory of human migration: insights from autosomal and non-autosomal variant clustering patterns

Genetic variations present in the Y chromosomal and mitochondrial DNA provide the mole-cular basis to support the archeological and anthropological evidence that formulates the theories for describing the trajectory of human migration, which started almost 200,000 years ago out of Africa. These genetic variations have long been used as ancestry informative markers (AIMs) in forensics and evolutionary studies, primarily because of their uniparental inheritance and lack of recombination, despite the fact that gender-specific gene flow and socio-cultural practices may cause discrepancies. Moreover, the genetic markers on the Y chromosome constitute only a minor fraction of the entire human genome. Here, we analyzed over 75 million genetic variants (single nucleotide variants (SNVs) and short insertion-deletion (InDels)) within consecutive 2500000 base pair windows in the autosomal as well as non-autosomal chromosomes of 22 populations in four major geographic regions that are cataloged in the 1000 Genomes Project to understand the clustering patterns of the autosomal and non-autosomal variants. While autosomal and X-chromosomal variants cluster the populations of similar geographic regions together, Y-chromosomal variants constantly place the East Asian Japanese and the European Finnish populations in a single clade in hierarchical clusters. This comprehensive genome-wide analysis essentially introduces new insights into mapping the path of human migration based on the Y-chromosomal and other chromosomal variants.

Quantitative Real-Time PCR for Circular RNA Detection and Analysis.

In eukaryotes, nearly 2% of the genome represented by the coding proteins. However, emerging evidence suggest more than 75% of the human genome referred to as noncoding part also plays a crucial role in governing major regulatory pathways. Noncoding RNAs can be categorized into several groups, such as microRNAs (miRNAs), small nuclear RNA (snRNAs), small nucleolar RNA (snoRNAs), transfer RNA (tRNA), and circular RNA (circRNAs), which contribute to this regulatory landscape. Circular RNAs (circRNAs) are identified as a new class of regulatory noncoding RNAs with gene regulatory roles by acting as miRNA or RNA binding protein sponges or interacting with proteins. Researchers employ quantitative real-time PCR methods to examine circular RNA expression utilizing divergent primers for identification and quantification.

Ancient DNA elucidates the migration and evolutionary history of northern and southern populations in East Asia.

Over the past decade, the continuous development of ancient genomic technology and research has significantly advanced our understanding of human history. Since 2017, large-scale studies of ancient human genomes in East Asia, particularly in China, have emerged, resulting in a wealth of ancient genomic data from various time periods and locations, which has provided new insights into the genetic history of East Asian populations over tens of thousands of years. Especially since 2022, there emerged a series of new research progresses in the genetic histories of the northern and southern Chinese populations within the past 10,000 years. However, there is currently no systematic review focused on these recent ancient genomic studies in East Asia. Therefore, this article emphasizes the study of ancient human genomes in China and systematically reviews the genetic patterns and migration history of populations in East Asia since the Late Paleolithic. Existing research indicates that by at least 19,000 years ago, there was a north-south differentiation among ancient East Asian populations, leading to different genetic lineages divided by the Qinling-Huaihe line. Gene flow and interactions between northern and southern East Asians began in the Early Neolithic and were further strengthened from the Mid-Neolithic. By the historical period, northern East Asian ancestry played a profound role in the genetic components of southern populations, shaping the genetic structure of present-day Chinese populations. Throughout this process, ancient populations in northern and southern China also engaged in extensive interactions through coastal and inland routes with populations from surrounding regions, including Siberia, Japan, Korea, Southeast Asia, and Pacific islands, playing a crucial role in the formation of different linguistic groups. These studies have charted the evolutionary and interaction history of East Asian populations over tens of thousands of years; yet, many unresolved mysteries remain. Further exploration is needed through ancient genomic data from additional time periods and broader geographic areas to facilitate a more comprehensive and detailed investigation, thereby advancing related scientific questions.

Current approaches in CRISPR-Cas systems for diabetes.

In the face of advancements in health care and a shift towards healthy lifestyle, diabetes mellitus (DM) still presents as a global health challenge. This chapter explores recent advancements in the areas of genetic and molecular underpinnings of DM, addressing the revolutionary potential of CRISPR-based genome editing technologies. We delve into the multifaceted relationship between genes and molecular pathways contributing to both type1 and type 2 diabetes. We highlight the importance of how improved genetic screening and the identification of susceptibility genes are aiding in early diagnosis and risk stratification. The spotlight then shifts to CRISPR-Cas9, a robust genome editing tool capable of various applications including correcting mutations in type 1 diabetes, enhancing insulin production in T2D, modulating genes associated with metabolism of glucose and insulin sensitivity. Delivery methods for CRISPR to targeted tissues and cells are explored, including viral and non-viral vectors, alongside the exciting possibilities offered by nanocarriers. We conclude by discussing the challenges and ethical considerations surrounding CRISPR-based therapies for DM. These include potential off-target effects, ensuring long-term efficacy and safety, and navigating the ethical implications of human genome modification. This chapter offers a comprehensive perspective on how genetic and molecular insights, coupled with the transformative power of CRISPR, are paving the way for potential cures and novel therapeutic approaches for DM.

Identifying somatic driver mutations in cancer with a language model of the human genome

Identifying somatic driver mutations in cancer with a language model of the human genome

A multi-modal transformer for cell type-agnostic regulatory predictions.

Sequence-based deep learning models have emerged as powerful tools for deciphering the cis-regulatory grammar of the human genome but cannot generalize to unobserved cellular contexts. Here, we present EpiBERT, a multi-modal transformer that learns generalizable representations of genomic sequence and cell type-specific chromatin accessibility through a masked accessibility-based pre-training objective. Following pre-training, EpiBERT can be fine-tuned for gene expression prediction, achieving accuracy comparable to the sequence-only Enformer model, while also being able to generalize to unobserved cell states. The learned representations are interpretable and useful for predicting chromatin accessibility quantitative trait loci (caQTLs), regulatory motifs, and enhancer-gene links. Our work represents a step toward improving the generalization of sequence-based deep neural networks in regulatory genomics.

Study of the genomics and transcriptomics profiles of male-infertility genes in human prostate cancer: an in silico analysis

The World Health Organization has considered the infertility as an international public health problem. Infertility affect nearly 1 in 7 couples and male component contributes to 50% of infertility cases. There is a clear link between male infertility and some cancers such as testicular germ cell, prostate and colon cancers. Two possibilities support this finding: 1) Cancer treatments can affect the fertility factors 2) Genetic profile of infertility genes have been altered in cancer patients. Although the previously published researches have mostly focused on the first factor, no article has yet confirmed the role of genetic factors. In this in silico study, we collected the large number of genes (n = 17703) involved in infertility. These genes were collected from NGS panel tests of male infertility and comprehensive literature review or online data base. The Prostate Adenocarcinoma genomic and transcriptomics raw data were downloaded from the cBioPortal Cancer dataset. This included with 494 patients of Prostate Cancer with 494 mutation data, 489 with CNA and 493 with RNA seqV2 data. TCGA RNA-Seq raw data was extracted in R using the cgdsr extension package with a threshold of ±2 relative to normal samples. The observed data showed that male infertility genes have been distributed through the human genome. Among the 17703 analyzed genes of this study, the genomic profile of three genes including OR9Q1, H4C6 and PSG7 were changed approximately in 100% of (n = 493) patients. In most of patients (>98%), genetic alteration was related to change in gene expression. In conclusion, this study showed that the genomic and transcriptomics patterns of some male-infertility genes are notably altered in patients of prostate cancer and suggested a possible role of genetic factors in occurrence of infertility in cancer patients. Our information can be used as a source for the design of genetic database of male-infertility.

Effect of a LINE 1 DNA Sequence on Expression of Long Human Genes

Although LINE1 DNA sequence elements are well known for their ability to replicate and move autonomously within the human genome, these features are observed in only a small proportion (0.02%) of the total human LINE1 population. Nearly all of the total ~500,000 LINE1 elements are fragments of full-length LINE1 and are inactive for autonomous replication or movement. Truncated, inactive LINE1 sequences are found throughout the human genome including within the body of protein-coding genes, and this intragenic population is the subject of the study described here. The goal was to extend what is known about the properties of intragenic LINE1 sequences. The study was carried out with t1519, a truncated LINE1 sequence composed of the 3’ terminal ~1500 bp of the ~6000 bp full length LINE1 element, and with the sequences of three human chromosomes 16, 17 and 18, that are rich in t1519 sequences. NCBI BLAST was used to identify t1519-containing genes in each chromosome, and the length and expression level of those genes was compared with control genes lacking t1519. A striking result was observed in the case of long protein-coding genes, genes longer than 140 kb. All had one or more t1519 sequences in the gene body, all in introns. An effect on the level of gene expression was also observed. Low expression (&lt;50 TPM) was found in all long, t1519 positive genes while much higher levels (500-600 TPM) were found with genes in the common length range (&gt;&lt; 140 kb) regardless of the presence of t1519. Similar results were obtained when lncRNA genes were studied instead of protein-coding ones. The results are interpreted to support a strong suppressive effect of t1519 on expression of long protein coding genes and also on certain lncRNA genes. It is suggested that the suppressive effect is due to a need for the cell to limit the overall level of transcription it can support.