scholarly journals Identification of conserved and novel miRNAs responsive to heat stress in flowering Chinese cabbage using high-throughput sequencing

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Waqas Ahmed ◽  
Yanshi Xia ◽  
Hua Zhang ◽  
Ronghua Li ◽  
Guihua Bai ◽  
...  
Keyword(s):  
Heat Stress ◽  
Abiotic Stress ◽  
High Throughput ◽  
Chinese Cabbage ◽  
Stress Responses ◽  
High Throughput Sequencing ◽  
Differential Expression Analysis ◽  
Plant Responses ◽  
Limited Information ◽  
Flowering Chinese Cabbage

Abstract Plant microRNAs (miRNAs) are noncoding and endogenous key regulators that play significant functions in regulating plant responses to stress, and plant growth and development. Heat stress is a critical abiotic stress that reduces the yield and quality of flowering Chinese cabbage (Brassica campestris L. ssp. chinensis var. utilis Tsen et Lee). However, limited information is available on whether miRNAs are involved in the regulation of heat stress in B. campestris. A high-throughput sequencing approach was used to identify novel and conserved heat-responsive miRNAs in four small RNA libraries of flowering Chinese cabbage using leaves collected at 0 h, 1 h, 6 h and 12 h after a 38 °C heat-stress treatment. The analysis identified 41 conserved miRNAs (belonging to 19 MIR families), of which MIR156, MIR159, MIR168, MIR171 and MIR1885 had the most abundant molecules. Prediction and evaluation of novel miRNAs using the unannotated reads resulted in 18 candidate miRNAs. Differential expression analysis showed that most of the identified miRNAs were downregulated in heat-treated groups. To better understand functional importance, bioinformatic analysis predicted 432 unique putative target miRNAs involved in cells, cell parts, catalytic activity, cellular processes and abiotic stress responses. Furthermore, the Kyoto Encyclopedia of Genes and Genomes maps of flowering Chinese cabbage identified the significant role of miRNAs in stress adaptation and stress tolerance, and in several mitogen-activated protein kinases signaling pathways including cell death. This work presents a comprehensive study of the miRNAs for understanding the regulatory mechanisms and their participation in the heat stress of flowering Chinese cabbage.

scholarly journals Identification and Analysis of Small Interfering RNAs Associated With Heat Stress in Flowering Chinese Cabbage Using High-Throughput Sequencing

2021 ◽  
Vol 12 ◽  
Author(s):  
Waqas Ahmed ◽  
Yanshi Xia ◽  
Ronghua Li ◽  
Hua Zhang ◽  
Kadambot H.M Siddique ◽  
...  
Keyword(s):  
Heat Stress ◽  
Heat Tolerance ◽  
Chinese Cabbage ◽  
High Throughput Sequencing ◽  
Target Genes ◽  
Small Interfering Rnas ◽  
Flowering Chinese Cabbage ◽  
Disease Resistance Protein ◽  
Temperature Stimulus ◽  
Tolerance Gene

Endogenous small interfering RNAs (siRNAs) are substantial gene regulators in eukaryotes and play key functions in plant development and stress tolerance. Among environmental factors, heat is serious abiotic stress that severely influences the productivity and quality of flowering Chinese cabbage (Brassica campestris L. ssp. chinensis var. utilis Tsen et Lee). However, how siRNAs are involved in regulating gene expression during heat stress is not fully understood in flowering Chinese cabbage. Combining bioinformatical and next-generation sequencing approaches, we identified heat-responsive siRNAs in four small RNA libraries of flowering Chinese cabbage using leaves collected at 0, 1, 6, and 12 h after a 38°C heat-stress treatment; 536, 816, and 829 siRNAs exhibited substantial differential expression at 1, 6, and 12 h, respectively. Seventy-five upregulated and 69 downregulated differentially expressed siRNAs (DE-siRNAs) were common for the three time points of heat stress. We identified 795 target genes of DE-siRNAs, including serine/threonine-protein kinase SRK2I, CTR1-like, disease resistance protein RML1A-like, and RPP1, which may play a role in regulating heat tolerance. Gene ontology showed that predictive targets of DE-siRNAs may have key roles in the positive regulation of biological processes, organismal processes, responses to temperature stimulus, signaling, and growth and development. These novel results contribute to further understanding how siRNAs modulate the expression of their target genes to control heat tolerance in flowering Chinese cabbage.

scholarly journals High-throughput profiling and analysis of plant responses over time to abiotic stress

2017 ◽  
Author(s):  
Kira M. Veley ◽  
Jeffrey C. Berry ◽  
Sarah J. Fentress ◽  
Daniel P. Schachtman ◽  
Ivan Baxter ◽  
...  
Keyword(s):  
Abiotic Stress ◽  
High Throughput ◽  
Stress Responses ◽  
Low Cost ◽  
Abiotic Stress Tolerance ◽  
Crop Improvement ◽  
Plant Responses ◽  
Nitrogen Deprivation ◽  
Plant Nitrogen ◽  
Over Time

ABSTRACTSorghum (Sorghum bicolor (L.) Moench) is a rapidly growing, high-biomass crop prized for abiotic stress tolerance. However, measuring genotype-by-environment (G × E) interactions remains a progress bottleneck. Here we describe strategies for identifying shape, color and ionomic indicators of plant nitrogen use efficiency. We subjected a panel of 30 genetically diverse sorghum genotypes to a spectrum of nitrogen deprivation and measured responses using high-throughput phenotyping technology followed by ionomic profiling. Responses were quantified using shape (16 measurable outputs), color (hue and intensity) and ionome (18 elements). We measured the speed at which specific genotypes respond to environmental conditions, both in terms of biomass and color changes, and identified individual genotypes that perform most favorably. With this analysis we present a novel approach to quantifying color-based stress indicators over time. Additionally, ionomic profiling was conducted as an independent, low cost and high throughput option for characterizing G × E, identifying the elements most affected by either genotype or treatment and suggesting signaling that occurs in response to the environment. This entire dataset and associated scripts are made available through an open access, user-friendly, web-based interface. In summary, this work provides analysis tools for visualizing and quantifying plant abiotic stress responses over time. These methods can be deployed as a time-efficient method of dissecting the genetic mechanisms used by sorghum to respond to the environment to accelerate crop improvement.

scholarly journals Metabolomics-Guided Elucidation of Plant Abiotic Stress Responses in the 4IR Era: An Overview

Metabolites ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. 445
Author(s):  
Morena M. Tinte ◽  
Kekeletso H. Chele ◽  
Justin J. J. van der Hooft ◽  
Fidele Tugizimana
Keyword(s):  
Machine Learning ◽  
Abiotic Stress ◽  
Stress Responses ◽  
Abiotic Stresses ◽  
Industrial Revolution ◽  
Chemical Space ◽  
Big Data Analytics ◽  
Plant Responses ◽  
Next Generation ◽  
Computational Tools

Plants are constantly challenged by changing environmental conditions that include abiotic stresses. These are limiting their development and productivity and are subsequently threatening our food security, especially when considering the pressure of the increasing global population. Thus, there is an urgent need for the next generation of crops with high productivity and resilience to climate change. The dawn of a new era characterized by the emergence of fourth industrial revolution (4IR) technologies has redefined the ideological boundaries of research and applications in plant sciences. Recent technological advances and machine learning (ML)-based computational tools and omics data analysis approaches are allowing scientists to derive comprehensive metabolic descriptions and models for the target plant species under specific conditions. Such accurate metabolic descriptions are imperatively essential for devising a roadmap for the next generation of crops that are resilient to environmental deterioration. By synthesizing the recent literature and collating data on metabolomics studies on plant responses to abiotic stresses, in the context of the 4IR era, we point out the opportunities and challenges offered by omics science, analytical intelligence, computational tools and big data analytics. Specifically, we highlight technological advancements in (plant) metabolomics workflows and the use of machine learning and computational tools to decipher the dynamics in the chemical space that define plant responses to abiotic stress conditions.

scholarly journals The Construction of Plant Expression Vector harbouring Carica Papaya L. WRKY Gene in Escherichia coli

2020 ◽  
Vol 28 (S2) ◽  
Author(s):  
Fauziah Abu Bakar ◽  
Pavitra Paramalingam ◽  
Kamariah Hasan
Keyword(s):  
Abiotic Stress ◽  
Stress Responses ◽  
Expression Vector ◽  
Carica Papaya ◽  
Sequencing Analysis ◽  
Wrky Gene ◽  
Limited Information ◽  
Abiotic Stress Response ◽  
Plant Expression ◽  
Plant Expression Vector

Carica papaya is a well-liked and economically important fruit with outstanding nutritional and medicinal values. Its susceptibility to abiotic stress which affects the growth and harvest, causes significant yield loss to farmers. In recent years, significant progress has been made to understand the genes that play critical roles in abiotic stress response, especially some transcription factor (TF) encoding genes. Among all TFs, WRKY TF gene family is one of the best-studied TFs involved in various stress responses. To date, only limited information on functionally characterised WRKY TFs is available for C. papaya. The aim of this study was to produce a recombinant construct harbouring WRKY gene in pGEM®-T Easy cloning vector. The presence of a DNA band of the expected size of 465 bp on agarose gel electrophoresis indicated that WRKY gene was successfully amplified from all treated samples. DNA sequencing analysis revealed that the amplified sequence isolated from the treated samples were closely related to Carica papaya species with 97% similarity. Following transformation, 4 out of 5 colonies that were randomly selected showed the WRKY gene had been successfully inserted into pGEM®-T Easy vector and transformed into E. coli. In future, the WRKY gene from pGEMT-WRKY recombinant construct will be cloned into the plant expression vector pCAMBIA 1304 prior to transformation in the plant. The success of demonstrating the WRKY gene towards the response in abiotic stress will enable us to produce stress tolerant transgenic crops under unfavourable conditions via genetic engineering for sustained growth.

scholarly journals HTSeq - A Python framework to work with high-throughput sequencing data

2014 ◽  
Author(s):  
Simon Anders ◽  
Paul Theodor Pyl ◽  
Wolfgang Huber
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Rapid Development ◽  
Differential Expression Analysis ◽  
Rna Seq ◽  
Sequencing Data ◽  
Standard Work ◽  
Data Formats ◽  
High Throughput Sequencing Data ◽  
Python Package

Motivation: A large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard work flows, custom scripts are needed. Results: We present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data such as genomic coordinates, sequences, sequencing reads, alignments, gene model information, variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes. Availability: HTSeq is released as open-source software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index, https://pypi.python.org/pypi/HTSeq

Identification and characterization of microRNAs in the liver of rainbow trout in response to heat stress by high-throughput sequencing

Gene ◽  
2018 ◽  
Vol 679 ◽  
pp. 274-281 ◽  
Author(s):  
Jinqiang Huang ◽  
Yongjuan Li ◽  
Fang Ma ◽  
Yujun Kang ◽  
Zhe Liu ◽  
...  
Keyword(s):  
Heat Stress ◽  
Rainbow Trout ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Identification And Characterization

scholarly journals A Comparison of Methods: Normalizing High-Throughput RNA Sequencing Data

2015 ◽  
Author(s):  
Rahul Reddy
Keyword(s):  
Differential Expression ◽  
Expression Analysis ◽  
High Throughput ◽  
High Throughput Sequencing ◽  
Differential Expression Analysis ◽  
Simulated Data ◽  
Sequencing Data ◽  
Technical Variability ◽  
Expression Studies ◽  
Normalization Methods

As RNA-Seq and other high-throughput sequencing grow in use and remain critical for gene expression studies, technical variability in counts data impedes studies of differential expression studies, data across samples and experiments, or reproducing results. Studies like Dillies et al. (2013) compare several between-lane normalization methods involving scaling factors, while Hansen et al. (2012) and Risso et al. (2014) propose methods that correct for sample-specific bias or use sets of control genes to isolate and remove technical variability. This paper evaluates four normalization methods in terms of reducing intra-group, technical variability and facilitating differential expression analysis or other research where the biological, inter-group variability is of interest. To this end, the four methods were evaluated in differential expression analysis between data from Pickrell et al. (2010) and Montgomery et al. (2010) and between simulated data modeled on these two datasets. Though the between-lane scaling factor methods perform worse on real data sets, they are much stronger for simulated data. We cannot reject the recommendation of Dillies et al. to use TMM and DESeq normalization, but further study of power to detect effects of different size under each normalization method is merited.

scholarly journals Modulation of GmFAD3 expression alters responses to abiotic stress in soybean

2020 ◽  
Author(s):  
Ajay Singh ◽  
Mahesh Kumar ◽  
Susheel Raina ◽  
Milind Ratnaparkhe ◽  
Jagadish Rane ◽  
...  
Keyword(s):  
Heat Stress ◽  
Abiotic Stress ◽  
Fatty Acid ◽  
Stress Tolerance ◽  
Salinity Stress ◽  
Stress Responses ◽  
Fatty Acid Desaturase ◽  
Stress Conditions ◽  
Omega 3 ◽  
Soybean Plants

FAD3 play important roles in modulating membrane fluidity in response to various abiotic stresses. However, a comprehensive analysis of FAD3 in drought, salinity and heat stress tolerance is lacking in soybean. The present study assessed the functional role of fatty acid desaturase 3 to abiotic stress responses in soybean. We used Bean Pod Mottle Virus -based vector to alter expression of Glycine max omega-3 fatty acid desaturase . Higher levels of recombinant BPMV-GmFAD3 transcripts were detected in overexpressing soybean plants. Overexpression of GmFAD3 in soybean resulted in increased levels of jasmonic acid and higher expression of GmWRKY54 as compared to mock-inoculated, vector-infected and FAD3-silenced soybean plants under drought and salinity stress conditions. FAD3 overexpressing plants showed higher levels of chlorophyll content, leaf SPAD value, relative water content, chlorophyll fluorescence, transpiration rate, carbon assimilation rate, proline content and also cooler canopy under drought and salinity stress conditions as compared to mock-inoculated, vector-infected and FAD3-silenced soybean plants. Results from current study revealed that GmFAD3 overexpressing soybean plants exhibited drought and salinity stress tolerance although tolerance to heat stress was reduced. On the other hand, soybean plants silenced for GmFAD3 exhibited tolerance to heat stress, but were vulnerable to drought and salinity stress

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