Transcriptome Profile of Near-isogenic Soybean Lines for α-Subunit Deficiency during Seed Maturation
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ABSTRACT:
ORGANISM(S): Glycine max
PROVIDER: GSE79327 | GEO | 2017/02/11
SECONDARY ACCESSION(S): PRJNA315512
REPOSITORIES: GEO
Similar Datasets
Project description:Crossing, backcrossing, and molecular marker-assisted background selection produced a soybean (Glycine max) near-isogenic line (cgy-2-NIL) containing the cgy-2 allele, which is responsible for the absence of the allergenic α-subunit of β-conglycinin. To identify α-null-related transcriptional changes, the gene expressions of cgy-2-NIL and its recurrent parent DN47 were compared using Illumina high-throughput RNA-sequencing of samples at 25, 35, 50, and 55 days after flowering (DAF). Seeds at 18 DAF served as the control. Comparison of the transcript profiles identified 3,543 differentially expressed genes (DEGs) between the two genotypes, with 2,193 genes downregulated and 1,350 genes upregulated. The largest numbers of DEGs were identified at 55 DAF. The DEGs identified at 25 DAF represented a unique pattern of GO category distributions. KEGG pathway analyses identified 541 altered metabolic pathways in cgy-2-NIL. At 18DAF, 12 DEGs were involved in arginine and proline metabolism. The cgy-2 allele in the homozygous form modified the expression of several Cupin allergen genes. The cgy-2 allele is an alteration of a functional allele that is closely related to soybean protein amino acid quality, and is useful for hypoallergenic soybean breeding programs that aim to improve seed protein quality.
| S-EPMC4988716 | biostudies-literature
Project description:Phytophthora root and stem rot (PRR) of soybean, caused by Phytophthora sojae, is effectively controlled by Rps genes in soybean. Rps genes are race-specific, yet the mechanism of resistance, as well as susceptibility, remains largely unclear. Taking advantage of RNA-seq technology, we sequenced the transcriptomes of 10 near isogenic lines (NIL), each with a unique Rps gene, and the recurrent susceptible parent ‘Williams’. A total of 4330 differentially expressed genes (DEGs) were identified in ‘Williams’ while 2075 to 5499 DEGs were identified in each NIL. Comparisons between the NILs and ‘Williams’ allowed classification of two major groups of DEGs of interest: incompatible reaction associated genes (IRAGs) and compatible reaction associated genes (CRAGs). Hierarchical cluster analysis divided NILs into three clusters: Cluster I (Rps1-a), Cluster II (Rps1-b, 1-c and 1-k) and Cluster III (Rps3-a, 3-b, 3-c, 4, 5, and 6). Heatmap analysis, along with GO analysis suggested that the diversity of clusters for NILs were likely due to variation of the number of DEGs and the intensity of gene expression, rather than functional differentiation. Further analysis suggested that transcription factors might play pivotal role in determination of the cluster pattern, and that WRKY family were strongly associated with incompatible reactions. Analysis of IRAGs and CRAGs with putative functions suggested that the regulation of many phytohormone signaling pathways were associated with incompatible or compatible interactions with potential crosstalk between each other. As such, our study provides an in depth view of both incompatible and compatible interactions between soybean and P. sojae, which provides further insight into the mechanisms involved in host-pathogen interactions.
2014-04-16 | GSE48524 | GEO
Project description:Phytophthora root and stem rot (PRR) of soybean, caused by Phytophthora sojae, is effectively controlled by Rps genes in soybean. Rps genes are race-specific, yet the mechanism of resistance, as well as susceptibility, remains largely unclear. Taking advantage of RNA-seq technology, we sequenced the transcriptomes of 10 near isogenic lines (NIL), each with a unique Rps gene, and the recurrent susceptible parent ‘Williams’. A total of 4330 differentially expressed genes (DEGs) were identified in ‘Williams’ while 2075 to 5499 DEGs were identified in each NIL. Comparisons between the NILs and ‘Williams’ allowed classification of two major groups of DEGs of interest: incompatible reaction associated genes (IRAGs) and compatible reaction associated genes (CRAGs). Hierarchical cluster analysis divided NILs into three clusters: Cluster I (Rps1-a), Cluster II (Rps1-b, 1-c and 1-k) and Cluster III (Rps3-a, 3-b, 3-c, 4, 5, and 6). Heatmap analysis, along with GO analysis suggested that the diversity of clusters for NILs were likely due to variation of the number of DEGs and the intensity of gene expression, rather than functional differentiation. Further analysis suggested that transcription factors might play pivotal role in determination of the cluster pattern, and that WRKY family were strongly associated with incompatible reactions. Analysis of IRAGs and CRAGs with putative functions suggested that the regulation of many phytohormone signaling pathways were associated with incompatible or compatible interactions with potential crosstalk between each other. As such, our study provides an in depth view of both incompatible and compatible interactions between soybean and P. sojae, which provides further insight into the mechanisms involved in host-pathogen interactions. 22 samples were sequenced, 11 inoculated with P. sojae, the other 11 were mock-inoculated
2014-04-16 | E-GEOD-48524 | biostudies-arrayexpress
Project description:Near isogenic lines (NILs) are a critical genetic resource for the soybean research community. The ability to identify and characterize the genes driving the phenotypic differences between NILs is limited by the degree to which differential genetic introgressions can be resolved. Furthermore, the genetic heterogeneity extant among NIL sub-lines is an unaddressed research topic that might have implications for how genomic and phenotypic data from NILs are utilized. In this study, a recently developed high-resolution comparative genomic hybridization (CGH) platform was used to investigate the structure and diversity of genetic introgressions in two classical soybean NIL populations, respectively varying in protein content and iron deficiency chlorosis (IDC) susceptibility. There were three objectives: assess the capacity for CGH to resolve genomic introgressions, identify introgressions that are heterogeneous among NIL sub-lines, and associate heterogeneous introgressions with susceptibility to IDC. Using the CGH approach, introgression boundaries were refined and previously unknown introgressions were revealed. Furthermore, heterogeneous introgressions were identified within seven sub-lines of the IDC NIL "IsoClark." This included three distinct introgression haplotypes linked to the major iron susceptible locus on chromosome 03. A phenotypic assessment of the seven sub-lines did not reveal any differences in IDC susceptibility, indicating that the genetic heterogeneity among the lines does not have a significant impact on the primary NIL phenotype.
| S-EPMC3633938 | biostudies-literature
Project description:To investigate the genetic relationship between two major grain length loci GS3 and qGL3, we developed the near-isogenic lines (NILs), NIL-GS3 (GS3/qGL3), NIL-qgl3 (gs3/qgl3), NIL-GS3/qgl3 (GS3/qgl3) in the background of 93-11 (gs3/qGL3) by crossing and MAS approach.
2014-07-22 | GSE59619 | GEO
Project description:The soybean aphid, a plant sap sucking insect, is an important soybean pest in the USA causing significant yield losses. The Rag2 gene of soybean provides resistance to soybean aphid biotypes I and II. Transcriptomic analyses were performed on near isogenic lines (NILs) with the Rag2 allele for aphid resistance or rag2 for susceptibility at the Rag2 locus. Soybeans were infested with soybean aphids and leaves were collected at 0, 4, 8, 24, and 48 hours after infestation. RNA were extracted and a high throughput RNA-seq approach was used to examine mRNA expression in Rag2 and rag2 soybean leaves. The expression of ~43,000 genes was detected in both the Rag2 and rag2 leaves. Statistical analysis identified 2361 genes significantly regulated between the resistant and susceptible lines at different times after aphid infestation. Genes found up-regulated in the Rag2 line were annotated as involved in the cell wall, secondary and hormone metabolism, as well as in stress, signaling and transcriptional responses. Genes found up-regulated in the rag2 line were annotated as involved in photosynthesis and carbon metabolism. Interestingly, mRNAs of 2 genes (unknown and mitochondrial protease) located within the Rag2 locus were expressed significantly higher in the resistant genotype. The expression of the putative NBS-LRR resistant gene present in the Rag2 locus was not different between the two soybean lines. However, another NBL-LRR gene located just at the border of the Rag2 locus was and, therefore, may be involved in the differential resistance to aphid infestation exhibited by the two NIL genotypes analyzed.
2016-04-08 | GSE67779 | GEO
Project description:BACKGROUND: Iron is one of fourteen mineral elements required for proper plant growth and development of soybean (Glycine max L. Merr.). Soybeans grown on calcareous soils, which are prevalent in the upper Midwest of the United States, often exhibit symptoms indicative of iron deficiency chlorosis (IDC). Yield loss has a positive linear correlation with increasing severity of chlorotic symptoms. As soybean is an important agronomic crop, it is essential to understand the genetics and physiology of traits affecting plant yield. Soybean cultivars vary greatly in their ability to respond successfully to iron deficiency stress. Microarray analyses permit the identification of genes and physiological processes involved in soybean's response to iron stress. RESULTS: RNA isolated from the roots of two near isogenic lines, which differ in iron efficiency, PI 548533 (Clark; iron efficient) and PI 547430 (IsoClark; iron inefficient), were compared on a spotted microarray slide containing 9,728 cDNAs from root specific EST libraries. A comparison of RNA transcripts isolated from plants grown under iron limiting hydroponic conditions for two weeks revealed 43 genes as differentially expressed. A single linkage clustering analysis of these 43 genes showed 57% of them possessed high sequence similarity to known stress induced genes. A control experiment comparing plants grown under adequate iron hydroponic conditions showed no differences in gene expression between the two near isogenic lines. Expression levels of a subset of the differentially expressed genes were also compared by real time reverse transcriptase PCR (RT-PCR). The RT-PCR experiments confirmed differential expression between the iron efficient and iron inefficient plants for 9 of 10 randomly chosen genes examined. To gain further insight into the iron physiological status of the plants, the root iron reductase activity was measured in both iron efficient and inefficient genotypes for plants grown under iron sufficient and iron limited conditions. Iron inefficient plants failed to respond to decreased iron availability with increased activity of Fe reductase. CONCLUSION: These experiments have identified genes involved in the soybean iron deficiency chlorosis response under iron deficient conditions. Single linkage cluster analysis suggests iron limited soybeans mount a general stress response as well as a specialized iron deficiency stress response. Root membrane bound reductase capacity is often correlated with iron efficiency. Under iron-limited conditions, the iron efficient plant had high root bound membrane reductase capacity while the iron inefficient plants reductase levels remained low, further limiting iron uptake through the root. Many of the genes up-regulated in the iron inefficient NIL are involved in known stress induced pathways. The most striking response of the iron inefficient genotype to iron deficiency stress was the induction of a profusion of signaling and regulatory genes, presumably in an attempt to establish and maintain cellular homeostasis. Genes were up-regulated that point toward an increased transport of molecules through membranes. Genes associated with reactive oxidative species and an ROS-defensive enzyme were also induced. The up-regulation of genes involved in DNA repair and RNA stability reflect the inhospitable cellular environment resulting from iron deficiency stress. Other genes were induced that are involved in protein and lipid catabolism; perhaps as an effort to maintain carbon flow and scavenge energy. The under-expression of a key glycolitic gene may result in the iron-inefficient genotype being energetically challenged to maintain a stable cellular environment. These experiments have identified candidate genes and processes for further experimentation to increase our understanding of soybeans' response to iron deficiency stress.
| S-EPMC2253546 | biostudies-literature
Project description:To investigate the genetic relationship between two major grain length loci GS3 and qGL3, we developed the near-isogenic lines (NILs), NIL-GS3 (GS3/qGL3), NIL-qgl3 (gs3/qgl3), NIL-GS3/qgl3 (GS3/qgl3) in the background of 93-11 (gs3/qGL3) by crossing and MAS approach. Four samples was analyzed: three near-isogenic lines (NILs), NIL-GS3 (GS3/qGL3), NIL-qgl3 (gs3/qgl3), NIL-GS3/qgl3 (GS3/qgl3) and their background of 93-11. Every sample had three independed duplications. And the primary panicle with 3-6 cm length from the three NILs and 93-11 were used for RNA preparation and hybrid with Rice Genome OneArray Microarray (Phalanx Biotech Group).
2014-07-22 | E-GEOD-59619 | biostudies-arrayexpress
Project description:Methodologies for untargeted metabolomic profiling using liquid chromatography-mass spectrometry (LC-MS) were developed and applied to lipid-depleted methanolic extracts of soybeans seeds obtained from four near isogenic soybean lines (NILs) that differed in phytate content. The four lines differed in mutations for genes encoding two highly homologous multi-drug resistant proteins (MRPs). The double mutant exhibited the low phytate/emergence phenotype whereas the other three NILs, namely the two single mutants and the wild type, did not. Lipid-depleted aqueous methanol extracts were analyzed by orthogonal chromatographic separations (reversed-phase and hydrophilic interaction) in both positive and negative ionization modes. Principal component analysis (PCA) of the LC-MS data clearly separated the low phytate line from the other three, with the major metabolite differences residing in the soyasaponin composition. Group A soyasaponins containing C22-terminated acetylated glucosides were of much lower concentration in the low phytate line, which favored terminally acetylated xyloside-based soyasaponins (soyasaponin A4, A5 and A6). Differing levels of the allergen Gly m 1 were also detected.
2016-02-04 | MTBLS120 | MetaboLights
Project description:To explore transcriptional regulations in common wheat cultivars Norstar (NO), Manitou (MA), and the near-isogenic lines (NIL) spring Norstar (SN) and winter Manitou (WM) during seasonal cold acclimation.
2018-03-30 | GSE101118 | GEO