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Inference of transcription regulatory network in low phytic acid soybean seeds

ABSTRACT: A dominant loss of function mutation in myo-inositol phosphate synthase gene and recessive loss of function mutations in two multidrug resistant protein type-ABC transporter genes not only reduce the seed phytic acid levels in soybean, but also affect the pathways associated with seed development, ultimately resulting in low emergence. To understand the regulatory mechanisms and identify key genes that intervene in the seed development process in low phytic acid crops, we performed computational inference of gene regulatory networks in low and normal phytic acid soybeans using a time course transcriptomic data and multiple network inference algorithms. We identified several transcription factors and their regulatory interactions with genes that have functions in myo-inositol biosynthesis, auxin-ABA signaling and seed dormancy. We validated the predicted regulatory network by comparing it with published regulatory interactions in Arabidopsis. Some regulatory interactions were found in the low phytic acid mutants but not in non-mutant plants. These findings provide important hypotheses on expression regulation of myo-inositol metabolism, and phytohormone signaling in developing low phytic acid soybeans. The computational pipeline used for unsupervised network learning in this study is provided as open source software and is freely available at https://lilabatvt.github.io/LPANetwork/.

ORGANISM(S): Glycine max

PROVIDER: GSE101692 | GEO | 2018/01/12

SECONDARY ACCESSION(S): PRJNA395215

REPOSITORIES: GEO

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Project description:The low phytic acid trait in soybeans can be conferred by loss-of-function mutations in genes encoding myo-inositol phosphate synthase and two epistatically interacting genes encoding multidrug-resistance protein ABC transporters. However, perturbations in phytic acid biosynthesis are associated with poor seed vigor. Since the benefits of the low phytic acid trait, in terms of end-use quality and sustainability, far outweigh the negatives associated with poor seed performance, a fuller understanding of the molecular basis behind the negatives will assist crop breeders and engineers in producing variates with low phytic acid and better germination rate. The gene regulatory network for developing low and normal phytic acid soybean seeds was previously constructed, with genes modulating a variety of processes pertinent to phytic acid metabolism and seed viability being identified. In this study, a comparative time series analysis of low and normal phytic acid soybeans was carried out to investigate the transcriptional regulatory elements governing the transitional dynamics from dry seed to germinated seed. Gene regulatory networks were reverse engineered from time series transcriptomic data of three distinct genotypic subsets composed of low phytic acid soybean lines and their normal phytic acid sibling lines. Using a robust unsupervised network inference scheme, putative regulatory interactions were inferred for each subset of genotypes. These interactions were further validated by published regulatory interactions found in Arabidopsis thaliana and motif sequence analysis. Results indicate that low phytic acid seeds have increased sensitivity to stress, which could be due to changes in phytic acid levels, disrupted inositol phosphate signaling, disrupted phosphate ion homeostasis, and altered myo-inositol metabolism. Putative regulatory interactions were identified for the latter two processes. Changes in abscisic acid signaling candidate transcription factors putatively regulating genes in this process were identified as well. Analysis of the gene regulatory networks reveal altered regulation in processes that may be affecting the germination of low phytic acid soybean seeds. Therefore, this work contributes to the ongoing effort to elucidate molecular mechanisms underlying altered seed viability, germination and field emergence of low phytic acid crops, understanding of which is necessary in order to mitigate these problems.

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Inference of transcription regulatory network in low phytic acid soybean seeds

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