545
Distribution of DArT, AFLP, and SSR markers in a
genetic linkage map of a doubled-haploid
hexaploid wheat population
Kassa Semagn, Åsmund Bjørnstad, Helge Skinnes, Anne Guri Marøy,
Yalew Tarkegne, and Manilal William
Abstract: A genetic linkage mapping study was conducted in 93 doubled-haploid lines derived from a cross between
Triticum aestivum L. em. Thell ‘Arina’ and a Norwegian spring wheat breeding line, NK93604, using diversity arrays
technology (DArT), amplified fragment length polymorphism (AFLP), and simple sequence repeat (SSR) markers. The
objective of this study was to understand the distribution, redundancy, and segregation distortion of DArT markers in
comparison with AFLP and SSR markers. The map contains a total of 624 markers with 189 DArTs, 165 AFLPs and
270 SSRs, and spans 2595.5 cM. All 3 marker types showed significant (p < 0.01) segregation distortion, but it was
higher for AFLPs (24.2%) and SSRs (22.6%) than for DArTs (13.8%). The overall segregation distortion was 20.4%.
DArTs showed the highest frequency of clustering (27.0%) at < 0.5 cM intervals between consecutive markers, which
is 3 and 15 times higher than SSRs (8.9%) and AFLPs (1.8%), respectively. This high proportion of clustering of
DArT markers may be indicative of gene-rich regions and (or) the result of inclusion of redundant clones in the
genomic representations, which was supported by the presence of very high correlation coefficients (r > 0.98) and
multicollinearity among the clustered markers. The present study is the first to compare the utility of DArT with AFLP
and SSR markers, and the present map has been successfully used to identify novel QTLs for resistance to Fusarium
head blight and powdery mildew and for anther extrusion, leaf segment incubation, and latency.
Key words: ‘Arina’, diversity arrays technology, double haploid, genetic map, marker clustering, microsatellite.
Résumé : Les auteurs ont réalisé une cartographie génétique sur 93 lignées haploïdes doublées dérivées d’un croisement entre le blé d’automne Triticum aestivum L. em. Thell ‘Arina’ et NK93604, une lignée norvégienne de blé de
printemps, au moyen de marqueurs DArT (« diversity arrays technology »), AFLP (« amplified fragment length polymorphism ») et microsatellites (SSRs). L’objectif de ce travail était d’étudier la distribution, la redondance et la distorsion de la ségrégation des marqueurs DArT par rapport aux AFLP et SSR. La carte totalisait 624 marqueurs dont
189 DArT, 165 AFLP et 270 SSR et s’étendait sur 2 595,5 cM. Les 3 types de marqueurs souffraient de distorsion
(à p < 0,01), mais celle-ci était plus importante chez les AFLP (24,2 %) et les SSR (22,6 %) que chez les marqueurs
DArT (13,8 %). Globalement, 20,4 % des marqueurs montraient une distorsion de leur ségrégation. Les marqueurs
DArT présentaient la plus forte incidence de groupement de marqueurs (27,0 %), avec moins de 0,5 cM entre marqueurs voisins, ce qui est 3 à 15 fois plus que pour les marqueurs SSR (8,9 %) ou AFLP (1,8 %). Cette forte proportion de marqueurs groupés pourrait découler de régions riches en gènes ou l’inclusion de clones redondants au sein des
représentations génomiques. Cette dernière hypothèse était supportée par des coefficients de corrélation très élevés (r >
0,98) et une colinéarité multiple parmi les marqueurs groupés. La présente étude est la première à comparer l’utilité
des marqueurs DArT par rapport aux AFLP et SSR. De plus, la présente carte a été employée avec succès pour identifier de nouveaux QTL pour la résistance à la fusariose de l’épi et à l’oïdium ainsi que des QTL pour l’extrusion des
anthères, la durée d’incubation et la latence des segments foliaires.
Mots clés : ‘Arina’, « diversity arrays technology », haploïde doublé, carte génétique, groupement de marqueurs,
microsatellite.
[Traduit par la Rédaction]
Semagn et al.
555
Received 20 September 2005. Accepted 13 December 2005. Published on the NRC Research Press Web site at http://genome.nrc.ca
on 8 June 2006.
K. Semagn, Å. Bjørnstad1, H. Skinnes, A.G. Marøy, and Y. Tarkegne. Department of Plant and Environmental Sciences,
Norwegian University of Life Sciences, P.O. Box 5003, N-1432, Ås, Norway.
M. William. Centro Internacional de Mejoramiento de Maizy Trigo (CIMMYT), Apdo Postal 6-641, 06600 Mexico, D.F. Mexico.
1
Corresponding author (e-mail: [email protected]).
Genome 49: 545–555 (2006)
doi:10.1139/G06-002
© 2006 NRC Canada
546
Introduction
Hexaploid wheat (Triticum aestivum L. em. Thell) is one
of the world’s most important food crops, supplying nearly
55% of the carbohydrates consumed worldwide (Gupta et al.
1999). It is an allohexaploid (2n = 6x = 42) with 3 distinct
but genetically related (homoeologous) genomes, A, B, and
D, each with 7 chromosomes. Wheat has a large genome,
16 million kilobases per haploid cell (Bennett and Smith
1976), with a <2.7% gene-containing fraction and >80% repetitive DNA.
The advent of DNA marker technology in the 1980s offered a large number of environmentally insensitive genetic
markers that could be generated to follow the inheritance of
important agronomic traits (Gupta et al. 1999; Peleman and
van der Voort 2003). Restriction fragment length polymorphisms (RFLPs) (Botstein et al. 1980), random amplified
polymorphic DNA (RAPD) (Williams et al. 1990), microsatellite or simple sequence repeats (SSRs) (Akkaya et al.
1992), sequence-tagged-sites (STS) (Talbert et al. 1994), and
amplified fragment length polymorphisms (AFLPs) (Vos et
al. 1995) are the most commonly used marker types for
wheat map construction. Microsatellite markers remain a
standard for map construction, as they are highly polymorphic even between closely related lines, require a small
amount of DNA, can be easily automated, allow highthroughput screening, can be exchanged between laboratories, and are highly transferable between populations (Gupta
et al. 1999). AFLP offers a high level of utility for various
purposes and has been used to generate large numbers of
markers for the construction of high-density genetic maps
(e.g., Barrett and Kidwell 1998; Parker et al. 1998; Huang et
al. 2000; Schwarz et al. 2000; Chalmers et al. 2001). Diversity arrays technology (DArT) is a microarray hybridizationbased technique that enables the simultaneous typing of
several hundred polymorphic loci spread over the genome
without the need of prior sequence information (Jaccoud et
al. 2001; Wenzl et al. 2004). DArT has recently been used in
genetic mapping and fingerprinting studies in Arabidopsis
(Wittenberg et al. 2005), barley (Wenzl et al. 2004), rice
(Jaccoud et al. 2001), cassava (Xia et al. 2005), and wheat
(Akbari et al. 2006). DArT is a high-throughput, quick, and
highly reproducible method.
Several genetic maps have been reported for all hexaploid
wheat chromosomes (Liu and Tsunewaki 1991; Gale et al.
1995; Roder et al. 1998a; Li et al. 1999; Messmer et al.
1999; Mingeot and Jacquemin 1999; Gupta et al. 2002;
Paillard et al. 2003; Somers et al. 2004; Song et al. 2005).
The International Triticeae Mapping Initiative (ITMI) population (Synthetic × ‘Opata’; T. aestivum) is one of the most
polymorphic wheat-mapping populations and has been extensively mapped with RFLP, AFLP, and SSR markers (Nelson et al. 1995a, 1995b, 1995c; Van Deynze et al. 1995;
Marino et al. 1996; Roder et al. 1998a; Song et al. 2005). To
raise the density of microsatellite markers available on a
wheat genetic map, Somers et al. (2004) constructed a highdensity microsatellite consensus map by mapping common
microsatellites on each chromosome in 4 different mapping
populations. DArT has the potential for increasing marker
density within a short time and at low cost (Jaccoud et al.
2001; Wenzl et al. 2004). The cost of DArT per data point
Genome Vol. 49, 2006
has been reported to be 10-fold lower than the cost of SSR
(Xia et al. 2005). However, the distribution of loci over the
genome has not been compared with other marker technologies. The objective of this study was, therefore, to construct
a genetic linkage map in a doubled-haploid (DH) population
using DArT, AFLP and SSR markers to understand the distribution, redundancy, and segregation distortion of DArT
markers in comparison with AFLP and SSR markers.
Materials and methods
Plant materials and DNA extraction
A DH mapping population was developed from a cross
between 2 parents of T. aestivum, a winter wheat cultivar
‘Arina’ and NK93604 (a Norwegian spring wheat breeding
line) using the wheat × maize system (Laurie and Bennett
1988). ‘Arina’ was released in 1981 and has covered more
than 40% of the wheat acreage of Switzerland since 1985. It
has excellent spike resistance against leaf and glume blotch
caused by Stagonospora nodorum, and a good level of resistance to Fusarium head blight (FHB) (Paillard et al. 2003).
‘Arina’ was chosen as a donor parent owing to its good level
of resistance to FHB and to its greater ability to adapt to the
Scandinavian climatic conditions than other exotic hexaploid
wheat cultivars. NK93604 is a well-adapted and highly productive breeding line in Norway. Genomic DNA of the parents and 93 DH lines was extracted from young leaves using
the DNeasy Plant DNA extraction kit (Qiagen, Mississauga,
Ont.).
AFLP assay
AFLP analysis was carried out according to the methods
of Vos et al. (1995) with some modifications as described by
Grønnerød et al. (2002). MseI and PstI were used as
frequent- and rare-cutter enzymes, respectively. Selective
amplification was performed with primers having 3 selective
nucleotides, with the PstI primers labeled with 6-carboxyfluorescein (6-FAM), hexachloro-6-carboxy-fluorescein
(HEX), or tetrachloro-6-carboxy-fluorescein (TET), whereas
the MseI primers were unlabelled. Selective amplification
was performed in 10 µL reaction volumes that contained
0.25 µmol/L of each primer, 200 µmol/L each dNTP
(Amersham Biosciences Europe GmbH, Freiburg, Germany), 1× PCR buffer (50 mmol/L KCl, 1.5 mmol/L MgCl2,
10 mmol/L Tris–HCl (pH 9.0)), 0.5 U Taq DNA polymerase
(Amersham Biosciences), and 2.5 µL template DNA. The selective amplification was carried out using a “touchdown”
profile of 1 cycle at 94 °C for 30 s, 65 °C for 30 s, and
72 °C for 1 min, followed by 9 cycles over which the annealing temperature was decreased by 1 °C/cycle, and a final
step of 23 cycles of 94 °C for 30 s, 56 °C for 30 s, and
72 °C for 1 min. All PCRs were carried out using an MJ
Research Tetrad thermal cycler (MJ Research, Waltham,
Mass.).
AFLP fragments were separated on an ABI PRISM™ 377
DNA Sequencer (PE Applied Biosystems, Foster City,
Calif.) using 4.5% polyacrylamide denaturing gels (acrylamide:bisacrylamide, 19:1) as described in the user manual.
GS-500 (TAMRA labeled) size standard from ABI was
loaded into each lane to facilitate the semiautomatic analysis
of the gel and the sizing of the fragments. Semiautomated
© 2006 NRC Canada
Semagn et al.
AFLP fragment analysis was performed with GeneScan™
3.1 and Genotyper™ 2.1 programs as described in the user
manual, with some modification as reported by Schwarz et
al. (2000).
Ninety-six MseI and PstI AFLP primer combinations were
screened for polymorphism and 45 informative primer pairs
were used to genotype the mapping population. The nomenclature for an AFLP marker is derived from the enzyme
combination, the primer combinations, and the molecular
mass of the product. The standard list for AFLP primer nomenclature provided by KeyGene (http://wheat.pw.usda.gov/
ggpages/keygeneAFLPs.html) was employed.
Microsatellite assay
A total of 874 wheat microsatellite (SSR) primers originated from 5 different groups were screened for polymorphism: 150 BARC primers from the Beltsville Agricultural
Research Center (Song et al. 2002, 2005), 21 CFA and 50
CFD primers from INRA Clermont-Ferrand (Guyomarc’h et
al. 2002; Sourdille et al. 2003), 195 DuPw primers from
DuPont company (Eujayl et al. 2002; DuPont, unpublished
data; Dreisigacker et al. 2005), 50 GDM and 232 GWM
primers from Institut fur Pflanzengenetik und Kulturpflanzenforschung (Roder et al. 1998a; Pestsova et al. 2000), and
176 WMC primers from the Wheat Microsatellite Consortium (Gupta et al. 2002). Three hundred polymorphic primers synthesized by Invitrogen Life Technologies (Carlsbad,
Calif.) were used for segregation data collection. Microsatellite analysis was performed using the fluorescent fragment detection system on an ABI PRISM 377 DNA
Sequencer. For this method, either the forward primer was
directly labeled with a fluorochrome or had a 19-bp M13 tail
at the 5′ end. In the latter case, a third universal fluorescentlabeled M13 primer (5′-CACGACGTTGTAAAACGAC-3′)
was added to the PCR (Schuelke 2000; Somers et al. 2004).
The PCR for directly labeled forward primers contained
25 ng DNA, 1× PCR buffer, 0.30 µmol/L reverse primer,
0.30 µmol/L forward primer labeled with 6-FAM, TET, or
HEX, 200 µmol/L each dNTP, and 0.5 U Taq DNA polymerase (Amersham Biosciences Europe GmbH). For M13-tailed
forward primers, the directly labeled forward primer was replaced with 0.03 µmol/L M13 tailed forward primer and
0.27 µmol/L of a universal fluorescent labeled M13 primer.
Amplifications were performed for each primer pair separately in microtiter plates using the following programs:
2 min at 94 °C, followed by 40 cycles of 1 min 94 °C, 1 min
annealing (between 50 and 62 °C, depending on the published optimal annealing temperature of the primer), and
1 min at 72 °C, and a final extension of 10 min at 72 °C.
SSR amplification products were multiplexed by combining 0.7 µL of 6-FAM-, 0.7 µL of TET-, and 1.0 µL of HEXlabeled PCR products with 0.3 µL of GS-500 (TAMRA) and
0.8 µL of ABI loading buffer (blue dextran and EDTA). The
multiplex was denatured for 3 min at 94 °C and quickly
chilled on ice, and 0.8 µL of the denatured sample was
loaded on to a 4.5% denaturing polyacrylamide gel using a
membrane-loading comb. SSR fragments were analyzed in
the same way as described for the AFLPs.
DArT assay
DArT markers were generated by Triticarte Pty. Ltd.
547
(Canberra, Australia; http://www.triticarte.com.au), which is
a whole-genome profiling service laboratory, as described
by Wenzl et al. (2004) and Akbari et al. (2006). Briefly, a
genomic representation of a mixture of 13 cultivars was produced after PstI–TaqI digestion, spotted on microarray slides
and the individual genotypes screened for polymorphism
based on fluorescence signals. The system was optimized for
polymorphism and detection accuracy. DNA from the parents (‘Arina’ and NK93604) was first screened for polymorphism (giving a polymorphism rate of about 30%) and then
the individual DH lines were genotyped. Two hundred
seventy-one loci were scored as present (1) or absent (0).
The locus designations used by Triticarte Pty. Ltd. were
adopted in this paper. DArT markers consisted of the prefix
“wPt”, followed by numbers corresponding to a particular
clone in the genomic representation, where w stands for
wheat, P for PstI (primary restriction enzyme used) and t for
TaqI (secondary restriction enzyme).
Segregation analysis and map construction
For each segregating marker, a χ2 goodness-of-fit analysis
was performed to test for deviation from the 1:1 expected
segregation ratio at a 1% level of significance. Linkage
groups were established using a minimum LOD score of 4.0
after preliminary analysis using LOD scores ranging from 2
to 10. A linkage group was assigned to a chromosome when
it contained at least 2 SSR loci that had been assigned to a
particular chromosome in previously published genetic (Liu
and Tsunewaki 1991; Gale et al. 1995; Roder et al. 1998a;
Li et al. 1999; Messmer et al. 1999; Mingeot and Jacquemin
1999; Gupta et al. 2002; Paillard et al. 2003; Somers et al.
2004; Song et al. 2005) and physical (Roder et al. 1998b;
Sourdille et al. 2004; Song et al. 2005) maps. Final mapping
was done by combining 2 or more linkage groups that belong to the same chromosome. The order of the markers of
each chromosome was determined using fixed order of selected SSR loci from previous publications using the following parameters: recombination threshold = 0.45; minimum
LOD score for calculating map distance = 0.10; ripple value =
1; jump threshold = 5; and the Haldane mapping function.
When necessary, markers were removed and the order recalculated until a stable order was reached. All χ2 analysis and
linkage mapping were performed using JoinMap, v. 3.0 (Van
Ooijen and Voorrips 2001). The final map was drawn using
the MapChart program, v. 2.1 (Voorrips 2002).
Results
Map construction
Two hundred ninety polymorphic loci were scored from
45 AFLP primer pairs, an average of 6.4 loci/primer pair.
The 300 SSR primers revealed 343 segregating loci that varied from 1 to 3 loci. Among the 904 loci (271 DArTs, 290
AFLPs, and 343 SSRs) used for preliminary mapping in the
‘Arina’ × NK93604 (ArNK) population, 724 loci mapped to
58 linkage groups, each with 3–40 loci. The number of linkage groups remained basically the same when only the 343
SSR markers were used for linkage analysis. Final mapping
was performed by combining 2 or more linkage groups that
belong to the same chromosome, and a total of 280 noninformative loci (31%) were excluded from mapping for the
© 2006 NRC Canada
548
following reasons: (i) they did not meet the threshold value
for entry with respect to jumps in goodness of fit; (ii) they
contributed to negative distance in the final map; and (or)
(iii) they changed the order of anchoring markers.
The final genetic map (Fig. 1) consisted of 624 markers
assigned to the 21 chromosomes, giving a total map length
of 2595.5 cM. The number of SSRs with physical map information varied from 2 in 5B to 11 in 2B and 7A (markers in
boldface in Fig. 1). The total number of mapped loci per
chromosome ranged from 8 on 7D to 55 on 7A, and the
average was 29.7 loci/chromosome. The largest chromosome
map was for 7A (202.8 cM); the shortest was for 4D
(69.3 cM), and the average chromosome length was
123.6 cM. The density of markers on the maps ranged from
2.5 cM/marker on 6B to 12.2 cM/marker on 7D, with an average density of 4.2 cM/marker. Map distances between 2
consecutive markers varied from 0 to 49 cM, and 589 of the
603 intervals (97.6%) were less than 20 cM. There were
only 11 intervals with gaps larger than 20 cM, and the largest gaps between markers were observed on chromosomes
6A (42.4 cM) and 7D (49.0 cM).
There was variation in the number of markers, map
length, and marker density on the basis of the homoeologous
group. Marker number and density were the highest in
homoeologous group 2 (117 loci and 3.5 cM/marker, respectively), whereas map length was the highest (423.8 cM) in
both groups 1 and 7. Homoeologous group 5 had the lowest
number of markers (52 loci), lowest marker density
(5.2 cM/marker), and shortest map length (269.4 cM).
Homoeologous group 2 contained the highest number of
AFLPs and SSRs, whereas DArTs were highest in group 7.
For the former, the number of AFLPs was more than twice
that of the number of DArTs.
Map length was relatively shorter for the D genome
(813.8 cM) than for the A (929.0) and B (852.7 cM)
genomes. The distribution of markers among the genomes
was also not uniform, with twice as many markers mapped
to the A and B genomes than the D genome: 245, 257, and
122 markers for the A, B, and D genomes, respectively. The
number of AFLP and DArT markers mapped to the D genome was very low (27 AFLPs and 20 DArTs) compared
with the A (71 loci for each) and B (67 AFLPs and 98
DArTs) genomes.
Segregation distortion
On the whole, the ArNK population was not skewed, with
49.5% for the alleles coming from ‘Arina’ and 51.5% of the
alleles from NK93604. However, χ2 segregation tests for
each locus showed significant (p < 0.01) segregation distortion for 127 markers (20.4%). Markers exhibiting segregation distortion in favor of NK93604 alleles were more
frequent (56.7%) than those in favor of ‘Arina’ alleles
(43.3%). About 60% of the entire length of chromosome 2D
showed distorted segregation, with an excess of NK93604
alleles. Seven other chromosomes showed minor regions of
distorted segregation. In this study, a chromosomal region
was regarded as being associated with skewed segregation
if 4 or more closely linked markers showed significant
segregation distortion. Based on these criteria, 10 regions of
significant segregation distortion (shown as filled or crosshatched boxes within chromosomes in Fig. 1) were found on
Genome Vol. 49, 2006
7 chromosomes: 6 regions on chromosomes 1A, 3A, 4D,
5D, and 6B contained an excess of alleles from ‘Arina’, and
3 other regions on 2A and 7A contained an excess of alleles
from NK93604.
Marker evaluation
Among the 624 markers mapped to the 21 chromosomes,
the majority of markers were SSRs (270), with 165 AFLPs
and 189 DArTs. Chromosomes 2A, 7A, and 7B have the
highest number of AFLPs, SSRs, and DArTs, respectively. A
total of 40 AFLPs (24.2%), 26 DArTs (13.8%), and 61 SSRs
(22.6%) showed significant (p < 0.01) segregation distortion.
Clustering of intra- and inter-marker intervals below a map
distance of 0.5 cM was observed in 110 of 603 intervals
(18.2%) between adjacent markers. The total number of intervals between 2 consecutive loci of the same marker type
was 52 for AFLPs, 90 for DArTs, and 131 for SSRs,
whereas the remaining 330 intervals were between different
marker types. Map distances in 51 intervals between 2 consecutive DArT markers (27.0%) was less than 0.5 cM, which
was much higher compared with 3 for AFLP (1.8%) and 24
for SSR (8.9%). Clustering of DArTs was more frequent on
chromosome 3B, 3D, 4A, and 7A, and was more frequent
for SSRs on 2A and 4A.
Discussion
Linkage groups and marker order
Preliminary linkage mapping in the present study identified 58 linkage groups, many more than the 21 haploid chromosomes of hexaploid wheat. This large number of linkage
groups compared with haploid chromosome number may
suggest that several areas of the genome remain undetected
with the present set of markers. The requirement for a large
number of markers or mapping populations to reduce the
linkage group number to haploid chromosome numbers and
increase map accuracy has been emphasized in other mapping studies (e.g., Jeuken et al. 2001; Sharma et al. 2002;
Crane and Crane 2005). To test if the large number of linkage groups in the ArNK population was due to poor data
quality, errors in scoring or establishing linkage groups, and
(or) insufficient coverage of the genome by the markers, the
raw segregation data (1468 loci for 115 recombinant inbred
lines) for the most extensively studied ITMI population
(Wheat, Synthetic × ‘Opata’, BARC) was downloaded from
the GrainGenes Web site (http://wheat.pw.usda.gov/GG2/
index.shtml), and mapped in the same way as described by
Song et al. (2005). In contrast to the 21 groups reported by
the authors from the same dataset, we found 56–63 linkage
groups depending on the LOD score used to establish linkages. For the latter, the number of linkage groups per chromosome varied from 1 for 4B and 4D to 5 for 7A, 7B, and
7D. The authors have also confirmed the presence of several
linkage groups for several chromosomes during preliminary
mapping of the ITMI population (J.R. Shi and Q.J. Song,
personal communication). Twenty-one linkage groups with
the same map order and length as that of Song et al. (2005)
was obtained only when 2 or more linkage groups that belong to the same chromosome were combined and remapped
using selected anchoring markers, based on previous publi© 2006 NRC Canada
Fig. 1. Genetic linkage map of 624 loci in 93 double-haploid lines derived from a cross between Triticum aestivum L em. Thell ‘Arina’ and NK93604. AFLP markers are
named as described in Materials and methods. The blue, green, and black colors indicate AFLP, DArT, and SSR markers, respectively. A single SSR primer with 2 mapped
loci on the same chromosome have a suffix of either “.1” or “.2”. SSRs that showed discrepancies in terms of chromosome or marker order compared with published maps are
in parentheses. SSRs with available physical mapping information are in boldface. SSRs known by chromosomal location without specific marker order are in italics. Cumulative map distances are shown in centimorgans (cM) on the left side of the linkage groups and was calculated using the Haldane mapping function. Loci marked with * and **
deviate significantly from 1:1 ratio at p < 0.01 and p < 0.001, respectively. Chromosome segments shown in shaded boxes indicate regions of significant (p < 0.01) segregation
distortion (cross hatched box, ‘Arina’ alleles in excess; solid filled box, NK93604 alleles in excess).
Semagn et al.
549
© 2006 NRC Canada
Genome Vol. 49, 2006
Fig 1 (continued).
550
© 2006 NRC Canada
551
Fig 1 (concluded).
Semagn et al.
© 2006 NRC Canada
552
cations, as fixed order. We therefore followed the same approach to construct the final map for the ArNK population.
SSR marker order from the present study was compared
with published maps in hexaploid wheat. Although there are
various published maps for all hexaploid wheat chromosomes (e.g., Liu and Tsunewaki 1991; Gale et al. 1995;
Roder et al. 1998a; Li et al. 1999; Messmer et al. 1999;
Mingeot and Jacquemin 1999; Gupta et al. 2002; Paillard et
al. 2003; Somers et al. 2004; Song et al. 2005), the authors
believe that the wheat consensus map (Somers et al. 2004),
the ITMI map (Song et al. 2005), and the wheat composite
map by Rudi Appels (http://www.shigen.nig.ac.jp/wheat/
komugi/maps/markerMap.jsp) are the most detailed maps for
comparative purposes. The presence of various contradictory
locus orders among these maps, as detected by the freely
available CMap program at the GrainGenes Web site, created difficulty in deciding the correct locus order. For the
ArNK population, different locus orders were checked and
the best orders were compared with one or more of these
maps. SSR marker order correlated very well with the consensus map in 10 chromosomes (1D, 2B, 2D, 3A, 4D, 5A,
5B, 5D, 6B, and 7D) and with the composite map in 2 chromosomes (2A and 3D). Marker order in 1B was the same as
the consensus map in all except the interval between
Xgwm11 and Xbarc187, which was in agreement with the
ITMI map. On 7A, the interval from Xgwm282 to
Xgwm525 was the same as the consensus map, but the other
was the same as the ITMI map. SSR marker orders in the
other chromosomes showed partial correlation to 2 or 3 of
these maps at different regions: 3 chromosomes (3B, 4B,
and 7B) to the consensus and ITMI maps, 2 chromosomes
(4A and 6A) to the consensus and composite maps, and 2
other chromosomes (1A and 6D) to 3 maps at different regions. A difference in marker order among genetic maps is
not unexpected, as genetic mapping only gives an indication
of the relative position of the markers to each other (Sourdille
et al. 2004). The chromosomal location of 38 SSRs (loci in
italic in Fig. 1) was available at the GrainGenes Web site, but
their map position and locus order in their respective chromosomes was the first in the present study.
Genome coverage
The ArNK map covers 2595.5 cM, which is similar to the
2569 cM of the wheat consensus map (Somers et al. 2004)
and 2655 cM of the recently published ITMI map (Song et
al. 2005), but it represents only 84% of 3086 cM map in the
ArFo (Paillard et al. 2003). The ArNK map shows 7 chromosomes (1A, 1D, 4A, 4B, 4D, 6B, and 6D) as being longer, and shows the remaining 14 chromosomes as being
shorter. In fact, the ArFo map length for 11 chromosomes
(1B, 2A, 2B, 2D, 3B, 3D, 5A, 5D, 6A, 7A, and 7D) was
much longer than that of the high-density wheat consensus
and ITMI maps. The overall average marker density in the
ArNK map (4.2 cM/marker) was much better than that of the
ArFo maps (8 cM/marker), but lower than that of the ITMI
(1.9 cM/marker) and the wheat consensus (2.2 cM) maps.
Despite the larger number of markers in the present map, the
total genome coverage and the length of several individual
chromosomes are shorter than the ArFo map. Differences in
recombination frequencies owing to genetic background ef-
Genome Vol. 49, 2006
fects from the other parents and (or) a difference in mapping
algorithm may be possible explanations for such differences.
Although we generally had good coverage, the short arms
of 5 chromosomes (3A, 4A, 4B, 4D, and 6A) and the long
arm of 5D were under represented in the map. In all except
4BS, this was mainly due to lack of a sufficient number of
polymorphic microsatellite markers in the corresponding
regions (Somers et al. 2004; Song et al. 2005). The total
length and the number of markers mapped to the D genome
were much lower than the A and B genomes. The low level
of polymorphism in the D genome is well known (e.g., Röder
et al. 1998a; Chalmers et al. 2001) and is in agreement with
the hypothesis of a mono- or oligophyletic origin of hexaploid
wheat (Lagudah et al. 1991; Salamini et al. 2002).
Segregation distortion
The observed segregation distortion (20.4%) in the ArNK
population is in agreement with Cadalen et al. (1997), who
found segregation distortion of 20% at a 1% level of significance. Markers showing distorted segregation were clustered
together on specific regions on 8 chromosomes (1A, 2A, 2D,
3A, 4D, 5D, 6B, and 7A). Clustering of distorted markers on
various chromosomes have been reported in various studies
(Cadalen et al. 1997; Faris et al. 1998; Messmer et al. 1999;
Kammholz et al. 2001; Paillard et al. 2003), and it may be
caused by different factors. First, the ArNK population was
derived from a wide cross between winter and spring wheat,
and segregation distortion is a common phenomenon in wide
crosses and has been reported on various wheat chromosomes (Cadalen et al. 1997; Messmer et al. 1999; Kammholz
et al. 2001; Paillard et al. 2003). Second, the ArNK population was also developed by means of wheat × maize crosses,
and non-Mendelian segregation within wheat × maize derived DH populations may be due to (i) heterogeneity within
the parents, (ii) selection associated with the DH production
process, and (iii) outcrossing and admixture of seed during
increase for trials (Kammholz et al. 2001). Third, gametocidal and pollen-killer genes have been reported in wheat
as being distributed in different homoeologous groups (Gill
et al. 1996a; Faris et al. 1998a; McIntosh et al. 1998) and
may be responsible for the observed distorted segregation
in the ArNK population. Kammholz et al. (2001) had also
speculated that clustering of distorted loci appeared to be
associated with introgressed alien chromatin involving
translocations into one of the parents. However, the parents
used in this study are not known to have any alien translocations.
Distribution of markers among and within linkage
maps
In some chromosomes (e.g., 2A and 2D), AFLP markers
appeared as clustered but the interval between most adjacent
markers was >1.5 cM. In contrast to frequent clustering of
AFLP markers reported by several researchers at the
centromere and surrounding heterochromatin regions of the
genome based on an EcoRI–MseI combination, extensive
clustering was not apparent in the ArNK genetic map. The
methylation-sensitive PstI–MseI combination was used in
the present study, which revealed a significantly lower level
of polymorphism in wheat than the methylation-insensitive
EcoRI–MseI combination (Barrett and Kidwell 1998). Co© 2006 NRC Canada
Semagn et al.
553
Fig. 2. Observed distribution of Haldane map distance between 2 consecutive loci over all chromosomes. AFLP, DArT, and SSR are
intramarker intervals. Bars represent standard error of the mean.
migration and scoring error may, therefore, be very much
lower in the PstI–MseI than in the EcoRI–MseI combination.
AFLP fragments were analyzed using an ABI PRISM 377
DNA Sequencer in combination with the computer software
GenScan and Genotyper (PE Applied Biosystems), and the
application of an internal-lane size standard ensured accurate
sizing of fragments by minimizing the lane-to-lane or gel-to
gel variation present in other studies that used silver staining
or radioactivity, as reported by Huang et al. (2000) and
Schwarz et al. (2000).
Clustering of SSR markers was observed in 3 chromosomes (1B, 2A, and 4B). Roder et al. (1998a) reported clustering of microsatellites in several centromeric regions on 6
chromosomes in hexaploid wheat. Gene-rich regions in the
euchromatin tend to be low copy and hypomethylated
(Naveh-Many and Cedar 1981). Cardle et al. (2000) and
Morgante et al. (2002) indicated that microsatellites are significantly associated with the low-copy fraction of plant
genomes based on the estimation of their density in Arabidopsis, rice, soybean, maize, and wheat. Clustering may,
therefore, occur when genetic maps are constructed with
hypomethylated and low-copy SSRs.
The frequency of clustering in DArT markers at intervals
less than 0.5 cM was 3- and 15-fold higher than SSRs and
AFLPs, respectively (Fig. 2). High-density physical maps in
wheat reveal that more than 85% of wheat genes are present
in gene-rich regions, physically spanning only 5%–10% of
the chromosomal regions (Gill et al. 1996a, 1996b; Faris et
al. 2000; Sandhu et al. 2001). A high correlation between
gene-rich regions and recombination is common in wheat
(Gill et al. 1996a, 1996b; Sandhu et al. 2001; Weng and
Lazar 2002) and many other organisms. In homoeologous
group 6 chromosomes, for example, gene-rich regions pres-
ent near telomeric ends show 10–20 fold more recombination than proximal regions on the chromosome (Shah and
Hassan 2005). The high proportion of clustering of DArT
markers may therefore be indicative of gene-rich regions.
Clustering in DArTs may also be due to the presence of
redundant clones in the genomic representation, which was
supported in the following 2 ways: (i) all intervals <0.5 cM
between 2 consecutive DArT markers showed high correlation coefficients (r > 0.98) and (ii) strong multicollinearities
were observed between DArT markers with such high correlation coefficients in QTL analysis for FHB resistance (data
not shown). Genomic reduction is the critical step in producing genomic representations with a sufficient number of
unique polymorphic clones in DArT libraries. This step may
be more complex in species with high ploidy level and genome size, such as hexaploid wheat. The data from the present study may, therefore, suggest that the present genomic
representations for hexaploid wheat at Triticarte Pty. Ltd. requires additional sieving steps to exclude highly correlated
clones and incorporate more unique clones with even distribution along chromosomes.
The map presented here provides insight regarding the
distribution of DArT markers in comparison with the wellestablished microsatellite and AFLP markers for linkage
mapping. It also provided readily detectable markers for
identifying novel quantitative trait loci for resistance to FHB
and powdery mildew and for anther extrusion, leaf segment
incubation, and latency.
Acknowledgements
We thank Dr. M. Roder (IPK Gatersleben, Germany) for
providing some unpublished primer sequences. This work
© 2006 NRC Canada
554
was supported by the Research Council of Norway (project
No. 151281/110) and was a collaboration with CIMMYT.
References
Akbari, M., Wenzl, P., Caig, V., Carlig, J., Xia, L., Yang, S., et al.
2006. Diversity arrays technology (DArT) for high-throughput
profiling of the hexaploid wheat genome. Theor. Appl. Genet. In
press.
Akkaya, M.S., Bhagwat, A.A., and Cregan, P.B. 1992. Length
polymorphism of simple sequence repeat DNA in soybean. Genetics, 132: 1131–1139.
Barrett, B.A., and Kidwell, K.K. 1998. AFLP-based genetic diversity assessment among wheat cultivars from the Pacific Northwest. Crop Sci. 38: 1261–1271.
Bennett, M.D., and Smith, J.B. 1976. Nuclear DNA amounts in angiosperms. Philos. Trans. R. Soc. Lond. Ser. B. Biol. Sci. 274:
227–274.
Botstein, D., White, R.L., Skolnick, M., and Davis, R.W. 1980.
Construction of a genetic linkage map in man using restriction
fragment length polymorphisms. Am. J. Hum. Genet. 32: 314–
331.
Cadalen, T., Boeuf, C., Bernard, S., and Bernard, M. 1997. An
intervarietal molecular marker map in Triticum aestivum L. Em.
Thell., and comparison with a map from a wide cross. Theor.
Appl. Genet. 94: 367–377.
Cardle, L., Ramsay, L., Milbourne, D., Macaulay, M., Marshal, D.,
and Waugh, R. 2000. Computational and experimental characterization of physically clustered simple sequence repeats in
plants. Genetics, 156: 847–854.
Chalmers, K.J., Cambell, A.W., Kretschmer, J., Karakousis, A.,
Henschke, P.H., Pierens, S., et al. 2001. Construction of three
linkage maps in bread wheat, Triticum aestivum. Aust. J. Agric.
Res. 52: 1089–1119.
Crane, C.F., and Crane, Y.M. 2005. A nearest-neighboring-end algorithm for genetic mapping. Bioinformatics, 21: 1579–1591.
Dreisigacker, S., Zhang, P., Warburton, M.L., Skovmand, B.,
Hoisington, D., and Melchinger, A.E. 2005 Genetic diversity
among and within CIMMYT landrace accessions investigated
with SSRs and implications for plant genetic resources management. Crop Sci. 45: 653–661.
Eujayl, L., Sorrells, M.E., Baum, M., Wolters, P., and Powell, W.
2002. Isolation of EST-derived microsatellite markers for genotyping the A and B genomes of wheat. Theor. Appl. Genet. 104:
399–407.
Faris, J.D., Laddomada, B., and Gill, B.S. 1998. Molecular mapping of segregation distortion loci in Aegilops tauschii. Genetics, 149: 319–327.
Faris, J.D., Haen, K.M., and Gill, B.S. 2000. Saturation mapping
of a gene-rich recombination hot spot region in wheat. Genetics,
154: 823–835.
Gale, M.D., Atkinson, M.D., Chinoy, C.N., Harcourt, R.L., Jia, J.,
Li, Q.Y., and Devos, K.M. 1995. Genetic maps of hexaploid
wheat. Proceedings of the 8th International Wheat Genetics
Symposium. 20–25 July 1993, Beijing, China. Edited by Z.S.
Li and Z.Y. Xin. China Agricultural Scientech Press, Vol. 1.
pp. 29–40.
Gill, K.S., Gill, B.S., Endo, T.R., and Boyko, E.V. 1996a. Identification of high-density mapping of gene-rich regions in chromosome group 5 of wheat. Genetics, 143: 1001–1012.
Gill, K.S., Gill, B.S., Endo, T.R., and Taylor. T. 1996b. Identification and high-density mapping of gene-rich regions in chromosome group 1 of wheat. Genetics, 144: 1883–1891.
Genome Vol. 49, 2006
Grønnerød, S., Marøy, A.G., MacKey, J., Tekauz, A., Penner, G.A.,
and Bjørnstad, A. 2002. Genetic analysis of resistance to barley
scald (Rhynchosporium secalis) in the Ethiopian line ‘Abyssinian’ (CI668). Euphytica, 126: 235–250.
Gupta, P.K., Varshney, R.K., Sharma, P.C., and Ramesh, B. 1999.
Molecular markers and their application in wheat breeding: a review. Plant Breed. 118: 369–390.
Gupta, P.K., Balyan, H.S., Edwards, K.J., Isaac, P., Korzun, V.,
Röder, M., et al. 2002. Genetic mapping of 66 new microsatellite (SSR) loci in bread wheat. Theor. Appl. Genet. 105:
413–422.
Guyomarc’h, H., Sourdille, P., Charmet, G., Edwards, K.J., and
Bernard, M. 2002. Characterization of polymorphic microsatellite markers from Aegilops tauschii and transferability to
the D-genome of bread wheat. Theor. Appl. Genet. 104: 1164–
1172.
Huang, X., Zeller, F.J., Hsam, S.L.K., Wenzel, G., and Mohler, V.
2000. Chromosomal location of AFLP markers in common
wheat utilizing nulli-tetrasomic stocks. Genome, 43: 298–305.
Jaccoud, D., Peng, K., Feinstein, D., and Kilian, A. 2001. Diversity
arrays: a solid state technology for sequence information independent genotyping. Nucleic Acids Res. [online], 29: e25. Available from http://nar.oxfordjournals.org/cgi/reprint/29/4/e25.
Jeuken, M., van Wijk, R., Peleman, J., and Lindhout, P. 2001. An
integrated interspecific AFLP map of lettuce (Lactuca) based on
two L. sativa × L. saligna F2 populations. Theor. Appl. Genet.
103: 638–647.
Kammholz, S.J., Campbell, A.W., Sutherland, M.W., Hollamby,
G.J., Martin, P.J., Eastwood, R.F., et al. 2001. Establishment and
characterization of wheat genetic mapping populations. Aust. J.
Agric. Res. 52: 1079–1088.
Lagudah, E.S., Appels, R., Brown, A.H.D., and McNeil, D. 1991.
The molecular-genetic analysis of Triticum tauschii, the Dgenome donor to hexaploid wheat. Genome, 34: 375–386.
Laurie, D.A., and Bennett, M.D. 1988. The production of haploid
wheat plants from wheat × maize crosses. Theor. Appl. Genet.
76: 393–397.
Li, W.L., Faris, J.D., Chittoor, J.M., Leach, J.E., Hulbert, S.H., Liu,
D.J., et al. 1999. Genomic mapping of defense response genes
in wheat. Theor. Appl. Genet. 98: 226–233.
Liu, Y.G., and Tsunewaki, K. 1991. Restriction fragment length
polymorphism (RFLP) analysis in wheat. II. Linkage maps of
the RFLP sites in common wheat. Jpn. J. Genet. 66: 617–633.
Marino, C.L., Nelson, J.C., Lu, Y.H., Sorrells, M.E., Leroy, P.,
Tuleen, N.A., et al. 1996. Molecular genetic maps of the group 6
chromosomes of hexaploid wheat (Triticum aestivum L. em.
Thell). Genome, 39: 359–366.
McIntosh, R.A., Hart, G.E., Devos, K.M., Gale, M.D., and Rogers,
W.J. 1998. Catalogue of gene symbols for wheat. In Proceedings
of the 9th International Wheat Genetics Symposium, 2–7 August 1998, Saskatoon, Saskatchewan. Slinkard (ed.). University
Extension Press. Vol. 5. pp. 13–72.
Messmer, M.M., Keller, M., Zanetti, S., and Keller, B. 1999. Genetic linkage map of a wheat × spelt cross. Theor. Appl. Genet.
98: 1163–1170.
Mingeot, D., and Jacquemin, J.M. 1999. Mapping of RFLP probes
characterized for their polymorphism on wheat. Theor. Appl.
Genet. 98: 1132–1137.
Morgante, M., Hanafey, M., and Powell, W. 2002. Microsatellites
are preferentially associated with nonrepetitive DNA in plant
genomes. Nat. Genet. 30: 194–200.
Naveh-Many, T., and Cedar, H. 1981. Active gene sequences are
undermethylated. Proc. Natl. Acad. Sci. U.S.A. 78: 4226–4250.
© 2006 NRC Canada
Semagn et al.
Nelson, J.C., van Deynze, A.E., Autrique, E., Sorrells, M.E., Lu,
Y.H., Merlino, M., et al. 1995a. Molecular mapping of wheat.
Homoeologous group 2. Genome, 38: 516–524.
Nelson, J.C., van Deynze, A.E., Autrique, E., Sorrells, M.E., Lu,
Y.H., Negre, S., et al. 1995b. Molecular mapping of wheat.
Homoeologous group 3. Genome, 38: 525–533.
Nelson, J.C., Sorrells, M.E., van Deynze, A.E., Lu, Y.H., Atinkson,
M., Bernard, M., et al. 1995c. Molecular mapping of wheat. Major genes and rearrangements in homoeologous groups 4, 5, and
7. Genetics, 141: 721–731.
Paillard, S., Schnurbusch, T., Winzeler, M., Messmer, M.,
Sourdille, P., Abderhalden, O., et al. 2003. An integrative genetic linkage map of winter wheat (Triticum aestivum L.).
Theor. Appl. Genet. 107: 1235–1242.
Parker, G.D., Chalmers, K.J., Rathjen, A.J., and Langridge, P.
1998. Mapping loci associated with flour colour in wheat
(Triticum aestivum L.). Theor. Appl. Genet. 96: 238–245.
Peleman, J.D., and van der Voort, J.R. 2003. Breeding by design.
Trends Plant Sci. 8: 330–334.
Pestsova, E., Ganal, M.W., and Roder, M.S. 2000. Isolation and
mapping of microsatellite markers specific for the D genome of
bread wheat. Genome, 43: 689–697.
Roder, M.S., Korzun, V., Wendehake, K., Plaschke, J., Tixier,
M.H., Leroy, P., and Ganal, M.W. 1998a. A microsatellite map
of wheat. Genetics, 149: 2007–2023.
Roder, M.S., Korzun, V., Gill, B.S., and Ganal, M. 1998b. The
physical mapping of microsatellite markers in wheat. Genome,
41: 278–283.
Salamini, F., Ôzkan, H., Brandolini, A., Schäfer-Pregl, R., and
Martin, W. 2002 Genetics and geography of wild cereal domestication in the Near East. Nat. Rev. Genet. 3: 429–441.
Sandhu, D., Champoux, J.A., Bondareva, S.N., and Gill, K.S.
2001. Identification and physical localization of useful genes
and markers to major gee-rich region on wheat group 1S chromosomes. Genetics, 157: 1735–1747.
Schuelke, M. 2000. An economic method for the fluorescent labeling of PCR fragments. Nat. Biotechnol. 18: 233–234.
Schwarz, G., Herz, M., Huang, X.Q., Michalek, W., Jahoor, J.,
Wenzel, G., and Mohler, V. 2000. Application of fluorescentbased semi-automated AFLP analysis in barley and wheat.
Theor. Appl. Genet. 100: 545–551.
Shah, M.M., and Hassan, A. 2005. Distribution of genes recombination on wheat homoeologous group 6 chromosomes: a synthesis of available information. Mol. Breed. 15: 45–53.
Sharma, R., Aggarwal, R.A.K., Kumar, R., Mohapatra, T., and
Sharma, R.P. 2002. Construction of an RAPD linkage map and
localization of QTLs for oleic acid level using recombinant
inbreds in mustard (Brassica juncea). Genome, 45: 467–472.
Somers, D.J., Isaac, P., and Edwards, K. 2004. A high-density
microsatellite consensus map for bread wheat (Triticum
aestivum L.). Theor. Appl. Genet. 109: 1105–1114.
555
Song, Q.J., Fickus, E.W., and Cregan, P.B. 2002. Characterization
of trinucleotide SSR motifs in wheat. Theor. Appl. Genet. 104:
286–293.
Song, Q.J., Shi, J.R., Singh, S., Fickus, E.W., Costa, J.M., Lewis,
J., et al. 2005. Development and mapping of microsatellite
(SSR) markers in wheat. Theor. Appl. Genet. 110: 550–560.
Sourdille, P., Cadalen, T., Guyomarc’h, H., Snape, J.W., Perretant,
M.R., Charmet, G., et al. 2003. An update of the Courtot × Chinese Spring intervarietal molecular marker linkage map for the
QTL detection of agronomic traits in wheat. Theor. Appl. Genet.
106: 530–538.
Sourdille, P., Singh, S., Cadalen, T., Brown-Guedira, G.L., Gay, G.,
Qi, L., et al. 2004. Microsatellite-based deletion bin system for
the establishment of genetic-physical map relationships in wheat
(Triticum aestivum L.). Funct. Integr. Genomics, 4: 12–25.
Talbert, L.E., Blake, N.K., Chee, P.W., Blake, T.K., and Magyar,
G.M. 1994. Evaluation of sequence-tagged-site-facilitated PCR
products as molecular markers in wheat. Theor. Appl. Genet. 87:
789–794.
Van Deynze, A.E., Dubcovsky, J., Gill, K.S., Nelson, J.C., Sorrells,
M.E., Dvorak, J., et al. 1995. Molecular-genetic maps for group
1 chromosomes of Triticeae species and their relation to chromosomes in rice and oat. Genome, 38: 45–59.
Van Ooijen, J.W., and Voorrips, R.E. 2001. JoinMap 3.0 software
for the calculation of genetic linkage maps [computer program].
Plant Research International, Wageningen, the Netherlands.
Voorrips, R.E. 2002. MapChart: software for the graphical presentation of linkage maps and QTLs. J. Hered. 93: 77–78.
Vos, P., Hogers, R., Reijans, M., van de Lee, T., Hornes, M.,
Friters, A., et al. 1995. AFLP: a new technique for DNA fingerprinting. Nucleic Acids Res. 23: 4407–4414.
Weng, Y., and Lazar, M.D. 2002. Comparison of homoeologous
group-6 short arm physical maps of wheat and barley reveals a
similar distribution of recombinogenic and gene-rich regions.
Theor. Appl. Genet. 104: 1078–1085.
Wenzl, P., Carling, J., Kudrna, D., Jaccoud, D., Huttner, E.,
Kleinhofs, A., and Kilian, A. 2004. Diversity arrays technology
(DArT) for whole-genome profiling of barley. Proc. Natl. Acad.
Sci. U.S.A. 101: 9915–9920.
Williams, J.G.K., Kubelik, A.R.K., Livak, J.L., Rafalski, J.A., and
Tingey, S.V. 1990. DNA polymorphisms amplified by random
primers are useful as genetic markers. Nucleic Acids Res. 18:
6531–6535.
Wittenberg, A.H.J., van der Lee, T., Cayla, C., Kilian, A., Visser,
R.G.F., and Schouten, H.J. 2005. Validation of the highthroughput marker technology DArT using the model plant
Arabidopsis thaliana. Mol. Genet. Genomics, 274: 30–39.
Xia, L., Peng, K., Yang, S., Wenzl, P., de Vicente, M.C., Fregene,
M., and Kilian, A. 2005. DArT for high-throughput genotyping
of cassava (Manihot esculenta) and its wild relatives. Theor.
Appl. Genet. 110: 1092–1098.
© 2006 NRC Canada