Gauld, 1992). Taxa currently placed in Aphelinidae are primarily parasitoids of aphids, scales and whiteflies (Viggiani, 1984). Encyrtidae are parasitic mostly on non-heteropteran Euhemiptera (Noyes and Hayat, 1994). Eulophidae attack a wide variety of insects, primarily the larval stages of Coleoptera, Lepidoptera and Hymenoptera (Goulet and Huber, 1993). Trichogrammatidae are egg para- sitoids of primarily Hemiptera, but importantly Lepidoptera. While Trichogrammatidae are important for augmentative control measures (Smith, 1996), Aphelinidae, Encyrtidae and Eulophidae are used primarily for the classi- cal biological control of pests such as cassava mealybug, olive scale, citrus black- fly and purple scale (DeBach, 1971).
Chalcidoidea are recognized to contain approximately 21,000 described species, distributed in 19 families and 89 subfamilies (Noyes, 1990; Gibson et al., 1999). Estimates of the number of species range between 60,000 and 400,000 (Noyes, 1978, 1990, 2000; Gordh, 1979). Ecologically and economically, Chalcidoidea are one of the most important groups for control of insect popula- tions (Noyes, 1978; LaSalle, 1993). The importance of Chalcidoidea in agricul- tural systems is unchallenged. They have one of the highest success rates in biological control programmes, in terms of both establishment and control of pest populations. Additionally, because of their high degree of host specificity, Chalcidoidea present the least number of problems from introduced species attacking non-target organisms (Noyes, 1978; Greathead, 1986; LaSalle and Gauld, 1992; LaSalle, 1993; Noyes and Hayat, 1994). Perhaps surprisingly, for 39
©CAB International 2004.Genetics, Evolution and Biological Control (eds L.E. Ehler, R. Sforza and T. Mateille)
such an important group of insects, the taxonomy and classification of the super- family is still unresolved, frequently revised, and largely lacking a consensus in understanding of monophyly at higher taxonomic levels (Gibson et al., 1999). In part, this taxonomic confusion stems from an overwhelming number of unde- scribed species that remain to be collected, curated and compared with existing material, and often the condition of the existing material (LaSalle, 1993). Many cryptic species are known that can be recognized only by their degree of repro- ductive isolation. For biological control, providing correct names is an essential part of any successful programme. Taxonomic identification is usually a cursory assessment based solely upon morphological distinctness, which is often later cor- roborated by information on degree of reproductive isolation or other behav- ioural data. Differentiation of species has also benefited from various molecular methods of analysis, ranging from allozyme profiles to the more recent use of molecular markers such as random amplified fragment polymorphism (RAPD) analysis and restriction fragment length polymorphism (RFLP) analyses (Landry et al., 1993; Vanlerberghe-Masutti, 1994; Antolinet al., 1996; Silva et al., 1999;
Unruh and Woolley, 1999; Zhu and Greenstone, 1999; Zhu et al., 2000).
Furthermore, because of their small size, convergence of morphological traits and the frequent reduction or loss of features, it can be difficult to assess the rela- tionships of species, or even the relationships between genera, with any degree of confidence. Also, the general lack of available hypotheses of relationships for most taxa prevent application of the predictive power of phylogenetic systemat- ics to practical and theoretical aspects of biological control.
Over the past decade there has been a tremendous change in the use and application of molecular methods both for the recognition of species and for understanding the relationships of Hymenoptera. Of specific interest to biologi- cal control are the recent molecular applications within Ichneumonoidea and Chalcidoidea (Noyes and Hayat, 1994); two of the most frequently used groups in classical or augmentative biological control programmes. With the exception of the subfamily Aphidiinae, most of the work in Ichneumonoidea has been focused on the understanding of higher taxonomic relationships (Belshaw and Quicke, 1997, 2002; Gimeno et al., 1997; Belshawet al., 1998, 2001; Dowton and Austin, 1998; Whitfield and Cameron, 1998; Mardulyn and Whitfield, 1999;
Kambhampati et al., 2000; Sanchis et al., 2000; Dowton et al., 2002). Although Chalcidoidea have been included in studies of relationships at the ordinal level (Derr et al., 1992a,b; Dowton and Austin, 1994, 1995, 1998, 2001) and at the superfamily level (Campbell et al., 2000), within this superfamily, there is a much greater emphasis on problems associated with the recognition of species and resolving the relationships between closely related groups of species and genera.
The resolution of the higher-level relationships of these groups is important for understanding major evolutionary events within each group, although it is prob- ably of less direct relevance for biological control programmes, which are focused on populations, species, or at most, closely related groups of species. Unruh and Woolley (1999) provided a comprehensive review of molecular methods and their application to biological control. However, even since 1999, there has been a
40 J. Heraty
general shift to the application of DNA sequencing over other marker-based techniques (i.e. allozymes, RAPD, RFLP). This new emphasis on sequencing over marker-based techniques has allowed for a greater focus on understanding rela- tionships over recognition, and for Chalcidoidea, the importance of understand- ing these relationships within the context of biological control needs to be emphasized.
‘Molecular methods’ refers broadly to techniques used for the recognition of groups of individuals, whether they be populations, species or higher taxonomic groups, and ultimately the understanding of relationships between these different units (Unruh and Woolley, 1999). The term ‘molecular systematics’ is generally reserved for sequencing technology and the comparison of nucleotide strings of known genetic regions (Fig. 3.1). For the recognition of species, unique strings diagnostic for a group are important. For postulating relationships, the possession of derived features shared with a common ancestor (synapomorphies) are most important. In either case, a single mutational event resulting in a nucleotide change in the common ancestor of a group, which subsequently becomes fixed within a lineage, can be applicable to either recognition or relationships.
Subsequent changes at other sites can help to reinforce our concepts, whereas multiple changes at the same sites (homoplasies) can obfuscate our ideas, espe- cially regarding relationships, as these changes become more common. Alone or in combination with morphology or behavioural information, sequence data can be used to develop better phylogenies, classifications and identification keys, which are fundamental to all biological control programmes. Also, the interpre- tation of environmental or behavioural change on a given phylogeny can improve our knowledge of the rate and means of acquiring novel host associa- tions or other adaptations or features that might improve our evaluation of new control agents.
Molecular Systematics 41
Fig. 3.1. General procedure for comparison of DNA sequences leading to the final development of phylogenies, classifications and identification keys, which hinge on the correct assessment of shared homologous features or synapomorphies (boxes).
DNA sequence
Morphology
Phylogeny
Interpretation Classification and keys
Identification
G A Sawfly
Braconid Scelionid Chalcidid Aphelinid
5′ 3′
Genes of interest
The potential array of genetic regions that have been used in molecular studies of insects was reviewed by Simon et al. (1994) and more specifically within the Hymenoptera by Cameron et al. (1992). Of the vast array of possibilities, only a few regions have been used for Chalcidoidea or, for that matter, even insects in general (Caterino et al., 2000). The most commonly used regions involve nuclear or mitochondrial DNA sequences that transcribe for ribosomal sequences or mitochondrial coding genes. Each gene region, or in some cases portions of a region, evolves at different rates, depending on the degree of tolerance for muta- tions before the function of the region is adversely affected. Important consider- ations for choosing a particular gene are the amount of within-site variation (slow or fast evolving) and changes in length of the region by insertion and deletion events, which ultimately affect our ability to align sequences with each other. The latter case really only affects our ability to analyse the data phylogenetically.
Differences in sequence length using specific primers may aid in our ability to discriminate taxa, but only between closely related species where the length dif- ferences are well characterized.
Nuclear genes
The 28S rDNA transcript region that codes for ribosomal RNA is most com- monly sequenced for studies ranging from species recognition to subfamilial rela- tionships with divergence times ranging from 60 to 200 million years ago (MYA) (Cameron et al., 1992). The 28S region is comprised of a series of highly con- served regions and 11 expansion regions. Each expansion region consists of a series of stem (conserved) and loop (variable) regions, which are useful for assess- ing different levels of taxonomic divergence. Typically, the D2 expansion region (600–700 bp) has been used in most analyses, with the more conserved and much shorter D1 and D3 expansion regions (each < 350 bp) used in fewer studies, and usually providing supporting evidence for relationships inferred by the D2 region.
The 18S rDNA region is highly conserved in insects and generally is used for study of ordinal-level relationships with estimated divergence time of 65–250 MYA (Caterino et al., 2000; Wiegmann et al., 2000). However, the 18S-E23 expansion region can be used for support of family and subfamily group rela- tionships in Eucharitidae and Perilampidae (Heraty unpublished; cf. Figs 3.2, 3.4). Ribosomal genes, both nuclear and mitochondrial, have both a secondary and a tertiary structure that affect the rate of change along the gene, with a series of highly conserved stem regions and more rapidly evolving loop regions. Two internal transcribed spacer regions (ITS1 and ITS2) are both 400–600 bp regions located between 18S and 28S and separated by the 5.8S rDNA region. These are transcribed, but non-coding, and therefore typically tolerate a greater rate of mutation than the surrounding regions, with ITS1 expressing a higher rate of change than ITS2. Both regions are applicable for observing change between closely related species; however, differences in length and rapid changes within the region mean that they could be difficult to align beyond closely related species
42 J. Heraty
within a genus. All of the above gene regions usually occur in numerous identi- cal copies within each cell (pleurologous genes) and thus are relatively easy to extract and amplify from single individuals of even the smallest Chalcidoidea.
However, even pleurologous genes can have more than one copy in the same individual, which can complicate the search for homologous changes (i.e. ITS2 in Trichogramma, R. Stouthamer, California, 2002, personal communication). The problem of dealing with this gene duplication (paralogy) and the evolution of gene families (gene trees) that may or may not correspond to the correct phylo- genetic or species tree is well understood (Goodman et al., 1979; Hillis, 1994;
Nelson, 1994). The challenge is to find single-copy (orthologous) nuclear-coding genes of similar utility, or at least to be able to recognize the different copies of a paralogous region. Coding genes are much easier to align between different taxa, and orthologous copies better estimate the phylogeny of the taxa being com- pared (Cameron et al., 1992). Within Hymenoptera, elongation factor 1 (EF-1α, copies F1 and F2; cf. Danforth and Ji, 1998; Danforth, 1999; Rokas et al., 2002), long-wavelength opsin (LW Rh; Mardulyn and Cameron, 1999; Rokas et al., 2002) and phosphoenolpyruvate carboxykinase (PEPCK) and DOPA decarboxy- lase (DDC) (C. Desjardins, Maryland, 2002, personal communication) are poten- tial candidates for exploration.
Mitochondrial genes
Within Chalcidoidea, the 16S rDNA transcript region (~500 bp) has been used only for studies interested in the placement of Chalcidoidea within Hymenoptera (Derr et al., 1992a,b; Dowton and Austin, 1994, 1995, 2001; Dowton et al., 1998).
The 12S rDNA transcript region (~350 bp) was used for analyses at the generic level in Agaonidae (Herre et al., 1996; Machado et al., 1996). Three protein- coding regions have been used, cytochrome b(Cyt b), and cytochrome oxidase I and II (COI, COII) in Chalcidoidea. Cyt b sequences (~800 bp) were used to compare species relationships within Agaonidae (Kerdelhue et al., 1999; Lopez- Vaamonde et al., 2001). The COI and COII gene regions (~1400 and 650 bp, respectively) are used for analysis of various levels of diversification within Chalcidoidea, although usually only about half of each region is used in most analyses. COI is considered to be more conserved and has been used in the analysis of ordinal relationships in Hymenoptera (Dowton and Austin, 2001), although it can be variable enough to be useful at the population level (Scheffer and Grissell, 2003).
There are a few fundamental properties that govern the use and application of each gene region. These properties vary at different taxonomic levels, and importantly at different rates in different taxonomic groups. For understanding relationships at most taxonomic levels, single-copy nuclear genes (excluding introns) are probably the best choice. In the Apocrita, nuclear-coding genes have roughly an equal base composition (equal frequency of the four bases) and their alignment, with only rare insertion or deletion events, is trivial and accomplished with most automated alignment packages. For protein-coding mitochondrial genes, Apocrita have a distinct A–T compositional bias, with greater than 70%
Molecular Systematics 43
of nucleotides either adenine or thymine (Dowton and Austin, 1995, 1997).
Mitochondrial ribosomal genes have the same base compositional bias, but for either genome these are more difficult to align. Ribosomal genes have a second- ary coding structure that can make them relatively easy to align within the con- served stem or loop regions, but difficult or nearly impossible to align without bias in the variable loop regions, which may have both numerous substitutions and multiple insertion and deletion events. These regions can be hypervariable, with unique long insertions that make them difficult to align, especially between diver- gent taxa, and these regions are either subjectively aligned by eye or the ambigu- ous alignment regions are excluded from the analysis (Cameron et al., 1992;
Unruh and Woolley, 1999).