Transcriptome Analysis of Cucumber Roots Reveals Key Cold-Resistance Genes Induced by AM Fungi

Late leaf spot (LLS) caused by fungus Nothopassalora personata in groundnut is responsible for up to 50% yield loss. To dissect the complex nature of LLS resistance, comparative transcriptome analysis was performed using resistant (GPBD 4), susceptible (TAG 24) and a resistant introgression line (ICGV 13208) and identified a total of 12,164 and 9954 DEGs (differentially expressed genes) respectively in A- and B-subgenomes of tetraploid groundnut. There were 135 and 136 unique pathways triggered in A- and B-subgenomes, respectively, upon N. personata infection. Highly upregulated putative disease resistance genes, an RPP-13 like (Aradu.P20JR) and a NBS-LRR (Aradu.Z87JB) were identified on chromosome A02 and A03, respectively, for LLS resistance. Mildew resistance Locus (MLOs)-like proteins, heavy metal transport proteins, and ubiquitin protein ligase showed trend of upregulation in susceptible genotypes, while tetratricopeptide repeats (TPR), pentatricopeptide repeat (PPR), chitinases, glutathione S-transferases, purple acid phosphatases showed upregulation in resistant genotypes. However, the highly expressed ethylene responsive factor (ERF) and ethylene responsive nuclear protein (ERF2), and early responsive dehydration gene (ERD) might be related to the possible causes of defoliation in susceptible genotypes. The identified disease resistance genes can be deployed in genomics-assisted breeding for development of LLS resistant cultivars to reduce the yield loss in groundnut.

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Comparative transcriptome analysis reveals an early gene expression profile that contributes to cold resistance in Hevea brasiliensis (the Para rubber tree)

Tree Physiology ◽

10.1093/treephys/tpy014 ◽

2018 ◽

Vol 38 (9) ◽

pp. 1409-1423 ◽

Cited By ~ 8

Author(s):

Han Cheng ◽

Xiang Chen ◽

Jialin Fang ◽

Zewei An ◽

Yanshi Hu ◽

...

Keyword(s):

Gene Expression ◽

Gene Expression Profile ◽

Expression Profile ◽

Transcriptome Analysis ◽

Hevea Brasiliensis ◽

Cold Resistance ◽

Rubber Tree ◽

Early Gene ◽

Comparative Transcriptome ◽

Comparative Transcriptome Analysis

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A pan-transcriptome analysis shows that disease resistance genes have undergone more selection pressure during barley domestication

BMC Genomics ◽

10.1186/s12864-018-5357-7 ◽

2019 ◽

Vol 20 (1) ◽

Cited By ~ 13

Author(s):

Yanling Ma ◽

Miao Liu ◽

Jiri Stiller ◽

Chunji Liu

Keyword(s):

Disease Resistance ◽

Resistance Genes ◽

Transcriptome Analysis ◽

Selection Pressure ◽

Disease Resistance Genes ◽

Barley Domestication

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QTL Mapping and Transcriptome Analysis to Identify Differentially Expressed Genes Induced by Septoria Tritici Blotch Disease of Wheat

Agronomy ◽

10.3390/agronomy9090510 ◽

2019 ◽

Vol 9 (9) ◽

pp. 510 ◽

Cited By ~ 3

Author(s):

Odilbekov ◽

He ◽

Armoniené ◽

Saripella ◽

Henriksson ◽

...

Keyword(s):

Qtl Mapping ◽

Differentially Expressed Genes ◽

Resistance Genes ◽

Transcriptome Analysis ◽

Resistance Mechanism ◽

Transcriptome Profiling ◽

Wheat Breeding ◽

Differentially Expressed ◽

Septoria Tritici Blotch ◽

Septoria Tritici

Resistance to Septoria tritici blotch (STB) is an economically important trait in many wheat-breeding programs across the world. Several quantitative trait loci (QTL) for STB resistance were identified in wheat but due to the dynamic pathogen population it is necessary to continuously identify new resistance genes/QTL and determine the underlying resistance mechanism. In this work, we integrated QTL mapping and transcriptome profiling to identify candidate genes underlying QTL associated with STB resistance in bread wheat at the seedling stage. The results revealed four QTL on chromosomes 1BS, 1BL, 3AS and 3DL for STB resistance. Among these, two QTL on 2BL and 3DL were mapped for chlorosis, necrosis and pycnidia while the other two on 1BS and 3AS were associated with necrosis and pycnidia. Among the four identified QTL, genes were identified in three QTL (1BS, 2BL and 3DL). In total, 238 differentially expressed genes (DEGs) were localized in 1BS, 16 DEGs in 2BL and 80 DEGs in 3DL QTL region respectively. F-box protein, NBS-LRR disease resistance genes and receptor-like protein kinase were the most over-represented. The results emphasize the importance of integrating QTL and transcriptome analysis to accelerate the identification of key genes underlying the traits of interest.

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