Ontology highlight
ABSTRACT:
PROVIDER: PRJNA394791 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR5834390_1.fastq.gz | Fastqsanger.gz | |||
| SRR5834390_2.fastq.gz | Fastqsanger.gz |
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Project description:<p>The common cutworm (CCW; <em>Spodoptera litura</em>) is one of the major insect pests of soybean in Asia and Oceania. Although quantitative trail loci related to CCW resistance have been introduced into leading soybean cultivars, these do not exhibit sufficient resistance against CCW. Thus, understanding the genetic and metabolic resistance mechanisms of CCW as well as integrating other new resistance genes are required. In this study, we focused on a primitive soybean landrace, Peking, which has retained resistances to various pests. We found a resistance to CCW in Peking by the detached-leaf feeding assay, and subsequently determined the genetic and metabolic basis of the resistance mechanism using chromosome segment substitution lines (CSSLs) of Peking. Several characteristic metabolites for Peking were identified by the metabolomic approach using liquid chromatography/mass spectrometry combined with a principle component analysis. The structure of seven metabolites were determined by nuclear magnetic resonance (NMR) analysis. The genomic segments of Peking on chromosome 06 (Chr06) and Chr20 had a clear association with these metabolites. Moreover, a line possessing a Peking genomic segment on Chr20 inhibited growth of the CCW. The genetic factors and the metabolites on Chr20 in Peking will be useful for understanding mechanisms underlying CCW resistance and breeding resistant soybean cultivars.</p>
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Project description:Phytophthora root and stem rot caused by the oomycete pathogen Phytophthora sojae, is one of the most destructive diseases of soybean. Deploying soybean cultivars carrying race-specific resistance conferred by Rps genes is the most practicalapproach to managing this disease. Previously, two Rps genes, RpsUN1 and RpsUN2 conferring broad spectra of resistance to P. sojae isolates, were identified in a landrace PI 567139B and mapped to a 6.5-cM region on chromosome 3 and a 3.0-cM region on chromosome 16, corresponding to 840 kb and 600 kb of sequences, respectively,of the soybean reference genome. By analyzing ten and nine recombinants defined by genotypic and phenotypic screening of the 826 F2:3 families derived from two reciprocal crosses between the two parental lines of the mapping populations, RpsUN1 and RpsUN2 were further narrowed to a 151-kb region that harbors five genes including three NBS-LRR genes, and a 36-kb region that contains four genes including five NBS-LRR genes, respectively, according to the reference genome. Analysis of expressional changes of these nine genes before and after inoculation with the pathogen suggest that the counterparts of Glyma.03g034600 in the RpsUN1 region and the counterparts of Glyma.16g215200 and Glyma.16g214900 in the RpsUN2 region of PI 567139B may be associated with the resistance to P. sojae. It is also suggested that unequal recombination between different NBS-LRR genes in the mapped regions may have occurred, resulting in the formation of two recombinants with inconsistent genotypes and phenotypes detected by molecular markers within the fine-mapped regions. The haplotypes of genomic regions surrounding RpsUN1 and RpsUN2 in the entire soybean germplasm deposited in the US soybean germplasm collection were analyzed towards a better understanding of the origins of these two novel sources of resistance and screening of effective markers for marker-assisted selectionof these two resistance genes for soybean breeding.
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Project description:Interactions among genomic loci have often been overlooked in genome-wide association studies, revealing the combinatorial effects of variants on phenotype or disease manifestation. Unexplained genetic variance, interactions amongst causal genes of small effects, and biological pathways could be identified using a network biology approach. The main objective of this study was to determine the genome-wide epistatic variants affecting feed efficiency traits [feed conversion ratio (FCR) and residual feed intake (RFI)] based on weighted interaction SNP hub (WISH-R) method. Herein, we detected highly interconnected epistatic SNP modules, pathways, and potential biomarkers for the FCR and RFI in Duroc and Landrace purebreds considering the whole population, and separately for low and high feed efficient groups. Highly interacting SNP modules in Duroc (1,247 SNPs) and Landrace (1,215 SNPs) across the population and for low feed efficient (Duroc - 80 SNPs, Landrace - 146 SNPs) and high feed efficient group (Duroc - 198 SNPs, Landrace - 232 SNPs) for FCR and RFI were identified. Gene and pathway analyses identified ABL1, MAP3K4, MAP3K5, SEMA6A, KITLG, and KAT2B from chromosomes 1, 2, 5, and 13 underlying ErbB, Ras, Rap1, thyroid hormone, axon guidance pathways in Duroc. GABBR2, GNA12, and PRKCG genes from chromosomes 1, 3, and 6 pointed towards thyroid hormone, cGMP-PKG and cAMP pathways in Landrace. From Duroc low feed efficient group, the TPK1 gene was found involved with thiamine metabolism, whereas PARD6G, DLG2, CRB1 were involved with the hippo signaling pathway in high feed efficient group. PLOD1 and SETD7 genes were involved with lysine degradation in low feed efficient group in Landrace, while high feed efficient group pointed to genes underpinning valine, leucine, isoleucine degradation, and fatty acid elongation. Some SNPs and genes identified are known for their association with feed efficiency, others are novel and potentially provide new avenues for further research. Further validation of epistatic SNPs and genes identified here in a larger cohort would help to establish a framework for modelling epistatic variance in future methods of genomic prediction, increasing the accuracy of estimated genetic merit for FE and helping the pig breeding industry.
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