Biology subjects

Macias-Velasco, J. F.

Publications and source records attributed to Macias-Velasco, J. F..

13 recordsLinked to original sources

bioRxiv2026

The genetic architecture of human DNA methylome variation

Population DNA methylome analyses remain largely confined to reference-defined genomic space despite extensive human genetic diversity. A central challenge is therefore to define comparable methylation phenotypes across diverse genomes and map the genetic architecture of methylome variation. Here, using 460 haplotypes from the Human Pangenome Reference Consortium Release 2, we develop two complementary pangenome-based frameworks: one compares methylation within homologous regions while retaining haplotype-specific structural configuration and CpG content; the other represents CpG island (CGI) variation at homologous loci as sequence-resolved alleles. We identified 47,039 CGI alleles, including 8,040 absent from CHM13; 62% were attributable to structural variants and 31% to small variants. Through local genealogies, we reconstructed CGI gain, loss and turnover, revealing how present-day methylation differences align with CGI evolutionary trajectories. We found that genome-wide, methylation variability was buffered against genetic diversity across more than 90% of the genome, with exceptions at extreme nucleotide diversity and locally around structural variants. Our methylation framework enabled population-scale allele-aware methylation quantitative trait locus (mQTL) mapping into non-reference and structurally complex sequence, where mQTL-associated intervals were enriched. mQTLs linked methylation to transcriptomic phenotypes, population differentiation and complex traits, supporting 8% of population differentially methylated regions and colocalizing with more than half of genome-wide association study loci. Together, our study redefines human methylome analysis and our findings reveal a genome-wide architecture of genetic-epigenetic coupling, reshaping how methylation variation is interpreted across human development and disease.

genetics↗

bioRxiv2026

Human panepigenome represents epigenomic diversity

The human pangenome captures genetic diversity beyond a single linear reference, yet conventional DNA methylome maps largely assume that the underlying CpG substrate is fixed. Here we present a first draft of the human panepigenome on DNA methylation, generated from 440 haplotype-resolved long-read methylomes spanning 26 globally distributed populations. This map jointly captures CpG presence, absence and methylation across diverse human haplotypes, revealing 12.8 million CpGs absent from GRCh38 and an average of 1.2 million variant-associated CpGs (var-CpGs) per methylome. Var-CpGs captured population-associated epigenomic variation beyond that represented by shared reference CpGs, and structural variants could create or remove entire CpG islands, frequently through mobile element insertions. Promoter var-CpG methylation was associated with transcript expression, with most associations persisting after adjustment for the underlying CpG-altering variant, whereas a subset showed evidence of mediation or variant-by-methylation interactions. CpG-altering variants were also enriched among molecular QTLs in HPRC2 and across GTEx tissues, and among clinically and pharmacogenomically annotated loci. Together, these results establish a haplotype-resolved framework in which human epigenomic diversity reflects not only variation in methylation level but also genetic variation in presence or absence of CpG substrates, providing a foundation for panepigenomic studies across tissues, populations and disease contexts.

genomics↗

bioRxiv2026

HPRC2: A human pangenome reference with near-complete coverage of common genetic variation

A pangenome reference overcomes the inherent limitation of any individual reference genome by integrating the variation present in a population. We present the Human Pangenome Reference Consortiums (HPRC) Release 2 (HPRC2), an openly available, second phase pangenome that is an approximately fivefold expansion in genome number over HPRC Release 1 (HPRC1) and measurable improvement in genome completeness, contiguity, and accuracy. Selecting samples with a principled algorithm prioritising common variant coverage, HPRC2 contributes 460 haplotypes that together capture over 99% of common variation observed in the All of Us Research Program v8 cohort. Combining high-coverage long and ultra-long reads with modern assemblers and polishers, we produce thousands of telomere-to-telomere (T2T) chromosomes, and relative to HPRC1 halve the number of structurally unreliable regions as well as individual base errors per haplotype. We complement the assemblies with whole genome multiple alignments and gene annotations, and derive formal pangenome coordinate systems for addressing off-reference variation, demonstrating that individual human genomes contain more than one hundred thousand variants not succinctly described with respect to existing reference genomes. We also present the first matched long-read backed pantranscriptome and panepigenome at this scale, provide continuous local-ancestry estimates spanning every genome, and outline a host of new tools and applications that leverage the pangenome resource for improved genomics analysis.

genomics↗

bioRxiv2026

Fully T2T pedigree assemblies reveal genetic stability and epigenetic plasticity of human centromeres across inheritance and cell-fate transitions

Centromeres are essential chromosome components yet remain poorly understood due to their highly repetitive sequence architecture. Using fully-phased telomere-to-telomere diploid assemblies from a three-generation pedigree integrated with long-read epigenomes from matched peripheral blood mononuclear cells, induced pluripotent stem cells, and neural progenitor cells, we generate allele-resolved single basepair resolution maps of centromere genetic and epigenetic dynamics across inheritance, reprogramming, and differentiation. We show that centromeric dip regions (CDRs), which define the functional core of centromeres, are positionally stable across generations and cell-fate transitions. In contrast, CDR epigenetic architecture is highly dynamic. Reprogramming markedly attenuates CDR hypomethylation, which is partially restored during differentiation in parallel with global hypomethylation of active alpha-satellite arrays and coordinated changes in nucleosome organization and protein occupancy. Centromeric remodeling is insulated from X-chromosome status, including Xa, Xi, and erosion. Finally, de novo mutations arising during reprogramming are enriched in centromeric regions but depleted within functional centromeric cores.

genomics↗

bioRxiv2026

Leveraging Human Pangenome for Improved Somatic Variant Detection

Somatic variant detection is technically challenging due to low variant allele fractions, the confounding presence of germline variation, and reference bias. Linear references such as GRCh38 miss sample-specific variation, causing misalignments and incorrect variant calls. Although telomere-to-telomere donor-specific assemblies (DSAs) accurately represent individual genomes, their application is limited by cost and technical barriers. Alternatively, the graph-based human pangenome provides a scalable framework to improve read alignment and perform genome inference. Here, we benchmarked somatic variant detection using GRCh38, graph-based pangenomes, and pangenome-inferred DSAs with a HapMap mixture dataset and the COLO829 melanoma cell line. Pangenome-guided alignment improves read mapping and somatic variant calling accuracy. Furthermore, personalized pangenomes partially reconstruct donor-specific genomic content, improving accuracy, reducing germline contamination, and enabling detection of events in loci absent or poorly represented in GRCh38. These findings demonstrate that graph-based and personalized pangenomes are effective strategies for enhancing somatic variant detection compared with GRCh38.

genomics↗

bioRxiv2025

A Pangenomic Method for Establishing a Somatic Variant Detection Resource in HapMap Mixtures

Somatic mosaicism is essential in human biology and disease, yet robust benchmarks are scarce. The SMaHT Consortium mixed six HapMap cell lines to create artificial somatic variants spanning 0.25% to 16.5% variant allele fractions. We developed a technology-agnostic method that builds pangenome graphs from individual assemblies to create unified benchmarking sets: > 6M single-nucleotide variants, 1.8M small insertions/deletions, 49K structural variations, and 10K mobile element insertions across autosomes, X, and mitochondrial chromosomes. We validated the variants using ultra-deep simulated reads and developed a binomial-based model to estimate coverage requirements for variant detection. Evaluating multiple callers showed CHM13 alignment improves structural variant detection and offers advantages in difficult-to-map regions compared to GRCh38. Systematic characterization showed regions with low detection rate are enriched in centromeres, satellite sequences, tandem repeats, and falsely duplicated genes. This accurate, versatile resource enables systematic evaluation of somatic variant detection technologies.

genomics↗

bioRxiv2021

Genetic, epigenetic, and environmental mechanisms govern allele-specific gene expression

Allele-specific expression (ASE) is a phenomenon where one allele is preferentially expressed over the other. Genetic and epigenetic factors cause ASE by altering the final allelic composition of a genes product, leading to expression imbalances that can have functional consequences on phenotypes. Environmental signals also impact allele-specific gene regulation, but how they contribute to this crosstalk remains understudied. Here, we explored how allelic genotype, parent-of-origin, tissue type, sex, and dietary fat simultaneously influence ASE biases in a F1 reciprocal cross mouse model. Male and female mice from a F1 reciprocal cross of the LG/J and SM/J strains were fed a high fat or low fat diet. We harnessed strain-specific variants to distinguish between two classes of ASE: parent-of-origin dependent (unequal expression based on an alleles parental origin) and sequence dependent (unequal expression based on an alleles nucleotide identity). We present a comprehensive map of ASE patterns in 2,853 genes across three metabolically-relevant tissues and nine environmental contexts. We found that both ASE classes are highly dependent on tissue type and environmental context. They vary across metabolic tissues, between males and females, and in response to dietary fat levels. Surprisingly, we found 45 genes with inconsistent ASE biases that switched direction across tissues and/or contexts (e.g. SM/J biased in one cohort, LG/J biased in another). We also integrated ASE and QTL data from populations at various degrees of intercrossing the LG/J and SM/J strains. ASE genes in these tissues are often enriched in QTLs for metabolic and musculoskeletal traits, highlighting how this orthogonal approach can prioritize candidate genes for functional validation. Together, our results provide novel insights into how genetic, epigenetic, and environmental mechanisms govern allele-specific gene regulation, which is an essential step towards deciphering the genotype to phenotype map.

genomics↗

bioRxiv2021

Parent-of-origin effects propagate through networks to shape metabolic traits

Parent-of-origin effects are unexpectedly common in complex traits, including metabolic and neurological diseases. Parent-of-origin effects can be modified by the environment, but the architecture of these gene-by-environmental effects on phenotypes remains to be unraveled. Previously, quantitative trait loci (QTL) showing context-specific parent-of-origin effects on metabolic traits were mapped in the F16 generation of an advanced intercross between LG/J and SM/J inbred mice. However, these QTL were not enriched for known imprinted genes, suggesting another mechanism is needed to explain these parent-of-origin effects phenomena. We propose that non-imprinted genes can generate complex parent-of-origin effects on metabolic traits through interactions with imprinted genes. Here, we employ data from mouse populations at different levels of intercrossing (F0, F1, F2, F16) of the LG/J and SM/J inbred mouse lines to test this hypothesis. Using multiple populations and incorporating genetic, genomic, and physiological data, we leverage orthogonal evidence to identify networks of genes through which parent-of-origin effects propagate. We identify a network comprised of 3 imprinted and 6 non-imprinted genes that show parent-of-origin effects. This epistatic network forms a nutritional responsive pathway and the genes comprising it jointly serve cellular functions associated with growth. We focus on 2 genes, Nnat and F2r, whose interaction associates with serum glucose levels across generations in high fat-fed females. Single-cell RNAseq reveals that Nnat and F2r are negatively correlated in pre-adipocytes along an adipogenic trajectory, a result that is consistent with our observations in bulk white adipose tissue.

genomics↗

bioRxiv2020

TRAP-based allelic translation efficiency imbalance analysis to identify genetic regulation of ribosome occupancy in specific cell types in vivo.

The alteration of gene expression due to variations in the sequences of transcriptional regulatory elements has been a focus of substantial inquiry in humans and model organisms. However, less is known about the extent to which natural variation contributes to post-transcriptional regulation. Allelic Expression Imbalance (AEI) is a classical approach for studying the association of specific haplotypes with relative changes in transcript abundance. Here, we piloted a new TRAP based approach to associate genetic variation with transcript occupancy on ribosomes in specific cell types, to determine if it will allow examination of Allelic Translation Imbalance (ATI), and Allelic Translation Efficiency Imbalance, using as a test case mouse astrocytes in vivo. We show that most changes of the mRNA levels on ribosomes were reflected in transcript abundance, though [~]1.5% of transcripts have variants that clearly alter loading onto ribosomes orthogonally to transcript levels. These variants were often in conserved residues and altered sequences known to regulate translation such as upstream ORFs, PolyA sites, and predicted miRNA binding sites. Such variants were also common in transcripts showing altered abundance, suggesting some genetic regulation of gene expression may function through post-transcriptional mechanisms. Overall, our work shows that naturally occurring genetic variants can impact ribosome occupancy in astrocytes in vivo and suggests that mechanisms may also play a role in genetic contributions to disease.

genetics↗

bioRxiv2020

Spontaneous restoration of functional β-cell mass in obese SM/J mice

Maintenance of functional {beta}-cell mass is critical to preventing diabetes, but the physiological mechanisms that cause {beta}-cell populations to thrive or fail in the context of obesity are unknown. High fat-fed SM/J mice spontaneously transition from hyperglycemic-obese to normoglycemic-obese with age, providing a unique opportunity to study {beta}-cell adaptation. Here, we characterize insulin homeostasis, islet morphology, and {beta}-cell function during SM/Js diabetic remission. As they resolve hyperglycemia, obese SM/J mice dramatically increase circulating and pancreatic insulin levels while improving insulin sensitivity. Immunostaining of pancreatic sections reveals that obese SM/J mice selectively increase {beta}-cell mass but not -cell mass. Obese SM/J mice do not show elevated {beta}-cell mitotic index, but rather elevated -cell mitotic index. Functional assessment of isolated islets reveals that obese SM/J mice increase glucose stimulated insulin secretion, decrease basal insulin secretion, and increase islet insulin content. These results establish that {beta}-cell mass expansion and improved {beta}-cell function underlie the resolution of hyperglycemia, indicating that obese SM/J mice are a valuable tool for exploring how functional {beta}-cell mass can be recovered in the context of obesity.

physiology↗

bioRxiv2019

Natural brown adipose expansion and remission of hyperglycemia in obese SM/J mice

Disruption of glucose homeostasis increases the risk of type II diabetes, cardiovascular disease, stroke, and cancer. We leverage a novel rodent model, the SM/J mouse, to understand glycemic control in obesity. On a high fat diet, obese SM/J mice initially develop impaired glucose tolerance and elevated fasting glucose. Strikingly, their glycemic dysfunction resolves by 30 weeks of age despite persistence of obesity. A prominent phenotype is that they dramatically expand their brown adipose depots as they resolve glycemic dysfunction. This occurs naturally and spontaneously on a high fat diet, with no temperature or genetic manipulation. When the brown adipose depot is removed from normoglycemic obese mice, fasting blood glucose and glucose tolerance revert to unhealthy levels, and animals become insulin resistant. We identified 267 genes whose expression changes in the brown adipose when the mice resolve their unhealthy glycemic parameters, and find the expanded tissue has a healthier expression profile of cytokines and extracellular matrix genes. We describe morphological, physiological, and transcriptomic changes that occur during the unique brown adipose expansion and remission of glycemic dysfunction in obese SM/J mice. Understanding this phenomenon in mice will open the door for innovative therapies aimed at improving glycemic control in obesity. Significance StatementSome obese individuals maintain normal glycemic control. Despite being obese, these individuals have low risk for metabolic complications, including type-II diabetes. If we better understood why some obese people maintain normoglycemia then we might develop new approaches for treating metabolic complications associated with obesity. However, the causative factors underlying glycemic control in obesity remain unknown. We discovered that, despite persistence of the obese state, SM/J mice enter into diabetic remission: returning to normoglycemia and reestablishing glucose tolerance and improving insulin sensitivity. A prominent phenotype is that they dramatically expand their brown adipose depots as they resolve glycemic dysfunction. Understanding this phenomenon in mice will open the door for innovative therapies aimed at improving glycemic control in obesity.

physiology↗

bioRxiv2019

Epistatic Networks Associated with Parent-of-Origin Effects on Metabolic Traits

Parent-of-origin effects (POE) are unexpectedly common in complex traits, including metabolic and neurological diseases. POE can also be modified by the environment, but the architecture of these gene-by-environmental effects on phenotypes remains to be unraveled. Previously, quantitative trait loci (QTL) showing context-specific POE on metabolic traits were mapped in the F16 generation of an advanced intercross between LG/J and SM/J inbred mice. However, these QTL were not enriched for known imprinted genes, suggesting another mechanism is needed to explain these POE phenomena. Here, we use a simple yet powerful F1 reciprocal cross model to test the hypothesis that non-imprinted genes can generate complex POE on metabolic traits through genetic interactions with imprinted genes. Male and female mice from a F1 reciprocal cross of LG/J and SM/J strains were fed either high or low fat diets. We generated expression profiles from three metabolically-relevant tissues: hypothalamus, white adipose, and liver. We identified two classes of parent-of-origin expression biases: genes showing parent-of-origin-dependent allele-specific expression and biallelic genes that are differentially expressed by reciprocal cross. POE patterns of both gene classes are highly tissue-and context-specific, sometimes occurring only in one sex and/or diet cohort in a particular tissue. We then constructed tissue-specific interaction networks among genes from these two classes of POE. A key subset of gene pairs show significant epistasis in the F16 LG/J x SM/J advanced intercross data in cases where the biallelic gene fell within a previously-identified metabolic POE QTL interval. We highlight one such interaction in adipose, between Nnat and Mogat1, which associates with POE on multiple adiposity traits. Both genes localize to the endoplasmic reticulum of adipocytes and play a role in adipogenesis. Additionally, expression of both genes is significantly correlated in human visceral adipose tissue. The genes and networks we present here represent a set of actionable interacting candidates that can be probed to further identify the machinery driving POE on complex traits.

systems biology↗

bioRxiv2018

Evaluation of North American Asian citrus psyllid (Hemiptera: Liviidae) population genetics by cytochrome P450 melt curve analysis

The Asian Citrus Psyllid (ACP) (Diaphorina citri) is a Hemipteran which feeds on Citrus and is the principal vector of the pathogen Candidatus Liberibacter asiaticus (Las); the primary causal agent of Huanglongbing (HLB) or citrus greening disease. Currently HLB is the single greatest threat to the American citrus industry. Previous work has shown that that Cytochrome P450 (CYP4) genes are associated with insecticidal resistance to neonicotinoid insecticides. Infection by Las has also been shown to affect the expression of CYP4 genes. In this study the genetic relationships of ACP populations was evaluated using melting curve analysis of CYP4 genes. Principal component analysis shows the presence of two potential haplotypes. The groups identified by principal component analysis are significantly different from each other (P < 0.05) for all CYP4 genes tested. All populations are most likely within 2-3 mutations of each other. The existence of these mutations sheds light on the potential evolution of ACP in North America. Indicating either coevolution with Las or difference in imidacloprid basal selective pressure in the United States and Mexico.

evolutionary biology↗