Annals of Botany 105: 1199– 1210, 2010
doi:10.1093/aob/mcp253, available online at www.aob.oxfordjournals.org
PART OF A SPECIAL ISSUE ON PLANT NUTRITION
Genetic analysis of potassium use efficiency in Brassica oleracea
P. J. White1,*, J. P. Hammond2, G. J. King3, H. C. Bowen2, R. M. Hayden2, M. C. Meacham2, W. P. Spracklen2
and M. R. Broadley4
1
Scottish Crop Research Institute, Invergowrie, Dundee DD2 5DA, UK, 2Warwick HRI, University of Warwick, Wellesbourne,
Warwick CV35 9EF, UK, 3Rothamsted Research, Harpenden, Hertfordshire AL5 2JQ, UK and 4Plant and Crop Sciences
Division, University of Nottingham, Sutton Bonington Campus, Loughborough, Leicestershire LE12 5RD, UK
* For correspondence. E-mail [email protected]
Received: 7 July 2009 Returned for revision: 18 August 2009 Accepted: 10 September 2009 Published electronically: 8 October 2009
† Background and Aims Potassium (K) fertilizers are used in intensive and extensive agricultural systems to maximize production. However, there are both financial and environmental costs to K-fertilization. It is therefore
important to optimize the efficiency with which K-fertilizers are used. Cultivating crops that acquire and/or
utilize K more effectively can reduce the use of K-fertilizers. The aim of the present study was to determine
the genetic factors affecting K utilization efficiency (KUtE), defined as the reciprocal of shoot K concentration
(1/[K]shoot), and K acquisition efficiency (KUpE), defined as shoot K content, in Brassica oleracea.
† Methods Genetic variation in [K]shoot was estimated using a structured diversity foundation set (DFS) of 376
accessions and in 74 commercial genotypes grown in glasshouse and field experiments that included phosphorus
(P) supply as a treatment factor. Chromosomal quantitative trait loci (QTL) associated with [K]shoot and KUpE
were identified using a genetic mapping population grown in the glasshouse and field. Putative QTL were tested
using recurrent backcross substitution lines in the glasshouse.
† Key Results More than two-fold variation in [K]shoot was observed among DFS accessions grown in the glasshouse, a significant proportion of which could be attributed to genetic factors. Several QTL associated with
[K]shoot were identified, which, despite a significant correlation in [K]shoot among genotypes grown in the glasshouse and field, differed between these two environments. A QTL associated with [K]shoot in glasshouse-grown
plants (chromosome C7 at 62.2 cM) was confirmed using substitution lines. This QTL corresponds to a segment
of arabidopsis chromosome 4 containing genes encoding the Kþ transporters AtKUP9, AtAKT2, AtKAT2 and
AtTPK3.
† Conclusions There is sufficient genetic variation in B. oleracea to breed for both KUtE and KUpE. However, as
QTL associated with these traits differ between glasshouse and field environments, marker-assisted breeding programmes must consider carefully the conditions under which the crop will be grown.
Key words: Arabidopsis, Brassica oleracea, genetics, potassium (K), potassium use efficiency (KUE),
quantitative trait loci (QTL), shoot.
IN T RO DU C T IO N
Potassium (K) is an essential mineral element for plant growth,
development and fecundity (White and Karley, 2009). It is
required in large amounts by crop plants and, because many
agricultural soils lack sufficient phytoavailable K for
maximal crop production, it is generally supplied as
K-fertilizers in both intensive and extensive agricultural
systems (Lægreid et al., 1999; Pettigrew, 2008; Rengel and
Damon, 2008; Fageria, 2009). However, there are both financial and environmental costs, inherent in the energy required
for their production, distribution and application, to the consumption of K-fertilizers (Lægreid et al., 1999). In the
immediate future, a scarcity of K-fertilizers is unlikely, but
unstable energy prices, which affect the mining, distribution
and application of K-fertilizers, and the introduction of financial instruments associated with meeting climate change and
other environmental targets, will determine their cost, availability and usage. For these reasons, K-fertilizers must be
deployed efficiently.
Breeding crops that acquire and/or utilize K more effectively
is one strategy that could reduce the use of K-fertilizers
(Baligar et al., 2001; Trehan, 2005; Pettigrew, 2008; Rengel
and Damon, 2008; Fageria, 2009; Szczerba et al., 2009).
Agronomic K use efficiency is defined as crop dry matter
yield per unit K supplied (g DM g21 Ks). This is numerically
equal to the product of plant K content per unit K supplied
(g K g21 Ks), which is referred to as plant K uptake efficiency
(KUpE), and crop yield per unit plant K content (g DM g21
K), which is referred to as plant K utilization efficiency
(KUtE). In general, plant K content can be estimated from
shoot K content, and KUtE can then be expressed as the reciprocal of shoot K concentration ([K]shoot) if the entire shoot is
harvested (White et al., 2005).
Potassium is the most abundant inorganic cation in plants,
comprising up to 10 % of a plant’s dry weight (Watanabe
et al., 2007), and [K]shoot is often higher in plants from the
Brassicaceae than in those from many other angiosperm
families when grown under comparable conditions (Broadley
et al., 2004). Variation in [K]shoot has been observed among
genotypes of several plant species grown in the same
environment (Baligar et al., 2001; Pelletier et al., 2008;
Pettigrew, 2008; Rengel and Damon, 2008; Fageria, 2009),
# The Author 2009. Published by Oxford University Press on behalf of the Annals of Botany Company. All rights reserved.
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1200
White et al. — Genetics of potassium use efficiency in Brassica oleracea
including Brassica oleracea kales and collards (Kopsell et al.,
2004; Vilar et al., 2008), Brassica rapa (Wu et al., 2008),
Brassica napus (Brennan and Bolland, 2007; Damon et al.,
2007; Rose et al., 2007; Bhardwaj and Mamama, 2009) and
Brassica juncea (Shi et al., 2004).
This paper describes the genetic variation in, and chromosomal quantitative trait loci (QTL) associated with, [K]shoot and
therefore KUtE in Brassica oleracea, a major edible crop
worldwide that includes several morphologically distinct
subtaxa, such as acephala (kale/collards), alboglabra (oriental
kale), botrytis (cauliflower), capitata (cabbage), gemmifera
(Brussels sprout), gongylodes (kohlrabi), italica (broccoli/
calabrese), sabauda (Savoy cabbage) and sabellica (borecole/curly kale), in which the entire shoot is generally harvested (Broadley et al., 2008). Brassica oleracea is a diploid
plant species for which significant genetic resources are available, including (1) a diversity foundation set (DFS) thought to
contain most of the common allelic variation within this
species (Broadley et al., 2008), (2) genetic mapping populations suitable for the identification of chromosomal loci
affecting quantitative traits (Sebastian et al., 2000; Pink
et al., 2008), (3) collections suitable for isolating mutants in
specific genes (Himelblau et al., 2009), (4) extensive
genome sequence (Schranz et al., 2007) and (5) routine techniques for genetic transformation (Cogan et al., 2004). In
addition, the genus Brassica contains the closest crop relatives
of the model plant Arabidopsis thaliana and genomic relationships between A. thaliana, B. oleracea (Brassica C genome)
and other Brassica crops, such as B. rapa (A genome),
B. napus (AC genome) and the B genome-containing mustards
(B. nigra, B. juncea, B. carinata), are becoming increasingly
well characterized (Parkin et al., 2005; Schranz et al., 2006,
2007). Ultimately, this knowledge of comparative genomics
will facilitate the identification of genes affecting KUpE and
KUtE among the Brassicaceae and the breeding of Brassica
crops that utilize K-fertilizers more efficiently.
M AT E R IA L S A ND M E T HO DS
Plant material
The plant material used in this study consisted of: (1) a DFS of
376 Brassica oleracea L. accessions, selected from the .4300
accessions held in the Warwick-HRI Genetic Resources Unit
and thought to contain most of the common allelic variation
within this species (Broadley et al., 2008); (2) a set of 74 commercial genotypes sampled to represent the distinct major
B. oleracea morphotypes in current or recent cultivation in
northern Europe (Broadley et al., 2008); (3) the 90 most
informative lines from the ‘AGDH’ genetic mapping population, to enable the identification of QTL associated with
shoot K concentration in B. oleracea. The AGDH population
was generated through anther culture of the F1 of a cross
between a DH rapid-cycling accession of B. oleracea var.
alboglabra (A12DHd) and a DH accession derived from an
F1 hybrid calabrese cultivar, ‘Green Duke’, B. oleracea var.
italica (GDDH33). A linkage map of 906 cM for the AGDH
mapping population has been developed, with a mean distance
between marker loci of 1.92 + 3.49 cM, such that approx.
90 % of the genome is within 5 cM of a marker (Sebastian
et al., 2000; Broadley et al., 2008; Pink et al., 2008). There
were physical limitations on the number of AGDH lines that
could be grown in these experiments. Hence, a subset of
AGDH lines was selected that maximized the range of recombination break points, as well as the marker scoring density.
This subset has been shown to be adequate for the successful
detection of QTL for shoot mineral concentrations (Broadley
et al., 2008; Hammond et al., 2009). (4) A set of 20 recurrent
backcross substitution lines (the ‘AGSL’ population), each
containing chromosomal segments of GDDH33 introgressed
into the A12DHd background, was used to validate the
location of QTL in the AGDH population (Rae et al., 1999;
Broadley et al., 2008). (5) A common reference set of genotypes consisting of A12DHd, GD33DH and eight commercial
B. oleracea cultivars allowed comparisons between experiments (Greenwood et al., 2005, 2006; Broadley et al., 2008;
Hammond et al., 2009).
Field and glasshouse experiments
Plants were grown in a series of field and glasshouse experiments at Wellesbourne, UK (528120 3000 N, 18360 3900 W, 45 m
above sea level), each temporally arranged over several
occasions, as described by Broadley et al. (2008). Each
occasion represented an independent experimental run, containing a subset of the accessions being screened. Sets of
plants were grown with different applications of P-fertilizers
to investigate the effect of plant growth rate on [K]shoot.
Although most plants were grown successfully, not all of the
accessions sown in each experiment survived to harvest,
especially in the field. The experiments were as follows. (1)
A glasshouse experiment (GE1), in which three replicates of
the 376 DFS accessions and nine replicates of the 74 commercial cultivars were sown over six occasions between June,
2003 and July, 2004 in a 40-m2 ‘Cambridge’-type glasshouse
compartment that was set to maintain temperatures of 24 8C by
day and 15 8C at night using automatic vents and supplementary heating. Daylight was supplemented by artificial lighting
(Son-T 400-W Philips phi 0.85i, Groote, Noort, The
Netherlands) to maintain 16 h light per day above a photosynthetically active radiation (PAR) of 300 W m22. Plants
were grown in compressed polystyrene pots (dimensions
11 11 12 cm; Desch Plantpak Ltd, Mundon, Maldon,
UK), filled to a depth of approx. 0.5 cm below the rim with
a peat-based compost. The compost contained either
5.25 mg L21 (low [P]ext) or 15.75 mg L21 (high [P]ext) of
added P following the incorporation of 0.075 and 0.225 g of
sieved (500 mm) single superphosphate [SSP, CaSO4 þ
Ca(H2PO4)2, containing 7 % P] per litre of compost
(Greenwood et al., 2005). Other nutrients were incorporated
in the potting-mix in sufficient amounts to prevent mineral
deficiencies. Analysis of compost samples gave Olsen’s extractable P values of 9.2 and 20.2 mg L21 for low and high [P]ext
composts, respectively. The average water-extractable K concentration in these composts was 183 + 3 mg L21 (mean +
s.e.m., n ¼ 34), resembling soils of high K-fertility. Plant
shoots were sampled at similar developmental stages, 39, 47,
49, 49, 42 and 37 d after sowing on the six occasions. (2) A
field experiment (FE1) conducted in Wharf Ground,
Wellesbourne, between May, 2004 and May, 2005 in which
White et al. — Genetics of potassium use efficiency in Brassica oleracea
three replicates of the 74 commercial cultivars were sown over
three occasions at four [P]ext using an alpha design (Patterson
and Williams, 1976). The Wharf Ground soil is a sandy loam
Inceptisol in the Wick series of English classification
(Whitfield, 1974). Supplementary irrigation was supplied via
oscillating lines when required, and pesticide applications
were made according to horticultural best-practice. The
[P]ext treatments were imposed by incorporating triple superphosphate [TSP, Ca(H2PO4)2, containing 21 % P] equivalent
to 0, 298, 1125 or 2713 kg TSP ha21 to a depth of 0.10 m
using a power harrow (Greenwood et al., 2005). Analysis of
soil samples (to a depth of 30 cm) from these plots gave
average Olsen’s extractable P values of 40.7, 39.6, 81.7 and
152.1 mg P L21 for the four [P]ext treatments. Unfertilized
soils had ammonium nitrate-extractable K concentrations of
59 + 1.8 mg L21 (mean + s.e.m., n ¼ 40) and there was an
annual overall dressing of 289 kg N ha21 and 250 kg K2O
ha21 to the Wharf Ground field. Plant shoots were sampled
after 101, 97 and 93 d growth on the three occasions. These
timings were chosen to represent pre-commercial maturity.
(3) A second glasshouse experiment (GE2), in which nine
replicates of the 90 AGDH lines plus the A12DHd and
GDDH33 parents of the AGDH population and eight reference
commercial cultivars were sown over three occasions between
February and July, 2005 in the same glasshouse compartment
and at the same two [P]ext as GE1 using an alpha design. Plant
shoots were sampled at a comparable growth stage, after 50, 50
and 34 d growth on the three occasions. (4) A second field
experiment (FE2), conducted on Wharf Ground between
March and May, 2006, in which three replicates of 72 genotypes (62 AGDH lines, A12DHd, GDDH33 and eight reference commercial cultivars) were sown at the same four [P]ext
levels, and with the same amounts of N and K fertilizer, as
FE1 using an alpha design. Plant shoots were sampled after
105 d growth. (5) A third glasshouse experiment (GE3),
undertaken between March and May, 2006, in which three
replicates of 30 genotypes (20 AGSLs, A12DHd, GDDH33
and eight reference commercial cultivars) were sown in the
same glasshouse compartment and at the same two [P]ext as
GE1 and GE2. Plant shoots were sampled 39 d after sowing.
Potassium analysis
In all experiments, shoot fresh weight (FW), comprising all
above-ground biomass, was recorded immediately upon harvesting and shoot dry matter (DM) was determined after ovendrying at 60 8C for 72 h. For GE1, [K]shoot was determined by
a commercial foliar analysis laboratory (Yara Phosyn Ltd,
Pocklington, York, UK). For all other experiments, [K]shoot
was determined at Warwick-HRI using inductively coupled
plasma emission spectrometry (JY Ultima 2, Jobin Yvon
Ltd, Stanmore, Middlesex, UK) following the digestion of
dried plant material using the micro Kjeldahl method
(Bradstreet, 1965).
Data analysis
Data were analysed using REML procedures in GenStat
(Release 9.1.0.147, VSN International, Oxford, UK) to allocate sources of variation and estimate accession means for
1201
individual experiments (Patterson and Thompson, 1971;
Robinson, 1987). QTL mapping was performed with QTL
Cartographer 2.0 (Wang et al., 2004), using the composite
interval mapping (CIM) option as described previously
(Broadley et al., 2008; Hammond et al., 2009). Summary statistics of [K]shoot for the DFS, commercial cultivars and AGDH
lines are expressed as mean + s.e. for n genotypes.
R E S ULT S
Species-wide genetic variation in shoot K concentration
in B. oleracea
Species-wide genetic variation in [K]shoot of B. oleracea was
quantified in glasshouse (GE1) and field (FE1) experiments
that included substrate P concentration ([P]ext) as a treatment
factor (Fig. 1). There was substantial variation in [K]shoot
among the 343 B. oleracea genotypes of the DFS grown in
GE1, among the 75 commercial cultivars grown in GE1 and
among the 72 commercial cultivars grown in FE1.
In GE1, 18.3 % of the total variation in [K]shoot was attributed to the accession, [P]ext and [P]ext accession terms
(Table 1). The genetic variance component was highly significant (P , 0.001), accounting for 16.8 % of the total variation
in [K]shoot (Table 1). [K]shoot was greater at high [P]ext for most
accessions (Fig. 2A), but [P]ext accession interactions were
not significant (P . 0.05). In general, therefore, [K]shoot of
B. oleracea genotypes did not respond differently to altered
[P]ext. The [K]shoot of B. oleracea genotypes grown in GE1
ranged from 2.72 to 6.56 %DM at low [P]ext and from 2.06
to 6.94 %DM at high [P]ext (Figs 1 and 2A). [K]shoot differed
between subtaxa, with botrytis (cauliflower) and gongylodes
(kohlrabi) subtaxa having highest values and sabellica (borecole/curly kale), acephala (kale/collards) and italica (broccoli/calabrese) the lowest values (Fig. 1). Averaged across
both [P]ext, [K]shoot among DFS accessions ranged from 2.92
to 6.64 %DM (n ¼ 343) and the [K]shoot of commercial cultivars ranged from 3.27 to 5.94 %DM (n ¼ 75). Thus, the
extent of variation in [K]shoot observed among commercial cultivars was 72 % of the species-wide variation in [K]shoot. The
effect of shoot DM accumulation on [K]shoot was tested within
subtaxa, to avoid confounding effects of shoot morphology
(data not shown). These relationships were rarely significant.
At low [P]ext, [K]shoot was significantly (Fprob , 0.05) inversely correlated with shoot DM only within the alboglabra subtaxon. At high [P]ext, [K]shoot was significantly (Fprob , 0.05)
inversely correlated with shoot DM within the acephala and
capitata subtaxa.
There was substantial variation in [K]shoot among the 72
commercial cultivars grown in FE1 (Figs 1 and 2C).
Variance components attributed to accession, [P]ext and
[P]ext accession terms accounted for 16.4 % of the total variation in [K]shoot (Table 1). Genetic variance components for
[K]shoot were highly significant (P , 0.001) in FE1 and
accounted for 10.5 % of the total variation. The [P]ext accession interactions for [K]shoot were marginally significant (P ,
0.05). There were significant positive correlations between
[K]shoot at different [P]ext among the 72 commercial cultivars
grown in FE1 (e.g. Fig. 2C; P , 0.001). However, in contrast
to values in GE1, the [K]shoot of most genotypes grown in FE1
1202
White et al. — Genetics of potassium use efficiency in Brassica oleracea
8
A
Shoot K concentration (%DM)
7
6
5
4
3
2
FS
ea
D
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lic
ita
B
C
Shoot K concentration (%DM)
6
5
4
3
2
1
Glasshouse
Field
Glasshouse
Field
F I G . 1 Shoot K concentrations of Brassica oleracea genotypes represented in (A) the structured diversity foundation set (DFS) in glasshouse experiment one
(GE1; n ¼ 343), in B. oleracea subtaxa surveyed in GE1 (sabellica, n ¼ 6; acephala, n ¼ 40; italica, n ¼ 89; alboglabra, n ¼ 13; sabauda, n ¼ 15; tronchuda,
n ¼ 17; gemmifera, n ¼ 43; capitata, n ¼ 63; gongylodes, n ¼ 23; and botrytis, n ¼ 108), in (B) the commercial cultivars grown in GE1 and field experiment one
(FE1; n ¼ 75 and n ¼ 72, respectively), and in (C) lines from the AGDH genetic mapping population grown in GE2 and FE2 (n ¼ 92 and n ¼ 62, respectively).
Data are means of genotypes, averaged across all external P concentrations. The boundaries of the box closest to and furthest from zero indicate the 25th and 75th
percentiles, respectively. The solid and dotted lines within the box indicate the median and mean, respectively. Error bars indicate the 10th and 90th percentiles.
Circles indicate genotypes with extreme shoot K concentrations.
was greater at the lowest [P]ext than at the highest [P]ext
(Fig. 2C). In general, the [K]shoot of plants grown in the field
were lower than the [K]shoot of plants grown in the glasshouse,
which might, in part, be attributed to differences in available K
and/or the presence of competing cations between the two
environments. Averaged across all [P]ext, [K]shoot of
B. oleracea genotypes grown in FE1 ranged from 1.72 to
2.70 %DM, and [K]shoot were significantly (P , 0.001) positively correlated among the 70 cultivars grown successfully
in experiments GE1 and FE1 (Fig. 3A), indicating that
genotypic differences in [K]shoot were consistent between
field and glasshouse environments. However, the [K]shoot of
all commercial cultivars was higher in GE1 than in FE1
(Fig. 3A). Although there was a significant (P ¼ 0.0011) negative relationship between [K]shoot and shoot DM among commercial cultivars when grown at high [P]ext in the glasshouse,
no significant relationships were obtained between [K]shoot and
shoot DM among commercial cultivars when grown at low
[P]ext in the glasshouse or at any [P]ext in the field (data not
shown).
x2
,0.001
,0.001
0.577
0.20
0.20
0.16
0.46
0.82
0.26
16.8
1.5
0.0
47.2
W
1434
55
382
d.f.
428
1
424
x2
,0.001
,0.001
0.93
0.08
0.09
0.08
d.f.
71
3
213
x2
,0.001
,0.001
0.018
0.20
0.21
0.20
d.f.
99
1
99
x2
,0.001
,0.001
,0.001
0.17
0.18
0.16
d.f.
71
3
213
x2
,0.001
0.163
0.103
39.3
14.2
-1.9
48.3
W
235
32
28
12.3
6.5
10.0
23.7
2.0
1.9
43.7
W
512
5
239
32.1
4.7
2.9
12.2
22.2
2.2
1.4
22.2
W
936
89
154
25.7
4.1
3.1
19.7
10.5
5.1
0.8
30.9
W
867
26
259
Variance component
% variance, occasion
% variance, occasion/(bench, replicate)
% variance, occasion/(bench, replicate)/(run, block)
% variance, occasion/replicate/block/main_plot
% variance, accession (VA)
% variance, [P]ext
% variance, [P]ext/accession
% variance, residual
Fixed term
accession
[P]ext
[P]ext/accession
Standard errors of differences of mean
Average
Maximum
Minimum
19.5
7.3
7.7
1203
QTL affecting shoot K concentration in B. oleracea
d.f.
30
1
30
AGSL accessions
AGDH accessions
F1 cultivars
DFS and F1 cultivars
AGDH accessions
GE3
FE2
GE2
FE1
GE1
TA B L E 1. Variance components analyses of shoot K concentrations (%DM) of Brassica genotypes grown in the three glasshouse experiments (GE1, GE2 and GE3) and
the two field experiments (FE1, FE2)
White et al. — Genetics of potassium use efficiency in Brassica oleracea
Chromosomal QTL associated with [K]shoot were mapped
using an informative subset of 90 DH lines from the AGDH
population in both glasshouse (GE2) and field (FE2) experiments that included [P]ext as a treatment factor (Table 2).
These loci were confirmed and resolved using substitution
lines in a further glasshouse experiment (GE3).
A significant (P ¼ 0.014) positive correlation was observed
for [K]shoot among the nine reference B. oleracea accessions
grown in both GE1 and GE2 (Fig. 3B), suggesting that these
experiments were comparable. In GE2, the variance components attributed to accession, [P]ext and [P]ext accession
terms amounted to 25.8 % of the total variation in [K]shoot
(Table 1). The genetic variance component was highly significant (P , 0.001) and accounted for 22.2 % of the total variance in [K]shoot. However, in contrast to DFS accessions
and commercial cultivars grown in GE1, [P]ext accession
interactions were marginally significant (P , 0.05) for
[K]shoot in GE2, despite the highly significant (P , 0.001)
positive relationship between [K]shoot at low and high [P]ext
among the genotypes of the AGDH population (Fig. 2B).
[K]shoot varied significantly among the 92 DH lines and
parents of the AGDH population studied in GE2 and, as was
observed for the DFS and commercial cultivars studied in
GE1, [K]shoot was greater at high [P]ext for most AGDH lines
(Figs 1 and 2C). The [K]shoot of the DH lines grown in GE2
ranged from 3.93 to 6.50 %DM at low [P]ext and from 3.90
to 6.23 %DM at high [P]ext (Figs 1 and 2C). Averaged across
both [P]ext, the range of [K]shoot among the 92 B. oleracea genotypes sampled in GE2 (4.12– 6.36 %DM) suggested that this
population approximated 60 % of the species-wide variation in
[K]shoot observed in the glasshouse.
A significant (P ¼ 0.039, n ¼ 28) positive correlation was
observed for [K]shoot among the seven reference B. oleracea
accessions successfully grown in both FE1 and FE2
(Fig. 3C), suggesting that these experiments were comparable.
The variance components attributed to accession, [P]ext and
[P]ext accession terms amounted to 27.6 % of the total variation in [K]shoot in FE2 (Table 1). The genetic variance component was highly significant (P , 0.001) and accounted for
23.7 % of the total variation in [K]shoot (Table 1). Averaged
over all [P]ext, there was a significant (P , 0.001) positive correlation in the [K]shoot of the 62 genotypes from the AGDH
population grown in FE2 and GE2 (Fig. 3D), which is consistent with the significant positive correlation in [K]shoot of the 70
commercial cultivars grown in FE1 and GE1 (Fig. 3A). In
addition, [K]shoot of all the AGDH population was lower in
FE2 than in GE2 (Fig. 3D), as was observed for the commercial cultivars grown in FE1 and GE1 (Fig. 3A). The [P]ext accession interactions were not significant (P . 0.05) in
FE2. Thus, [K]shoot did not respond differently to altered
[P]ext among the AGDH lines grown in FE2. Shoot K concentration varied significantly among the 62 lines of the AGDH
population studied in FE2 and, as was observed for the commercial cultivars studied in FE1, [K]shoot was greater at low
[P]ext for most of the AGDH population (Figs 1 and 2).
There were also significant positive correlations between
[K]shoot at different [P]ext among the 62 lines of the AGDH
population grown in FE2 (e.g. Fig. 2D; P , 0.001).
White et al. — Genetics of potassium use efficiency in Brassica oleracea
Shoot K concentration (%DM)
at high [P]ext
1204
8
4
A (GE1)
6
3
4
2
2
1
0
0
0
Shoot K concentration (%DM)
at high [P]ext
C (FE1)
2
4
6
8
8
0
1
2
3
4
5
B (GE2)
D (FE2)
4
6
3
4
2
2
1
0
0
0
2
4
6
Shoot K concentration (%DM) at low [P]ext
8
0
1
2
3
4
5
Shoot K concentration (%DM) at low [P]ext
F I G . 2 Shoot K concentrations of Brassica oleracea genotypes grown at either low or high external P concentrations ([P]ext) in (A) glasshouse experiment one
(GE1) and (B) GE2, and at the lowest and highest P-fertilizer application rate ([P]ext) in (C) field experiment one (FE1) and (D) FE2. Among the 418 genotypes
compared in GE1, the following subtaxa were represented: acephala (n ¼ 40), alboglabra (13), botrytis (108), capitata (63), gemmifera (43), gongylodes (23),
italica (89), sabauda (15), sabellica (6), tronchuda (17) and one accession with no subtaxon assigned. Among the 72 commercial cultivars compared in FE1, the
following subtaxa were represented: acephala (n ¼ 6), alboglabra (1), botrytis (12), capitata (16), gemmifera (7), gongylodes (6), italica (10), sabauda (8) and
sabellica (6). Ninety accessions from the AGDH genetic mapping population plus the parents of this population, A12DHd and GDDH33, were compared in GE2
and 61 accessions from the AGDH genetic mapping population plus A12DHd were compared in FE2.
The [K]shoot of the 62 AGDH lines grown in FE2 ranged from
2.04 to 4.11 %DM with the lowest rate of P-fertilizer application and from 2.05 to 3.57 %DM with the highest rate of
P-fertilizer application (Figs 1 and 2D). Highly significant
(P , 0.001) negative relationships were observed between
[K]shoot and shoot Ca and Mg concentrations in the AGDH
population grown in the glasshouse (Fig. 4), and negative
relationships were also observed between [K]shoot and shoot
Ca (P ¼ 0.0018) and Mg (P ¼ 0.176) in the field (data not
shown).
In both glasshouse and field experiments, A12DHd had a
consistently higher [K]shoot than GDDH33 (e.g. Fig. 5).
Significant (log-likelihood of there being one vs. no QTL,
LOD . 3) or indicative (LOD . 2) QTL associated with
[K]shoot were detected on six of the nine linkage groups of
B. oleracea (Table 2). No QTL associated with [K]shoot were
detected on chromosomes C5, C6 or C8. The observed QTL
accounted for 83 % of the additive genetic variance component
(VA) for [K]shoot for plants grown in the glasshouse (GE2) and
44 % of the VA in [K]shoot for plants grown in the field (FE2).
However, no QTL associated with [K]shoot were identified in
both environments, despite the significant positive correlation
in [K]shoot among genotypes grown in the glasshouse and
field (Fig. 3). In GE2, there was a positive additive effect of
the A12DHd allele on [K]shoot at QTL on chromosomes C3,
C4 and C7, and a negative effect of the A12DHd allele
on [K]shoot at QTL on chromosomes C1 and C9 (Table 2).
In FE2, there was a positive effect of the A12DHd allele on
[K]shoot at QTL on chromosome C2 and a negative effect of
the A12DHd allele on [K]shoot at the QTL on chromosome
C9 (Table 2).
The presence of QTL associated with [K]shoot in glasshousegrown plants was tested using the AGSL substitution lines, in
which segments of GDDH33 are introgressed into the
A12DHd background (Rae et al., 1999; Broadley et al.,
2008; Hammond et al., 2009). As was observed in previous
experiments in the glasshouse, A12DHd had a higher
[K]shoot than GDDH33 (Fig. 5). Of the AGSL lines screened,
AGSL118 and ASGL119 were potentially informative for a
putative QTL associated with [K]shoot on chromosome C1
(91.2 cM) and AGSL121, AGSL122 and ASGL129 were
potentially informative for a putative QTL associated with
[K]shoot on chromosome C9 (33.5 cM), although the QTL lie
within chromosomal regions whose parental identity has not
yet been attributed in the AGSL lines, and AGSL165 and
AGSL168 were informative for a putative QTL associated
with [K]shoot on chromosome C7 (62.2 cM). The phenotypes
of AGSL118, ASGL119, AGSL121, AGSL122 and
ASGL129 were similar to A12DHd and therefore did not
confirm the putative QTL associated with [K]shoot on chromosome C1 (91.2 cM) or C9 (33.5 cM). However, the [K]shoot of
AGSL165 and AGSL168 (line 27) were lower than A12DHd,
apparently confirming the putative QTL associated with
[K]shoot on chromosome C7 (62.2 cM).
3·0
Shoot K concentration (%DM)
in GE2
Shoot K concentration (%DM)
in FE1
White et al. — Genetics of potassium use efficiency in Brassica oleracea
A
2·5
2·0
1·5
1·0
0·5
6
B
5
4
3
2
Low [P]ext
High [P]ext
1
0
0·0
0
1
2
3
4
5
6
7
0
1
Shoot K concentration (%DM) in GE1
4
C
3
2
1
0
0·0
40·7 mg P L–1
39·6 mg P L–1
81·7 mg P L–1
152·1 mg P L–1
0·5
1·0
1·5
2·0
2·5
2
3
4
5
6
Shoot K concentration (%DM) in GE1
Shoot K concentration (%DM)
in FE2
Shoot K concentration (%DM)
in FE2
1205
3·0
Shoot K concentration (%DM) in FE1
4
D
3
2
1
0
0
2
4
6
8
Shoot K concentration (%DM) in GE2
F I G . 3 (A) Shoot K concentrations averaged across all P-fertilizer application rates ([P]ext) of 70 Brassica oleracea genotypes grown in both field experiment one
(FE1) and glasshouse experiment one (GE1). The fitted line represents a significant linear regression (y ¼ 0.178x þ 1.396, R ¼ 0.402, Fprob , 0.001). (B) Shoot
K concentrations of nine reference B. oleracea genotypes grown in both GE1 and GE2 at low or high [P]ext as indicated. The fitted line represents a significant
linear regression (y ¼ 0.508x þ 2.293, R ¼ 0.57, Fprob ¼ 0.014, n ¼ 18). (C) Shoot K concentrations of seven reference B. oleracea genotypes grown in both FE1
and FE2 at [P]ext of 40.7, 39.6, 81.7 and 152.1 mg P L21 as indicated. The fitted line represents a linear regression (y ¼ 0.563x þ 1.586, R ¼ 0.391, Fprob ¼
0.039, n ¼ 28). (D) Shoot K concentrations averaged across all [P]ext of 62 accessions from the AGDH genetic mapping population grown in both field
(FE2) and glasshouse (GE2) environments. The fitted line represents a significant linear regression (y ¼ 0.360x þ 1.117, R ¼ 0.514, Fprob , 0.001).
TA B L E 2. Chromosomal quantitative trait loci (QTL) associated
with shoot K concentration (%DM) of Brassica oleracea grown
in glasshouse experiment two (GE2) and field experiment two
(FE2)
Glasshouse
Field
Linkage group
Position (cM)
LOD*
a†
R 2‡
C1
C3
C4
C4
C7
C9
C2
C2
C9
91.2
81.7
10.0
31.5
62.2
33.5
43.8
117.5
55.1
7.06
3.05
5.13
4.23
2.08
6.60
2.36
2.16
4.99
20.22
0.14
0.18
0.15
0.10
20.20
0.11
0.10
20.17
0.216
0.092
0.156
0.114
0.051
0.204
0.107
0.098
0.230
The QTL analysis is based on data for 90 lines (GE2) or 61 lines (FE2)
from the AGDH genetic mapping population averaged across all P
treatments.
* Log-likelihood of there being one vs. no QTL.
†
Additive effect of female (var. alboglabra) alleles.
‡
Proportion of additive genetic variance component (VA) explained by
QTL.
Potassium use efficiency in B. oleracea
Agronomic K use efficiency is the product of KUpE and
KUtE of a crop. The KUtE of a plant can be estimated as
the reciprocal of [K]shoot. There is therefore significant
genetic variation in KUtE, and QTL associated with KUtE correspond to QTL associated with [K]shoot (Table 2). The KUpE
of a plant can be estimated as the shoot K content and calculated as the product of shoot DM and [K]shoot. When grown in
the glasshouse or field, there is considerable variation in KUpE
among genotypes of B. oleracea. For example, in GE1 KUpE
varied between 1.7 and 62.5 mg K per plant when grown at
low P and between 6.1 and 108.9 mg K per plant when
grown at high P (Fig. 6A). Subtaxa differed in KUpE, with
botrytis and italica subtaxa having the lowest KUpE, and
capitata, sabauda and tronchuda subtaxa having the highest
KUpE. KUpE was higher in commercial cultivars than in
the DFS when grown in the glasshouse at low [P]ext (30.8 +
0.73 mg K per plant, n ¼ 79, vs. 27.8 + 0.47 mg K per
plant, n ¼ 340) or high [P]ext (71.4 + 1.76 mg K per plant,
n ¼ 79, vs. 59.9 + 1.00 mg K per plant, n ¼ 341). In FE1,
KUpE varied between 138.3 and 368.0 mg K per plant
among commercial cultivars when grown at the lowest
P-fertilizer application and between 110.3 and 300.3 mg K
per plant when grown at the highest P-fertilizer application
(data not shown). The KUpE of commercial cultivars was significantly (P ¼ 0.0012, n ¼ 70) correlated between glasshouse
and field experiments performed with an adequate P supply
(data not shown). Several QTL associated with KUpE were
identified using the AGDH population, which differed
1206
White et al. — Genetics of potassium use efficiency in Brassica oleracea
Shoot K concentration (%DM)
7
A
6
B
C
5
4
3
2
1
0
0·0
0·5
1·0
1·5
2·0
2·5
Shoot Ca concentration (%DM)
3·0
0·0
0·2
0·4
0·6
Shoot Mg concentration (%DM)
0·8
0·00
0·05
0·10
0·15
0·20
Shoot Na concentration (%DM)
0·25
F I G . 4. Relationships between shoot K concentration ([K]shoot) and (A) shoot Ca concentration ([Ca]shoot), (B) shoot Mg concentration ([Mg]shoot) and (C) shoot
Na concentration ([Na]shoot) averaged across both P-fertilizer application rates ([P]ext) for the 90 accessions from the AGDH genetic mapping population grown in
glasshouse experiment two (GE2). The fitted lines represent significant linear relationships between [K]shoot and [Ca]shoot (y ¼ 6.728 2 0.887x, R ¼ 0.436,
Fprob , 0.001), [K]shoot and [Mg]shoot (7.265 – 4.121x, R ¼ 0.482, Fprob , 0.001), and [K]shoot and [Na]shoot (y ¼ 5.534 þ3.857, R ¼ 0.296, Fprob ¼ 0.004).
6·0
Shoot K concentration (%DM)
A
C1
C9
C7
5·5
D IS C US S IO N
Genetic factors affecting shoot K concentration in B. oleracea
5·0
4·5
4·0
B
Shoot K concentration (%DM)
between glasshouse and field environments (Table 3). None of
these coincided with QTL for KUtE in this population.
6·0
5·5
5·0
4·5
A1
2D
H
d
G
D
D
H
AG 33
SL
1
AG 18
SL
1
AG 19
SL
1
AG 21
SL
1
AG 22
SL
1
AG 29
SL
1
AG 65
SL
16
8
4·0
F I G . 5. Shoot K concentrations ([K]shoot) in A12DHd (A alleles), GDDH33
(G alleles), and the AGSL substitution lines AGSL118, ASGL119,
AGSL121, AGSL122, ASGL129, AGSL165 and AGSL168 in which chromosomal segments of GDDH33 are introgressed into the A12DHd background
(Rae et al., 1999; Broadley et al., 2008; Hammond et al., 2009). Lines
AGSL118 and ASGL119 were potentially informative for a putative QTL on
chromosome C1 (91.2 cM) in which the G alleles increase [K]shoot. Lines
AGSL121, AGSL122 and ASGL129 were potentially informative for a putative QTL associated with [K]shoot on C9 (33.5 cM) in which the G alleles
increase [K]shoot. Lines AGSL165 and AGSL168 were informative for a putative QTL associated with [K]shoot on C7 (62.2 cM) in which the G alleles
decrease [K]shoot. Data show means + s.e.m. of three replicates of each genotype grown in glasshouse experiment three (GE3) with (A) low P or (B) high P
supply. Horizontal lines indicate the mean [K]shoot of the parental lines
AD12DHd and GDDH33.
This study has demonstrated up to 3.4-fold variation in [K]shoot
among B. oleracea genotypes when grown under identical
conditions (Fig. 1), a significant proportion of which could
be attributed to genetic factors (Table 1). This is consistent
with previous studies showing 1.4- to 2.3-fold variation in
[K]shoot among B. oleracea kales and collards grown together
in the glasshouse or field (Kopsell et al., 2004; Vilar et al.,
2008). The [K]shoot of B. oleracea genotypes correlated
between glasshouse and field environments (Fig. 3A, D), and
was relatively insensitive to P supply (Table 1, Fig. 2).
When grown in the glasshouse, the variation in [K]shoot
among commercial cultivars was about 72 % of the specieswide variation in [K]shoot, and the variation in [K]shoot
among AGDH lines was about 60 % of the species-wide variation in [K]shoot (Fig. 1). This suggests an opportunity to alter
[K]shoot through the introduction of alleles from the wider gene
pool into elite germplasm.
Several QTL associated with [K]shoot were identified using
the AGDH population, although these differed between glasshouse and field environments (Table 2). It is most likely that
environmental factors affecting, for example, plant growth
rates, rooting volume or differences in K availability determined the most influential physiological traits and therefore
the QTL associated with [K]shoot in the glasshouse and field
environments. It is unlikely that the different QTL arose as
an artefact from the different numbers of AGDH lines
employed for mapping QTL in glasshouse and field environments. One of the QTL associated with [K]shoot in glasshousegrown plants (on chromosome C7 at 62.2 cM) was confirmed
from the phenotypes of AGSL165 and AGSL168 (Fig. 5). This
locus falls largely in a region of co-linearity with a section of
arabidopsis chromosome 4 (Parkin et al., 2005). The closest
genetic marker on the B. oleracea map is an orthologue of
arabidopsis AtIRT1 (At4g19690) at 61.3 cM, and a gene encoding the putative plasma membrane Kþ transporter AtKUP9
(At4g19960) is in the vicinity of AtIRT1 (White and Karley,
White et al. — Genetics of potassium use efficiency in Brassica oleracea
2·5
TA B L E 3. Chromosomal quantitative trait loci (QTL) associated
with Kþ uptake efficiency (KUpE) of Brassica oleracea grown in
glasshouse experiment two (GE2) and field experiment two
(FE2)
A
Yield (g DM)
2·0
1·5
Glasshouse
1·0
Field
0·5
0·0
0
20
40
60
80
100
120
KUpE (mg K plant–1 )
2·5
B
Yield (g DM)
2·0
1·5
1·0
0·5
0·0
0·00
0·01
0·02
0·03
KUtE (g DM
0·04
mg–1
0·05
0·06
100
120
K)
0·06
C
KUtE (g DM mg–1 K)
0·05
0·04
0·03
0·02
0·01
0·00
0
1207
20
40
60
KUpE (mg K
80
plant–1
)
F I G . 6. Relationships between shoot biomass and (A) potassium uptake efficiency (KUpE), expressed as plant K content, and (B) potassium utilisation
efficiency (KUtE), expressed as the reciprocal of shoot K concentration,
among B. oleracea genotypes assayed in glasshouse experiment one (GE1)
with adequate P supply (high [P]ext). The fitted line in A represents a significant linear relationship between plant biomass and plant K content (y ¼
0.019x þ 0.156, R ¼ 0.904, Fprob , 0.001, n ¼ 420). (C) Relationship
between KUtE and KUpE among B. oleracea genotypes assayed in the GE1
with adequate P supply (high [P]ext). The fitted line represents a significant
linear relationship between KUtE and KUpE (y ¼ 0.025 2 0.000053x, R ¼
0.314, Fprob , 0.001, n ¼ 420).
Linkage group
Position (cM)
LOD*
a†
R 2‡
C1
C3
C3
C9
C5
32.6
23.1
43.4
103.9
36.1
2.36
3.81
4.35
2.96
2.70
3.38
3.91
4.06
23.41
216.92
0.077
0.126
0.138
0.099
0.16
The QTL analysis is based on data for 90 lines (GE2) or 61 lines (FE2)
from the AGDH genetic mapping population averaged across all P
treatments.
* Log-likelihood of there being one vs. no QTL.
†
Additive effect of female (var. alboglabra) alleles.
‡
Proportion of additive genetic variance component (VA) explained by
QTL.
2009). Genes encoding the Kþ channels AtAKT2 (At4g22200),
AtKAT2 (At4g18290) and the putative Kþ channel AtTPK3
(At4g18160) are also in close proximity to AtIRT1 (White
and Karley, 2009). Similarly, this marker is present within a
sequenced B. rapa BAC (KBrB085J21), which contains an
orthologue of AtKUP9. The arabidopsis genome contains
approximately 32 000 genes and about 450 of these are
located between At4g18160 and At4g222000. Based on a
two-way contingency table, the probability that four of the
111 genes encoding Kþ-transporters are found in this region
(P ¼ 0.048) suggests that it contains more Kþ-transporters
than would be expected by chance (Karley and White, 2009).
To confirm and resolve QTL associated with [K]shoot to
smaller candidate regions a further backcrossing programme
would now be appropriate using a subset of the AGSL lines.
No QTL associated with [K]shoot in the AGDH population
observed in either the glasshouse or the field co-localized
with any QTL associated with shoot DM accumulation or
shoot P, Mg or Ca concentrations (Broadley et al., 2008;
Hammond et al., 2009), despite highly significant (P ,
0.001) negative relationships between [K]shoot and shoot Ca
and Mg concentrations in these plants in the glasshouse
(Fig. 4). Similarly, no QTL associated with [K]shoot in the
AGDH population observed in either the glasshouse or the
field co-localized with any QTL associated with shoot Na concentration (Table 4), despite the significant (P ¼ 0.0042) positive correlation between [K]shoot and shoot Na concentration
among AGDH lines assayed in the glasshouse (Fig. 4C) and
the significant (P ¼ 0.008) negative correlation between
[K]shoot and shoot Na concentration among AGDH lines
assayed in the field (data not shown). Nor did any QTL associated with [K]shoot co-localize with any QTL associated with
aspects of seedling vigour previously identified in this population (Bettey et al., 2000). No QTL associated with [K]shoot
in the AGDH population co-localized with any QTL associated with leaf N concentration in another B. oleracea genetic
mapping population (NGDH) grown in the glasshouse
(Hall et al., 2005), nor did any QTL associated with [K]shoot
1208
White et al. — Genetics of potassium use efficiency in Brassica oleracea
TA B L E 4. Chromosomal quantitative trait loci (QTL) associated
with shoot Na concentration (%DM) of Brassica oleracea grown
in glasshouse experiment two (GE2) and field experiment two
(FE2)
Glasshouse
Field
Linkage group
Position (cM)
LOD*
a†
R 2‡
C2
C2
C2
C3
C9
C2
70.2
100.4
113.5
70.4
12.9
78.2
2.35
2.12
2.11
3.56
4.04
10.57
20.01
20.01
20.01
0.01
20.01
20.07
0.074
0.084
0.065
0.127
0.142
0.572
AtNHX3 (Harada and Leigh, 2006). Recently, large-scale
ionomic profiling programmes have collected data on [K]shoot
for many arabidopsis accessions and for several arabidopsis
genetic mapping populations (Baxter et al., 2007). Rapid progress in linkage mapping and association genetics in arabidopsis (Nordborg and Weigel, 2008), together with the use of
comparative genomic information (Parkin et al., 2005;
Schranz et al., 2006, 2007), will facilitate the transfer of
knowledge of QTL and genes affecting [K]shoot between arabidopsis and other species in the Brassicaceae.
Potassium use efficiency in B. oleracea
The QTL analysis is based on data for 90 lines (GE2) or 61 lines (FE2)
from the AGDH genetic mapping population averaged across all P
treatments.
* Log-likelihood of there being one vs. no QTL.
†
Additive effect of female (var. alboglabra) alleles.
‡
Proportion of additive genetic variance component (VA) explained by
QTL.
identified in the AGDH population co-localize with any of the
QTL for the 17 morphological and developmental traits scored
in the NGDH population (Sebastian et al., 2002). Thus, it
would appear that the QTL associated with [K]shoot reported
here were not associated with any QTL associated with plant
growth rate or morphology, nor were they the consequence
of pleiotropic effects of a non-specific QTL.
Significant genetic variation in [K]shoot has also been
observed among arabidopsis accessions, and genetic variation
in [K]shoot among a recombinant inbred population of arabidopsis developed from a cross between the Landsberg erecta
(Ler) and Cape Verde Island (CVI) accessions has allowed
several QTL associated with this trait to be mapped (Harada
and Leigh, 2006). Four QTL associated with [K]shoot expressed
on a fresh weight basis were mapped to chromosomes 2 (at
40 cM), 4 (at 43 cM) and 5 (at 82 and 106 cM), and three
QTL associated with [K]shoot in dry matter were mapped to
chromosomes 3 (at 0 cM), 4 (at 43 cM) and 5 (at 106 cM).
None of these QTL co-localized with QTL associated with
either FW or DM accumulation, suggesting that [K]shoot and
biomass accumulation were genetically independent under
the environmental conditions in which these plants were
grown. However, the QTL on chromosome 2 co-localized
with a QTL for seed K concentration occasionally observed
in this population (Waters and Grusak, 2008) and the QTL
on the bottom of chromosome 3 co-localized with one of
several QTL associated with seed K concentration in both
this and three other genetic mapping populations of arabidopsis (Vreugdenhil et al., 2004; Ghandilyan et al., 2009). On
chromosome 5 the QTL at 82 cM co-localized with a QTL
for seed K concentration occasionally observed in two other
genetic mapping populations of arabidopsis (Waters and
Grusak, 2008; Ghandilyan et al., 2009), and the QTL on
chromosome 5 at 106 cM co-localized with a QTL associated
with shoot Cs concentration expressed on a fresh weight basis
in the Ler CVI population (Payne et al., 2004). Candidate
genes within these chromosomal QTL include many putative
cation transporters, including AtAKT1, AtAKT6, AtKAT1,
AtSKOR, AtCNGC1, AtCNGC5, AtCNGC6, AtCNGC14,
AtTPK1, AtTPK2, AtKCO3, AtHAK5, AtKEA5 and
The efficiency with which K-fertilizers are used in crop production is of both commercial and environmental importance.
Considerable variation in both KUpE and KUtE was observed
among genotypes of B. oleracea when grown in either
the glasshouse or the field (Fig. 6). Several QTL associated
with KUpE (Table 3) and KUtE (1/[K]shoot, Table 2) were
identified using the AGDH population, but these QTL differed
between glasshouse and field environments, suggesting that
they are influenced profoundly by environmental vagaries.
Furthermore, no QTL for KUpE coincided with QTL for
KUtE in either environment, and there was a strong negative
correlation between these traits (Fig. 6C). These observations
imply that several QTL will have to be combined to achieve
improved KUpE and/or KUtE across diverse environments,
and that the environmental factors influencing the relative
importance of specific QTL will have to be defined.
Greater KUpE is generally attributed to better Kþ acquisition from the soil solution (Jungk and Claassen, 1997;
Baligar et al., 2001; Trehan, 2005; Rengel and Damon,
2008; White and Karley, 2009). Theoretical models suggest
that diffusion through, and mass flow of, the soil solution contribute most to the delivery of Kþ to the root surface (Jungk
and Claassen, 1997). Differences in Kþ acquisition between
genotypes might therefore be attributed to: (1) the rate of Kþ
uptake across the plasma membrane of root cells, which
reduces the Kþ concentration in the rhizosphere solution
and increases diffusional Kþ fluxes; (2) the release of
non-exchangeable Kþ by root exudates, which increases Kþ
concentration and availability in the soil solution; (3) the proliferation of roots into the soil volume, which increases the
area for Kþ uptake and also reduces the distance required for
Kþ diffusion and water flow; and (4) the transpiration rate of
the plant, which drives mass flow of the soil solution to the
root (Jungk and Claassen, 1997; Baligar et al., 2001;
Høgh-Jensen and Pedersen, 2003; Trehan, 2005; Rengel and
Damon, 2008; White and Karley, 2009). It has been observed
that Brassica genotypes differ greatly in their ability to
reduce Kþ concentrations in the rhizosphere (Shi et al.,
2004), that members of the Brassicaceae access considerable
quantities of soil K from the non-exchangeable fraction
(Jungk and Claassen, 1997; Shi et al., 2004), that the identity
and quantities of organic acids exuded by roots differ markedly
between Brassica genotypes (Akhtar et al., 2006, 2008), and
that the growth rate and architecture of the root system differ
markedly between genotypes of B. oleracea (Hammond et al.,
2009). Future studies should investigate these properties in
B. oleracea genotypes with contrasting KUpE.
White et al. — Genetics of potassium use efficiency in Brassica oleracea
Greater KUtE, especially at low K supply, can be achieved
by better K redistribution within a plant to tissues with
immediate K requirements and/or by improving a plant’s
ability to maintain appropriate cytoplasmic K concentrations,
either by anatomical adaptations or by the substitution of Kþ
for other solutes, such as Ca2þ or Naþ, in the vacuole
(Rengel and Damon, 2008; White and Karley, 2009). Future
studies should investigate these properties in B. oleracea genotypes with contrasting KUtE.
There was a highly significant (P , 0.001) negative correlation between KUpE and KUtE among B. oleracea genotypes
in both the glasshouse and the field (e.g. Fig. 6C). In addition,
there was a highly significant (P , 0.001) correlation between
shoot biomass and KUpE (Fig. 6A), but no relationship
between shoot biomass and KUtE (Fig. 6B). This suggests
that shoot biomass and KUtE are genetically independent.
This contrasts with a previous study of 84 canola (B. napus)
genotypes, which suggested that growth responses to low
soil K phytoavailability in glasshouse trials could be determined by either KUpE or KUtE depending upon the genotype
(Damon et al., 2007). In their study, Damon et al. (2007)
classified canola genotypes as K-efficient based on high
values for the shoot DM ratio at deficient versus adequate
K supply. They observed that growth rates of K-efficient genotypes differed considerably at low K supply and concluded
that K-efficient genotypes with high growth rates at low
K supply have the ability to improve yields irrespective of
K supply. Several B. oleracea accessions studied here can
similarly be identified as having high yields and high KUtE
or KUpE when grown with an adequate P supply (Fig. 6).
CON C L U S IO NS
Considerable variation in [K]shoot was observed among
B. oleracea genotypes grown in the glasshouse or the field, a
significant proportion of which (between 10 and 25 %) could
be attributed to genetic factors. This should be sufficient for
breeding for KUtE in B. oleracea. However, although
several QTL associated with [K]shoot were identified using
the AGDH genetic mapping population, and despite a significant correlation in [K]shoot among these genotypes grown in
the glasshouse and field, QTL differed between glasshouse
and field environments. One of the QTL associated with
[K]shoot in glasshouse-grown plants (chromosome C7 at
62.2 cM) was confirmed from the phenotypes of AGSL165
and AGSL168. This QTL corresponds to a segment of arabidopsis chromosome 4 that contains genes encoding the
plasma membrane Kþ-transporter AtKUP9 (At4g19960) and
the Kþ channels AtAKT2 (At4g22200), AtKAT2
(At4g18290) and AtTPK3 (At4g18160). Agronomic K use
efficiency is the product of KUpE and KUtE. In B. oleracea,
KUpE correlated strongly with shoot biomass, but KUtE
(1/[K]shoot) did not. This implies that KUtE and biomass can
be genetically manipulated independently. In the context of
conventional agriculture, breeding for increased KUtE and
KUpE will decrease crop K requirements and K-fertilizer
applications. However, as QTL impacting these traits differ
between glasshouse and field environments, marker-assisted
breeding programmes must consider carefully the conditions
under which the crop will be grown.
1209
ACK NOW LED GE MENTS
This work was supported by the UK Biotechnology and
Biological Sciences Research Council, the UK Department
for Environment, Food and Rural Affairs, and the Scottish
Government Rural and Environment Research and Analysis
Directorate.
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