Bioassay
Quantifying sweetpotato resistance to M. enterolobii is currently expensive and labor-intensive, and standardized resistance thresholds for M. enterolobii do not yet exist for this crop. Resistance in sweetpotato is here defined as a diminished capacity for RKN to reproduce on the host. While a RF less than one is, by this definition, resistant, maintaining nematode populations at or near the initial load is not satisfactory for growers. Ideally, a next-generation sweetpotato variety would be so highly resistant as to be considered a non-host (RF < 0.1), as defined by Hamidi and Hajihassani (2020). The TB population has demonstrated that this level of resistance is attainable in sweetpotato through a single cross with a resistant parent. ‘Tanzania’ averaged RF = 0.03 in four biological replicates, and between the two biological replicates for TB progenies, 233 out of the 246 genotypes assayed (~ 95%) were in concordance between replicates about RF = 1. Further, 35.4% (87/246) of the TB progeny could be classed as non-hosts by the RF < 0.1 definition.
Our second measure of resistance, EGRT, may be confounded by the fact that sweetpotato forms storage roots, though not all genotypes did in our bioassay. For an equal mass of storage roots and fibrous roots, the fibrous roots would have a greater surface area; M. enterolobii may interact with these root tissues differently, influencing relative EGRT. Second stage juveniles of Meloidogyne spp. establish at the zone of cell elongation behind the host plant’s root cap, which is the preferred site of invasion (Karssen et al. 2013), which could indicate that susceptible sweetpotato genotypes with heavy fibrous root production may be particularly susceptible. A third measure, root gall severity rating, is commonly used for Meloidogyne spp.; however, gall severity ratings are poorly correlated with egg counts in the case of M. enterolobii. For example, in a sweetpotato diversity bioassay, Schwarz et. al (2021) found no M. enterolobii gall severity rating above 20%, despite heavy egg production in some lines. Kiewnick et al. (2021) also observed an inconsistent relationship between gall index (a categorical rating of gall severity) and egg counts for M. enterolobii in tomato. Carmona et al. (2020) recommended that RF be used as the primary measure of resistance to M. enterolobii in sweetpotato, while gall index can facilitate the interpretation of RF.
In this experiment we found samples with high egg counts and low (or zero) gall severity ratings. For example, in replicate 1, TB210 had a gall severity rating of 0% yet 3,793 EGRT, while TB135 in replicate 1, had a gall severity rating of 50% and 1,700 EGRT. For close relative M. incognita, certain environmental conditions have been observed to favor many eggs yet few galls in sweetpotato, or many galls with few eggs. Notably, galling is the plant’s response to the nematode, while egg production is the nematode’s response to the plant (Shepherd 1979). Meloidogyne enterolobii may be more sensitive than M. incognita to these conditions. For all traits evaluated, ‘Tanzania’ was highly M. enterolobii resistant while ‘Beauregard’ was highly susceptible, which is consistent with results from Schwarz et al. (2021). Our results also agree with resistance ratings for the eight TB progeny screened by Schwarz et al. (2021): TB019, TB056, TB068, TB146, TB257 were resistant, while TB085, TB131, TB252 were susceptible.
Meloidogyne enterolobii is under internal quarantine in NC and is also subject to quarantine in several other states in the Southeastern US, and is further included on the European and Mediterranean Plant Protection Organization (EPPO) A2 pest list. These quarantines represent a barrier to resistance evaluations in field settings. The inoculation-based greenhouse bioassay provided consistent inoculation to all genotypes tested, but there were some drawbacks. Due to their small size, M. enterolobii eggs are particularly prone to being flushed from our sand-based media by an overwatering event, and great care was taken to avoid this. Contamination between samples (i.e., splashing during watering, or egg transfer on improperly rinsed sieves during extraction, etc.) may also confound results, though this would largely be an issue for negative controls, as small amounts of added inoculum should not drastically affect resistance classes of inoculated resistant plants. Pearson correlations between replicates were moderate for RF, yet highly significant (r = 0.534, P < 0.001). Eggs may have had differential hatch rates between replicates or genotypes, and root growth differences could also explain this moderate correlation.
The bioassay for M. enterolobii requires permitted and quarantined greenhouse space, specially trained staff, takes at least 74 days, and requires extensive resistance evaluations. We estimate that to screen 500 sweetpotato lines in replicated trials for M. enterolobii resistance would require between 200–500 hours of labor, plus supply costs and specialized greenhouse space. It is not feasible to routinely screen large numbers of sweetpotato breeding lines for M. enterolobii resistance in this fashion, yet in a breeding program, evaluating large numbers of genotypes in a high throughput assay is increasingly necessary. The need to assay up to 500 lines annually is not uncommon, and thus designing molecular markers in this QTL region would save a tremendous amount of labor each year and would facilitate the development of a new M. enterolobii-resistant sweetpotato variety. It is not yet known how greenhouse resistance correlates with field resistance to M. enterolobii, and field trials to test greenhouse-resistant genotypes are becoming increasingly necessary.
Plant resistance to RKN is typically race-specific (Ukoskit et al. 1997). Currently it is not clear if distinct races or pathotypes exist for M. enterolobii. For example, M. enterolobii populations on a diversity of crops from sixteen nations exhibited very low genetic diversity based on several different marker types (AFLP, ISSR and RAPD), leading to the conclusion that M. enterolobii was “genetically homogeneous” (Tigano et al. 2010). A phylogenetic analysis and sequencing study of five African M. enterolobii populations found no genetic differences between groups (Onkendi and Moleleki 2013). Four populations of M. enterolobii isolated in NC were found to have no variation in virulence (Schwarz et al. 2020). It may be that diversification of this pest has yet to occur. A recent USDA report found some variation in sweetpotato cultivar response to different M. enterolobii isolates from the Carolinas (Rutter et al. 2021), but there is insufficient evidence to conclusively support the presence of multiple races or pathotypes of M. enterolobii at this time. Meloidogyne enterolobii reproduces via mitotic parthenogenesis, and extremely low diversity would be expected in this primarily asexually reproducing species, however M. incognita, which does have several races, reproduces in the same fashion (Tigano et al. 2010; Yang and Eisenback 1983). Because of the low diversity amongst M. enterolobii populations worldwide, it has been hypothesized that host resistance to one population of M. enterolobii may be effective against many (Tigano et al. 2010).
QTL Analysis
Here, we report a single major QTL, qIbMe-4.1, that was consistently detected by multiple models and for multiple resistance parameters. The REMIM model detected a QTL explaining 70% of the variation in M. enterolobii RF and EGRT in the TB population. A population size of 200 individuals is sufficient for detecting QTL with large effects, especially in high-density maps (Hackett et al. 2014). For a map of this marker density, the TB population of 246 individuals was more than sufficient.
The FEIM model tests the null hypothesis that the additive allelic effects are zero using likelihood ratio tests, versus the alternate hypothesis that there is one QTL present (Pereira et al. 2020). Fixed effect models are appropriate for single-QTL scenarios; however, they offer reduced detection power compared to multiple effect models (Pereira et al. 2020). REMIM is the better model for traits explained by multiple QTL, or linked QTL, and this model produces consistently better results than FEIM (Pereira et al. 2020) by using forward-backward significance thresholds established by score-based genome-wide resampling (Zou et al. 2004).
Both FEIM and REMIM models estimated a single major QTL in the same peak position for mean RF and mean EGRT, and in a nearby position for mean gall severity ratings. We tested both replicates individually and found that both models estimated peak QTL position for RF and EGRT at 57.5 cM (Table 2). The 95% support intervals for these QTL were estimated using the peak LOP (REMIM) and LOD (FEIM) minus constant d, for which we used the widely adopted value d = 1.5 (Pereira et al. 2020; Li 2011; Wu et al. 2021). Confidence could be increased to 98% or more, but the tradeoff is a much broader support interval and therefore less precise position estimates for trait-associated markers.
In summary, we report a single major QTL, qIbMe-4.1, at 57.5 cM on LG 4 of I. batatas explaining 70% of the variation in resistance to M. enterolobii within the ‘Tanzania’ x ‘Beauregard’ mapping population. We observed a 1:1 segregation pattern for resistance based on three parameters (RF, EGRT, and gall severity ratings) and qIbMe-4.1 was detected in approximately the same position by all three measures. This segregation pattern, the presence of a single major QTL, and the allele h detected on ‘Tanzania’ at the peak QTL position all provide strong evidence that M. enterolobii may be controlled by a single locus. Detection of qIbMe-4.1 or associated markers within other populations and germplasm is necessary for validation, as it is possible that there are different genetic bases for resistance. It is possible that ‘Tanzania’ may have acquired its resistance to M. enterolobii through a different evolutionary pathway than other resistant lines, but this has not yet been explored. Validation of qIbMe-4.1 in diverse backgrounds would help to resolve this possibility.