scholarly journals Transcriptome analysis of drought-tolerant sorghum genotype SC56 in response to water stress reveals an oxidative stress defense strategy

2019 ◽  
Author(s):  
Farida Olden ◽  
Arthur G. Hunt ◽  
Randy Dinkins
Keyword(s):  
Oxidative Stress ◽  
Water Stress ◽  
Drought Tolerance ◽  
Stress Tolerance ◽  
Differential Expression ◽  
Expression Analysis ◽  
Transcriptome Analysis ◽  
Differential Expression Analysis ◽  
Drought Tolerant ◽  
Drought Conditions

Abstract Background Drought tolerance is a crucial trait for crops to curtail the yield loss inflicted by water stress to crops, yet genetic improvement efforts are challenged by the complexity of this character. The adaptation of sorghum to abiotic stress, its genotypic variability, and relatively small genome make this species well-suited to dissect the molecular basis of drought tolerance. One efficient approach to this question is the use of differential transcriptome analysis, which provides a snapshot of the processes underlying drought response as well as genes that might be determinants of the drought tolerance trait. Results RNA sequencing was used to compare the transcriptome profiles of two sorghum lines, the drought-tolerant SC56 and the drought-sensitive Tx7000. The differential expression analysis revealed unambiguous genotypic disparities, including a massive increase of upregulated transcripts in SC56. Concomitantly, gene ontology enrichment showed that SC56 biologically outperformed Tx7000 in wet conditions, since it upregulated processes driving growth and guaranteeing homeostasis. The drought tolerance of SC56 seems to be an intrinsic trait that occurs through the overexpression of stress tolerance genes in wet conditions, notably those acting in defense against oxidative stress (SOD1, SOD2, VTC1, MDAR1, MSRB2, and ABC1K1). Under drought conditions, SC56 enhanced its transmembrane transport and maintained growth-promoting mechanisms similar to those implemented under wet conditions. SC56 also appears to preserve its biological function, in a limiting environment, by relying on reported validated stress tolerance genes that heighten the antioxidant capacity (SOD1, RCI3, VTE1, UCP1, FD1, and FD2), regulatory factors (CIPK1 and CRK7), and repressors of premature senescence (SAUL1). Of the stress tolerance genes overexpressed under both wet and drought conditions, DHAR2 might be a key determinant of drought tolerance since its role in recycling ascorbic acid was described to be directly linked to protection against reactive oxygen species-mediated damage, positive effects on photosynthetic activity, higher rate of plant growth, and delayed leaf aging. Conclusion The differential expression analysis uncovered biological processes which upregulation enables SC56 to be a better accumulator of biomass and connects the drought tolerance trait to key stress tolerance genes, making this genotype a judicious choice for isolation of tolerance genes.

scholarly journals Transcriptome analysis of peripheral whole blood identifies crucial lncRNAs implicated in childhood asthma

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
Peiyan Zheng ◽  
Chen Huang ◽  
Dongliang Leng ◽  
Baoqing Sun ◽  
Xiaohua Douglas Zhang
Keyword(s):  
Network Analysis ◽  
Differential Expression ◽  
Expression Analysis ◽  
Transcriptome Analysis ◽  
Childhood Asthma ◽  
Differential Expression Analysis ◽  
Rna Molecules ◽  
Asthmatic Children ◽  
Distinct Level ◽  
Before And After

Abstract Background Asthma is a chronic disorder of both adults and children affecting more than 300 million people heath worldwide. Diagnose and treatment for asthma, particularly in childhood asthma have always remained a great challenge because of its complex pathogenesis and multiple triggers, such as allergen, viral infection, tobacco smoke, dust, etc. It is thereby great significant to deeply investigate the transcriptome changes in asthmatic children before and after desensitization treatment, in order that we could identify potential and key mRNAs and lncRNAs which might be considered as useful RNA molecules for observing and supervising desensitization therapy for asthma, which might guide the diagnose and therapy in childhood asthma. Methods In the present study, we performed a systematic transcriptome analysis based on the deep RNA sequencing of ten asthmatic children before and after desensitization treatment, including identification of lncRNAs using a stringent filtering pipeline, differential expression analysis and network analysis, etc. Results First, a large number of lncRNAs were identified and characterized. Then differential expression analysis revealed 39 mRNAs and 15 lncRNAs significantly differentially expressed which involved in two biological processes and pathways. A co-expressed network analysis figured out a desensitization-treatment-related module which contains 27 mRNAs and 21 lncRNAs using WGCNA R package. Module analysis disclosed 17 genes associated to asthma at distinct level. Subsequent network analysis based on PCC figured out several key lncRNAs probably interacted to those key asthma-related genes, i.e., LINC02145, GUSBP2. Our functional investigation indicated that their functions might involve in immune, inflammatory response and apoptosis process. Conclusions Our study successfully discovered many key noncoding RNA molecules related to pathogenesis of asthma and relevant treatment, which may provide some clues for asthmatic diagnose and therapy in future.

scholarly journals Best practices on the differential expression analysis of multi-species RNA-seq

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Matthew Chung ◽  
Vincent M. Bruno ◽  
David A. Rasko ◽  
Christina A. Cuomo ◽  
José F. Muñoz ◽  
...  
Keyword(s):  
Best Practices ◽  
Differential Expression ◽  
Expression Analysis ◽  
Differential Expression Analysis ◽  
Single Species ◽  
Rna Seq ◽  
Species Analysis ◽  
Differential Gene ◽  
Multiple Species ◽  
Downstream Analysis

AbstractAdvances in transcriptome sequencing allow for simultaneous interrogation of differentially expressed genes from multiple species originating from a single RNA sample, termed dual or multi-species transcriptomics. Compared to single-species differential expression analysis, the design of multi-species differential expression experiments must account for the relative abundances of each organism of interest within the sample, often requiring enrichment methods and yielding differences in total read counts across samples. The analysis of multi-species transcriptomics datasets requires modifications to the alignment, quantification, and downstream analysis steps compared to the single-species analysis pipelines. We describe best practices for multi-species transcriptomics and differential gene expression.

scholarly journals Genetic Diversity of Selected Rice Genotypes under Water Stress Conditions

Plants ◽  
2020 ◽  
Vol 10 (1) ◽  
pp. 27
Author(s):  
Mahmoud M. Gaballah ◽  
Azza M. Metwally ◽  
Milan Skalicky ◽  
Mohamed M. Hassan ◽  
Marian Brestic ◽  
...  
Keyword(s):  
Genetic Diversity ◽  
Water Stress ◽  
Drought Stress ◽  
Drought Tolerance ◽  
Ssr Markers ◽  
Similarity Index ◽  
Stress Conditions ◽  
Yield Potential ◽  
Drought Tolerant ◽  
Rice Genotypes

Drought is the most challenging abiotic stress for rice production in the world. Thus, developing new rice genotype tolerance to water scarcity is one of the best strategies to achieve and maximize high yield potential with water savings. The study aims to characterize 16 rice genotypes for grain and agronomic parameters under normal and drought stress conditions, and genetic differentiation, by determining specific DNA markers related to drought tolerance using Simple Sequence Repeats (SSR) markers and grouping cultivars, establishing their genetic relationship for different traits. The experiment was conducted under irrigated (normal) and water stress conditions. Mean squares due to genotype × environment interactions were highly significant for major traits. For the number of panicles/plants, the genotypes Giza179, IET1444, Hybrid1, and Hybrid2 showed the maximum mean values. The required sterility percentage values were produced by genotypes IET1444, Giza178, Hybrid2, and Giza179, while, Sakha101, Giza179, Hybrid1, and Hybrid2 achieved the highest values of grain yield/plant. The genotypes Giza178, Giza179, Hybrid1, and Hybrid2, produced maximum values for water use efficiency. The effective number of alleles per locus ranged from 1.20 alleles to 3.0 alleles with an average of 1.28 alleles, and the He values for all SSR markers used varied from 0.94 to 1.00 with an average of 0.98. The polymorphic information content (PIC) values for the SSR were varied from 0.83 to 0.99, with an average of 0.95 along with a highly significant correlation between PIC values and the number of amplified alleles detected per locus. The highest similarity coefficient between Giza181 and Giza182 (Indica type) was observed and are susceptible to drought stress. High similarity percentage between the genotypes (japonica type; Sakha104 with Sakha102 and Sakha106 (0.45), Sakha101 with Sakha102 and Sakha106 (0.40), Sakha105 with Hybrid1 (0.40), Hybrid1 with Giza178 (0.40) and GZ1368-S-5-4 with Giza181 (0.40)) was also observed, which are also susceptible to drought stress. All genotypes are grouped into two major clusters in the dendrogram at 66% similarity based on Jaccard’s similarity index. The first cluster (A) was divided into two minor groups A1 and A2, in which A1 had two groups A1-1 and A1-2, containing drought-tolerant genotypes like IET1444, GZ1386-S-5-4 and Hybrid1. On the other hand, the A1-2 cluster divided into A1-2-1 containing Hybrid2 genotype and A1-2-2 containing Giza179 and Giza178 at coefficient 0.91, showing moderate tolerance to drought stress. The genotypes GZ1368-S-5-4, IET1444, Giza 178, and Giza179, could be included as appropriate materials for developing a drought-tolerant variety breeding program. Genetic diversity to grow new rice cultivars that combine drought tolerance with high grain yields is essential to maintaining food security.

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