Identification of Transcription Factors Regulating Senescence in Wheat through Gene Regulatory Network Modelling

Borrill, Philippa; Harrington, Sophie A; Simmonds, James; Uauy, Cristóbal

doi:10.1104/pp.19.00380

Cited by 75 publications

(59 citation statements)

References 78 publications

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“…Compared to coding genes and microRNAs, the function of lncRNAs in abiotic stress response remains largely unknown. Computational construction of gene co-expression networks can be a valuable tool for linking lncRNAs and coding RNAs and also for beginning to infer potential biological functions, because co-expressed genes are often members of the same pathway or protein complexes, are often either functionally related, or are controlled by the same transcriptional regulatory program [33, 40–42].…”

Section: Resultsmentioning

confidence: 99%

Transposable elements contribute to regulatory hub stress-related long noncoding RNAs in Maize

Zhou

et al. 2019

Preprint

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Several studies have mined short-read RNA sequencing datasets to identify lncRNAs, and others have focused on the function of individual lncRNA in abiotic stress response. However, our understanding of the complement, function and origin of long-non-coding RNA (lncRNAs) response to abiotic stress, especially transposon derived lncRNA (TE-lncRNA), is still in its infancy. To discover and study lncRNAs in maize (Zea mays ssp. mays), we utilized a dataset of 127 RNA sequencing samples that included PacBio fl-cDNA and total RNA-Seq datasets. Overall, we identified 23,309 candidate lncRNAs, 60% of which were identified in polyadenylated (polyA+) samples. The majority (65%) of the 23,309 lncRNAs had sequence similarity to transposable elements (TEs). Most had similarity to long-terminal-repeat retrotransposons from the Copia and Gypsy superfamilies, representing the high proportion of these elements in the genome, but class II, DNA transposons were enriched for lncRNAs relative to their genomic representation by 2-fold. By assessing the fraction of lncRNAs that respond to abiotic stresses like heat, cold, salt and drought, we identified 1,077 differentially expressed lncRNA transcripts. Their expression was correlated (r2=0.48) with their nearest gene, suggesting that lncRNAs are subject to some of the cis regulatory features as neighboring genes. By inferring co-expression networks across our large dataset, we found that 39 lncRNAs act as major hubs in co-expression networks, of which 18 appeared to be derived from TEs. These results suggest that lncRNAs, especially TE-lncRNAs, may play key regulatory roles in moderating abiotic responses.

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Section: Resultsmentioning

confidence: 99%

Transposable elements contribute to regulatory hub stress-related long noncoding RNAs in Maize

Zhou

et al. 2019

Preprint

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“…This dataset was included in the generation of the GENIE3 network. The senescence-specific time course was first published in [3], from the spring wheat cultivar Bobwhite, and was not included in the GENIE3 network.…”

Section: Methodsmentioning

confidence: 99%

“…Twenty transcription factors were identified which had a higher shared ratio between the GENIE3-predicted targets and the RNA-Seq DEGs than NAM-A1 itself. ( A ) Their expression pattern is shown across a developmental time course [2] and a senescence-specific time course [3]. The TPM reported is averaged across three samples of the same tissue and timepoint from each dataset.…”

Section: Methodsmentioning

confidence: 99%

“…More recently, a high-quality genome and gene annotation has facilitated transcriptomics work in wheat [1, 2]. This has allowed the use of substantial RNA-Seq datasets to build gene regulatory networks and predict transcription factors involved in complex processes such as senescence [3] and grain development [4, 5]. However, these studies typically use bespoke RNA-Seq datasets to generate the regulatory networks, rather than exploiting publicly-available data.…”

Section: Introductionmentioning

confidence: 99%

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Validation and characterisation of a wheat GENIE3 network using an independent RNA-Seq dataset

Harrington

Singh

et al. 2019

Preprint

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13Gene regulatory networks are powerful tools which facilitate hypothesis generation and candidate 14 gene discovery. However, the extent to which the network predictions are biologically relevant is 15 often unclear. Recently, as part of an analysis of the RefSeqv1.0 wheat transcriptome, a GENIE3 16network which predicted targets of wheat transcription factors was produced. Here we have used an 17 independent and publicly-available RNA-Seq dataset to validate the predictions of the wheat GENIE3 18 network for the senescence-regulating transcription factor NAM-A1 (TraesCS6A02G108300). We re-19analysed the RNA-Seq data against the RefSeqv1.0 genome and identified a de novo set of 20 differentially expressed genes (DEGs) between the wild-type and nam-a1 mutant which recapitulated 21 the known role of NAM-A1 in senescence and nutrient remobilisation. We found that the GENIE3-22predicted target genes of NAM-A1 overlap significantly with the de novo DEGs, more than would be 23 expected for a random transcription factor. Based on high levels of overlap between GENIE3-24 predicted target genes and the de novo DEGs, we also identified a set of candidate senescence 25 regulators. We then explored genome-wide trends in the network related to polyploidy and 26 homoeolog expression levels and found that only homoeologous transcription factors are likely to 27 share predicted targets in common. However, homoeologs in dynamic triads, i.e. with higher variation 28 in homoeolog expression levels across tissues, are less likely to share predicted targets than stable 29triads. This suggests that homoeologs in dynamic triads are more likely to act on distinct pathways. 30This work demonstrates that the wheat GENIE3 network can provide biologically-relevant predictions 31 of transcription factor targets, which can be used for candidate gene prediction and for global analyses 32of transcription factor function. The GENIE3 network has now been integrated into the KnetMiner 33 web application, facilitating its use in future studies. 34 35

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“…Most of the essential domestication genes of crop plants have been shown to encode transcription factors (Borrill et al, 2019). Plants regulate intrinsic gene expression by transcription factors (TFs), transcriptional regulators (TRs), chromatin regulators (CRs) and the basal transcription machinery (Dai et al, 2013).…”

Section: Transcription Factorsmentioning

confidence: 99%

Rice Bean (Vigna umbellata) draft genome sequence: unravelling the late flowering and unpalatability related genomic resources for efficient domestication of this underutilized crop

Kaul

Eswaran

Thangaraj

et al. 2019

Preprint

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Rice bean is a less well known and underutilized legume crop that has proved to be highly favourable due to its rich nutritional value in comparison with other members of the Vigna family. As an initiative to compose rice bean (Vigna umbellata) genomic resource, the size of 414 mega-base pairs with an estimate of 31276 highly confidential genes from 15521 scaffolds and functional coverage of 96.08% was sequenced from 30X coverage data from Illumina and PacBio platform. Rice bean genome assembly was found to be exquisitely close to V. angularis (experimental control/outgroup), V. radiata and V. unguiculata, however, V. angularis being the closest. Heuristically, the assembled genome was further aligned with 31 leguminous plants (13 complete genomes and 18 partial genomes), by collinearity block mapping. Further, we predicted similar discriminant results by complete CDS alignment. In contrast, 17 medically influential genomes from NIGMS-NIH, when compared with rice bean assembly for LCB clusters led to identification of more than 18000 genes from the entire selected medicinal genomes. Empirical construction of all genome comparisons revealed symplesiomorphic character in turn uncovering the lineage of genetic and functional features of rice beans. Signifiacantly, we found deserving late-flowering genes, palatablyindexed uncommon genes that regulate various metabolite pathways, related to abiotic and biotic stress pathways and those that are specific to photoperiod and disease resistance and so on. Further, we developed a repository for underutilised crop genome facility using D3.js at www.nicg.in. Therefore, the findings from this report addresses the genomic value of rice bean to be escalated via breeding by allied and applied approaches.Research), IBPR (International Board for Plant Genetic Resources) and ICUC (International Centre for Underutilized Crops) organisations, form a network called FOSRIN (Food Security through Ricebean Research in India and Nepal), wherein Rice bean has been labeled as one of the future crops foreseen for domestication by farmers in marginal lands (Venkatesha 2012).Despite the nutritional excellence of rice bean, the prevailing lack of awareness of its complete nutritional benefits means that rice bean can be categorized as an underutilized crop. Rice bean can become established and grow in various soil types. It is pest resistant and presents tremendous potential as a nutritious fodder and high-quality grain. The major drawbacks of this pulse crop of the kharif season include late flowering, indeterminate nature and tastelessness. Furthermore, there are meagre possibilities for the improvement of rice bean due to its predominant landraces, nominal modern plant breeding and limited seed supply. Consequently, the high diversity retained within its limited geographical distribution and the existence of few marketing channels mean that there is a great scope for the genetic improvement of rice bean. Despite the importance of rice bean as a multipurpose legume utilized for culinary purpos...

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Identification of Transcription Factors Regulating Senescence in Wheat through Gene Regulatory Network Modelling

Cited by 75 publications

References 78 publications

Transposable elements contribute to regulatory hub stress-related long noncoding RNAs in Maize

Transposable elements contribute to regulatory hub stress-related long noncoding RNAs in Maize

Validation and characterisation of a wheat GENIE3 network using an independent RNA-Seq dataset

Rice Bean (Vigna umbellata) draft genome sequence: unravelling the late flowering and unpalatability related genomic resources for efficient domestication of this underutilized crop

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