A. Varsani and others INTRODUCTION Maize streak virus (MSV; family Geminiviridae, genus Mastrevirus) is best known as the causal agent of maize streak disease. Although the geographical range of MSV is largely restricted to subSaharan Africa, its serious impact on food security in the world’s poorest countries ranks it amongst the most important agricultural pathogens globally (Bosque-Perez, 2000). Although a significant degree of MSV diversity has been documented (Dekker et al. 1988; Clarke et al., 1989; Pinner & Markham, 1990; Peterschmitt et al., 1991; Martin et al., 2001; Willment et al., 2001), only one low diversity strain, called MSV-A (McClean, 1947; Storey & McClean, 1930), is responsible for maize streak disease (Pinner et al., 1988; Briddon et al., 1994). MSV-A variants are generally the only viruses sampled from field-collected maize plants presenting with severe streak disease, and the only variants known to cause the disease under laboratory conditions (Martin et al., 2001). Other strains of MSV – called MSV-B to -E, but often collectively referred to as ‘grass-infecting’ or non-maize- adapted MSVs – have only very rarely been isolated from maize plants, and generally only produce very mild symptoms in even the most MSV-sensitive maize geno- types (Pinner et al., 1988; Martin et al., 1999, 2001; Schnippenkoetter et al., 2001; Willment et al. 2002). While this might suggest that these other MSV strains are largely irrelevant to African agriculture, they have been found infecting other cultivated crops such as wheat, rye, barley and oats (Willment et al., 2001). Under laboratory testing conditions, MSV-B and -C are significantly more virulent than MSV-A isolates in wheat and barley (Schnippenkoetter et al., 2001; Willment et al., 2002), suggesting that these viruses may have a substantial, albeit an as yet undetermined, impact on African agriculture. Besides their potential agricultural relevance, the non- maize-adapted MSV strains may hold important clues to the past and ongoing evolution and epidemiology of the maize-adapted MSV-A strain. Given that the most prevalent MSV-A variant in southern Africa – MSV-A4 – is actually a MSV-A/B recombinant (Martin et al., 2001), there is a clear precedent for the non-maize-adapted MSV strains directly contributing via recombination to ongoing MSV-A evolution. More thorough analyses of MSV recombination involving a greater diversity of MSV full- length genomes could, as has been done with other geminiviruses (Lefeuvre et al., 2007b; Prasanna & Rai, 2007), provide a more detailed picture of sequence exchange patterns most commonly associated with evolu- tionary advancement of MSVs. Also, from both an ecological and evolutionary perspective, comparative analyses of geographical and host range distributions of different MSV strains could help identify unique aspects of MSV-A epidemiology that have facilitated its emergence as an important agricultural pathogen. 2064 We therefore undertook a survey of MSV diversity in indigenous uncultivated African grass species. Amongst 83 MSV isolates sampled in West Africa, East Africa, southern Africa and La Re´union, we identified six new MSV strains. We present evidence of extensive inter-strain MSV recombination and identify recombination breakpoint hot- and cold-spots that are partially conserved amongst all geminiviruses. Our analysis reveals significant differ- ences in the natural host and geographical ranges of various MSV strains that may have a bearing on the emergence of MSV-A as a maize pathogen. METHODS Virus sampling. Grasses displaying symptoms characteristic of MSV infection were sampled between 2005 and 2007 from South Africa (n539), Zimbabwe (n51), Mozambique (n54), Nigeria (n59), La Re´union (n58) and Uganda (n57). We also analysed archived samples collected in previous studies between 1986 and 2000 from Nigeria (n53), Burundi (n51) and Rwanda (n51; Pinner et al., 1988; Pinner & Markham, 1990), Mali (n51), Zimbabwe (n52; Peterschmitt et al., 1991) and South Africa (n57; Willment et al., 2001). Only one sample was taken per host species in any given sampling location and different sampling locations were separated by two or more kilometres (see Supplementary Table S1 available in JGV Online for sampling coordinates, dates and host species). Cloning and sequencing of full genomes. Viral genomes were isolated from plant material as described previously (Owor et al., 2007a; Shepherd et al., 2008a). Amplified concatemers were digested with either BamHI, KpnI or SalI to yield ~2.7 kb linearized viral genomes that were ligated into pGEMZf+ (Promega Biotech). Both strands of cloned genomes were commercially sequenced (Macrogen) using the primer set described by Owor et al. (2007a). Host species identification. Host species were identified by chloroplast ndhF gene sequencing. C-terminal encoding portions (~ 1.1 kb) of the ndhF genes were amplified from grass genomic DNA using the PCR primers: 972-F (59-GTCTCAATTGGGTTATA- TGATG-39) and 2110-R (59-CCCCCTAYATATTTGATACCTT- CTCC-39) using Kapa Taq (Kapa Biosystems) described by Olmstead & Sweere (1994) and Giussani et al. (2001). The ndhF amplicons were ligated into pGEM-T Easy (Promega Biotech) and completely sequenced by Macrogen using M13 standard sequencing primers. Sequence analyses. All available African streak virus genome sequences, including those of Urochloa streak virus (Oluwafemi et al., 2008), Eragrostis streak virus (Shepherd et al., 2008b), Panicum streak virus (Briddon et al., 1992; Varsani et al., 2008), Sugar cane streak virus (Hughes et al., 1993; Shepherd et al., 2008b), Sugar cane streak Egypt virus (Bigarre´ et al., 1999) and Sugar cane streak Reunion virus (Bigarre´ et al., 1999; Shepherd et al., 2008b), were obtained from public sequence databases. Sequence alignments were constructed using the POA program (Grasso & Lee, 2004) and edited both by eye and using the CLUSTAL W-based (Thompson et al., 1994) sequence alignment tool implemented in MEGA (version 4; Tamura et al., 2007). MEGA was also used to calculate the pairwise sequence identities shared by aligned genomes using pairwise deletion of gaps. Maximum-likelihood phylogenetic trees were constructed using the PHYML program (Guindon & Gascuel, 2003). The F81+G4 nucleotide substitution model was selected as being the most appropriate for the Journal of General Virology 89