The EN-TEx resource of multi-tissue personal epigenomes & variant-impact models.

Understanding how genetic variants impact molecular phenotypes is a key goal of functional genomics, currently hindered by reliance on a single haploid reference genome. Here, we present the EN-TEx resource of 1,635 open-access datasets from four donors (∼30 tissues × âˆ¼15 assays). The datasets are mapped to matched, diploid genomes with long-read phasing and structural variants, instantiating a catalog of >1 million allele-specific loci. These loci exhibit coordinated activity along haplotypes and are less conserved than corresponding, non-allele-specific ones. Surprisingly, a deep-learning transformer model can predict the allele-specific activity based only on local nucleotide-sequence context, highlighting the importance of transcription-factor-binding motifs particularly sensitive to variants. Furthermore, combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci. It also enables models for transferring known eQTLs to difficult-to-profile tissues (e.g., from skin to heart). Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.

Characterizing the Major Structural Variant Alleles of the Human Genome.

In order to provide a comprehensive resource for human structural variants (SVs), we generated long-read sequence data and analyzed SVs for fifteen human genomes. We sequence resolved 99,604 insertions, deletions, and inversions including 2,238 (1.6 Mbp) that are shared among all discovery genomes with an additional 13,053 (6.9 Mbp) present in the majority, indicating minor alleles or errors in the reference. Genotyping in 440 additional genomes confirms the most common SVs in unique euchromatin are now sequence resolved. We report a ninefold SV bias toward the last 5 Mbp of human chromosomes with nearly 55% of all VNTRs (variable number of tandem repeats) mapping to this portion of the genome. We identify SVs affecting coding and noncoding regulatory loci improving annotation and interpretation of functional variation. These data provide the framework to construct a canonical human reference and a resource for developing advanced representations capable of capturing allelic diversity.

KRAS Dimerization Impacts MEK Inhibitor Sensitivity and Oncogenic Activity of Mutant KRAS.

The mechanism by which the wild-type KRAS allele imparts a growth inhibitory effect to oncogenic KRAS in various cancers, including lung adenocarcinoma (LUAD), is poorly understood. Here, using a genetically inducible model of KRAS loss of heterozygosity (LOH), we show that KRAS dimerization mediates wild-type KRAS-dependent fitness of human and murine KRAS mutant LUAD tumor cells and underlies resistance to MEK inhibition. These effects are abrogated when wild-type KRAS is replaced by KRASD154Q, a mutant that disrupts dimerization at the α4-α5 KRAS dimer interface without changing other fundamental biochemical properties of KRAS, both in vitro and in vivo. Moreover, dimerization has a critical role in the oncogenic activity of mutant KRAS. Our studies provide mechanistic and biological insights into the role of KRAS dimerization and highlight a role for disruption of dimerization as a therapeutic strategy for KRAS mutant cancers.

Biology and Clinical Implications of the 19q13 Aggressive Prostate Cancer Susceptibility Locus.

Genome-wide association studies (GWAS) have identified rs11672691 at 19q13 associated with aggressive prostate cancer (PCa). Here, we independently confirmed the finding in a cohort of 2,738 PCa patients and discovered the biological mechanism underlying this association. We found an association of the aggressive PCa-associated allele G of rs11672691 with elevated transcript levels of two biologically plausible candidate genes, PCAT19 and CEACAM21, implicated in PCa cell growth and tumor progression. Mechanistically, rs11672691 resides in an enhancer element and alters the binding site of HOXA2, a novel oncogenic transcription factor with prognostic potential in PCa. Remarkably, CRISPR/Cas9-mediated single-nucleotide editing showed the direct effect of rs11672691 on PCAT19 and CEACAM21 expression and PCa cellular aggressive phenotype. Clinical data demonstrated synergistic effects of rs11672691 genotype and PCAT19/CEACAM21 gene expression on PCa prognosis. These results provide a plausible mechanism for rs11672691 associated with aggressive PCa and thus lay the ground work for translating this finding to the clinic.

Impacts of Neanderthal-Introgressed Sequences on the Landscape of Human Gene Expression.

Regulatory variation influencing gene expression is a key contributor to phenotypic diversity, both within and between species. Unfortunately, RNA degrades too rapidly to be recovered from fossil remains, limiting functional genomic insights about our extinct hominin relatives. Many Neanderthal sequences survive in modern humans due to ancient hybridization, providing an opportunity to assess their contributions to transcriptional variation and to test hypotheses about regulatory evolution. We developed a flexible Bayesian statistical approach to quantify allele-specific expression (ASE) in complex RNA-seq datasets. We identified widespread expression differences between Neanderthal and modern human alleles, indicating pervasive cis-regulatory impacts of introgression. Brain regions and testes exhibited significant downregulation of Neanderthal alleles relative to other tissues, consistent with natural selection influencing the tissue-specific regulatory landscape. Our study demonstrates that Neanderthal-inherited sequences are not silent remnants of ancient interbreeding but have measurable impacts on gene expression that contribute to variation in modern human phenotypes.

Genetic Drivers of Epigenetic and Transcriptional Variation in Human Immune Cells.

Characterizing the multifaceted contribution of genetic and epigenetic factors to disease phenotypes is a major challenge in human genetics and medicine. We carried out high-resolution genetic, epigenetic, and transcriptomic profiling in three major human immune cell types (CD14+ monocytes, CD16+ neutrophils, and naive CD4+ T cells) from up to 197 individuals. We assess, quantitatively, the relative contribution of cis-genetic and epigenetic factors to transcription and evaluate their impact as potential sources of confounding in epigenome-wide association studies. Further, we characterize highly coordinated genetic effects on gene expression, methylation, and histone variation through quantitative trait locus (QTL) mapping and allele-specific (AS) analyses. Finally, we demonstrate colocalization of molecular trait QTLs at 345 unique immune disease loci. This expansive, high-resolution atlas of multi-omics changes yields insights into cell-type-specific correlation between diverse genomic inputs, more generalizable correlations between these inputs, and defines molecular events that may underpin complex disease risk.

A Cre-driven allele-conditioning line to interrogate CD4+ conventional T cells.

CD4+ T cells share common developmental pathways with CD8+ T cells, and upon maturation, CD4+ T conventional T (Tconv) cells lack phenotypic markers that distinguish these cells from FoxP3+ T regulatory cells. We developed a tamoxifen-inducible ThPOKCreERT2.hCD2 line with Frt sites inserted on either side of the CreERT2-hCD2 cassette, and a Foxp3Ametrine-FlpO strain, expressing Ametrine and FlpO in Foxp3+ cells. Breeding these mice resulted in a CD4conviCreERT2-hCD2 line that allows for the specific manipulation of a gene in CD4+ Tconv cells. As FlpO removes the CreERT2-hCD2 cassette, CD4+ Treg cells are spared from Cre activity, which we refer to as allele conditioning. Comparison with an E8IiCreERT2.GFP mouse that enables inducible targeting of CD8+ T cells, and deletion of two inhibitory receptors, PD-1 and LAG-3, in a melanoma model, support the fidelity of these lines. These engineered mouse strains present a resource for the temporal manipulation of genes in CD4+ T cells and CD4+ Tconv cells.

Transcriptional regulation and chromatin architecture maintenance are decoupled functions at the Sox2 locus.

How distal regulatory elements control gene transcription and chromatin topology is not clearly defined, yet these processes are closely linked in lineage specification during development. Through allele-specific genome editing and chromatin interaction analyses of the Sox2 locus in mouse embryonic stem cells, we found a striking disconnection between transcriptional control and chromatin architecture. We traced nearly all Sox2 transcriptional activation to a small number of key transcription factor binding sites, whose deletions have no effect on promoter-enhancer interaction frequencies or topological domain organization. Local chromatin architecture maintenance, including at the topologically associating domain (TAD) boundary downstream from the Sox2 enhancer, is widely distributed over multiple transcription factor-bound regions and maintained in a CTCF-independent manner. Furthermore, partial disruption of promoter-enhancer interactions by ectopic chromatin loop formation has no effect on Sox2 transcription. These findings indicate that many transcription factors are involved in modulating chromatin architecture independently of CTCF.

Opportunities and tradeoffs in single-cell transcriptomic technologies.

Recent technological and algorithmic advances enable single-cell transcriptomic analysis with remarkable depth and breadth. Nonetheless, a persistent challenge is the compromise between the ability to profile high numbers of cells and the achievement of full-length transcript coverage. Currently, the field is progressing and developing new and creative solutions that improve cellular throughput, gene detection sensitivity and full-length transcript capture. Furthermore, long-read sequencing approaches for single-cell transcripts are breaking frontiers that have previously blocked full transcriptome characterization. We here present a comprehensive overview of available options for single-cell transcriptome profiling, highlighting the key advantages and disadvantages of each approach.

Investigating the potential of single-cell DNA methylation data to detect allele-specific methylation and imprinting.

Allele-specific methylation (ASM) is an epigenetic modification whereby one parental allele becomes methylated and the other unmethylated at a specific locus. ASM is most often driven by the presence of nearby heterozygous variants that influence methylation, but also occurs somatically in the context of genomic imprinting. In this study, we investigate ASM using publicly available single-cell reduced representation bisulfite sequencing (scRRBS) data on 608 B cells sampled from six healthy B cell samples and 1,230 cells from 11 chronic lymphocytic leukemia (CLL) samples. We developed a likelihood-based criterion to test whether a CpG exhibited ASM, based on the distributions of methylated and unmethylated reads both within and across cells. Applying our likelihood ratio test, 65,998 CpG sites exhibited ASM in healthy B cell samples according to a Bonferroni criterion (p < 8.4 × 10-9), and 32,862 CpG sites exhibited ASM in CLL samples (p < 8.5 × 10-9). We also called ASM at the sample level. To evaluate the accuracy of our method, we called heterozygous variants from the scRRBS data, which enabled variant-based calls of ASM within each cell. Comparing sample-level ASM calls to the variant-based measures of ASM, we observed a positive predictive value of 76%-100% across samples. We observed high concordance of ASM across samples and an overrepresentation of ASM in previously reported imprinted genes and genes with imprinting binding motifs. Our study demonstrates that single-cell bisulfite sequencing is a potentially powerful tool to investigate ASM, especially as studies expand to increase the number of samples and cells sequenced.

Ornaments for efficient allele-specific expression estimation with bias correction.

Allele-specific expression plays a crucial role in unraveling various biological mechanisms, including genomic imprinting and gene expression controlled by cis-regulatory variants. However, existing methods for quantification from RNA-sequencing (RNA-seq) reads do not adequately and efficiently remove various allele-specific read mapping biases, such as reference bias arising from reads containing the alternative allele that do not map to the reference transcriptome or ambiguous mapping bias caused by reads containing the reference allele that map differently from reads containing the alternative allele. We present Ornaments, a computational tool for rapid and accurate estimation of allele-specific transcript expression at unphased heterozygous loci from RNA-seq reads while correcting for allele-specific read mapping biases. Ornaments removes reference bias by mapping reads to a personalized transcriptome and ambiguous mapping bias by probabilistically assigning reads to multiple transcripts and variant loci they map to. Ornaments is a lightweight extension of kallisto, a popular tool for fast RNA-seq quantification, that improves the efficiency and accuracy of WASP, a popular tool for bias correction in allele-specific read mapping. In experiments with simulated and human lymphoblastoid cell-line RNA-seq reads with the genomes of the 1000 Genomes Project, we demonstrate that Ornaments improves the accuracy of WASP and kallisto, is nearly as efficient as kallisto, and is an order of magnitude faster than WASP per sample, with the additional cost of constructing a personalized index for multiple samples. Additionally, we show that Ornaments finds imprinted transcripts with higher sensitivity than WASP, which detects imprinted signals only at gene level.

Substitution of a single non-coding nucleotide upstream of TMEM216 causes non-syndromic retinitis pigmentosa and is associated with reduced TMEM216 expression.

Genome analysis of individuals affected by retinitis pigmentosa (RP) identified two rare nucleotide substitutions at the same genomic location on chromosome 11 (g.61392563 [GRCh38]), 69 base pairs upstream of the start codon of the ciliopathy gene TMEM216 (c.-69G>A, c.-69G>T [GenBank: NM_001173991.3]), in individuals of South Asian and African ancestry, respectively. Genotypes included 71 homozygotes and 3 mixed heterozygotes in trans with a predicted loss-of-function allele. Haplotype analysis showed single-nucleotide variants (SNVs) common across families, suggesting ancestral alleles within the two distinct ethnic populations. Clinical phenotype analysis of 62 available individuals from 49 families indicated a similar clinical presentation with night blindness in the first decade and progressive peripheral field loss thereafter. No evident systemic ciliopathy features were noted. Functional characterization of these variants by luciferase reporter gene assay showed reduced promotor activity. Nanopore sequencing confirmed the lower transcription of the TMEM216 c.-69G>T allele in blood-derived RNA from a heterozygous carrier, and reduced expression was further recapitulated by qPCR, using both leukocytes-derived RNA of c.-69G>T homozygotes and total RNA from genome-edited hTERT-RPE1 cells carrying homozygous TMEM216 c.-69G>A. In conclusion, these variants explain a significant proportion of unsolved cases, specifically in individuals of African ancestry, suggesting that reduced TMEM216 expression might lead to abnormal ciliogenesis and photoreceptor degeneration.

Maternal-biased H3K27me3 correlates with paternal-specific gene expression in the human morula.

Genomic imprinting is an epigenetic mechanism by which genes are expressed in a parental origin-dependent manner. We recently discovered that, like DNA methylation, oocyte-inherited H3K27me3 can also serve as an imprinting mark in mouse preimplantation embryos. In this study, we found H3K27me3 is strongly biased toward the maternal allele with some associated with DNA methylation-independent paternally expressed genes (PEGs) in human morulae. The H3K27me3 domains largely overlap with DNA partially methylated domains (PMDs) and occupy developmental gene promoters. Thus, our study not only reveals the H3K27me3 landscape but also establishes a correlation between maternal-biased H3K27me3 and PEGs in human morulae.

Long-read transcriptome sequencing reveals allele-specific variants at high resolution.

Disturbance in the regulation of transcript structure plays a crucial role in human disease. In a recent study, Glinos et al. characterized allele-specific transcript alterations in long-read RNA sequencing (RNA-seq) data derived from multiple human tissues and provide a high-resolution view of how disease-associated genetic variants affect transcript structure.

Patterns of mosaicism for sequence and copy-number variants discovered through clinical deep sequencing of disease-related genes in one million individuals.

DNA variants that arise after conception can show mosaicism, varying in presence and extent among tissues. Mosaic variants have been reported in Mendelian diseases, but further investigation is necessary to broadly understand their incidence, transmission, and clinical impact. A mosaic pathogenic variant in a disease-related gene may cause an atypical phenotype in terms of severity, clinical features, or timing of disease onset. Using high-depth sequencing, we studied results from one million unrelated individuals referred for genetic testing for almost 1,900 disease-related genes. We observed 5,939 mosaic sequence or intragenic copy number variants distributed across 509 genes in nearly 5,700 individuals, constituting approximately 2% of molecular diagnoses in the cohort. Cancer-related genes had the most mosaic variants and showed age-specific enrichment, in part reflecting clonal hematopoiesis in older individuals. We also observed many mosaic variants in genes related to early-onset conditions. Additional mosaic variants were observed in genes analyzed for reproductive carrier screening or associated with dominant disorders with low penetrance, posing challenges for interpreting their clinical significance. When we controlled for the potential involvement of clonal hematopoiesis, most mosaic variants were enriched in younger individuals and were present at higher levels than in older individuals. Furthermore, individuals with mosaicism showed later disease onset or milder phenotypes than individuals with non-mosaic variants in the same genes. Collectively, the large compendium of variants, disease correlations, and age-specific results identified in this study expand our understanding of the implications of mosaic DNA variation for diagnosis and genetic counseling.

HLAIImaster: a deep learning method with adaptive domain knowledge predicts HLA II neoepitope immunogenic responses.

While significant strides have been made in predicting neoepitopes that trigger autologous CD4+ T cell responses, accurately identifying the antigen presentation by human leukocyte antigen (HLA) class II molecules remains a challenge. This identification is critical for developing vaccines and cancer immunotherapies. Current prediction methods are limited, primarily due to a lack of high-quality training epitope datasets and algorithmic constraints. To predict the exogenous HLA class II-restricted peptides across most of the human population, we utilized the mass spectrometry data to profile >223 000 eluted ligands over HLA-DR, -DQ, and -DP alleles. Here, by integrating these data with peptide processing and gene expression, we introduce HLAIImaster, an attention-based deep learning framework with adaptive domain knowledge for predicting neoepitope immunogenicity. Leveraging diverse biological characteristics and our enhanced deep learning framework, HLAIImaster is significantly improved against existing tools in terms of positive predictive value across various neoantigen studies. Robust domain knowledge learning accurately identifies neoepitope immunogenicity, bridging the gap between neoantigen biology and the clinical setting and paving the way for future neoantigen-based therapies to provide greater clinical benefit. In summary, we present a comprehensive exploitation of the immunogenic neoepitope repertoire of cancers, facilitating the effective development of "just-in-time" personalized vaccines.

polyGBLUP: a modified genomic best linear unbiased prediction improved the genomic prediction efficiency for autopolyploid species.

Given the universality of autopolyploid species in nature, it is crucial to develop genomic selection methods that consider different allele dosages for autopolyploid breeding. However, no method has been developed to deal with autopolyploid data regardless of the ploidy level. In this study, we developed a modified genomic best linear unbiased prediction (GBLUP) model (polyGBLUP) through constructing additive and dominant genomic relationship matrices based on different allele dosages. polyGBLUP could carry out genomic prediction for autopolyploid species regardless of the ploidy level. Through comprehensive simulations and analysis of real data of autotetraploid blueberry and guinea grass and autohexaploid sweet potato, the results showed that polyGBLUP achieved higher prediction accuracy than GBLUP and its superiority was more obvious when the ploidy level of autopolyploids is high. Furthermore, when the dominant effect was added to polyGBLUP (polyGDBLUP), the greater the dominance degree, the more obvious the advantages of polyGDBLUP over the diploid models in terms of prediction accuracy, bias, mean squared error and mean absolute error. For real data, the superiority of polyGBLUP over GBLUP appeared in blueberry and sweet potato populations and a part of the traits in guinea grass population due to the high correlation coefficients between diploid and polyploidy genomic relationship matrices. In addition, polyGDBLUP did not produce higher prediction accuracy than polyGBLUP for most traits of real data as dominant genetic variance was not captured for these traits. Our study will be a significant promising method for genomic prediction of autopolyploid species.

Whole-genome sequences from wild-type and laboratory-evolved strains define the alleleome and establish its hallmarks.

The genomic diversity across strains of a species forms the genetic basis for differences in their behavior. A large-scale assessment of sequence variation has been made possible by the growing availability of strain-specific whole-genome sequences (WGS) and with the advent of large-scale databases of laboratory-acquired mutations. We define the Escherichia coli "alleleome" through a genome-scale assessment of amino acid (AA) sequence diversity in open reading frames across 2,661 WGS from wild-type strains. We observe a highly conserved alleleome enriched in mutations unlikely to affect protein function. In contrast, 33,000 mutations acquired in laboratory evolution experiments result in more severe AA substitutions that are rarely achieved by natural selection. Large-scale assessment of the alleleome establishes a method for the quantification of bacterial allelic diversity, reveals opportunities for synthetic biology to explore novel sequence space, and offers insights into the constraints governing evolution.

A small-molecule allele-selective transcriptional inhibitor of the MIF immune susceptibility locus.

Functional variants of the gene for the cytokine macrophage migration inhibitory factor (MIF) are defined by a 4-nucleotide promoter microsatellite (-794 CATT5-8, rs5844572) and confer risk for autoimmune, infectious, and oncologic diseases. We describe herein the discovery of a prototypic, small molecule inhibitor of MIF transcription with selectivity for high microsatellite repeat number and correspondingly high gene expression. Utilizing a high-throughput luminescent proximity screen, we identify 1-carbomethoxy-5-formyl-4,6,8-trihydroxyphenazine (CMFT) to inhibit the functional interaction between the transcription factor ICBP90 (namely, UHRF1) and the MIF -794 CATT5-8 promoter microsatellite. CMFT inhibits MIF mRNA expression in a -794 CATT5-8 length-dependent manner with an IC50 of 470 nM, and preferentially reduces ICBP90-dependent MIF mRNA and protein expression in high-genotypic versus low-genotypic MIF-expressing macrophages. RNA expression analysis also showed CMFT to downregulate MIF-dependent, inflammatory gene expression with little evidence of off-target metabolic toxicity. These findings provide proof-of-concept for advancing the pharmacogenomic development of precision-based MIF inhibitors for diverse autoimmune and inflammatory conditions.

Genome-wide chromatin accessibility reveals transcriptional regulation of heterosis in inter-subspecific hybrid rice.

The utilization of rice heterosis is essential for ensuring global food security; however, its molecular mechanism remains unclear. In this study, comprehensive analyses of accessible chromatin regions (ACRs), DNA methylation, and gene expression in inter-subspecific hybrid and its parents were performed to determine the potential role of chromatin accessibility in rice heterosis. The hybrid exhibited abundant ACRs, in which the gene ACRs and proximal ACRs were directly related to transcriptional activation rather than the distal ACRs. Regarding the dynamic accessibility contribution of the parents, paternal ZHF1015 transmitted a greater number of ACRs to the hybrid. Accessible genotype-specific target genes were enriched with overrepresented transcription factors, indicating a unique regulatory network of genes in the hybrid. Compared with its parents, the differentially accessible chromatin regions with upregulated chromatin accessibility were much greater than those with downregulated chromatin accessibility, reflecting a stronger regulation in the hybrid. Furthermore, DNA methylation levels were negatively correlated with ACR intensity, and genes were strongly affected by CHH methylation in the hybrid. Chromatin accessibility positively regulated the overall expression level of each genotype. ACR-related genes with maternal Z04A-bias allele-specific expression tended to be enriched during carotenoid biosynthesis, whereas paternal ZHF1015-bias genes were more active in carbohydrate metabolism. Our findings provide a new perspective on the mechanism of heterosis based on chromatin accessibility in inter-subspecific hybrid rice.