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

Lee, Sungho; Lee, Tak H.; Yang, Sunmo; Lee, Insuk

doi:10.3389/fpls.2020.00098

Cited by 19 publications

(10 citation statements)

References 44 publications

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“…BarleyNet is a PFIN for barley, Hordeum vulgare, based on orthology to Arabidopsis and rice [254]. Five computationally-predicted interactomes were produced for Zea mays, maize [13,231,238,239,255].…”

Section: Plantsmentioning

confidence: 99%

Expanding Interactome Analyses beyond Model Eukaryotes

James¹,

Wipat²,

Cockell³

2021

Preprint

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Interactome analyses have traditionally been applied to yeast, human and other model organisms due to the availability of protein-protein interactions data for these species. Recently these techniques have been applied to more diverse species using computational interaction prediction from genome sequence and other data types. This review describes the various types of computational interactome networks that can be created and how they have been used in diverse eukaryotic species, highlighting some of the key interactome studies in non-model organisms.

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Section: Plantsmentioning

confidence: 99%

Expanding Interactome Analyses beyond Model Eukaryotes

James¹,

Wipat²,

Cockell³

2021

Preprint

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“…The haploid barley genome contains 83,105 putative genetic loci including 39,734 high-confidence ones. It is among the largest diploid genomes sequenced to date [ 17 ]. However, barley miRNAs sequence identification has so far been limited to only four tissues, i.e., stem, leaves, ears, and roots at different stages of development (seedlings, tillering, shading, grain filling) using Illumina sequencing technology.…”

Section: Introductionmentioning

confidence: 99%

Barley Seeds miRNome Stability during Long-Term Storage and Aging

Puchta

Groszyk

Małecka

et al. 2021

IJMS

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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.

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“…GCNs have been constructed for several plants, such as rice (6,7), maize (8), wheat (9), soybean (10). Several plant co-expression databases have been published, for example, ATTED-II (11), RiceFREND (7), PLANEX (12), PlaNet (13), and BarleyNet (14) for the exploration of gene co-expressions. However, GCN tools are limited by outdated datasets or are not currently available for some plant species, for example, Sorghum bicolor (sorghum).…”

Section: Introductionmentioning

confidence: 99%

“…A better understanding of gene functions and regulatory mechanisms is essential for developing strategies to increase grain yield and nutrient qualities. Original barley GCNs were constructed using microarray-based data (16), were local GCNs constructed from certain conditions or treatments (17,18), or were constructed using relatively few RNA-seq data (14,19).…”

Section: Introductionmentioning

confidence: 99%

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

Zhou¹,

Sukul²,

Jw³

et al. 2021

Preprint

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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. With the recent accumulation of RNA-seq data sets, the construction of RNA-seq-based GCNs has now become possible. Cereal crops, such as Hordeum vulgare (barley) and Sorghum bicolor (sorghum), are among the most important plants to humanity and contribute significantly to our food supply. However, co-expression network tools for these plants are outdated or lacking. In this study, we constructed global GCNs for barley and sorghum using 500 and 774 RNA-seq data sets, respectively. In addition, we curated the meta-information of these RNA-seq data sets and categorized them into four main tissue types, leaf, root, shoot, and flower/seed, and built tissue-specific GCNs. To enable GCN searching and visualization, we implemented a website and database named PlantNexus, offering an immersive environment for the exploration and visualization of gene expressions and co-expressions of barley and sorghum at the global and tissue-specific levels. PlantNexus is freely available at https://plantnexus.ohio.edu/.

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

Cited by 19 publications

References 44 publications

Expanding Interactome Analyses beyond Model Eukaryotes

Expanding Interactome Analyses beyond Model Eukaryotes

Barley Seeds miRNome Stability during Long-Term Storage and Aging

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

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