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3 March 2006 A super-family of genes coding for secreted salivary gland proteins from the Hessian fly, Mayetiola destructor
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Abstract

We have previously characterized a gene coding for the secreted-salivary-gland-protein 11A1 (SSGP-11A1) from the Hessian fly,Mayetiola destructor (Say) (Diptera Cecidomyiidae). Here we report the cloning and characterization of three new genes coding for proteins designated SSGP-11B1, SSGP-11C1, and SSGP-11C2, and their relationship with the SSGP-11A1-encoding gene. Based on their structural conservation, similar regulation, and clustered genomic organization, we conclude that the four genes represent a gene superfamily, designated SSGP-11, which originated from a common ancestor. Cloning, Southern blot and in situ hybridization data suggest that each of theSSGP-11 families has multiple members that cluster within short chromosome regions. The presence of a secretion signal peptide, the exclusive expression in the larval stage, and the clustered genomic organization indicate that this superfamily might be important for Hessian fly virulence/avirulence.

INTRODUCTION

The Hessian fly, Mayetiola destructor (Say) (Diptera Cecidomyiidae), is one of the most destructive pests of wheat in Southern Europe, Northern Africa, Central Asia, and North America (Hatchett et al. 1987). Resistance genes in wheat have long been used for controlling this insect (Ratcliff and Hatchett 1997). Host-plant resistance provides an effective, cost-efficient, and environment-friendly way to control many important insect pests (Gracen 1986; Ratcliffe and Hatchett 1997). The challenge for the host-plant resistance strategy is the constant development of new biotypes that can overcome the resistance of deployed genes (Ratcliffe et al. 1994; Ratcliffe et al. 2000). To improve the durability of host-plant resistance, we need to understand how new biotypes arise. At present, little is known about the genetic basis for insect biotype differentiation. Thirty-one resistance genes have been identified and many biotypes have been isolated and are being maintained in laboratory collections of the Hessian fly (Ratcliff and Hatchett 1997; Martin-Sanchez et al. 2003; Williams et al. 2003). The availability of a large collection of host resistance genes and insect biotypes for this insect provides an ideal model system to reveal the genetic basis for biotype differentiation.

Numerous effector proteins from bacterial pathogens have been characterized (Leach et al. 1996; Dent et al. 1997). There is considerable evidence that these effector proteins are essential for microbes to be successful (Bai et al. 2000). Effector proteins that are recognized by specific plant-resistance-gene products and, thus, cause avirulence are designatedAvr proteins (Baker et al. 1997). Pathogenic fungi also secret Avr proteins into plant tissues, but less is known about this process (Orbach et al. 2000).

The Hessian fly interacts with wheat in a typical gene-for-gene specificity (Hatchett and Gallun 1970; Rider et al. 2002). Like pathogens, Hessian fly larvae apparently inject substances into host plants via their salivary glands during feeding (Byers and Gallun 1971;Hatchett et al 1990). Thus the genetic determinants for Hessian fly biotypes could be those genes that encode secreted salivary gland proteins (SSGP) that are injected into host plants. The injected substances could be determinants for Hessian fly virulence and the variations in these substances could be determinants for biotype differentiation. As the first step in determining the relationship between SSGP and virulence/avirulence of specific Hessian fly biotypes, we systematically analyzed the genes coding for SSGP from Hessian fly larvae following an expressed sequence tag (EST) approach. Numerous SSGP-encoding genes have been identified as a result of this analysis (Chen et al. 2004; Liu et al. 2004; Chen et al., unpublished). We previously characterized a gene coding for a small (7.1 kDa) protein designated SSGP-11A1 (Liu et al. 2004). Phylogenetic analysis of SSGP-11A1 together with other putative SSGP revealed that there are three other groups of SSGP that belong to the same sublineage group. The three new groups were named SSGP-11B1, SSGP-11C1, and SSGP-11C2, respectively. Here we report the isolation and characterization of the corresponding genes for these three new groups and their evolutionary relationship with the SSGP-11A1-encoding gene.

MATERIALS AND METHODS

Hessian flies

Insects were from a laboratory colony that originated from insects collected in Ellis County, Kansas (Gagne and Hatchett 1989). Since then, the insects were maintained on susceptible wheat seedlings in environmental chambers at 20° C and 12:12 (L:D) photoperiod. The majority of the insects were biotype GP (Great Plains) although biotypes A, B and others were also found in low frequencies (Harris and Rose 1989).

Library construction, screening, and sequencing

cDNA and BAC library construction, library screening and sequencing were conducted as described previously (Chen et al. 2004; Liu et al. 2004). The nucleotide sequences of genes and cDNAs from this article have been deposited in GenBank under accession nos. AY828552 to AY828563.

RNA isolation and Northern blot analysis

Total RNA was extracted from salivary glands or whole insects using TRI reagentTM (Molecular Research Inc.,  www.mrcgene.com) following the protocol provided by the manufacturer. For Northern blots, equal amounts (5 μg) of total RNA were separated on a 1.2% agarose gel containing formaldehyde and blotted onto GeneScreen membrane (Perkin Elmer, www.perkinelmer.com). The membrane was incubated at 80° C for two hours. Hybridization and washing conditions are the same as described elsewhere (Liu et al. 2004). For dot blot analysis, 2.5 μg of total RNA was used for each sample.

Sequence analysis

Open-Reading-Frame (ORF) and sequence similarity analysis were performed using ORF finder and various BLAST programs on the website ( http://www.ncbi.nlm.nih.gov/) of the National Center for Biotechnology Information (Bethesda, MD). Analysis for secretion signal peptides was carried out using SignalP (Center for Biological Sequence Analysis, Technical University of Denmark,  http://www.cbs.dtu.dk/services/SignalP/) and PSORT II analysis (Prediction of Protein Sorting Signals and Localization Sites in Amino Acid Sequences,  http://psort.nibb.ac.jp/). Molecular weight calculations and pI prediction of mature proteins were carried out using the