Biology subjects

Orozco, L.

Publications and source records attributed to Orozco, L..

5 recordsLinked to original sources

bioRxiv2026

Ancient Mitogenomes from Belize Provide Insights into the Mobility and Migration of Ancient Communities in Mesoamerica and the Caribbean.

Maya peoples have undergone several largescale demographic transformations over the past 3000 years, including the formation and depopulation of large urban centers, climatic events, and multiple colonial regimes. Archaeological and stable isotope evidence from across the Maya lowlands throughout these periods paints a picture of a demographically mobile population with complex and dynamic relationships among some of the largest urban polities in antiquity. The nature of the genomic relationship between ancient Maya urban centers, as well as their relationship with present-day Maya communities, however, remains under-characterized. Here, we present mitogenomic data of 16 ancient Maya Ancestors recovered from interments in the ancient Maya cities of Caracol and Santa Rita Corozal located in Western and Northern Belize. These ancient data were combined with 110 newly collected contemporary individuals from Northern Belize, along with nearly 600 previously published ancient and contemporary comparative mitogenomes recovered from sites spanning Mesoamerica and the Caribbean to reconstruct paleodemographic and mobility patterns of maternal lineages through time. Our results are consistent with broadly interconnected Maya populations that have maintained maternal genetic continuity across much of the Holocene, and which are not structured by linguistic family.

genetics↗

bioRxiv2023

Whole mitogenome analysis highlights demographic history and shared connections among distal Indigenous groups of Mexico Complete mitogenome sequencing from 60 Mexican Native American groups

The study of mitochondrial DNA is a valuable tool to delve into the demographic history of human populations. Particularly in the Americas, five widespread Native American specific mitochondrial lineages have been identified. Here we included the complete mitogenome sequencing of 572 Indigenous individuals belonging to 60 populations spanning the Mexican territory. Our results show a great diversity of matrilineages widespread across the country, revealing shared mtDNA haplogroups in populations from distant regions. We identified all the five main Native American haplogroups clades, including 83 different subhaplogroups, from which nine are novel. The most frequent of the novel haplogroups was A2+64. A phylogenetic inference suggests that A2+64 comes from an ancestral maternal lineage that spread into the Caribbean islands. Additionally, a demographic reconstruction from whole mitogenomes showed an exponential increase in female Ne around 10 Ka ago in all the tested regions. All these findings suggest a genetic persistence through Mexico and possibly the Americas, in agreement with the model of the Mesoamerican-related expansion into the Caribbean and South America.

genetics↗

bioRxiv2021

Mct11 deficiency alters hepatic glucose metabolism and energy homeostasis

Genetic variation at the SLC16A11 locus contributes to the disproportionate impact of type 2 diabetes (T2D) on Latino populations. We recently demonstrated that T2D risk variants reduce SLC16A11 liver expression and function of MCT11, the monocarboxylate transporter encoded by the SLC16A11 gene. Here, we show that SLC16A11 expression within the liver is primarily localized to the low oxygen pericentral region, and that T2D risk variants disrupt oxygen-regulated SLC16A11 expression in human hepatocytes. Under physiologic oxygen conditions, MCT11 deficiency alters hepatocyte glucose metabolism, resulting in elevated intracellular lactate and a metabolic shift toward triacylglycerol accumulation. We also demonstrate an impact of Mct11 deficiency on glucose and lipid metabolism in Slc16a11 knockout mice, which display physiological changes that are observed in individuals with T2D. Our findings provide mechanistic insight into how SLC16A11 disruption impacts hepatic energy metabolism and T2D risk, and highlight MCT11-mediated regulation of lactate levels as a potential therapeutic target.

genetics↗

bioRxiv2019

Improving drug discovery using image-based multiparametric analysis of epigenetic landscape.

With the advent of automatic cell imaging and machine learning, high-content phenotypic screening has become the approach of choice for drug discovery due to its ability to extract drug specific multilayered data and compare it to known profiles. In the field of epigenetics such screening approaches has suffered from the lack of tools sensitive to selective epigenetic perturbations. Here we describe a novel approach Microscopic Imaging of Epigenetic Landscapes (MIEL) that captures patterns of nuclear staining of epigenetic marks (e.g. acetylated and methylated histones) and employs machine learning to accurately distinguish between such patterns (1). We demonstrated that MIEL has superior resolution compared to conventional intensity thresholding techniques and enables efficient detection of epigenetically active compounds, function-based classification, flagging possible off-target effects and even predict novel drug function. We validated MIEL platform across multiple cells lines and using dose-response curves to insure the robustness of this approach for the high content high throughput drug discovery.

cell biology↗

bioRxiv2017

Epigenome-wide association in adipose tissue from the METSIM cohort identifies novel loci and the involvement of adipocytes and macrophages in diabetes traits

Most epigenome-wide association studies to date have been conducted in blood. However, metabolic syndrome is mediated by a dysregulation of adiposity and therefore it is critical to study adipose tissue in order to understand the effects of this syndrome on epigenomes. To determine if natural variation in DNA methylation was associated with metabolic syndrome traits, we profiled global methylation levels in subcutaneous abdominal adipose tissue. We measured association between 32 clinical traits related to diabetes and obesity in 201 people from the Metabolic Syndrome In Men cohort. We performed epigenome-wide association studies between DNA methylation levels and traits, and identified associations for 13 clinical traits in 21 loci. We prioritized candidate genes in these loci using eQTL, and identified 18 high confidence candidate genes, including known and novel genes associated with diabetes and obesity traits. Using methylation deconvolution, we examined which cell types may be mediating the associations, and concluded that most of the loci we identified were specific to adipocytes. We determined whether the abundance of cell types varies with metabolic traits, and found that macrophages increased in abundance with the severity of metabolic syndrome traits. Finally, we developed a DNA methylation based biomarker to assess type II diabetes risk in adipose tissue. In conclusion, our results demonstrate that profiling DNA methylation in adipose tissue is a powerful tool for understanding the molecular effects of metabolic syndrome on adipose tissue, and can be used in conjunction with traditional genetic analyses to further characterize this disorder.

genetics↗