RNA-seq Analysis Reveals Different Drought Tolerance Mechanisms in Two Broadly Adapted Wheat Cultivars ‘TAM 111’ and ‘TAM 112’
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ABSTRACT:
PROVIDER: PRJNA659916 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR12539313_1.fastq.gz | Fastqsanger.gz | |||
| SRR12539313_2.fastq.gz | Fastqsanger.gz | |||
| SRR12539314_1.fastq.gz | Fastqsanger.gz | |||
| SRR12539314_2.fastq.gz | Fastqsanger.gz | |||
| SRR12539315_1.fastq.gz | Fastqsanger.gz |
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Project description:Wheat cultivars ‘TAM 111’ and ‘TAM 112’ have been dominantly grown in the Southern U.S. Great Plains for many years due to their excellent, yet variable, drought tolerance. To identify the molecular basis and genetic control of drought tolerance in these two landmark cultivars, RNA-seq analysis was conducted to compare gene expression difference in flag leaves under fully irrigated (wet) and water deficient (dry) conditions. Of the 122,017 gene sequences assembled, 2,254 genes showed significantly altered expression patterns under dry and wet conditions in the two cultivars. TAM 111 had 593 and 1,532 dry-wet differentially expressed genes (DEGs), and TAM 112 had 777 and 1,670 at heading and grain-filling stages, respectively. The two cultivars have 1,214 (53.9%) dry-wet DEGs in common, which agreed with their excellent adaption to drought, but 438 and 602 dry-wet DEGs were respectively shown only in TAM 111 and TAM 112 suggested that each may have a specific mechanism to cope with drought. Annotation of all 2,254 genes with dry-wet expression difference found 1,855 have functions related to biosynthesis, stress responses, defense responses, transcription factors and cellular components related to ion or protein transportation and signal transduction. Comparing hierarchical structure of biological processes, molecule functions and cellular components revealed the significant regulation differences between TAM 111 and TAM 112, particularly for genes of phosphorylation and adenyl ribonucleotide binding, and proteins located in nucleus and plasma membrane. Comparing gene expressions involved in responses to stresses of water deprivation, heat and oxidative, ABA-induced signal pathway and transcription regulation found TAM 112 have more specific dry-wet DEGs than TAM 111 with most of them up-regulated, indicating that TAM 112 is more active than TAM 111 in response to drought. In addition, 399 dry-wet DEGs with unknown functions included 258 genes encoding predicted uncharacterized proteins and 141 unannotated genes with no similar sequences identified in the databases. These may represent novel genes related to drought response in TAM 111 or TAM 112. This research thus revealed different drought-tolerance mechanisms in TAM 111 and TAM 112 and identified useful drought tolerance genes for wheat adaption.
2020-08-29 | GSE157033 | GEO
Project description:Wheat cultivars 'TAM 111' and 'TAM 112' have been dominantly grown in the Southern U.S. Great Plains for many years due to their high yield and drought tolerance. To identify the molecular basis and genetic control of drought tolerance in these two landmark cultivars, RNA-seq analysis was conducted to compare gene expression difference in flag leaves under fully irrigated (wet) and water deficient (dry) conditions. A total of 2254 genes showed significantly altered expression patterns under dry and wet conditions in the two cultivars. TAM 111 had 593 and 1532 dry-wet differentially expressed genes (DEGs), and TAM 112 had 777 and 1670 at heading and grain-filling stages, respectively. The two cultivars have 1214 (53.9%) dry-wet DEGs in common, which agreed with their excellent adaption to drought, but 438 and 602 dry-wet DEGs were respectively shown only in TAM 111 and TAM 112 suggested that each has a specific mechanism to cope with drought. Annotations of all 2254 genes showed 1855 have functions related to biosynthesis, stress responses, defense responses, transcription factors and cellular components related to ion or protein transportation and signal transduction. Comparing hierarchical structure of biological processes, molecule functions and cellular components revealed the significant regulation differences between TAM 111 and TAM 112, particularly for genes of phosphorylation and adenyl ribonucleotide binding, and proteins located in nucleus and plasma membrane. TAM 112 showed more active than TAM 111 in response to drought and carried more specific genes with most of them were up-regulated in responses to stresses of water deprivation, heat and oxidative, ABA-induced signal pathway and transcription regulation. In addition, 258 genes encoding predicted uncharacterized proteins and 141 unannotated genes with no similar sequences identified in the databases may represent novel genes related to drought response in TAM 111 or TAM 112. This research thus revealed different drought-tolerance mechanisms in TAM 111 and TAM 112 and identified useful drought tolerance genes for wheat adaption. Data of gene sequence and expression regulation from this study also provided useful information of annotating novel genes associated with drought tolerance in the wheat genome.
| S-EPMC7900135 | biostudies-literature
Project description:TAM 111 and TAM 112 are two popular cultivars grown in the Southern US Great Plains with significantly different protein content. Thus, to investigate likely regulatory differences, transcriptome data were analyzed from developing grains at early- and mid-filling stages.
2022-11-02 | GSE210495 | GEO
Project description:Water deficit stress between the booting and grain filling stages significantly affect grain yield and quality of hard red winter wheat. Several stress tolerant cultivars with different adaptation mechanisms have been released and are widely cultivated on the Southern Great Plains of the US. However, the physiological, molecular, and genetic basis of adaptation to drought stress for these cultivars remains unknown. Use of transcriptome profiling to identify drought responsive genes in hexaploid wheat is a challenging process given the quantitative nature of drought stress, genome complexity, and the intricacy of interaction effects. If the information generated from functional genomics studies is to be used in molecular breeding programs for cultivar development, it is highly desirable to use cultivars better adapted for the region. In the current study we used two well-adapted, drought-tolerant, high-yielding, cultivated varieties, TAM 111 and TAM 112, which appear to have different adaptation mechanisms, to identify drought stress induced transcripts during heading and early dough stages. A set of 24 Affymetrix GeneChip wheat genome arrays (2 cultivars; 2 water treatments; 2 sampling stages; 3 biological replicates) from plants subjected to water deficit stress under controlled glasshouse conditions. Differentially expressed genes were identified using a ANOVA (p<0.01) controlling false discovery rate (FDR, q<0.01) using Benjamini Hochberg approach.
2022-01-01 | GSE45262 | GEO
Project description:Two drought-tolerant wheat cultivars, 'TAM 111' and 'TAM 112', have been widely grown in the Southern Great Plains of the U.S. and used as parents in many wheat breeding programs worldwide. This study aimed to reveal genetic control of yield and yield components in the two cultivars under both dryland and irrigated conditions. A mapping population containing 124 F5:7 recombinant inbred lines (RILs) was developed from the cross of TAM 112/TAM 111. A set of 5,948 SNPs from the wheat 90K iSelect array and double digest restriction-site associated DNA sequencing was used to construct high-density genetic maps. Data for yield and yield components were obtained from 11 environments. QTL analyses were performed based on 11 individual environments, across all environments, within and across mega-environments. Thirty-six unique consistent QTL regions were distributed on 13 chromosomes including 1A, 1B, 1D, 2A, 2D, 3D, 4B, 4D, 6A, 6B, 6D, 7B, and 7D. Ten unique QTL with pleiotropic effects were identified on four chromosomes and eight were in common with the consistent QTL. These QTL increased dry biomass grain yield by 16.3 g m-2, plot yield by 28.1 g m-2, kernels spike-1 by 0.7, spikes m-2 by 14.8, thousand kernel weight by 0.9 g with favorable alleles from either parent. TAM 112 alleles mainly increased spikes m-2 and thousand kernel weight while TMA 111 alleles increased kernels spike-1, harvest index and grain yield. The saturated genetic map and markers linked to significant QTL from this study will be very useful in developing high throughput genotyping markers for tracking the desirable haplotypes of these important yield-related traits in popular parental cultivars.
| S-EPMC7710072 | biostudies-literature
Project description:In the Southern Great Plains, wheat cultivars have been selected for a combination of outstanding yield and drought tolerance as a long-term breeding goal. To understand the underlying genetic mechanisms, this study aimed to dissect the quantitative trait loci (QTL) associated with yield components and kernel traits in two wheat cultivars `TAM 112' and `Duster' under both irrigated and dryland environments. A set of 182 recombined inbred lines (RIL) derived from the cross of TAM 112/Duster were planted in 13 diverse environments for evaluation of 18 yield and kernel related traits. High-density genetic linkage map was constructed using 5,081 single nucleotide polymorphisms (SNPs) from genotyping-by-sequencing (GBS). QTL mapping analysis detected 134 QTL regions on all 21 wheat chromosomes, including 30 pleiotropic QTL regions and 21 consistent QTL regions, with 10 QTL regions in common. Three major pleiotropic QTL on the short arms of chromosomes 2B (57.5 - 61.6 Mbps), 2D (37.1 - 38.7 Mbps), and 7D (66.0 - 69.2 Mbps) colocalized with genes Ppd-B1, Ppd-D1, and FT-D1, respectively. And four consistent QTL associated with kernel length (KLEN), thousand kernel weight (TKW), plot grain yield (YLD), and kernel spike-1 (KPS) (Qklen.tamu.1A.325, Qtkw.tamu.2B.137, Qyld.tamu.2D.3, and Qkps.tamu.6A.113) explained more than 5% of the phenotypic variation. QTL Qklen.tamu.1A.325 is a novel QTL with consistent effects under all tested environments. Marker haplotype analysis indicated the QTL combinations significantly increased yield and kernel traits. QTL and the linked markers identified in this study will facilitate future marker-assisted selection (MAS) for pyramiding the favorable alleles and QTL map-based cloning.
| S-EPMC9768232 | biostudies-literature
Project description:AtERF#111/ABR1 belongs to the group X of the ERF/AP2 transcription factor family (GXERFs) and is shoot specifically induced under submergence and hypoxia. It was described to be an ABA-response repressor, but our data hint at a completely different function. Here we present evidence that AtERF#111 is involved in the wounding response. Expression profiling of ERF#111-overexpressing (OE) plants demonstrates that AtERF#111 is a transcriptional activator of wounding response genes. Furthermore, direct target genes of AtERF#111 were identified by microarray analyses. However, knockout mutants of AtERF#111 only show a slightly reduced wounding response, suggesting the involvement of other GXERFs in wound signaling and repair mechanisms.
2019-08-28 | GSE121587 | GEO
Project description:To further analyze the change of microRNA(miRNA) between normal peritoneal macrophage(PEC) and TAM from early tumor(12 days after 4T1 cell injection) or TAM from late tumor(21 days after 4T1 cell injection) , we employed Agilent mouse microRNA microarray Rel 12.0 as a discovery platform to identify miRNAs Total RNA from peritoneal macrophage and TAM of early tumor (tumor formed for 12days after BALB/c mice injected wth 4T1 cell) or TAM of late tumor(tumor formed for 21days after BALB/c mice injected with 4T1 cell) were extracted and analyzed using Agilent mouse microRNA microarray platform, and changes of miRNA were screened out. Agilent mouse microRNA microarray is designed for the profiling of mouse miRNA .627 mouse miRNA and 39 mouse virus-related miRNA can be detected by our microRNA microarray.
2015-03-31 | E-GEOD-67408 | biostudies-arrayexpress