Keywords: paralog processing, deep learning, spatial transcriptomics, single-cell RNA sequencing

Latest 26 Papers

Cell-type specific gating of gene regulatory modules as a hallmark of early immune responses in Arabidopsis leaves

Authors: Wang, S., Bezrukov, I., Wu, P.-J., Gauss, H., Timmermans, M., Weigel, D.

Date: 2025-08-01 · Version: 1

DOI: 10.1101/2025.08.01.668105

Model Organism: Arabidopsis thaliana

single-cell RNA sequencing Arabidopsis thaliana plant immunity PTI and ETI WRKY transcription factors

Plant-Compatible Xenium In Situ Sequencing: Optimised Protocol for Spatial Transcriptomics in Medicago truncatula Roots and Nodules

Authors: Jhu, M.-Y., Heffer, J., Deamer, A., Moraes, T. A., Piskorz, A. M., Xia, C.

Date: 2025-07-25 · Version: 1

DOI: 10.1101/2025.07.22.663073

Model Organism: Medicago truncatula

spatial transcriptomics Xenium in situ sequencing Medicago truncatula root nodules autofluorescence mitigation

Phenotypic scoring of Canola Blackleg severity using machine learning image analysis

Authors: Hu, Q., Anderson, S. N., Gardner, S., Ernst, T. W., Koscielny, C. B., Bahia, N. S., Johnson, C. G., Jarvis, A. C., Hynek, J., Coles, N., Falak, I., Charne, D. R., Ruidiaz, M. E., Linares, J. N., Mazis, A., Stanton, D. J.

Date: 2025-07-22 · Version: 1

DOI: 10.1101/2025.07.17.665372

Model Organism: Multi-species

blackleg disease canola (Brassica spp.)deep learning image-based phenotyping disease severity scoring

RegenPGC View: Semantic Segmentation of Perennial Groundcover Cropping Systems to Restore American Croplands

Authors: Meyering, B., Schlautman, B.

Date: 2025-07-06 · Version: 1

DOI: 10.1101/2025.07.03.663038

Model Organism: General

perennial groundcovers cover cropping deep learning convolutional neural network image‑based phenotyping

Spatial transcriptomics of developing wheat seed reveals radial expression patterns in endosperm and subgenome biased expression of key genes

Authors: Millsteed, T., Kainer, D., Sullivan, R., Sun, X., Li, K. L., Mao, L., Macdonald, A., Henry, R. J.

Date: 2025-06-08 · Version: 1

DOI: 10.1101/2025.06.08.658529

Model Organism: Triticum aestivum

spatial transcriptomics wheat seed development endosperm gene expression subgenome bias STOmics platform

Spatial and single-cell transcriptomics capture two distinct cell states in plant immunity

Authors: Hu, Y., Schaefer, R., Rendleman, M., Slattery, A., Cramer, A., Nahiyan, A., Breitweiser, L., Shah, M., Kaehler, E., Yao, C., Bowling, A., Crow, J., May, G., Tabor, G., Thatcher, S., Uppalapati, S. R., Muppirala, U., Deschamps, S.

Date: 2025-06-06 · Version: 1

DOI: 10.1101/2025.06.03.657683

Model Organism: Glycine max

spatial transcriptomics single-nuclei RNA-seq plant immunity Phakopsora pachyrhizi cell non‑autonomous defense

Unraveling the cis-regulatory code controlling abscisic acid-dependent gene expression in Arabidopsis using deep learning

Authors: Opdebeeck, H., Smet, D., Thierens, S., Minne, M., De Beukelaer, H., Zuallaert, J., Van Bel, M., Van Montagu, M., Degroeve, S., De Rybel, B., Vandepoele, K.

Date: 2025-06-06 · Version: 1

DOI: 10.1101/2025.06.03.657584

Model Organism: Arabidopsis thaliana

Abscisic acid Arabidopsis thaliana deep learning promoter motifs ABF binding sites

Single-cell metabolome and RNA-seq multiplexing on single plant cells

Authors: Kang, M., Vu, A. H., Casper, A. L., Kim, R., Wurlitzer, J., Heinicke, S., Yeroslaviz, A., Caputi, L., O'Connor, S. E.

Date: 2025-05-23 · Version: 1

DOI: 10.1101/2025.05.20.655036

Model Organism: General

single-cell RNA sequencing single-cell mass spectrometry metabolomics gene‑to‑metabolite correlation plant biosynthetic pathways multimodal single‑cell analysis

Conserved spatial patterning of gene expression in independent lineages of C4 plants

Authors: Sun, T., Bonthala, V. S., Stich, B., Luginbuehl, L. H., Hibberd, J. M.

Date: 2025-05-15 · Version: 1

DOI: 10.1101/2025.05.14.654047

Model Organism: Gynandropsis gynandra, Flaveria bidentis

C4 photosynthesis single-cell RNA sequencing single-nucleus RNA sequencing bundle sheath cells transcription factors

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

PreviousPage 2 of 3Next