Genetic diversity and structure of Lolium perenne ssp. multiflorum in California vineyards and orchards indicate potential for spread of herbicide resistance via gene flow

Abstract

Management of agroecosystems with herbicides imposes strong selection pressures on weedy plants leading to the evolution of resistance against those herbicides. Resistance to glyphosate in populations of Lolium perenne L. ssp. multiflorum is increasingly common in California, USA, causing economic losses and the loss of effective management tools. To gain insights into the recent evolution of glyphosate resistance in L. perenne in perennial cropping systems of northwest California and to inform management, we investigated the frequency of glyphosate resistance and the genetic diversity and structure of 14 populations. The sampled populations contained frequencies of resistant plants ranging from 10% to 89%. Analyses of neutral genetic variation using microsatellite markers indicated very high genetic diversity within all populations regardless of resistance frequency. Genetic variation was distributed predominantly among individuals within populations rather than among populations or sampled counties, as would be expected for a wide-ranging outcrossing weed species. Bayesian clustering analysis provided evidence of population structuring with extensive admixture between two genetic clusters or gene pools. High genetic diversity and admixture, and low differentiation between populations, strongly suggest the potential for spread of resistance through gene flow and the need for management that limits seed and pollen dispersal in L. perenne.

Keywords: Italian ryegrass; Lolium perenne ssp. multiflorum; agricultural weed; glyphosate; glyphosate resistance; herbicide; microsatellite markers.

Figure 1

Geographic distribution of the populations sampled for this study in northwest California. Circles indicate the proportion of glyphosate‐resistant (black) and glyphosate‐susceptible (gray) individuals in each population, based on glasshouse screening of plants grown from field‐collected seeds. Numbers are the population IDs (see Table 1)

Figure 2

Principal coordinate analysis (PCoA) of pairwise genetic distances between populations. The first two axes explain 32.2% and 19.1% of genetic variation

Figure 3

Bayesian clustering analysis (STRUCTURE, Pritchard et al., 2000) of Lolium perenne plots of (a, c, e) the log likelihood ln P[D] for five runs at each value of K, and (b, d, f) the second order of change in ln P[D], ΔK, as a function of the number of clusters or gene pools, K, from the analysis of all samples (a, b) and subclustering analysis of individuals assigning with q > 0.6 to cluster 1 (c, d) and to cluster 2 (e, f) within the global analysis

Figure 4

Assignment of 412 individuals of L. perenne ssp. multiflorum to the genetic clusters inferred by Bayesian clustering analysis (STRUCTURE). Each vertical bar corresponds to a distinct individual and its probability of assignment, q, to each cluster. (a) K = 2, the most likely number of genetic clusters for the global data set, (b) K = 3, the most likely number of subclusters among individuals assigning with q > 0.6 to cluster 1, and (c) K = 4, the most likely number of subclusters among individuals assigning with q > 0.6 to cluster 2