Identification and diversity of tropical maize inbred lines with resistance to common rust (Puccinia sorghi Schwein)

Identification of gray leaf spot-resistant donor lines in tropical maize germplasm and their agronomic performance under artificial inoculation

Gray leaf spot (GLS) disease is caused by two fungal pathogens, Cercospora zeae-maydis and Cercospora zeina. The current study evaluated 427 elite tropical/subtropical lines for their responses to GLS under artificial inoculation in Kakamega in western Kenya for 4 years. Furthermore, a subset of 140 lines was used for a high-resolution genome-wide association study (GWAS) for GLS resistance. Among the 427 lines evaluated, 14 were identified as resistant on the basis of a <4 (on a scale of 1-9) GLS disease severity score. Among these 14 lines, three lines, namely CML540, CML559, and CML566, are also known for resistance to MSV, tolerance to drought, and resistance to MLN, respectively. The phenotypic evaluation revealed significant (P < 0.01) genotypic and genotype x environment interaction variances and moderate to high heritability for GLS disease severity, area under disease progress curve (AUDPC), and other agronomic traits. GLS disease severity traits were negatively and significantly correlated (P < 0.01) with anthesis date, silking date, plant height, and ear height. A subset of 140 lines was genotyped with 33,740 DART-GBS SNP markers. Population structure and principal component analysis grouped the lines into two major clusters with moderate structure in the population. GWAS revealed 13 and 11 SNPs significantly associated with GLS disease severity and AUDPC values. Six among the 13 SNPs detected for GLS resistance are overlapped with earlier studies, which can be used for fine mapping and improvement of GLS resistance through marker-assisted selection. However, SNPs on chromosomes 9 and 10 were unique to the present study. Genomic prediction on GLS traits revealed moderate to high prediction correlations, suggesting its usefulness in the selection of desirable candidates with favorable alleles for GLS resistance. Overall, 14 GLS resistance lines identified in this study can be used as donor lines in both genetic studies and resistance breeding programs.

Inheritance of resistance to maize lethal necrosis in tropical maize inbred lines

Maize (Zea mays L.) production in sub-Saharan Africa can be improved by using hybrids with genetic resistance to maize lethal necrosis (MLN). This study aimed to assess the general (GCA) and specific combining ability (SCA), reciprocal effects, and quantitative genetic basis of MLN resistance and agronomic traits in tropical maize inbred lines. A total of 182 hybrids from a 14-parent diallel, along with their parents, were evaluated under artificial MLN inoculation and rainfed conditions for 3 years in Kenya. Disease ratings at four time points, grain yield (GY), and other agronomic traits were analyzed using Griffing's Method 3 and Hayman's diallel models. Significant (P < 0.001) GCA and SCA mean squares were observed for all traits under disease conditions and most traits under rainfed conditions, highlighting the importance of both additive and non-additive genetic effects. However, additive gene action predominated for all traits. Narrow-sense heritability estimates for MLN resistance (h 2 = 0.52-0.56) indicated a strong additive genetic component. Reciprocal effects were not significant for MLN resistance, suggesting minimal maternal or cytoplasmic inheritance. Four inbred lines showed significant negative GCA effects for MLN resistance and positive GCA effects for GY under artificial MLN inoculation. Inbred lines CKL181281 and CKL182037 (GCA effects for MLN4 = -0.45 and -0.24, respectively) contained the most recessive alleles for MLN resistance. The minimum number of groups of genes involved in MLN resistance was estimated to be three. Breeding strategies that emphasize GCA could effectively be used to improve MLN resistance in this germplasm.

Use of remote sensing for linkage mapping and genomic prediction for common rust resistance in maize

Breeding for disease resistance is a central component of strategies implemented to mitigate biotic stress impacts on crop yield. Conventionally, genotypes of a plant population are evaluated through a labor-intensive process of assigning visual scores (VS) of susceptibility (or resistance) by specifically trained staff, which limits manageable volumes and repeatability of evaluation trials. Remote sensing (RS) tools have the potential to streamline phenotyping processes and to deliver more standardized results at higher through-put. Here, we use a two-year evaluation trial of three newly developed biparental populations of maize doubled haploid lines (DH) to compare the results of genomic analyses of resistance to common rust (CR) when phenotyping is either based on conventional VS or on RS-derived (vegetation) indices. As a general observation, for each population × year combination, the broad sense heritability of VS was greater than or very close to the maximum heritability across all RS indices. Moreover, results of linkage mapping as well as of genomic prediction (GP), suggest that VS data was of a higher quality, indicated by higher - log p values in the linkage studies and higher predictive abilities for genomic prediction. Nevertheless, despite the qualitative differences between the phenotyping methods, each successfully identified the same genomic region on chromosome 10 as being associated with disease resistance. This region is likely related to the known CR resistance locus Rp1. Our results indicate that RS technology can be used to streamline genetic evaluation processes for foliar disease resistance in maize. In particular, RS can potentially reduce costs of phenotypic evaluations and increase trialing capacities.

Combination of linkage and association mapping with genomic prediction to infer QTL regions associated with gray leaf spot and northern corn leaf blight resistance in tropical maize

Among the diseases threatening maize production in Africa are gray leaf spot (GLS) caused by Cercospora zeina and northern corn leaf blight (NCLB) caused by Exserohilum turcicum. The two pathogens, which have high genetic diversity, reduce the photosynthesizing ability of susceptible genotypes and, hence, reduce the grain yield. To identify population-based quantitative trait loci (QTLs) for GLS and NCLB resistance, a biparental population of 230 lines derived from the tropical maize parents CML511 and CML546 and an association mapping panel of 239 tropical and sub-tropical inbred lines were phenotyped across multi-environments in western Kenya. Based on 1,264 high-quality polymorphic single-nucleotide polymorphisms (SNPs) in the biparental population, we identified 10 and 18 QTLs, which explained 64.2% and 64.9% of the total phenotypic variance for GLS and NCLB resistance, respectively. A major QTL for GLS, qGLS1_186 accounted for 15.2% of the phenotypic variance, while qNCLB3_50 explained the most phenotypic variance at 8.8% for NCLB resistance. Association mapping with 230,743 markers revealed 11 and 16 SNPs significantly associated with GLS and NCLB resistance, respectively. Several of the SNPs detected in the association panel were co-localized with QTLs identified in the biparental population, suggesting some consistent genomic regions across genetic backgrounds. These would be more relevant to use in field breeding to improve resistance to both diseases. Genomic prediction models trained on the biparental population data yielded average prediction accuracies of 0.66-0.75 for the disease traits when validated in the same population. Applying these prediction models to the association panel produced accuracies of 0.49 and 0.75 for GLS and NCLB, respectively. This research conducted in maize fields relevant to farmers in western Kenya has combined linkage and association mapping to identify new QTLs and confirm previous QTLs for GLS and NCLB resistance. Overall, our findings imply that genetic gain can be improved in maize breeding for resistance to multiple diseases including GLS and NCLB by using genomic selection.

Genetic Variation Among Tropical Maize Inbred Lines from NARS and CGIAR Breeding Programs

The use of molecular markers allows for precise estimates of genetic diversity, which is an important parameter that enables breeders to select parental lines and designing breeding systems. We assessed the level of genetic diversity and population structure in a panel of 151 tropical maize inbred lines using 10,940 SNP (single nucleotide polymorphism) markers generated through the DArTseq genotyping platform. The average gene diversity was 0.39 with expected heterozygosity ranging from 0.00 to 0.84, and a mean of 0.02. Analysis of molecular variance showed that 97% of allelic diversity was attributed to individual inbred lines within the populations while only 3% was distributed among the populations. Both neighbor-joining clustering and STRUCTURE analysis classified the inbred lines into four major groups. The crosses that involve inbred lines from most divergent subgroups are expected to generate maximum heterosis and produce wide variation. The results will be beneficial for breeders to better understand and exploit the genetic diversity available in the set of maize inbred lines we studied.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11105-022-01358-2.

Comparative genome analysis unravels pathogenicity of Xanthomonas albilineans causing sugarcane leaf scald disease

Background

Xanthomonas is a genus of gram-negative bacterium containing more than 35 species. Among these pathogenic species, Xanthomonas albilineans (Xal) is of global interest, responsible for leaf scald disease in sugarcane. Another notable Xanthomonas species is Xanthomonas sachari (Xsa), a sugarcane-associated agent of chlorotic streak disease.

Result

The virulence of 24 Xanthomonas strains was evaluated by disease index (DI) and Area Under Disease Progress Curve (AUDPC) in the susceptible inoculated plants (GT 46) and clustered into three groups of five highly potent, seven mild virulent, and twelve weak virulent strains. The highly potent strain (X. albilineans, Xal JG43) and its weak virulent related strain (X. sacchari, Xsa DD13) were sequenced, assembled, and annotated in the circular genomes. The genomic size of JG43 was smaller than that of DD13. Both strains (JG43 and DD13) lacked a Type III secretory system (T3SS) and T6SS. However, JG43 possessed Salmonella pathogenicity island-1 (SPI-1). More pathogen-host interaction (PHI) genes and virulent factors in 17 genomic islands (GIs) were detected in JG43, among which six were related to pathogenicity. Albicidin and a two-component system associated with virulence were also detected in JG43. Furthermore, 23 Xanthomonas strains were sequenced and classified into three categories based on Single Nucleotide Polymorphism (SNP) mutation loci and pathogenicity, using JG43 as a reference genome. Transitions were dominant SNP mutations, while structural variation (SV) is frequent intrachromosomal rearrangement (ITX). Two essential genes (rpfC/rpfG) of the two-component system and another gene related to SNP were mutated to understand their virulence effect. The mutation of rpfG resulted in a decrease in pathogenicity.

Conclusion

These findings revealed virulence of 24 Xanthomonas strains and variations by 23 Xanthomonas strains. We sequenced, assembled, and annotated the circular genomes of Xal JG43 and Xsa DD13, identifying diversity detected by pathogenic factors and systems. Furthermore, complete genomic sequences and sequenced data will provide a theoretical basis for identifying pathogenic factors responsible for sugarcane leaf scald disease.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-022-08900-2.

Studies of Evaluation Methods for Resistance to Fusarium Wilt Race 4 (Fusarium oxysporum f. sp. vasinfectum) in Cotton: Effects of Cultivar, Planting Date, and Inoculum Density on Disease Progression

Fusarium wilt caused by Fusarium oxysporum f. sp. vasinfectum race 4 (FOV4) is an early season disease causing root rot, seedling wilt, and death. To develop an appropriate field evaluation method for resistance to FOV4 in cotton breeding, the objectives of this study were to investigate the effects of cultivar, planting date, and inoculum density on disease progression in 2020-2021. Results showed that the usual local mid-April planting had the lowest disease severity (DSR) or mortality rate (MR) in 2020 and 2021. DSR or MR increased at the late April and early May plantings in both years and reached the highest at the early May planting in 2020, while MR in 2021 was followed by a decrease in the late May planting and reached the highest in the mid-June planting. Local daily low temperatures between mid-April and mid-June were favorable for FOV4 infections, whereas daily high temperatures at 35°C or higher suppressed wilt severity. When seedlings at the 2-true leaf stage were inoculated with 10⁴, 10⁵, 10⁶, and 10⁷ conidia ml^-1 per plant in 2020, DSR was low but a linear relationship between inoculum density and DSR was observed. When a FOV4-infested soil supplemented with artificial inoculation was used, disease progression in three moderately susceptible or moderately resistant cultivars followed a linear model, while it followed a quadratic model in the highly susceptible Pima S-7 cultivar only. Among the other three cultivars, FM 2334GLT had the lowest DSR or MR except for one planting date in both years, followed by PHY 725 RF and Pima PHY 881 RF in ascending order, which were consistent with the difference in regression coefficients of the linear models. This study demonstrates that disease progression curves due to FOV4 can be used to compare responses to FOV4 infections among cotton genotypes in cotton breeding and genetic studies, regardless of planting date and inoculation method.

Genetic Dissection of Quantitative Resistance to Common Rust (Puccinia sorghi) in Tropical Maize (Zea mays L.) by Combined Genome-Wide Association Study, Linkage Mapping, and Genomic Prediction

Common rust is one of the major foliar diseases in maize, leading to significant grain yield losses and poor grain quality. To dissect the genetic architecture of common rust resistance, a genome-wide association study (GWAS) panel and a bi-parental doubled haploid (DH) population, DH1, were used to perform GWAS and linkage mapping analyses. The GWAS results revealed six single-nucleotide polymorphisms (SNPs) significantly associated with quantitative resistance of common rust at a very stringent threshold of P-value 3.70 × 10^-6 at bins 1.05, 1.10, 3.04, 3.05, 4.08, and 10.04. Linkage mapping identified five quantitative trait loci (QTL) at bins 1.03, 2.06, 4.08, 7.03, and 9.00. The phenotypic variation explained (PVE) value of each QTL ranged from 5.40 to 12.45%, accounting for the total PVE value of 40.67%. Joint GWAS and linkage mapping analyses identified a stable genomic region located at bin 4.08. Five significant SNPs were only identified by GWAS, and four QTL were only detected by linkage mapping. The significantly associated SNP of S10_95231291 detected in the GWAS analysis was first reported. The linkage mapping analysis detected two new QTL on chromosomes 7 and 10. The major QTL on chromosome 7 in the region between 144,567,253 and 149,717,562 bp had the largest PVE value of 12.45%. Four candidate genes of GRMZM2G328500, GRMZM2G162250, GRMZM2G114893, and GRMZM2G138949 were identified, which played important roles in the response of stress resilience and the regulation of plant growth and development. Genomic prediction (GP) accuracies observed in the GWAS panel and DH1 population were 0.61 and 0.51, respectively. This study provided new insight into the genetic architecture of quantitative resistance of common rust. In tropical maize, common rust could be improved by pyramiding the new sources of quantitative resistance through marker-assisted selection (MAS) or genomic selection (GS), rather than the implementation of MAS for the single dominant race-specific resistance gene.