BarleyNet: A Network-Based Functional Omics Analysis Server for Cultivated Barley, Hordeum vulgare L

StCoExpNet: a global co-expression network analysis facilitates identifying genes underlying agronomic traits in potatoes

KEY MESSAGE

We constructed a gene expression atlas and co-expression network for potatoes and identified several novel genes associated with various agronomic traits. This resource will accelerate potato genetics and genomics research. Potato (Solanum tuberosum L.) is the world's most crucial non-cereal food crop and ranks third in food production after wheat and rice. Despite the availability of several potato transcriptome datasets at public databases like NCBI SRA, an effort has yet to be put into developing a global transcriptome atlas and a co-expression network for potatoes. The objectives of our study were to construct a global expression atlas for potatoes using publicly available transcriptome datasets, identify housekeeping and tissue-specific genes, construct a global co-expression network and identify co-expression clusters, investigate the transcriptional complexity of genes involved in various essential biological processes related to agronomic traits, and provide a web server (StCoExpNet) to easily access the newly constructed expression atlas and co-expression network to investigate the expression and co-expression of genes of interest. In this study, we used data from 2299 publicly available potato transcriptome samples obtained from 15 different tissues to construct a global transcriptome atlas. We found that roughly 87% of the annotated genes exhibited detectable expression in at least one sample. Among these, we identified 281 genes with consistent and stable expression levels, indicating their role as housekeeping genes. Conversely, 308 genes exhibited marked tissue-specific expression patterns. We exemplarily linked some co-expression clusters to important agronomic traits of potatoes, such as self-incompatibility, anthocyanin biosynthesis, tuberization, and defense responses against multiple pathogens. The dataset compiled here constitutes a new resource (StCoExpNet), which can be accessed at https://stcoexpnet.julius-kuehn.de . This transcriptome atlas and the co-expression network will accelerate potato genetics and genomics research.

Unleashing the power within short-read RNA-seq for plant research: Beyond differential expression analysis and toward regulomics

RNA-seq has become a state-of-the-art technique for transcriptomic studies. Advances in both RNA-seq techniques and the corresponding analysis tools and pipelines have unprecedently shaped our understanding in almost every aspects of plant sciences. Notably, the integration of huge amount of RNA-seq with other omic data sets in the model plants and major crop species have facilitated plant regulomics, while the RNA-seq analysis has still been primarily used for differential expression analysis in many less-studied plant species. To unleash the analytical power of RNA-seq in plant species, especially less-studied species and biomass crops, we summarize recent achievements of RNA-seq analysis in the major plant species and representative tools in the four types of application: (1) transcriptome assembly, (2) construction of expression atlas, (3) network analysis, and (4) structural alteration. We emphasize the importance of expression atlas, coexpression networks and predictions of gene regulatory relationships in moving plant transcriptomes toward regulomics, an omic view of genome-wide transcription regulation. We highlight what can be achieved in plant research with RNA-seq by introducing a list of representative RNA-seq analysis tools and resources that are developed for certain minor species or suitable for the analysis without species limitation. In summary, we provide an updated digest on RNA-seq tools, resources and the diverse applications for plant research, and our perspective on the power and challenges of short-read RNA-seq analysis from a regulomic point view. A full utilization of these fruitful RNA-seq resources will promote plant omic research to a higher level, especially in those less studied species.

Integration of probabilistic functional networks without an external Gold Standard

BACKGROUND

Probabilistic functional integrated networks (PFINs) are designed to aid our understanding of cellular biology and can be used to generate testable hypotheses about protein function. PFINs are generally created by scoring the quality of interaction datasets against a Gold Standard dataset, usually chosen from a separate high-quality data source, prior to their integration. Use of an external Gold Standard has several drawbacks, including data redundancy, data loss and the need for identifier mapping, which can complicate the network build and impact on PFIN performance. Additionally, there typically are no Gold Standard data for non-model organisms.

RESULTS

We describe the development of an integration technique, ssNet, that scores and integrates both high-throughput and low-throughout data from a single source database in a consistent manner without the need for an external Gold Standard dataset. Using data from Saccharomyces cerevisiae we show that ssNet is easier and faster, overcoming the challenges of data redundancy, Gold Standard bias and ID mapping. In addition ssNet results in less loss of data and produces a more complete network.

CONCLUSIONS

The ssNet method allows PFINs to be built successfully from a single database, while producing comparable network performance to networks scored using an external Gold Standard source and with reduced data loss.

Korean naked waxy barley (saechalssal) extract reduces blood glucose in diabetic mice by modulating the PI3K-Akt-GSK3β pathway

Saechalssal barley is Korea's representative naked waxy barley. This study investigated the anti-diabetic effect of the extract derived from saechalssal and its mechanism. The prethanol extract of saechalssal (SPE) showed greater α-glucosidase inhibitory activity in vitro and a more significant lowering of the postprandial blood glucose levels in normal mice compared to its water extract (SWE). When mice with type 2 diabetes (T2DM) induced by a high-fat diet and streptozotocin were fed SPE (200 mg/kg/day) for six weeks, the fasting blood glucose and serum free fatty acid levels were significantly lower than those of the control group. SPE significantly elevated the hepatic glycogen accumulation with increasing glycogen synthesis-related gene (GYS2 and UGP2) levels compared to the control group. SPE stimulated the expression of the hepatic glycolysis-related genes (GK, PFK1, and PK) and suppressed the gluconeogenesis-related genes (G6Pase, FBP1, and PEPCK). SPE up-regulated the phosphorylation of phosphatidylinositol 3-kinase (PI3K) and protein kinase B (Akt), whereas it down-regulated the phosphorylation of glycogen synthase kinase 3 beta (GSK3β) compared to the control. The major flavonoids of SPE were naringin, prunin, and catechin, while its phenolic acids were ferulic acid and vanillic acid. These phytochemical compounds may contribute to the anti-hyperglycemic effects of SPE in diabetes. Overall, these results suggest that SPE has potential anti-diabetic activity through the regulating the PI3K/Akt/GSK3β pathway.

PlantNexus: A Gene Co-expression Network Database and Visualization Tool for Barley and Sorghum

Global gene co-expression networks (GCNs) are powerful tools for functional genomics whereby putative functions and regulatory mechanisms can be inferred by gene co-expression. Cereal crops, such as Hordeum vulgare (barley) and Sorghum bicolor (sorghum), are among the most important plants to civilization. However, co-expression network tools for these plants are lacking. Here, we have constructed global GCNs for barley and sorghum using existing RNA-seq data sets. Meta-information was manually curated and categorized by tissue type to also build tissue-specific GCNs. To enable GCN searching and visualization, we implemented a website and database named PlantNexus. PlantNexus is freely available at https://plantnexus.ohio.edu/.

Genome Editing-accelerated Re-Domestication (GEaReD) - a new major direction in plant breeding

BACKGROUND

The effects of climate change, soil depletion, a growing world population putting pressure on food safety and security are major challenges for agriculture in the 21st century. The breeding success of the green revolution has decelerated and current programs can only offset the yield affecting factors.

PURPOSE AND SCOPE

New approaches are urgently needed and we propose "Genome Editing-accelerated Re-Domestication" (GEaReD) as a major new direction in plant breeding. By combining the upcoming technologies for phenotyping, omics, and artificial intelligence with the promising new CRISPR-toolkits, this approach is closer than ever.

SUMMARY AND CONCLUSION

Wild relatives of current crops are often adapted to harsh environments and have a high genetic diversity. Redomestication of wild barley or teosinte could generate new cultivars adapted to environmental changes. De novo domestication of perennial relatives such as Hordeum bulbosum could counter soil depletion and increase soil carbon. Recent research already proved the principle of redomestication in tomato and rice and therefore laid the foundation for GEaReD. This article is protected by copyright. All rights reserved.

Barley Seeds miRNome Stability during Long-Term Storage and Aging

Seed aging is a complex biological process that has been attracting scientists’ attention for many years. High-throughput small RNA sequencing was applied to examine microRNAs contribution in barley seeds senescence. Unique samples of seeds that, despite having the same genetic makeup, differed in viability after over 45 years of storage in a dry state were investigated. In total, 61 known and 81 novel miRNA were identified in dry seeds. The highest level of expression was found in four conserved miRNA families, i.e., miR159, miR156, miR166, and miR168. However, the most astonishing result was the lack of significant differences in the level of almost all miRNAs in seed samples with significantly different viability. This result reveals that miRNAs in dry seeds are extremely stable. This is also the first identified RNA fraction that is not deteriorating along with the loss of seed viability. Moreover, the novel miRNA hvu-new41, with higher expression in seeds with the lowest viability as detected by RT-qPCR, has the potential to become an indicator of the decreasing viability of seeds during storage in a dry state.