Plant Biotechnology Journal (2013) 11, pp. 279–295
doi: 10.1111/pbi.12009
Discovery and development of exome-based, co-dominant
single nucleotide polymorphism markers in hexaploid
wheat (Triticum aestivum L.)
Alexandra M. Allen1,*, Gary L. A. Barker1, Paul Wilkinson1, Amanda Burridge1, Mark Winfield1, Jane Coghill1,
Cristobal Uauy2, Simon Griffiths2, Peter Jack3, Simon Berry4, Peter Werner5, James P. E. Melichar6, Jane McDougall7,
Rhian Gwilliam7, Phil Robinson7 and Keith J. Edwards1
1
School of Biological Sciences, University of Bristol, Bristol, UK
2
John Innes Centre, Norwich, UK
3
RAGT, Ickleton, Essex, UK
4
Limagrain, Woolpit, Suffolk, UK
5
KWS, Thriplow, Hertfordshire, UK
6
Syngenta Seeds Ltd, Whittlesford, Cambridge, UK
7
KBioscience Unit 7, Hertfordshire, UK
Received 20 April 2012;
revised 6 August 2012;
accepted 10 August 2012.
*Correspondence (Tel 44 117 331 6770;
fax 44 117 925 7374;
email [email protected])
Keywords: wheat, next-generation
sequencing, KASPar genotyping, single
nucleotide polymorphism.
Summary
Globally, wheat is the most widely grown crop and one of the three most important crops for
human and livestock feed. However, the complex nature of the wheat genome has, until
recently, resulted in a lack of single nucleotide polymorphism (SNP)-based molecular markers of
practical use to wheat breeders. Recently, large numbers of SNP-based wheat markers have been
made available via the use of next-generation sequencing combined with a variety of genotyping
platforms. However, many of these markers and platforms have difficulty distinguishing between
heterozygote and homozygote individuals and are therefore of limited use to wheat breeders
carrying out commercial-scale breeding programmes. To identify exome-based co-dominant
SNP-based assays, which are capable of distinguishing between heterozygotes and homozygotes, we have used targeted re-sequencing of the wheat exome to generate large amounts of
genomic sequences from eight varieties. Using a bioinformatics approach, these sequences have
been used to identify 95 266 putative single nucleotide polymorphisms, of which 10 251 were
classified as being putatively co-dominant. Validation of a subset of these putative co-dominant
markers confirmed that 96% were true polymorphisms and 65% were co-dominant SNP assays.
The new co-dominant markers described here are capable of genotypic classification of a
segregating locus in polyploid wheat and can be used on a variety of genotyping platforms; as
such, they represent a powerful tool for wheat breeders. These markers and related information
have been made publically available on an interactive web-based database to facilitate their use
on genotyping programmes worldwide.
Introduction
Bread wheat (Triticum aestivum) is an allohexaploid (AABBDD)
crop derived from the hybridisation of the diploid genome of
Aegilops tauschii (DD) with the AABB tetraploid genome of
Triticum turgidum (Dubcovsky and Dvorak, 2007). These hybridisation events, the domestication process and the inbreeding
nature of wheat have together resulted in a reduced level of
genetic diversity between cultivated wheat varieties, when
compared with their wild ancestors (Haudry et al., 2007). Wheat
breeders and geneticists require tools to exploit the genetic
diversity available within germplasm collections and carry out
breeding programmes, which utilise this diversity to maximum
effect. Molecular markers enable breeders and geneticists to carry
out this process; however, in allohexaploid wheat, the development of molecular markers has, until recently, been problematic
due to the presence of homoeologous and paralogous copies of
the various genes (Kaur et al., 2012). Recent advances in
genotyping platforms have built upon the wealth of data
provided by next-generation sequencing (NGS) technologies to
enable, for the first time, the large-scale identification, validation
and application of molecular markers in wheat breeding programmes (Berkman et al., 2012; Paux et al., 2011). These
developments have come at a critical time, where the need for
a substantial increase in yields to feed a growing global
population has coincided with reduced genetic gains and
increasing climatic and environmental pressures (Dixon et al.,
2009; Reynolds et al., 2009).
Many of the recently developed genotyping platforms rely on
the identification of single nucleotide polymorphisms (SNPs),
which are polymorphic between different wheat varieties (Paux
et al., 2011). To overcome the various bottlenecks and problems
associated with SNP generation, characterisation and most
importantly validation in wheat, we and others have previously
used NGS-based technology to identify and map relatively large
numbers of gene-based SNP loci (Allen et al., 2011; Akhunov
et al., 2009; Chao et al., 2010). However, these studies used
cDNA and EST sequences and were therefore subject to variation
ª 2012 The Authors
Plant Biotechnology Journal ª 2012 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd
279
280 Alexandra M. Allen et al.
in expression of homoeologous and paralogous genes. In
hexaploid wheat, this situation is further aggravated as homoeologous and paralogous genes are often silenced or can show
differential spatial and/or temporal expressions (Adams and
Wendel, 2005; Akhunova et al., 2010; Liu et al., 2009). Genomic
DNA is likely to be a more reliable source of putative SNPs;
however, the size of the wheat genome means that sequencing
the whole genome of multiple varieties to the depths required for
successful SNP identification is impractical, time consuming and
costly (Biesecker et al., 2011). To overcome these resourceassociated problems, we have used a recently developed
sequence capture targeted resequencing approach to characterise a significant proportion of the wheat exome (Winfield et al.,
2012). By using a reference collection of the wheat exome as the
basis of our SNP collection, we have been able to sequence and
compare equivalent regions of the wheat genome from several
wheat varieties.
To be fully utilised in breeding programmes, putative SNPs
need to be identified and converted to working assays on a highthroughput genotyping platform. Recently, several technologies
have revolutionised wheat genotyping: Illumina’s GoldenGate/
Infinium technologies and KBioscience’s KASPar (Akhunov et al.,
2009; Allen et al., 2011). Development of these platforms has
encouraged the widespread uptake of SNP-based genotyping in
wheat; however, both technologies have two significant drawbacks. Firstly, they require the identification and characterisation
of varietal SNPs among an excess of homoeologous and
paralogous SNPs. Secondly, as both platforms were developed
for diploid species, they have problems with the scoring of varietal
SNPs in polyploid heterozygotes, for instance, F2 and backcross
populations. The detection of heterozygous SNPs in allohexaploid
wheat is dependent on the ability of the system to accurately
discriminate between different call ratios. For ‘dominant’ SNP
assays, which amplify all three homoeologous copies, these
systems are often incapable of distinguishing homozygote (having
a call ratio of 4 : 2) and heterozygote lines (having a call ratio of
5 : 1) (Allen et al., 2011; Paux et al., 2011). In contrast, both
genotyping platforms work well when the SNP is amplified from
just a single homoeologous/paralogous copy. Such SNP assays are
usually referred to as co-dominant SNP assays, that is, they are
capable of differentiating between homozygotes (having a call
ratio of 2 : 0) and heterozygotes (having a call ratio of 1 : 1). As
such, co-dominant SNP assays are preferred markers compared
with dominant SNP assays. Unfortunately, co-dominant SNP
assays usually make up < 20% of the SNP assays generated by
conventional means (Allen et al., 2011). However, careful primer
design can lead to the successful amplification of just one
homoeolog/paralog, but this process is time consuming as the
variable nature of each set of sequences demands a manual
approach to primer design. To overcome this bottleneck, we have
developed a SNP identification pipeline which incorporates a
novel bioinformatics procedure designed to identify putative
co-dominant SNP assays.
The developments described here have led to both the
generation of an extensive set of putative varietal SNPs from
genomic DNA and within this data set the identification of a
subset of putative co-dominant SNPs. The use of an exome-based
SNP discovery strategy has targeted gene discovery to genic
regions. Validation of a subset of these putative co-dominant SNP
assays and a comparison with dominant SNP markers has
provided useful insights into their design and characteristics.
Finally, the work described here has resulted in a significant
increase in the number of gene-derived co-dominant SNP assays,
which will be of considerable interest to wheat researchers, and in
particular, the breeding community.
Results
SNP discovery
In this study, the exome of the UK varieties Alchemy, Avalon,
Cadenza, Hereward, Rialto, Robigus, Savannah and Xi19 was
captured using the NimbleGen capture array (NimbleGen array
reference 100819_Wheat_Hall_cap_HX1) described in Winfield
et al. (2012). This generated between 9.8 and 48.7 million reads
on the Illumina GAIIx platform. Sequence data were filtered as
described in the experimental procedures. Varietal SNPs were
called in the filtered data where read coverage was sufficiently
high that there was less than a 0.1% chance of an observed allelic
difference between two varieties being due to failure to sample
an allele. For example, if the varieties Avalon and Cadenza have
observed calls of A(20) and A(10)G(10), respectively, we would
expect half of the alleles in Avalon (10 calls) to be G under the null
hypothesis that there is no real genotypic difference. Randomisation tests showed that for the data set as a whole, using a
minimum expected count of 10 for null bases resulted in a false
discovery rate of < 1%. Putative co-dominant SNP markers were
identified as the subset of SNPs meeting the above criteria, but
where every variety had only a single allele called. The SNP
discovery pipeline identified 95 266 putative varietal SNPs in
26 551 distinct reference sequences (Winfield et al., 2012).
Examination of these SNPs suggested that as in our previous
work, only 10%–20% were co-dominant (Table 1; Allen et al.,
2011), with 10 251 putative co-dominant SNP markers identified
within 5308 contigs.
Co-dominant SNP validation
As co-dominant SNP assays are of significant interest to the wheat
community, it is important that such assays have a level of
polymorphism that is not significantly different to that previously
shown for dominant SNP assays. In addition, it is important that
the distribution of the co-dominant SNP markers across the three
homoeologous genomes do not show a bias beyond those shown
previously for mapped dominant SNP markers (Allen et al., 2011).
To assess both of these features, we selected a subset of 1337
putative co-dominant SNP assays for validation and further
analysis. While the selection process used to identify this subset
was essentially random, to aid further investigation, we selected
those SNPs that appeared, via the sequence analysis, to be
polymorphic between the parents of the UK mapping populations
Avalon 9 Cadenza and Savannah 9 Rialto. Of the 1337 SNPs
selected, we were able to design working KASPar assays for 1190
SNPs (89%; Data S1).
Genotyping of a panel of 47 wheat varieties using the 1190
KASPar probes resulted in 1138 probes (96%) generating data
that could be scored consistently and were polymorphic in at least
one of the varieties screened (Data S2). Examination of the
genotypic data revealed three types of varietal SNP markers:
co-dominant SNP markers (where homozygous scores were
detected for all hexaploid varieties, for instance, only scores of
A:A or T:T were obtained, Figure 1a); partially co-dominant SNP
markers (where heterozygous and homozygous scores were
detected in hexaploid varieties, that is, A:A, T:T and the mixed A:
T, Figure 1b); and dominant SNP markers (where a single
homozygous and heterozygous score was detected in hexaploid
ª 2012 The Authors
Plant Biotechnology Journal ª 2012 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd, Plant Biotechnology Journal, 11, 279–295
Wheat exome-based co-dominant SNPs 281
Table 1 Summary of next-generation
sequence data and SNPs identified for eight
wheat varieties
No. of
No. of SNPs
No. of co-dominant
Proportion of total
sequences
No. mapped
(compared with
SNPs (compared
SNPs that are
Variety
(million)
reads (million)
Avalon)
with Avalon)
co-dominant (%)
Avalon
27.2
10.9
N/A
N/A
Alchemy
44.4
16.9
22 092
2558
11.6
Cadenza
20.2
4.9
8909
1550
17.4
Hereward
41.0
15.2
13 379
2399
17.9
Rialto
30.4
11.8
15 141
2662
17.6
Robigus
31.4
6.3
10 823
2114
19.5
Savannah
48.7
16.8
18 648
2818
15.1
9.8
2.9
4391
899
20.5
Xi19
varieties, that is, A:A and mixed A:T only, Figure 1c). Of the 1138
validated probes, 734 (65%) were co-dominant, 194 (17%) were
partially co-dominant and 210 (18%) were dominant. Dominant
and co-dominant markers were used to screen an F4 population
known to contain homozygote and heterozygote individuals.
Screening this population with co-dominant SNP assays resulted
in three separate clusters for the various homozygote and
heterozygote individuals (Figure 1d). However, screening the
same population with dominant SNP assays produced a more
scattered cluster where homozygous and heterozygous loci were
indistinguishable (Figure 1e). Screening the F4 population with
partially co-dominant SNPs yielded the same results as described
for both dominant and co-dominant SNP assays depending on
the genotypes of the population parents (data not shown).
The SNP markers developed through the NimbleGen exome
capture were compared with the existing database of SNP
markers developed from EST and normalised cDNA sequences
using the experimental procedures described in Allen et al., 2011;
(Table 2; Data S3). The number of co-dominant SNP assays
generated was significantly higher, and dominant SNPs significantly lower, when compared with the previous data set of
validated EST/cDNA-derived SNPs (v2 = 131.98, P < 0.001).
Comparison of the two data sets showed that the numbers of
partially co-dominant SNP assays were not significantly different
between the two data sets (v2 = 3.87, P = 0.14). In addition, the
polymorphism information content (PIC) scores and minor allele
frequencies (MAF) were similar between the two data sets; they
Figure 1 KASPar plots of different varietal SNP
types screened against a panel of hexaploid wheat
varieties with examples of (a) a co-dominant SNP
assay, (b) a partially co-dominant SNP assay and
(c) a dominant SNP assay. Screening an F4
population containing heterozygotes with a
co-dominant SNP assay results in a separate
cluster for heterozygote individuals (d). Screening
the same population with a dominant SNP assay
produces a more scattered cluster where
homozygote and heterozygote individuals are
indistinguishable.
were highest for the partially co-dominant SNP assays and lowest
for the dominant SNP assays.
Characterisation of the different SNP types
To characterise the different SNP marker types identified in
this study, and in particular, the co-dominant and partially
co-dominant SNP assays, several analyses were performed using
the contig sequences containing the SNPs. The average sizes of
contigs containing different SNP types were similar (co-dominant,
692 bp; dominant, 690 bp; partially co-dominant, 666 bp). We
hypothesised that co-dominant SNP assays were likely to be
derived from 5′ or 3′ untranslated regions (UTRs) of genic
sequences. In the absence of functional coding constraints, such
regions are more likely to have diverged between homoeologs
and thus represent effectively unique regions of sequence. To
address this hypothesis, SNP-containing contig sequences were
used to screen, via BLASTX (Altschul et al., 1990), the nonredundant (nr) protein database. If a match was found (E-value
1e-5), a further analysis was then performed to identify whether
the SNP was located inside or outside the coding region. This
analysis showed that a higher proportion of the contig sequences
used to develop co-dominant SNP assays returned no hit when
subjected to a BLASTX analysis against the nr database, compared
with dominant SNP assay sequences. Where a hit was identified,
a higher proportion of the co-dominant SNPs were found to lie
outside the coding region, compared with dominant SNPs. The
number of co-dominant SNPs located within known coding
(c)
(b)
(a)
(d)
N/A
(e)
ª 2012 The Authors
Plant Biotechnology Journal ª 2012 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd, Plant Biotechnology Journal, 11, 279–295
282 Alexandra M. Allen et al.
Table 2 Summary of validated SNPs
Validated
Validated
NimbleGen
EST/cDNA
Total validated
Average minor
Average
SNPs (%)
SNPs (%)
SNPs
allele frequency
PIC score
Dominant
210 (19)
1195 (58)
1407
0.249
0.273
Partially
194 (17)
437 (21)
632
0.315
0.315
734 (64)
444 (21)
1175
0.270
0.287
1138
2076
3214
0.270
0.286
SNP type
co-dominant
Co-dominant
All SNPs
PIC, polymorphism information content.
Map location of dominant, partially co-dominant and
co-dominant SNP assays
The map positions of the different SNP marker types were
investigated to determine whether any bias in genetic location
was introduced by using co-dominant SNP assays in two doubledhaploid mapping populations developed from UK cultivars
Avalon 9 Cadenza (A 9 C) and Savannah 9 Rialto (S 9 R). Of
the 3214 SNP markers developed to date (Table 2), 2109 were
identified as polymorphic between Avalon and Cadenza (via
Percentage of total number of
sequences
(a)
60
50
40
30
No hits
20
SNP outside coding
region
SNP within coding
region
10
0
(b) 9000
8000
7000
6000
5000
4000
3000
2000
1000
0
Frequency
Dominant
Co-dominant
Partially codominant
0
5
10 15 20 25
Coverage in 5x genome
30
(c) 25
20
Frequency
regions was significantly lower than would be expected to occur
by chance (v2 = 7.56, P = 0.02). Partially co-dominant SNPs were
midway between dominant and co-dominant SNPs (Figure 2a).
Across all SNP marker types, the average length of contigs
returning no hit was lower (approximately 520 bp) than the
average length of contigs returning BLASTX hits (approximately
770 bp), suggesting that contig length affected the likelihood of
obtaining a BLASTX match. To check whether the contigs
returning no hit represent genes that had not yet been
annotated, the same contig sequences were subjected to a
BLASTN analysis (E-value 1e-3) against the NCBI nr nucleotide
database; 86% of the contigs returning no hit from the BLASTX
analysis also had no match in the BLASTN nr database.
We further hypothesised that some co-dominant SNP assays may
have been derived from single-copy regions of the wheat genome.
Such regions may have either been unique to only one progenitor
genome or alternatively one or more copies have been lost since
polyploidisation. To address this second hypothesis, the same sets
of sequences were screened, using BLASTN, against the 5 9
Chinese Spring genomic raw reads at http://www.cerealsdb.uk.
net/. BLAST hit coverage was calculated for every nucleotide
position in the query sequence and averaged over the whole
sequence to derive a mean contig coverage. All three SNP types
peak in coverage at 15 9 , indicative of three gene copies each at
5 9 coverage; however, the co-dominant SNPs and to a lesser
extent the partially co-dominant SNPs had a secondary peak of
coverage at fivefold coverage, indicative of single-copy number
sequences. This peak is absent from the dominant SNPs (Figure 2b).
These analyses were combined by comparing the coverage of
sequences containing co-dominant SNPs that had different
BLASTX results. The sequences with 5 9 coverage are most
highly represented by those returning a ‘no hit’ from BLASTX
analysis (Figure 2c). When contig length was plotted against
median coverage for co-dominant SNPs, no relationship was
observed (r = 0.0009). A similar result (r = 0.0009) was
obtained by performing the same analysis using only sequences
returning no BLASTX hit, suggesting that the contig length does
not affect the number of hits returned from the BLASTN analysis
or the estimated level of coverage.
15
no hit
10
SNP outside coding
region
SNP within coding
reigon
5
0
0
5
10 15 20 25
Coverage in 5x genome
30
Figure 2 Characteristics of sequences containing dominant, partially
dominant and co-dominant SNP types. (a) BLASTX analysis against the
non-redundant (nr) protein database and (b) BLASTN against the 5 9
Chinese Spring raw reads. (c) Coverage of sequences containing
co-dominant SNPs against the 5 9 Chinese Spring raw reads classified
according to the BLASTX designation in (a).
screening of the 47 varieties above), of which 1807 were placed
on the Avalon 9 Cadenza map. These consisted of 1152 EST/
cDNA-derived markers and 655 NimbleGen-derived markers. Of
the remaining 1105 SNP assays not polymorphic between Avalon
ª 2012 The Authors
Plant Biotechnology Journal ª 2012 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd, Plant Biotechnology Journal, 11, 279–295
Wheat exome-based co-dominant SNPs 283
and Cadenza, 562 were identified as polymorphic between
Savannah and Rialto and 541 of these markers were placed on
the Savannah 9 Rialto map. These consisted of 187 EST/cDNAderived markers and 375 NimbleGen-derived markers. To enable
comparisons between the maps, 231 evenly spaced loci from
the Avalon 9 Cadenza map were also included on the
Savannah 9 Rialto map (Figure 3; Data S3). For the Avalon 9 Cadenza map, previously mapped SSR markers were used
to help assign linkage groups to chromosomes (http://www.wgin.
org.uk/resources/MappingPopulation/TAmapping.php; Data S4).
In total, 2350 (73%) of the validated SNP markers were mapped;
these comprised of 969 dominant SNP loci, 444 partially
co-dominant loci and 937 co-dominant SNP loci. In the Avalon 9 Cadenza map, the linkage groups ranged from 54.5 to
239.0 centiMorgans (cM) in size, with 8–214 SNP markers. The
total map length was 2434.4 cM with an average spacing of
1.3 cM between SNP loci. In the Savannah 9 Rialto map, linkage
groups ranged from 1.3 to 221.1 cM, with 2–98 SNP markers.
The total Savannah 9 Rialto map length was 2861.8 cM with an
average spacing of 3.8 cM between SNP loci (Table 3). The two
linkage maps aligned well with each other, showing similar
arrangements of common loci within linkage groups.
In both populations, over 97.5% of the SNP markers could be
mapped unequivocally to a linkage group and assigned to a
unique chromosome position. The lack of markers on the short
arm of chromosome 1B in the Savannah 9 Rialto map can be
attributed to the presence of the same 1BL.1RS rye translocation
in both Savannah and Rialto, where the short arm of rye
chromosome 1B has replaced the short arm of wheat chromosome 1B (Figure 3). Clustering of SNP markers was observed in
both linkage maps, with 55% of A 9 C markers and 61% of
S 9 R markers being completely linked (0 cM distance between
them). Of the remaining markers, 81% of A 9 C markers are
separated by < 5 cM and 90% are within 10 cM of the next
marker. For the S 9 R map, these figures are lower (55% markers
separated by < 5 cM and 74% within 10 cM), probably due to a
smaller number of markers on the map. Similar levels of clustering
were observed for the different SNP marker types; 60% of A 9 C
co-dominant markers and 52% of dominant markers were
completely linked. Of the remaining co-dominant markers, 77%
of markers are within 5 cM of each other and 88% are within a
10 cM interval. The corresponding proportions for dominant
markers are similar (84% within 5 cM and 92% within
10 cM).The different SNP types showed similar patterns of
distribution between the A, B and D linkage groups in both the
Avalon 9 Cadenza and Savannah 9 Rialto maps, with the only
difference of a higher proportion of the partially co-dominant
markers mapped to the D genome (Figure 4a). Similarly, although
clustering of SNP markers was observed within the linkage
groups, there was no obvious bias of different marker types
(Figure 3).
Summary statistics of mapped loci
The summary statistics of mapped SNP markers were compared
to assess whether different marker types had varying levels of
polymorphism in the 47 varieties screened and to ensure that the
co-dominant SNP markers developed in this study would be
useful across a wide range of material. The mean MAF and levels
of genetic diversity of SNP markers were compared between the
different marker types and assigned genomes of the
Avalon 9 Cadenza and Savannah 9 Rialto maps (Table 4). These
summary statistics were very similar for both maps; however,
differences within the maps were observed. Partially co-dominant
SNP assays had the highest average MAF and PIC scores, and
dominant SNP assays had the lowest. Loci from the separate
homoeologous genomes had consistent MAF and PIC measurements, although the A and D genome measurements were
slightly higher than the B genome (Table 4). The different classes
of SNP loci showed differences in the distribution of MAF scores.
Co-dominant and partially co-dominant loci showed an increased
proportion of medium and high frequency alleles compared with
dominant loci (Figure 5a). Similarly, D genome loci showed a
trend to have higher MAF compared with A and B genome loci
(Figure 5b). The distribution of PIC scores showed that codominant and partially co-dominant loci types had a higher
proportion of high PIC scores than dominant SNP assays
(Figure 5c). A and B genome loci had a similar distribution of
PIC scores, while D genome loci had a comparatively higher
proportion of high PIC scores (Figure 5d).
Discussion
In this study, we present a SNP discovery pipeline capable of
identifying large numbers of putative SNPs from genomic
sequence obtained by targeted exome capture. This proved an
efficient method to generate equivalent sequences from multiple
varieties from which we were able to generate over 90 000
putative SNPs between eight elite UK cultivars. Given our results,
this same approach is likely to prove highly effective at
identifying SNPs across a wide range of cultivars, and in a
wider range of germplasms, such as landraces, progenitors and
alien species. By cataloguing SNPs using a reference collection of
sequences derived from just the wheat exome, we provide a
unique context for each SNP, thereby both reducing the chance
of duplications within the SNP data set and allowing direct
comparisons between different wheat lines. A key advantage to
the SNP collection described here compared with other SNP
markers such as insertion site–based polymorphisms (ISBPs; Paux
et al., 2010) is that by the nature of the targeted sequencing,
all the SNPs developed are associated with genes, and as
such, are likely to prove useful in gene-based marker-assisted
breeding.
When examined further, the SNP database was shown to
contain 10 251 putative co-dominant SNPs. Validation of over
10% of the co-dominant SNP assays on the KASPar genotyping
platform resulted in a significantly improved validation rate
compared with our previous study with 96% being polymorphic
between the varieties screened compared with 67% as described
in Allen et al. (2011). This increased validation rate is probably
due to the use of genomic DNA, as opposed to transcriptomederived data, in the SNP discovery phase where the problems of
expression differences and presence of intron–exon splice sites
hindered effective SNP identification and primer design (Trick
et al., 2012). Of the subset of putative co-dominant SNP
assays, over 80% were validated as co-dominant or partially
co-dominant, compared with < 20% in previous studies where
random SNPs were validated (Allen et al., 2011). The occurrence
of putative co-dominant SNP assays, which were dominant when
validated, is likely to be due to the presence of homeologous
sequences that were not represented in the sequence data but
were amplified by the KASPar primers. This may be due to a
feature of individual sequences that prevent them from mapping
on to the assembly or a consequence of reduced sequence
coverage.
ª 2012 The Authors
Plant Biotechnology Journal ª 2012 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd, Plant Biotechnology Journal, 11, 279–295
284 Alexandra M. Allen et al.
A C_1A SxR_1
Ax
R A
XBS00010488
0
5
X
XBS0
0023118
XBS00010488
X
XBS00000713 XBS00004528
XBS00005272 XBS00022506
XBS00022677 XBS00022759
XBS00022770 XBS00023176
XBS00000742 XBS00022355
XBS00022483 XBS00022566
XBS00023130 XBS00023167
XBS00023201
10
15
XBS00022361
X
X S00010128 XBS0
XB
X
0001635
XBS00004382 XBS0
X
0010039
X
XBS0
0010267
XBS00022271 XBS0
X
0022285
XBS00022270 XBS0
X
0022701
XBS00010054 XBS0
X
0012072
XBS00012226
X
XBS0
0022070
X
XBS0
0022934
XBS00003572 XBS0
X
0003761
X
XBS0
0012052
X
XBS0
0021662
X S00011787 XBS00022391
XB
XBS00009885 XBS0
X
0009926
X
XBS0
0003851
XBS00014906 XBS0
X
0021661
XBS00009866 XBS0
X
0022152
XBS00011128 XBS0
X
0011286
X S00021779 XBS0
XB
X
0022201
XBS00022130 XBS0
X
0010481
X S00022144 XBS0
XB
X
0003758
X S00009444 XBS0
XB
X
0009495
XBS00009603 XBS0
X
0010004
XBS00010416 XBS0
X
0010452
XBS00010595 XBS0
X
0010643
XBS00011835 XBS0
X
0011864
XBS00021730 XBS0
X
0021777
X
XBS0
0021863
XBS00022156 XBS0
X
0022217
X
XBS0
0022132
XBS00022149 XBS0
X
0022167
XBS00022216 XBS0
X
0022207
XBS00000853 XBS0
X
0021864
X
XBS0
0022733
XBS00009559 XBS0
X
0010187
XBS00003656 XBS0
X
0003829
XBS00021741 XBS0
X
0022172
X S00022173 XBS00022220
XB
X
XBS0
0022158
X S0000374
XB
7 3 XBS0
X
0009808
XBS00011146 XBS0
X
0009459
X
XBS0
0021764
XBS00009700 XBS0
X
0012042
XBS00021665 XBS0
X
0021758
X S00022061 XBS00022239
XB
X S00022396 XBS0
XB
X
0022848
X
XBS0
0021759
X
XBS0
0003863
X S00021797 XBS0
XB
X
0021798
X
XBS0
0022356
X
XBS0
0021778
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
XBS00009466
XBS00003691
X S00012226 XB
XB
X S00022997
X S00010128
XB
XBS00022667
XBS00022243 XBS00022443
XBS00022682
XBS00004033
XBS00004043
XBS00021740
XBS00023065 XBS00023141
XBS00012210
XBS00022885
XBS00022426 XBS00022714
XBS00022870
XBS00004266 XBS00021714
XBS00022698 XBS00023101
XBS00002000 XBS00002215
X S00009444 XB
XB
X S00012496
XBS00021672 XBS00021719
XBS00021766 XB
X S00021779
XBS00021808 XBS00021878
XBS00021889 XBS00021916
X S00022144 XB
XB
X S00022275
XBS00022286 XBS00023126
X S00022173 XB
XB
X S00022220
XBS00022432
95
X S00022061
XBS00021760 XB
X S00022239 XB
XB
X S00022396
100
105
XBS00021879
XBS00022351
110
XBS00009510
115
120
125
XBS00000226
130
135
140
Ax
xC_1B
XBS00010592 XBS00010791
XBS00022505 XBS00003831
XBS00011608 XBS00001634
XBS00022650 XBS00010076
XBS00003930 XBS00003880
XBS00003911 XBS00003917
X 00010032 XBS
XBS
X 00010106
XBS00010508 XBS00010868
XBS00011695 XBS00011961
XBS00022310
XBS00022702 XBS00022973
XBS00022102 XBS00023102
XBS00023177
XBS00022294 XBS00022101
XBS00003684
XBS00011641 XBS00022030
XBS00022135
XBS00022247 XBS00022687
XBS00022632 XBS00022670
XBS00022104 XBS00023162
XBS00023122 XBS00022303
XBS00022508 XBS00022575
XBS00022011 XBS00022089
XBS00022133 XBS00022324
XBS00022375 XBS00021946
XBS00022616 XBS00022888
XBS00022581 XBS00022740
XBS00021947 XBS00022490
XBS00022536 XBS00022085
XBS00022645 XBS00022748
XBS00022749 XBS00022909
XBS00022088 XBS00022739
XBS00023213 XBS00022625
XBS00021996 XBS00022007
XBS00022722 XBS00021995
XBS00022549 XBS00022648
XBS00022690 XBS00023044
XBS00021954
XBS00022783 XBS00022911
XBS00022005
XBS00022281 XBS00003619
XBS00003839 XBS00009381
XBS00014413 XBS00021052
XBS00009827
XBS00003822
XBS00010246 XBS00010992
XBS00013901
XBS00009675 XBS00015200
XBS00011462 XBS00021866
XBS00011379 XBS00003575
XBS00003844 XBS00009921
XBS00009977 XBS00011745
XBS00012062 XBS00010875
XBS00013824 XBS00018526
XBS00009488 XBS00010352
XBS00009483
XBS00011104 XBS00011333
XBS00000496 XBS00003627
XBS00009731 XBS00009983
XBS00010428 XBS00011324
XBS00012051 XBS00021907
XBS00003677 XBS00010253
XBS00011008 XBS00017597
XBS00003567 XBS00011463
X 00011712 XBS
XBS
X 00003600
XBS00003634 XBS00009270
XBS00009502 XBS00009547
XBS00009952 XBS00010549
XBS00011159 XBS00011222
XBS00011450 XBS00011468
XBS00012079 XBS00021900
XBS00011500
XBS00018653
X S00010735
XB
XBS00001224
XBS00023113 XBS00023142
XBS00009945
XBS00023001
XBS00022878
XBS00022343 XBS00022569
XBS00022615 XBS00022842
XBS00022920
XBS00012056 XBS00021711
XBS00010130 XBS00001414
X 00011062 XBS
XBS
X 00011274
7
XBS00011423 XBS00011841
XBS00011973
XBS00010475 XBS00010779
XBS00010888 XBS00012456
X S00022093
XB
X S00022778
X
XBS0
0022468 XB
X S00022779 XBS00022883
XB
XBS00012021 XBS00010625
XBS00010399
XBS00021988 XBS00021975
X
XBS0
0010157 XB
X S00021710
XBS00010536 XBS00010938
XBS00003934 XBS00009706
XBS00013948 XBS00022626
X S00023148 XBS00021680
XB
XBS00004328 XBS00010009
XBS00022889 XBS00022392
XBS00009500 XBS00012502
X S00009324
X
XBS0
0000651 XB
XBS00010148 XBS00010436
XBS00011934 XBS00012029
X S00022567
XB
X S00022851
X
XBS0
0022577 XB
X S00022530 XBS00022775
XB
X S00022411
XB
X S00003633
XB
XBS00021941 XBS00002250
XBS00004129 XBS00010392
XBS00021876
XBS00009909 XBS00011670
X S00023173
XB
7
XBS00012012
X S00009709 XBS00010610
XB
XBS00022342
XBS00003702
XBS00011811
X S00001128
XB
XBS00022153
SxR_1B
Ax
xC_1D
X
XBS0
0021748
X S00003806
XB
XBS00021723 XBS0
X
0022323
XBS00021710
X
X S00022778
X
XBS0
0002301 XB
X S00022779
XB
X S0001073
XB
7 5 XBS00011783
X
XBS0
0012250 XB
X S00012899
X S00022093
X
XBS0
0021935 XB
X
XBS0
0022639 XB
X S00022742
X
XBS0
0012525 XB
X S00022571
X S0000374
XB
7 3 XBS00004269
X S00009324 XBS00012443
XB
X S00023148
X
XBS0
0012480 XB
X
XBS0
0022789
X S00022567 XBS00022614
XB
X
XBS0
0022849 XB
X S00023071
X S00022411 XB
XB
X S00022530
X S00022851
XB
X
XBS0
0000764 XB
X S00012773
X
XBS0
0022249 XB
X S00022251
SxR_1D
X S00003806 XBS0
XB
X
0003823
X
XBS0
0003751
X
XBS0
0023049
XBS00010661 XBS0
X
0021819
X
XBS0
0022984
X S00003633 XBS00022539
XB
X S00001737
XB
XBS00021934 XB
X
X S00022609
X
XBS0
0023194
XBS00011451 XBS0
X
0010486
XBS00022633 XBS0
X
0022595
XBS00022027 XBS0
X
0022962
XBS00009639 XBS0
X
0010435
X S00022623
X S00014671 XB
XB
X S00022768 XB
XB
X S00021690
XBS00022334 XBS0
X
0004282
X
XBS0
0011310
X S00003558 XBS0
XB
X
0021702
X S00003559 XBS0
XB
X
0018250
XBS00003816
X
X
XBS0
0022041
XBS00003558 XBS0
X
X
0017501
X S00021690 XB
XB
X S00022623
X S00003559
XB
X S00023173
XB
XBS00012449
X
X S00021851
XB
X S00009709
X
XBS0
0000033 XB
X
XBS0
0022188
XBS00022398 XB
X
X S00022676
X
XBS0
0023105
X
XBS0
0000010
XBS00004145 XBS00012350
X
X S00012392 XBS00012455
XB
X S00013397
XB
X
XBS0
0021877
X
XBS0
0021697
X S00001128
XB
XBS00011855 XBS0
X
0000424
XBS00003573 XBS0
X
0003687
XBS00003725 XBS0
X
0009375
XBS00009377 XBS0
X
0009389
XBS00009625 XBS0
X
0010248
XBS00010402 XBS0
X
0010498
XBS00010528 XBS0
X
0010669
XBS00010713 XBS0
X
0010807
XBS00010851 XBS0
X
0010946
XBS00011041 XBS0
X
0011168
XBS00011292 XBS0
X
0011672
X
XBS0
0011947
X
XBS0
0022485
X
XBS0
0022654
X
XBS0
0009412
X
XBS0
0022484
X
XBS0
0021667 XB
X S00022802
XBS00023203
X S00021797
XB
145
Figure 3 Genetic linkage maps of wheat derived from 190 Avalon 9 Cadenza doubled-haploid lines and 95 Savannah 9 Rialto doubled-haploid
lines. Each linkage group was assigned to a chromosome indicated above the linkage group, and chromosomes are arranged with the short arm
above the long arm. SNP loci mapped in this study are designated XBS and are coloured according to the SNP type: Dominant SNP loci are shown in
black, co-dominant SNP loci are shown in red and partially co-dominant SNP loci are shown in blue. Common markers between the Avalon 9 Cadenza
and Savannah 9 Rialto maps are underlined. Map distances, calculated using the Kosambi mapping function, are shown in centiMorgans (cM) on the
ruler to the left of linkage groups.
ª 2012 The Authors
Plant Biotechnology Journal ª 2012 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd, Plant Biotechnology Journal, 11, 279–295
Wheat exome-based co-dominant SNPs 285
Ax
xC_2A
0
5
XBS00022024 XBS00023039
XBS00023052
X S00022777
XB
XBS00010624 XBS00003735
XBS00004385
XBS00011271
X
10
15
20
25
30
35
XBS00023215
X S00003845 XBS00003867
XB
XBS00011101 XBS00011593
XBS00014736 XBS00016676
XBS00021691 XBS00021706
X S00009604 XBS00009933
XB
X S00022487
XB
40
SxR_2A
XBS00004496 XBS00009837
XBS00010629 XBS00012284
XBS00012592
XBS00011949
XBS00004089 XBS00004673
XBS00004156 XBS00012249
XBS00012628 XBS00012784
XBS00014923 XBS00022665
X S00003845 XB
XB
X S00004112
XBS00004243 XBS00005283
XBS00012221 XBS00012228
XBS00012313 XBS00013085
XBS00013294 XBS00013474
XBS00013669 XBS00018554
XBS00022322 XB
X S00022777
XBS00003807
XBS00004221 XBS00012561
XBS00013258 XBS00022799
XBS00023143
XBS00004040
XBS00003999 XBS00004067
XBS00005270 XB
X S00011271
X S00011466 XBS
XB
X 00011893
XBS00012205 XBS00012239
XBS00012409 XBS00013209
XBS00013534 XBS00022327
XBS00022331 XBS00023206
Ax
xC_2B SxR_2B
X S00023068 XB
XB
X S00010734
X S00009972
XB
XBS00012159
XBS00014046
XBS00004244 XBS00004262
X S00010734
XB
XBS00012471
X
XBS00
010318 XB
X S00010711
X S00002660
XB
X S00022059
XB
X
XBS00
022493 XB
X S00003833
X
XBS00
009263 XB
X S00010637
X
XBS00
010700 XB
X S00012209
X
XBS00
003719 XB
X S00009801
X
XBS00
022330 XB
X S00023025
X S00009848
XB
XBS00012202
Ax
xC_2D
SxR_2D
X S00018412
XB
X S00018412
XB
XBS00009771
Xbarc1
r 24
XBS00003791 XBS00009976
XBS00010492
Xbarc2
r 04
XBS00018347 XBS00022305
XBS00023062 XBS00023099
XBS00022957
X S00023068
XB
XBS00021707 XBS00021724
XBS00022059 XB
X
X S00022391
X S00002660
XB
XBS00009575 XBS
X
X 00010031
XBS00022730 XBS00022900
XBS00011425
X S00012081
XB
X S00022950
XB
45
50
55
60
65
70
75
XBS00009730 XBS00016060
XBS00022332
XBS00009697 XBS00022982
X S00009604 XB
XB
X S00022487
XBS00010087
XBS00003779 XBS00011865
XBS00022872 XBS00003574
XBS00010194 XB
X
X S00009588
X
XBS0
0021812 XB
X S00009667
XBS00002994 XBS00003878
XBS00003898 XBS00004004
X S00009256 XBS
XB
X 00010672
XBS00011045 XBS00011467
XBS00012040
XBS00023157
XBS00022301 XBS00022494
XBS00021767
X S00011517 XBS00012126
XB
XBS00011945
XBS00010696
80
85
XBS00022108
90
95
100
105
110
115
120
125
130
135
XBS00010901
XBS00001260
X S00011478
XB
XBS00003663
XBS00011075
XBS00004090
XBS00009959 XBS00021893
XBS00022209
X
XBS0
0022321 XB
X S00011169
XBS00009692 XBS00009737
XBS00010760 XBS00011190
XBS00011392 XBS00011539
XBS00011792 XBS00012066
XBS00013738 XBS00022150
XBS00014087 XBS00010477
X S00009
XB
S00009295
95 XB
X S000
S00021937
93
XBS00009616 XBS00009710
XBS00010729 XBS00014037
XBS00022467 XBS00022923
XBS00022925
XBS00009362
XBS00021676
140
145
XBS00021739
XBS00000590 XBS00021751
XBS00003582 XB
X S00009588
X S00010014
X S00009667 XB
XB
XBS00010932 XB
X S00011517
XBS00012111 XBS00012154
XBS00012545
XBS00022641 XBS00022896
XBS00022945
XBS00004255 XBS00012320
XBS00022241 XBS00022257
XBS00022260 XBS00022377
XBS00023123
XBS00012237 XBS00023214
XBS00021693
XBS00023048
XBS00022456 XBS00022461
XBS00011478 XB
X
X S00022265
XBS00012343 XBS00016238
XBS00022381 XBS00022585
XBS00022813
XBS00023144
XBS00022409
X S00022060
XB
X S00022734
XB
X
XBS00
014974 XB
X S00009807
X S00012078
XB
X S00010688
XB
X S00010055
XB
X S00021959
XB
X
XBS00
011039 XB
X S00011187
X
XBS00
004433 XB
X S00009305
X
XBS00
010219 XB
X S00010829
X
XBS00
010916 XB
X S00009962
X
XBS00
009989 XB
X S00011958
X
XBS00
011990 XB
X S00012103
X
XBS00
009247 XB
X S00009461
X
XBS00
011275 XB
X S00011315
X
XBS00
012071 XB
X S00022558
X
XBS00
011229 XB
X S00009442
X
XBS00
010567 XB
X S00012036
X
XBS00
022707 XB
X S00022014
X
XBS00
016650 XB
X S00019285
X
XBS00
022350 XB
X S00023145
X S00003714
XB
X S00003788 XB
XB
X S00010012
X
XBS00
011630 XB
X S00022091
X S00009258 XB
XB
X S00011954
X
XBS00
022295 XB
X S00003810
X
XBS00
011531 XB
X S00011737
X
XBS00
021896 XB
X S00022765
X
XBS00
009722 XB
X S00010303
X
XBS00
011709 XB
X S00021713
X S00011757
XB
X
XBS00
022335 XB
X S00022781
X S00022819
XB
X
XBS00
022314 XB
X S00022002
X
XBS00
022712 XB
X S00023124
X S00022010
XB
X S00022112
XB
X S00003585 XB
XB
X S00010432
X
XBS00
011430 XB
X S00011483
X
XBS00
022064 XB
X S00010523
X
XBS00
003589 XB
X S00003597
X
XBS00
003673 XB
X S00004405
X
XBS00
009437 XB
X S00009519
X S00009736 XB
XB
X S00009791
X
XBS00
009864 XB
X S00010361
X
XBS00
010640 XB
X S00011047
X
XBS00
011276 XB
X S00011858
X
XBS00
021895 XB
X S00022222
X
XBS00
009460 XB
X S00010081
X S00022478
XB
X S00022185
XB
X S00010918
XB
X S00009418 XB
XB
X S00011078
X S00011384
XB
X
XBS00
019095 XB
X S00009594
X S00010591
XB
X
XBS00
010859 XB
X S00011388
XBS00023015 XBS00023195
XBS00023043
XBS00000011 XBS00000092
XBS00004120 XBS00004140
XBS00022422 XBS00022503
XBS00022651 XBS00022966
XBS00004372 XBS00009815
XBS00010513 XBS00012294
XBS00012538 XB
X S00022112
XBS00022374
X S00003585 XB
XB
X S00003788
XBS00004011 XBS00004223
XBS00004224 XBS00004241
XBS00004242 XBS00004417
XBS00004422 XBS00012171
XBS00012190 XBS00012336
XBS00012382 XBS00012517
XBS00022313 XBS00022394
XBS00022497 XBS00022547
XBS00022618 XBS00022674
XBS00022713 XBS00022805
XBS00023169
XBS00003939 XBS00004130
XBS00004228 XBS00004322
XBS00004378 XBS00004420
X S00009258 XB
XB
X S00009511
XBS00012230 XBS00012390
XBS00012468 XBS00012830
XBS00020962 XBS00021892
XBS00021908 XBS00021931
XBS00022272 XBS00022421
XBS00022445 XBS00022563
XBS00022649 XB
X S00022837
XBS00023011 XBS00023047
XBS00011182
XBS00012251 XBS00012493
XBS00022399 XBS00022515
XBS00009998
XBS00011313 XBS00016116
XBS00022976
XBS00022210
XBS00021888
XBS00010681 XBS00011752
XBS00021852
XBS00010514 XBS00014219
XBS00021923 XBS00003660
XBS00009606 XBS00011740
XBS00000002 XBS00003804
XBS00010131
XBS00009673 XBS00010184
X
XBS00
009932 XB
X S00014647
X S00021865
XB
XBS00021823
XBS00021940 XBS00022019
X S00023211 XBS00022679
XB
XBS00022917
XBS00021912
XBS00000905 XBS00010472
XBS00010792 XBS00011413
XBS00021483 XBS00021927
XBS00022337
XBS00009982
XBS00011109
XBS00021950
Xbarc1
r 68
XBS00014647 XB
X
X S00021865
X S00023211
XB
XBS00021891
Xgwm
w 539
Xgwm
w 320
XBS00022941 XBS00022942
XBS00021828
XBS00003584 XBS00009533
XBS00009637 XBS00009901
XBS00010323 XBS00010382
X S00010393 XBS00010442
XB
XBS00012014 XBS00021825
XBS00021826 XBS00021827
X S00010393
XB
XBS00010685
150
155
X S00011169
XB
160
165
170
175
180
XBS00004303
185
190
XBS00010726
XBS00010005 XBS00012328
XBS00012379 XBS00023104
X S00009418
XB
195
200
XBS00000972 XBS00004200
XBS00012438 XB
X S00022478
205
XBS00012467
210
Figure 3 Continued
ª 2012 The Authors
Plant Biotechnology Journal ª 2012 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd, Plant Biotechnology Journal, 11, 279–295
286 Alexandra M. Allen et al.
Ax
xC_3A
0
XBS00003774
7
XBS00003733 XBS00009793
X S00010059 XBS00011516
XB
XBS00011840
5
SxR_3A
XBS00012160
XBS00003932 XBS00004149
XBS00004158 XBS00004414
X S00010059
XBS00005117 XB
X S00022006
XBS00021872 XB
XBS00022279 XBS00022347
XBS00022452 XBS00022798
XBS00022985 XBS00023022
XBS00019919
10
X S00022006
XB
15
20
XBS00000628
25
XBS00003933 XBS00022695
XBS00022746
30
35
40
45
50
55
60
65
70
75
80
85
90
95
X S00021981
XBS00022624 XB
X S00022844
XB
XBS00021976
XBS00022029 XBS00022129
XBS00022016
X S00022516
XBS00022148 XB
XBS00003801 XBS00013997
XBS00021699
XBS00010947
XBS00003837 XBS00010204
X S00010531
XB
XBS00011270 XBS00011929
XBS00009357
XBS00003964 XBS00010284
X S00011158 XBS00011170
XB
XBS00011798
XBS00022631 XBS00022881
X S00022502 XBS00022882
XB
X S00022719
XB
XBS00022083 XBS00022325
XBS00022629 XBS00022675
XBS00022691
XBS00009465 XBS00010295
XBS00010854 XBS00011612
XBS00011660 XBS00022612
XBS00023026
X S00011012
XB
XBS00021909
XBS00010022 XBS00011456
XBS00003778 XBS00010167
XBS00000646 XBS00003768
XBS00003924 XBS00010414
XBS00017988 XBS00019326
XBS00022703 XBS00022692
X 00022752 XBS
XBS
X 00023087
XBS00022845 XBS00022989
XBS00022533
XBS00021980
XBS00009740
XBS00022058
X S00011171 XBS00011231
XB
XBS00011280 XBS00011812
X S00011888 XBS00012084
XB
XBS00009516
XBS00001088 XBS00021694
X S00021981 XB
XB
X S00022516
X S00022844
XBS00022711 XB
XBS00022379
XBS00012551
X S00010531
XB
X S00011012
XB
XBS00003971 XBS00004183
X S00011158 XB
XB
X S00022159
X S00022502 XB
XB
X S00022719
XBS00021772 XBS00022552
100
X S00011171 XB
XB
X S00011888
105
XBS00022256
X S00022245
XBS00003935 XB
XBS00022459 XBS00022658
XBS00022804 XBS00022884
110
Ax
xC_3B SxR_3B
XBS00010945 XBS
X
X 00021849
X S00009440 XBS
XB
X 00012316
X 00009992
XBS
X 00001335
XBS
X 00003596
XBS
X 00012531
X S00009476 XBS
XB
X 00011532
XBS
X S00011806 XBS00022154
XB
X S00022971 XBS
XB
X 00011438
X S00003814 XBS
XB
X 00010844
X S00012127 XBS
XB
X 00011373
X S00004074 XBS
XB
X 00009393
X 00010849
XBS
XBS00022190
X 00022622
XBS
X 00009839
XBS
X S00011966 XBS00004108
XB
X S00011277 XBS
XB
X 00011551
X S00009805 XBS
XB
X 00011596
X S00003902 XBS
XB
X 00022315
X 00010332
XBS
X 00022048
XBS
X 00022242
XBS
X S00003871 XBS
XB
X 00009513
X S00022961 XBS
XB
X 00010060
X S00010396 XBS
XB
X 00011243
X 00010818
XBS
X S00010405 XBS
XB
X 00010778
X S00010881 XBS
XB
X 00019018
X S00015306 XBS00011042
XB
X S00003864 XBS
XB
X 00010826
X S00011064 XBS
XB
X 00011570
X S00003708 XBS
XB
X 00010795
X S00022415 XBS00023074
XB
7
X S00023037 XBS
XB
X 00023227
X S00022072 XBS
XB
X 00023191
X 00022741
XBS
X S00023121 XBS00023120
XB
X 00022078
XBS
X S00022453 XBS
XB
X 00022708
X S00011264 XBS
XB
X 00011720
X S00009411 XBS
XB
X 00010715
X S00009289 XBS00022728
XB
X 00011869
XBS
X 00009475
XBS
X S00015099 XBS
XB
X 00022051
X S00009651 XBS
XB
X 00003727
X S00003781 XBS
XB
X 00012452
X S00000793 XBS
XB
X 00009632
X S00022099 XBS
XB
X 00022732
X 00022792
XBS
XBS00022122
X S00009990 XBS00009579
XB
X 00010136
XBS
X S00009701 XBS
XB
X 00009892
X S00017577 XBS
XB
X 00010083
X S00022513 XBS
XB
X 00022021
X S00023190 XBS
XB
X 00000978
X S00010316 XBS
XB
X 00001242
X S00009549 XBS
XB
X 00020861
X S00022025 XBS
XB
X 00022039
X S00022084 XBS
XB
X 00022512
X S00022826 XBS
XB
X 00022939
X 00023030
XBS
X 00022316
XBS
X 00022611
XBS
X S00022440 XBS
XB
X 00011937
X S00012388 XBS
XB
X 00013262
X 00011766
XBS
X S00022219 XBS
XB
X 00022140
X S00010324 XBS
XB
X 00012080
X 00009337
XBS
X 00022131
XBS
X S00022403 XBS00022245
XB
X S00010572 XBS
XB
X 00022904
X 00021978
XBS
X 00022803
XBS
Ax
xC_3D
X S00021930 XBS
XB
X 00022212
SxR_3D
Xgwm383-3D
X 00003639
XBS
X S00009476
XB
XBS00022669 XBS00023186
X
X S00022154
XB
XBS00021920
X
X 00022166
XBS
X S00011395 XBS
XB
X 0001173
7 8
X 00010258
XBS
Xwmc529-3D
Xwmc294-3D Xw
Xwmc533-3D
X S00023210
XB
XBS00022190
X
X S00004108 XBS00011966
XB
X 00022387 XBS00022397
XBS
X 00023188
XBS
X 00022501
XBS
X 00021850
XBS
X S00003688 XBS
XB
X 00021919
X S00004334
XB
XBS00011042 XBS00022415
X
X S00023074
XB
7 XBS00023120
X 00003262 XBS00009579
XBS
X 00010407 XBS00011022
XBS
X 00012450 XBS00012472
XBS
X 00012549 XBS00012743
XBS
X S00022474
X S00022122 XB
XB
X S00022728 XB
XB
X S00022774
X 00023091
XBS
X 00005059
XBS
X fd009
Xc
f
-3D
115
120
125
XBS00022715
130
X 00003836
XBS
X 00003931
XBS
X S00021967 XBS00022441
XB
135
140
145
150
155
XBS00009649 XBS00022410
X S00022182
XB
XBS00022862
XBS00013724
XBS00022419 XBS00022915
XBS00022735
160
X S00022715
XB
X S00003717 XBS00009671
XB
XBS00011898 XBS00022401
X
X 00003884
XBS
XBS00022273
X S00022182
XB
X S00022441
XB
XBS00022092
165
X S00003849
XB
170
175
XBS00003956 XBS00022968
180
X 00018668
XBS
185
190
195
XBS00003849 XB
X
X S00021754
X S00022401
XB
X S00009671
XB
Figure 3 Continued
ª 2012 The Authors
Plant Biotechnology Journal ª 2012 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd, Plant Biotechnology Journal, 11, 279–295
Wheat exome-based co-dominant SNPs 287
Ax
xC_4A
0
XBS00003914
SxR_4A
X S00003914
XB
5
Ax
xC_4B
SxR_4B
Ax
xC_4D
XBS00011038
X
X S00022183
XB
XBS00022113
XBS00021924
XBS00021903
XBS00022846 XB
X S00022847
X 00003854 XBS00018120
XBS
XBS00023046
XBS00023095
XBS00017267
XBS00001207 XBS00003776
SxR_4D
X S00023046
XBS00022376 XB
X
X S00023131
XB
10
XBS00022015
X S00001207
XB
15
XBS00011060
X S00022015
XB
20
XBS00022125
XBS00022189
X 0001117 3 XB
XBS
X S00011378
25
30
35
40
X 00001241 XBS00009974
XBS
X 00011261 XBS00021736
XBS
XBS00022169 XBS00022174
XBS00022661
X 00022816 XBS00015312
XBS
X 00011628 XBS00010339
XBS
X 00010925 XBS00011273
XBS
XBS00012054
X 00009492 XBS00011224
XBS
XBS00010455
XBS00019518
X 00022213 XBS00023031
XBS
XBS00003623
Xgwm
gw 194
XBS00022090 XBS00022988
XBS00009915
XBS00010235 XB
X S00011148
X 00003674 XBS00010216
XBS
XBS00010504
X 0001111 5 XBS00022418
XBS
XBS00011336
X S00009970
XB
XBS00012006 XBS00023035
XBS00009426 XB
X S00009480
XBS00010115 XB
X S00012107
X S00015504
XB
X S00011510
XB
X S00021715
XB
50
X S00021727
XB
55
XBS00011939
60
XBS00010582
65
XBS00012457
XBS00012419
X S00021737 XBS
XB
X 00021738
45
XBS00023014
XBS00022837
XBS00018651
70
75
80
XBS00023220
85
90
95
XBS00010830 XB
X S00014274
X S00022534
XB
XBS00022686 XB
X S00021984
X S00022785
XB
XBS00010374 XB
X S00011338
X S00022038
XB
X S00021986
XB
X S00022258
XB
XBS00022090 XB
X S00022161
XBS00022193 XB
X S00022227
XBS00009253 XB
X S00009439
XBS00003646 XB
X S00011851
XBS00011859 XB
X S00022809
XBS00022179 XB
X S00009530
XBS00018707 XB
X S00022576
XBS00009915 XB
X S00014289
XBS00003858 XB
X S00009672
X S00011085
XB
XBS00022186 XB
X S00022194
X S00020575
XB
XBS00010940 XB
X S00009774
XBS00022184 XB
X S00003759
XBS00010067 XB
X S00010409
XBS00021752 XB
X S00022136
X S00022653
XB
X
2
X S00022046 XBS0002258
XB
XBS00022363 XB
X S00022364
XBS00003765 XB
X S00011040
X S00017892
XB
X S00009272 XB
XB
X S00022646
X S00009342
XB
X S00011336
X S00004407 XB
XB
X S00022830
XB
X S00022855
XB
XBS00022972 XB
X S00022413
X S00023035
XB
X S00012006
XB
XBS00014075 XB
X S00022466
X S00023179
XB
XBS00003704 XB
X S00003927
XBS00022018 XB
X S00022055
X S00022808
XB
XBS00022793 XB
X S00023024
X S00023051
XB
XBS00022366 XB
X S00023204
XBS00009333 XB
X S00010015
XBS00021722 XBS00022582
XBS00022646 XBS00022653
X wm609
Xgw
XBS00023014
Xgwm
Xg
w 194
Xgwm
w 624
100
XBS00022395
XBS00021957
105
110
XBS00009882 XBS00010716
X 00000346 XBS00009590
XBS
X 00009387 XBS00011583
XBS
X 00011623 XBS00010645
XBS
X 00021989 XBS00010766
XBS
X 00021958 XBS00022929
XBS
X S00012482 XBS
XB
X 00020151
115
120
XBS00022932
XBS00023219
XBS00023164
XBS00023007
125
130
135
140
X 00010116 XBS00010202
XBS
XBS00009680
XBS00009703
X 00003587 XBS00023012
XBS
XBS00017912
XBS00022546
XBS00022338
X 00022996 XBS00003692
XBS
XBS00022414
X S00021957 XB
XB
X S00022395
X S00010716
XB
145
150
155
X S00023164
XB
160
165
Figure 3 Continued
ª 2012 The Authors
Plant Biotechnology Journal ª 2012 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd, Plant Biotechnology Journal, 11, 279–295
288 Alexandra M. Allen et al.
Ax
xC_5A SxR_5A
0
X S00004373 XBS00010953
XB
X S00003643 XBS00022116
XB
Ax
xC_5B
XBS00022336
SxR_5B
X S00003944
XB
X S00022336
X S00011294 XB
XB
5
Ax
xC_5D2
XBS00021901
X
X 00022100
XBS
X 00022067
XBS
SxR_5D
XBS00012312 XB
X S00021670
XBS00000763
10
XBS00023008
XBS00022116
15
X S00021743
XB
XBS00022107 XBS00022773
X
X S00023134
XB
X S00004283 XB
XB
X S00023072
X S00023226
XB
20
XBS00023008
25
XBS00003696
X S00021734
XB
30
35
40
45
50
55
60
65
70
75
XBS00021708
X S00010218 XBS00011722
XB
XBS00021873
XBS00011537
X S00011116
XB
XBS00021963
X S00022034 XBS00022500
XB
XBS00022110
XBS00011278
XBS00005311
X S00000645 XBS00021801
XB
XBS00000373
XBS00009484
XBS00021953
XBS00022815
X S00015653 XBS00011873
XB
X S00003746 XBS00009531
XB
X S00009658 XBS00022495
XB
X S00022191 XBS00010275
XB
XBS00010966
XBS00000435
XBS00011318
XBS00000648
80
85
90
X S00021773
XB
105
110
115
XBS00022710
X
X S00010190
XB
XBS00022110
X S00022812
XB
X S00000615 XBS00000962
XB
XBS00003746 XBS
X 00004142
X S00004148 XBS00004187
XB
X S00004202 XBS00012772
XB
X S00013703 XBS00022191
XB
X S00022358 XBS00022509
XB
X S00022914 XBS00022974
XB
X S00023180
XB
X S00022987
XB
X S00023013
XB
XBS00011116
X S00022683
XB
X S00009745
XB
X S00021725
XB
XBS00022608 XBS00022761
X
X S00022762 XBS00022817
XB
X S00022818 XBS00022936
XB
X S00023029 XBS00023076
XB
XBS00022457
120
125
XBS00022128 XBS00022198
X
X S00010882 XBS00011298
XB
130
135
140
XBS00022200
145
150
155
160
165
170
175
180
XBS00022115 XBS
X 00003739
X 00021732
XBS
XBS00010153 XBS
X 00011495
XBS00021708
95
100
XBS00009264 XBS
X 00010981
XBS00023103
XBS00011095 XBS
X 00015136
XBS00010491 XBS
X 00011480
XBS00022107 XBS
X 00022602
XBS00022773
7
X 00018917
XBS
X 00003726
XBS
XBS00021695 XBS
X 00010616
X 000111 86
XBS
X 00003715
XBS
X 00003789
XBS
X 00021952
XBS
X 00022056
XBS
X 00022326
XBS
X 00001817
XBS
XBS00011890
XBS00022457
XBS00011235 XBS00021669
X
X S00021678 XBS00022215
XB
X S00021955 XBS00011227
XB
XBS00001735
XBS00009799
XBS00009369
X S00018510 XBS00021942
XB
X S00022071 XBS00022638
XB
X S00010757 XBS00010419
XB
X S00010702 XBS00011360
XB
XBS00011605
X S00022069 XBS00022893
XB
XBS00022205
X S00021968 XBS00022838
XB
XBS00022867
XBS00022299 XBS00021703
X S00021969 XBS00022681
XB
XBS00023070
X 00022545 XBS00022630
XBS
XBS00022864
XBS00022028
XBS00022890 XBS00023125
X S00003501 XBS00009274
XB
X S00011915 XBS00021684
XB
X S00000006 XBS00000028
XB
X S00000037 XBS00001953
XB
X S00003693 XBS00010048
XB
X S00011221 XBS00011592
XB
X S00011816 XBS00011846
XB
XBS00021860
XBS00010234
XBS00010757 XBS
X 00022311
X S00009369
XB
X S00023016
XB
XBS00021756 XBS00021757
X
XBS00022128 XBS
X 00022891
X S00022656
XB
185
190
195
XBS00021703 XB
X S00022299
200
XBS00021969 XB
X S00023070
205
210
215
220
225
230
235
X 00022228
XBS
X S00023018
XB
X S00022664
XB
XBS00004166 XBS00015694
X
XBS00022890
XBS00000006 XB
X S00010234
XBS00022630 XB
X S00023125
X S00012489
XB
XBS00003565 XBS
X 00004427
X 00010573
XBS
XBS00022673
7
XBS00011282
X 00004296
XBS
X 00022755
XBS
X 00018740
XBS
X 00011633
XBS
X 00022141
XBS
X 00003586
XBS
X 00021948
XBS
XBS00010703 XBS
X 00022476
XBS00021709 XBS
X 00012098
XBS00021960
XBS00009388 XBS
X 00021671
XBS00003655 XBS
X 00009378
XBS00022065 XBS
X 00022852
XBS00010287 XBS
X 00010802
X S00011183 XBS00023067
XB
XBS00009621
XBS00003592 XBS
X 00023064
X 00009816
XBS
XBS00011049 XBS
X 00018073
X 00022718
XBS
XBS00022963 XBS
X 00023077
XBS00009443 XBS
X 00003615
XBS00003637 XBS
X 00003770
XBS00011453 XBS
X 00011514
XBS00022780 XBS
X 00003904
X 00010311
XBS
X 00003740
XBS
XBS00012038 XBS
X 00017264
X 00000592
XBS
XBS00021971 XBS
X 00022017
X 00022400
XBS
XBS00022918 XBS
X 00023216
XBS00000701 XBS
X 00010590
X 00009414
XBS
X 00009589
XBS
XBS00009335
XBS00014912 XBS
X 00014954
X 00010017
XBS
XBS00010923 XBS
X 00022033
XBS00022763 XBS
X 00022068
XBS00022408 XBS
X 00022471
XBS00023098 XBS
X 00022520
XBS00022578 XBS
X 00022640
XBS00023096 XBS
X 00022040
XBS00022063 XBS
X 00022999
XBS00015364 XBS
X 00000865
XBS00003724 XBS
X 00003736
XBS00009373 XBS
X 00009382
XBS00009581 XBS
X 00009851
XBS00009931 XBS
X 00010033
XBS00010366 XBS
X 00010542
XBS00010581 XBS
X 00010636
XBS00010675 XBS
X 00010863
XBS00010886 XBS
X 00010929
XBS00010952 XBS
X 00011006
XBS00011123 XBS
X 00011635
XBS00011782 XBS
X 00011946
XBS00021869 XBS
X 00003879
XBS00010341 XBS
X 00010720
XBS00011474 XBS
X 00011750
XBS00010631 XBS
X 000111 08
XBS00021994 XBS
X 00011558
XBS00010124 XBS
X 00010301
XBS00010532 XBS
X 00012035
XBS00011931 XBS
X 00010044
X 00015089
XBS
X 00022075
XBS
XBS00022600 XBS
X 00023078
X 00021949
XBS
X 00009366
XBS
XBS00009311 XBS
X 00009607
XBS00010292 XBS
X 00011386
X 00003681
XBS
XBS00003705
X 00009789
XBS
X S00009719 XBS00003876
XB
X 00011205
XBS
XBS00003900 XBS
X 00011655
X 00016286
XBS
XBS00022293 XBS
X 00022663
XBS00023132 XBS
X 00022086
XBS00022103 XBS
X 00022662
X 00022652
XBS
XBS00022151
X 00022037
XBS
XBS00022542 XBS
X 00023174
7
X 00022699
XBS
XBS00004201 XB
X
X S00012140
X S00022647 XB
XB
X S00022886
X S00004698
XB
X S00001597 XB
XB
X S00003993
X S00022231 XB
XB
X S00022477
X S00012503
XB
X S00004195
XB
X S00021868 XB
XB
X S00022899
X S00022956
XB
X S00000703
XB
X S00022433 XB
XB
X S00022991
X S00021960
XB
X S00003655
XB
XBS00022559
X 00009821
XBS
X S00022157 XBS00022537
XB
X 00022850
XBS
XBS00011469 XBS
X 00011794
XBS00011829 XBS
X 00022036
X 00022291
XBS
XBS00011077 XBS
X 00011769
XBS00004065 XBS
X 00013935
XBS00022688 XBS
X 00009287
X 00021687
XBS
XBS00003783
XBS00003826 XBS
X 00009294
X 00021731
XBS
XBS00000622 XBS
X 00003711
XBS00010322 XBS
X 00012069
X 00021742
XBS
X S00021991 XBS00022277
XB
X S00022570 XBS00022814
XB
X S00009777 XBS00023094
XB
X S00022065
XBS00003942 XB
X
X S00023067
XB
X S00009621 XBS00011282
XB
X S00022689
XB
XBS00010337 XB
X
X S00012348
X S00022673 XBS00023127
XB
X S00023139
XB
XBS00003563
XBS00009335 XBS00012975
X
X S00023163
XB
XBS00022559
XBS00004065 XBS00022688
XBS00003705 XBS00021925
X
X S00022555 XB
XB
X S00022743
X S00023081
XB
X S00022357
XB
X S00003876 XBS00022151
XB
X S00023161
XB
XBS00000622 XB
X S00003580
XBS00003995 XB
X S00019894
XBS00021991 XBS00022277
X S00022814
XBS00022352 XB
XBS00023094
XBS00003783
XBS00022537
XBS00003563
Figure 3 Continued
ª 2012 The Authors
Plant Biotechnology Journal ª 2012 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd, Plant Biotechnology Journal, 11, 279–295
Wheat exome-based co-dominant SNPs 289
Ax
xC_6A SxR_6A
0
X S00011125 XBS00011445
XB
XBS00010922
XBS00010458
XBS00011125 XBS00012304
X
X S00021982
XB
5
10
15
20
25
30
35
40
45
50
55
60
65
70
75
80
85
90
95
100
XBS00012530
XBS00011642
X S00021982 XB
XB
X S00022843
XBS00003632 XBS00004278
XBS00009759 XBS00010401
XBS00011131 XBS00012150
XBS00012414
XBS00022946
XBS00022926
XBS00023192
XBS00009331 XBS00010600
XBS00011010 XBS00011436
XBS00003635 XBS00009584
XBS00022292 XBS00022660
XBS00022951
XBS00023054
5
XBS00003861 XBS00009664
XBS00009729 XBS00009746
XBS00009782 XBS00010360
XBS00010933 XBS00011711
XBS00009985 XBS00011034
X 00009319 XB
XBS
X S00009783
XBS00010777 XBS00010850
XBS00011861 XBS00003881
XBS00004377 XBS00010441
XBS00016670 XBS00021765
XBS00009988 XBS00011265
XBS00011789 XBS00013851
XBS00014317 XBS00001132
XBS00003581 XBS00009871
XBS00010497 XBS00010872
XBS00011122 XBS00014117
XBS00010749 XBS00014510
XBS00015710
XBS00001037
XBS00021999 XBS00023086
XBS00009376
XBS00011607
XBS00022704
XBS00022057
XBS00010811
XBS00022947 XBS00022031
XBS00022992
XBS00023089
XBS00023119
XBS00022120 XBS00022412
XBS00022553 XBS00022605
XBS00022879 XBS00022892
XBS00022894 XBS00022913
XBS00023183
XBS00023092
XBS00023020
XBS00022613 XBS00022628
XBS00022840 XBS00022836
XBS00001405 XBS00003616
XBS00003676 XBS00003877
XBS00003916 XBS00009261
XBS00010576 XBS00010586
XBS00010780 XBS00011696
XBS00011982 XBS00012028
XBS00010730 XBS00019008
X S00023033
XB
XBS00018855
XBS00022489 XBS00022592
XBS00003835 XBS00021961
XBS00012319
XBS00021965
120
XBS00023088
125
135
140
145
X
XBS0
0004009
X
XBS0
0012308
X S00003786
XB
XBS00003339 XBS00009351
XBS00010195 XBS00012050
XBS00010526 XBS00011578
XBS00012046
XBS00010408 XBS00011376
XBS00003818 XBS00003958
XBS00009314
XBS00003723 XBS00009300
XBS00003905
XBS00011962
XBS00010129 XBS00010326
XBS00011404
XBS00021704
XBS00022953 XBS00023197
XBS00022095 XBS00022164
Ax
xC_6D
X
XBS0
0021867 XBS00022481
XBS00009806
XBS00022795
X S00021983
XB
XBS00010742
X S00009514
XB
SxR_6D
XBS00009514
XBS00021983 XBS00022094
X
XBS0
0011604
X S00010600
XBS00010144 XB
X S00022951
XBS00011591 XB
X S00023054
XB
XBS00001234
X S00021999
XBS00021747 XB
X S00023086
XB
XBS00021343
X
XBS0
0012491
XBS00023196 XBS0
X
X
0003852
X S00003893 XBS0
XB
X
0010415
XBS00010420 XBS0
X
0010985
X S00011365 XBS0
XB
X
0011665
X
XBS0
0023223
XBS00004016 XBS0
X
0009844
X S00010179 XBS0
XB
X
0010602
X S00011624 XBS0
XB
X
0011995
X S00021674 XBS0
XB
X
0021686
X S00021698 XBS0
XB
X
0021705
X S00022772 XBS0
XB
X
0011036
X S00011301 XBS0
XB
X
0011809
X S00012093 XBS0
XB
X
0019726
X S00003897
XBS00003620 XB
X S00009695 XBS0
XB
X
0023208
X S00022096 XB
XB
X S00010223
X S00014588 XBS
XB
X 00010093
X 00022668
XBS
X 00022226
XBS
X S00022163 XBS
XB
X 00022370
XBS00010328 XB
X S00022117
X S00010537 XBS
XB
X 00003641
X S00014363 XBS
XB
X 00022155
X S00003671
XB
X S00003562 XBS
XB
X 00011429
X S00010993 XBS
XB
X 00011479
X 00023187
XBS
X 00023032
XBS
X
XBS0
0021677
XBS00021970
X 00022865
XBS
XBS00022621 XBS00022823
X
X S00010420
XB
XBS00022856
X
XBS0
0003891 XBS00012411
XBS00019487
XBS00012213
X S00022937
XBS00022832 XB
X S00022553
XBS00000043 XB
X S00022605 XBS00022913
XB
XBS00022480
X
X 00023224
XBS
X S00019487
XB
XBS00021862 XBS00021881
X 00022081
XBS
XBS00022937
X
X
XBS0
0021658
X
XBS0
0011458
XBS00010902 XBS00012454
X
X
XBS0
0022672
X
XBS0
0010618
115
130
X
XBS0
0010693
XBS00003786 XBS0
X
0011821
X S00018835 XBS0
XB
X
0003593
X S00003622 XBS0
XB
X
0003659
X S00003748 XBS0
XB
X
0003772
X S00003792 XBS0
XB
X
0003812
X S00009825 XBS0
XB
X
0010277
X S00010439 XBS0
XB
X
0010551
X S00011746 XBS0
XB
X
0015492
X
XBS0
0016587
X S00012481 XBS0
XB
X
0022232
X S00022491 XBS0
XB
X
0003785
X S00009795 XB
XB
XBS0000996
S00009967
X
XBS0
0010580
X S00010443 XBS0
XB
X
0010869
X S00011381 XBS0
XB
X
0022499
SxR_6B
X
XBS0
0010403
105
110
Ax
xC_6B
XBS00021965
X
XBS00000749 XB
X S00022372
XBS00023199
X
XBS0
0023066
XBS00023042 XBS0
X
X
0022444
X S00022240 XBS0
XB
X
0022529
X S00022437 XBS0
XB
X
0023021
X S00009548 XBS0
XB
X
0010627
X S00010870 XBS0
XB
X
0011603
X S00012034 XBS0
XB
X
0022828
X S00022278 XBS0
XB
X
0011795
X S00010121 XBS
XB
XBS0
X
00010342
0010342
XBS00003897 XBS00010223
X
X
XBS0
0012274 XBS00022709
X
XBS0
0023168
X
XBS0
0004012 XBS00021726
X
XBS0
0004272 XBS00021729
X
XBS0
0022345 XBS00022599
X
XBS0
0023050 XBS00023061
X
XBS0
0023217
X S00003562
XB
X S00003671 XBS00004016
XB
X S00022117
XB
X
XBS0
0011671
X S00022096
XB
X
XBS0
0022462
XBS00009390 XB
X S00009835
XBS00012510 XB
X S00010049
X
XBS0
0001068 XBS00003569
XBS00003697 XB
X S00010186
X S00011542
XBS00010787 XB
X S00011061
XB
X S00003653
XBS00003568 XB
XBS00003753 XB
X S00003827
XBS00003903 XB
X S00011111
XBS00012247 XB
X S00014600
X S00022204
XB
XBS00022206
XBS00023009
XBS00009390 XB
X S00009835
XBS00010049 XB
X S00010186
XBS00012510
X S00011542
XBS00010540 XB
XBS00003697 XB
X S00011061
XBS00003653 XB
X S00003753
XBS00003827 XB
X S00003903
XBS00004157 XBS00010516
XBS00011111 XB
X S00012247
XBS00014600 XB
X S00022204
XBS00022787
150
Figure 3 Continued
ª 2012 The Authors
Plant Biotechnology Journal ª 2012 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd, Plant Biotechnology Journal, 11, 279–295
290 Alexandra M. Allen et al.
Ax
xC_7A SxR_7A
0
5
10
X S00009404
XBS00003665 XB
X S00010783 XB
XB
X S00011724
X S00011813 XB
XB
X S00022146
X S00010887 XB
XB
X S00016937
X S00012368
XB
X S00009332
XB
X S00022705
XB
X S00022406
XB
X S00010006 XB
XB
X S00012133
X S00010796
XB
X S00009543 XB
XB
X S00011883
X S00022082 XB
XB
X S00022404
X S00009404 XB
XB
X S00009736
15
XBS00022386
X
X S00022538
XB
X S00016214 XB
XB
X S00022724
20
XBS00010783
X
X S00012033
XB
25
Ax
xC_7B
XBS00003494 XBS
X
X 00003760
X 00003830 XBS
XBS
X 00010557
X 00012117
XBS
X 00022009 XBS
XBS
X 00021972
X 00011069 XBS
XBS
X 00009290
X 00003350
XBS
X 00010500 XBS
XBS
X 00022045
X 00022106
XBS
X 00022390
XBS
X 00022053
XBS
X 00009556
XBS
SxR_7B
X S00023198
XB
XBS00012587 XB
X
X S00013172
X S00022522 XB
XB
X S00023034
X S00023166
XB
X S00019563
XB
XBS00010988
X
X S00023055
XB
45
50
X S00022076
XB
XBS00022406 XBS00022720
X
X S00022857 XB
XB
X S00023147
XBS00013872
X
X S00002556
XB
X S00011330
XB
X S00010796
XB
X S00022097
XB
X S00000345
XB
55
75
80
85
90
95
X S00022145
XB
X S00009978
XB
X S00010020 XB
XB
X S00010307
X S00010765
XB
X S00010605
XB
X S00022187
XB
X S00022435
XB
X S00021964 XB
XB
X S00022469
X S00022475 XB
XB
X S00022306
X S00021771 XB
XB
X S00021769
X S00021770
XB
X S00011072 XB
XB
X S00021789
X S00021997
XB
X S00022751
XB
X S00022757
XB
X S00022049 XB
XB
X S00022959
X S00011244
XB
X S00009477
XB
X S00011241
XB
X S00009346 XB
XB
X S00011248
X S00022079
XB
X S00022202 XB
XB
X S00022895
X S00009694 XB
XB
X S00009838
X S00011179 XB
XB
X S00011701
X S00022004
XB
X S00023128
XB
100
105
XBS00009457 XB
X
X S00018030
X S00021838 XB
XB
X S00022077
X S00010427
XB
X 00009398
XBS
40
70
XBS00001983 XB
X
X S00022948
X S00023108
XB
X S00022203
XB
35
65
X S00022610
XB
X S00022825 XB
XB
X S00023150
X S00023159
XB
XBS00012174
X
X S00022087 XB
XB
X S00022756
30
60
Ax
xC_7D SxR_7D
X S00004136
XB
X S00022442 XB
XB
X S00023172
X S00010988 XB
XB
X S00023055
X S00022076
XB
X S00012317
XB
X S00003894
XB
X S00010809 XB
XB
X S00022170
XBS00009403
X
X S00011872
XB
X S00009565
XB
X S00010064
XB
X S00022463
XB
X S00010142
XB
X S00022463
XB
XBS00021987 XB
X
X S00022511
X S00022721 XB
XB
X S00022875
X S00023045
XB
X S00023184
XB
X S00003945
XB
X S00021745
XBS00010071 XB
X S00012122
XBS00011507 XB
X S00003749 XB
XB
X S00009623
X S00011639
XB
X S00021861
XB
X S00003945
XB
X S00022145 XBS00022235
XB
XBS00022290 XB
X
X S00022907
XBS00021745
X
X S00010967 XB
XB
X S00012122
X S00021987 XB
XB
X S00022511
X S00023045
XB
X S00021859
XB
115
120
XBS00009464 XBS
X
X 00010082
X 00010454 XBS
XBS
X 00010660
X 00011065
XBS
X S00023166
XB
X S00023034
XB
X S00022087 XB
XB
X S00022756
X 00023059
XBS
X 00010327
XBS
X 00022195 XBS
XBS
X 00003664
X 00003672 XBS
XBS
X 00010560
X 00009879 XBS
XBS
X 00010348
X 00005062 XBS
XBS
X 00009455
X 00010208
XBS
X 00010181 XBS
XBS
X 00021666
X 00009245 XBS
XBS
X 00009379
X 00010819
XBS
X 00003756 XBS
XBS
X 00004376
X 00009619
XBS
X 00021717 XBS
XBS
X 00009794
X 0001074
XBS
7 7 XBS
X 00022175
X 00003703 XBS
XBS
X 00010689
X 00011571 XBS
XBS
X 00023069
X 00003649 XBS
XBS
X 00011767
X S00004171 XBS
XB
X 00004403
X S00010355 XBS
XB
X 00011217
X 00011399
XBS
XBS00004171 XBS
X
X 00004346
X S00010355
X S00004350 XB
XB
XBS00022097
X
X S00021692
XB
X S00022983 XB
XB
X S00023027
X S00009550
XB
X S00009975
XB
110
X 00010251
XBS
X 00009861
XBS
X 00023023 XBS
XBS
X 00022455
XBS00003843
X
X S00000816 XB
XB
X S00011244
X S00012302 XB
XB
X S00021659
X S00021668 XB
XB
X S0002174
7 9
125
X S00022202 XB
XB
X S00022895
130
X S00011350
XB
X S00011677
XB
135
140
145
150
155
160
165
170
X S00022427
XBS00022560 XB
X S00011597
XB
X S00010748
XB
X S00021962
XB
X S00023178 XB
XB
X S00023207
X S00021966
XB
X S00022617
XB
X S00022811
XB
X S00001450 XB
XB
X S00003621
X S00011622 XB
XB
X S00011926
X S00014199
XB
X S00013951
XB
X S00014246
XB
X S00023109
XB
X S00000663 XB
XB
X S00003720
X S00009797
XB
X S00021685 XB
XB
X S00021744
X S00003865
XB
X S00004348 XB
XB
X S00009283
X S00009886 XB
XB
X S00011689
X S00022269 XB
XB
X S00023200
X S00022284 XB
XB
X S00022447
X S00022119 XB
XB
X S00022137
XBS00021657
X
X S00002048 XB
XB
X S00003894
X S00022266
XB
X S00022169
X S00021663 XB
XB
X S00023218
XB
X S00009995
XB
175
180
185
190
195
200
XBS00003952
X
X S00022427
XB
20
Figure 3 Continued
ª 2012 The Authors
Plant Biotechnology Journal ª 2012 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd, Plant Biotechnology Journal, 11, 279–295
Wheat exome-based co-dominant SNPs 291
Table 3 Summary of linkage groups and
mapped loci
Avalon 9 Cadenza map
Number of
Chromosome
Savannah 9 Rialto map
Average
Number of
bristol SNP
Size
spacing between
bristol SNP
Size
Average
spacing
loci
(cM)
loci (cM)
loci
(cM)
between loci (cM)
1A
89
74.8
0.8
68
143.4
2.1
1B
214
126.4
0.6
50
115.9
2.3
1D
57
116.2
1.6
15
104.1
6.9
2A
82
132.2
1.6
98
211.1
2.2
2B
118
129.4
1.1
91
221.7
2.4
2D
63
77.7
1.2
13
49.8
3.8
3A
86
107.6
1.3
55
194.3
3.5
3B
136
154.5
1.1
34
205.0
6.0
3D
11
66.7
6.1
2
72.3
36.2
4A
71
136.3
1.9
14
157.7
11.3
4B
87
94.4
1.1
12
23.9
2.0
4D
8
60.3
7.5
4
1.3
0.3
5A
93
162.7
1.7
64
223.8
3.5
5B
172
239.0
1.4
51
147.2
2.9
5D
38
95.0
2.5
19
194.6
10.2
6A
136
141.1
1.0
23
111.4
4.8
6B
105
120.2
1.1
37
158.6
4.3
6D
31
91.6
3.0
28
135.6
4.8
7A
103
171.0
1.7
48
200.2
4.2
7B
64
82.8
1.3
14
56.1
4.0
7D
29
54.5
1.9
13
133.8
10.3
3.8
Total
1793
2434.4
1.3
753
2861.8
A genome
660
925.7
1.4
370
1241.9
3.4
B genome
896
946.7
1.1
289
928.4
3.2
D genome
237
562
2.2
94
691.4
7.4
Group 1
360
317.4
0.8
133
363.4
2.7
Group 2
263
339.3
1.3
202
482.6
2.4
Group 3
233
328.8
1.4
91
471.6
5.2
Group 4
166
291
1.8
30
182.9
6.1
Group 5
303
496.7
1.6
134
565.6
4.2
Group 6
272
352.9
1.3
88
405.6
4.6
Group 7
193
308.3
1.6
75
390.1
5.2
Characterisation of the validated co-dominant SNP assays
showed that their PIC scores and MAF were on average higher
than dominant SNP assays, suggesting they are highly useful
genetic markers for use on a range of materials. Analyses using
the contig sequences containing the different SNP types revealed
that co-dominant SNP assays were more likely to be located in
contigs returning no BLAST hit to either protein or nucleotide
databases, or outside coding regions in those contigs returning a
BLASTX hit. Our analysis is consistent with the hypothesis that a
proportion of the contigs used to develop co-dominant SNP
assays represent single-copy genes. These contigs most likely
represent genes that were lost before or during the domestication
process as they are found as single copies in both landraces, such
as Chinese Spring, and modern varieties. For those SNP contigs
with 15 9 Chinese Spring genomic coverage, it is quite possible
that while these are represented as three homoeologs in Chinese
Spring, they have undergone gene loss down to single copy in the
UK germplasm we have studied. Intracultivar heterogeneity has
been documented between elite inbred lines of crop species, and
there are reports of intervarietal gene loss in wheat (Haun et al.,
2011; Swanson-Wagner et al., 2010; Winfield et al., 2012).
In addition to the factors outlined above, the Chinese Spring
reference used to map the NimbleGen-captured sequences was
based upon cDNA. If only one homoeolog was sampled in the
cDNA data, and this was sufficiently divergent from the other two
homoeologous copies, we may have only been able to map
Illumina sequence data to that single genome. This would be the
case in many 3′ UTR regions that are more divergent than proteincoding sequence and have diverged sufficiently during evolution
to preclude their co-amplification in the KASPar PCR. This
homoeolog-specific amplification could fortuitously lead to the
development of co-dominant markers, yet BLAST analysis of such
sequences against the Chinese Spring genome would show them
to be present in three copies. In summary, investigations into the
average copy number of sequences used to develop co-dominant
SNP assays and the location of the SNP in the sequence suggests
that these SNPs are likely to reside in single-copy genes of as yet
unknown function, and/or three-copy genes which are sufficiently divergent that sequence data from one homoeolog does
not map to other copies. The uncharacterised nature of these
genes makes them an exciting and intriguing source of further codominant markers and scientific investigation.
ª 2012 The Authors
Plant Biotechnology Journal ª 2012 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd, Plant Biotechnology Journal, 11, 279–295
292 Alexandra M. Allen et al.
Proportion of total (%)
(a) 60.0
50.0
40.0
30.0
A genome
20.0
B genome
10.0
D genome
0.0
Dominant partially co- co-dominant
dominant
All loci
Dominant partially co- co-dominant
dominant
AxC
SxR
Marker type
(b) 40.0
Proportion of total (%)
All loci
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
Group 1
Group 2
Group 3
Group 4
Group 5
Dominant partially co- co-dominant
dominant
All loci
Dominant partially co- co-dominant
dominant
AxC
All loci
Group 6
Group 7
SxR
Marker type
Figure 4 Distribution of the different marker types across the (a) A, B and D linkage groups and (b) homoeologous chromosome groups of the
Avalon 9 Cadenza and Savannah 9 Rialto genetic maps.
Table 4 Summary statistics for mapped loci
Avalon 9 Cadenza
Number of
Minor allele
Polymorphism
loci
frequency
information content
1793
0.264
0.284
mapped loci
Co-dominant loci
672
0.277
0.290
Partially co-dominant
332
0.308
0.313
loci
Dominant loci
789
0.235
0.266
A genome
660
0.263
0.284
B genome
896
0.260
0.283
D genome
237
0.278
0.288
753
0.284
0.299
Savannah 9 Rialto
mapped loci
Co-dominant loci
395
0.291
0.300
Partially co-dominant
213
0.319
0.323
loci
Dominant loci
145
0.246
0.280
A genome
370
0.290
0.305
B genome
289
0.272
0.290
D genome
94
0.294
0.305
During this study, we have created two complementary genetic
maps, enabling 73% of our validated SNPs to be assigned a map
location. The co-dominant SNP loci had a similar pattern of
distribution between linkage groups compared with dominant
loci, suggesting that co-dominant SNP markers have a similar
distribution to the previously used dominant markers. Analysis of
the MAF and PIC scores of the different types of mapped SNPs
demonstrated that the co-dominant and partially co-dominant
SNP markers had higher levels of genetic diversity within the lines
tested, compared with dominant SNP assays, suggesting that codominant SNP assays are highly suitable for use as genetic
markers.
The two genetic maps aligned well with each other, with a
similar assignment and order of common markers. Clustering of
SNP markers was observed in both linkage maps, indicating that
despite the relatively large mapping populations used, a lack of
recombination events between these markers may affect map
resolution. This may be overcome by mapping these markers
against a larger number of individuals. Preliminary results indicate
that mapping a subset of 223 evenly spaced A 9 C markers on
566 individuals from an extended A 9 C population reduced the
proportion of completely linked markers from 50.4% to 44.9%,
and it is likely that this figure could be further decreased by
specifically targeting clustered markers. However, despite the
high proportion of clustered markers, 89% of the remaining
markers map to within 10 cM of the next marker, suggesting that
these provide good overall coverage of the genome, with few
gaps. When co-dominant and dominant markers were compared
separately, similar proportions of markers were observed to map
to within 10 cM of each other (88% and 92%, respectively),
suggesting that both marker types are similarly distributed across
the map.
Both maps had a relatively low proportion of D genome loci;
this has been observed in previous studies and is likely to relate to
a lower level of diversity found in the D genome due to the effects
of the genetic bottleneck that accompanied the domestication of
hexaploid wheat (Allen et al., 2011; Caldwell et al., 2004; Chao
ª 2012 The Authors
Plant Biotechnology Journal ª 2012 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd, Plant Biotechnology Journal, 11, 279–295
Wheat exome-based co-dominant SNPs 293
25.0
25.0
20.0
Co-dominant loci
15.0
Partially codominant loci
10.0
5.0
Proprtion of total (%)
(b) 30.0
30.0
Proportion of total (%)
(a) 35.0
Dominant loci
20.0
15.0
A genome loci
10.0
B genome loci
5.0
D genome loci
0.0
0.0
Minor allele frequency
Minor allele frequency
(d) 70.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
Co-dominant loci
Partially codominant loci
Dominant loci
Polymorphism information content
et al., 2009). Although the mean MAF and PIC scores were
similar for A, B and D genome loci, some differences were
observed in the distributions of these measurements. The results
for A and B genome markers were similar; however, loci assigned
to the D genome had a higher proportion of high MAF and PIC
scores compared with A and B genome loci. This is the opposite
to what has been detected in previous studies (Akhunov et al.,
2010; Chao et al., 2009) and suggests that, although the lower
genetic diversity within the D genome hinders SNP discovery and
marker development, the D genome SNPs identified by our
pipeline are as informative and useful as loci from the A and B
genome.
This study has described the design, implementation and validation of a pipeline designed to identify gene-based co-dominant
SNP assays from genomic DNA sequence data. The validation
results suggest that this approach is highly efficient and the
resulting co-dominant SNP markers are evenly distributed across
the genome with relatively high MAF and PIC scores. As such,
these should prove a highly valuable resource for use in breeding
programmes. The construction of two complementary genetic
maps has maximised the amount of mapped SNP loci and allowed
comparisons between UK breeding materials. The genotype data
generated in this study for 47 widely used wheat lines, combined
with genetic map locations for SNP markers, should enable wheat
researchers to target their efforts to regions of interest and enable
QTL studies and marker-assisted selection. The markers described
in this study will be useful in linking the genetic map with the
developing physical maps and so will enhance the possibility of
efficient map-based cloning in hexaploid wheat. The entire data
set presented in this study has been made publicly available via
the provision of supplementary data sets and an interactive
website (http://www.cerealsdb.uk.net/), to make this resource as
accessible and useful as possible. These new co-dominant wheat
SNP-based markers will be useful on a number of genotyping
platforms and germplasm collections and hence should be a
powerful new tool for wheat breeders and researchers alike. In
addition, the pipeline developed here to identify co-dominant
SNP markers should be applicable to other polyploid crops where
Proportion of total (%)
Figure 5 Distribution of minor allele frequency
(MAF) and polymorphism information content
(PIC) scores among the 47 wheat varieties. Loci
were separated into subgroups according to (a,c)
marker type and (b,d) genome.
Proportion of total (%)
(c) 80.0
60.0
50.0
40.0
30.0
A genome loci
20.0
B genome loci
10.0
D genome loci
0.0
Polymorphism information content
SNP discovery and marker development have previously been
challenging (Cordeiro et al., 2006; Trick et al., 2009; Yu et al.,
2012).
Experimental procedures
Plant material
Forty-seven wheat varieties were grown for DNA extraction (for
details see Data S5). The Avalon 9 Cadenza doubled-haploid
(DH) population was supplied by the John Innes Centre and was
developed by Clare Ellerbrook, Liz Sayers and the late Tony
Worland as part of a Defra-funded project led by ADAS. The
parents were originally chosen (to contrast for canopy architecture traits) by Steve Parker (CSL), Tony Worland and Darren Lovell
(Rothamsted Research). The Savannah 9 Rialto DH population
was supplied by Limagrain UK Limited (Woolpit, Suffolk, UK). All
plants were grown in pots in a peat-based soil and maintained in
a glasshouse at 15–25 °C under a light regime of 16 h light and
8 h dark. Leaf tissues were harvested from 6-week-old plants and
immediately frozen on liquid nitrogen and stored at 80 °C until
nucleic acid extraction. Genomic DNA was prepared from leaf
tissue using a phenol–chloroform extraction method (Sambrook
et al., 1989).
Preparation of NimbleGen libraries
The NimbleGen capture array was designed to capture a significant
proportion of the wheat exome and was developed using a generich assembly of 454 titanium sequence data from normalised and
non-normalised cDNA libraries of Chinese Spring line 42, publically
available EST sequences and the NCBI unigene set (Winfield et al.,
2012). The resulting assembly was used by NimbleGen to design an
array containing 132 605 features with an average length of
426 bp (NimbleGen array reference 100819_Wheat_Hall_cap_HX1). NimbleGen sequence libraries were prepared for eight
wheat varieties (Alchemy, Avalon, Cadenza, Hereward, Rialto,
Robigus, Savannah and Xi19) as described by Winfield et al.
(2012). Post-capture-enriched sequencing libraries were subjected
to 110 bp of paired end sequencing on a Illumina Genome
ª 2012 The Authors
Plant Biotechnology Journal ª 2012 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd, Plant Biotechnology Journal, 11, 279–295
294 Alexandra M. Allen et al.
Analyser (GAIIx) using Illumina TruSeq v5 Cluster Generation
(Illumina Inc., San Diego, CA) and sequencing reagents following
the manufacturers preparation guides for paired end runs (Part
15019435 RevB, Oct2010 and Part 15013595 Rev C, Feb 2011,
respectively).
SNP discovery
After pre-processing of reads, where adapter sequences were
removed, the data were submitted to a custom pipeline (Winfield
et al., 2012). NGS sequences generated from the eight varieties
were mapped to the NimbleGen array reference using BWA
version 0.5.9-r16 (Li and Durbin, 2009) with a seed length of 32
bases, and the resulting SAM files were used for downstream
analysis. Uniquely mapped reads were analysed using a series of
custom PERL scripts designed to identify only differences between
varieties as opposed to those between each variety and the
reference sequence. This enabled the exclusion of homoeologous
SNPs (which are not useful markers), which were removed from
the SNP discovery pipeline. SNPs were called where there were at
least two alternative bases predicted at a reference position. An
additional constraint on SNP prediction required each SNP to be
represented by two or more independent reads or 2% of all reads
examined (whichever was the greater). Only bases that were
located at the centre of a three-base window of PHRED
quality 20 were included in the analysis. Sequences were
discarded if they displayed more than 10% sequence variation
from the reference over their length or if they mapped equally
well to more than one locus, as the mapping in these situations
could be regarded as uncertain. In cases where multiple reads
started at the same position in the reference, all but one were
ignored to guard against clonal reads being sampled more than
once. All NGS data generated for this study will be available at:
http://www.cerealsdb.uk.net. In addition, the Illumina fastq files
and associated metadata have been uploaded to NCBI Sequence
Read Archive (SRA) under the study accession SRP011067.
Accession numbers of fastq files for each variety are as follows:
Alchemy (SRR417586.1), Avalon (SRR417587.1), Cadenza
(SRR417953.1), Hereward (SRR417954.1), Rialto (SRR417955.1),
Robigus (SRR418209.1), Savannah (SRR418210.1) and Xi19
(SRR418211.1).
SNP validation
For each putative varietal SNP, two allele-specific forward primers
and one common reverse primer (Data S1) were designed
(KBioscience, Hoddesdon, UK). Genotyping reactions were performed in a Hydrocycler (KBioscience) in a final volume of 1 lL
containing 1 9 KASP 1536 Reaction Mix (KBioscience), 0.07 lL
assay mix (containing 12 lM each allele-specific forward primer
and 30 lM reverse primer) and 10–20 ng genomic DNA. The
following cycling conditions were used: 15 min at 94 °C; 10
touchdown cycles of 20 s at 94 °C, 60 s at 65–57 °C (dropping
0.8 °C per cycle); and 26–35 cycles of 20 s at 94 °C, 60 s at
57 °C. Fluorescence detection of the reactions was performed
using a Omega Pherastar scanner (BMG LABTECH GmbH,
Offenburg, Germany), and the data were analysed using the
KlusterCaller 1.1 software (KBioscience).
Genetic map construction
The software programme MapDisto v. 1.7 (Lorieux, 2012) was
used to place the SNP markers in the previously established
genetic map for Avalon 9 Cadenza (http://www.wgin.org.uk/
resources/MappingPopulation/TAmapping.php). A chi-square test
was performed on all loci to test for segregation distortion from
the expected 1 : 1 ratio of each allele in a DH population, and any
loci showing significant distortion were removed from the data
set before constructing the linkage groups. Loci were assembled
into linkage groups using likelihood odds (LOD) ratios with a LOD
threshold of 6.0 and a maximum recombination frequency
threshold of 0.40. The linkage groups were ordered using the
likelihoods of different locus-order possibilities and the iterative
error removal function (maximum threshold for error probability
0.05) in MapDisto and drawn in MapChart (Voorrips, 2002). The
Kosambi mapping function (Kosambi, 1944) was used to calculate map distances (cM) from recombination frequency.
SNP data analysis
Summary statistics (MAF and PIC estimates) were calculated for
loci using Powermarker 3.25 software (Liu and Muse, 2005).
Acknowledgements
We are grateful to the Biotechnology and Biological Sciences
Research Council, UK, and the Crop Improvement Research Club
(CIRC) for providing the funding for this work (awards BB/
I003207/1, BB/I017496/1). We are grateful to the Wheat Genetic
Improvement Network for making the mapping data relating to
the Avalon 9 Cadenza population public. For further details of
the Avalon 9 Cadenza mapping population, please refer to the
Wheat Genetic Improvement Network web site at: http://www.
wgin.org.uk/resources/MappingPopulation/TAmapping.php. We
also thank Limagrain UK limited for supplying the Savannah 9 Rialto mapping population and related marker data.
References
Adams, K.L. and Wendel, J.F. (2005) Novel patterns of gene expression in
polyploid plants. Trends Genet. 21, 539–543.
Akhunov, E., Nicolet, C. and Dvorak, J. (2009) Single nucleotide polymorphism
genotyping in polyploidy wheat with the Illumina GoldenGate assay. Theor.
Appl. Genet. 119, 507–517.
Akhunov, E.D., Akhunova, A.R., Anderson, O.D., Anderson, J.A., Blake, N.,
Clegg, M.T., Coleman-Derr, D., Conley, E.J., Crossman, C.C., Deal, K.R.,
Dubcovsky, J., Gill, B.S., Gu, Y.Q., Hadam, J., Heo, H., Huo, N., Lazo, G.R.,
Luo, M.C., Ma, Y.Q., Matthews, D.E., McGuire, P.E., Morrell, P.L., Qualset,
C.O., Renfro, J., Tabanao, D., Talbert, L.E., Tian, C., Toleno, D.M.,
Warburton, M.L., You, F.M., Zhang, W. and Dvorak, J. (2010) Nucleotide
diversity maps reveal variation in diversity among wheat genomes and
chromosomes. BMC Genomics, 11, 702.
Akhunova, A.R., Matniyazov, R.T., Liang, H. and Akhunov, E.D. (2010)
Homoeolog-specific transcriptional bias in allopolyploid wheat. BMC
Genomics, 11, 505.
Allen, A.M., Barker, G.L., Berry, S.T., Coghill, J.A., Gwilliam, R., Kirby, S.,
Robinson, P., Brenchley, R.C., D’Amore, R., McKenzie, N., Waite, D., Hall, A.,
Bevan, M., Hall, N. and Edwards, K.J. (2011) Transcript-specific, singlenucleotide polymorphism discovery and linkage analysis in hexaploid bread
wheat (Triticum aestivum L.). Plant Biotechnol. J. 9, 1086–1099.
Altschul, S.F., Gish, W., Miller, W., Myers, E.W. and Lipman, D.J. (1990) Basic
local alignment search tool. J. Mol. Biol. 215, 403–410.
Berkman, P.J., Lai, K., Lorenc, M.T. and Edwards, D. (2012) Next generation
sequencing applications for wheat crop improvement. Am. J. Bot. 99, 365–
371.
Biesecker, L.G., Shianna, K.V. and Mullikin, J.C. (2011) Exome sequencing: the
expert view. Genome Biol. 12, 128.
Caldwell, K.S., Dvorak, J., Lagudah, E.S., Akhunov, E., Luo, M.C., Wolters, P.
and Powell, W. (2004) Sequence polymorphism in polyploid wheat and their
D-genome diploid ancestor. Genetics, 167, 941–947.
ª 2012 The Authors
Plant Biotechnology Journal ª 2012 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd, Plant Biotechnology Journal, 11, 279–295
Wheat exome-based co-dominant SNPs 295
Chao, S., Zhang, W., Akhunov, E., Sherman, J., Ma, Y., Luo, M.C.
and Dubcovsky, J. (2009) Analysis of gene-derived SNP marker
polymorphism in US wheat (Triticum aestivum L.) cultivars. Mol. Breed.
23, 23–33.
Chao, S., Dubcovsky, J., Dvorak, J., Luo, M.C., Baenziger, S.P., Matnyazov, R.,
Clark, D.R., Talbert, L.E., Anderson, J.A., Dreisigacker, S., Glover, K., Chen, J.,
Campbell, K., Bruckner, P.L., Rudd, J.C., Haley, S., Carver, B.F., Perry, S.,
Sorrells, M.E. and Akhunov, E.D. (2010) Population- and genome-specific
patterns of linkage disequilibrium and SNP variation in spring and winter
wheat (Triticum aestivum L.). BMC Genomics, 11, 727.
Cordeiro, G.M., Eliott, F., McIntyre, C.L., Casu, R.E. and Henry, R.J. (2006)
Characterisation of single nucleotide polymorphisms in sugarcane ESTs.
Theor. Appl. Genet. 113, 331–343.
Dixon, J., Braun, H.J. and Crouch, J. (2009) Transitioning wheat research to
serve the future needs of the developing world. In: Wheat Facts and
Futures (Dixon, J., Braun, H.J. and Kosina, P., eds), pp. 1–19. Mexico:
CIMMYT.
Dubcovsky, J. and Dvorak, J. (2007) Genome plasticity a key factor in the
success of polyploid wheat under domestication. Science, 316, 1862–1866.
Haudry, A., Cenci, A., Ravel, C., Bataillon, T., Brunel, D., Poncet, C., Hochu, I.,
Poirier, S., Santoni, S., Glémin, S. and David, J. (2007) Grinding up wheat: a
massive loss of nucleotide diversity since domestication. Mol. Biol. Evol. 24,
1506–1517.
Haun, W.J., Hyten, D.L., Xu, W.W., Gerhardt, D.J., Albert, T.J., Richmond, T.,
Jeddeloh, J.A., Jia, G., Springer, N.M., Vance, C.P. and Stupar, R.M.
(2011) The composition and origins of genomic variation among
individuals of the soybean reference cultivar Williams 82. Plant Physiol.
155, 645–655.
Kaur, S., Francki, M.G. and Forster, J.W. (2012) Identification, characterization
and interpretation of single-nucleotide sequence variation in allopolyploid
crop species. Plant Biotechnol. J. 10, 125–138.
Kosambi, D.D. (1944) The estimation of map distances from recombination
values. Ann. Eugen. 12, 172–175.
Li, H. and Durbin, R. (2009) Fast and accurate short read alignment with
Burrows-Wheeler transform. Bioinformatics, 25, 1754–1760.
Liu, K. and Muse, S.V. (2005) PowerMarker: an integrated analysis environment
for genetic marker analysis. Bioinformatics, 21, 2128–2129.
Liu, B., Xu, C., Zhao, N., Qi, B., Kimatu, J.N., Pang, J. and Han, F. (2009) Rapid
genomic changes in polyploid wheat and related species: implications for
genome evolution and genetic improvement. J. Genet. Genomics, 36, 519–
528.
Lorieux, M. (2012) MapDisto: fast and efficient computation of genetic linkage
maps. Mol. Breeding, 30, 1231–1235.
Paux, E., Faure, S., Choulet, F., Roger, D., Gauthier, V., Martinant, J.P.,
Sourdille, P., Balfourier, F., Le Paslier, M.C., Chauveau, A., Cakir, M.,
Gandon, B. and Feuillet, C. (2010) Insertion site-based polymorphism markers
open new perspectives for genome saturation and marker-assisted selection
in wheat. Plant Biotechnol. J. 8, 196–210.
Paux, E., Sourdille, P., Mackay, I. and Feuillet, C. (2011) Sequence-based marker
development in wheat: advances and applications to breeding. Biotechnol.
Adv. http://dx.doi.org/10.1016/j.bbr.2011.03.031.
Reynolds, M., Foulkes, M.J., Slafer, G.A., Berry, P., Parry, M.A.J., Snape, J.W.
and Angus, W.J. (2009) Raising yield potential in wheat. J. Exp. Bot. 60,
1899–1918.
Sambrook, J., Fritsch, E.F. and Maniatis, T. (1989) Molecular Cloning:
A Laboratory Manual, 2nd edn. Cold Spring Harbor: Cold Spring Harbor
Laboratory Press.
Swanson-Wagner, R.A., Eichten, S.R., Kumari, S., Tiffin, P., Stein, J.C., Ware, D.
and Springer, N.M. (2010) Pervasive gene content variation and copy number
variation in maize and its undomesticated progenitor. Genome Res. 20,
1689–1699.
Trick, M., Long, Y., Meng, J. and Bancroft, I. (2009) Single nucleotide
polymorphism (SNP) discovery in the polyploid Brassica napus using Solexa
transcriptome sequencing. Plant Biotechnol. J. 7, 334–346.
Trick, M., Adamski, N., Mugford, S.G., Jiang, C., Febrer, M. and Uauy, C. (2012)
Combining SNP discovery from next-generation sequencing data with bulked
segregant analysis (BSA) to fine-map genes in polyploid wheat. BMC Plant
Biol. 12, 1–14.
Voorrips, R.E. (2002) MapChart: software for the graphical presentation of
linkage maps and QTLs. J. Hered. 93, 77–78.
Winfield, M.O., Wilkinson, P.A., Allen, A.M., Barker, G.L.A., Coghill, J.A.,
Burridge, A., Hall, A., Brenchley, R.C., D’Amore, R., Hall, N., Bevan, M.,
Richmond, T., Gerhardt, D.J., Jeddeloh, J.A. and Edwards, K.J. (2012)
Targeted re-sequencing of the allohexaploid wheat exome. Plant Biotechnol.
J. 10, 733–742.
Yu, J.Z., Kohel, R.J., Fang, D.D., Cho, J., Van Deynze, A., Ulloa, M., Hoffman,
S.M., Pepper, A.E., Stelly, D.M., Jenkins, J.N., Saha, S., Kumpatla, S.P., Shah,
M.R., Hugie, W.V. and Percy, R.G. (2012) A high-density simple sequence
repeat and single nucleotide polymorphism genetic map of the tetraploid
cotton genome. Genes Genomes Genetics, 2, 43–58.
Supporting information
Additional Supporting information may be found in the online
version of this article:
Data S1 KASPar assay details for 1190 SNPs designed as part of
this study.
Data S2 Genotyping results of a panel of 47 wheat varieties
screened with 1138 KASPar assays.
Data S3 KASPar assay details for all assays, including genetic map
position.
Data S4 Mapping data for all assays mapped on the
Avalon 9 Cadenza and Savannah 9 Rialto cross.
Data S5 Details of the 47 wheat varieties used in this study.
ª 2012 The Authors
Plant Biotechnology Journal ª 2012 Society for Experimental Biology, Association of Applied Biologists and Blackwell Publishing Ltd, Plant Biotechnology Journal, 11, 279–295