Biology subjects

Franklin, J. M.

Publications and source records attributed to Franklin, J. M..

8 recordsLinked to original sources

bioRxiv2026

Pangenome alignment reveals global diversity and evolution of human centromeric regions

Centromeres play essential roles in chromosome segregation and genome stability, yet they remain among the least characterized regions of the human genome. Despite advances in long-read sequencing and complete genome assembly, the extreme repetitiveness and structural complexity of these regions still challenge population-scale analysis, obscuring their mutational dynamics. The Human Pangenome Reference Consortium has now accurately assembled over 6,000 centromeres, providing an opportunity to catalog global centromere variation. However, centromeric regions have been systematically excluded from pangenome alignments due to the technical challenge of aligning their highly repetitive tandem arrays and extreme structural variability. Here we introduce Centrolign, a graph-based multiple sequence alignment tool that combines a uniqueness-driven objective function with partial-order partial-order alignment to accurately align alpha satellite higher-order repeats. By prioritizing rare matches within tandem arrays and leveraging extended centromere-spanning haplotypes formed by suppressed recombination, Centrolign produces progressive multiple sequence alignments that preserve ancestral repeat organization. Applied across human centromeres, these alignments reveal the phylogenetic structure of similar satellite array haplotypes and enable precise estimation of variation rates, structural variant frequencies, and spatial patterns of mutation within satellite arrays. Integrating Centrolign graphs with repeat annotation tools and pangenome mapping algorithms allows accurate variant calling and genotyping from long reads without prior assembly. Moreover, we show that centromere haplotypes can be accurately subtyped with k-mers alone. Together, these advances establish a robust framework for incorporating centromeres into broader pangenomes, and population genomics in general, advancing our understanding of human genome evolution and diversity.

genomics↗

bioRxiv2026

Nuclear stress bodies enable a germline-specific transcriptional stress response in Drosophila

The germline ensures the continuity of genetic information across generations, but how this immortal lineage functions under stress conditions remains incompletely understood. Here, we identify that heat shock factor (Hsf), a conserved master regulator of the stress response, drives the expression of transposable elements (TEs), in addition to molecular chaperones upon heat shock in Drosophila gonads. In germ cells, this potential intra-genomic conflict is countered by the formation of nuclear stress bodies (nSBs) at non-coding satellite DNA repeats. Using chemical and genetic perturbations, we demonstrate that nSBs are both necessary and sufficient to delay Hsf-dependent transcription. Notably, this nSB-mediated delay, in tandem with the piRNA pathway, allows germ cells to selectively express molecular chaperones, but not transposable elements, upon heat shock. Overall, we propose that this unique transcriptional stress response preserves germline function and evolutionary fitness, especially in natural populations routinely exposed to environmental stress.

cell biology↗

bioRxiv2025

DiMeLo-cito: a one-tube protocol for mapping protein-DNA interactions reveals CTCF bookmarking in mitosis

Genome regulation relies on complex and dynamic interactions between DNA and proteins. Recently, powerful methods have emerged that leverage third-generation sequencing to map protein-DNA interactions genome-wide. For example, Directed Methylation with Long-read sequencing (DiMeLo-seq) enables mapping of protein-DNA interactions along long, single chromatin fibers, including in highly repetitive genomic regions. However, DiMeLo-seq involves lossy centrifugation-based wash steps that limit its applicability to many sample types. To address this, we developed DiMeLo-cito, a single-tube, wash-free protocol that maximizes the yield and quality of genomic DNA obtained for long-read sequencing. This protocol enables the interrogation of genome-wide protein binding with as few as 100,000 cells and without the requirement of a nuclear envelope, enabling confident measurement of protein-DNA interactions during mitosis. Using this protocol, we detected strong binding of CTCF to mitotic chromosomes in diploid human cells, in contrast with earlier studies in karyotypically unstable cancer cell lines, suggesting that CTCF "bookmarks" specific sites critical for maintaining genome architecture across cell divisions. By expanding the capabilities of DiMeLo-seq to a broader range of sample types, DiMeLo-cito can provide new insights into genome regulation and organization.

genomics↗

bioRxiv2025

Integrating Single-Molecule Sequencing and Deep Learning to Predict Haplotype-Specific 3D Chromatin Organization in a Mendelian Condition

The three-dimensional (3D) architecture of the genome plays a crucial role in gene regulation and various human diseases. Short-read sequencing methods for measuring 3D genome organization are powerful, but they lack the ability to resolve individual human haplotypes or structurally complex regions. To address this, we present FiberFold, a deep learning model that combines convolutional neural networks and transformer architectures to accurately predict cell-type-specific and haplotype-specific 3D genome organization using multi-omic data from a single, long-read sequencing assay, Fiber-seq. By applying FiberFold to a cell line with allelic X-inactivation, we show that Topologically Associated Domains (TADs) are attenuated on the inactive chrX. Furthermore, FiberFold predicts significant changes to TADs surrounding a 13;X balanced translocation in a patient with a rare Mendelian disease. FiberFold showcases the power of integrating long-read epigenomic sequencing with deep learning tools to investigate fundamental chromatin biology as well as the molecular basis of human disease.

genomics↗

bioRxiv2024

Human Satellite 3 DNA encodes megabase-scale transcription factor binding platforms

Eukaryotic genomes frequently contain large arrays of tandem repeats, called satellite DNA. While some satellite DNAs participate in centromere function, others do not. For example, Human Satellite 3 (HSat3) forms the largest satellite DNA arrays in the human genome, but these multi-megabase regions were almost fully excluded from genome assemblies until recently, and their potential functions remain understudied and largely unknown. To address this, we performed a systematic screen for HSat3 binding proteins. Our work revealed that HSat3 contains millions of copies of transcription factor (TF) motifs bound by over a dozen TFs from various signaling pathways, including the growth-regulating transcription effector family TEAD1-4 from the Hippo pathway. Imaging experiments show that TEAD recruits the co-activator YAP to HSat3 regions in a cell-state specific manner. Using synthetic reporter assays, targeted repression of HSat3, inducible degradation of YAP, and super-resolution microscopy, we show that HSat3 arrays can localize YAP/TEAD inside the nucleolus, enhancing RNA Polymerase I activity. Beyond discovering a direct relationship between the Hippo pathway and ribosomal DNA regulation, this work demonstrates that satellite DNA can encode multiple transcription factor binding motifs, defining an important functional role for these enormous genomic elements.

cell biology↗

bioRxiv2019

NuSeT: A Deep Learning Tool for Reliably Separating and Analyzing Crowded Cells

Segmenting cell nuclei within microscopy images is a ubiquitous task in biological research and clinical applications. Unfortunately, segmenting low-contrast overlapping objects that may be tightly packed is a major bottleneck in standard deep learning-based models. We report a Nuclear Segmentation Tool (NuSeT) based on deep learning that accurately segments nuclei across multiple types of fluorescence imaging data. Using a hybrid network consisting of U-Net and Region Proposal Networks (RPN), followed by a watershed step, we have achieved superior performance in detecting and delineating nuclear boundaries in 2D and 3D images of varying complexities. By using foreground normalization and additional training on synthetic images containing non-cellular artifacts, NuSeT improves nuclear detection and reduces false positives. NuSeT addresses common challenges in nuclear segmentation such as variability in nuclear signal and shape, limited training sample size, and sample preparation artifacts. Compared to other segmentation models, NuSeT consistently fares better in generating accurate segmentation masks and assigning boundaries for touching nuclei.

bioinformatics↗

bioRxiv2019

Spatial resets modulate YAP-dependent transcription

Yes-associated protein 1 (YAP) is a transcriptional regulator with critical roles in mechanotransduction, organ size control, and regeneration. Here, using new tools for real-time visualization of native YAP and target gene transcription dynamics, we show that a cycle of fast exodus of nuclear YAP to the cytoplasm followed by fast reentry to the nucleus ("localization-resets") activates YAP target genes. These "resets" could be induced by calcium signaling, modulation of actomyosin contractility, or mitosis. Using nascent-transcription reporter knock-ins of YAP target genes, we observed a strict association between these resets and downstream transcription. Oncogenically-transformed transformed cell lines lacked localization-resets and instead showed dramatically elevated rates of nucleocytoplasmic shuttling of YAP, suggesting an escape from compartmentalization-based control. The single-cell localization and transcription traces suggest that YAP activity is not a simple linear function of nuclear enrichment and point to a new model of transcriptional activation based on nucleocytoplasmic exchange properties of YAP.

cell biology↗

bioRxiv2017

A fluorogenic nanobody array tag for prolonged single molecule imaging in live cells

Prolonged single molecule imaging in live cells requires labels that do not aggregate, have high contrast, and are photo-stable. To address these requirements, we have generated arrays of modular protein domains that function as fluorophore recruitment platforms. ArrayG, a linear repeat of GFP-nanobodies, recruits free monomeric wild-type GFP, which brightens ~15-fold upon binding the array. The fluorogenic ArrayG tag effectively eliminates background fluorescence from free binders, a major impediment to high-throughput acquisition of long trajectories in recruitment based imaging strategies. The photo-stability of ArrayG and consistently low background made it possible to continuously track single integrins for as long as 105 seconds (2100 frames). Prolonged tracking of both kinesin and integrin revealed repeated state-switching events, a measurement capability that is crucial to a mechanistic understanding of complex cellular processes. We also report an orthogonal array tag, based on a DHFR-nanobody, for prolonged dual color imaging of single molecules.

biophysics↗