Keywords: paralog processing, spatial transcriptomics, transcriptomics, SWI3, wheat, high‑throughput phenotyping

Latest 65 Papers

Imputation integrates single-cell and spatial gene expression data to resolve transcriptional networks in barley shoot meristem development

Authors: Demesa-Arevalo, E., Dorpholz, H., Vardanega, I., Maika, J. E., Pineda-Valentino, I., Eggels, S., Lautwein, T., Kohrer, K., Schnurbusch, T., von Korff, M., Usadel, B., Simon, R.

Date: 2025-05-11 · Version: 1

DOI: 10.1101/2025.05.09.653223

Model Organism: Hordeum vulgare

Barley (Hordeum vulgare)inflorescence meristems single-cell RNA sequencing spatial transcriptomics developmental gene regulation

Comparative multi-omics profiling of Gossypium hirsutum and Gossypium barbadense fibers at high temporal resolution reveals key differences in polysaccharide composition and associated glycosyltransferases

Authors: Swaminathan, S., Lee, Y., Grover, C. E., DeTemple, M. F., Mugisha, A. S., Sichterman, L. E., Yang, P., Xie, J., Wendel, J. F., Szymanski, D. B., Zabotina, O. A.

Date: 2025-04-30 · Version: 1

DOI: 10.1101/2025.04.26.650795

Model Organism: Multi-species

cotton fiber development polysaccharide composition glycome profiling transcriptomics glycosyltransferases

ERF transcription factor regulons underpin growth-defence trade-off under acute heat stress in rice seedlings

Authors: Nair, A. U., Vishwakarma, S., Guha, T., Kadumuri, R. V., Fritschi, F. B., Chavali, S., Allu, A. D.

Date: 2025-04-22 · Version: 1

DOI: 10.1101/2025.04.21.649784

Model Organism: Oryza sativa

heat stress Oryza sativa seedling transcriptomics ethylene responsive factors phytohormone treatment

A transcriptional dissection of the petty spurge (Euphorbia peplus L.) reproductive structure

Authors: Johnson, A. R., Bao, A., Frank, M. H.

Date: 2025-04-17 · Version: 2

DOI: 10.1101/2024.05.06.592779

Model Organism: Euphorbia peplus

cyathium transcriptomics floral development genes SEP1 paralogs Euphorbia peplus

Data-driven mathematical modelling explains altered timing of EARLY FLOWERING 3 in the wheat circadian oscillator

Authors: Upadhyay, A., Rowland-Chandler, J., Stewart-Wood, J., Pingarron-Cardenas, G., Tokuda, I. T., Webb, A. A., Locke, J. C.

Date: 2025-04-08 · Version: 1

DOI: 10.1101/2025.04.08.644541

Model Organism: Triticum aestivum

circadian rhythm ELF3 wheat TOC1 repression computational modeling

Welcome pathogens: transient heat dampens the responses to acibenzolar-S-methyl beyond defenses in apple plants

Authors: Chavonet, E., Nguyen, B.-h., Heintz, C., Cournol, R., Siroka, J., Novak, O., Larbat, R., Gaucher, M., Brisset, M.-N., Pantin, F., Degrave, A.

Date: 2025-04-06 · Version: 1

DOI: 10.1101/2025.04.03.647103

Model Organism: Malus domestica

heat stress acibenzolar‑S‑methyl (ASM)induced immunity apple (Malus domestica)transcriptomics

Omics-driven Identification of Candidate Genes and SNP markers in a Major QTL Controlling Early Heading in Rice

Authors: Rao, D., T, N. S., CG, G., Gaur, N., Jamaloddin, M., Maganti, S. M., Raman, M. S., Patel, H. K., Tiwari, S., Sonti, R. V.

Date: 2025-03-27 · Version: 1

DOI: 10.1101/2025.03.25.645207

Model Organism: Oryza sativa

heading date rice (Oryza sativa)QTL-seq SNP markers transcriptomics

Multilevel analysis of response to plant growth promoting and pathogenic bacteria in Arabidopsis roots and the role of CYP71A27 in this response

Authors: Koprivova, A., Ristova, D., Berka, M., Berkova, V., Türksoy, G. M., Andersen, T. G., Westhoff, P., Cerny, M., Kopriva, S.

Date: 2025-03-27 · Version: 1

DOI: 10.1101/2025.03.26.645393

Model Organism: Arabidopsis thaliana

CYP71A27 plant‑microbe interaction Pseudomonas fluorescens CH267 Burkholderia glumeae PG1 transcriptomics

The Global Wheat Full Semantic Organ Segmentation (GWFSS) dataset

Authors: Wang, Z., Zenkl, R., Greche, L., De Solan, B., Bernigaud Samatan, L., Ouahid, S., Visioni, A., Robles-Zazueta, C. A., Pinto, F., Perez-Olivera, I., Reynolds, M. P., Zhu, C., Liu, S., D'argaignon, M.-P., Lopez-Lozano, R., Weiss, M., Marzougui, A., Roth, L., Dandrifosse, S., Carlier, A., Dumont, B., Mercatoris, B., Fernandez, J., Chapman, S., Najafian, K., Stavness, I., Wang, H., Guo, W., Virlet, N., Hawkesford, M., Chen, Z., David, E., Gillet, J., Irfan, K., Comar, A., Hund, A.

Date: 2025-03-19 · Version: 1

DOI: 10.1101/2025.03.18.642594

Model Organism: Triticum aestivum

wheat semantic segmentation computer vision deep learning phenotyping

The FIP 1.0 Data Set: Highly Resolved Annotated Image Time Series of 4,000 Wheat Plots Grown in Six Years

Authors: Roth, L., Boss, M., Kirchgessner, N., Aasen, H., Aguirre-Cuellar, B. P., Akiina, P. P. A., Anderegg, J., Gajardo Castillo, J., Chen, X., Corrado, S., Cybulski, K., Keller, B., Kortstee, S. G., Kronenberg, L., Liebisch, F., Nousi, P., Oppliger, C., Perich, G., Pfeifer, J., Yu, K., Storni, N., Tschurr, F., Volpi, M., Treier, S., Zellweger, H., Zumsteg, O., Hund, A., Walter, A.

Date: 2025-03-11 · Version: 3

DOI: 10.1101/2024.10.04.616624

Model Organism: Triticum aestivum

genotype‑environment interaction winter wheat high‑throughput phenotyping genomic prediction crop modeling

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