SAW: an efficient and accurate data analysis workflow for Stereo-seq spatial transcriptomics.

The basic analysis steps of spatial transcriptomics require obtaining gene expression information from both space and cells. The existing tools for these analyses incur performance issues when dealing with large datasets. These issues involve computationally intensive spatial localization, RNA genome alignment, and excessive memory usage in large chip scenarios. These problems affect the applicability and efficiency of the analysis. Here, a high-performance and accurate spatial transcriptomics data analysis workflow, called Stereo-seq Analysis Workflow (SAW), was developed for the Stereo-seq technology developed at BGI. SAW includes mRNA spatial position reconstruction, genome alignment, gene expression matrix generation, and clustering. The workflow outputs files in a universal format for subsequent personalized analysis. The execution time for the entire analysis is ∼148 min with 1 GB reads 1 × 1 cm chip test data, 1.8 times faster than with an unoptimized workflow.

Genome-Wide and Expression Pattern Analysis of the DVL Gene Family Reveals GhM_A05G1032 Is Involved in Fuzz Development in G. hirsutum.

DVL is one of the small polypeptides which plays an important role in regulating plant growth and development, tissue differentiation, and organ formation in the process of coping with stress conditions. So far, there has been no comprehensive analysis of the expression profile and function of the cotton DVL gene. According to previous studies, a candidate gene related to the development of fuzz was screened, belonging to the DVL family, and was related to the development of trichomes in Arabidopsis thaliana. However, the comprehensive identification and systematic analysis of DVL in cotton have not been conducted. In this study, we employed bioinformatics approaches to conduct a novel analysis of the structural characteristics, phylogenetic tree, gene structure, expression pattern, evolutionary relationship, and selective pressure of the DVL gene family members in four cotton species. A total of 117 DVL genes were identified, including 39 members in G. hirsutum. Based on the phylogenetic analysis, the DVL protein sequences were categorized into five distinct subfamilies. Additionally, we successfully mapped these genes onto chromosomes and visually represented their gene structure information. Furthermore, we predicted the presence of cis-acting elements in DVL genes in G. hirsutum and characterized the repeat types of DVL genes in the four cotton species. Moreover, we computed the Ka/Ks ratio of homologous genes across the four cotton species and elucidated the selective pressure acting on these homologous genes. In addition, we described the expression patterns of the DVL gene family using RNA-seq data, verified the correlation between GhMDVL3 and fuzz development through VIGS technology, and found that some DVL genes may be involved in resistance to biotic and abiotic stress conditions through qRT-PCR technology. Furthermore, a potential interaction network was constructed by WGCNA, and our findings demonstrated the potential of GhM_A05G1032 to interact with numerous genes, thereby playing a crucial role in regulating fuzz development. This research significantly contributed to the comprehension of DVL genes in upland cotton, thereby establishing a solid basis for future investigations into the functional aspects of DVL genes in cotton.

Genetic and Morpho-Physiological Differences among Transgenic and No-Transgenic Cotton Cultivars.

Three carbon-chain extension genes associated with fatty acid synthesis in upland cotton (Gossypium hirsutum), namely GhKAR, GhHAD, and GhENR, play important roles in oil accumulation in cotton seeds. In the present study, these three genes were cloned and characterized. The expression patterns of GhKAR, GhHAD, and GhENR in the high seed oil content cultivars 10H1014 and 10H1041 differed somewhat compared with those of 10H1007 and 2074B with low seed oil content at different stages of seed development. GhKAR showed all three cultivars showed higher transcript levels than that of 2074B at 10-, 40-, and 45-days post anthesis (DPA). The expression pattern of GhHAD showed a lower transcript level than that of 2074B at both 10 and 30 DPA but a higher transcript level than that of 2074B at 40 DPA. GhENR showed a lower transcript level than that of 2074B at both 15 and 30 DPA. The highest transcript levels of GhKAR and GhENR were detected at 15 DPA in 10H1007, 10H1014, and 10H1041 compared with 2074B. From 5 to 45 DPA cotton seed, the oil content accumulated continuously in the developing seed. Oil accumulation reached a peak between 40 DPA and 45 DPA and slightly decreased in mature seed. In addition, GhKAR and GhENR showed different expression patterns in fiber and ovule development processes, in which they showed high expression levels at 20 DPA during the fiber elongation stage, but their expression level peaked at 15 DPA during ovule development processes. These two genes showed the lowest expression levels at the late seed maturation stage, while GhHAD showed a peak of 10 DPA in fiber development. Compared to 2074B, the oil contents of GhKAR and GhENR overexpression lines increased 1.05~1.08 folds. These results indicated that GhHAD, GhENR, and GhKAR were involved in both seed oil synthesis and fiber elongation with dual biological functions in cotton.

Weighted Gene Co-Expression Network Analysis Reveals Hub Genes for Fuzz Development in Gossypium hirsutum.

Fuzzless Gossypium hirsutum mutants are ideal materials for investigating cotton fiber initiation and development. In this study, we used the fuzzless G. hirsutum mutant Xinluzao 50 FLM as the research material and combined it with other fuzzless materials for verification by RNA sequencing to explore the gene expression patterns and differences between genes in upland cotton during the fuzz period. A gene ontology (GO) enrichment analysis showed that differentially expressed genes (DEGs) were mainly enriched in the metabolic process, microtubule binding, and other pathways. A weighted gene co-expression network analysis (WGCNA) showed that two modules of Xinluzao 50 and Xinluzao 50 FLM and four modules of CSS386 and Sicala V-2 were highly correlated with fuzz. We selected the hub gene with the highest KME value among the six modules and constructed an interaction network. In addition, we selected some genes with high KME values from the six modules that were highly associated with fuzz in the four materials and found 19 common differential genes produced by the four materials. These 19 genes are likely involved in the formation of fuzz in upland cotton. Several hub genes belong to the arabinogalactan protein and GDSL lipase, which play important roles in fiber development. According to the differences in expression level, 4 genes were selected from the 19 genes and tested for their expression level in some fuzzless materials. The modules, hub genes, and common genes identified in this study can provide new insights into the formation of fiber and fuzz, and provide a reference for molecular design breeding for the genetic improvement of cotton fiber.

Spatiotemporal transcriptomic atlas of mouse organogenesis using DNA nanoball-patterned arrays.

Spatially resolved transcriptomic technologies are promising tools to study complex biological processes such as mammalian embryogenesis. However, the imbalance between resolution, gene capture, and field of view of current methodologies precludes their systematic application to analyze relatively large and three-dimensional mid- and late-gestation embryos. Here, we combined DNA nanoball (DNB)-patterned arrays and in situ RNA capture to create spatial enhanced resolution omics-sequencing (Stereo-seq). We applied Stereo-seq to generate the mouse organogenesis spatiotemporal transcriptomic atlas (MOSTA), which maps with single-cell resolution and high sensitivity the kinetics and directionality of transcriptional variation during mouse organogenesis. We used this information to gain insight into the molecular basis of spatial cell heterogeneity and cell fate specification in developing tissues such as the dorsal midbrain. Our panoramic atlas will facilitate in-depth investigation of longstanding questions concerning normal and abnormal mammalian development.