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A sodium azide-mutagenized population of barley (cv. ‘Morex’) was developed and utilized to identify mutants at target genes using the ‘targeting induced local lesions in genomes’ (TILLING) procedure. Screening for mutations at four agronomically important genes (HvCO1, Rpg1, eIF4E and NR) identified a total of 22 new mutant alleles, equivalent to the extrapolated rate of one mutation every 374 kb. All mutations except one were G/C to A/T transitions and several (approximately 68%) implied a change in protein amino acid sequence and therefore a possible effect on phenotype. The high rate of mutation detected through TILLING is in keeping with the high frequency (32.7%) of variant phenotypes observed amongst the M3 families. Our results indicate the feasibility of using this resource for both reverse and forward genetics approaches to investigate gene function in barley and related crops.
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Barley (Hordeum vulgare L.) is one of the most important cereal crops and, despite its large genome (more than 5000 Mb; Bennett and Smith, 1976), can be considered a model species for more complex genomes, such as those of polyploid durum and bread wheat. Although a large repertoire of genetics and genomics resources are available in barley (Close et al., 2004; Varshney et al., 2007a), the production of information on gene function on a large scale remains a challenging task. Data based on patterns of differential gene expression (e.g. microarrays) may contribute to the categorization of genes, but are not sufficient for the assignment of gene function. Gene inactivation by insertional mutagenesis, based on transposons or T-DNA (Singh et al., 2006; Zhao et al., 2006) and RNA interference (Douchkov et al., 2005), is currently under development in barley. These strategies, however, suffer from the controversy of growing transgenics in open fields. Thus, the implementation of rapid and high-throughput methods for the confirmation and validation of gene function is a recognized priority.
‘Targeting induced local lesions in genomes’ (TILLING) is a reverse genetics technique enabling the recovery of individuals carrying allelic variants at candidate genes (McCallum et al., 2000; Till et al., 2007a). TILLING requires the production of a mutagenized population, the polymerase chain reaction (PCR) amplification of a target gene in pools of individual DNAs of such a population, and a biochemical assay (using mismatch-specific endonucleases) for the recognition of the plants carrying the mutant allele. TILLING can be applied to both chemically mutagenized populations and collections of genotypes (e.g. cultivars, collection of ecotypes, landraces, wild accessions, etc.), an approach known as EcoTILLING (Comai et al., 2004). Since its introduction in Arabidopsis (McCallum et al., 2000), TILLING has been applied in Lotus (Perry et al., 2003), maize (Till et al., 2004), wheat (Slade et al., 2005), rice (Suzuki et al., 2007; Till et al., 2007b), pea (Triques et al., 2007), zebrafish (Wienholds et al., 2003), rat (Smits et al., 2004), Drosophila (Winkler et al. 2005) and Caenorhabditis (Gilchrist et al. 2006), and is underway in a number of other species (Gilchrist and Haughn, 2005). In barley, a TILLING resource has already been generated using ethylmethanesulphonate (EMS) chemical mutagenesis of Optic, a European two-row malting variety (Caldwell et al., 2004). In this study, TILLMore, a new TILLING resource in barley obtained from the chemical mutagenic treatment of seeds of cv. Morex with sodium azide (NaN3), is described, and its first reverse genetics implementation is evaluated.
The mutagenized population for TILLMore
In order to gain information on the toxicity and/or lethality of NaN3 treatment and to predict its actual mutagenicity, M1 plants derived from seed treated with different NaN3 concentrations were scored for seed germination, reduction of coleoptile length, frequency of leaf chimeras and fertility of M1 ears. The samples treated with 1, 5 and 10 mm NaN3 showed germination rates of 85.0%, 82.5% and 81.3%, respectively, whereas the untreated control displayed 95.8% germination. All NaN3 concentrations significantly reduced germination when compared with the control (P < 0.05); however, the germination rates at the three concentrations did not show significant differences. The two highest NaN3 concentrations (5 and 10 mm) significantly reduced (P < 0.05) the coleoptile length (–36% and –42%, respectively), increased the frequency of foliar chimeras (36- and 42-fold, respectively) and decreased the fertility of M1 ears (–32% and –48%, respectively), with respect to untreated Morex (Figure 1). On the basis of these results, it was concluded that the 10 mm treatment would guarantee the highest mutation density whilst causing an acceptable level of toxic/lethal effects. Therefore, to create TILLMore, the set of plants treated with 10 mm NaN3 was processed further.
To prevent redundancy of mutations (i.e. the presence of multiple plants carrying the same mutation, and therefore hindering the efficiency of the allele recovering process), a single M2 seed was harvested for each M1 plant. The M2 population was subsequently grown in the field to allow for leaf DNA sampling and seed increase. A total of approximately 5600 M2 plants reached maturity. A further generation was carried out to increase the amount of stock DNA and seed for each family. For 4906 families (the current dimension of the TILLMore resource), it was eventually possible to prepare suitable DNA for molecular screening and to obtain at least 100 M3 and/or M4 seeds for stock purposes.
TILLMore reverse genetics screening
For molecular screening, a CelI-based heteroduplex assay was used, coupled with gel electrophoresis on DNA sequencers (an example of gel electrophoresis is provided in Figure 2); 3148 DNA samples from individual M2 plants were utilized, and mutations were screened in eightfold sample pools using 96-well format plates. To date, TILLMore has been screened with assays designed on four genes: eukaryotic translation initiation factor 4E (eIF4E), Hordeum vulgare Constans-like 1 (HvCO1), nitrate reductase (NR) and barley stem rust resistance protein gene 1 (Rpg1). With the exception of eIF4E, PCR primers were designed to yield amplicons as close as possible to 1 kb (Table 1).
Table 1. Genes targeted within TILLMore and number of mutations identified
The TILLMore mutation density was estimated by dividing the total number of identified mutations by the number of base pairs screened (the cumulative length of the four amplicons multiplied by the number of samples). As observed previously (Greene et al., 2003), mutations can escape identification when placed in the terminal 80 bp of both ends of the amplicon as a result of PCR priming and electrophoresis artefacts. A correction on the effective screening window can be applied by subtracting 160 bp from the length of each amplicon (Greene et al., 2003). Applying such a correction, the mutation density is estimated as 22 mutations/(2613 bp × 3148 individuals), i.e. one mutation per 374 kb screened.
The molecular screening identified an allelic series for each tilled gene (Table 1), with an average of approximately six alleles per gene. This clearly represents an underestimation of the TILLMore potential to provide mutated alleles for a target gene, because the screening was performed on a portion of the mutagenized population (approximately 65% of the whole population), and because, for one gene (eIF4E), the amplicon was about half of the ideal length. Based on the mutation density observed (one per 374 kb) and extrapolating to the whole population of 4906 lines, the expected mean number of alleles per 0.84 kb of effectively tilled amplicon should be approximately 11.
A total of 22 point mutations was identified for the four target genes. In three cases, the mutations were in non-coding regions (some non-coding regions are included in PCR amplicons because of constraints in primer design). Of the 19 mutations identified in coding regions, 32% were predicted to be silent, because they affected the third base of a codon which does not change the amino acid encoded by that codon; 68% were classified as mis-sense alleles, causing changes in one of the amino acids in the protein (Table 1). No non-sense (truncation) alleles were identified for the tested genes. Of the 22 mutations, 21 were G/C to A/T transitions, and one was a C/G to A/T transversion. Because a previous study has proposed that NaN3 causes mutations of transition type (Olsen et al., 1993), and because all but one of our mutations were G/C to A/T transitions, the possibility that the polymorphisms identified in TILLMore are naturally occurring as a result of seed contamination of our starting Morex seed stock can be ruled out.
Fifteen homozygous mutations and seven heterozygous mutations were identified. This is a higher than expected (χ2 test, P < 0.01) rate of homozygous over heterozygous mutations (expected to be 1 : 2 for M2 plants). The higher proportion of homozygous mutant plants was probably caused by a sensitivity limitation in our molecular screening, which may have hindered the detection of some heterozygous samples. Indeed, heterozygous mutations are diluted 16-fold in DNA pools from eight diploid individuals, twice as large as that observed for homozygous mutations. This observation also indicates a slight underestimation of the actual mutation density.
A closer analysis of the 15 mis-sense mutations revealed that four were unlikely to cause any phenotypic effect as they produced amino acid substitutions with similar charge and polarity. Bioinformatic methods can also be applied to estimate the impact of mutations on protein function. Two such methods, sift and parsesnp (Ng and Henikoff, 2001; Taylor and Greene, 2003), were applied. sift or position-specific scoring matrix (PSSM; for parsesnp) values above specific thresholds should indicate mis-sense mutations which are more likely to have a deleterious effect on protein function. In our case, the mutations HvCO1 3252 and NR 294 showed PSSM values of 14.5 and 13.5, respectively (mutations are considered to be deleterious for PSSM values above 10). The application of the sift algorithm predicted a possible deleterious effect for mutation HvCO1 3252 only (sift value for HvCO1 3252 of 0.08; mutations are predicted to be deleterious for sift values below 0.05 or even below 0.10; Greene et al., 2003). Because both methods rank the effects of mis-sense mutations on the basis of the conservation of amino acids within protein families, the reliability of the predictions is dependent intrinsically on the gene (e.g. the gene belongs to a family with few members) and on the information available in the databases used by the programs, and therefore the results should be considered as indicative. Nevertheless, these approaches can at least provide a means to prioritize mutations for further analysis. Following these indications, collaborative research is in progress to investigate the possible phenotypic effects of some of the mutant lines identified through TILLMore.
TILLMore forward genetics screening
To assess the usefulness of our barley mutagenized population for forward genetics studies, the 4906 M3 families were grown in the field and repeatedly evaluated during the growing season to annotate and record the phenotypic differences with reference to untreated Morex plants. Phenotypes were organized into the following categories: surface wax coating; habitus; heading date; leaf morphology; necrotic spots; tillering; plant colour; plant height; plant morphology; and ear appearance (Table 2). Eventually, 32.7% (1605 of 4906) of the M3 families showed a distinct phenotype, either fixed or segregating within the plot. Changes in plant colour, including families showing segregation for albino seedlings, were the phenotypes most frequently observed (27% of mutated families; 12% of total families). For necrotic and ear morphology categories, a detailed photographic documentation was collected (an example is shown in Figure 3). An on-line database with further information on the phenotypes observed in the forward genetics screening is publicly accessible at http://www.distagenomics.unibo.it/TILLMore/, and seed is available on request.
Table 2. Summary of phenotypic screening
Mutants (% mutants)
Mutants (% population)
Surface wax coating
The increasing speed with which DNA sequence data are being acquired in different species indicates that functional genomics will increasingly become a major limiting factor in plant genetics and breeding. Accordingly, new functional genomics tools should be integrated as much as possible with extant genomics resources and platforms. On the basis of these considerations, Morex was chosen as the barley cultivar for the new TILLING resource TILLMore. Currently, Morex is the barley cultivar with the largest list of genomics resources and information available, including bacterial artificial chromosome (BAC) libraries (Yu et al., 2000), high-density genetic maps (Wenzl et al., 2006; Varshney et al., 2007b), extensive transcriptional genomics data (Druka et al., 2006) and proof-of-concept preliminary genome sequencing (Wicker et al., 2006). An anchored physical map as a prerequisite to genome sequencing is also underway (Stein, 2007). In addition, Morex is a malting industry cultivar standard, therefore providing an opportunity for gene function analysis directly in an elite breeding context.
TILLING populations in plants have been produced using EMS, N-methyl-N-nitrosourea (MNU), diepoxybutane, NaN3 or mixtures of these chemicals as mutagenic agents. TILLMore is the first TILLING resource developed using NaN3 as the only mutagen. NaN3 has long been known to be a respiratory inhibitor, and its ability to produce a high frequency of point mutations and low frequency of chromosome aberrations in barley has been well documented (Nilan et al., 1973; Owais and Kleinhofs, 1988). The mutagenic effect of NaN3 is a result of its metabolic activation into a mutagenic compound (Kleinhofs et al., 1974; Owais and Kleinhofs, 1988), and this is probably the key to its variable mutagenic efficacy across species, which is relatively low in Arabidopsis (Gichner and Veleminsky, 1977), Drosophila (Kamra and Gallopudi, 1979) and mammals (Arenaz et al., 1989). A desirable feature of a mutagenic agent should be the low level of cell toxicity. A mutagen with high cell toxicity will decrease the germination ability and seedling viability to unacceptable levels without reaching sufficiently high mutation density in the surviving plants, as observed in rice when treated with EMS and MNU for example (Wu et al., 2005; Till et al., 2007b). Although an appropriate experiment to obtain a titration (killing) curve was not carried out, our results empirically confirmed that, by NaN3 mutagenic treatment, a mutation density compatible with high-efficiency TILLING can be reached without decreasing the germination ability (only about 20% of seed did not germinate at the highest NaN3 concentration), viability and fertility (in our experiments, the sterility of M1 ears did not decrease below 50% of the untreated control) of M1 barley plants. Similar mild effects of NaN3 on germination have been observed previously (Nilan et al., 1975). Ilbas et al. (2005) even observed a recovery to almost full germination if seeds were allowed to grow for a 2-week period compared with that recorded after 1 week. Because of these observations and the low toxicity of NaN3 for human health, we strongly encourage its use for the production of new TILLING resources in barley and cereals.
The mutation density estimated in our study (approximately one mutation per 374 kb) suggests the suitability of TILLMore for high-throughput reverse genetics, as it is well within the range of the currently screened TILLING resources in diploid species. For comparison, the Arabidopsis ATP team efficiently tills by exploiting a mutation density of one per 170 kb (Greene et al., 2003), and rice is being tilled with mutation densities from one per 265 kb to one per 294 kb (Till et al., 2007b) up to one per 135 kb (Suzuki et al., 2007); maize is tilled at approximately one mutation per 400 kb (Till et al., 2004). Furthermore, the TILLMore mutation density appears to be higher than that (approximately one mutation per 1000 kb) reported in barley by Caldwell et al. (2004) for cv. Optic. For the latter comparison, it would be interesting to determine whether the difference is a result of the random variation between experiments, the different mutagens, the different genetic backgrounds or another cause and/or interaction. As expected, TILLMore scored a lower mutation density than those reported for hexaploid (one per 24 kb) and tetraploid (one per 40 kb) wheat. Such extremely high values are believed to be the result of the buffering effect against lethal mutations provided by polyploidy (Slade et al., 2005).
All four genes screened yielded an allelic series of mutants, and all mutations but one were G/C to A/T transitions. Although a base transition mechanism has been postulated to explain the mutagenic effect of NaN3 (Kleinhofs et al., 1978), the exact nature of NaN3-derived mutants has not been exhaustively described in terms of nucleotide change typology. To our knowledge, to date only one study investigating the nucleotide changes induced by NaN3 in barley has been published (Olsen et al., 1993). These authors analysed the barley Ant18 gene and four of its NaN3-induced mutant alleles to determine the base changes elicited. The analysis revealed 21 base substitutions, 86% of which were transitions of both types. Although limited to only a few genes, our results, combined with those reported by Olsen et al. (1993), suggest that barley NaN3-induced sequence alterations are mainly transitions.
As more than 30% of families of the TILLMore population showed a visible phenotype when observed during a single year in field plots, this population provides a means to identify interesting phenotypes at target traits (e.g. root architecture; R. Bovina, V. Talamè, S. Salvi, M.C. Sanguineti, R. Tuberosa, unpubl. data), which can then be molecularly dissected using forward genetics approaches such as positional cloning (Tuberosa and Salvi, 2006).
Irrespective of the use of TILLMore plant material within a forward or reverse genetics context, the high mutation load carried by each individual TILLMore plant should be duly considered. Based on an average coding space of approximately 1 kb per barley gene, and 50 000 genes in the barley genome, the coding space covers approximately 50 × 106 bp. Furthermore, approximately 75% of point mutations in coding regions cause amino acid substitutions (Lynch, 2007). Disregarding the cases in which two or more independent mutations are present within the same gene, a mutation density of one per 374 kb would then correspond to approximately 262 mutations in coding regions, and to approximately 197 genes harbouring one amino acid substitution, per diploid barley genome (plant) within TILLMore.
In addition to being a well-established reverse genetics technique, TILLING has been proposed as a tool for the identification of new alleles, which can be directly useful in plant breeding (Slade et al., 2005; Waugh et al., 2006). Accordingly, fewer than 2000 wheat plants were successfully screened for mutations in a gene involved in starch production, and a new (null) allele potentially useful for breeding purposes towards specific industrial processing needs was identified amongst hundreds of other mutant alleles of the same gene (Slade et al., 2005). This effort took advantage of the very high mutation density obtainable in polyploid wheat. However, because of the lower mutation density observed in diploid crop species, a population of several tens of thousands of mutagenized plants should be screened in order to identify a comparable number of new alleles, and to guarantee the identification of specific knockout or knockdown alleles (if these allele types are predicted to provide a useful phenotype). Of course, the identification of new, amino acid-specific, gain-of-function mutations is even more unlikely. Therefore, for the purpose of identifying new, valuable, breeding alleles in a diploid species, the production of a very large TILLING population and/or the integration of different TILLING populations (as may already be the case for barley) and, if possible, the improvement of mutagenic protocols to allow a higher mutation density appear to be advisable.
TILLING has already been proven to be a useful technique for functional genomics in several species. This report describes TILLMore, a new TILLING resource in barley based on a mutagenized population derived from cv. Morex. The use of NaN3 provided an efficient alternative to the more commonly employed mutagenic agents to obtain a high mutation density suitable for TILLING. In addition, the high frequency of visible phenotypes makes this population useful for forward genetics screening. TILLMore should efficiently complement existing functional genomics resources within the cereal research community, and help us to move closer to a more tangible impact of TILLING on breeding programmes.
Mutagenesis and production of the population for TILLING
Seeds of barley (Hordeum vulgare L.) cv. Morex were used for the mutagenesis experiment. Three batches of approximately 20 000 seeds each were treated with different concentrations of NaN3 following published protocols (Nilan et al., 1973), with minor modifications. Briefly, the seeds were imbibed in deionised H2O (dH2O) for 16 h at 4 °C in 5-cm-deep trays, one batch of seeds per tray. The seeds were then transferred for 4 h at 20 °C. After discarding the dH2O, the three batches were treated with 1, 5 or 10 mm NaN3 (Sigma-Aldrich, S2002; St. Louis, MO, USA) in 2 L per batch of 0.1 m phosphate buffer, pH 3, for 2 h at 20 °C, applying gentle shaking to allow for aeration. Following NaN3 treatment, the seeds were washed for 1 h in tap water, stored at 4 °C for 12 h, and then planted directly in the field. For the 10-mm NaN3 set, two fields of approximately 9000 M1 plants each were grown, and the plants were allowed to self-pollinate. One M2 seed per M1 plant was collected from one field only, and planted to produce the M2 population for DNA extraction and TILLMore production. Seed and DNA were eventually obtained for 4906 M3/4 families. M2 seeds from the second 10-mm NaN3 field were stored for future needs.
Evaluation of the effects of mutagenic treatment on the M1 generation
Early indications of the mutagenic effect of the three NaN3 concentrations were obtained by measuring the germination of M1 seed, the length of the coleoptiles of M1 seedlings, the frequency of foliar chimeras and the fertility of M1 plants. The effect on seed germination was assessed by planting 100 seeds in shallow trays filled with sand (three replications per NaN3 concentration), and growing them for 8 days at 20 °C in the dark 5 days after mutagenesis. The length (mm) of coleoptiles was measured for approximately 100 M1 seedlings per concentration, grown in Petri dishes in the dark at 20 °C. The frequency of sectorial leaf chimeras was measured as the number of plants showing at least one leaf chimera (white or yellow visible sector) over a random sample (700 plants) of contiguous M1 plants in the field. The fertility of M1 ears was evaluated by considering the number of M2 grains per ear in a random sample of 100 M1 ears per NaN3 concentration. Untreated Morex (seed, seedlings or plants) was always included as a control. Fisher's least significant difference (LSD) tests with Bonferroni correction for multiple comparisons were carried out to test for the presence of significant differences between NaN3 concentrations in seed germination, coleoptile length and fertility of the M1 plants; χ2 tests were used for the frequency of foliar chimeras.
Genomic DNA isolation
Leaf tissue samples were collected from M2 plants at the tillering stage. Approximately 2-cm2 leaf portions (corresponding to about 20–30 mg dry weight) were collected in single tubes in a 96-well format (Cluster tubes; Simport Plastics Ltd., Beloeil, QC, Canada) and immediately lyophilized. Dried samples were ground using a Mixer-Mill (Retsch MM300; Qiagen GmbH, Hilden, Germany) for 3 min at 30 agitations/s with a 4-mm-diameter Inox sphere, and DNA isolation was performed following a standard cetyltrimethylammonium bromide (CTAB) protocol (Saghai-Maroof et al., 1984). Aliquots of genomic DNA were separated on 0.8% agarose gel to check for yield and variability of the DNA preparation. Genomic DNA was diluted to a concentration of 30 ng/µL and used for serial dilution stocks of 10 and 2.5 ng/µL; 3148 DNA samples from the current TILLMore population of 4906 were utilized for mutation screening.
DNA samples from individual plants were pooled fourfold and then combined to obtain eightfold pools; 3148 individual DNA samples were eventually included in five 96-well plates. Two positive controls were prepared by mixing DNA isolated from HOR1 1508, an accession of H. vulgare ssp. spontaneum (kindly provided by A. Börner, IPK, Gatersleben, Germany), with Morex DNA in different proportions (1 : 1 and 1 : 7 v/v), and included on each plate. Primers were designed on the basis of the Morex genomic sequence. For Rpg1 (GenBank accession number AF509748), Primer3 (http://frodo.wi.mit.edu//cgi-bin/primer3/primer3_www.cgi) was used. For HvCO1 (GenBank accession number AF490468) and NR (GenBank accession number X57845), primers were designed with CODDLE (http://www.proweb.org/coddle), selecting ‘TILLING w/EMS (plants)’ as the mutation method as an NaN3 option was not available. For eIF4E (GenBank accession number AY661558), the primer design was based on previous information on protein domain function (N. Stein, IPK, Gatersleben personal communication). The following primer sequences were used for PCR and sequencing of the population and putative mutants: Rpg1_F, CGAAGGATGGTGATGAAGGT; Rpg1_R, GCACCTGTTTTGTGTGATGG; HvCO1_F, GCAAGTCACAAGGCCACCTT; HvCO1_R, GCTGTTGTTGACGGAATCTG; NR_F, GGTGCGCACGTGGGATCAGA; NR_R, GCGCTGCTTGCCGTTGATGA; eIF4E_F, GCCGTCGCCAGCTCTCATCCG; eIF4E_R, TTCACCACATGGACGACAATC. PCR amplification was carried out in a 15-µL volume containing 7.5 ng of pooled DNA, 0.5 × ExTaq buffer (including 1 mm MgCl), 0.8 mm MgCl2, 0.2 mm deoxynucleoside triphosphates (dNTPs), 0.3 µm primers and 0.4 U ExTaq DNA polymerase (Takara Biomedicals, Cambrex Biosciences, Wokingham, UK). PCR cycling was performed as described in Colbert et al. (2001). After PCR amplification, the samples were treated according to the manufacturer's directions for the Surveyor® Mutation Detection Kit for agarose gel (Transgenomics Inc., Omaha, NE, USA), and according to the protocol described in Colbert et al. (2001). Briefly, 10 µL of a PCR product were added to 20 µL of a solution containing 10 mm N-2-hydroxyethylpiperazine-N′-2-ethanesulphonic acid (HEPES), pH 7.5, 10 mm MgSO4, 10 mm KCl, 0.002% (w/v) Triton X-100, 20 ng/mL of bovine serum albumin and 0.25 µL CelI Surveyor Nuclease, and incubated at 45 °C for 15 min. The reactions were stopped by the addition of 10 µL of ethylenediaminetetraacetic acid (EDTA) (150 mm), and purified with the Qiagen DyeEx 96 Kit (Qiagen GmbH, Hilden, Germany), according to the manufacturer's directions, on a plate containing 2 µL of formamide loading buffer (1 mm EDTA, pH 8 and 200 µg/mL of bromophenol blue in deionized formamide). The samples were reduced to a minimum volume, denatured by incubation at 96 °C (20–30 min), stored on ice and loaded on to 96-tooth membrane combs (LI-COR membrane combs and dipping tray; LI-COR Biosciences, Lincoln, NE, USA). Electrophoresis was performed through a 6.5% polyacrylamide, 7 m urea gel in 0.8 × Tris-Borate-EDTA running buffer at settings of 1500 V, 40 mA and 40 W on a LI-COR gel analyser (LI-COR 4200). Images were analysed visually for the presence of cleavage products using Adobe Photoshop software (Adobe Systems Inc., San José, CA, USA). Positive bulks were then analysed for single mutant identification following the same procedure as described for bulk analysis.
To reconfirm the presumptive mutants, genomic DNA from DNA stocks of the positive samples was used as a template for sequencing. Cycle sequencing was performed using an ABI BigDye Terminator V1.1 Cycle Sequencing Kit (Applied Biosystems, Foster City, CA, USA). Reactions were cleaned up using the Qiagen DyeEx Kit, according to the manufacturer's directions, and subsequently analysed on an ABI 377 DNA Sequencer (Applied Biosystems). The sequences of mutant alleles were analysed using sift (Ng and Henikoff, 2001) and parsesnp (Taylor and Greene, 2003) programs in order to rank the mutations on the basis of their probability of affecting protein function.
Forward genetics screening
The entire population of 4906 M3 families was field grown in plots of 30 plants per family, and repeatedly scored for visible phenotypes with reference to untreated Morex. Phenotypic data were collected for plant habitus, morphology and appearance, presence of leaf necrosis, heading date, ear morphology and floret appearance. All data have been registered into a database publicly available at the following website: http://www.distagenomics.unibo.it/TILLMore/. M4 seeds were collected and catalogued at the University of Bologna, where they represent the TILLMore seed resource.
Availability of the resource
The TILLMore resource, including both the TILLING platform and the mutagenized population, is available to the research community at a fully costed recovery basis or, eventually, through collaborations. The TILLMore website is http://www.distagenomics.unibo.it/TILLMore/.
We would like to thank Luca Comai and Bradley Till for helpful discussions and advice, and Sandra Stefanelli and Elena Govoni for technical assistance. This work was supported by FIRB-Ministry of Research and University, Italy.