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Literature review: Impact of Chilean needle grass ... - Weeds Australia

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identified as Stipa. neesiana by Dr. J.R. Swallen but also referred to also as “Stipa sp.?”, had 2n = 60. It differed<br />

morphologically from the tetraploid specimens, “but it was not possible to clarify the identification” (Bowden and Senn 1962 p.<br />

1122). According to Moraldo (1986) N. neesiana is tetraploid with 2n = 44.<br />

The lowest known chromosome count <strong>of</strong> a stipoid species is n =10 in a Piptatherum sp. and the highest are n = 41 and n = 48<br />

(Barkworth and Everett 1986). In Stipa (sens. lat.) and Oryzopsis (sens. lat.) the chromosome numbers range from n = 11 to at<br />

least n = 41 (including n = 12, 16, 17, 18, 20, 21, 22, 23, 24, 32, 33, 34, 35), a situation that can be explained by recurrent<br />

amphiploidy, i.e. combinations <strong>of</strong> autopolyploidy (simple doubling <strong>of</strong> the number <strong>of</strong> chromosomes in an individual) and<br />

allopolyploidy (hybridisation <strong>of</strong> diploid and/or polyploid individuals), begining with n = 6 and n = 5 (Johnson 1972). In most<br />

European Stipa species that have been studied 2n = 44 (Tsvelev 1977, Moore 1982), derived through aneuploidy from a primary<br />

basic number <strong>of</strong> 2n = 22 (De Wet 1986). Of other European species, S. capensis Thunb. 2n = 34, 36, S. parviflora Desf. and S.<br />

bromoides (L.) Dörfler 2n = 28, and S. gigantea Link 2n = 96 (Moore 1982, Tsvelev 1984, Moraldo 1986). 2n = 24 in many<br />

Achnatherum spp. (Tsvelev 1977). Among other South American stipoids, 2n = 40 in Jarava plumosa (Spreng.) S.W.L. Jacobs<br />

and J. Everett, 2n = 42 and 44 in J.ichu Ruiz and Pavon and 2n = 40 and 44 in Amelichloa brachychaeta (Godr.) Arriaga and<br />

Barkworth (Bowden and Senn 1962). Of the North American species, 2n = 24 in Piptatherum pungens (Torrey) Dorn, 2n = 44 in<br />

Heterostipa comata (Trin. and Rupr.) Barkworth and 2n = 48 in Oryzopsis asperifolia Michaux and Piptatherum racemosa (Sm.)<br />

Barkworth (Barkworth 2006). Stipa sens. str. has a base number <strong>of</strong> 11, while the base number <strong>of</strong> Acnatherum is unclear but<br />

frequently cited as 11 or 12 (Vásquez and Barkworth 2004).<br />

Among the North American Nassella species, n = 11 in N. pungens E.Desv., n = 16 in N. tenuissima, n = 17 in N. lepida<br />

(Hitchc.) Barkworth, n = 23 in N. tucumana (Parodi) Torres, n = 32 in N. pulchra (Hitchc.) Barkworth, n =35 in N. cernua<br />

(Stebbins and Love) Barkworth and n = 41 in N. viridula (Trin.) Barkworth (Johnson 1972). However N. tenuissima material<br />

from Argentina examined by Bowden and Senn (1962) had a diploid number <strong>of</strong> 40, different from that <strong>of</strong> Texas plants. Of the<br />

South American species, 2n = 34 in N. hyalina, 2n = 36 in N. charruana, 2n = 36 and 38 in N. trichotoma, 2n = 42 in N. chilensis<br />

(Trin.) E. Desv., and N. exserta Phil., 2n = 64 in N. mucronata (Kunth) R.W. Pohl, 2n = 66 in N. lachnophylla (Trin.) Barkworth<br />

(Bowden and Senn 1962). But according to Watson and Dallwitz (2005) 2n = 38 in N. trichotoma.<br />

Genetic variation<br />

Grass species <strong>of</strong>ten possess wide racial or ecoytpic variation within their populations, partial discontinuities <strong>of</strong> phenotypes<br />

resulting from self-fertilisation, hybrid sterility between phenotypically similar populations, and other features, including<br />

polyploidy, that tend to obscure species boundaries (Stebbins 1972). Ecotype variation is known for N. trichotoma in <strong>Australia</strong><br />

(Michalk et al. 2002) but has not been recorded for N. neesiana.<br />

Britt (2001) and Britt et al. (2002) sought evidence <strong>of</strong> genotypic variation in <strong>Australia</strong>n populations. They compared four<br />

Victorian (Altona, Melton, Bacchus Marsh and Tarrawingee) and two New South Wales (Armidale and New England<br />

Tablelands) populations, using three molecular genetic pr<strong>of</strong>iling methods:<br />

1. ITS – RFLP. Internal transcribed spacer - restriction fragment length polymorphism – a method for cutting the DNA at<br />

particular short sequences <strong>of</strong> nucleotides using restriction endonucleases – the polymorphisms in the restriction fragments<br />

are RFLPs and variation in the size <strong>of</strong> the RFLPs is dependent on the particular sequence recognised by each endonuclease.<br />

The ITS is a moderately conserved region <strong>of</strong> nuclear ribosomal DNA, and differences in its length and base pair pattern<br />

have revealed taxonomic patterns in <strong>grass</strong>es and enabled accurate scoring <strong>of</strong> their genotypes (Britt 2001).<br />

2. ITS – PCR sequencing. Using the polymerase chain reaction (PCR) to generate large quantities <strong>of</strong> DNA to enable<br />

sequencing <strong>of</strong> the ITS region.<br />

3. RAPD - PCR. Using PCR and random amplified polymorphic DNA (RAPD) analysis on the whole genome. The technique<br />

allows differentiation <strong>of</strong> closely related organisms or even single base changes by display <strong>of</strong> the DNA banding patterns<br />

using gel electrophoresis.<br />

DNA was extracted from between 18 and 10 plants grown from seeds collected in each geographical area (Britt 2001 p. 21), but<br />

no indication was provided <strong>of</strong> the number <strong>of</strong> individuals sampled from each population, their spatial arrangement in the source<br />

area, or the date <strong>of</strong> sampling (Britt 2001, Britt et al. 2002). The plants from which DNA were extracted were grown from seed<br />

collected in a particular area, but that seed could have been harvested from a single mother plant, and even if multiple mother<br />

plants were sampled a variable proportion <strong>of</strong> the seed from each would be cleistogamous. Thus all the individuals from which<br />

DNA was extracted for a particular area could have been genetically identical because <strong>of</strong> inadequate population sampling.<br />

No variation was found in the size <strong>of</strong> the ITS region (650 base pairs) or in the ITS-RFLP patterns tested. ITS sequencing<br />

revealed uniformity within the plants analysed from a particular area, but differences between plants from different areas,<br />

unrelated to their geographical proximity. All areas had shared homologies above 90%, suggesting conspecificity, except for<br />

Bacchus Marsh and Tarrawingee populations, but no one else appear to have suggested these populations are not N. neesiana.<br />

98% homology – suggestive <strong>of</strong> convarietal status – was shared only by Altona and New England samples (Britt 2001). Jacobs et<br />

al. (2000) also analysed sequence data <strong>of</strong> the ITS region <strong>of</strong> nuclear rDNA and found no variation within the species tested,<br />

however, again, the number and intra-population source <strong>of</strong> their samples were not published. Britt’s (2001) RAPDs showed<br />

inter- but not intra-area variation but no consistent area groupings. Comparison <strong>of</strong> population differences using the two different<br />

methods produced two inconsistent ‘distance tree’ structures. ITS data indicated that the Melton population was most similar to<br />

N. leucotricha (Britt et al. 2002), suggesting the possibility that some hybridisation may be occurring. Jacobs et al. (2000)<br />

indicated that they are sister species.<br />

Britt (2001) and Britt et al. (2002) concluded that <strong>Australia</strong>n N. neesiana possesses large genetic variation between areas (a<br />

number <strong>of</strong> subspecies/varieties – the terms were used interchangably – are present), that this may have arisen locally, and that<br />

local populations have no variation, so must have arisen via cleistogenes or seeds fertilised only by local pollen.The latter<br />

argument is flawed because Britt (2001) failed to demonstrate that the real population variation in each area was sampled. It is<br />

32

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