Comparative transcriptomics reveals the difference in early endosperm development between maize with different amylose contents

In seeds, the endosperm is a crucial organ that plays vital roles in supporting embryo development and determining seed weight and quality. Starch is the predominant storage carbohydrate of the endosperm and accounts for ∼70% of the mature maize kernel weight. Nonetheless, because starch biosynthesis is a complex process that is orchestrated by multiple enzymes, the gene regulatory networks of starch biosynthesis, particularly amylose and amylopectin biosynthesis, have not been fully elucidated. Here, through high-throughput RNA sequencing, we developed a temporal transcriptome atlas of the endosperms of high-amylose maize and common maize at 5-, 10-, 15- and 20-day after pollination and found that 21,986 genes are involved in the programming of the high-amylose and common maize endosperm. A coexpression analysis identified multiple sequentially expressed gene sets that are closely correlated with cellular and metabolic programmes and provided valuable insight into the dynamic reprogramming of the transcriptome in common and high-amylose maize. In addition, a number of genes and transcription factors were found to be strongly linked to starch synthesis, which might help elucidate the key mechanisms and regulatory networks underlying amylose and amylopectin biosynthesis. This study will aid the understanding of the spatiotemporal patterns and genetic regulation of endosperm development in different types of maize and provide valuable genetic information for the breeding of starch varieties with different contents.

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Comparative transcriptomics reveals the difference in early endosperm development between maize with different amylose contents

10.7287/peerj.preprints.27577v1 ◽

2019 ◽

Author(s):

Zhou Jian Qu ◽

Tu Shu Xu ◽

Kang Xiao Tian ◽

Ting Li ◽

Cheng Li Wang ◽

...

Keyword(s):

Regulatory Networks ◽

Genetic Regulation ◽

Starch Synthesis ◽

Endosperm Development ◽

Starch Biosynthesis ◽

Kernel Weight ◽

Valuable Insight ◽

Storage Carbohydrate ◽

The Difference ◽

High Amylose

The endosperm is a crucial organ for seeds that plays vital roles in supporting embryo development and determining seed weight and quality. Starch is the predominant storage carbohydrate of the endosperm and accounts for ~70% of the mature maize kernel weight. Nonetheless, because starch biosynthesis is a complex process that is orchestrated by multiple enzymes, the gene regulatory networks of starch biosynthesis, particularly amylose and amylopectin biosynthesis, have not been fully elucidated. Here, through high-throughput RNA sequencing, we developed a temporal transcriptome atlas of the endosperms of high-amylose maize and common maize at 5-, 10-, 15- and 20-day after pollination and found that 21,986 genes are involved in the programming of the high-amylose maize and common maize endosperm. A coexpression analysis identified multiple sequentially expressed gene sets that are closely correlated cellular and metabolic programs and provided valuable insight into the dynamic reprogramming of the transcriptome in common and high-amylose maize. In addition, a number of genes and transcription factors (TFs) were found to be strongly linked to starch synthesis, which might help elucidate the key mechanisms and regulatory networks underlying amylose and amylopectin biosynthesis. This study will aid the understanding of the spatiotemporal patterns and genetic regulation of endosperm development in different types of maize.

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Comparative transcriptomics reveals the difference in early endosperm development between maize with different amylose contents

10.7287/peerj.preprints.27577 ◽

2019 ◽

Author(s):

Zhou Jian Qu ◽

Tu Shu Xu ◽

Kang Xiao Tian ◽

Ting Li ◽

Cheng Li Wang ◽

...

Keyword(s):

Regulatory Networks ◽

Genetic Regulation ◽

Starch Synthesis ◽

Endosperm Development ◽

Starch Biosynthesis ◽

Kernel Weight ◽

Valuable Insight ◽

Storage Carbohydrate ◽

The Difference ◽

High Amylose

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A new paradigm for animal symmetry

Interface Focus ◽

10.1098/rsfs.2015.0032 ◽

2015 ◽

Vol 5 (6) ◽

pp. 20150032 ◽

Cited By ~ 9

Author(s):

Gábor Holló

Keyword(s):

Regulatory Networks ◽

Genetic Regulation ◽

Bilateral Symmetry ◽

Whole Body ◽

Functional Requirements ◽

New Paradigm ◽

Anatomical Structures ◽

Flexible Framework ◽

The Difference ◽

Biological Patterns

My aim in this article is to soften certain rigid concepts concerning the radial and bilateral symmetry of the animal body plan, and to offer a more flexible framework of thinking for them, based on recent understandings of how morphogenesis is regulated by the mosaically acting gene regulatory networks. Based on general principles of the genetic regulation of morphogenesis, it can be seen that the difference between the symmetry of the whole body and that of minor anatomical structures is only a question of a diverse timing during development. I propose that the animal genome, as such, is capable of expressing both radial and bilateral symmetries, and deploys them according to the functional requirements which must be satisfied by both the anatomical structure and body as a whole. Although it may seem paradoxical, this flexible view of symmetry, together with the idea that symmetry is strongly determined by function, bolsters the concept that the presence of the two main symmetries in the animal world is not due to chance: they are necessary biological patterns emerging in evolution.

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Down-regulation of the Genome Uncoupled 4 Retards Starch Biosynthesis in Rice

10.21203/rs.3.rs-30603/v1 ◽

2020 ◽

Author(s):

Ruiqing Li ◽

Meng Jiang ◽

Huali Zhang

Keyword(s):

Target Genes ◽

Starch Synthesis ◽

Underlying Mechanism ◽

Starch Biosynthesis ◽

Down Regulation ◽

Dynamic Activity ◽

High Photosynthetic Capacity ◽

Storage Carbohydrate ◽

Physical Functions ◽

Abnormal Performance

Abstract BackgroundStarch is the major storage carbohydrate in rice, with essential physical functions for plant growth. The starch biosynthesis in rice employs the cooperation of nucleus and plastid, which requires regulation of the signals from nucleus to plastid. However, the plastid-to-nucleus retrograde signals for starch biosynthesis is partly mediated by tetrapyrrole intermediates, i.e., heme, but the underlying mechanism is largely unknown. In previous studies, we revealed that the Genome Uncoupled 4 (OsGUN4) mutation in rice have been revealed to greatly affect tetrapyrrole intermediates but retain a high photosynthetic capacity. ResultsHere, we further found that down-regulation of OsGUN4 promoted to accumulate sucrose but reduce the total starch, attributing to abnormal performance of metabolisms and enzyme activities of starch biosynthesis in leaves of gun4epi. Besides, the exogenous sucrose led to induced starch synthesis but reduced sucrose contents in wild-type, while norflurazon(NF) treatments could eliminate or weaken these inductions. Nevertheless, no changes were detectedbetween check and sucrose treatments in the gun4epi,whereas NF treatment enhanced the trends of increased sucrose but reduced starch,suggesting the roles of OsGUN4 on balance of photosynthesis and starch biosynthesis. Dynamic activity changes of starch biosynthetic enzymes were in accordance with the contents of carbon metabolites. Moreover, RNA sequencing revealed that a great deal DEGs were associated with starch metabolic pathways, with 62 genes being up-regulated and 25 down-regulated in gun4epi. Many genes involved in starch biosynthesis performed down-regulated expression, including the transcription factor of bZIP58 and its target genes of OsBEIIb and OsSSI, which are vital for the formation of amylopectin and starch granules, while displayed up-regulatedexpression of OsSSIIIa and OsGBSSI that promotes the formation of amylose. ConclusionIn conclusion, these findings confirm that OsGUN4 play regulatory roles on biosynthetic genes and enzyme activity in starch biosynthesis.

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Expression Pattern of Starch Biosynthesis Genes in Relation to the Starch Molecular Structure in High-Amylose Maize

Journal of Agricultural and Food Chemistry ◽

10.1021/acs.jafc.0c07354 ◽

2021 ◽

Author(s):

Yuyue Zhong ◽

Jianzhou Qu ◽

Andreas Blennow ◽

Xingxun Liu ◽

Dongwei Guo

Keyword(s):

Molecular Structure ◽

Expression Pattern ◽

Starch Biosynthesis ◽

High Amylose

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The HrpG/HrpX Regulon of Xanthomonads—An Insight to the Complexity of Regulation of Virulence Traits in Phytopathogenic Bacteria

Microorganisms ◽

10.3390/microorganisms9010187 ◽

2021 ◽

Vol 9 (1) ◽

pp. 187

Author(s):

Doron Teper ◽

Sheo Shankar Pandey ◽

Nian Wang

Keyword(s):

Regulatory Network ◽

Regulatory Networks ◽

Focal Point ◽

Genetic Regulation ◽

Transcriptional Regulators ◽

Secretion System ◽

In Planta ◽

Type 3 Secretion System ◽

Type 3 ◽

Made In

Bacteria of the genus Xanthomonas cause a wide variety of economically important diseases in most crops. The virulence of the majority of Xanthomonas spp. is dependent on secretion and translocation of effectors by the type 3 secretion system (T3SS) that is controlled by two master transcriptional regulators HrpG and HrpX. Since their discovery in the 1990s, the two regulators were the focal point of many studies aiming to decipher the regulatory network that controls pathogenicity in Xanthomonas bacteria. HrpG controls the expression of HrpX, which subsequently controls the expression of T3SS apparatus genes and effectors. The HrpG/HrpX regulon is activated in planta and subjected to tight metabolic and genetic regulation. In this review, we cover the advances made in understanding the regulatory networks that control and are controlled by the HrpG/HrpX regulon and their conservation between different Xanthomonas spp.

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Dissipativity and Error Feedback Controller Design of Time-Delay Genetic Regulatory Networks

Journal of Mathematics ◽

10.1155/2021/9940229 ◽

2021 ◽

Vol 2021 ◽

pp. 1-10

Author(s):

Yonggang Ma ◽

Junmei Liu ◽

Jiao Ai

Keyword(s):

Time Delay ◽

Regulatory Networks ◽

Controller Design ◽

Estimation Error ◽

Rapid Development ◽

Genetic Regulation ◽

Genetic Regulatory Networks ◽

Error Feedback ◽

Attraction Set ◽

Parameter Dependent

Genetic regulatory networks (GRNs) play an important role in the development and evolution of the biological system. With the rapid development of DNA technology, further research on GRNs becomes possible. In this paper, we discuss a class of time-delay genetic regulatory networks with external inputs. Firstly, under some reasonable assumptions, using matrix measures, matrix norm inequalities, and Halanay inequalities, we give the global dissipative properties of the solution of the time-delay genetic regulation networks and estimate the parameter-dependent global attraction set. Secondly, an error feedback control system is designed for the time-delay genetic control networks. Furthermore, we prove that the estimation error of the model is asymptotically stable. Finally, two examples are used to illustrate the validity of the theoretical results.

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Inference of differential gene regulatory networks based on gene expression and genetic perturbation data

Bioinformatics ◽

10.1093/bioinformatics/btz529 ◽

2019 ◽

Vol 36 (1) ◽

pp. 197-204 ◽

Cited By ~ 2

Author(s):

Xin Zhou ◽

Xiaodong Cai

Keyword(s):

Gene Expression ◽

Gene Regulatory Networks ◽

Structural Equation ◽

Regulatory Networks ◽

Supplementary Information ◽

Specific Gene ◽

Joint Inference ◽

Perturbation Data ◽

Gene Regulatory ◽

The Difference

Abstract Motivation Gene regulatory networks (GRNs) of the same organism can be different under different conditions, although the overall network structure may be similar. Understanding the difference in GRNs under different conditions is important to understand condition-specific gene regulation. When gene expression and other relevant data under two different conditions are available, they can be used by an existing network inference algorithm to estimate two GRNs separately, and then to identify the difference between the two GRNs. However, such an approach does not exploit the similarity in two GRNs, and may sacrifice inference accuracy. Results In this paper, we model GRNs with the structural equation model (SEM) that can integrate gene expression and genetic perturbation data, and develop an algorithm named fused sparse SEM (FSSEM), to jointly infer GRNs under two conditions, and then to identify difference of the two GRNs. Computer simulations demonstrate that the FSSEM algorithm outperforms the approaches that estimate two GRNs separately. Analysis of a dataset of lung cancer and another dataset of gastric cancer with FSSEM inferred differential GRNs in cancer versus normal tissues, whose genes with largest network degrees have been reported to be implicated in tumorigenesis. The FSSEM algorithm provides a valuable tool for joint inference of two GRNs and identification of the differential GRN under two conditions. Availability and implementation The R package fssemR implementing the FSSEM algorithm is available at https://github.com/Ivis4ml/fssemR.git. It is also available on CRAN. Supplementary information Supplementary data are available at Bioinformatics online.

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