Marker-assisted mapping and backcross breeding for late wilt disease resistance in NAI-137, the seed parent of public bred single cross maize (Zea mays L.) hybrid Hema

doi:10.21203/rs.3.rs-4898174/v1

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Marker-assisted mapping and backcross breeding for late wilt disease resistance in NAI-137, the seed parent of public bred single cross maize (Zea mays L.) hybrid Hema

https://doi.org/10.21203/rs.3.rs-4898174/v1

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Development and deployment of late wilt disease (LWD) resistant cultivar(s) is a cost-effective and eco-friendly strategy to reduce losses due to LWD. DNA markers could be potential surrogates for selection of complexly inherited resistance to LWD. Two linkage maps were constructed using the genotypic data of 64 and 40 polymorphic SSR markers on BC₁F₁ populations derived from NAI-137×97B and NAI-137×MAI-345, respectively. Three main effect-QTL were detected on chromosomes 1, 4 and 10 in NAI-137×97B, while one QTL on chromosome 9 in NAI-137×MAI-345. Therefore, only the BC₁F₁ population of NAI-137×97B was back-crossed to NAI-137. Linkage map was constructed in BC₂F₁ population using the genotypic data of 64 SSR, 3456 unbinned-SNP and 104 binned-SNP + 64 SSR markers in combination. A total of 5, 2 and 11 main effect-QTL were detected on SSR, unbinned-SNP and binned-SNP + SSR based QTL maps, respectively. In NAI-137×97B derived BC₁F₁ and BC₂F₁, 2 QTL on chromosomes 4 and 10 flanked by common SSR markers i.e., mmc0371 and umc2350, respectively were detected. Sixteen NAI-137×97B derived BC₁F₁ plants carried QTL controlling LWD resistance with > 80% recovery of recipient parent genome and LWD score ≤ 4. Ten NAI-137×97B derived BC₂F₁ plants carried QTL controlling LWD resistance with > 90% recovery of recipient parent genome and LWD score ≤ 3. They were selfed and evaluated for response to LWD. Three BC₂F₂ families (BC₂F₂-84, BC₂F₂-88 and BC₂F₂-179) with LWD score 2, lower than the donor parent (NAI-137, LWD score 8) were identified. LWD resistant version of NAI-137 developed from the present study shall be used to cross with MAI-105 (the male parent of maize hybrid Hema) to generate improvised “Hema” after evaluating the grain yield potential in comparison to original “Hema” hybrid.

Late wilt disease

QTL mapping

Marker-assisted introgression

Resistance breeding

Harpophora maydis

The low productivity of the third most important staple cereal food crop of the world, maize is attributed to various biotic and abiotic constraints. Of the biotic factors, post flowering stalk rot (PFSR) is the most complex disease. It affects the maize plants when they are about to initiate tassel and just prior to physiological maturity, causing wilting and premature killing, hence the name PFSR. It is caused by three pathogens; Fusarium moniliforme causes stalk rot, Macrophomina phaseolina causes charcoal rot and Harpophora maydis causes late wilt disease (LWD). Infection caused exclusively by Harpophora maydis, a seed and soil-borne pathogen results in premature wilting in the post-flowering stage. The LWD infected plants normally wilt from the upper leaves which eventually become dry and cause discoloration in stalk. At advanced stages, stalk tissue disintegrates resulting in fibrousness (Samra et al. 1963). Diseased plants produce ears with under developed shrunken kernels in severe cases. The PFSR complex has been reported to cause severe yield loss across the globe (Zeller et al. 2000). Economic losses of 40–100% in Egypt (Labib et al. 1975; Galal et al. 1979) and upto 51% in India (Johal et al. 2004) due to LWD is reported. However, reports based on empirical studies suggest 3.50–38.40% loss in grain yield attributable to soil inoculation by Harpophora maydis (El-Naggarr et al. 2015). While, Sunitha et al. (2020) reported that for every one unit increase in disease score, the per plant yield is reduced by 7.31 g, which indicates that in one-hectare area of maize crop, LWD has the potential to cause ~ 19.00% yield loss. Most of the currently grown commercial single cross hybrids (SCH) are susceptible to LWD (Sunitha et al. 2020). It can be managed through chemical control measures which are non-durable and non eco-friendly. Hence, genetic intervention is the best choice to mitigate losses caused by PFSR complex in general and LWD in particular (Samra et al. 1963; El-Shafey et al. 1988).

Development and deployment of LWD resistant (LWDR) version of existing popular high yielding but LWD susceptible hybrids is the short-term strategy to minimize the losses due to LWD. However, this strategy also helps meet immediate requirement of the farmers to stabilize maize production in areas prone to LWD. Conventional phenotype-based selection for LWDR is expected to be less effective as resistance to LWD is complexly inherited with significant genotype × environment interaction (Shekhar et al. (2010); Kumar et al. (2017); Mir et al. (2018)). DNA markers have proved powerful surrogates for such traits. However, identification of DNA markers linked to genomic regions controlling LWDR is a pre-requisite. With this background, a strategy to develop LWDR version of the existing popular high yielding single cross maize hybrid bred by the University of Agricultural Sciences, Bangalore, “Hema” (NAI-137 × MAI-105) through simultaneous discovery and introgression of quantitative trait loci (QTL) controlling LWDR to its seed parent, NAI-137 was conceived. The strategy of simultaneous discovery and introgression of QTL controlling desired traits is referred as marker assisted back cross(MABC) breeding. Based on the success of empirical results on introgression of QTL controlling resistance to biotic stresses in several crops (Ahmadikhah et al. 2015; Miah et al. 2015), we hypothesize that the resistance level of the seed parent (NAI-137) of SCH “Hema” will be improved to the level of LWD resistant donor parents. To test this hypothesis, the present investigation was planned with the objective to identify QTL controlling LWD resistance and to develop LWD resistant version of NAI-137.

Basic genetic material and development of mapping population

Two LWD resistant inbreds identified from an earlier study (Aruna, 2017) were used as donor parents and crossed to the recurrent parent NAI-137 to generate backcross-derived mapping populations in Kharif-2018 (Table 1). The resulting F₁s were backcrossed to NAI-137 in summer 2019 to generate the BC₁F₁ population (NAI-137 × 97B; NAI-137×MAI-345). The BC₁F₁ plants of the cross NAI-137 × 97B were backcrossed to NAI-137 to generate the BC₂F₁ population. Those BC₂F₁ individuals harboring the DNA markers flanking the QTL governing LWD resistance with LWD score ≤ 3 were selfed to generate BC₂F₂ families.

Table 1

Characteristics of the basic genetic material used in the study
Inbred	Features	LWD score (on 1–9 scale)
97B	High yield and resistance to LWD	3.00
MAI-345	High yield and resistance to LWD	2.75
NAI-137	High yield and resistance to LWD	8.00

Phenotyping mapping population for response to LWD

The mapping populations (BC₁F₁ and BC₂F₁) and the BC₂F₂ families were evaluated for response to LWD by challenging the plants with H. maydis inoculum as described by Rakesh et al. (2016) in Augmented Design with four checks (Hema, NAI-137, 97B and MAI-345) at the experimental plots of ‘K’ Block, Department of Genetics and Plant Breeding, University of Agricultural Sciences, Bangalore, India.

Genotyping mapping population

The BC₁F₁ mapping populations derived from NAI-137×97B and NAI-137×MAI-345 were genotyped using the genome wide polymorphic simple sequence repeat (SSR) markers. Since, the cross NAI-137 × 97B exhibited comparatively more number of QTL and higher number of backcross individuals with LWD resistant scores. Hence, BC₁F₁ mapping population derived from the cross NAI-137 × 97B was forwarded for further experiment, and was genotyped not just by SSR markers, but also 12,73,823 single nucleotide polymorphic (SNP) markers identified from genotyping-by-sequencing (GBS) to dissect additional QTL and confirmation of QTL identified in BC₁F₁ mapping population. After excluding the SNP markers with > 5% missing data, 3425 out of 12,73,823 polymorphic SNPs were identified and referred as Unbinned-SNP markers. DNA from 20 days old parents, BC₁F₁ and BC₂F₁ plants was extracted following modified Cetyltrimethylammonium bromide (CTAB) method (Hoisington et al. 1994).

Binning of redundant SNP markers

The 3425 polymorphic SNPs were subjected for binning to identify and remove redundant markers in the dataset. Markers with > 2% missing rate and a lower P-value (< 0.01) were excluded to identify 104 SNPs out of 3425 polymorphic SNPs. The genotypic data of the binned SNP markers was designated as “Binned-SNP” throughout. The genotypic data of 104 Binned-SNP markers was integrated with genotypic data of 64 SSR markers and used in the discovery of QTL conferring resistance to LWD.

Statistical analysis

Phenotypic data analysis

The analysis of variance (ANOVA) for augmented design (Federer, 1961) was carried out to dissect the total variability into sources attributable to BC₁F₁/ BC₂F₁ plants, checks and BC₁F₁/BC₂F₁ plants vs. checks using R software ver 4.0.0.

Genotypic data analysis

Linkage map was constructed using ‘QTL IciM’ software version 4.1 based on the genotypic data of 64 and 40 SSR markers on 133 and 131 BC₁F₁ individuals derived from the cross NAI-137×97B and NAI-137×MAI-345, respectively. Threshold LOD score of 3.0 was used to test the significance of inter-marker recombination frequencies which were converted into map distances using the mapping function (Kosambi, 1944). The constructed linkage map was used to detect genomic regions controlling LWD resistance.

Detection of QTL controlling resistance to LWD using SSR and SNP markers

The phenotypic and genotypic data obtained using SSR and SNP marker systems were used to detect QTL using (1) only SSR data (2) only unbinned-SNP markers and (3) binned-SNP + SSR marker data (Fig. 1).

Introgression of LWD resistance QTL to NAI-137

Based on the QTL mapping results, the 3 pairs of markers flanking QTL controlling LWD resistance were used for foreground selection (Table 2). Markers that were unlinked to QTL governing LWD resistance and those evenly distributed across the recurrent parent genome were used for background selection.

Table 2

Markers flanking QTL controlling LWD resistance that were used for foreground selection
Flanking markers		Chromosomal location
umc1955	umc1147	1
mmc0371	umc1808	4
umc1930	umc2350	10

Determining the extent of recurrent parent genome recovery

The extent of recurrent parent genome (RPG) recovery in BC₁F₁ and BC₂F₁ generations was calculated using the formula given below.

RPG (%) =			2(x)+(y)	× 100
RPG (%) =			2N	× 100
x	=	Number of marker loci homozygous for recurrent parent allele
Y	=	Number of marker loci still remaining heterozygous
N	=	Total number of polymorphic markers screened

Graphical genotyping

It is a visual method to represent genetic marker profile of genotypes (Young and Tanksley, 1989). Graphical genotypes display the positions and the proportions of donor and recurrent genome during subsequent backcross generations. Graphical genotyping 2.0 (GGT) software was used to visualize and analyze molecular marker data scores. The marker profiles generated by the polymorphic SSR markers for background selection of recurrent parent genome in BC₁F₁ population was scored in a co-dominant manner. The individual bands were scored as ‘A’ for the recurrent parent type and ‘H’ for the presence of both the parent allele i.e., heterozygous. In the NAI-137 × 97B derived BC₁F₁ population, the plants showing highest recurrent parent genome recovery (> 75%) and harboring the SSR markers linked to QTL governing LWD resistance were crossed to the recurrent parent (NAI-137) to generate BC₂F₁ population. Further, the BC₂F₁ population showing highest recurrent parent genome recovery (> 85%) and harboring the SSR markers linked to QTL governing LWD resistance were selfed to generate the BC₂F₂ families.

Comparison of resistant BC₂F₂ families with NAI-137 for LWD resistance

The significance of differences in LWD scores among selected BC₂F₂ plants, LWD resistance donor parents and recipient parent plants was examined using “F-test”. Significance of “F-test” coupled with low LWD scores of BC₂F₂ plants compared to those of recipient parent was considered as an evidence for effectiveness of MABC for enhancing LWD resistance of NAI-137.

Parental polymorphism

Of the 705 SSR markers screened, 650 amplified, of which 66 (9.36%) and 54 (7.65%) produced clear, scorable and consistent polymorphic amplicons between the parents of the crosses NAI-137×97B and NAI-137×MAI-345, respectively.

Development of linkage map

Linkage map was constructed using the genotypic data of 64 and 40 polymorphic markers in NAI-137×97B and NAI-137×MAI-345, respectively after excluding the distorted markers (2 in NAI-137×97B and 14 in NAI-137×MAI-345). The linkage map length varied from 83.80 cM (LG3) to 1275.79 cM (LG8) in NAI-137×97B and from 0.00 cM (LG1 and LG8) to 491.98 cM (LG9) in NAI-137×MAI-345. The total length of the linkage map spanned 4336.66 cM and 2050.47cM of the genome with an average inter-marker distances of 67.76 cM and 42.00 cM in NAI-137×97B and NAI-137×MAI-345, respectively.

ANOVA

Mean squares attributable to BC₁F_1s and BC₁F₁ Vs Checks derived from NAI-137× 97B and NAI-137×MAI-345 were significant for response to LWD (Table 3). The BC1F1 plants of NAI-137×97B and NAI-137×MAI-345 based mapping populations exhibited LWD response with scores ranging from 2–8. The response to LWD in NAI-137×97B derived BC₁F₁ population is depicted in Fig. 5a.

Table 3

**Analysis of variance of the two backcross populations derived from two bi-parental crosses for response to late wilt disease (LWD) in maize**
Source of variation	Degrees of freedom		Mean sum of squares		‘F’ statistic		Probability
Source of variation	NAI-137 × 97B	NAI-137× MAI-345	NAI-137 × 97B	NAI-137 × MAI-345	NAI-137 × 97B	NAI-137 × MAI-345	NAI-137 × 97B	NAI-137 × MAI-345
BC₁F₁	132	130	1.21	1.82	3.47	3.45	0.00	0.00
BC₁F₁ vs. Checks	1	1	35.27	8.83	101.02	16.69	0.00	0.00
NAI-137 × 97B derived BC₂F₁ mapping population
BC₂F₁	117		460.25		71.80		0.00
BC₂F₁ vs. Checks	1		3.08		5.55		0.032

QTL Detection in BC₁F₁ mapping population

Three main effect-QTL with phenotypic variance 8.44, 6.50 and 4.04% were detected on chromosome 1, 4 and 10, respectively in NAI-137×97B and one on chromosome 9 with phenotypic variance of 8.45% in NAI-137×MAI-345 (Table 4). The size effects of the four QTL ranged from 4.04 to 8.44.

Table 4

Main effect-QTL detected for late wilt disease (LWD) resistance in BC₁F₁ and BC₂F₁ mapping populations
Generation	Cross	Marker system	No. of markers used	Polymorphic markers identified	Markers distorted	QTL identified					Flanking marker
Generation	Cross	Marker system	No. of markers used	Polymorphic markers identified	Markers distorted	Chromosome	Position (cM)	LOD	Phenotypic variance (%)	Additive effects	Right marker	Left marker
BC₁F₁	NAI-137 × 97B	SSR	705	66	2	1	110.00	2.54	8.44	-0.95	umc1955	umc1147
						4	168.00	2.41	6.50	-0.82	mmc0371	umc1808
						10	113.00	2.02	4.04	-0.70	umc1930	umc2350
	NAI-137 × MAI-345			54	14	9	22.00	2.31	8.45	-0.91	phi065	bnlg1129
BC₂F₁	NAI-137× 97B	SSR	705	66	2	2	159.00	2.02	2.57	-1.02	phi101049	bnlg1175
						4	91.00	2.22	4.52	-1.34	umc2150	mmc0371
						6	201.00	2.50	5.45	-1.49	umc1063	umc1859
						10	59.00	2.39	5.08	-1.43	umc2018	umc2163
						10	180.00	4.02	7.03	-1.68	umc2352	umc2350
		Unbinned-SNP	12,73,823	3456	0	5	946.00	2.01	6.40	-0.72	LWD_1771	LWD_2001
		Unbinned-SNP	12,73,823	3456	0	10	549.00	3.08	11.18	-1.58	LWD_3373	LWD_3428
		SSR+ Binned-SNP	12,73,823 + 66	104 + 64	3366	1	582.00	2.10	6.95	-3.57	LWD_312	LWD_216
						1	911.00	2.78	2.24	-3.85	umc2080	umc1955
						2	207.00	2.14	2.18	-3.81	bnlg1175	LWD_550
						2	661.00	2.94	2.31	-3.91	phi101049	bnlg1893
						4	396.00	3.00	2.27	-3.96	umc2150	mmc0371
						6	321.00	3.28	2.29	-3.98	phi077	LWD_2090
						6	532.00	2.10	2.15	-3.77	umc1859	phi299852
						6	617.00	3.90	12.28	-0.66	umc1063	umc1859
						8	49.00	2.73	8.58	-0.80	LWD_2777	umc1974
						9	371.00	2.45	6.18	-3.38	LWD_3094	LWD_3029
						10	637.00	2.66	8.12	-23.55	LWD_3421	umc2350

Confirmation and identification of additional QTL governing LWD resistance in NAI-137 × 97B derived BC₂F₁ population

The SSR marker-based linkage map length varied from 51.54 cM (LG 3) to 313.29 cM (LG 10); that based on unbinned-SNP markers ranged from 196.76 cM (LG 7) to 767.74 cM (LG 1) and the one based on a combination of binned-SNP + SSR markers varied from 435.44 cM (LG 4) to 1052.57 cM (LG 1). The total length of the linkage maps based on SSR, unbinned-SNP and binned-SNP + SSR markers spanned 2213.84 cM, 5799.18 cM and 6949.76 cM, respectively. Mean squares attributable to individuals of BC₂F_1s and BC₂F₁ Vs Checks were significant for response to LWD (Table 3). The response to LWD in BC₂F₁ population is depicted in Fig. 5b. A total of 5, 2 and 11 main effect-QTL were detected in SSR, Unbinned-SNP and Binned-SNP + SSR based QTL maps, respectively. In the SSR based QTL map, one QTL on each of the chromosome 2, 4 and 6 and two QTL on chromosome 10 were detected (Fig. 2a). In the Unbinned-SNP based QTL map, one QTL each on the chromosome 5 and 10 was detected (Fig. 2b). In the Binned-SNP + SSR based QTL map, three QTL on chromosome 6, two QTL on chromosome 1 and 2, whereas, one QTL each on chromosome 4, 8, 9 and 10 were dispersed. These QTL were flanked by both SNP and SSR markers with distance ranging from 3.47 to 101.31 cM and explained phenotypic variance ranging from 2.15 to 12.28% (Table 4).

Introgression of LWD resistant QTL in NAI-137, the seed parent of hybrid Hema

Foreground and background selection in BC₁F₁

Sixteen out of 133 plants in NAI-137 × 97B carried LWD resistance QTL, besides capturing over 80% of the recipient genetic background (Table 5). Of these 16 plants, the plant No. 31 showed highest recipient parent genome recovery of 84.21% with LWD score of 3 (Resistant).

Table 5

Extent of recovery of recipient parents (NAI-137) genome (%) using SSR markers and LWD scores of individuals in the BC₁F₁ population derived from the cross NAI-137 × 97B
Plant No.	% Recovery	LWD score	Plant No.	% Recovery	LWD score
62	75.66	2	110	80.47	4
58	78.36	2	114	77.35	4
3	79.21	2	96	79.14	4
130	80.12	2	132	72.14	4
78	81.27	2	70	77.22	4
37	81.02	3	75	80.88	4
43	80.17	3	109	75.48	4
53	82.54	3	122	79.48	4
31	84.21	3	129	77.28	4
127	75.67	3	98	76.23	4
73	82.69	3	7	76.60	4
97	81.00	3	12	78.23	4
116	82.56	3	34	72.91	4
123	80.20	3	56	79.52	4
32	75.00	3	60	74.54	4
14	83.40	4	11	76.00	4
10	75.21	4	19	74.14	4
29	76.89	4	1	76.15	4
45	75.23	4	69	79.41	4
57	80.47	4	119	73.20	4
24	76.58	4	101	73.87	4
22	80.41	4	92	75.23	4
66	82.46	4	111	77.28	4

Foreground and background selection in BC₂F₁

Ten out of 16 BC₂F₁ plants had RPG content > 90.00% and LWD score of ≤ 3 (Table 6). The lines BC₂F₁-174, BC₂F₁-137 and BC₂F₁-179 had > 90% RPG (Fig. 3).

Table 6

Extent of recovery of recipient parents (NAI-137) genome (%) and LWD scores of individuals in the BC₂F₁ population derived from the cross NAI-137 × 97B estimated using SSR markers, Unbinned-SNP markers, and combination of Binned-SNP and SSR markers
Plant No.	% Recovery			LWD score
Plant No.	SSR	Unbinned-SNP	Binned-SNP + SSR	LWD score
174	90.27	90.00	92.77	2
137	92.01	90.00	91.00	2
179	91.68	90.69	91.47	2
83	91.23	90.00	91.75	3
109	90.12	90.58	91.80	3
52	90.28	90.80	91.55	3
133	90.78	91.05	93.00	3
145	91.21	90.10	91.00	3
122	91.89	91.00	92.53	3
125	90.87	90.00	93.48	3

Effectiveness of two cycles of MABC for enhancing LWD resistance of NAI-137:

The selected BC₂F₂ families differed significantly from recipient susceptible parent (NAI-137) for mean LWD score as evident from the probability value (Fig. 4a). Comparison of the LWD means of the two backcross populations indicated the presence of significant differences between them with that of NAI-137. The disease score significantly reduced from BC₁F₁ to BC₂F₁ population as indicated by a lower “P” statistic value (Fig. 4b). The gradual improvement in response to LWD was evident over the backcross generations (Fig. 5a and Fig. 5b). We could identify 3 progenies homozygous for LWD resistance controlling QTL (Fig. 5c). The estimates of the trait means of flowering related traits of the BC₂F₂ families and the recipient parent (NAI-137) injected with H. maydis spores were comparable as indicated by a lower probability value (Table 7).

Table 7

Estimates of traits’ means of resistant BC₂F₂ individuals and NAI-137 and test for significance of differences between them
Traits	Resistant BC₂F₂ individuals (10)	NAI-137 (30)	Difference between resistant and NAI-137	‘t’ statistic	Probability
Days to tasseling	53.00	52.00	1.00	2.15	0.00
Days to silking	56.00	54.00	2.00	1.04	0.00
ASI (days)	3.00	2.00	1.00	1.97	0.03
Mean LWD score	2.70	7.84	5.14	2.01	0.00

Phenotype based selection for complex traits such as resistance to LWD is less effective, in such instances DNA markers have proved effective surrogates for selection. However, identification and validation of QTL controlling LWD resistance and markers closely linked to them is a pre-requisite. MABC facilitates simultaneous identification and introgression of the desired QTL from donor to desired genetic background. In the present investigation, an effort was made to identify and introgress QTL controlling resistance to LWD to NAI-137, the seed parent of maize hybrid “Hema”, by crossing it with the LWD resistant inbreds (97B and MAI-345) to generate backcross mapping population. The two BC₁F₁ populations were phenotyped for response to LWD and genotyped using polymorphic SSR markers. The linkage map was constructed (after excluding the distorted markers) using 64 and 40 SSR markers that spanned 4336.66 cM and 2050.47 cM of the genomes of NAI-137×97B and NAI-137×MAI-345 derived BC₁F₁ populations, respectively. A higher number of markers were distorted in latter, which may be due to selection during gametogenesis, fertilization or germination (Lyttle, 1991) and this kind of distortion has been previously reported in maize (Zhou et al. 2011; Fu et al. 2017) and also in other crops. Large inter-marker distances were observed, perhaps due to fewer mapped markers possibly driven by low frequency and uneven distribution of the recombination events. The ANOVA indicated substantial differences among the crosses for their response to LWD. Although, the NAI-137 × MAI-345 derived backcross population expressed lower mean (for response to late wilt disease), wider absolute range and standardized range, and higher phenotypic coefficient of variation and frequency of transgressive segregants indicating better breeding potential than NAI-137 × 97B (Gazala et al. 2021).

The region on chromosome 1, 4 and 10 in NAI-137 × 97B and chromosome 9 in NAI-137 × MAI-345 harbored QTL governing resistance to LWD. Failure to detect major effect QTL in desirable direction in both the populations could be attributed to fewer polymorphic SSR markers identified. Sunitha et al. (2021) and Rakesh et al. (2022), however, detected a few major effect QTL controlling LWD resistance, although in different mapping populations. Nevertheless, one of the SSR markers, mmc0371 flanking the QTL controlling LWD resistance on chromosome 4 in NAI-137×97B population was also found linked to QTL controlling Pythium stalk rot in maize (Yang et al. 2004). The DNA markers significantly linked to QTL controlling traits of interest are very often genotype specific. Hence, for their effective use in marker-assisted selection, they need to be confirmed in diverse genetic backgrounds. Relatively a greater number of QTL were detected in NAI-137×97B derived population (03), than those in NAI-137×MAI-345 (01). Hence, individuals of the former population were backcrossed to generate BC₂F₁ population. Three linkage maps were constructed in NAI-137×97B derived BC₂F₁ population; one using the genotypic data of 64 SSR markers only, second using 3456 unbinned-SNP markers only and third using a combination of 104 binned-SNP + 64 SSR markers. Not surprisingly, the inter-marker distances in unbinned SNP marker based linkage map was the least. As expected, more markers were evenly distributed on the chromosomes when the combination of binned-SNP + SSR was used for linkage map construction. The ANOVA indicated substantial differences in the BC₂F₁ population for response to LWD. In the binned-SNP + SSR marker based QTL map, a large number of QTL were identified, while least in unbinned-SNP markers based QTL map. Also, the size effects of detected QTL were higher and inter-marker distances between the markers flanking QTL controlling LWD resistance were lower in binned-SNP + SSR based QTL map, than those detected in the other two QTL maps. The QTL detected on chromosome 4 was flanked by the same pair of markers (umc2150 and mmc0371) in both SSR based and binned-SNP + SSR based maps, although in different positions. Similarly, the QTL detected on chromosome 6 was flanked by same pair of markers (umc1063 and umc1859) in SSR and binned-SNP + SSR based maps with varying LOD scores, per cent phenotypic variance and additive effects. In all the three maps, a common QTL located on chromosome 10 was detected, although the position, LOD score, phenotypic variance and additive effects varied. One of the flanking SSR markers, umc2350 was common in SSR and binned-SNP + SSR based QTL maps. The differences in the positions of the detected QTL and their size effects in the three maps of the same mapping population could be attributable to the varying levels of marker coverage and their distribution. Similar results were reported by Wei et al. (2009) while investigating the influence of dent corn genetic backgrounds on QTL detection for plant-height traits and their relationships in high-oil maize. They detected 28 QTL for four traits in the two F_2:3 families. Of these, only one QTL was common between the two populations. A total of two common QTL were detected in the two backcross populations derived from NAI-137×97B. However, as is true with the first common QTL, the size effects of the second QTL slightly varied with the mapping population as well as the kind of markers used and their combination.

The development of resistant cultivars is generally the preferred strategy to manage any disease, as host plant resistance is economical and eco-friendly (Varshney et al. 2009). We used MABC to detect, confirm and introgress QTL controlling resistance to LWD from donor to recipient parent. The BC₁F₁ and BC₂F₁ population of NAI-137×97B was used for introgression of QTL governing LWD resistance. In BC₁F₁ population of NAI-137×97B, both foreground and background selection was implemented using flanking markers controlling LWD resistance QTL and polymorphic markers distributed evenly throughout the recipient parent genome, respectively. Sixteen BC₁F₁ plants carrying LWD resistance QTL with over 80% recipient parent genetic background were identified. Further, 10 out of 16 BC₂F₁ plants carried LWD resistance QTL flanked by markers with varying inter-marker distance with over 90% recipient genetic background. Their resistance level was better than or comparable to donor parent and showed LWD score of ≤ 3. The selfed progenies of these 10 plants were evaluated for resistance to LWD to identify the plants homozygous for LWD resistance controlling QTL, as self-fertilization is capable of increasing the homozygosity of non-carrier chromosomes, while reducing the heterozygosity and avoid further segregation in subsequent generations. Muthusamy et al. (2014) reported successful introgression of β-carotene hydroxylase (crtRB1) gene to elite maize inbreds deficient for vitamin-A in two cycles of MABC. About 90% of the recurrent parent genome was recovered in the selected progenies with increased concentration levels of β -carotene among the crtRB1-introgressed inbreds. Simultaneously, lpa2-2 recessive allele (confers low phytate) was successfully introgressed from alpa2‐2 mutant line into a well‐adapted maize line using two MABC cycles using SSR markers (Sureshkumar et al., 2014).

The BC₂F₂ selfed families with lower LWD score (02) differed significantly from recipient susceptible parent as evident from probability value. We could identify 3 progenies homozygous for LWD resistance controlling QTL, this exemplifies the effectiveness of 2 cycles of MABC for enhancing LWD resistance level of NAI-137. Similarly, there are only a few reports on the effectiveness of MABC for enhancing levels of resistance to diseases in maize. Lohitaswa et al. (2015) could successfully identify and introgress sorghum downy mildew (SDM) resistance controlling QTL into recipient genetic background using 2 cycles of MABC. Abalo et al. (2009), Korinsak et al. (2011) and Willcox et al. (2002) have also documented the effectiveness of MABC for enhancing the resistance to maize streak virus, rice leaf blast and south-western corn borer, respectively. Further, the LWD resistant version of NAI-137 shall be used to cross with MAI-105 (the male parent of hybrid Hema) to generate “Hema” whose grain yield potential need to be evaluated in comparison to LWD susceptible “Hema”.

Authors’ contributions

Conceptualization of research (EG, SR); Designing of the experiments (EG, GPS, RR, VMS, DS); Contribution of experimental materials (EG); Execution of field/lab experiments and data collection (GPS, RR, VMS); Analysis of data and interpretation (GPS, RR); Preparation of the manuscript (GPS, SR).

Conflict of Interest:

“The authors declare no conflict of interest”

Ethical approval:

This article does not contain any studies with human participants or animals performed by any of the authors.

Acknowledgment:

Senior author gratefully acknowledges Directorate of Minorities Welfare, Karnataka, for providing fellowship to smoothen the research work. Additionally, acknowledge the facilities aided by CAAST/NGT project for provision of the consumables in lab and conducting various workshops, training programs that helped us troubleshoot the research problems.

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Marker-assisted mapping and backcross breeding for late wilt disease resistance in NAI-137, the seed parent of public bred single cross maize (Zea mays L.) hybrid Hema

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Abstract

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Introduction

Material and Methods

Statistical analysis

Results

Introgression of LWD resistant QTL in NAI-137, the seed parent of hybrid Hema

Effectiveness of two cycles of MABC for enhancing LWD resistance of NAI-137:

Discussion

Declarations

Conflict of Interest:

Acknowledgment:

References

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