Transcriptomic Time-Series Analyses of Gene Expression Profile During Zygotic Embryo Development in Picea mongolica

Transcriptome Landscape Analyses of the Regulatory Network for Zygotic Embryo Development in Paeonia ostii

Paeonia ostii is a worldwide ornamental flower and an emerging oil crop. Zyotic embryogenesis is a critical process during seed development, and it can provide a basis for improving the efficiency of somatic embryogenesis (SE). In this study, transcriptome sequencing of embryo development was performed to investigate gene expression profiling in P. ostii and identified Differentially expressed genes (DEGs) related to transcription factors, plant hormones, and antioxidant enzymes. The results indicated that IAA (Indole-3-acetic acid), GA (Gibberellin), BR (Brassinosteroid) and ETH (Ethylene) were beneficial to early embryonic morphogenesis, while CTK (Cytokinin) and ABA (Abscisic Acid) promoted embryo morphogenesis and maturation. The antioxidant enzymes' activity was the highest in early embryos and an important participant in embryo formation. The high expression of the genes encoding fatty acid desaturase was beneficial to fast oil accumulation. Representative DEGs were selected and validated using qRT-PCR. Protein-protein interaction network (PPI) was predicted, and six central node proteins, including AUX1, PIN1, ARF6, LAX3, ABCB19, PIF3, and PIF4, were screened. Our results provided new insights into the formation of embryo development and even somatic embryo development in tree peonies.

Time-Series Transcriptomic Analysis of Contrasting Rice Materials under Heat Stress Reveals a Faster Response in the Tolerant Cultivar

Short-term heat stress can affect the growth of rice (Oryza sativa L.) seedlings, subsequently decreasing yields. Determining the dynamic response of rice seedlings to short-term heat stress is highly important for accelerating research on rice heat tolerance. Here, we observed the seedling characteristics of two contrasting cultivars (T11: heat-tolerant and T15: heat-sensitive) after different durations of 42 °C heat stress. The dynamic transcriptomic changes of the two cultivars were monitored after 0 min, 10 min, 30 min, 1 h, 4 h, and 10 h of stress. The results indicate that several pathways were rapidly responding to heat stress, such as protein processing in the endoplasmic reticulum, glycerophospholipid metabolism, and plant hormone signal transduction. Functional annotation and cluster analysis of differentially expressed genes at different stress times indicate that the tolerant cultivar responded more rapidly and intensively to heat stress compared to the sensitive cultivar. The MAPK signaling pathway was found to be the specific early-response pathway of the tolerant cultivar. Moreover, by combining data from a GWAS and RNA-seq analysis, we identified 27 candidate genes. The reliability of the transcriptome data was verified using RT-qPCR on 10 candidate genes and 20 genes with different expression patterns. This study provides valuable information for short-term thermotolerance response mechanisms active at the rice seedling stage and lays a foundation for breeding thermotolerant varieties via molecular breeding.

Network Approaches for Charting the Transcriptomic and Epigenetic Landscape of the Developmental Origins of Health and Disease

The early developmental phase is of critical importance for human health and disease later in life. To decipher the molecular mechanisms at play, current biomedical research is increasingly relying on large quantities of diverse omics data. The integration and interpretation of the different datasets pose a critical challenge towards the holistic understanding of the complex biological processes that are involved in early development. In this review, we outline the major transcriptomic and epigenetic processes and the respective datasets that are most relevant for studying the periconceptional period. We cover both basic data processing and analysis steps, as well as more advanced data integration methods. A particular focus is given to network-based methods. Finally, we review the medical applications of such integrative analyses.