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

Ulloa, Mauricio; Wang, Congli; Hutmacher, Robert B.; Wright, Steven D.; Davis, R. M.; Saski, Christopher; Roberts, Philip A.

doi:10.1007/s00438-011-0616-1

Cited by 51 publications

(62 citation statements)

References 34 publications

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“…Genetic mapping coupled with physical alignment of genomic regions into chromosomal maps will expedite the discovery of resistance (R) or pathogen-induced R genes underlying QTL involved in resistance to nematode and Fusarium wilt (Ulloa et al 2011). Chromosomes 11 (A11) and 21 (D11) are homologs that harbor important genes for cotton improvement because these chromosomes contain genes for resistance to reniform (Dighe et al 2009) and root-knot nematodes (Wang et al 2006a), race 1 of Fusarium (Ulloa et al 2010) and other traits affecting fiber yield and quality.…”

Section: Discussionmentioning

confidence: 99%

A High-Density Simple Sequence Repeat and Single Nucleotide Polymorphism Genetic Map of the Tetraploid Cotton Genome

Kohel

Fang

et al. 2012

G3 Genes|Genomes|Genetics

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112

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Genetic linkage maps play fundamental roles in understanding genome structure, explaining genome formation events during evolution, and discovering the genetic bases of important traits. A high-density cotton (Gossypium spp.) genetic map was developed using representative sets of simple sequence repeat (SSR) and the first public set of single nucleotide polymorphism (SNP) markers to genotype 186 recombinant inbred lines (RILs) derived from an interspecific cross between Gossypium hirsutum L. (TM-1) and G. barbadense L. (3-79). The genetic map comprised 2072 loci (1825 SSRs and 247 SNPs) and covered 3380 centiMorgan (cM) of the cotton genome (AD) with an average marker interval of 1.63 cM. The allotetraploid cotton genome produced equivalent recombination frequencies in its two subgenomes (At and Dt). Of the 2072 loci, 1138 (54.9%) were mapped to 13 At-subgenome chromosomes, covering 1726.8 cM (51.1%), and 934 (45.1%) mapped to 13 Dt-subgenome chromosomes, covering 1653.1 cM (48.9%). The genetically smallest homeologous chromosome pair was Chr. 04 (A04) and 22 (D04), and the largest was Chr. 05 (A05) and 19 (D05). Duplicate loci between and within homeologous chromosomes were identified that facilitate investigations of chromosome translocations. The map augments evidence of reciprocal rearrangement between ancestral forms of Chr. 02 and 03 versus segmental homeologs 14 and 17 as centromeric regions show homeologous between Chr. 02 (A02) and 17 (D02), as well as between Chr. 03 (A03) and 14 (D03). This research represents an important foundation for studies on polyploid cottons, including germplasm characterization, gene discovery, and genome sequence assembly.

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Section: Discussionmentioning

confidence: 99%

A High-Density Simple Sequence Repeat and Single Nucleotide Polymorphism Genetic Map of the Tetraploid Cotton Genome

Kohel

Fang

et al. 2012

G3 Genes|Genomes|Genetics

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103

112

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“…Markers can be used to improve elite cotton cultivar productivity, fiber and seed quality properties, and stress tolerance through marker-assisted selection (MAS) (Cao et al 2014;Said et al 2013). Using MAS, the breeding process can be accelerated, labor costs and time reduced, and selection effectiveness increased in identification of improved genotypes (Buckler et al 2009;Ulloa et al 2010Ulloa et al , 2011.…”

Section: Introductionmentioning

confidence: 99%

Mapping genomic loci for cotton plant architecture, yield components, and fiber properties in an interspecific (Gossypium hirsutum L. × G. barbadense L.) RIL population

Ulloa²,

Hoffman

et al. 2014

Mol Genet Genomics

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A quantitative trait locus (QTL) mapping was conducted to better understand the genetic control of plant architecture (PA), yield components (YC), and fiber properties (FP) in the two cultivated tetraploid species of cotton (Gossypium hirsutum L. and G. barbadense L.). One hundred and fifty-nine genomic regions were identified on a saturated genetic map of more than 2,500 SSR and SNP markers, constructed with an interspecific recombinant inbred line (RIL) population derived from the genetic standards of the respective cotton species (G. hirsutum acc. TM-1 × G. barbadense acc. 3-79). Using the single nonparametric and MQM QTL model mapping procedures, we detected 428 putative loci in the 159 genomic regions that confer 24 cotton traits in three diverse production environments [College Station F&B Road (FB), TX; Brazos Bottom (BB), TX; and Shafter (SH), CA]. These putative QTL loci included 25 loci for PA, 60 for YC, and 343 for FP, of which 3, 12, and 60, respectively, were strongly associated with the traits (LOD score ≥ 3.0). Approximately 17.7 % of the PA putative QTL, 32.9 % of the YC QTL, and 48.3 % of the FP QTL had trait associations under multiple environments. The At subgenome (chromosomes 1-13) contributed 72.7 % of loci for PA, 46.2 % for YC, and 50.4 % for FP while the Dt subgenome (chromosomes 14-26) contributed 27.3 % of loci for PA, 53.8 % for YC, and 49.6 % for FP. The data obtained from this study augment prior evidence of QTL clusters or gene islands for specific traits or biological functions existing in several non-homoeologous cotton chromosomes. DNA markers identified in the 159 genomic regions will facilitate further dissection of genetic factors underlying these important traits and marker-assisted selection in cotton.

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“…51). In earlier studies under different evaluation conditions and using cultivars as parents and derived progeny with different response to FOV infection and different genetic backgrounds, FOV resistance was indicated to be under control of one or two major genes with complete to incomplete dominance, and possibly additional minor genes (Mohamed 1963;Smith and Dick 1960;Ulloa et al 2006Ulloa et al , 2011Ulloa et al , 2013. As disease progressed and wilt severity increased over time from inoculation, especially for heterozygous progeny, fewer resistant plants could be identified.…”

Section: Resultsmentioning

confidence: 99%

“…The effective approaches to combat FOV epidemics are to understand the genetics of host-plant resistance, FOV race-plant interactions, and FOV pathogenicity Ulloa et al 2011Ulloa et al , 2013. These are important steps and prerequisites for cotton breeding targeting introgression of resistance loci into adapted elite cultivar .…”

Section: Introductionmentioning

confidence: 99%

“…In early studies, successive genetic analyses indicated that FOV resistance was determined by one or two major genes with complete to incomplete dominance, and possibly additional minor genes (Mohamed 1963;Smith and Dick 1960;Ulloa et al 2006). In recent inheritance and quantitative trait (QTL) studies (Wang et al 2009;Ulloa et al 2011Ulloa et al , 2013Becerra Lopez-Lavalle et al 2012;Mei et al 2014), resistance to races 1, 4, 7 and the Australian FOV races was reported to be inherited through gene interactions detected in more than one chromosome. Collectively, the results from these studies (Wang et al 2009;Ulloa et al 2011Ulloa et al , 2013Becerra Lopez-Lavalle et al 2012) suggested a different race gene-specificity of FOV resistance in cotton [Fov1 (race 1)-chromosome 16, Fov4 (race 4)-chromosome 14 or 17 Wang et al 2014), FW R (race 7)-chromosome 17, and-Australian race of Fov-chromosomes 6, 22, and 25] .…”

Section: Introductionmentioning

confidence: 99%

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

Абдуллаев

Salakhutdinov²,

Egamberdiev³

et al. 2015

Genetica

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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.

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

Cited by 51 publications

References 34 publications

A High-Density Simple Sequence Repeat and Single Nucleotide Polymorphism Genetic Map of the Tetraploid Cotton Genome

A High-Density Simple Sequence Repeat and Single Nucleotide Polymorphism Genetic Map of the Tetraploid Cotton Genome

Mapping genomic loci for cotton plant architecture, yield components, and fiber properties in an interspecific (Gossypium hirsutum L. × G. barbadense L.) RIL population

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

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