Identification of genetic loci associated with rough dwarf disease resistance in maize by integrating GWAS and linkage mapping

Unveiling alfalfa root rot resistance genes through an integrative GWAS and transcriptome study

BACKGROUND

Root rot is a major disease affecting alfalfa (Medicago sativa L.), causing significant yield losses and economic damage. The primary pathogens include Fusarium spp., Rhizoctonia spp., Pythium spp., and Phytophthora spp., with Fusarium being particularly severe. Breeding disease-resistant varieties is crucial for mitigating these losses.

RESULTS

Under conditions of inoculation with Fusarium oxysporum, we conducted a statistical analysis of six phenotypic traits in alfalfa. Significant phenotypic variation was observed among different alfalfa varieties. Correlation analysis revealed significant relationships among traits such as relative yield, relative plant height (PH), and relative root number (NR), indicating potential synergistic roles of these traits in disease resistance. Through GWAS analysis, we identified 41 significant single nucleotide polymorphisms (SNP) associated with root rot resistance across eight chromosomes. The transcriptome analysis identified multiple differentially expressed genes (DEGs) associated with root rot stress, including transcription factors such as WRKY, NAC, AP2, GRAS, HLH, B3, MYB, and ARF. By integrating GWAS and transcriptome data, we identified four key DEGs significantly associated with root rot resistance, offering valuable insights for developing disease-resistant alfalfa varieties and enhancing overall crop resilience.

CONCLUSION

Our study identified significant phenotypic variation and key correlations among traits under root rot stress in alfalfa. We pinpointed 41 significant SNPs associated with root rot resistance across eight chromosomes and identified several key DEGs, including WRKY, NAC, and MYB transcription factors. The integration of GWAS and RNA-Seq data identified four key DEGs associated with root rot resistance, providing valuable insights for breeding disease-resistant alfalfa varieties and enhancing crop resilience.

Combined Genome-Wide Association Study and Linkage Analysis for Mining Candidate Genes for the Kernel Row Number in Maize (Zea mays L.)

Kernel row number (KRN) is one of the key traits that significantly affect maize yield and productivity. Therefore, investigating the candidate genes and their functions in regulating KRN provides a theoretical basis and practical direction for genetic improvement in maize breeding, which is vital for increasing maize yield and understanding domestication. In this study, three recombinant inbred line (RIL) populations were developed using the parental lines AN20, YML1218, CM395, and Ye107, resulting in a multiparent population comprising a total of 490 F9 RILs. Phenotypic evaluation of the RILs for KRN was performed in three distinct environments. The heritability estimates of the RILs ranged from 81.40% to 84.16%. Genotyping-by-sequencing (GBS) of RILs identified 569,529 high-quality single nucleotide polymorphisms (SNPs). Combined genome-wide association study (GWAS) and linkage analyses revealed 120 SNPs and 22 quantitative trait loci (QTLs) which were significantly associated with KRN in maize. Furthermore, two novel candidate genes, Zm00001d042733 and Zm00001d042735, regulating KRN in maize were identified, which were located in close proximity to the significant SNP3-178,487,003 and overlapping the interval of QTL qKRN3-1. Zm00001d042733 encodes ubiquitin carboxyl-terminal hydrolase and Zm00001d042735 encodes the Arabidopsis Tóxicos en Levadura family of proteins. This study identified novel candidate loci and established a theoretical foundation for further functional validation of candidate genes. These findings deepen our comprehension of the genetic mechanisms that underpin KRN and offer potential applications of KRN-related strategies in developing maize varieties with higher yield.

The role of the rhizobiome recruited by root exudates in plant disease resistance: current status and future directions

Root exudates serve as a bridge connecting plant roots and rhizosphere microbes, playing a key role in influencing the assembly and function of the rhizobiome. Recent studies have fully elucidated the role of root exudates in recruiting rhizosphere microbes to enhance plant performance, particularly in terms of plant resistance to soil-borne pathogens; however, it should be noted that the composition and amount of root exudates are primarily quantitative traits regulated by a large number of genes in plants. As a result, there are knowledge gaps in understanding the contribution of the rhizobiome to soil-borne plant disease resistance and the ternary link of plant genes, root exudates, and disease resistance-associated microbes. Advancements in technologies such as quantitative trait loci (QTL) mapping and genome-wide association studies (GWAS) offer opportunities for the identification of genes associated with quantitative traits. In the present review, we summarize recent studies on the interactions of plant and rhizosphere microbes through root exudates to enhance soil-borne plant disease resistance and also highlight methods for quantifying the contribution of the rhizobiome to plant disease resistance and identifying the genes responsible for recruiting disease resistance-associated microbes through root exudates.

Mining of Oil Content Genes in Recombinant Maize Inbred Lines with Introgression from Temperate and Tropical Germplasm

The oil content of maize kernels is essential to determine its nutritional and economic value. A multiparent population (MPP) consisting of five recombinant inbred line (RIL) subpopulations was developed to elucidate the genetic basis of the total oil content (TOC) in maize. The MPP used the subtropical maize inbred lines CML312 and CML384, along with the tropical maize inbred lines CML395, YML46, and YML32 as the female parents, and Ye107 as the male parent. A genome-wide association study (GWAS) was performed using 429 RILs of the multiparent population across three environments, employing 584,847 high-quality single nucleotide polymorphisms (SNPs). Furthermore, linkage analysis was performed in the five subpopulations to identify quantitative trait loci (QTL) linked to TOC in maize. Through QTL mapping and GWAS, 18 QTLs and 60 SNPs that were significantly associated with TOC were identified. Two novel candidate genes, Zm00001d029550 and Zm00001d029551, related to TOC in maize and located on chromosome 1 were reported, which have not been previously reported. These genes are involved in biosynthesis, lipid signal transduction, plant development and metabolism, and stress responses, potentially influencing maize TOC. Haplotype analysis of Zm00001d029550 and Zm00001d029551 revealed that Hap3 could be considered a superior haplotype for increasing TOC in maize. A co-located SNP (SNP-75791466) on chromosome 1, located 5648 bp and 11,951 bp downstream of the candidate genes Zm00001d029550 and Zm00001d029551, respectively, was found to be expressed in various maize tissues. The highest expression was observed in embryos after pollination, indicating that embryos are the main tissue for oil accumulation in maize. This study provides a theoretical basis for understanding the genetic mechanisms underlying maize TOC and developing high-quality, high-oil maize varieties.

Gene pyramiding of ZmGLK36 and ZmGDIα-hel for rough dwarf disease resistance in maize

Maize rough dwarf disease (MRDD) caused by pathogenic viruses in the genus Fijivirus in the family Reoviridae is one of the most destructive diseases in maize. The pyramiding of effective resistance genes into maize varieties is a potential approach to reduce the damage resulting from the disease. Two major quantitative trait loci (QTLs) (qMrdd2 and qMrdd8) have been previously identified. The resistance genes ZmGLK36 and ZmGDIα-hel have also been cloned with the functional markers Indel-26 and IDP25K, respectively. In this study, ZmGLK36 and ZmGDIα-hel were introgressed to improve MRDD resistance of maize lines (Zheng58, Chang7-2, B73, Mo17, and their derived hybrids Zhengdan958 and B73 × Mo17) via marker-assisted selection (MAS). The converted lines and their derived hybrids, carrying one or two genes, were evaluated for MRDD resistance using artificial inoculation methods. The double-gene pyramiding lines and their derived hybrids exhibited increased resistance to MRDD compared to the monogenic lines and the respective hybrids. The genetic backgrounds of the converted lines were highly similar (90.85-98.58%) to the recurrent parents. In addition, agronomic trait evaluation demonstrated that pyramiding lines with one or two genes and their derived hybrids were not significantly different from the recurrent parents and their hybrids under nonpathogenic stress, including period traits (tasseling, pollen shedding, and silking), yield traits (ear length, grain weight per ear and 100-kernel weight) and quality traits (protein and starch content). There were differences in plant architecture traits between the improved lines and their hybrids. This study illustrated the successful development of gene pyramiding for improving MRDD resistance by advancing the breeding process.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-024-01466-9.

Advancements and Prospects of Genome-Wide Association Studies (GWAS) in Maize

Genome-wide association studies (GWAS) have emerged as a powerful tool for unraveling intricate genotype-phenotype association across various species. Maize (Zea mays L.), renowned for its extensive genetic diversity and rapid linkage disequilibrium (LD), stands as an exemplary candidate for GWAS. In maize, GWAS has made significant advancements by pinpointing numerous genetic loci and potential genes associated with complex traits, including responses to both abiotic and biotic stress. These discoveries hold the promise of enhancing adaptability and yield through effective breeding strategies. Nevertheless, the impact of environmental stress on crop growth and yield is evident in various agronomic traits. Therefore, understanding the complex genetic basis of these traits becomes paramount. This review delves into current and future prospectives aimed at yield, quality, and environmental stress resilience in maize and also addresses the challenges encountered during genomic selection and molecular breeding, all facilitated by the utilization of GWAS. Furthermore, the integration of omics, including genomics, transcriptomics, proteomics, metabolomics, epigenomics, and phenomics has enriched our understanding of intricate traits in maize, thereby enhancing environmental stress tolerance and boosting maize production. Collectively, these insights not only advance our understanding of the genetic mechanism regulating complex traits but also propel the utilization of marker-assisted selection in maize molecular breeding programs, where GWAS plays a pivotal role. Therefore, GWAS provides robust support for delving into the genetic mechanism underlying complex traits in maize and enhancing breeding strategies.

Utilizing Two Populations Derived from Tropical Maize for Genome-Wide Association Analysis of Banded Leaf and Sheath Blight Resistance

Banded leaf and sheath blight (BLSB) in maize is a soil-borne fungal disease caused by Rhizoctonia solani Kühn, resulting in significant yield losses. Investigating the genes responsible for regulating resistance to BLSB is crucial for yield enhancement. In this study, a multiparent maize population was developed, comprising two recombinant inbred line (RIL) populations totaling 442 F8RILs. The populations were generated by crossing two tropical inbred lines, CML444 and NK40-1, known for their BLSB resistance, as female parents, with the high-yielding but BLSB-susceptible inbred line Ye107 serving as the common male parent. Subsequently, we utilized 562,212 high-quality single nucleotide polymorphisms (SNPs) generated through genotyping-by-sequencing (GBS) for a comprehensive genome-wide association study (GWAS) aimed at identifying genes responsible for BLSB resistance. The objectives of this study were to (1) identify SNPs associated with BLSB resistance through genome-wide association analyses, (2) explore candidate genes regulating BLSB resistance in maize, and (3) investigate pathways involved in BLSB resistance and discover key candidate genes through Gene Ontology (GO) analysis. The GWAS analysis revealed nineteen SNPs significantly associated with BLSB that were consistently identified across four environments in the GWAS, with phenotypic variation explained (PVE) ranging from 2.48% to 11.71%. Screening a 40 kb region upstream and downstream of the significant SNPs revealed several potential candidate genes. By integrating information from maize GDB and the NCBI, we identified five novel candidate genes, namely, Zm00001d009723, Zm00001d009975, Zm00001d009566, Zm00001d009567, located on chromosome 8, and Zm00001d026376, on chromosome 10, related to BLSB resistance. These candidate genes exhibit association with various aspects, including maize cell membrane proteins and cell immune proteins, as well as connections to cell metabolism, transport, transcriptional regulation, and structural proteins. These proteins and biochemical processes play crucial roles in maize defense against BLSB. When Rhizoctonia solani invades maize plants, it induces the expression of genes encoding specific proteins and regulates corresponding metabolic pathways to thwart the invasion of this fungus. The present study significantly contributes to our understanding of the genetic basis of BLSB resistance in maize, offering valuable insights into novel candidate genes that could be instrumental in future breeding efforts to develop maize varieties with enhanced BLSB resistance.

Plasticity QTLs specifically contribute to the genotype × water availability interaction in maize

KEY MESSAGE

Multi-trial genome wide association study of plasticity indices allow to detect QTLs specifically involved in the genotype x water availability interaction. Concerns regarding high maize yield losses due to increasing occurrences of drought events are growing, and breeders are still looking for molecular markers for drought tolerance. However, the genetic determinism of traits in response to drought is highly complex and identification of causal regions is a tremendous task. Here, we exploit the phenotypic data obtained from four trials carried out on a phenotyping platform, where a diversity panel of 254 maize hybrids was grown under well-watered and water deficit conditions, to investigate the genetic bases of the drought response in maize. To dissociate drought effect from other environmental factors, we performed multi-trial genome-wide association study on well-watered and water deficit phenotypic means, and on phenotypic plasticity indices computed from measurements made for six ecophysiological traits. We identify 102 QTLs and 40 plasticity QTLs. Most of them were new compared to those obtained from a previous study on the same dataset. Our results show that plasticity QTLs cover genetic regions not identified by QTLs. Furthermore, for all ecophysiological traits, except one, plasticity QTLs are specifically involved in the genotype by water availability interaction, for which they explain between 60 and 100% of the variance. Altogether, QTLs and plasticity QTLs captured more than 75% of the genotype by water availability interaction variance, and allowed to find new genetic regions. Overall, our results demonstrate the importance of considering phenotypic plasticity to decipher the genetic architecture of trait response to stress.

A transcription factor ZmGLK36 confers broad resistance to maize rough dwarf disease in cereal crops

Maize rough dwarf disease (MRDD), caused by maize rough dwarf virus (MRDV) or rice black-streaked dwarf virus (RBSDV), seriously threatens worldwide production of all major cereal crops, including maize, rice, wheat and barley. Here we report fine mapping and cloning of a previously reported major quantitative trait locus (QTL) (qMrdd2) for RBSDV resistance in maize. Subsequently, we show that qMrdd2 encodes a G2-like transcription factor named ZmGLK36 that promotes resistance to RBSDV by enhancing jasmonic acid (JA) biosynthesis and JA-mediated defence response. We identify a 26-bp indel located in the 5' UTR of ZmGLK36 that contributes to differential expression and resistance to RBSDV in maize inbred lines. Moreover, we show that ZmDBF2, an AP2/EREBP family transcription factor, directly binds to the 26-bp indel and represses ZmGLK36 expression. We further demonstrate that ZmGLK36 plays a conserved role in conferring resistance to RBSDV in rice and wheat using transgenic or marker-assisted breeding approaches. Our results provide insights into the molecular mechanisms of RBSDV resistance and effective strategies to breed RBSDV-resistant cereal crops.

Advanced backcross QTL analysis and comparative mapping with RIL QTL studies and GWAS provide an overview of QTL and marker haplotype diversity for resistance to Aphanomyces root rot in pea (Pisum sativum)

Aphanomyces euteiches is the most damaging soilborne pea pathogen in France. Breeding of pea resistant varieties combining a diversity of quantitative trait loci (QTL) is a promising strategy considering previous research achievements in dissecting polygenic resistance to A. euteiches. The objective of this study was to provide an overview of the diversity of QTL and marker haplotypes for resistance to A. euteiches, by integrating a novel QTL mapping study in advanced backcross (AB) populations with previous QTL analyses and genome-wide association study (GWAS) using common markers. QTL analysis was performed in two AB populations derived from the cross between the susceptible spring pea variety "Eden" and the two new sources of partial resistance "E11" and "LISA". The two AB populations were genotyped using 993 and 478 single nucleotide polymorphism (SNP) markers, respectively, and phenotyped for resistance to A. euteiches in controlled conditions and in infested fields at two locations. GWAS and QTL mapping previously reported in the pea-Aphanomyces collection and from four recombinant inbred line (RIL) populations, respectively, were updated using a total of 1,850 additional markers, including the markers used in the Eden x E11 and Eden x LISA populations analysis. A total of 29 resistance-associated SNPs and 171 resistance QTL were identified by GWAS and RIL or AB QTL analyses, respectively, which highlighted 10 consistent genetic regions confirming the previously reported QTL. No new consistent resistance QTL was detected from both Eden x E11 and Eden x LISA AB populations. However, a high diversity of resistance haplotypes was identified at 11 linkage disequilibrium (LD) blocks underlying consistent genetic regions, especially in 14 new sources of resistance from the pea-Aphanomyces collection. An accumulation of favorable haplotypes at these 11 blocks was confirmed in the most resistant pea lines of the collection. This study provides new SNP markers and rare haplotypes associated with the diversity of Aphanomyces root rot resistance QTL investigated, which will be useful for QTL pyramiding strategies to increase resistance levels in future pea varieties.

Genome-wide association and genomic prediction for resistance to southern corn rust in DH and testcross populations

Southern corn rust (SCR), caused by Puccinia polysora Underw, is a destructive disease that can severely reduce grain yield in maize (Zea mays L.). Owing to P. polysora being multi-racial, it is very important to explore more resistance genes and develop more efficient selection approaches in maize breeding programs. Here, four Doubled Haploid (DH) populations with 384 accessions originated from selected parents and their 903 testcross hybrids were used to perform genome-wide association (GWAS). Three GWAS processes included the additive model in the DH panel, additive and dominant models in the hybrid panel. As a result, five loci were detected on chromosomes 1, 7, 8, 8, and 10, with P-values ranging from 4.83×10^-7 to 2.46×10^-41. In all association analyses, a highly significant locus on chromosome 10 was detected, which was tight chained with the known SCR resistance gene RPPC and RPPK. Genomic prediction (GP), has been proven to be effective in plant breeding. In our study, several models were performed to explore predictive ability in hybrid populations for SCR resistance, including extended GBLUP with different genetic matrices, maker based prediction models, and mixed models with QTL as fixed factors. For GBLUP models, the prediction accuracies ranged from 0.56-0.60. Compared with traditional prediction only with additive effect, prediction ability was significantly improved by adding additive-by-additive effect (P-value< 0.05). For maker based models, the accuracy of BayesA and BayesB was 0.65, 8% higher than other models (i.e., RRBLUP, BRR, BL, BayesC). Finally, by adding QTL into the mixed linear prediction model, the accuracy can be further improved to 0.67, especially for the G_A model, the prediction performance can be increased by 11.67%. The prediction accuracy of the BayesB model can be further improved significantly by adding QTL information (P-value< 0.05). This study will provide important valuable information for understanding the genetic architecture and the application of GP for SCR in maize breeding.

Two decades of association mapping: Insights on disease resistance in major crops

Climate change across the globe has an impact on the occurrence, prevalence, and severity of plant diseases. About 30% of yield losses in major crops are due to plant diseases; emerging diseases are likely to worsen the sustainable production in the coming years. Plant diseases have led to increased hunger and mass migration of human populations in the past, thus a serious threat to global food security. Equipping the modern varieties/hybrids with enhanced genetic resistance is the most economic, sustainable and environmentally friendly solution. Plant geneticists have done tremendous work in identifying stable resistance in primary genepools and many times other than primary genepools to breed resistant varieties in different major crops. Over the last two decades, the availability of crop and pathogen genomes due to advances in next generation sequencing technologies improved our understanding of trait genetics using different approaches. Genome-wide association studies have been effectively used to identify candidate genes and map loci associated with different diseases in crop plants. In this review, we highlight successful examples for the discovery of resistance genes to many important diseases. In addition, major developments in association studies, statistical models and bioinformatic tools that improve the power, resolution and the efficiency of identifying marker-trait associations. Overall this review provides comprehensive insights into the two decades of advances in GWAS studies and discusses the challenges and opportunities this research area provides for breeding resistant varieties.

Genome-wide association study reveals the genetic basis of brace root angle and diameter in maize

Brace roots are the main organ to support the above-ground part of maize plant. It involves in plant growth and development by water absorption and lodging resistance. The bracing root angle (BRA) and diameter (BRD) are important components of brace root traits. Illuminating the genetic basis of BRA and BRD will contribute the improvement for mechanized harvest and increasing production. A GWAS of BRA and BRD was conducted using an associated panel composed of 508 inbred lines of maize. The broad-sense heritability of BRA and BRD was estimated to be respectively 71% ± 0.19 and 52% ± 0.14. The phenotypic variation of BRA and BRD in the non-stiff stalk subgroup (NSS) and the stiff stalk subgroup (SS) subgroups are significantly higher than that in the tropical/subtropical subgroup (TST) subgroups. In addition, BRA and BRD are significantly positive with plant height (PH), ear length (EL), and kernel number per row (KNPR). GWAS revealed 27 candidate genes within the threshold of p < 1.84 × 10⁻⁶ by both MLM and BLINK models. Among them, three genes, GRMZM2G174736, GRMZM2G445169 and GRMZM2G479243 were involved in cell wall function, and GRMZM2G038073 encoded the NAC transcription factor family proteins. These results provide theoretical support for clarifying the genetic basis of brace roots traits.

A Nuclear Factor Y-B Transcription Factor, GmNFYB17, Regulates Resistance to Drought Stress in Soybean

Soybean is sensitive to drought stress, and increasing tolerance to drought stresses is an important target for improving the performance of soybean in the field. The genetic mechanisms underlying soybean's drought tolerance remain largely unknown. Via a genome-wide association study (GWAS) combined with linkage analysis, we identified 11 single-nucleotide polymorphisms (SNPs) and 22 quantitative trait locus (QTLs) that are significantly associated with soybean drought tolerance. One of these loci, namely qGI10-1, was co-located by GWAS and linkage mapping. The two intervals of qGI10-1 were differentiated between wild and cultivated soybean. A nuclear factor Y transcription factor, GmNFYB17, was located in one of the differentiated regions of qGI10-1 and thus selected as a candidate gene for further analyses. The analysis of 29 homologous genes of GmNFYB17 in soybean showed that most of the genes from this family were involved in drought stress. The over-expression of GmNFYB17 in soybean enhanced drought resistance and yield accumulation. The transgenic plants grew better than control under limited water conditions and showed a lower degree of leaf damage and MDA content but higher RWC, SOD activity and proline content compared with control. Moreover, the transgenic plants showed a fast-growing root system, especially regarding a higher root-top ratio and more branching roots and lateral roots. The better agronomic traits of yield were also found in GmNFYB17 transgenic plants. Thus, the GmNFYB17 gene was proven to positively regulate drought stress resistance and modulate root growth in soybean. These results provide important insights into the molecular mechanisms underlying drought tolerance in soybean.