Combined QTL mapping, physiological and transcriptomic analyses to identify candidate genes involved in Brassica napus seed aging

2018 ◽  
Vol 293 (6) ◽  
pp. 1421-1435 ◽  
Author(s):  
Tengyue Wang ◽  
Lintao Hou ◽  
Hongju Jian ◽  
Feifei Di ◽  
Jiana Li ◽  
...  
Keyword(s):  
Brassica Napus ◽  
Qtl Mapping ◽  
Candidate Genes ◽  
Seed Aging

QTL Mapping for Seedling Dry Weight and Fresh Weight under Salt Stress and Candidate Genes Analysis in Brassica napus L.

2017 ◽  
Vol 43 (2) ◽  
pp. 179
Author(s):  
Lin-Tao HOU ◽  
Teng-Yue WANG ◽  
Hong-Ju JIAN ◽  
Jia WANG ◽  
Jia-Na LI ◽  
...  
Keyword(s):  
Salt Stress ◽  
Brassica Napus ◽  
Qtl Mapping ◽  
Candidate Genes ◽  
Dry Weight ◽  
Fresh Weight ◽  
Brassica Napus L

SEED COLOUR IN BRASSICA NAPUS: QTL MAPPING, CANDIDATE GENES AND ASSOCIATIONS WITH QUALITY TRAITS

2006 ◽  
pp. 203-210 ◽  
Author(s):  
A.G. Badani ◽  
B. Wittkop ◽  
W. Lühs ◽  
R. Baetzel ◽  
R. Horn ◽  
...  
Keyword(s):  
Brassica Napus ◽  
Qtl Mapping ◽  
Candidate Genes ◽  
Quality Traits ◽  
Seed Colour

scholarly journals QTL Mapping and Diurnal Transcriptome Analysis Identify Candidate Genes Regulating Brassica napus Flowering Time

2021 ◽  
Vol 22 (14) ◽  
pp. 7559
Author(s):  
Jurong Song ◽  
Bao Li ◽  
Yanke Cui ◽  
Chenjian Zhuo ◽  
Yuanguo Gu ◽  
...  
Keyword(s):  
Brassica Napus ◽  
Qtl Mapping ◽  
Flowering Time ◽  
Candidate Genes ◽  
Genetic Regulation ◽  
Snp Array ◽  
Expression Library ◽  
Seed Formation ◽  
Dh Population ◽  
Time Points

Timely flowering is important for seed formation and maximization of rapeseed (Brassica napus) yield. Here, we performed flowering-time quantitative trait loci (QTL) mapping using a double haploid (DH) population grown in three environments to study the genetic architecture. Brassica 60 K Illumina Infinium™ single nucleotide polymorphism (SNP) array and simple sequence repeat (SSR) markers were used for genotyping of the DH population, and a high-density genetic linkage map was constructed. QTL analysis of flowering time from the three environments revealed five consensus QTLs, including two major QTLs. A major QTL located on chromosome A03 was detected specifically in the semi-winter rapeseed growing region, and the one on chromosome C08 was detected in all environments. Ribonucleic acid sequencing (RNA-seq) was performed on the parents’ leaves at seven time-points in a day to determine differentially expressed genes (DEGs). The biological processes and pathways with significant enrichment of DEGs were obtained. The DEGs in the QTL intervals were analyzed, and four flowering time-related candidate genes were found. These results lay a foundation for the genetic regulation of rapeseed flowering time and create a rapeseed gene expression library for seven time-points in a day.

scholarly journals QTL mapping and candidate genes screening of earliness traits in <italic>Brassica napus</italic> L.

2020 ◽  
Vol 47 (4) ◽  
pp. 650-659
Author(s):  
Shu-Yu LI ◽  
Yang HUANG ◽  
Jie XIONG ◽  
Ge DING ◽  
Lun-Lin CHEN ◽  
...  
Keyword(s):  
Brassica Napus ◽  
Qtl Mapping ◽  
Candidate Genes

scholarly journals High-throughput phenotyping-based QTL mapping reveals the genetic architecture of the salt stress tolerance of Brassica napus

2021 ◽  
Author(s):  
Guofang Zhang ◽  
Jinzhi Zhou ◽  
Yan Peng ◽  
Zengdong Tan ◽  
Yuting Zhang ◽  
...  
Keyword(s):  
Salt Stress ◽  
Brassica Napus ◽  
Qtl Mapping ◽  
Stress Tolerance ◽  
Candidate Genes ◽  
Natural Population ◽  
High Throughput ◽  
Stress Conditions ◽  
Salt Stress Tolerance ◽  
High Throughput Phenotyping

Salt stress is a major limiting factor that severely affects the survival and growth of crops. It is important to understand the salt tolerance ability of Brassica napus and explore the underlying related genetic resources. We used a high-throughput phenotyping platform to quantify 2,111 image-based traits (i-traits) of a natural population under 3 different salt stress conditions and an intervarietal substitution line (ISL) population under 9 different stress conditions to monitor and evaluate the salt stress tolerance of B. napus over time. We finally identified 928 high-quality i-traits associated with the salt stress tolerance of B. napus. Moreover, we mapped the salt stress-related loci in the natural population via a genome-wide association study (GWAS) and performed a linkage analysis associated with the ISL population, respectively. The results revealed 234 candidate genes associated with salt stress response, and two novel candidate genes, BnCKX5 and BnERF3, were experimentally verified to regulate the salt stress tolerance of B. napus. This study demonstrates the feasibility of using high-throughput phenotyping-based QTL mapping to accurately and comprehensively quantify i-traits associated with B. napus. The mapped loci could be used for genomics-assisted breeding to genetically improve the salt stress tolerance of B. napus.

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

Identification of candidate genes involved in fatty acids degradation at the late maturity stage in Brassica napus based on transcriptomic analysis

2017 ◽  
Vol 83 (3) ◽  
pp. 385-396 ◽  
Author(s):  
Longhua Zhou ◽  
Haoyi Wang ◽  
Xin Chen ◽  
Yuling Li ◽  
Nazim Hussain ◽  
...  
Keyword(s):  
Fatty Acids ◽  
Brassica Napus ◽  
Candidate Genes ◽  
Transcriptomic Analysis ◽  
Maturity Stage ◽  
Late Maturity

scholarly journals High-resolution QTL mapping for grain appearance traits and co-localization of chalkiness-associated differentially expressed candidate genes in rice

Rice ◽  
2016 ◽  
Vol 9 (1) ◽  
Author(s):  
Likai Chen ◽  
Weiwei Gao ◽  
Siping Chen ◽  
Liping Wang ◽  
Jiyong Zou ◽  
...  
Keyword(s):  
High Resolution ◽  
Qtl Mapping ◽  
Candidate Genes ◽  
Differentially Expressed

Detection of a Major QTL and Development of KASP Markers for Seed Weight by Combining QTL-seq, QTL-mapping and RNA-seq in Peanut

2021 ◽  
Author(s):  
Zhihui Wang ◽  
Liying Yan ◽  
Yuning Chen ◽  
Xin Wang ◽  
Dongxin Huai ◽  
...  
Keyword(s):  
Qtl Mapping ◽  
Candidate Genes ◽  
Seed Development ◽  
Seed Weight ◽  
Molecular Mechanisms ◽  
Large Contribution ◽  
Phenotypic Variance ◽  
Rna Seq ◽  
Late Stages ◽  
Kasp Markers

Abstract Seed weight is a major target of peanut breeding as an important component of seed yield. However, relatively little is known about QTLs and candidate genes associated with seed weight in peanut. In this study, three major QTLs on chromosomes A05, B02 and B06 were determined by applying NGS-based QTL-seq approach for a RIL population. These three QTL regions have been successfully narrowed down through newly developed SNP and SSR markers based on traditional QTL mapping. Among these three QTL regions, qSWB06.3 exhibited stable expression with large contribution to phenotypic variance across all environments. Furthermore, RNA-seq were applied for early, middle and late stages of seed development, and differentially expression genes (DEGs) were identified in ubiquitin-proteasome pathway, serine/threonine protein pathway and signal transduction of hormones and transcription factors. Notably, DEGs at early stage were majorly related to regulating cell division, whereas DEGs at middle and late stages were mainly associated with cell expansion during seed development. Through integrating SNP variation, gene expression and functional annotation, candidate genes related to seed weight in qSWB06.3 were predicted and distinct expression pattern of those genes were exhibited using qRT-PCR. In addition, KASP-markers in qSWB06.3 were successfully validated in diverse peanut varieties and the alleles of parent Zhonghua16 in qSWB06.3 was associated with high seed weight. This suggested that qSWB06.3 was reliable and the markers in qSWB06.3 could be deployed in marker-assisted breeding to enhance seed weight. This study provided insights into the understanding of genetic and molecular mechanisms of seed weight in peanut.

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