scholarly journals The infection processes of Sclerotinia sclerotiorum in cotyledon tissue of a resistant and a susceptible genotype of Brassica napus

2010 ◽  
Vol 106 (6) ◽  
pp. 897-908 ◽  
Author(s):  
Harsh Garg ◽  
Hua Li ◽  
Krishnapillai Sivasithamparam ◽  
John Kuo ◽  
Martin J. Barbetti
2012 ◽  
Vol 40 (1) ◽  
pp. 143 ◽  
Author(s):  
Robab DAVAR ◽  
Reza DARVISHZADEH ◽  
Ahmad MAJD ◽  
Ardashir KHARABIAN MASOULEH ◽  
Yobert GHOSTA

Sunflower, Helianthus annuus L., is a major oil seed crop widely cultivated throughout the globe. White mold, caused by necrotrophic pathogen Sclerotinia sclerotiorum (Lib.) de Bary, is a common and widespread pathogen of sunflower. The infection process of S. sclerotiorum was studied in the stem base of infected host tissues by light microscopy and Hemi-thin sectioning techniques. Host-pathogen interactions were examined at the plant surface and cellular level of a susceptible genotype (C146), 12, 24 and 48 h of post inoculation. The results showed that the appressoria were formed and the hyphal strands branched upon contact of pathogen with the host surface. Moreover a direct penetration of fungal hyphae was observed through the cuticle within 12h of inoculation. Microscopic observation of inoculated tissues after 24 hours revealed that fungal hyphae have developed both inter- and intra-cellular layer. Moreover, the fungal hyphae growth was incremental among and inside the host cells. The host cells were completely colonized by fungal mycelium 48 hour after inoculation, leading to a tissue collapse. The hyphae invaded the dead host tissues and emerged from the host tissue after extensive colonization. The present study has detailed the infection processes and pathogen development both at plant surface and inside the host tissues. The results of this study will be useful for engineering of disease-resistant genotypes and development of markers for screening pathogen resistance individuals.


2004 ◽  
Vol 41 (8) ◽  
pp. 754-765 ◽  
Author(s):  
Rugang Li ◽  
Roger Rimmer ◽  
Lone Buchwaldt ◽  
Andrew G Sharpe ◽  
Ginette Séguin-Swartz ◽  
...  

Author(s):  
Fereshteh Shahoveisi ◽  
Atena Oladzad ◽  
Luis E. del Rio Mendoza ◽  
Seyedali Hosseinirad ◽  
Susan Ruud ◽  
...  

The polyploid nature of canola (Brassica napus) represents a challenge for the accurate identification of single nucleotide polymorphisms (SNPs) and the detection of quantitative trait loci (QTL). In this study, combinations of eight phenotyping scoring systems and six SNP calling and filtering parameters were evaluated for their efficiency in detection of QTL associated with response to Sclerotinia stem rot, caused by Sclerotinia sclerotiorum, in two doubled haploid (DH) canola mapping populations. Most QTL were detected in lesion length, relative areas under the disease progress curve (rAUDPC) for lesion length, and binomial-plant mortality data sets. Binomial data derived from lesion size were less efficient in QTL detection. Inclusion of additional phenotypic sets to the analysis increased the numbers of significant QTL by 2.3-fold; however, the continuous data sets were more efficient. Between two filtering parameters used to analyze genotyping by sequencing (GBS) data, imputation of missing data increased QTL detection in one population with a high level of missing data but not in the other. Inclusion of segregation-distorted SNPs increased QTL detection but did not impact their R2 values significantly. Twelve of the 16 detected QTL were on chromosomes A02 and C01, and the rest were on A07, A09, and C03. Marker A02-7594120, associated with a QTL on chromosome A02 was detected in both populations. Results of this study suggest the impact of genotypic variant calling and filtering parameters may be population dependent while deriving additional phenotyping scoring systems such as rAUDPC datasets and mortality binary may improve QTL detection efficiency.


2018 ◽  
Vol 74 (11) ◽  
pp. 2594-2600 ◽  
Author(s):  
Kyran D Brooks ◽  
Sarita J Bennett ◽  
Leon M Hodgson ◽  
Michael B Ashworth

2020 ◽  
Vol 18 (5) ◽  
pp. 1255-1270 ◽  
Author(s):  
Li‐Na Ding ◽  
Ming Li ◽  
Xiao‐Juan Guo ◽  
Min‐Qiang Tang ◽  
Jun Cao ◽  
...  

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