Biology subjects

Yukselen, O.

Publications and source records attributed to Yukselen, O..

5 recordsLinked to original sources

bioRxiv2025

tRNA-derived RNA processing in sperm transmits non-genetically inherited phenotypes to offspring in C. elegans

The environment encountered by an organism can modulate epigenetic information in gametes to transmit non-genetically inherited phenotypes to offspring. In mouse models, the diet of males regulates specific tRNA-derived RNAs (tDRs) in sperm. After fertilization, tDRs regulate embryonic gene expression and generate metabolic phenotypes in adult offspring through uncharacterized changes during development. Here we demonstrate that in C. elegans, tDRs also accumulate in sperm and can similarly transmit epigenetically inherited phenotypes to offspring. We identify the RNaseT2 enzyme, rnst-2, as a regulator of C. elegans tDR accumulation. RNST- 2 processes or degrades tRNA-halves, leading to short <30 nt fragments. This rnst-2 dependent regulation of tDR length distribution modulates specific tDRs in sperm which, after fertilization, regulate early embryonic and developmental gene expression, leading to adaptive phenotypes in progeny. Our findings establish tDRs as a deeply conserved carrier of intergenerational epigenetic information and position the worm as a model for dissecting paternal non-genetic inheritance mechanistically.

developmental biology↗

bioRxiv2025

Worm Perturb-Seq: massively parallel whole-animal RNAi and RNA-seq

The transcriptome provides a highly informative molecular phenotype to connect genotype to phenotype and is most frequently measured by RNA-sequencing (RNA-seq). Therefore, an ultimate goal is to perturb every gene and measure changes in the transcriptome. However, this remains challenging, especially in intact organisms due to different experimental and computational challenges. Here, we present Worm Perturb-Seq (WPS), which provides high-resolution RNA-seq profiles for hundreds of replicate perturbations at a time in a living animal. WPS introduces multiple experimental advances that combine strengths of bulk and single cell RNA-seq, and that further provides an analytical framework, EmpirDE, that leverages the unique power of the large WPS datasets. EmpirDE identifies differentially expressed genes (DEGs) by using gene-specific empirical null distributions, rather than control conditions alone, thereby systematically removing technical biases and improving statistical rigor. We applied WPS to 103 Caenhorhabditis elegans nuclear hormone receptors (NHRs) to delineate a Gene Regulatory Network (GRN) and found that this GRN presents a striking pairwise modularity where pairs of NHRs regulate shared target genes. We envision that the experimental and analytical advances of WPS should be useful not only for C. elegans, but will be broadly applicable to other models, including human cells.

genomics↗

bioRxiv2020

An atlas of cell types in the mammalian epididymis and vas deferens

Following spermatogenesis in the testis, mammalian sperm continue to mature over the course of approximately 10 days as they transit a long epithelial tube known as the epididymis. The epididymis is comprised of multiple segments/compartments that, in addition to concentrating sperm and preventing their premature activation, play key roles in remodeling the protein, lipid, and RNA composition of maturing sperm. In order to understand the complex roles for the epididymis in reproductive biology, we generated a single cell atlas of gene expression from the murine epididymis and vas deferens. We recovered all the key cell types of the epididymal epithelium, including principal cells, clear cells, and basal cells, along with associated support cells that include fibroblasts, smooth muscle, macrophages and other immune cells. Moreover, our data illuminate extensive regional specialization of principal cell populations across the length of the epididymis, with a substantial fraction of segment-specific genes localized in genomic clusters of functionally-related genes. In addition to the extensive region-specific specialization of principal cells, we find evidence for functionally-specialized subpopulations of stromal cells, and, most notably, two distinct populations of clear cells. Analysis of ligand/receptor expression reveals a network of potential cellular signaling connections, with several predicted interactions between cell types that may play roles in immune cell recruitment and other aspects of epididymal function. Our dataset extends on existing knowledge of epididymal biology, and provides a wealth of information on potential regulatory and signaling factors that bear future investigation.

developmental biology↗

bioRxiv2019

DolphinNext: A distributed data processing platform for high throughput genomics

The emergence of high throughput technologies that produce vast amounts of genomic data, such as next-generation sequencing (NGS) are transforming biological research. The dramatic increase in the volume of data makes analysis the main bottleneck for scientific discovery. The processing of high throughput datasets typically involves many different computational programs, each of which performs a specific step in a pipeline. Given the wide range of applications and organizational infrastructures, there is a great need for a highly-parallel, flexible, portable, and reproducible data processing frameworks. Flexibility ensures that pipelines can support a variety of applications without requiring one-off modifications. Portability ensures that users can leverage computationally available resources and work within economic constraints. Reproducibility warrants credibility to the results and is particularly challenging in the face of the sheer volume of data and the complexity of processing pipelines that vary widely between users.\n\nSeveral platforms currently exist for the design and execution of complex pipelines (e.g. Galaxy, GenePattern, GeneProf). Unfortunately, these platforms lack the necessary combination of parallelism, portability, flexibility and/or reproducibility that are required by the current research environment. To address these shortcomings, Nextflow was implemented to simplify portable, scalable, and reproducible scientific pipelines using containers. We have used Nextflow capabilities as leverage and developed a user interface, DolphinNext, for creating, deploying, and executing complex Nextflow pipelines for high throughput data processing. The guiding principle of DolphinNext is to facilitate the building and deployment of complex pipelines using a modular approach implemented in a graphical interface. DolphinNext provides: 1. A drag and drop user interface that abstracts pipelines and allows users to create pipelines without familiarity in underlying programming languages. 2. A user interface to monitor pipeline execution that allows the re-initiation of pipelines at intermediate steps 3. Reproducible pipelines with version tracking and stand-alone versions that can be run independently. 4. Seamless portability to distributed computational environments such as high-performance clusters or cloud computing environments.

bioinformatics↗

bioRxiv2018

DEBrowser: Interactive Differential Expression Analysis and Visualization Tool for Count Data

BackgroundSequencing data has become a standard measure for studying diverse cellular activities. For example, gene expression is accurately measured by RNA sequencing (RNA-Seq) libraries, protein-DNA interactions are captured by chromatin immunoprecipitation sequencing (ChIP-Seq), protein-RNA interactions by crosslinking immunoprecipitation (CLIP-Seq) or RNA immunoprecipitation (RIP-Seq) sequencing, DNA accessibility by assay for transposase-accessible chromatin (ATAC-Seq), and DNase or MNase sequencing libraries. Analysis of these sequencing techniques involve library-specific approaches. However, in all cases, once the sequencing libraries are processed, the result is a count table specifying the estimated number of reads originating from a genomic locus. Differential analysis to determine which loci have different cellular activity under different conditions starts with the count table and iterates through a cycle of data assessment, preparation and analysis. Such iterative approach relies on multiple programs and is therefore a challenge for those without programming skills.\n\nResultsWe developed DEBrowser, as an R bioconductor project, to interactively visualize each step of the differential analysis of count data, without any requirement for programming expertise. The application presents a rich and interactive web based graphical user interface based on Rs shiny infrastructure. We use shinys reactive programming interface for a dynamic webpage that responds to user input and integrates its visualization widgets at each stage of the analysis. In this way, every step of the analysis can be displayed in one application that combines many approaches and multiple results. We show DEBrowsers capabilities by reproducing the analysis of two previously published data sets.\n\nConclusionsDEBrowser is a flexible, intuitive, web-based analysis platform that enables an iterative and interactive analysis of count data without any requirement of programming knowledge.

bioinformatics↗