scholarly journals Applying HPLC to Screening QTLs for BLB Resistance in Rice

Plants ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 2145
Author(s):  
Xiao-Xuan Du ◽  
Jae-Ryoung Park ◽  
Xiao-Han Wang ◽  
Yoon-Hee Jang ◽  
Eun-Gyeong Kim ◽  
...  
Keyword(s):  
Qtl Mapping ◽  
Candidate Genes ◽  
Resistance Genes ◽  
High Performance ◽  
Wrky Transcription Factor ◽  
Phenotypic Change ◽  
Analysis Method ◽  
Susceptible Population ◽  
Relative Expression Level ◽  
Trait Locus

Bacterial leaf blight (BLB) is caused by Xanthomonas oryzae pv. oryzae and is a major cause of rice yield reductions around the world. When diseased, plants produce a variety of metabolites to resist pathogens. In this study, the various defense metabolites were quantified using high-performance liquid chromatography (HPLC) after Xoo inoculation in a 120 Cheongcheong/Nagdong double haploid (CNDH) population. Quantitative trait locus (QTL) mapping was conducted using the concentration of the plant defense metabolites. HPLC analyzes the concentration of substances according to the severity of disease symptoms. Searching for BLB resistance candidate genes by applying this analysis method is very effective when mapping related genes. These resistance genes can be mapped directly to the causative pathogens. A total of 17 metabolites were detected by means of HPLC analysis after Xoo inoculation in the 120 CNDH population. QTL mapping of the metabolite concentrations resulted in the detection of the BLB resistance candidate gene, OsWRKYq6, in RM3343 of chromosome 6. OsWRKYq6 has a very high homology sequence with WRKY transcription factor 39, and when inoculated with Xoo, the relative expression level of the resistant population was higher than that of the susceptible population. Resistance genes have previously been detected using only phenotypic change data. In this study, resistance candidate genes were detected using the concentration of metabolites produced in plants after inoculation with pathogens. This newly developed analysis method can be used to effectively detect and identify genes directly involved in disease resistance for future studies.

scholarly journals QTL mapping in outbred populations: successes and challenges

2014 ◽  
Vol 46 (3) ◽  
pp. 81-90 ◽  
Author(s):  
Leah C. Solberg Woods
Keyword(s):  
Qtl Mapping ◽  
Candidate Genes ◽  
Complex Traits ◽  
Full Genome Sequence ◽  
Backcross Population ◽  
Animal Populations ◽  
Resolution Mapping ◽  
Trait Locus ◽  
Genomic Regions ◽  
Outbred Populations

Quantitative trait locus (QTL) mapping in animal populations has been a successful strategy for identifying genomic regions that play a role in complex diseases and traits. When conducted in an F2 intercross or backcross population, the resulting QTL is frequently large, often encompassing 30 Mb or more and containing hundreds of genes. To narrow the locus and identify candidate genes, additional strategies are needed. Congenic strains have proven useful but work less well when there are multiple tightly linked loci, frequently resulting in loss of phenotype. As an alternative, we discuss the use of highly recombinant outbred models for directly fine-mapping QTL to only a few megabases. We discuss the use of several currently available models such as the advanced intercross (AI), heterogeneous stocks (HS), the diversity outbred (DO), and commercially available outbred stocks (CO). Once a QTL has been fine-mapped, founder sequence and expression QTL mapping can be used to identify candidate genes. In this regard, the large number of alleles found in outbred stocks can be leveraged to identify causative genes and variants. We end this review by discussing some important statistical considerations when analyzing outbred populations. Fine-resolution mapping in outbred models, coupled with full genome sequence, has already led to the identification of several underlying causative genes for many complex traits and diseases. These resources will likely lead to additional successes in the coming years.

scholarly journals Identification of F3H, Major Secondary Metabolite-Related Gene That Confers Resistance against Whitebacked Planthopper through QTL Mapping in Rice

Plants ◽  
2021 ◽  
Vol 10 (1) ◽  
pp. 81
Author(s):  
Eun-Gyeong Kim ◽  
Sopheap Yun ◽  
Jae-Ryoung Park ◽  
Kyung-Min Kim
Keyword(s):  
Transcription Factors ◽  
Secondary Metabolites ◽  
Qtl Mapping ◽  
Cell Function ◽  
Poor Quality ◽  
Chromosome 4 ◽  
Biotic And Abiotic Stress ◽  
Relative Expression Level ◽  
Trait Locus ◽  
Whitebacked Planthopper

Whitebacked planthopper (WBPH) is a pest that causes serious damage to rice in Asian countries with a mild climate. WBPH causes severely rice yield losses and grain poor quality each year so needs biological control. Plants resist biotic and abiotic stress using expressing variety genes, such as kinase, phytohormones, transcription factors, and especially secondary metabolites. In this research, quantitative trait locus (QTL) mapping was performed by assigning the WBPH resistance score in the Cheongcheong/Nagdong doubled haploid (CNDH) line in 2018 and 2019. The RM280-RM6909 on chromosome 4 was detected as a duplicate in 2018, 2019, and derived from Cheongcheong. This region includes cell function, kinase, signaling, transcription factors, and secondary metabolites that protect plants from the stress of WBPH. The RM280-RM6909 on chromosome 4 contains candidate genes that are similar to the flavanone 3-hydroxylase (F3H) of rice. The F3H are homologous genes, which play an important role in biosynthesis defending against biotic stress in plants. After WBPH inoculation, the relative expression level of F3H was higher in resistant line than in a susceptible line. The newly identified WBPH resistance gene F3H by QTL mapping can be used for the breeding of rice cultivars that are resistant against WBPH.

scholarly journals Novel QTL and Meta-QTL Mapping for Major Quality Traits in Soybean

2021 ◽  
Vol 12 ◽  
Author(s):  
Heng Chen ◽  
Xiangwen Pan ◽  
Feifei Wang ◽  
Changkai Liu ◽  
Xue Wang ◽  
...  
Keyword(s):  
Qtl Mapping ◽  
Candidate Genes ◽  
Gene Annotation ◽  
Recombinant Inbred Lines ◽  
Meta Analysis ◽  
Interval Mapping ◽  
Quality Traits ◽  
Important Quality ◽  
Trait Locus ◽  
Whole Genome Resequencing

Isoflavone, protein, and oil are the most important quality traits in soybean. Since these phenotypes are typically quantitative traits, quantitative trait locus (QTL) mapping has been an efficient way to clarify their complex and unclear genetic background. However, the low-density genetic map and the absence of QTL integration limited the accurate and efficient QTL mapping in previous researches. This paper adopted a recombinant inbred lines (RIL) population derived from ‘Zhongdou27’and ‘Hefeng25’ and a high-density linkage map based on whole-genome resequencing to map novel QTL and used meta-analysis methods to integrate the stable and consentaneous QTL. The candidate genes were obtained from gene functional annotation and expression analysis based on the public database. A total of 41 QTL with a high logarithm of odd (LOD) scores were identified through composite interval mapping (CIM), including 38 novel QTL and 2 Stable QTL. A total of 660 candidate genes were predicted according to the results of the gene annotation and public transcriptome data. A total of 212 meta-QTL containing 122 stable and consentaneous QTL were mapped based on 1,034 QTL collected from previous studies. For the first time, 70 meta-QTL associated with isoflavones were mapped in this study. Meanwhile, 69 and 73 meta-QTL, respectively, related to oil and protein were obtained as well. The results promote the understanding of the biosynthesis and regulation of isoflavones, protein, and oil at molecular levels, and facilitate the construction of molecular modular for great quality traits in soybean.

Development of Simultaneous Analysis Method for Multi-Compounds Content of New Shilajit Using HPLC-UV and the Cognitive Enhancing Effect: Mongolian Shilajit

2021 ◽  
Vol 16 (7) ◽  
pp. 1934578X2110304
Author(s):  
SukJin Lee ◽  
HyeSung Ryu ◽  
WanKyunn Whang
Keyword(s):  
Quality Control ◽  
High Performance Liquid Chromatography ◽  
Liquid Chromatography ◽  
High Performance ◽  
High Resolution Mass Spectrometry ◽  
Radical Scavenging ◽  
Original Material ◽  
Analysis Method ◽  
Quality Control Standard ◽  
Quantitative Hplc Analysis

Shilajit has a longstanding use as an anti-aging and memory enhancing drug. It is known to have excellent anti-bacterial effects and is believed to be effective for cognitive enhancement, but is difficult to standardize because of the lack of quality control standards. This study, for the first time, proposes a quality control standard using a simultaneous analytical method for the drug’s multi-compound content using high-performance liquid chromatography-ultraviolet detection (HPLC-UV) as an aid for the internationalization of Mongolian Shilajit. Phenolic compounds 1-6 were isolated from Mongolian Shilajit extract using bioassay-guided isolation, and the isolated compounds were evaluated for cognitive-related anti-Alzheimer’s disease (AD) activities using 1,1-diphenyl-2-picrylhydrazyl (DPPH) free radical-scavenging, acetylcholinesterase (AChE), butyrylcholinesterase (BChE), β-site amyloid precursor protein-cleaving enzyme 1 (BACE1), and advanced glycation end-product (AGE) formation assays. The isolated compounds showed good effects for each activity. In addition, the isolated compounds were successfully quantified using a validated quantitative HPLC analysis method. As a result, the isolated compounds were suggested as standard marker compounds for Mongolian Shilajit. Also, we proved that the original material of Mongolian Shilajit is a lichen named Xanthoparmelia somloensis (Gyel.) Hale using HPLC-UV, ultra-high-performance liquid chromatography-electrospray ionization/hybrid linear trap-quadruple-orbitrap-high-resolution mass spectrometry (UHPLC-ESI/LTQ-HRMS).

scholarly journals Transcriptomic profiling of wheat near-isogenic lines reveals candidate genes on chromosome 3A for pre-harvest sprouting resistance

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Xingyi Wang ◽  
Hui Liu ◽  
Kadambot H. M. Siddique ◽  
Guijun Yan
Keyword(s):  
Candidate Genes ◽  
Quantitative Trait ◽  
Genomic Region ◽  
Nucleotide Polymorphisms ◽  
Near Isogenic Lines ◽  
Gene Effects ◽  
Isogenic Lines ◽  
Trait Locus ◽  
Grain Yield And Quality ◽  
Sprouting Resistance

Abstract Background Pre-harvest sprouting (PHS) in wheat can cause severe damage to both grain yield and quality. Resistance to PHS is a quantitative trait controlled by many genes located across all 21 wheat chromosomes. The study targeted a large-effect quantitative trait locus (QTL) QPhs.ccsu-3A.1 for PHS resistance using several sets previously developed near-isogenic lines (NILs). Two pairs of NILs with highly significant phenotypic differences between the isolines were examined by RNA sequencing for their transcriptomic profiles on developing seeds at 15, 25 and 35 days after pollination (DAP) to identify candidate genes underlying the QTL and elucidate gene effects on PHS resistance. At each DAP, differentially expressed genes (DEGs) between the isolines were investigated. Results Gene ontology and KEGG pathway enrichment analyses of key DEGs suggested that six candidate genes underlie QPhs.ccsu-3A.1 responsible for PHS resistance in wheat. Candidate gene expression was further validated by quantitative RT-PCR. Within the targeted QTL interval, 16 genetic variants including five single nucleotide polymorphisms (SNPs) and 11 indels showed consistent polymorphism between resistant and susceptible isolines. Conclusions The targeted QTL is confirmed to harbor core genes related to hormone signaling pathways that can be exploited as a key genomic region for marker-assisted selection. The candidate genes and SNP/indel markers detected in this study are valuable resources for understanding the mechanism of PHS resistance and for marker-assisted breeding of the trait in wheat.

scholarly journals QTL Mapping by SLAF-seq and Expression Analysis of Candidate Genes for Aphid Resistance in Cucumber

2016 ◽  
Vol 7 ◽  
Author(s):  
Danna Liang ◽  
Minyang Chen ◽  
Xiaohua Qi ◽  
Qiang Xu ◽  
Fucai Zhou ◽  
...  
Keyword(s):  
Qtl Mapping ◽  
Candidate Genes ◽  
Expression Analysis ◽  
Aphid Resistance
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