Regions Of Human Genome Research Articles

Ribosomal protein L24 mediates mammalian microRNA processing in an evolutionarily conserved manner

To investigate the mechanism(s) underlying the expression of primate-specific microRNAs (miRs), we sought DNA regulatory elements and proteins mediating expression of the primate-specific hsa-miR-608 (miR-608), which is located in the SEMA4G gene and facilitates the cholinergic blockade of inflammation by targeting acetylcholinesterase mRNA. ‘Humanized’ mice carrying pre-miR-608 flanked by 250 bases of endogenous sequences inserted into the murine Sema4g gene successfully expressed miR-608. Moreover, by flanking miR-608 by shortened fragments of its human genome region we identified an active independent promoter within the 150 nucleotides 5′ to pre-miR-608, which elevated mature miR-608 levels by 100-fold in transfected mouse- and human-originated cells. This highlighted a regulatory role of the 5′ flank as enabling miR-608 expression. Moreover, pull-down of the 150-base 5′ sequence revealed its interaction with ribosomal protein L24 (RPL24), implicating an additional mechanism controlling miR-608 levels. Furthermore, RPL24 knockdown altered the expression of multiple miRs, and RPL24 immunoprecipitation indicated that up- or down-regulation of the mature miRs depended on whether their precursors bind RPL24 directly. Finally, further tests showed that RPL24 interacts directly with DDX5, a component of the large microprocessor complex, to inhibit miR processing. Our findings reveal that RPL24, which has previously been shown to play a role in miR processing in Arabidopsis thaliana, has a similar evolutionarily conserved function in miR biogenesis in mammals. We thus characterize a novel extra-ribosomal role of RPL24 in primate miR regulation.Graphical abstract

The CUT&RUN greenlist: genomic regions of consistent noise are effective normalizing factors for quantitative epigenome mapping.

Cleavage Under Targets and Release Using Nuclease (CUT&RUN) is a recent development for epigenome mapping, but its unique methodology can hamper proper quantitative analyses. As traditional normalization approaches have been shown to be inaccurate, we sought to determine endogenous normalization factors based on the human genome regions of constant nonspecific signal. This constancy was determined by applying Shannon's information entropy, and the set of normalizer regions, which we named the 'Greenlist', was extensively validated using publicly available datasets. We demonstrate here that the greenlist normalization outperforms the current top standards, and remains consistent across different experimental setups, cell lines and antibodies; the approach can even be applied to different species or to CUT&Tag. Requiring no additional experimental steps and no added cost, this approach can be universally applied to CUT&RUN experiments to greatly minimize the interference of technical variation over the biological epigenome changes of interest.

Epigenetic Regulation of Cardiomyocyte Maturation by Arginine Methyltransferase CARM1.

During the neonatal stage, the cardiomyocyte undergoes a constellation of molecular, cytoarchitectural, and functional changes known collectively as cardiomyocyte maturation to increase myocardial contractility and cardiac output. Despite the importance of cardiomyocyte maturation, the molecular mechanisms governing this critical process remain largely unexplored. We leveraged an in vivo mosaic knockout system to characterize the role of Carm1, the founding member of protein arginine methyltransferase, in cardiomyocyte maturation. Using a battery of assays, including immunohistochemistry, immuno-electron microscopy imaging, and action potential recording, we assessed the effect of loss of Carm1 function on cardiomyocyte cell growth, myofibril expansion, T-tubule formation, and electrophysiological maturation. Genome-wide transcriptome profiling, H3R17me2a chromatin immunoprecipitation followed by sequencing, and assay for transposase-accessible chromatin with high-throughput sequencing were used to investigate the mechanisms by which CARM1 (coactivator-associated arginine methyltransferase 1) regulates cardiomyocyte maturation. Finally, we interrogated the human syntenic region to the H3R17me2a chromatin immunoprecipitation followed by sequencing peaks for single-nucleotide polymorphisms associated with human heart diseases. We report that mosaic ablation of Carm1 disrupts multiple aspects of cardiomyocyte maturation cell autonomously, leading to reduced cardiomyocyte size and sarcomere thickness, severe loss and disorganization of T tubules, and compromised electrophysiological maturation. Genomics study demonstrates that CARM1 directly activates genes that underlie cardiomyocyte cytoarchitectural and electrophysiological maturation. Moreover, our study reveals significant enrichment of human heart disease-associated single-nucleotide polymorphisms in the human genomic region syntenic to the H3R17me2a chromatin immunoprecipitation followed by sequencing peaks. This study establishes a critical and multifaceted role for CARM1 in regulating cardiomyocyte maturation and demonstrates that deregulation of CARM1-dependent cardiomyocyte maturation gene expression may contribute to human heart diseases.

ZSCAN4-binding motif-TGCACAC is conserved and enriched in CA/TG microsatellites in both mouse and human genomes.

The Zinc finger and SCAN domain containing 4 (ZSCAN4) protein, expressed transiently in pluripotent stem cells, gametes, and early embryos, extends telomeres, enhances genome stability, and improves karyotypes in mouse embryonic stem (mES) cells. To gain insights into the mechanism of ZSCAN4 function, we identified genome-wide binding sites of endogenous ZSCAN4 protein using ChIP-seq technology in mouse and human ES cells, where the expression of endogenous ZSCAN4 was induced by treating cells with retinoic acids or by overexpressing DUX4. We revealed that both mouse and human ZSCAN4 bind to the TGCACAC motif located in CA/TG microsatellite repeats, which are known to form unstable left-handed duplexes called Z-DNA that can induce double-strand DNA breaks and mutations. These ZSCAN4 binding sites are mostly located in intergenic and intronic regions of the genomes. By generating ZSCAN4 knockout in human ES cells, we showed that ZSCAN4 does not seem to be involved in transcriptional regulation. We also found that ectopic expression of mouse ZSCAN4 enhances the suppression of chromatin at ZSCAN4-binding sites. These results together suggest that some of the ZSCAN4 functions are mediated by binding to the error-prone regions in mouse and human genomes.

CmVCall: An automated and adjustable nanopore analysis pipeline for heteroplasmy detection of the control region in human mitochondrial genome

Genetic associations between human mitochondrial DNA (mtDNA) heteroplasmy and mitochondrial diseases, aging, and cancer have been elaborated, contributing a lot to the further understanding of mtDNA polymorphic spectrum in anthropology, population, and forensic genetics. In the past decade, heteroplasmy detection using Sanger sequencing and next generation sequencing (NGS) was hampered by the former’s inefficiency and the latter’s inherent bias due to amplification and mapping of short reads, respectively. Nanopore sequencing stands out for its ability to yield long contiguous segments of DNA, providing a new insight into heterogeneity authentication. In addition to MinION from Oxford Nanopore Technologies, an alternative nanopore sequencer QNome (Qitan Technology) has also been applied to various biological research and the forensic applicability of this platform has been proved recently. In this study, we evaluated the performance of four commonly used variant callers in the heterogeneity authentication of the control region of human mtDNA based on simulations of different ratios generated by mixing QNome nanopore sequencing reads of two synthetic sequences. Then, an open-source and python-based nanopore analytics pipeline, CmVCall was developed and incorporated multiple programs including reads filtering, removal of nuclear mitochondrial sequences (NUMTs), alignment, optional ‘Correction’ mode, and heterogeneity identification. CmVCall can achieve high precision, accuracy, and recall of 100%, 99.9%, and 92.3% with a 5% heteroplasmy level in ‘Correction’ mode. Moreover, blood, saliva, and hair shaft samples from monozygotic (MZ) twins were used for heterogeneity evaluation and comparison with the NGS data. Results of MZ twin samples showed that CmVCall could identify more point heteroplasmy sites, revealing significant levels of inter- and intra-individual mtDNA polymorphism. In conclusion, we believe that this analysis pipeline will lay a solid foundation for the development of a comprehensive nanopore analysis pipeline targeting the whole mitochondrial genome.

Concentration of inverted repeats along human DNA.

This work aims to describe the observed enrichment of inverted repeats in the human genome; and to identify and describe, with detailed length profiles, the regions with significant and relevant enriched occurrence of inverted repeats. The enrichment is assessed and tested with a recently proposed measure (z-scores based measure). We simulate a genome using an order 7 Markov model trained with the data from the real genome. The simulated genome is used to establish the critical values which are used as decision thresholds to identify the regions with significant enriched concentrations. Several human genome regions are highly enriched in the occurrence of inverted repeats. This is observed in all the human chromosomes. The distribution of inverted repeat lengths varies along the genome. The majority of the regions with severely exaggerated enrichment contain mainly short length inverted repeats. There are also regions with regular peaks along the inverted repeats lengths distribution (periodic regularities) and other regions with exaggerated enrichment for long lengths (less frequent). However, adjacent regions tend to have similar distributions.

COVID-19 mRNA vaccines as hypothetical epigenetic players: Results from an in silico analysis, considerations and perspectives

ObjectivesTo investigate in silico the occurrence of epigenetic crosstalk by nucleotide sequence complementarity between the BNT162b2 mRNA vaccine and whole human genome, including coding and noncoding (nc)RNA genes. To correlate these results with those obtained with the original spike (S) gene of Severe Acute Respiratory Syndrome CoronaVirus-2 (SARS-CoV-2). MethodsThe publicly available FASTA sequence of the BNT162b2 mRNA vaccine and the SARS-CoV-2 isolate Wuhan-Hu-1 S gene (NC_045512.2) were used separately as key input to the Ensembl.org library to evaluate base pair match to human GRCh38 genome. Human coding and noncoding genes harboring hits were assessed for functional activity and health effects using bioinformatics tools and GWAS databases. ResultsThe BLAT analysis against the human GRCh38 genome revealed a total of 37 hits for BNT162b2 mRNA and no hits for the SARS-CoV-2 S gene. More specifically, BNT162b2 mRNA matched 19 human genes whose protein products are variously involved in enzyme reactions, nucleotide or cation binding, signaling, and carrier functions.In BLASTN analysis of ncRNA genes, BNT162b2 mRNA and SARS-CoV-2 S gene matched 17 and 24 different human genomic regions, respectively. Overall, characterization of the matched noncoding sequences revealed stronger interference with epigenetic pathways for BNT162b2 mRNA compared with the original S gene. ConclusionThis pivotal in silico analysis shows that SARS-CoV-2 S gene and the BNT162b2 mRNA vaccine exhibit Watson-Crick nucleotide complementarity with human coding or noncoding genes. Although they do not share the same complementarity pattern, both may disrupt epigenetic mechanisms in target cells, potentially leading to long-term complications.

A Computational Method for Identification of Functional SNPs in Human Noncoding Genome Regions based on Multi-feature Mining

<p>Single Nucleotide Polymorphism (SNP) is the variant on a single nucleotide in the genome. Functional SNP, as one of the most important molecular markers in disease research, has been widely used in various research fields, such as tumor pathogenesis, disease diagnosis and treatment, prognostic evaluation, drug development, etc. The number of functional SNPs in noncoding genome regions is much more than that in coding regions, and their detection is more difficult. In this work, a multi-feature mining based computational method is proposed to predict the functional SNPs in human noncoding genomes. We first analyzed the sequence properties, evolutionary conservation properties and epigenetic modification signal properties of the sample SNPs. Statistical methods together with multiple annotation data from genomes and epigenetics were used to mine high-dimensional discriminative features subsequently. In particular, the allele-specific features were designed to distinguish the function of SNPs with close locations. The random forest method was used to conduct feature dimension reduction and classification. The 10-fold cross-validation result showed the Area Under the Receiver Operating Characteristic Curve (AUC) of our method improved by 16.9% and 43.4% over existing methods GWAVA and CADD, respectively, illustrating that the allele-specific based features can help to distinguish functional and netural SNPs with near locations.</p> <p> </p>

IEssLnc: quantitative estimation of lncRNA gene essentialities with meta-path-guided random walks on the lncRNA-protein interaction network.

Gene essentiality is defined as the extent to which a gene is required for the survival and reproductive success of a living system. It can vary between genetic backgrounds and environments. Essential protein coding genes have been well studied. However, the essentiality of non-coding regions is rarely reported. Most regions of human genome do not encode proteins. Determining essentialities of non-coding genes is demanded. We developed iEssLnc models, which can assign essentiality scores to lncRNA genes. As far as we know, this is the first direct quantitative estimation to the essentiality of lncRNA genes. By taking the advantage of graph neural network with meta-path-guided random walks on the lncRNA-protein interaction network, iEssLnc models can perform genome-wide screenings for essential lncRNA genes in a quantitative manner. We carried out validations and whole genome screening in the context of human cancer cell-lines and mouse genome. In comparisons to other methods, which are transferred from protein-coding genes, iEssLnc achieved better performances. Enrichment analysis indicated that iEssLnc essentiality scores clustered essential lncRNA genes with high ranks. With the screening results of iEssLnc models, we estimated the number of essential lncRNA genes in human and mouse. We performed functional analysis to find that essential lncRNA genes interact with microRNAs and cytoskeletal proteins significantly, which may be of interest in experimental life sciences. All datasets and codes of iEssLnc models have been deposited in GitHub (https://github.com/yyZhang14/iEssLnc).

PALM: a powerful and adaptive latent model for prioritizing risk variants with functional annotations.

The findings from genome-wide association studies (GWASs) have greatly helped us to understand the genetic basis of human complex traits and diseases. Despite the tremendous progress, much effects are still needed to address several major challenges arising in GWAS. First, most GWAS hits are located in the non-coding region of human genome, and thus their biological functions largely remain unknown. Second, due to the polygenicity of human complex traits and diseases, many genetic risk variants with weak or moderate effects have not been identified yet. To address the above challenges, we propose a powerful and adaptive latent model (PALM) to integrate cell-type/tissue-specific functional annotations with GWAS summary statistics. Unlike existing methods, which are mainly based on linear models, PALM leverages a tree ensemble to adaptively characterize non-linear relationship between functional annotations and the association status of genetic variants. To make PALM scalable to millions of variants and hundreds of functional annotations, we develop a functional gradient-based expectation-maximization algorithm, to fit the tree-based non-linear model in a stable manner. Through comprehensive simulation studies, we show that PALM not only controls false discovery rate well, but also improves statistical power of identifying risk variants. We also apply PALM to integrate summary statistics of 30 GWASs with 127 cell type/tissue-specific functional annotations. The results indicate that PALM can identify more risk variants as well as rank the importance of functional annotations, yielding better interpretation of GWAS results. The source code is available at https://github.com/YangLabHKUST/PALM. Supplementary data are available at Bioinformatics online.

Systemic interindividual epigenetic variation in humans is associated with transposable elements and under strong genetic control

BackgroundGenetic variants can modulate phenotypic outcomes via epigenetic intermediates, for example at methylation quantitative trait loci (mQTL). We present the first large-scale assessment of mQTL at human genomic regions selected for interindividual variation in CpG methylation, which we call correlated regions of systemic interindividual variation (CoRSIVs). These can be assayed in blood DNA and do not reflect interindividual variation in cellular composition.ResultsWe use target-capture bisulfite sequencing to assess DNA methylation at 4086 CoRSIVs in multiple tissues from each of 188 donors in the NIH Gene-Tissue Expression (GTEx) program. At CoRSIVs, DNA methylation in peripheral blood correlates with methylation and gene expression in internal organs. We also discover unprecedented mQTL at these regions. Genetic influences on CoRSIV methylation are extremely strong (median R2=0.76), cumulatively comprising over 70-fold more human mQTL than detected in the most powerful previous study. Moreover, mQTL beta coefficients at CoRSIVs are highly skewed (i.e., the major allele predicts higher methylation). Both surprising findings are independently validated in a cohort of 47 non-GTEx individuals. Genomic regions flanking CoRSIVs show long-range enrichments for LINE-1 and LTR transposable elements; the skewed beta coefficients may therefore reflect evolutionary selection of genetic variants that promote their methylation and silencing. Analyses of GWAS summary statistics show that mQTL polymorphisms at CoRSIVs are associated with metabolic and other classes of disease.ConclusionsA focus on systemic interindividual epigenetic variants, clearly enhanced in mQTL content, should likewise benefit studies attempting to link human epigenetic variation to the risk of disease.

GSEL: a fast, flexible python package for detecting signatures of diverse evolutionary forces on genomic regions.

GSEL is a computational framework for calculating the enrichment of signatures of diverse evolutionary forces in a set of genomic regions. GSEL can flexibly integrate any sequence-based evolutionary metric and analyze sets of human genomic regions identified by genome-wide assays (e.g. GWAS, eQTL, *-seq). The core of GSEL's approach is the generation of empirical null distributions tailored to the allele frequency and linkage disequilibrium structure of the regions of interest. We illustrate the application of GSEL to variants identified from a GWAS of body mass index, a highly polygenic trait. GSEL is implemented as a fast, flexible and user-friendly python package. It is available with demonstration data at https://github.com/abraham-abin13/gsel_vec. Supplementary data are available at Bioinformatics online.

Phosphorylation-Mediated Activation of β-Catenin-TCF4-CEGRs/ALCDs Pathway Is an Essential Event in Development of Aggressive Hepatoblastoma.

Hepatoblastoma (HBL), a deadly malignancy in children, is the most common type of pediatric liver cancer. We recently demonstrated that β-catenin, phosphorylated at S675 (ph-S675-β-catenin), causes pathological alterations in fibrolamellar hepatocellular carcinoma (FLC), by activating oncogenes and fibrotic genes via human genomic regions, known as cancer-enhancing genomic regions or aggressive liver cancer domains (CEGRs/ALCDs). The aim of this study was to determine the role of the ph-S675-β-catenin-TCF4-CEGRs/ALCDs pathway in HBL. The ph-S675-β-catenin-TCF4-CEGRs/ALCDs pathway was examined in a large cohort of HBL specimens, in HBL cell lines HepG2 and Huh6, and in patient-derived xenografts (PDXs). β-catenin is phosphorylated at S675 in a large portion of tested HBL patients. In these patients, ph-S675-β-catenin forms complexes with TCF4 and opens CEGRs/ALCDs-dependent oncogenes for transcription, leading to a massive overexpression of the oncogenes. The inhibition of the β-catenin-TCF4-CEGRs/ALCDs axis inhibits the proliferation of cancer cells and tumor growth in HBL cell lines and HBL-PDXs. The ph-S675-β-catenin is abundant in mitotic cells. We found that markers of HBL Glypican 3 (GPC3) and Alpha Fetoprotein (AFP) are increased in HBL patients by β-catenin-TCF4-p300 complexes. The phosphorylation-mediated activation of the β-catenin-TCF4-p300-CEGRs/ALCDs pathway increases oncogene expression in patients with aggressive liver cancer and promotes the development of hepatoblastoma.

Improvement of mutated peptide identification through MS/MS signals searching against the protein libraries generated from transcriptome and translatome

Single-nucleotide variants (SNVs) in the coding region of human genome, termed as nonsynonymous SNVs (nsSNVs), are regarded a causal factor of cancer. The cancer related SNVs have not been widely confirmed at protein level. Translatome is referred to the active mRNA population associated with ribosomes and is measurable through ribosome-nascent chain complex sequencing (RNC-seq). Herein, an approach was proposed, in which the protein library derived from transcriptome or translatome was generated and served for MS/MS signals searching. A cell line of human colorectal cancer, HCT116, was cultured and its mRNAs, ribosome-bound mRNAs and proteins were extracted and measured in parallel. The nsSNVs calling from transcriptome or translatome were taken to construct the protein libraries with single amino acid variants (SAVs). Meanwhile, another protein library with SAVs was made by COSMIC dataset. The MS/MS data were acquired from HCT116 proteins and were searched for the corresponding peptides against the protein libraries derived from transcriptome, translatome and COSMIC, resulting in 258, 146 and 62 SAV peptides identified, respectively. Of these peptides, 96% of peptides come from the translatome library were overlapped with that from transcriptome, whereas only three peptides from the COSMIC library were co-identified by the other two libraries. The corresponding MS/MS spectra of these identified SAV peptides were further assessed by posterior error probability (PEP). The SAV peptides from the transcriptome or translatome library possessed significantly lower PEP values as compared with that from the COSMIC library. Importantly, further evaluation with different PEP thresholds appeared the percentiles of the remaining SAV peptides from translatome consistently higher than that from transcriptome. MS/MS signal searching against the translatome library, therefore, has been proven as an efficient approach to identify SAV peptides.

Contribution of CRISPRable DNA to human complex traits

CRISPR-Cas is a powerful genome editing tool for various species and human cell lines, widely used in many research areas including studying the mechanisms, targets, and gene therapies of human diseases. Recent developments have even allowed high-throughput genetic screening using the CRISPR system. However, due to the practical and ethical limitations in human gene editing research, little is known about whether CRISPR-editable DNA segments could influence human complex traits or diseases. Here, we investigated the human genomic regions condensed with different CRISPR Cas enzymes’ protospacer-adjacent motifs (PAMs). We found that Cas enzymes with GC-rich PAMs could interfere more with the genomic regions that harbor enriched heritability for human complex traits and diseases. The results linked GC content across the genome to the functional genomic elements in the heritability enrichment of human complex traits. We provide a genetic overview of the effects of high-throughput genome editing on human complex traits.

Sex-specific epigenetic development in the mouse hypothalamic arcuate nucleus pinpoints human genomic regions associated with body mass index.

Recent genome-wide association studies corroborate classical research on developmental programming indicating that obesity is primarily a neurodevelopmental disease strongly influenced by nutrition during critical ontogenic windows. Epigenetic mechanisms regulate neurodevelopment; however, little is known about their role in establishing and maintaining the brain’s energy balance circuitry. We generated neuron and glia methylomes and transcriptomes from male and female mouse hypothalamic arcuate nucleus, a key site for energy balance regulation, at time points spanning the closure of an established critical window for developmental programming of obesity risk. We find that postnatal epigenetic maturation is markedly cell type and sex specific and occurs in genomic regions enriched for heritability of body mass index in humans. Our results offer a potential explanation for both the limited ontogenic windows for and sex differences in sensitivity to developmental programming of obesity and provide a rich resource for epigenetic analyses of developmental programming of energy balance.

β-catenin cancer-enhancing genomic regions axis is involved in the development of fibrolamellar hepatocellular carcinoma.

Fibrolamellar hepatocellular carcinoma (FLC) is a disease that occurs in children and young adults. The development of FLC is associated with creation of a fusion oncoprotein DNAJB1‐PKAc kinase, which activates multiple cancer‐associated pathways. The aim of this study was to examine the role of human genomic regions, called cancer‐enhancing genomic regions or aggressive liver cancer domains (CEGRs/ALCDs), in the development of FLC. Previous studies revealed that CEGRs/ALCDs are located in multiple oncogenes and cancer‐associated genes, regularly silenced in normal tissues. Using the regulatory element locus intersection (RELI) algorithm, we searched a large compendium of chromatin immunoprecipitation–sequencing (ChIP) data sets and found that CEGRs/ALCDs contain regulatory elements in several human cancers outside of pediatric hepatic neoplasms. The RELI algorithm further identified components of the β‐catenin–TCF7L2/TCF4 pathway, which interacts with CEGRs/ALCDs in several human cancers. Particularly, the RELI algorithm found interactions of transcription factors and chromatin remodelers with many genes that are activated in patients with FLC. We found that these FLC‐specific genes contain CEGRs/ALCDs, and that the driver of FLC, fusion oncoprotein DNAJB1‐PKAc, phosphorylates β‐catenin at Ser675, resulting in an increase of β‐catenin–TCF7L2/TCF4 complexes. These complexes increase a large family of CEGR/ALCD‐dependent collagens and oncogenes. The DNAJB1‐PKAc–β‐catenin–CEGR/ALCD pathway is preserved in lung metastasis. The inhibition of β‐catenin in FLC organoids inhibited the expression of CEGRs/ALCDs‐dependent collagens and oncogenes, preventing the formation of the organoid's structure. Conclusion: This study provides a rationale for the development of β‐catenin‐based therapy for patients with FLC.

GREAP: a comprehensive enrichment analysis software for human genomic regions.

The rapid development of genomic high-throughput sequencing has identified a large number of DNA regulatory elements with abundant epigenetics markers, which promotes the rapid accumulation of functional genomic region data. The comprehensively understanding and research of human functional genomic regions is still a relatively urgent work at present. However, the existing analysis tools lack extensive annotation and enrichment analytical abilities for these regions. Here, we designed a novel software, Genomic Region sets Enrichment Analysis Platform (GREAP), which provides comprehensive region annotation and enrichment analysis capabilities. Currently, GREAP supports 85 370 genomic region reference sets, which cover 634 681 107 regions across 11 different data types, including super enhancers, transcription factors, accessible chromatins, etc. GREAP provides widespread annotation and enrichment analysis of genomic regions. To reflect the significance of enrichment analysis, we used the hypergeometric test and also provided a Locus Overlap Analysis. In summary, GREAP is a powerful platform that provides many types of genomic region sets for users and supports genomic region annotations and enrichment analyses. In addition, we developed a customizable genome browser containing >400000000 customizable tracks for visualization. The platform is freely available at http://www.liclab.net/Greap/view/index.

Abstract 6344: HLA and non-HLA associations with childhood and adolescent Hodgkin lymphoma risk

Abstract The genetic etiology for Hodgkin lymphoma (HL) has been investigated with findings reported in both human leukocyte antigens (HLA) and non-HLA genomic regions. However, results of genetic association studies that focus on HL developed among children and adolescent individuals are limited. Given the historically high survival rate, it is reasonable to leverage available genetic data for survivors of childhood/adolescent HL for this investigation. Utilizing existing data from the St. Jude Lifetime Cohort, the Childhood Cancer Survivor Study (CCSS) original cohort and CCSS expansion cohort, we performed a fixed-effects meta-analysis of three genome-wide association studies for a total of 1,286 HL cases, 6,824 other childhood cancer cases and 373 non-cancer controls, all of whom are of European ancestry. Three independent SNPs in the HLA locus (rs28383311, Odds Ratio [OR] = 1.80, P = 2.14×10-21; rs3129198, OR = 1.52, P = 2.05×10-14; rs3129890, OR = 1.51, P = 6.21×10-13) were identified using step-wise conditional logistic regression. HLA SNP rs28383311 had a moderate correlation (r2 = 0.46) with rs2858870 reported previously by Cozen et al. (Blood, 2012) in the HLA-DRA gene region in adolescent/young adults onset HL. HLA SNP rs3129198 had a perfect correlation (r2 = 1.0) with rs2281389 (HLA-DPB1) reported previously by Moutsianas et al. (Blood, 2011) in mostly adults-onset HL. In contrast, SNP rs3129890 had a low correlation (r2 = 0.15) with rs2395185 (HLA-DRA) reported previously by Urayama et al. (JNCI, 2012) in HL cases diagnosed across a wide age range between 16 and 80 years old. Our analysis also identified additional SNPs for non-HLA loci at genome-wide significance level including: 1) rs1432297 (OR = 1.30, P = 2.5×10-8), which is in moderate correlation (r2=0.52) with previously reported rs1432295 (REL); 2) rs13279159 (OR = 1.32, P = 1.7×10-8), which is in high correlation (r2=0.75) with previously reported rs2019960 (PVT1); and 3) rs3824662 (OR = 1.52, P = 3.9×10-10), which had a high correlation (r2 = 0.91) with previously reported rs3781093 (GATA3). In addition, a novel uncommon SNP with a large effect size (rs117361561, OR = 1.95, P = 2.50×10-8, minor allele frequency = 0.02) was identified and mapped to PDGFD, a plausible gene for HL susceptibility. Twelve out 18 (67%) previously reported genome-wide significant non-HLA SNPs were replicated with P < 0.05 based on our meta-analysis. By analyzing early onset HL within pediatric and adolescent age range, we further dissected the associations in HLA locus by replicating three independent SNPs. We also found a novel non-HLA locus and replicated the majority of previous findings in the non-HLA region, suggesting mostly overlapping as well as potentially unique genetic etiology for HL risk across different ages of onset. Citation Format: Cheng Chen, Nan Song, Xiaojun Sun, Qian Dong, Zhenghong Li, Hui Wang, Smita Bhatia, Heather Mulder, John Easton, Jinghui Zhang, Yutaka Yasui, Gregory T. Armstrong, Kirsten K. Ness, Melissa M. Hudson, Leslie L. Robison, Zhaoming Wang. HLA and non-HLA associations with childhood and adolescent Hodgkin lymphoma risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 6344.

Sex-specific epigenetic development in the mouse hypothalamic arcuate nucleus pinpoints human genomic regions associated with body mass index

Sex-specific epigenetic development in the mouse hypothalamic arcuate nucleus pinpoints human genomic regions associated with body mass index