Scywalker: Scalable end-to-end data analysis workflow for long-read single-cell transcriptome sequencing.

MOTIVATION: Existing nanopore single-cell data analysis tools showed severe limitations in handling current data sizes. RESULTS: We introduce scywalker, an innovative and scalable package developed to comprehensively analyze long-read sequencing data of full-length single-cell or single-nuclei cDNA. We developed novel scalable methods for cell barcode demultiplexing and single-cell isoform calling and quantification and incorporated these in an easily deployable package. Scywalker streamlines the entire analysis process, from sequenced fragments in FASTQ format to demultiplexed pseudobulk isoform counts, into a single command suitable for execution on either server or cluster. Scywalker includes data quality control, cell type identification, and an interactive report. Assessment of datasets from the human brain, Arabidopsis leaves, and previously benchmarked data from mixed cell lines demonstrate excellent correlation with short-read analyses at both the cell-barcoding and gene quantification levels. At the isoform level, we show that scywalker facilitates the direct identification of cell-type-specific expression of novel isoforms. AVAILABILITY: Scywalker is available on github.com/derijkp/scywalker under the GNU General Public License (GPL) and at https://zenodo.org/records/13359438/files/scywalker-0.108.0-Linux-x86_64.tar.gz. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Systems genetic analysis of lignin biosynthesis in Populus tremula.

The genetic control underlying natural variation in lignin content and composition in trees is not fully understood. We performed a systems genetic analysis to uncover the genetic regulation of lignin biosynthesis in a natural 'SwAsp' population of aspen (Populus tremula) trees. We analyzed gene expression by RNA sequencing (RNA-seq) in differentiating xylem tissues, and lignin content and composition using Pyrolysis-GC-MS in mature wood of 268 trees from 99 genotypes. Abundant variation was observed for lignin content and composition, and genome-wide association study identified proteins in the pentose phosphate pathway and arabinogalactan protein glycosylation among the top-ranked genes that are associated with these traits. Variation in gene expression and the associated genetic polymorphism was revealed through the identification of 312 705 local and 292 003 distant expression quantitative trait loci (eQTL). A co-expression network analysis suggested modularization of lignin biosynthesis and novel functions for the lignin-biosynthetic CINNAMYL ALCOHOL DEHYDROGENASE 2 and CAFFEOYL-CoA O-METHYLTRANSFERASE 3. PHENYLALANINE AMMONIA LYASE 3 was co-expressed with HOMEOBOX PROTEIN 5 (HB5), and the role of HB5 in stimulating lignification was demonstrated in transgenic trees. The systems genetic approach allowed linking natural variation in lignin biosynthesis to trees´ responses to external cues such as mechanical stimulus and nutrient availability.

Best practices for the execution, analysis, and data storage of plant single-cell/nucleus transcriptomics.

Single-cell and single-nucleus RNA-sequencing technologies capture the expression of plant genes at an unprecedented resolution. Therefore, these technologies are gaining traction in plant molecular and developmental biology for elucidating the transcriptional changes across cell types in a specific tissue or organ, upon treatments, in response to biotic and abiotic stresses, or between genotypes. Despite the rapidly accelerating use of these technologies, collective and standardized experimental and analytical procedures to support the acquisition of high-quality data sets are still missing. In this commentary, we discuss common challenges associated with the use of single-cell transcriptomics in plants and propose general guidelines to improve reproducibility, quality, comparability, and interpretation and to make the data readily available to the community in this fast-developing field of research.

Spatial transcriptomics of a lycophyte root sheds light on root evolution.

Plant roots originated independently in lycophytes and euphyllophytes, whereas early vascular plants were rootless. The organization of the root apical meristem in euphyllophytes is well documented, especially in the model plant Arabidopsis. However, little is known about lycophyte roots and their molecular innovations during evolution. In this study, spatial transcriptomics was used to detect 97 root-related genes in the roots of the lycophyte Selaginella moellendorffii. A high number of genes showed expression patterns similar to what has been reported for seed plants, supporting the idea of a highly convergent evolution of mechanisms to control root development. Interaction and complementation data of SHORTROOT (SHR) and SCARECROW (SCR) homologs, furthermore, support a comparable regulation of the ground tissue (GT) between euphyllophytes and lycophytes. Root cap formation, in contrast, appears to be differently regulated. Several experiments indicated an important role of the WUSCHEL-RELATED HOMEOBOX13 gene SmWOX13a in Selaginella root cap formation. In contrast to multiple Arabidopsis WOX paralogs, SmWOX13a is able to induce root cap cells in Arabidopsis and has functionally conserved homologs in the fern Ceratopteris richardii. Lycophytes and a part of the euphyllophytes, therefore, may share a common mechanism regulating root cap formation, which was diversified or lost during seed plant evolution. In summary, we here provide a new spatial data resource for the Selaginella root, which in general advocates for conserved mechanisms to regulate root development but shows a clear divergence in the control of root cap formation, with a novel putative role of WOX genes in root cap formation in non-seed plants.