Biology subjects

Sauria, M. E. G.

Publications and source records attributed to Sauria, M. E. G..

10 recordsLinked to original sources

bioRxiv2026

Multiscale learning and topological analysis across complex postures enable robust nematode size quantification in pharmacological assays

Body size is an important trait that reflects animal development and physiology. In nematodes, precise measurement is valuable for linking variation in body dimensions to biological questions such as developmental timing, genetic regulation, and drug responses. However, robust size measurements can be difficult to obtain because nematodes can vary in curvature, have self-intersecting postures, and overlap with neighboring animals. Current image analysis software, such as CellProfiler, can measure isolated animals in straight postures but struggles with curly or overlapping animals. Here, we present NemaSize, an artificial intelligence (AI)-aided pipeline to measure Caenorhabditis nematode body sizes across complex postures using multi-scale learning and topology-aware skeletonization. Using You Only Look Once (YOLO) models trained at different spatial scales, NemaSize first identifies individual animals in a large field of view (FOV; 6.75 x 6.75 mm) and then performs high-resolution body segmentation in the region of interest (ROI). Next, NemaSize converts segmented body masks into topological graph representations, allowing curly and overlapping animals to be classified and skeletonized according to the body topology. NemaSize achieved less than 4% overall error in length and width measurements across all posture classes. Compared to CellProfiler, NemaSize demonstrated higher robustness for complex postures, including a 48% error reduction in length measurements for curly or self-overlapping animals. Application of NemaSize in high-throughput imaging assays further shows that NemaSize provides accurate quantification of Caenorhabditis briggsae larval development in response to the anthelmintic drug ivermectin, a task that was difficult for CellProfiler because of curly animal postures. Together, NemaSize provides a robust approach for automated body size quantification for Caenorhabditis nematodes and will support broad applications in high-throughput pharmacological and genetic screens. Beyond nematodes, NemaSize introduces a multiscale computational framework for analyzing elongated biological objects with complex topologies.

pharmacology and toxicology↗

bioRxiv2026

Global genomic diversity of the selfing nematode Caenorhabditis tropicalis correlates with geography

Self-fertilization reduces genetic diversity compared to outcrossing and hypothetically decreases the ability to adapt to diverse environments. Among Caenorhabditis nematodes, self-fertilization evolved three times independently in Caenorhabditis elegans, Caenorhabditis briggsae, and the more recently discovered Caenorhabditis tropicalis. To survey C. tropicalis genetic relatedness, the influence of geography and niche on species-wide variation, and the signatures of selection, we collected 785 wild strains, sequenced their genomes, and identified 622 distinct genotypes (isotypes). In contrast to C. elegans and C. briggsae, C. tropicalis relatedness shows substantial association with geography and no transcontinental selective sweeps or broadly sampled isotypes. Populations from the Hawaiian Islands or Taiwan harbor more genetic variation than populations from the Caribbean or Americas, suggesting a Pacific species origin similar to other members of the Elegans subclade. Punctuated genomic regions of extreme genetic variation pervade the genome. These hyper-divergent regions (HDRs) comprise less than 6% of the reference genome in any given strain despite harboring 73% of all variant sites and are enriched for genes likely involved in environmental adaptation. HDRs represent a shared genomic feature of self-fertilizing Caenorhabditis nematodes despite their independent evolutionary origins and suggest a mechanism to explain worldwide distributions despite low species-wide levels of genetic variation.

genomics↗

bioRxiv2025

Caenorhabditis briggsae ancestral genomic hyper-diversity contrasts with globally distributed genome-wide haplotypes

Comparative genomics provides a powerful framework to uncover the molecular and evolutionary mechanisms that shape genetic diversity within and across species, revealing how shared and lineage-specific processes influence their evolutionary trajectories through time. The nematode Caenorhabditis briggsae is distributed world-wide and is a comparative model to Caenorhabditis elegans in the biology of development, cellular mechanisms, neurobiology, genetic mappings of complex traits, and genome evolution. Following massive collection efforts by the nematode research community, we present the isolation of over 2,000 wild strains and analyses of genome sequences that catalog over six million single-nucleotide and insertion-deletion variants. This genome and strain resource provide a powerful means to interrogate the causal genetic bases of phenotypic variation for diverse traits. Additionally, we describe its global population structure and discover new and genetically distinct groups within this primarily self-fertilizing species, including groups of highly related strains that were sampled across different continents. We leverage expansive genetic variation to decipher the effects of linkage and selection on the distribution of genetic diversity across the genome and across geographic regions. Within the species, we find genomic regions with extremely high levels of genetic variation similar to hyper-divergent regions found in C. elegans and other species. These regions harbor new genes and variation enriched for environmental sensing and pathogen responses. In comparison to the outbreeding sister species Caenorhabditis nigoni, we conclude that long-term balancing selection has maintained substantial functional variation since the divergence from their outbreeding ancestor, likely in response to differences in the ecological niche. Overall, this massive strain resource enables future comparative genetics and genomics studies, including genome-wide association studies between Caenorhabditis species.

genomics↗

bioRxiv2023

Cross-species regulatory landscapes and elements revealed by novel joint systematic integration of human and mouse blood cell epigenomes

Knowledge of locations and activities of cis-regulatory elements (CREs) is needed to decipher basic mechanisms of gene regulation and to understand the impact of genetic variants on complex traits. Previous studies identified candidate CREs (cCREs) using epigenetic features in one species, making comparisons difficult between species. In contrast, we conducted an interspecies study defining epigenetic states and identifying cCREs in blood cell types to generate regulatory maps that are comparable between species, using integrative modeling of eight epigenetic features jointly in human and mouse in our Validated Systematic Integration (VISION) Project. The resulting catalogs of cCREs are useful resources for further studies of gene regulation in blood cells, indicated by high overlap with known functional elements and strong enrichment for human genetic variants associated with blood cell phenotypes. The contribution of each epigenetic state in cCREs to gene regulation, inferred from a multivariate regression, was used to estimate epigenetic state Regulatory Potential (esRP) scores for each cCRE in each cell type, which were used to categorize dynamic changes in cCREs. Groups of cCREs displaying similar patterns of regulatory activity in human and mouse cell types, obtained by joint clustering on esRP scores, harbored distinctive transcription factor binding motifs that were similar between species. An interspecies comparison of cCREs revealed both conserved and species-specific patterns of epigenetic evolution. Finally, we showed that comparisons of the epigenetic landscape between species can reveal elements with similar roles in regulation, even in the absence of genomic sequence alignment.

genomics↗

bioRxiv2021

Complete genomic and epigenetic maps of human centromeres

Existing human genome assemblies have almost entirely excluded highly repetitive sequences within and near centromeres, limiting our understanding of their sequence, evolution, and essential role in chromosome segregation. Here, we present an extensive study of newly assembled peri/centromeric sequences representing 6.2% (189.9 Mb) of the first complete, telomere-to-telomere human genome assembly (T2T-CHM13). We discovered novel patterns of peri/centromeric repeat organization, variation, and evolution at both large and small length scales. We also found that inner kinetochore proteins tend to overlap the most recently duplicated subregions within centromeres. Finally, we compared chromosome X centromeres across a diverse panel of individuals and uncovered structural, epigenetic, and sequence variation at single-base resolution across these regions. In total, this work provides an unprecedented atlas of human centromeres to guide future studies of their complex and critical functions as well as their unique evolutionary dynamics. One-sentence summaryDeep characterization of fully assembled human centromeres reveals their architecture and fine-scale organization, variation, and evolution.

genomics↗

bioRxiv2021

A complete reference genome improves analysis of human genetic variation

Compared to its predecessors, the Telomere-to-Telomere CHM13 genome adds nearly 200 Mbp of sequence, corrects thousands of structural errors, and unlocks the most complex regions of the human genome to clinical and functional study. Here we demonstrate how the new reference universally improves read mapping and variant calling for 3,202 and 17 globally diverse samples sequenced with short and long reads, respectively. We identify hundreds of thousands of novel variants per sample--a new frontier for evolutionary and biomedical discovery. Simultaneously, the new reference eliminates tens of thousands of spurious variants per sample, including up to 12-fold reduction of false positives in 269 medically relevant genes. The vast improvement in variant discovery coupled with population and functional genomic resources position T2T-CHM13 to replace GRCh38 as the prevailing reference for human genetics. One Sentence SummaryThe T2T-CHM13 reference genome universally improves the analysis of human genetic variation.

genomics↗

bioRxiv2021

Epigenetic Patterns in a Complete Human Genome

The completion of the first telomere-to-telomere human genome, T2T-CHM13, enables exploration of the full epigenome, removing limitations previously imposed by the missing reference sequence. Existing epigenetic studies omit unassembled and unmappable genomic regions (e.g. centromeres, pericentromeres, acrocentric chromosome arms, subtelomeres, segmental duplications, tandem repeats). Leveraging the new assembly, we were able to measure enrichment of epigenetic marks with short reads using k-mer assisted mapping methods. This granted array-level enrichment information to characterize the epigenetic regulation of these satellite repeats. Using nanopore sequencing data, we generated base level maps of the most complete human methylome ever produced. We examined methylation patterns in satellite DNA and revealed organized patterns of methylation along individual molecules. When exploring the centromeric epigenome, we discovered a distinctive dip in centromere methylation consistent with active sites of kinetochore assembly. Through long-read chromatin accessibility measurements (nanoNOMe) paired to CUT&RUN data, we found the hypomethylated region was extremely inaccessible and paired to CENP-A/B binding. With long-reads we interrogated allele-specific, longrange epigenetic patterns in complex macro-satellite arrays such as those involved in X chromosome inactivation. Using the single molecule measurements we can clustered reads based on methylation status alone distinguishing epigenetically heterogeneous and homogeneous areas. The analysis provides a framework to investigate the most elusive regions of the human genome, applying both long and short-read technology to grant new insights into epigenetic regulation.

genomics↗

bioRxiv2021

Temporal regulation of green and red cone specification in human retinas and retinal organoids

Trichromacy is unique to primates among mammals, enabled by blue (short/S), green (medium/M), and red (long/L) cones. In humans and Old World monkeys, cones make a poorly understood choice between M and L cone subtype fates. To determine mechanisms specifying M and L cones, we developed an approach to visualize expression of the highly similar M- and L-opsin mRNAs. M-opsin, but not L-opsin, was observed during early human eye development, suggesting that M cones are generated before L cones. In adult human tissue, the early-developing central retina contained a mix of M and L cones compared to the late-developing peripheral region, which contained a high proportion of L cones. Retinoic acid (RA)-synthesizing enzymes are highly expressed early in retinal development. High RA signaling early was sufficient to promote M cone fate and suppress L cone fate in retinal organoids. Across a human population sample, natural variation in the ratios of M and L cone subtypes was associated with a noncoding polymorphism in the NR2F2 gene, a mediator of RA signaling. Our data suggest that RA promotes M cone fate early in development to generate the pattern of M and L cones across the human retina.

developmental biology↗

bioRxiv2018

The repressive genome compartment is established early in the cell cycle before forming the lamina associated domains

Three-dimensional (3D) genome organization is thought to be important for regulation of gene expression. Chromosome conformation capture-based studies have uncovered ensemble organizational principles such as active (A) and inactive (B) compartmentalization. In addition, large inactive regions of the genome associate with the nuclear lamina, the Lamina Associated Domains (LADs). Here we investigate the dynamic relationship between A/B-compartment organization and the 3D organization of LADs. Using refined algorithms to identify active (A) and inactive (B) compartments from Hi-C data and to define LADs from DamID, we confirm that the LADs correspond to the B-compartment. Using specialized chromosome conformation paints, we show that LAD and A/B-compartment organization are dependent upon chromatin state and A-type lamins. By integrating single-cell Hi-C data with live cell imaging and chromosome conformation paints, we demonstrate that self-organization of the B-compartment within a chromosome is an early event post-mitosis and occurs prior to organization of these domains to the nuclear lamina.

genomics↗

bioRxiv2017

Measuring the reproducibility and quality of Hi-C data

Hi-C is currently the most widely used assay to investigate the 3D organization of the genome and to study its role in gene regulation, DNA replication, and disease. However, Hi-C experiments are costly to perform and involve multiple complex experimental steps; thus, accurate methods for measuring the quality and reproducibility of Hi-C data are essential to determine whether the output should be used further in a study. Using real and simulated data, we profile the performance of several recently proposed methods for assessing reproducibility of population Hi-C data, including HiCRep, GenomeDISCO, HiC-Spector and QuASAR-Rep. By explicitly controlling noise and sparsity through simulations, we demonstrate the deficiencies of performing simple correlation analysis on pairs of matrices, and we show that methods developed specifically for Hi-C data produce better measures of reproducibility. We also show how to use established (e.g., ratio of intra to interchromosomal interactions) and novel (e.g., QuASAR-QC) measures to identify low quality experiments. In this work, we assess reproducibility and quality measures by varying sequencing depth, resolution and noise levels in Hi-C data from 13 cell lines, with two biological replicates each, as well as 176 simulated matrices. Through this extensive validation and benchmarking of Hi-C data, we describe best practices for reproducibility and quality assessment of Hi-C experiments. We make all software publicly available at http://github.com/kundajelab/3DChromatin_ReplicateQC to facilitate adoption in the community.

genomics↗