Identification and molecular mapping of a Fusarium wilt resistant gene in upland cotton

Lightweight cotton diseases real-time detection model for resource-constrained devices in natural environments

Cotton, a vital textile raw material, is intricately linked to people's livelihoods. Throughout the cotton cultivation process, various diseases threaten cotton crops, significantly impacting both cotton quality and yield. Deep learning has emerged as a crucial tool for detecting these diseases. However, deep learning models with high accuracy often come with redundant parameters, making them challenging to deploy on resource-constrained devices. Existing detection models struggle to strike the right balance between accuracy and speed, limiting their utility in this context. This study introduces the CDDLite-YOLO model, an innovation based on the YOLOv8 model, designed for detecting cotton diseases in natural field conditions. The C2f-Faster module replaces the Bottleneck structure in the C2f module within the backbone network, using partial convolution. The neck network adopts Slim-neck structure by replacing the C2f module with the GSConv and VoVGSCSP modules, based on GSConv. In the head, we introduce the MPDIoU loss function, addressing limitations in existing loss functions. Additionally, we designed the PCDetect detection head, integrating the PCD module and replacing some CBS modules with PCDetect. Our experimental results demonstrate the effectiveness of the CDDLite-YOLO model, achieving a remarkable mean average precision (mAP) of 90.6%. With a mere 1.8M parameters, 3.6G FLOPS, and a rapid detection speed of 222.22 FPS, it outperforms other models, showcasing its superiority. It successfully strikes a harmonious balance between detection speed, accuracy, and model size, positioning it as a promising candidate for deployment on an embedded GPU chip without sacrificing performance. Our model serves as a pivotal technical advancement, facilitating timely cotton disease detection and providing valuable insights for the design of detection models for agricultural inspection robots and other resource-constrained agricultural devices.

A genome-wide association study for resistance to Fusarium wilt (Fusarium oxysporum f. sp. vasinfectum) race 4 in diploid cotton (Gossypium arboreum) and resistance transfer to tetraploid Gossypium hirsutum

Fusarium wilt, caused by the soilborne fungus Fusarium oxysporum f. sp. vasinfectum (FOV), is a devastating disease affecting cotton (Gossypium spp.) worldwide. Understanding the genetic basis of resistance in diploid cotton and successfully transferring the resistance to tetraploid Upland cotton (G. hirsutum) are crucial for developing resistant cotton cultivars. Although numerous studies have been conducted to investigate the genetic basis of Fusarium wilt in tetraploid cotton, little research has been conducted on diploid species. In this study, an association mapping panel consisting of 246 accessions of G. arboreum, was used to identify chromosomal regions for FOV race 4 (FOV4) resistance based on foliar disease severity ratings in four greenhouse tests. Through a genome-wide association study (GWAS) based on 7,009 single nucleotide polymorphic (SNP) markers, 24 FOV4 resistance QTLs, including three major QTLs on chromosomes A04, A06, and A11, were detected. A validation panel consisting of 97 diploid cotton accessions was employed, confirming the presence of several QTLs. Evaluation of an introgressed BC2F7 population derived from G. hirsutum/G. aridum/G. arboreum showed significant differences in disease incidence and mortality rate, as compared to susceptible and resistant controls, suggesting that the resistance in G. arboreum and/or G. aridum was transferred into Upland cotton for the first time. The identification of novel major resistance QTLs, along with the transfer of resistance from the diploid species, expands our understanding of the genomic regions involved in conferring resistance to FOV4 and contributes to the development of resilient Upland cotton cultivars.

Genetic Mapping and Characterization of Verticillium Wilt Resistance in a Recombinant Inbred Population of Upland Cotton

Verticillium wilt (VW) is an important and widespread disease of cotton and once established is long-lived and difficult to manage. In Australia, the non-defoliating pathotype of Verticillium dahliae is the most common, and extremely virulent. Breeding cotton varieties with increased VW resistance is the most economical and effective method of controlling this disease and is greatly aided by understanding the genetics of resistance. This study aimed to investigate VW resistance in 240 F7 recombinant inbred lines (RIL) derived from a cross between MCU-5, which has good resistance, and Siokra 1-4, which is susceptible. Using a controlled environment bioassay, we found that resistance based on plant survival or shoot biomass was complex but with major contributions from chromosomes D03 and D09, with genomic prediction analysis estimating a prediction accuracy of 0.73 based on survival scores compared to 0.36 for shoot biomass. Transcriptome analysis of MCU-5 and Siokra 1-4 roots uninfected or infected with V. dahliae revealed that the two cultivars displayed very different root transcriptomes and responded differently to V. dahliae infection. Ninety-nine differentially expressed genes were located in the two mapped resistance regions and so are potential candidates for further identifying the genes responsible for VW resistance.

Development and validation of allele-specific PCR-based SNP typing in a gene on chromosome D03 conferring resistance to Fusarium wilt race 4 in Upland cotton (Gossypium hirsutum)

Upland cotton (Gossypium hirsutum) is the most important fiber crop for the global textile industry. Fusarium oxysporum f. sp. vasinfectum (FOV) is one of the most destructive soil-borne fungal pathogens in cotton. Among eight pathogenic races and other strains, FOV race 4 (FOV4) is the most virulent race in US cotton production. A single nucleotide polymorphism (SNP) in a glutamate receptor-like gene (GhGLR4.8) on chromosome D03 was previously identified and validated to confer resistance to FOV race 7, and targeted genome sequencing demonstrated that it was also associated with resistance to FOV4. The objective of this study was to develop an easy and convenient PCR-based marker assay. To target the resistance SNP, a forward primer for the SNP with a mismatch in the 3rd position was designed for both the resistance (R) and susceptibility (S) alleles, respectively, with addition of 20-mer T7 promoter primer to the 5' end of the forward primer for the R allele. The two forward primers, in combination with each of five common reverse primers, were targeted to amplify amplicons of 50-260 bp in size with R and S alleles differing in 20 bp. Results showed that each of three common reverse primers in combination with the two forward primers produced polymorphic markers between R and S plants that were consistent with the targeted genome sequencing results. The polymorphism was distinctly resolved using both polyacrylamide and agarose gel electrophoreses. In addition, a sequence comparative analysis between the resistance gene and homologous sequences in sequenced tetraploid and diploid A and D genome species showed that none of the species possessed the resistance gene allele, suggesting its recent origin from a natural point mutation. The allele-specific PCR-based SNP typing method based on a three-primer combination provides a fast and convenient marker-assisted selection method to search and select for FOV4-resistant Upland cotton.

Unraveling genomic regions and candidate genes for multiple disease resistance in upland cotton using meta-QTL analysis

Verticillium wilt (VW), Fusarium wilt (FW) and Root-knot nematode (RKN) are the main diseases affecting cotton production. However, many reported quantitative trait loci (QTLs) for cotton resistance have not been used for agricultural practices because of inconsistencies in the cotton genetic background. The integration of existing cotton genetic resources can facilitate the discovery of important genomic regions and candidate genes involved in disease resistance. Here, an improved and comprehensive meta-QTL analysis was conducted on 487 disease resistant QTLs from 31 studies in the last two decades. A consensus linkage map with genetic overall length of 3006.59 cM containing 8650 markers was constructed. A total of 28 Meta-QTLs (MQTLs) were discovered, among which nine MQTLs were identified as related to resistance to multiple diseases. Candidate genes were predicted based on public transcriptome data and enriched in pathways related to disease resistance. This study used a method based on the integration of Meta-QTL, known genes and transcriptomics to reveal major genomic regions and putative candidate genes for resistance to multiple diseases, providing a new basis for marker-assisted selection of high disease resistance in cotton breeding.

Targeted development of diagnostic SNP markers for resistance to Fusarium wilt race 4 in Upland cotton (Gossypium hirsutum)

Fusarium wilt caused by the soil-borne fungus Fusarium oxysporum f. sp. vasinfectum (FOV) race 4 (FOV4) has become one of the most important emerging diseases in US cotton production. Numerous QTLs have been reported for resistance to FOV; however, no major FOV4-resistance QTL or gene has been identified and used in breeding Upland cotton (Gossypium hirsutum) for FOV4 resistance. In this study, a panel of 223 Chinese Upland cotton accessions was evaluated for FOV4 resistance based on seedling mortality rate (MR) and stem and root vascular discoloration (SVD and RVD). SNP markers were developed based on targeted genome sequencing using AgriPlex Genomics. The chromosome region at 2.130-2.292 Mb on D03 was significantly correlated with both SVD and RVD but not with MR. Based on the two most significant SNP markers, accessions homozygous for AA or TT SNP genotype averaged significantly lower SVD (0.88 vs. 2.54) and RVD (1.46 vs. 3.02) than those homozygous for CC or GG SNP genotype. The results suggested that a gene or genes within the region conferred resistance to vascular discoloration caused by FOV4. The Chinese Upland accessions had 37.22% homozygous AA or TT SNP genotype and 11.66% heterozygous AC or TG SNP genotype, while 32 US elite public breeding lines all had the CC or GG SNP genotype. Among 463 obsolete US Upland accessions, only 0.86% possessed the AA or TT SNP genotype. This study, for the first time, has developed diagnostic SNPs for marker-assisted selection and identified FOV4-resistant Upland germplasms with the SNPs.

Recent progression and future perspectives in cotton genomic breeding

Upland cotton is an important global cash crop for its long seed fibers and high edible oil and protein content. Progress in cotton genomics promotes the advancement of cotton genetics, evolutionary studies, functional genetics, and breeding, and has ushered cotton research and breeding into a new era. Here, we summarize high-impact genomics studies for cotton from the last 10 years. The diploid Gossypium arboreum and allotetraploid Gossypium hirsutum are the main focus of most genetic and genomic studies. We next review recent progress in cotton molecular biology and genetics, which builds on cotton genome sequencing efforts, population studies, and functional genomics, to provide insights into the mechanisms shaping abiotic and biotic stress tolerance, plant architecture, seed oil content, and fiber development. We also suggest the application of novel technologies and strategies to facilitate genome-based crop breeding. Explosive growth in the amount of novel genomic data, identified genes, gene modules, and pathways is now enabling researchers to utilize multidisciplinary genomics-enabled breeding strategies to cultivate "super cotton", synergistically improving multiple traits. These strategies must rise to meet urgent demands for a sustainable cotton industry.

Quantitative Trait Locus Mapping for Fusarium Wilt Race 4 Resistance in a Recombinant Inbred Line Population of Pima Cotton (Gossypium Barbadense)

Fusarium oxysporum f. sp. vasinfectum (FOV) race 4 (FOV4) causes seedling death immediately after emergence, in addition to leaf chlorosis and necrosis, vascular discoloration, plant wilting, defoliation, and plant death at late stages. Breeding for FOV4 resistance is the most cost effective management method. In this study, 163 recombinant inbred lines (RILs) of FOV4-resistant Pima S-6 × susceptible 89590, together with the two parents (Gossypium barbadense), were artificially inoculated with FOV4 and assayed for resistance based on foliar disease severity ratings (DSR) at 30 days post inoculation (dpi) in two replicated tests in the greenhouse or controlled conditions. Significant genotypic variations were detected for FOV4 resistance in a combined analysis of variance. Although a significant genotype × test interaction was detected for DSR, the 10 most resistant RILs had significantly and consistently lower DSR than the susceptible parent in both tests. The heritability estimate for DSR was 0.65, indicating that two-thirds of the phenotypic variation for FOV4 resistance in this Pima RIL population was due to genetic factors. Based on 404 polymorphic SSR markers, five and four quantitative trait loci (QTL) on six chromosomes (c14, c17, c19, c21, c24, and c25) were detected in Tests 1 and 2, respectively, and each explained 15 to 29% of the phenotypic variation. Three QTL on c17, c24, and c25 were in common between the two tests, accounting for 60% and 75% of the QTL detected in Tests 1 and 2, respectively. The three QTL were also reported in previous studies and will be useful for marker-assisted selection for FOV4 resistance in Pima cotton.

Effects of Fusarium wilt on Cotton Cultivars with and Without Meloidogyne incognita Resistance in Fields

Cotton (Gossypium hirsutum) cultivar trials were conducted in four fields (6 trials total) with Meloidogyne incognita (Mi)/Fusarium oxysporum f. sp. vasinfectum (Fov) from 2019 to 2021. Cotton cultivars were divided into groups based on company/Mi resistance: S = susceptible to Mi; R-FM, R-DP, and R-PHY = resistance to Mi in FiberMax®, Deltapine®, and Phytogen® cultivars, respectively; ST 4946GLB2 (moderate resistance to Mi and observed field tolerance to Fov); and ST 5600B2XF (resistance to Mi). The S and R-FM groups had the highest transformed Mi densities LOG10(Mi + 1) (LMi = 3.22 and 3.01, respectively), while R-DP and R-PHY had the lowest LMi (2.21 and 1.85, respectively). Plant mortality (%) was higher for R-DP (28.1%) than for all other groups except ST 5600B2XF (24.8%). Mi-susceptible cultivars averaged 23.3% mortality. Relative yield (0-1 scale) was higher for ST 4946GLB2 (0.706) and R-PHY (0.635) than for R-DP (0.530), ST 5600B2XF (0.578), and S (0.491). All groups except R-DP averaged higher relative yield than the susceptible cultivars. ST 4946GLB2 had the lowest mortality (16.5%) and highest relative yield, while R-DP cultivars had the highest mortality and no difference in relative yield from the Mi-susceptible cultivars. The group of R-DP cultivars had excellent Mi resistance but were susceptible to Fov. No cultivars were identified with high resistance to Fov.

A GWAS identified a major QTL for resistance to Fusarium wilt (Fusarium oxysporum f. sp. vasinfectum) race 4 in a MAGIC population of Upland cotton and a meta-analysis of QTLs for Fusarium wilt resistance

A major QTL conferring resistance to Fusarium wilt race 4 in a narrow region of chromosome D02 was identified in a MAGIC population of 550 RILs of Upland cotton. Numerous studies have been conducted to investigate the genetic basis of Fusarium wilt (FW, caused by Fusarium oxysporum f. sp. vasinfectum, FOV) resistance using bi-parental and association mapping populations in cotton. In this study, a multi-parent advanced generation inter-cross (MAGIC) population of 550 recombinant inbred lines (RILs), together with their 11 Upland cotton (Gossypium hirsutum) parents, was used to identify QTLs for FOV race 4 (FOV4) resistance. Among the parents, Acala Ultima, M-240 RNR, and Stoneville 474 were the most resistant, while Deltapine Acala 90, Coker 315, and Stoneville 825 were the most susceptible. Twenty-two MAGIC lines were consistently resistant to FOV4. Through a genome-wide association study (GWAS) based on 473,516 polymorphic SNPs, a major FOV4 resistance QTL within a narrow region on chromosomes D02 was detected, allowing identification of 14 candidate genes. Additionally, a meta-analysis of 133 published FW resistance QTLs showed a D subgenome and individual chromosome bias and no correlation between homeologous chromosome pairs. This study represents the first GWAS study using a largest genetic population and the most comprehensive meta-analysis for FW resistance in cotton. The results illustrated that 550 lines were not enough for high resolution mapping to pinpoint a candidate gene, and experimental errors in phenotyping cotton for FW resistance further compromised the accuracy and precision in QTL localization and identification of candidate genes. This study identified FOV4-resistant parents and MAGIC lines, and the first major QTL for FOV4 resistance in Upland cotton, providing useful information for developing FOV4-resistant cultivars and further genomic studies towards identification of causal genes for FOV4 resistance in cotton.

Quantitative Trait Locus Mapping and Identification of Candidate Genes for Resistance to Fusarium Wilt Race 7 Using a Resequencing-Based High Density Genetic Bin Map in a Recombinant Inbred Line Population of Gossypium barbadense

Fusarium wilt caused by Fusarium oxysporum f. sp. vasinfectum (FOV) is one of the most destructive diseases in cotton (Gossypium spp.) production, and use of resistant cultivars is the most cost-effective method managing the disease. To understand the genetic basis of cotton resistance to FOV race 7 (FOV7), this study evaluated a recombinant inbred line (RIL) population of 110 lines of G. barbadense from a cross between susceptible Xinhai 14 and resistant 06-146 in eight tests and constructed a high-density genetic linkage map with resequencing-based 933,845 single-nucleotide polymorphism (SNP) markers covering a total genetic distance of 2483.17 cM. Nine quantitative trait loci (QTLs) for FOV7 resistance were identified, including qFOV7-D03-1 on chromosome D03 in two tests. Through a comparative analysis of gene expression and DNA sequence for predicted genes within the QTL region between the two parents and selected lines inoculated with FOV7, GB_D03G0217 encoding for a calmodulin (CaM)-like (CML) protein was identified as a candidate gene. A further analysis confirmed that the expression of GB_D03G0217 was suppressed, leading to increased disease severity in plants of the resistant parent with virus induced gene silencing (VIGS).

Mapping of dynamic QTLs for resistance to Fusarium wilt (Fusarium oxysporum f. sp. vasinfectum) race 4 in a backcross inbred line population of Upland cotton

KEY MESSAGE

A backcross inbred line population of cotton was evaluated for Fusarium wilt race 4 resistance at different days after inoculation (DAI). Both constitutively expressed and developmentally regulated QTLs were detected. The soil-borne fungus Fusarium oxysporum f. sp. vasinfectum (FOV) race 4 (FOV4) causes Fusarium wilt including seedling mortality in cotton. A backcross inbred line (BIL) population of 181 lines, derived from a bi-parental cross of moderately resistant non-recurrent Hai 7124 (Gossypium barbadense) and recurrent parent CCRI 36 (G. hirsutum), was evaluated under temperature-controlled conditions for FOV4 resistance with artificial inoculations. Based on three replicated tests evaluated at 7, 14, 21, and 28 days after inoculation (DAI), only 2-5 BILs showed lower disease severity ratings (DSR) than the parents while 22-50 BILs were more susceptible, indicating transgressive segregation toward susceptibility. Although DSR were overall congruent between DAI, there were many BILs displaying different responses to FOV4 across DAI. Genetic mapping using 7709 SNP markers identified 42 unique QTLs for four evaluation parameters- disease incidence (DI), DSR, mortality rate (MR), and area under disease progress curve (AUDPC), including 26 for two or more parameters. All five QTLs for AUDPC were co-localized with QTLs for DI, DSR, and/or MR at one or two DAI, indicating the unnecessary use of AUDPC in QTL mapping for FOV4 resistance. Those common QTLs explained the significant positive associations between parameters observed. Ten common QTLs with negative or positive additive effects were detected between DAI. DAI-specific and consistent QTLs were detected between DAI in cotton for the first time, suggesting the existence of both constitutively expressed and developmentally regulated QTLs for FOV4 resistance and the importance of evaluating genetic populations for FOV4 resistance at different growth stages.

Novel Genomic Regions of Fusarium Wilt Resistance in Bottle Gourd [Lagenaria siceraria (Mol.) Standl.] Discovered in Genome-Wide Association Study

Fusarium wilt (FW) is a typical soil-borne disease that seriously affects the yield and fruit quality of bottle gourd. Thus, to improve resistance to FW in bottle gourd, the genetic mechanism underlying FW resistance needs to be explored. In this study, we performed a genome-wide association study (GWAS) based on 5,330 single-nucleotide polymorphisms (SNPs) and 89 bottle gourd accessions. The GWAS results revealed a total of 10 SNPs (P ≤ 0.01, -log₁₀ P ≥ 2.0) significantly associated with FW resistance that were detected in at least two environments (2019DI, 2020DI, and the average across the 2 years); these SNPs were located on chromosomes 1, 2, 3, 4, 8, and 9. Linkage disequilibrium (LD) block structure analysis predicted three potential candidate genes for FW resistance. Genes HG_GLEAN_10001030 and HG_GLEAN_10001042 were within the range of the mean LD block of the marker BGReSe_14202; gene HG_GLEAN_10011803 was 280 kb upstream of the marker BGReSe_00818. Real-time quantitative PCR (qRT-PCR) analysis showed that HG_GLEAN_10011803 was significantly up-regulated in FW-infected plants of YD-4, Yin-10, and Hanbi; HG_GLEAN_10001030 and HG_GLEAN_10001042 were specifically up-regulated in FW-infected plants of YD-4. Therefore, gene HG_GLEAN_10011803 is likely the major effect candidate gene for resistance against FW in bottle gourd. This work provides scientific evidence for the exploration of candidate gene and development of functional markers in FW-resistant bottle gourd breeding programs.

A Single-Nucleotide Mutation in a GLUTAMATE RECEPTOR-LIKE Gene Confers Resistance to Fusarium Wilt in Gossypium hirsutum

Fusarium wilt (FW) disease of cotton, caused by the fungus Fusarium oxysporum f. sp. vasinfectum (Fov), causes severe losses in cotton production worldwide. Though significant advancements have been made in development of FW-resistant Upland cotton (Gossypium hirsutum) in resistance screening programs, the precise resistance genes and the corresponding molecular mechanisms for resistance to Fov remain unclear. Herein it is reported that Fov7, a gene unlike canonical plant disease-resistance (R) genes, putatively encoding a GLUTAMATE RECEPTOR-LIKE (GLR) protein, confers resistance to Fov race 7 in Upland cotton. A single nucleotide polymorphism (SNP) (C/A) in GhGLR4.8, resulting in an amino acid change (L/I), is associated with Fov resistance. A PCR-based DNA marker (GhGLR4.8SNP(A/C) ) is developed and shown to cosegregate with the Fov resistance. CRISPR/Cas9-mediated knockout of Fov7 results in cotton lines extremely susceptible to Fov race 7 with a loss of the ability to induce calcium influx in response to total secreted proteins (SEPs) of Fov. Furthermore, coinfiltration of SEPs with GhGLR4.8A results in a hypersensitive response. This first report of a GLR-encoding gene that functions as an R gene provides a new insight into plant-pathogen interactions and a new handle to develop cotton cultivars with resistance to Fov race 7.

Regulatory Network of Cotton Genes in Response to Salt, Drought and Wilt Diseases (Verticillium and Fusarium): Progress and Perspective

In environmental conditions, crop plants are extremely affected by multiple abiotic stresses including salinity, drought, heat, and cold, as well as several biotic stresses such as pests and pathogens. However, salinity, drought, and wilt diseases (e.g., Fusarium and Verticillium) are considered the most destructive environmental stresses to cotton plants. These cause severe growth interruption and yield loss of cotton. Since cotton crops are central contributors to total worldwide fiber production, and also important for oilseed crops, it is essential to improve stress tolerant cultivars to secure future sustainable crop production under adverse environments. Plants have evolved complex mechanisms to respond and acclimate to adverse stress conditions at both physiological and molecular levels. Recent progresses in molecular genetics have delivered new insights into the regulatory network system of plant genes, which generally includes defense of cell membranes and proteins, signaling cascades and transcriptional control, and ion uptake and transport and their relevant biochemical pathways and signal factors. In this review, we mainly summarize recent progress concerning several resistance-related genes of cotton plants in response to abiotic (salt and drought) and biotic (Fusarium and Verticillium wilt) stresses and classify them according to their molecular functions to better understand the genetic network. Moreover, this review proposes that studies of stress related genes will advance the security of cotton yield and production under a changing climate and that these genes should be incorporated in the development of cotton tolerant to salt, drought, and fungal wilt diseases (Verticillium and Fusarium).

A genome-wide association study uncovers consistent quantitative trait loci for resistance to Verticillium wilt and Fusarium wilt race 4 in the US Upland cotton

A high-resolution GWAS detected consistent QTL for resistance to Verticillium wilt and Fusarium wilt race 4 in 376 U.S. Upland cotton accessions based on six independent replicated greenhouse tests. Verticillium wilt (VW, caused by Verticillium dahliae Kleb.) and Fusarium wilt (FOV, caused by Fusarium oxysporum f.sp. vasinfectum Atk. Sny & Hans) are the most important soil-borne fungal diseases in cotton. To augment and refine resistance quantitative trait loci (QTL), we conducted a genome-wide association study (GWAS) using high-density genotyping with the CottonSNP63K array. Resistance of 376 US Upland cotton accessions to a defoliating VW and virulent FOV4 was evaluated in four and two independent replicated greenhouse tests, respectively. A total of 15 and 13 QTL for VW and FOV4 resistances were anchored by 30 (on five chromosomes) and 56 (on six chromosomes) significant single nucleotide polymorphic (SNPs) markers, respectively. QTL on c8, c10, c16, and c21 were consistent in two or more tests for VW resistance, while two QTL on c8 and c14 were consistent for FOV4 resistance in two tests. Two QTL clusters on c16 and c19 were observed for both VW and FOV4 resistance, suggesting that these genomic regions may harbor genes in response to both diseases. Using BLAST search against the sequenced TM-1 genome, 30 and 35 candidate genes were identified on four QTL for VW resistance and on three QTL for FOV4 resistance, respectively. These genomic regions were rich in NBS-LRR genes presented in clusters. The results create opportunities for further studies to determine the correlations of field resistance with these QTL, molecular examinations of VW and FOV4 resistances, marker-assisted selection (MAS) and eventual cloning of QTL for disease resistance in cotton.

Dual species transcript profiling during the interaction between banana (Musa acuminata) and the fungal pathogen Fusarium oxysporum f. sp. cubense

Background

Banana wilt disease, caused by Fusarium oxysporum f. sp. cubense Tropical Race 4 (Foc TR4), is one of the most devastating diseases in banana (Musa spp.). Foc is a soil borne pathogen that causes rot of the roots or wilt of leaves by colonizing the xylem vessels. The dual RNA sequencing is used to simultaneously assess the transcriptomes of pathogen and host. This method greatly helps to understand the responses of pathogen and host to each other and discover the potential pathogenic mechanism.

Results

Plantlets of two economically important banana cultivars, Foc TR4 less susceptible cultivar NK and susceptible cultivar BX, were used to research the Foc-banana interaction mechanism. Notably, the infected NK had more significantly up-regulated genes on the respiration machinery including TCA cycle, glyoxylate, glycerol, and glycolysis compared to BX at 27 h post inoculation (hpi). In addition, genes involved in plant-pathogen interaction, starch, sucrose, linolenic acid and sphingolipid metabolisms were uniquely more greatly induced in BX than those in NK during the whole infection. Genes related to the biosynthesis and metabolism of SA and JA were greatly induced in the infected NK; while auxin and abscisic acid metabolisms related genes were strongly stimulated in the infected BX at 27 hpi. Furthermore, most of fungal genes were more highly expressed in the roots of BX than in those of NK. The fungal genes related to pathogenicity, pectin and chitin metabolism, reactive oxygen scavenging played the important roles during the infection of Foc. CCP1 (cytochrome c peroxidase 1) was verified to involve in cellulose utilization, oxidative stress response and pathogenicity of fungus.

Conclusion

The transcriptome indicated that NK had much faster defense response against Foc TR4 than BX and the expression levels of fungal genes were higher in BX than those in NK. The metabolisms of carbon, nitrogen, and signal transduction molecular were differentially involved in pathogen infection in BX and NK. Additionally, the putative virulence associated fungal genes involved in colonization, nutrition acquirement and transport provided more insights into the infection process of Foc TR4 in banana roots.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5902-z) contains supplementary material, which is available to authorized users.

Quantitative Trait Loci Mapping of Multiple Independent Loci for Resistance to Fusarium oxysporum f. sp. vasinfectum Races 1 and 4 in an Interspecific Cotton Population

Fusarium wilt, caused by the soilborne fungal pathogen Fusarium oxysporum f. sp. vasinfectum, is a vascular disease of cotton (Gossypium spp.). F. oxysporum f. sp. vasinfectum race 1 (FOV1) causes major plant injury and yield loss in G. hirsutum cultivars with coinfection with root-knot nematode (Meloidogyne incognita), while F. oxysporum f. sp. vasinfectum race 4 (FOV4) causes plant damage without nematode coinfection in G. hirsutum and in G. barbadense cultivars. Quantitative trait loci (QTL) analysis of the interspecific cross G. barbadense Pima S-7 × G. hirsutum Acala NemX revealed separate multiple loci determining resistance to FOV1 and FOV4, confirming that race specificity occurs in F. oxysporum f. sp. vasinfectum. Based on the area under the disease progress stairs, six major QTLs on chromosomes (Chrs) 1, 2, 12, 15 (2), and 21 contributing 7 to 15% to FOV1 resistance and two major QTLs on Chrs 14 and 17 contributing 12 to 33% to FOV4 resistance were identified. Minor-effect QTLs contributing to resistance to both FOV1 and FOV4 were also identified. These results define and establish a pathosystem of race-specific resistance under polygenic control. This research also validates the importance of previously reported markers and chromosome regions and adds new information for the location of F. oxysporum f. sp. vasinfectum resistance genes. Some F₈ recombinant inbred lines have resistance to both FOV1 and FOV4 and also to root-knot nematode, providing multiple resistance sources for breeding.

High-Density Genetic Map Construction and Gene Mapping of Basal Branching Habit and Flowers per Leaf Axil in Sesame

A good genetic map can provide the framework for quantitative trait loci (QTL) analysis, map-based gene cloning, and genome sequence assembling. The main objectives of this study were to develop a high-density genetic linkage map using specific length amplified fragment sequencing (SLAF-seq) in sesame. In the result, a high-resolution genetic map with 9,378 SLAF markers and 13 linkage groups (LGs) was constructed. The map spanned a total genetic distance of 1,974.23 cM, and the mean LG length was 151.86 cM, with an average genetic distance of 0.22 cM between adjacent markers. Based on the newly constructed genetic map, genes for basal branching habit (SiBH) and flowers per leaf axil (SiFA) were mapped to LG5 and LG11, respectively.

Genetic analysis of Verticillium wilt resistance in a backcross inbred line population and a meta-analysis of quantitative trait loci for disease resistance in cotton

Background

Verticillium wilt (VW) and Fusarium wilt (FW), caused by the soil-borne fungi Verticillium dahliae and Fusarium oxysporum f. sp. vasinfectum, respectively, are two most destructive diseases in cotton production worldwide. Root-knot nematodes (Meloidogyne incognita, RKN) and reniform nematodes (Rotylenchulus reniformis, RN) cause the highest yield loss in the U.S. Planting disease resistant cultivars is the most cost effective control method. Numerous studies have reported mapping of quantitative trait loci (QTLs) for disease resistance in cotton; however, very few reliable QTLs were identified for use in genomic research and breeding.

Results

This study first performed a 4-year replicated test of a backcross inbred line (BIL) population for VW resistance, and 10 resistance QTLs were mapped based on a 2895 cM linkage map with 392 SSR markers. The 10 VW QTLs were then placed to a consensus linkage map with other 182 VW QTLs, 75 RKN QTLs, 27 FW QTLs, and 7 RN QTLs reported from 32 publications. A meta-analysis of QTLs identified 28 QTL clusters including 13, 8 and 3 QTL hotspots for resistance to VW, RKN and FW, respectively. The number of QTLs and QTL clusters on chromosomes especially in the A-subgenome was significantly correlated with the number of nucleotide-binding site (NBS) genes, and the distribution of QTLs between homeologous A- and D- subgenome chromosomes was also significantly correlated.

Conclusions

Ten VW resistance QTL identified in a 4-year replicated study have added useful information to the understanding of the genetic basis of VW resistance in cotton. Twenty-eight disease resistance QTL clusters and 24 hotspots identified from a total of 306 QTLs and linked SSR markers provide important information for marker-assisted selection and high resolution mapping of resistance QTLs and genes. The non-overlapping of most resistance QTL hotspots for different diseases indicates that their resistances are controlled by different genes.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1682-2) contains supplementary material, which is available to authorized users.

Analyses of Fusarium wilt race 3 resistance in Upland cotton (Gossypium hirsutum L.)

Fusarium wilt [Fusarium oxysporum f.sp. vasinfectum (FOV) Atk. Sny & Hans] represents a serious threat to cotton (Gossypium spp.) production. For the last few decades, the FOV pathogen has become a significant problem in Uzbekistan causing severe wilt disease and yield losses of G. hirsutum L. cultivars. We present the first genetic analyses of FOV race 3 resistance on Uzbek Cotton Germplasm with a series of field and greenhouse artificial inoculation-evaluations and inheritance studies. The field experiments were conducted in two different sites: the experimental station in Zangiota region-Environment (Env) 1 and the Institute of Cotton Breeding (Env-2, Tashkent province). The Env-1 was known to be free of FOV while the Env-2 was known to be a heavily FOV infested soil. In both (Env-1 and Env-2) of these sites, field soil was inoculated with FOV race 3. F2 and an F3 Upland populations ("Mebane B1" × "11970") were observed with a large phenotypic variance for plant survival and FOV disease severity within populations and among control or check Upland accessions. Wilt symptoms among studied F2 individuals and F3 families significantly differed depending on test type and evaluation site. Distribution of Mendelian rations of susceptible (S) and resistant (R) phenotypes were 1S:1R field Env-1 and 3S:1R field Env-2 in the F2 population, and 1S:3R greenhouse site in the F3 population. The different segregation distribution of the Uzbek populations may be explained by differences in FOV inoculum level and environmental conditions during assays. However, genetic analysis indicated a recessive single gene action under high inoculum levels or disease pressure for FOV race 3 resistance. Uzbek germplasm may be more susceptible than expected to FOV race 3, and sources of resistance to FOV may be limited under the FOV inoculum levels present in highly-infested fields making the breeding process more complex.

Cotton QTLdb: a cotton QTL database for QTL analysis, visualization, and comparison between Gossypium hirsutum and G. hirsutum × G. barbadense populations

KEY MESSAGE

A specialized database currently containing more than 2200 QTL is established, which allows graphic presentation, visualization and submission of QTL. In cotton quantitative trait loci (QTL), studies are focused on intraspecific Gossypium hirsutum and interspecific G. hirsutum × G. barbadense populations. These two populations are commercially important for the textile industry and are evaluated for fiber quality, yield, seed quality, resistance, physiological, and morphological trait QTL. With meta-analysis data based on the vast amount of QTL studies in cotton it will be beneficial to organize the data into a functional database for the cotton community. Here we provide a tool for cotton researchers to visualize previously identified QTL and submit their own QTL to the Cotton QTLdb database. The database provides the user with the option of selecting various QTL trait types from either the G. hirsutum or G. hirsutum × G. barbadense populations. Based on the user's QTL trait selection, graphical representations of chromosomes of the population selected are displayed in publication ready images. The database also provides users with trait information on QTL, LOD scores, and explained phenotypic variances for all QTL selected. The CottonQTLdb database provides cotton geneticist and breeders with statistical data on cotton QTL previously identified and provides a visualization tool to view QTL positions on chromosomes. Currently the database (Release 1) contains 2274 QTLs, and succeeding QTL studies will be updated regularly by the curators and members of the cotton community that contribute their data to keep the database current. The database is accessible from http://www.cottonqtldb.org.

Cotton QTLdb: a cotton QTL database for QTL analysis, visualization, and comparison between Gossypium hirsutum and G. hirsutum × G. barbadense populations

KEY MESSAGE

A specialized database currently containing more than 2200 QTL is established, which allows graphic presentation, visualization and submission of QTL. In cotton quantitative trait loci (QTL), studies are focused on intraspecific Gossypium hirsutum and interspecific G. hirsutum × G. barbadense populations. These two populations are commercially important for the textile industry and are evaluated for fiber quality, yield, seed quality, resistance, physiological, and morphological trait QTL. With meta-analysis data based on the vast amount of QTL studies in cotton it will be beneficial to organize the data into a functional database for the cotton community. Here we provide a tool for cotton researchers to visualize previously identified QTL and submit their own QTL to the Cotton QTLdb database. The database provides the user with the option of selecting various QTL trait types from either the G. hirsutum or G. hirsutum × G. barbadense populations. Based on the user's QTL trait selection, graphical representations of chromosomes of the population selected are displayed in publication ready images. The database also provides users with trait information on QTL, LOD scores, and explained phenotypic variances for all QTL selected. The CottonQTLdb database provides cotton geneticist and breeders with statistical data on cotton QTL previously identified and provides a visualization tool to view QTL positions on chromosomes. Currently the database (Release 1) contains 2274 QTLs, and succeeding QTL studies will be updated regularly by the curators and members of the cotton community that contribute their data to keep the database current. The database is accessible from http://www.cottonqtldb.org.

A comparative meta-analysis of QTL between intraspecific Gossypium hirsutum and interspecific G. hirsutum × G. barbadense populations

KEY MESSAGE

Based on 1075 and 1059 QTL from intraspecific Upland and interspecific Upland × Pima populations, respectively, the identification of QTL clusters and hotspots provides a useful resource for cotton breeding. Mapping of quantitative trait loci (QTL) is a pre-requisite of marker-assisted selection for crop yield and quality. Recent meta-analysis of QTL in tetraploid cotton (Gossypium spp.) has identified regions of the genome with high concentrations of QTL for various traits called clusters and specific trait QTL called hotspots or meta-QTL (mQTL). However, the meta-analysis included all population types of Gossypium mixing both intraspecific G. hirsutum and interspecific G. hirsutum × G. barbadense populations. This study used 1,075 QTL from 58 publications on intraspecific G. hirsutum and 1,059 QTL from 30 publications on G. hirsutum × G. barbadense populations to perform a comprehensive comparative analysis of QTL clusters and hotspots between the two populations for yield, fiber and seed quality, and biotic and abiotic stress tolerance. QTL hotspots were further analyzed for mQTL within the hotspots using Biomercator V3 software. The ratio of QTL between the two population types was proportional yet differences in hotspot type and placement were observed between the two population types. However, on some chromosomes QTL clusters and hotspots were similar between the two populations. This shows that there are some universal QTL regions in the cultivated tetraploid cotton which remain consistent and some regions which differ between population types. This study for the first time elucidates the similarities and differences in QTL clusters and hotspots between intraspecific and interspecific populations, providing an important resource to cotton breeding programs in marker-assisted selection .

Molecular mapping and validation of a major QTL conferring resistance to a defoliating isolate of verticillium wilt in cotton (Gossypium hirsutum L.)

Verticillium wilt (VW) caused by Verticillium dahliae Kleb is one of the most destructive diseases of cotton. Development and use of a VW resistant variety is the most practical and effective way to manage this disease. Identification of highly resistant genes/QTL and the underlining genetic architecture is a prerequisite for developing a VW resistant variety. A major QTL qVW-c6-1 conferring resistance to the defoliating isolate V991 was identified on chromosome 6 in LHB22×JM11 F2∶3 population inoculated and grown in a greenhouse. This QTL was further validated in the LHB22×NNG F2∶3 population that was evaluated in an artificial disease nursery of V991 for two years and in its subsequent F4 population grown in a field severely infested by V991. The allele conferring resistance within the QTL qVW-c6-1 region originated from parent LHB22 and could explain 23.1-27.1% of phenotypic variation. Another resistance QTL qVW-c21-1 originated from the susceptible parent JM11 was mapped on chromosome 21, explaining 14.44% of phenotypic variation. The resistance QTL reported herein provides a useful tool for breeding a cotton variety with enhanced resistance to VW.

Plant defense response against Fusarium oxysporum and strategies to develop tolerant genotypes in banana

Soil-borne fungal pathogen, Fusarium oxysporum causes major economic losses by inducing necrosis and wilting symptoms in many crop plants. Management of fusarium wilt is achieved mainly by the use of chemical fungicides which affect the soil health and their efficiency is often limited by pathogenic variability. Hence understanding the nature of interaction between pathogen and host may help to select and improve better cultivars. Current research evidences highlight the role of oxidative burst and antioxidant enzymes indicating that ROS act as an important signaling molecule in banana defense response against Fusarium oxysporum f.sp. cubense. The role of jasmonic acid signaling in plant defense against necrotrophic pathogens is well recognized. But recent studies show that the role of salicylic acid is complex and ambiguous against necrotrophic pathogens like Fusarium oxysporum, leading to many intriguing questions about its relationship between other signaling compounds. In case of banana, a major challenge is to identify specific receptors for effector proteins like SIX proteins and also the components of various signal transduction pathways. Significant progress has been made to uncover the role of defense genes but is limited to only model plants such as Arabidopsis and tomato. Keeping this in view, we review the host response, pathogen diversity, current understanding of biochemical and molecular changes that occur during host and pathogen interaction. Developing resistant cultivars through mutation, breeding, transgenic and cisgenic approaches have been discussed. This would help us to understand host defenses against Fusarium oxysporum and to formulate strategies to develop tolerant cultivars.

Association analysis of fiber quality traits and exploration of elite alleles in Upland cotton cultivars/accessions (Gossypium hirsutum L.)

Exploring the elite alleles and germplasm accessions related to fiber quality traits will accelerate the breeding of cotton for fiber quality improvement. In this study, 99 Gossypium hirsutum L. accessions with diverse origins were used to perform association analysis of fiber quality traits using 97 polymorphic microsatellite marker primer pairs. A total of 107 significant marker-trait associations were detected for three fiber quality traits under three different environments, with 70 detected in two or three environments and 37 detected in only one environment. Among the 70 significant marker-trait associations, 52.86% were reported previously, implying that these are stable loci for target traits. Furthermore, we detected a large number of elite alleles associated simultaneously with two or three traits. These elite alleles were mainly from accessions collected in China, introduced to China from the United States, or rare alleles with a frequency of less than 5%. No one cultivar contained more than half of the elite alleles, but 10 accessions were collected from China and the two introduced from the United States did contain more than half of these alleles. Therefore, there is great potential for mining elite alleles from germplasm accessions for use in fiber quality improvement in modern cotton breeding.

A comprehensive meta QTL analysis for fiber quality, yield, yield related and morphological traits, drought tolerance, and disease resistance in tetraploid cotton

BACKGROUND

The study of quantitative trait loci (QTL) in cotton (Gossypium spp.) is focused on traits of agricultural significance. Previous studies have identified a plethora of QTL attributed to fiber quality, disease and pest resistance, branch number, seed quality and yield and yield related traits, drought tolerance, and morphological traits. However, results among these studies differed due to the use of different genetic populations, markers and marker densities, and testing environments. Since two previous meta-QTL analyses were performed on fiber traits, a number of papers on QTL mapping of fiber quality, yield traits, morphological traits, and disease resistance have been published. To obtain a better insight into the genome-wide distribution of QTL and to identify consistent QTL for marker assisted breeding in cotton, an updated comparative QTL analysis is needed.

RESULTS

In this study, a total of 1,223 QTL from 42 different QTL studies in Gossypium were surveyed and mapped using Biomercator V3 based on the Gossypium consensus map from the Cotton Marker Database. A meta-analysis was first performed using manual inference and confirmed by Biomercator V3 to identify possible QTL clusters and hotspots. QTL clusters are composed of QTL of various traits which are concentrated in a specific region on a chromosome, whereas hotspots are composed of only one trait type. QTL were not evenly distributed along the cotton genome and were concentrated in specific regions on each chromosome. QTL hotspots for fiber quality traits were found in the same regions as the clusters, indicating that clusters may also form hotspots.

CONCLUSIONS

Putative QTL clusters were identified via meta-analysis and will be useful for breeding programs and future studies involving Gossypium QTL. The presence of QTL clusters and hotspots indicates consensus regions across cultivated tetraploid Gossypium species, environments, and populations which contain large numbers of QTL, and in some cases multiple QTL associated with the same trait termed a hotspot. This study combines two previous meta-analysis studies and adds all other currently available QTL studies, making it the most comprehensive meta-analysis study in cotton to date.

Inheritance and QTL mapping of Fusarium wilt race 4 resistance in cotton

Diseases such as Fusarium wilt [Fusarium oxysporum f.sp. vasinfectum (FOV) Atk. Sny & Hans] represent expanding threats to cotton production. Integrating disease resistance into high-yielding, high-fiber quality cotton (Gossypium spp.) cultivars is one of the most important objectives in cotton breeding programs worldwide. In this study, we conducted a comprehensive analysis of gene action in cotton governing FOV race 4 resistance by combining conventional inheritance and quantitative trait loci (QTL) mapping with molecular markers. A set of diverse cotton populations was generated from crosses encompassing multiple genetic backgrounds. FOV race 4 resistance was investigated using seven parents and their derived populations: three intraspecific (G. hirsutum × G. hirsutum L. and G. barbadense × G. barbadense L.) F1 and F2; five interspecific (G. hirsutum × G. barbadense) F1 and F2; and one RIL. Parents and populations were evaluated for disease severity index (DSI) of leaves, and vascular stem and root staining (VRS) in four greenhouse and two field experiments. Initially, a single resistance gene (Fov4) model was observed in F2 populations based on inheritance of phenotypes. This single Fov4 gene had a major dominant gene action and conferred resistance to FOV race 4 in Pima-S6. The Fov4 gene appears to be located near a genome region on chromosome 14 marked with a QTL Fov4-C14 1 , which made the biggest contribution to the FOV race 4 resistance of the generated F2 progeny. Additional genetic and QTL analyses also identified a set of 11 SSR markers that indicated the involvement of more than one gene and gene interactions across six linkage groups/chromosomes (3, 6, 8, 14, 17, and 25) in the inheritance of FOV race 4 resistance. QTLs detected with minor effects in these populations explained 5-19 % of the DSI or VRS variation. Identified SSR markers for the resistance QTLs with major and minor effects will facilitate for the first time marker-assisted selection for the introgression of FOV race 4 resistance into elite cultivars during the breeding process.

Identification and evaluation of two diagnostic markers linked to Fusarium wilt resistance (race 4) in banana (Musa spp.)

Fusarium wilt caused by the fungus Fusarium oxysporum f. sp. cubense race 4 (FOC4) results in vascular tissue damage and ultimately death of banana (Musa spp.) plants. Somaclonal variants of in vitro micropropagated banana can hamper success in propagation of genotypes resistant to FOC4. Early identification of FOC4 resistance in micropropagated banana plantlets is difficult, however. In this study, we identified sequence-characterized amplified region (SCAR) markers of banana associated with resistance to FOC4. Using pooled DNA from resistant or susceptible genotypes and 500 arbitrary 10-mer oligonucleotide primers, 24 random amplified polymorphic DNA (RAPD) products were identified. Two of these RAPD markers were successfully converted to SCAR markers, called ScaU1001 (GenBank accession number HQ613949) and ScaS0901 (GenBank accession number HQ613950). ScaS0901 and ScaU1001 could be amplified in FOC4-resistant banana genotypes ("Williams 8818-1" and Goldfinger), but not in five tested banana cultivars susceptible to FOC4. The two SCAR markers were then used to identify a somaclonal variant of the genotype "Williams 8818-1", which lost resistance to FOC4. Hence, the identified SCAR markers can be applied for a rapid quality control of FOC4-resistant banana plantlets immediately after the in vitro micropropagation stage. Furthermore, ScaU1001 and ScaS0901 will facilitate marker-assisted selection of new banana cultivars resistant to FOC4.

Mapping Fusarium wilt race 1 resistance genes in cotton by inheritance, QTL and sequencing composition

Knowledge of the inheritance of disease resistance and genomic regions housing resistance (R) genes is essential to prevent expanding pathogen threats such as Fusarium wilt [Fusarium oxysporum f.sp. vasinfectum (FOV) Atk. Sny & Hans] in cotton (Gossypium spp.). We conducted a comprehensive study combining conventional inheritance, genetic and quantitative trait loci (QTL) mapping, QTL marker-sequence composition, and genome sequencing to examine the distribution, structure and organization of disease R genes to race 1 of FOV in the cotton genome. Molecular markers were applied to F(2) and recombinant inbred line (RIL) interspecific mapping populations from the crosses Pima-S7 (G. barbadense L.) × 'Acala NemX' (G. hirsutum L.) and Upland TM-1 (G. hirsutum) × Pima 3-79 (G. barbadense), respectively. Three greenhouse tests and one field test were used to obtain sequential estimates of severity index (DSI) of leaves, and vascular stem and root staining (VRS). A single resistance gene model was observed for the F(2) population based on inheritance of phenotypes. However, additional inheritance analyses and QTL mapping indicated gene interactions and inheritance from nine cotton chromosomes, with major QTLs detected on five chromosomes [Fov1-C06, Fov1-C08, (Fov1-C11 ( 1 ) and Fov1-C11 ( 2)) , Fov1-C16 and Fov1-C19 loci], explaining 8-31% of the DSI or VRS variation. The Fov1-C16 QTL locus identified in the F(2) and in the RIL populations had a significant role in conferring FOV race 1 resistance in different cotton backgrounds. Identified molecular markers may have important potential for breeding effective FOV race 1 resistance into elite cultivars by marker-assisted selection. Reconciliation between genetic and physical mapping of gene annotations from marker-DNA and new DNA sequences of BAC clones tagged with the resistance-associated QTLs revealed defenses genes induced upon pathogen infection and gene regions rich in disease-response elements, respectively. These offer candidate gene targets for Fusarium wilt resistance response in cotton and other host plants.