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. 2023 Mar;13(3):82.
doi: 10.1007/s13205-023-03481-7. Epub 2023 Feb 9.

QTL mapping and identification of candidate genes linked to red rot resistance in sugarcane

Affiliations

QTL mapping and identification of candidate genes linked to red rot resistance in sugarcane

Nandita Banerjee et al. 3 Biotech. 2023 Mar.

Abstract

Sugarcane (Saccharum species hybrid) is one of the most important commercial crops cultivated worldwide for products like white sugar, bagasse, ethanol, etc. Red rot is a major sugarcane disease caused by a hemi-biotrophic fungus, Colletotrichum falcatum Went., which can potentially cause a reduction in yield up to 100%. Breeding for red rot-resistant sugarcane varieties has become cumbersome due to its complex genome and frequent generation of new pathotypes of red rot fungus. In the present study, a genetic linkage map was developed using a selfed population of a popular sugarcane variety CoS 96268. A QTL linked to red rot resistance (qREDROT) was identified, which explained 26% of the total phenotypic variation for the trait. A genotype-phenotype network analysis performed to account for epistatic interactions, identified the key markers involved in red rot resistance. The differential expression of the genes located in the genomic region between the two flanking markers of the qREDROT as well as in the vicinity of the markers identified through the genotype-phenotype network analysis in a set of contrasting genotypes for red rot infection further confirmed the mapping results. Further, the expression analysis revealed that the plant defense-related gene coding 26S protease regulatory subunit is strongly associated with the red rot resistance. The findings can help in the screening of disease resistant genotypes for developing red rot-resistant varieties of sugarcane.

Supplementary information: The online version contains supplementary material available at 10.1007/s13205-023-03481-7.

Keywords: Linkage mapping; Marker-aided selection; QTL; Red rot; Sugarcane.

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Conflict of interest statement

Conflict of interestThe authors declare that they have no conflict of interest in the publication.

Figures

Fig. 1
Fig. 1
Frequency distribution of red rot reaction in the 134 individuals of the mapping population for C. falcatum pathotype Cf01. The y-axis represents the actual number of individuals with the respective red rot reaction score and x-axis represents the 0–9 score (Sreenivasan and Bhatt 1961)
Fig. 2
Fig. 2
Genetic map of sugarcane genotype CoS 69268, which is a promising clone obtained by crossing two sugarcane varieties Co 1158 × Co 62198. The mapping population was obtained by a single generation selfing of CoS 69268. The linkage map comprises 63 linkage groups; LG 4 is highly saturated with 180 alleles of studied SSRs
Fig. 3
Fig. 3
QTL analysis on LG 4; a interval mapping (LOD 4.1, trait threshold 19.0), and b composite interval mapping (LOD 4.5, trait threshold 20.54)
Fig. 4
Fig. 4
Details of QTL analysis on LG 4 and one QTL, qREDROT located at 1545 cM, and flanked by markers IISR139a_260 (1539.98 cM) and KS32_80 (1551.59 cM)
Fig. 5
Fig. 5
Undirected graphical model-based identification of the genotype–phenotype interaction network using data of all single-dose markers and average red rot resistance reaction score simultaneously. The markers highlighted in yellow are the ones which are directly interacting with red rot resistance
Fig. 6
Fig. 6
Amplification profile of the primer 256_C2_G39-2. The arrow indicates ~ 500 bp product specific to red rot resistance amplified only in red rot resistance genotypes. Lanes: M: DNA ladder; 1: Co 62198 (susceptible parent); 2: BO 91 (resistant variety); 3: SES 594 (resistant variety); 4: CoLk 94184 (resistant variety); 5: CoS 767 (susceptible variety); 6: CoJ 64 (susceptible variety); 7: Co 1148 (susceptible variety); 8: Co 1158 (resistant parent)
Fig. 7
Fig. 7
Gene expression pattern of MAP kinase 4 in panel of R and S plants (quantification was done with ∆∆Ct normalization method. ∆∆Ct = ∆Ct (Treated) − ∆Ct (Control). Ct is on a log scale, base 2)
Fig. 8
Fig. 8
Gene expression pattern of 26S protease regulatory complex subunit gene in panel of R and S plants (Quantification was done with ∆∆Ct normalization method. ∆∆Ct = ∆Ct (Treated) − ∆Ct (Control). Ct is on a log scale, base 2)
Fig. 9
Fig. 9
Gene expression pattern of RING-H2 finger protein gene in panel of R and S plants (Quantification was done with ∆∆Ct normalization method. ∆∆Ct = ∆Ct(Treated)—∆Ct(Control). Ct is on a log scale, base 2)
Fig. 10
Fig. 10
Gene expression pattern of Cytochrome P450 gene in panel of R and S plants (Quantification was done with ∆∆Ct normalization method. ∆∆Ct = ∆Ct (Treated) − ∆Ct (Control). Ct is on a log scale, base 2)
Fig. 11
Fig. 11
Expression pattern candidate gene lectin domain-containing protein in panel of R and S plants (Quantification was done with ∆∆Ct normalization method. ∆∆Ct = ∆Ct (Treated)—∆Ct (Control). Ct is on a log scale, base 2)
Fig. 12
Fig. 12
Expression pattern candidate gene disease resistance protein RGA1 in panel of R and S plants (Quantification was done with ∆∆Ct normalization method. ∆∆Ct = ∆Ct (Treated)—∆Ct (Control). Ct is on a log scale, base 2)

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