Identification of novel flowering genes using RNA-Seq pipeline employing combinatorial approach in Arabidopsis thaliana time-series apical shoot meristem data

AbstractIn Arabidopsis, the genes SHOOT MERISTEMLESS (STM) and CLAVATA3 (CLV3) antagonistically regulate shoot meristem development. STM is essential for both development and maintenance of the meristem, as stm mutants fail to develop a shoot meristem during embryogenesis. CLV3, on the other hand, negatively regulates meristem proliferation, and clv3 mutants possess an enlarged shoot meristem. Genetic interaction studies revealed that stm and clv3 dominantly suppress each other’s phenotypes. STM works in conjunction with its closely related homologue KNOTTED1-LIKE HOMEOBOX GENE 6 (KNAT6) to promote meristem development and organ separation, as stm knat6 double mutants fail to form a meristem and produce a fused cotyledon. In this study, we show that clv3 fails to promote post-embryonic meristem formation in stm-1 background if we also remove KNAT6. stm-1 knat6 clv3 triple mutants result in early meristem termination and produce fused cotyledons similar to stm knat6 double mutant. Notably, the stm-1 knat6 and stm-1 knat6 clv3 alleles lack tissue in the presumed region of SAM. stm knat6 clv3 also showed reduced inflorescence size and shoot apex size as compared to clv3 single or stm clv3 double mutants. In contrast to previously published data, these data suggest that stm is epistatic to clv3 in postembryonic meristem development.HighlightSTM and KNAT6 genes determine post-embryonic meristem formation and activity in Arabidopsis. clv3 mutation is unable to rescue the stm knat6 meristemless phenotype.

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The recognition of development-related genes in the testis and MAGs of time-series Harmonia axyridis adults using a time-series analysis by RNA-seq

Gene ◽

10.1016/j.gene.2019.01.021 ◽

2019 ◽

Vol 693 ◽

pp. 52-60 ◽

Cited By ~ 1

Author(s):

Wenxiao Du ◽

Zhenjun Zhao ◽

Wei Zheng

Keyword(s):

Time Series ◽

Time Series Analysis ◽

Harmonia Axyridis ◽

Rna Seq ◽

Series Analysis

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Time Series RNA-seq in Pigeonpea Revealed the Core Genes in Metabolic Pathways under Aluminum Stress

Genes ◽

10.3390/genes11040380 ◽

2020 ◽

Vol 11 (4) ◽

pp. 380 ◽

Cited By ~ 1

Author(s):

Zhaoxu Gao ◽

Biying Dong ◽

Hongyan Cao ◽

Hang He ◽

Qing Yang ◽

...

Keyword(s):

Time Series ◽

Metabolic Pathways ◽

Expression Patterns ◽

Plant Stress ◽

Regulation Mechanism ◽

Rna Seq ◽

Aluminum Stress ◽

Biological Regulation ◽

Al Stress ◽

The Impact

Pigeonpea is an important economic crop in the world and is mainly distributed in tropical and subtropical regions. In order to further expand the scope of planting, one of the problems that must be solved is the impact of soil acidity on plants in these areas. Based on our previous work, we constructed a time series RNA sequencing (RNA-seq) analysis under aluminum (Al) stress in pigeonpea. Through a comparison analysis, 11,425 genes were found to be differentially expressed among all the time points. After clustering these genes by their expression patterns, 12 clusters were generated. Many important functional pathways were identified by gene ontology (GO) analysis, such as biological regulation, localization, response to stimulus, metabolic process, detoxification, and so on. Further analysis showed that metabolic pathways played an important role in the response of Al stress. Thirteen out of the 23 selected genes related to flavonoids and phenols were downregulated in response to Al stress. In addition, we verified these key genes of flavonoid- and phenol-related metabolism pathways by qRT-PCR. Collectively, our findings not only revealed the regulation mechanism of pigeonpea under Al stress but also provided methodological support for further exploration of plant stress regulation mechanisms.

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ELONGATA3 is required for shoot meristem cell cycle progression in Arabidopsis thaliana seedlings

Developmental Biology ◽

10.1016/j.ydbio.2013.08.008 ◽

2013 ◽

Vol 382 (2) ◽

pp. 436-445 ◽

Cited By ~ 7

Author(s):

Anna Skylar ◽

Sean Matsuwaka ◽

Xuelin Wu

Keyword(s):

Cell Cycle ◽

Arabidopsis Thaliana ◽

Cell Cycle Progression ◽

Shoot Meristem ◽

Cycle Progression ◽

Meristem Cell

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Time Series Expression Analyses Using RNA-seq: A Statistical Approach

BioMed Research International ◽

10.1155/2013/203681 ◽

2013 ◽

Vol 2013 ◽

pp. 1-16 ◽

Cited By ~ 8

Author(s):

Sunghee Oh ◽

Seongho Song ◽

Gregory Grabowski ◽

Hongyu Zhao ◽

James P. Noonan

Keyword(s):

Time Series ◽

Statistical Approach ◽

Expression Patterns ◽

Temporal Analysis ◽

Rna Seq ◽

Computationally Efficient ◽

Evolutionary Trajectory ◽

Dynamic Methods ◽

Series Expression ◽

Time Lagged

RNA-seq is becoming thede factostandard approach for transcriptome analysis with ever-reducing cost. It has considerable advantages over conventional technologies (microarrays) because it allows for direct identification and quantification of transcripts. Many time series RNA-seq datasets have been collected to study the dynamic regulations of transcripts. However, statistically rigorous and computationally efficient methods are needed to explore the time-dependent changes of gene expression in biological systems. These methods should explicitly account for the dependencies of expression patterns across time points. Here, we discuss several methods that can be applied to model timecourse RNA-seq data, including statistical evolutionary trajectory index (SETI), autoregressive time-lagged regression (AR(1)), and hidden Markov model (HMM) approaches. We use three real datasets and simulation studies to demonstrate the utility of these dynamic methods in temporal analysis.

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