Diversity and temporal distribution of Fusarium oxysporum f. sp. vasinfectum races and genotypes as influenced by Gossypium cultivar

Abstract

This study assess the population diversity and temporal variability of caused by Fusarium oxysporum f. sp. vasinfectum (FOV) races/genotypes infecting cotton cultivars with either FOV or Meloidogyne incognita resistance. All plants sampled demonstrated typical symptoms of FOV including wilting, chlorosis and necrosis of the leaves, and discoloration of the vascular tissue in the stem. A diverse population of FOV was characterized. Eight races/genotypes of FOV were collected throughout the three site years. FOV race 1 was the most predominant in all tests (AUDPC=101.1); statistically higher numbers of isolates from LA-108 (AUDPC=59.9), race 8 (AUDPC=47.5), and race 2 (AUDPC=38.6) were also found compared to other races and genotypes collected. FOV race 1, race 2, race 8, and 108 were the most virulent races identified. The genotypes MDS-12, LA-110, and LA-127/140 were found in all tests but at a low incidence, and LA-112 was only found in trace amounts. MDS-12, LA-110, LA-112, and LA-127/140 produced less disease pressure. FOV race 4 which is highly virulent and present in California and Texas was not found in Alabama. A positive correlation was observed between the accumulation of growing degree days and FOV race 1, race 2, race 8, LA-108, and LA-110. Later symptom expression influenced by seasonal heat partially mitigates damage allowing cotton to produce bolls though they may be reduced in number and lint quality. Plant resistance to the FOV as expressed in these cultivars appears to provide better protection than M. incognita resistance. PhytoGen 72, which is resistant to FOV races/genotypes had low levels of FOV infection even though it sustained a high level of M. incognita root population density. The M. incognita resistant cultivars Deltapine 1558NR B2RF and PhytoGen 480 W3FE supported a lower nematode population density, however, FOV disease incidence was not reduced. FOV races/genotypes did not vary significantly between the nematode resistant and nematode susceptible cultivars.

Keywords: FOV; Fusarium oxysporum f. sp. vasinfectum; Gossypium; Meloidogyne incognita; cotton; genotype; root-knot nematode.

Figure 1

Signs and symptoms of Fusarium wilt on Gossypium hirsutum. (A) Wilting of cotton plant caused by Fusarium wilt infection. (B) Meloidogyne incognita galls on cotton roots. (C) Discoloration of the vascular tissue of a cotton stem. (D) Leaf necrosis and wilting caused by Fusarium wilt.

Figure 2

Condensed phylogenetic tree of FOV isolates collected during the 2018 and 2019 cotton seasons using a partial sequence analysis of the translation elongation factor, β-tubulin, and the phosphate permease genes. Tree was constructed in MEGAX using the maximum likelihood method based on the Tamura-Nei model (Tamura and Nei, 1993). The tree with the highest log likelihood (-2944.90) is shown. Bootstrap frequencies from 1,000 replications are noted next to every branch. Isolates with identical sequences collected during the study are represented by a single isolate in the tree and are labeled with the year of collection and the number of identical isolates that were found. For example, isolate 2019 (201) represents 201 identical isolates that were collected in 2019. Isolates collected during the 2018 season are shown in blue and isolates collected during 2019 are shown in red. References isolates (in black) used for comparison are labeled by the race followed by an isolate name, for example Race 1 (CA10) is a race 1 reference isolate identified as CA 10. A non-pathogenic Fusarium oxysporum (isolate 1502) was used as an outgroup to root the tree.

Figure 3

(A) Temporal disease progression curves for each race/genotype of FOV collected to show the distribution throughout the cotton seasons depicted as a solid line for 2018 testing and a dashed line for 2019 testing. Area under the disease progress curve (AUDPC) is shaded in a lighter color as indicated by the legend. (B) Box plots with means (indicated by thick horizontal lines) and 95% confidence intervals (shaded boxes) of the AUDPC values for each race/genotype of FOV as estimated by a linear mixed effect model shown as an average of all three test. Calculated AUDPC values for individual test plots are marked by symbols corresponding to the test from which they were collected. The mean AUDPC value is listed just above the mean line for each race/genotype of FOV and statistical significance is indicated by letters below the boxplots. Races/genotypes that share letters do not differ significantly.

Figure 4

Gel electrophoresis image of a PCR analysis for the detection of Tƒo1, MITE/Tƒo1, MULE/Tƒo1 insertions into the PHO gene of FOV isolates which are commonly found in FOV race 4 isolates in the United States. Bands appear at 396 bp when no insertion is present, 583 bp when the Tƒo1 insertion is present, 426 bp when the MULE/Tƒo1 insertion is present, and 663 bp when the MITE/Tƒo insertion is present. Isolates shown are lane 1, 100 bp DNA ladder; lane 2-17, MDS-12 isolates of FOV; lane 18 water control. All isolates produced a band at 396 bp showing the lack of a Tƒo insertion into the PHO gene.

Figure 5

Phylogenetic tree of FOV isolates collected during the 2018 and 2019 cotton seasons using a partial sequence analysis of the translation elongation factor and nearly full-length sequences of the intergenic spacer region. This tree only shows isolates that were identified as FOV race 4 and MDS-12 when sequenced at the translation elongation factor, β-tubulin, and the phosphate permease gene regions, and thus required further sequencing for identification. Tree was constructed in MEGAX using the maximum likelihood method based on the Tamura-Nei model (Tamura and Nei, 1993). The tree with the highest log likelihood (-7043.88) is shown. Bootstrap frequencies from 1,000 replications are noted next to every branch. Isolates are labeled with the year that they were collected followed by the cultivar from which they were collected, in the case of isolates having the identical name, a number was added in parenthesis to separate isolates. For example, isolate 2018 Rowden (2) represents the second isolate collected from the Rowden cultivar in 2018. Isolates collected during the 2018 season are shown in blue and isolates collected during 2019 are shown in red. Reference isolates (in black) used for comparison are labeled by the race followed by an isolate name, for example Race 1 (CA10) is a race 1 reference isolate identified as CA 10. A non-pathogenic Fusarium oxysporum (isolate 1502) was used as an outgroup to root the tree.

Figure 6

(A) Temporal disease progression curves for each cultivar included in the test to show the distribution throughout the cotton seasons demonstrated as a solid line for 2018 testing and a dashed line for 2019 testing. Area under the disease progress curve (AUDPC) is shaded in a lighter color as indicated by the legend. (B) Box plots means (indicated by thick horizontal lines) and 95% confidence intervals (shaded boxes) of the AUDPC values for each cotton cultivar as estimated by a linear mixed effect model shown as an average of all three test. Calculated AUDPC values for individual test plots are marked by symbols corresponding to the test from which they were collected. The mean AUDPC value is listed just above the mean line for each race/genotype of FOV and statistical significance is indicated by letters below the boxplots. Races/genotypes that share significance letters do not differ significantly.

Figure 7

The 2018 and 2019 temporal distribution of Fusarium oxysporum f. sp. vasinfectum (FOV) throughout the cotton growing season. Graph shows the linear relationship between the number of FOV samples collected and the accumulation of growing degree days (DD60’s). Linear relationships for race 1 race 2, race 8, LA-108, and LA-110 are shown. Other races and genotypes found in this study did not have a significant relationship with accumulation of DD60’s and therefore are not shown in this figure.