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Arslan, K.

Publications and source records attributed to Arslan, K..

3 recordsLinked to original sources

Integrating Orthology and Cross-Species Transcriptomics to Unravel Root Drought Responses in Faba Bean and Maize

During soil drying, roots in upper and deeper soil layers experience different hydraulic environments, yet the molecular programs that accompany and potentially drive depth-specific changes in root water uptake capacity remain poorly understood. Here, we address this gap by coupling depth-resolved RNA-seq with previously measured hydraulic uptake profiles in pot-grown faba bean (Vicia faba) and maize (Zea mays), two crop species with contrasting root architecture, sampled from upper (drying) and lower (comparatively wet) root zones at the onset and after four days of soil drying. Differential expression analysis revealed strongly top-region of the roots dominated transcriptional responses in both species, consistent with the steeper hydraulic challenge in drying upper layers. Maize displayed a TIP- and dehydrin-dominated drought response, whereas faba bean induced NIP-like aquaporins and a broader LEA repertoire, suggesting divergent strategies for root water and cellular stress protection. To compare transcriptome responses across these distally related species, we grouped orthologous genes across 26 species using OrthoFinder. With this approach, we identified 905 drought-responsive orthogroups, of which only 17% were shared between species despite broadly convergent gene onthology (GO) enrichment profiles. Phylogenetic tracing showed that 95.7% of faba bean-specific and 90.3% of maize-specific drought-responsive orthogroups are conserved across monocot and dicot lineages, indicating that species-specific drought transcriptomes arise primarily through differential recruitment of ancestral gene families rather than lineage-specific innovation. These findings define a molecular framework linking root hydraulic architecture to gene regulation under drought and identify conserved transcriptional regulatory hubs as targets for broad-spectrum abiotic stress improvement in both faba bean and maize.

plant biology↗

NOHIC: A PIPELINE FOR PLANT CONTIG SCAFFOLDING USING PERSONALIZED REFERENCES FROM PANGENOME GRAPHS

Hi-C data is commonly used for reference-free de novo scaffolding. However, with the rapid increase in high-quality reference genomes, reference-guided workflows are now more practical for assembling large numbers of target genomes without relying on costly and labor-intensive Hi-C sequencing. Recently, a pangenome graph-based haplotype sampling algorithm was introduced to generate personalized graphs for target genomes. Such graphs have strong potential as references for reference-guided contig scaffolding. Here, we present noHiC, a reference-guided scaffolding pipeline supporting key steps of plant contig scaffolding. A distinctive feature of noHiC is the nohic-refpick script, generating a best-fit synthetic reference (synref) from a pangenome graph that is genetically close to the target contigs. This enables the integration of genetic information from many references (up to 48 in our tests) without using them separately during scaffolding. Synrefs showed advantages over highly contiguous conventional references in reducing false contig breaking during reference-based correction. Additionally, nohic-refpick can be combined with fast scaffolders (ntJoin) to rapidly produce highly contiguous assemblies using synrefs derived from pangenome graphs. The noHiC pipeline, used alone or in combination with ntJoin, can generally produce assemblies that are structurally consistent with public Hi-C-based or manually curated genomes. The pipeline is publicly available at https://github.com/andyngh/noHiC. GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=82 SRC="FIGDIR/small/712436v1_ufig1.gif" ALT="Figure 1"> View larger version (9K): org.highwire.dtl.DTLVardef@40bd8forg.highwire.dtl.DTLVardef@5d2bbborg.highwire.dtl.DTLVardef@e214a3org.highwire.dtl.DTLVardef@b90b06_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

Integrative epigenomic analysis uncovers asymmetry of enhancer activity in Brassica napus

Non-coding regulatory regions are essential to the determination of gene expression and plant phenotypes. In this work, we investigated the cis-regulatory landscape of a winter type rapeseed, Express617, across multiple sample types. Combining chromatin accessibility, DNA methylation and gene expression, we annotated thousands of novel regulatory elements in the Brassica napus genome. Among those regions, we discovered and functionally characterized super-enhancers, observing an asymmetrical distribution of these regulatory elements favoring the Cn subgenome. Super-enhancer (SE) associated genes were found enriched in tissue identity and responses to stimuli related processes. We further establish and apply an in-silico validation pipeline for super-enhancers, integrating population-level expression analysis and machine learning (ML) models predicting gene expression levels. Almost 50% of the newly identified SE-associated genes had an observed expression higher than the expression levels predicted by the ML model. Moreover, structural variants disrupting super-enhancer elements correlate with a reduction of expression in the associated genes, both consistent with the positive effect of these regulatory regions. These results greatly expand the functional annotation of rapeseed and contribute to a better understanding of the link between regulatory elements and their target genes and processes, providing novel insights and targets for B. napus (epi)-genome editing strategies.

plant biology↗