Tissue-dependent limited pleiotropy affects geneexpression in barley

Elena Potokina1,†,‡, Arnis Druka2,†, Zewei Luo1,3, Matthew Moscou4, Roger Wise4,5, Robbie Waugh2 and Mike Kearsey1,*

1School of Biosciences, The University of Birmingham, Birmingham B15 2TT, UK,2Scottish Crop Research Institute, Invergowrie, Dundee DD2 5DA, UK,3Laboratory of Population & Quantitative Genetics, School of Life Sciences, Institute of Biomedical Sciences,

Fudan University, Shanghai 200433, China,4Bioinformatics and Computational Biology Graduate Program & Department of Plant Pathology, Iowa State University,

Ames, IA 50011-1020, USA, and5Corn Insects and Crop Genetics Research, USDA-ARS, Iowa State University, Ames, IA 50011-1020, USA

Received 16 April 2008; revised 21 May 2008; accepted 30 May 2008; published online 29 July 2008.*For correspondence (fax +44 121 414 5925; e-mail m.j.kearsey@bham.ac.uk).†Both authors contributed equally to this work.‡Present address: Vavilov Institute of Plant Industry (VIR), Bolshaya Morskaya, 44, 190000, St Petersburg, Russia.

Summary

Non-synonymous coding mutations in a gene change the resulting protein, no matter where it is expressed,

but the effects of cis-regulatory mutations could be spatially or temporally limited – a phenomenon termed

limited pleiotropy. Here, we report the genome-wide occurrence of limited pleiotropy of cis-regulatory

mutations in barley (Hordeum vulgare L.) using Affymetrix analysis of 22 840 genes in a population of 139

doubled haploid lines derived from a cross between the cultivars Steptoe (St) and Morex (Mx). We identified

robust cis-acting expression regulators that segregate as major genes in two successive ontogenetic stages:

germinating embryo tissues and seedling leaves from the embryonic axis. We show that these polymorphisms

may be consistent in both tissues or may cause a dramatic change in transcript abundance in one tissue but not

in another. We also show that the parental allele that increases expression can vary with the tissue, suggesting

nucleotide polymorphism in enhancer sequences. Because of the limited pleiotropy of cis-regulating

mutations, the number of cis expression quantitative trait loci (cis-eQTLs) discovered by ‘genetical genomics’

is strongly affected by the particular tissue or developmental stage studied. Given that limited pleiotropy is

a common feature of cis-regulatory mutations in barley, we predict that the phenomenon would be relevant

to developmental and/or tissue-specific interactions across wide taxonomic boundaries in both plants

and animals.

Keywords: barley, cis-eQTL, gene expression, genetical genomics, pleiotropy.

Introduction

Variation in gene expression is a heritable trait, and can be

mapped in segregating populations using the approaches of

genetical genomics (Jansen and Nap, 2001). For those

organisms with sequenced genomes, the approach provides

an unprecedented opportunity to compare the genetic

position of the gene encoding each transcript with the

position of its expression quantitative trait locus (eQTL),

thereby making it possible to discriminate between the cis-

and trans-regulatory control elements of gene expression

for thousands of genes across the genome (Brem et al.,

2002; Schadt et al., 2003; Hubner et al., 2005; Keurentjes

et al., 2007; West et al., 2007). Cis-acting variation has been

proposed as a major determinant of quantitative phenotypic

traits, and so the detection of cis-eQTLs is a matter of par-

ticular significance (Stamatoyannopoulos, 2004). Addition-

ally, co-segregation of a cis-eQTL with the gene itself

confirms its authenticity.

Whereas non-synonymous coding mutations change the

resulting protein, no matter where the gene is expressed, the

effects of cis-regulatory mutations could be spatially or

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The Plant Journal (2008) 56, 287–296 doi: 10.1111/j.1365-313X.2008.03601.x

temporally limited, e.g. to larval anatomy, without affecting

the adult, or just to a single organ or tissue, even when the

gene is much more widely expressed. This phenomenon is

known as reduced or limited pleiotropy (Stern, 2000; Wray,

2007). Similar effects can arise from tissue-specific tran-

scription factors. Limited pleiotropy has been observed in

many cases in which cis-regulatory mutations have an

ecologically significant phenotypic impact (Wray, 2007).

Analogously, Li et al. (2006) have demonstrated the exis-

tence of plasticity QTLs (pQTLs) in Caenorhabditis elegans,

which result in changing levels of expression in different

environments (temperature in their case) that were prepon-

derantly trans-acting QTLs, and which could be responsible

for responses to fluctuating environments.

Although variability in gene expression at a genome-wide

scale across tissues is well known for both sequenced (cf.

Novak et al., 2002) and unsequenced organisms (cf. Druka

et al., 2006), there are very few studies focusing on the

tissue-specific appearance and behaviour of cis-regulatory

elements. Recently, tissue specificity of eQTLs was reported

for rats (Petretto et al., 2006). The investigation of pleiotropy

of cis-regulatory mutations becomes more challenging with

unsequenced species, because the lack of precise informa-

tion about the physical location of genes makes separation

of cis- from trans- eQTLs very difficult. Rice synteny was

recently employed for physically mapping wheat expressed

sequence tags (ESTs), in order to compare the physical

position of the ESTs with their expression mapping data

obtained using wheat doubled haploid lines (Jordan et al.,

2007). Another approach employed for barley (Potokina

et al., 2007) was based on the numerous published reports

indicating that the proportion of gene expression patterns

that can be accounted for by cis-acting versus trans-acting

components depends heavily on the threshold applied for

eQTL detection (Gibson and Weir, 2005; Hubner et al., 2005;

Keurentjes et al., 2007; West et al., 2007; Yamashita et al.,

2005). As a result, the highly heritable cis-eQTLs can be

widely recognized by their extremely high log of odds (LOD)

scores relative to the rest of the genes (Potokina et al., 2007),

and confirmed by single-nucleotide polymorphisms (SNPs).

Although co-segregation technically only confirms local

regulation (Rockman and Kruglyak, 2006), we use the term

‘cis-regulation’ to imply all near-regulation that has not been

resolved by recombination. Trans-eQTLs may also have

high LOD scores, although less frequently (Luo et al., 2007),

but are less easy to reject as false positives.

In the present paper we investigate the tissue-specific

appearance of cis-eQTLs in barley, one of the most impor-

tant crop species with an unsequenced genome. To address

this issue we analysed the steady-state mRNA transcript

abundance (sometimes referred to as ‘expression’) reported

by 22 840 probe sets (from here on termed ‘genes’) on

Affymetrix Barley 1 GeneChips across 139 double-haploid

(DH) lines of the Steptoe (St)/Morex (Mx) barley mapping

population in one tissue, and in a subset of 30 DH lines for a

second tissue, with the two tissues being derived from

different temporal development stages. Working with the

restricted mapping population, we focused only on the

highly heritable cis-eQTLs that segregated like major genes

and that were reproducible with the larger set of 139 DH lines

both in expression and SNP genotype. The number of cis-

eQTLs detected with an empirically established statistical

threshold was found to be strongly dependent on the

particular tissue, demonstrating that limited pleiotropy of

cis-regulatory mutations occurs widely in barley. This sug-

gests that the question ‘how many genes are regulated in

cis?’ is context-dependent, with different outcomes for

different tissues, as well as different crosses, under analysis.

Results

The natural nucleotide polymorphism between St and Mx in

the regulatory part of genes may affect an interaction of a

gene promoter with RNA polymerase and transcription fac-

tors. As a consequence, alleles of St and Mx would result in

different levels of gene transcript abundance, and this can be

detected by eQTL analysis in the mapping population of DH

lines of the St/Mx cross. Because of the limited pleiotropy of

cis-regulatory mutations, the linkage might be discovered in

one tissue, but not in another. To test this hypothesis, we

compared the chromosomal locations of highly significant

eQTLs detected in two tissues: the embryo-derived tissue of

germinating barley grains (subsequently referred to as

‘embryo’) and leaves of 12-day-old seedlings (‘leaf’), and

compared them with SNP data for the same genes.

Overall tissue effect on transcript abundance level and

tissue-specific cis-regulators

We started by estimating the overall tissue effect on the

22 840 genes, by comparing the relative abundance of their

transcripts across 32 genotypes (two parents and 30 DH

lines) in embryo and leaf tissues. Initially, we mainly focused

on the between-group variation (expression in embryo vs

expression in leaves) caused by tissue-specific gene regula-

tion, without regard to genetic polymorphism within the DH

lines. A one-way ANOVA detected 19 958 genes (87% of the

total gene number on the array) in which the transcript

abundance level differed significantly between tissues

(FDR < 0.05; Benjamini and Hochberg, 1995) (Table S1).

Among these, approximately half (9985) were higher in the

embryo, whereas the other half (9973) were higher in the leaf.

We observed that replacing the St for an Mx allele for

many genes significantly affected the tissue-specific regula-

tion. Contig6206_s_at (Figure 1a) is an example of a gene

being completely suppressed in the embryo (all hybridiza-

tion signals were classified by the MAS 5.0 algorithm as

‘Absent’), but was activated in leaves, although only in DH

288 Elena Potokina et al.

ª 2008 The AuthorsJournal compilation ª 2008 Blackwell Publishing Ltd, The Plant Journal, (2008), 56, 287–296

lines that carried the Mx allele. In contrast, Contig19508_at

(Figure 1b) was not detectably transcribed in leaves (all

hybridization signals were classified as ‘Absent’), and was

specifically expressed in embryo tissue, but again only in

those offspring that inherited the Mx allele for the gene. The

St allele produced no detectable transcript in either tissue for

Contig3642_at (the ‘Absent’ call was obtained for all DH lines

carrying St allele; Figure 1c). Contig13784_at (Figure 2a) was

detectably expressed in both tissues; however, the St allele

decreased the transcript abundance just in the embryo,

while no allele-specific gene expression was detected in

leaves. Remarkably, the alleles of the particular parent (e.g.

Mx) may increase the transcription level of a gene in the

embryo, but decrease it in leaves (Figure 2b). To determine

the biological relevance of this phenomenon it would be

informative to estimate the frequency of occurrence for each

class of tissue-specific expression pattern. Technically, this

can be achieved via eQTL analysis of the gene expression

data available for the 30 DH lines in two tissues to compare

positions of the eQTLs mapped for the same gene, but in two

different tissues, as described below.

Tissue-specific cis-regulators and the empirical

genome-wide threshold of eQTL significance

In a previous paper (Potokina et al., 2007), we presented

evidence for 23 738 eQTLs in this population of 139 DH lines

for embryo tissue, whereas in an earlier paper (Luo et al.,

2007) we identified expression markers using a subset of 30

DH lines based on leaf tissue. In the latter case, only 30 lines

were available, but we now wish to compare the cis-eQTLs

for the two tissues in these 30 DH lines to explore limited

pleiotropy on a genome-wide scale. The use of such a small

population required several key steps to minimize false gene

discovery, including reference to the full 139-line set and to

SNP data.

We thus carried out eQTL analysis with gene expression

data available for the 30 DH lines, and compared the

positions of the eQTLs mapped in the two tissues. To avoid

false eQTLs artificially created by background noise, only

those genes expressed at a detectable level were subjected

to eQTL analysis. Thus, out of 22 840 genes on the chip, we

analysed the transcript abundance variation for the 15 967

(70%) genes for embryo tissue and the 15 247 (67%) genes

for leaf tissue that were classified by the MAS 5.0 algorithm

as ‘Present’ for at least two out of three replications of St or

Mx hybridizations. The ‘Present’ flags designate genes in

which the hybridization signal differs from the background

significantly (P < 0.05). The two sets of mapped expression

profiles for different tissues overlapped for 13 940 genes.

Altogether, 15 967 (embryo) and 15 247 (leaf) genes were

each tested by composite interval mapping (CIM) for linkage

between transcript level variation and a marker position

in one of the 209 recombination bins of the seven

9

10(a)

(b)

(c)

6

7

8

3

4

5

8.5

7.0

7.5

8.0

5.0

5.5

6.0

6.5

4.5

9.0

9.5

7.5

8.0

8.5

P1 DH(P1) P2 DH(P2) . P1 DH(P1) P2 DH(P2)

P1 DH(P1) P2 DH(P2) . P1 DH(P1) P2 DH(P2)

P1 DH(P1) P2 DH(P2) . P1 DH(P1) P2 DH(P2)

6.0

6.5

7.0

Figure 1. Tissue-specific pattern of gene expression across 30 double-haploid

(DH) lines of the Steptoe (St)/Morex (Mx) cross.

Expression level is shown on the y-axis (log scale) for embryo tissue (on the

left) and leaf tissue (on the right). The DHs are assigned to genotypic classes

and mean values (black mark) plus SD (hashed boxes) are depicted for P1

(Morex), P2 (Steptoe) and genotypic classes DH(P1) and DH(P2).

(a) Contig6206_s_at: allele-specific expression appearing only in leaf tissue.

(b) Contig19508_at: allele-specific expression appearing only in embryo

tissue.

(c) Contig3642_at: allele-specific expression detected in both tissues

analysed.

Tissue-dependent gene expression in barley 289

ª 2008 The AuthorsJournal compilation ª 2008 Blackwell Publishing Ltd, The Plant Journal, (2008), 56, 287–296

chromosomes in this restricted population. The resulting

LOD profiles were examined to determine eQTL peaks, as

described previously (Potokina et al., 2007). To establish a

threshold for declaring eQTLs to be statistically significant,

we used the global permutation threshold (GPT) approach

(West et al., 2007) (see also Experimental procedures).

Accordingly, each eQTL peak was assigned to the corre-

sponding P-value, reflecting its genome-wide significance

obtained by the permutation approach.

Not only do false eQTLs arise from the multiple testing of

thousands of expression traits, but they also arise from the

very small size of the mapping population (n = 30) for which

we had expression data for both tissues. The linkage

obtained might be consistent for the particular set of 30

genotypes and, therefore, it would pass through the permu-

tation test, but it is at risk of not being reproducible with a

larger set of recombinants. The smaller the subset of

genotypes, the more likely it is that a linkage can reflect a

spurious association from a biased selection of the 30

genotypes. For this reason, large mapping populations (of at

least n > 100) are routinely used for QTL mapping practice.

To account for these statistical issues, we have estab-

lished an empirically estimated genome-wide threshold for

the eQTL significance. The 30 DH lines analysed for eQTLs in

the present study were a subset of the larger mapping

population of 139 DHs previously subjected to eQTL analysis

using transcript abundance in embryo tissue (Potokina et al.,

2007). We evaluated the proportion of the eQTLs detected

with the 30-lines set that was also reproducible with the 139-

DH population, at different thresholds of the eQTL signifi-

cance obtained via permutation tests. Table 1 shows that a

genome-wide significance threshold of P £ 0.0004 allows us

to keep the empirical false discovery rate (FDR) at the 5%

level for the panel of 30 DH lines. The significance threshold

obtained was comparable with the threshold (P < 0.001,

FDR < 0.05) detected previously for a panel of 30 rat

recombinant inbred strains (Hubner et al., 2005; Petretto

et al., 2006). Using the established significance threshold

(P £ 0.0004, FDR < 0.05), 1527 eQTLs were detected for the

embryo tissue, and 1158 eQTLs were detected for the leaf

10.0

10.2(a)

(b)

9.4

9.6

9.8

8.6

8.8

9.0

9.2

8.2

8.4

9.5

10.0

8.0

8.5

9.0

6.5

7.0

7.5

5.5

6.0

P1 DH(P1) P2 DH(P2) . P1 DH(P1) P2 DH(P2)

P1 DH(P1) P2 DH(P2) . P1 DH(P1) P2 DH(P2)

Figure 2. Limited pleiotropy of cis-regulatory mutations and reciprocal

change in the parent that contributes the allele with the most abundant

transcript.

The double haploids (DHs) are assigned to genotypic classes and mean values

(black mark) plus SD (hashed boxes) are depicted for P1 (Morex), P2 (Steptoe)

and genotypic classes DH(P1) and DH(P2).

(a) Contig13784_at: a cis-regulatory mutation modifies transcript abundance

in just a single tissue, even when the gene is more widely expressed.

(b) Contig4374_s_at: the allele of parent Steptoe (P2) maintains consistent

expression in leaf and embryo, whereas the allele of parent Morex (P1)

increases transcription efficiency in embryo, but decreases efficiency in

leaves.

Table 1 Comparisons of the numbers of expression quantitative trait loci (eQTLs) controlling gene expression in the embryo detected at variousLOD thresholds in the 30 double-haploid (DH) line population compared with those confirmed in the 139-line population

LOD threshold foreQTLs in 30-DHpopulation

Genome-wide significanceafter a permutation testwith the 30-line population(P-value)

Total number of eQTLsdetected with the 30-linepopulation

Number of eQTLs detected withthe 30-line population andsupported with 139-linepopulation Proportion

>3.08 <0.05 32 401 6755 0.208>4.06 <0.01 19 984 5528 0.277>8.47 <0.001 2465 2051 0.832>9.47 <0.0006 1843 1697 0.921>9.85 <0.0005 1673 1581 0.945‡10 £0.0004 1607 1527 0.950

290 Elena Potokina et al.

ª 2008 The AuthorsJournal compilation ª 2008 Blackwell Publishing Ltd, The Plant Journal, (2008), 56, 287–296

tissue. Multiple eQTLs were identified in each tissue for�2%

of these genes, and were removed from the analysis. This

left 2081 unique eQTLs (one eQTL per gene), of which 1498

and 1134 eQTLs were found in the embryo and leaf tissue,

respectively; of these, 551 eQTLs were common to both

tissues (Table S2).

The selected eQTLs represent the highest LOD scores

relative to the rest of the genes: they fall into the 95% and

96% percentile boundaries of the total distribution of all LOD

scores detected for embryo and leaf tissue (data not shown),

and, therefore, they are most likely to be cis-regulators

(Gibson and Weir, 2005; Hubner et al., 2005; West et al.,

2007; Yamashita et al., 2005). To obtain experimental sup-

port for this assumption, the positions of 98 randomly taken

genes mapped using SNPs were compared with the posi-

tions of their eQTLs. The SNPs and corresponding eQTLs co-

segregated among the set of 30 DH lines for 93 out of the 98

genes. If the eQTL and SNP genotypes were independent,

the probability of all 30 co-segregating for a given gene

would be 0.530, i.e. �1 · 10)9. Based on this, we estimate

that 95% of the selected eQTLs are cis-eQTLs; the remaining

5% map elsewhere and may be strong trans-eQTLs or

cis-eQTLs associated with paralogues.

Co-appearance of cis-eQTLs when two tissues are compared

Figure 3 shows examples for three cases of co-appearance of

those 2081 eQTLs in the two tissues. In addition, the LOD

scores of all the 2081 eQTLs that were significant in one tis-

sue (P < 0.0004) were plotted for the other tissue (Figure 4).

For the first group of 1083 genes, an eQTL was mapped in the

same position for both embryo and leaf tissues (Figures 3a

and 4a–c). Among these, 551 eQTLs were highly significant

(P < 0.0004) in both tissues (Figure 4a). Another 532 eQTLs

were highly significant (P < 0.0004) in one tissue and sig-

nificant in the second tissue when the threshold was lowered

to P < 0.05 (Figure 4b,c). These 532 eQTLs were not consid-

ered as tissue specific because at least 20% of the eQTLs

mapped in the 30-DH line population with P < 0.05 could be

the true positives (Table 1). So, if the eQTL was mapped in

the same position in both tissues, with a level of significance

in one tissue of P < 0.0004 and in another of P < 0.05, it could

not be reliably classified as tissue-specific.

For the second group of 615 genes (Figure 3b), an eQTL

was mapped in embryos at P £ 0.0004, but it could not be

detected even at P < 0.05 in leaf tissue (Figure 4d). The

absence of the corresponding eQTLs in leaf tissue resulted

from two main reasons: (i) the gene was not detectably

expressed in leaf tissue, making any eQTL detection impos-

sible (236 genes); (ii) the gene was detectably expressed in

leaf tissue, but there was no genetical variation in expres-

sion level; i.e. no detectable eQTL (379 genes). The 379

P-values for the corresponding LODs in leaf tissue were far

from significant, even at P < 0.05: for 80% of them, the

P-values ranged from 0.98 up to 1 (data not shown). For the

third group of 383 genes (Figures 3c and 4e) eQTLs were

1H 2H 3H 4H 5H 6H 7H

1H 2H 3H 4H 5H 6H 7H

1H 2H 3H 4H 5H 6H 7H

1H 2H 3H 4H 5H 6H 7H

1H 2H 3H 4H 5H 6H 7H

1H 2H 3H 4H 5H 6H 7H

52% 30% 18%

1H 2H 3H 4H 5H 6H 7H

1H 2H 3H 4H 5H 6H 7H

1H 2H 3H 4H 5H 6H 7H

1H 2H 3H 4H 5H 6H 7H

1H 2H 3H 4H 5H 6H 7H

1H 2H 3H 4H 5H 6H 7H

Embryo

Leaf

Embryo

Leaf

Embryo

Leaf

(a) (b) (c)

Figure 3. Comparison of the tissue-specific detection of 2081 expression quantitative trait loci (eQTLs) in embryo-derived (embryo) and seedling leaf (leaf) tissues.

Examples: (a) an eQTL mapped in the same position for both embryo and leaf tissues, HVSMEa0001B10r2_x_at; (b) an eQTL mapped in embryo but not in leaf tissue,

baak13l10_s_at; (c) an eQTL mapped in leaf but not in embryo tissue, Contig86_at.

Tissue-dependent gene expression in barley 291

ª 2008 The AuthorsJournal compilation ª 2008 Blackwell Publishing Ltd, The Plant Journal, (2008), 56, 287–296

mapped in leaf tissue but not in embryos, for the same

reasons as above (126 and 257 genes, respectively).

We were able to check the extent to which limited

pleiotropy was being misidentified as a result of genuine

eQTLs failing to reach significance in the small set of 30 DH

lines (false negatives). We took those 383 cases where an

eQTL was clearly identified in leaf tissue (P < 0.0004; false-

positive rate < 5%), but not in embryos (P > 0.05), both

based on 30 DHLs. We then looked for evidence of significant

eQTLs for embryo tissue among these 383 genes based on

an analysis of all 139 DH lines, and found 73 such genes

(19%). This suggests that �81% of the cases of limited

pleiotropy are correctly identified. We do not have data for

the reciprocal set because expression in leaf tissue was not

studied on the 139-DH lines set, but we assume that the

same confidence applies.

In summary, the eQTL analysis in embryos and leaf tissue

yields 1498 and 1134 detected cis-eQTLs, respectively;

combining both tissues gives 2081 cis-eQTLs. Thus, by

adding another tissue for eQTL analysis, we increased the

number of detected cis-eQTLs by 39% compared with those

detected in embryos, and by 84% compared with those

detected in leaf.

Reversed effect of parental alleles in different tissues

The first group (i.e. genes with eQTLs mapping to the same

location in both tissues) was further characterized by iden-

tifying tissue-dependent cis-eQTLs that undergo a reciprocal

change in the parent that contributes the allele with the most

abundant transcript. Thirty-four of the 1083 genes were

found to invert the direction of the eQTLs between tissues

(Table S3). The example of Contig4374_s_at (Figure 2b)

shows that alleles of St maintain a consistent level of

expression in both leaves and embryos, whereas alleles of

Mx increase transcription levels in embryos, but decrease

transcription levels in leaves. The results can be explained by

assuming mutations exist in the putative enhancer sequence

for the gene. The enhancers being targeted for tissue-specific

or temporal regulation may recruit either negative or positive

regulators of gene expression, depending on the develop-

mental stage (Bilic et al., 2006; Lewin, 1997). For this partic-

ular sample, this might be the case for DH lines that inherit

the Mx allele. The mutations occurring in St might disable

the enhancer function, thereby reducing tissue-specific gene

regulation. Of the 34 genes, 19 had alleles generating higher

transcript abundance in Mx embryos and St leaves, whereas

15 had the opposite effect (i.e. higher transcript abundance

in Mx leaves and St embryos).

Gene function prevalence among the genes with

tissue-specific activity of cis-regulators

The gene ontology (GO SLIMS) classification provided by

GENESPRING 7.2 was employed to predict functions for the

cis-regulated genes based on the latest annotation infor-

mation available. We used the annotations for the genes

with detected cis-eQTLs to investigate possible cellular

activity associated with revealed tissue-specific cis-regula-

tors. Focusing on the functional category ‘Biological Pro-

cesses’, 4549 genes can be annotated (20% of all the genes

on the Affymetrix Barley 1 GeneChip). We investigated

whether the tissue-specific cis-regulators represent a ran-

dom sample of the total number of annotated barley genes,

or if there is over-representation of detected tissue-specific

cis-factors from one or more GO classifications related to the

particular biological goals. To make this comparison, we

considered only those functional categories where both 615

embryo-specific and 383 leaf-specific cis-regulators were

represented sufficiently to permit a chi-squared test (i.e. ‡ 5

genes expected per category). The selected functional cate-

gories included genes with unknown biological processes

(GO:0000004), regulation of gene expression, epigenetic

(GO:0040029), electron transport (GO:0006118) and genes

involved in high-level processes such as ‘nucleobase,

nucleoside, nucleotide and nucleic acid metabolism’ and

‘cell communication’.

Figure S1 shows the frequency distribution of the func-

tional categories among (i) all 4549 annotated genes,

(ii) annotated genes with eQTLs observed both in embryo

and leaf tissues, (iii) annotated genes with eQTLs detected in

embryo tissue only and (iv) annotated genes with eQTLs

detected in leaf tissue only. For each of the latter three

groups we compared the distribution of functional catego-

ries against the distribution of those categories in the total

sample of 4549 annotated genes.

P < 0.00001P < 0.0004P < 0.05

P < 0.00001

Lea

f

P < 0.05

P < 0.0004

Embryo

A B C D E

Figure 4. Comparison of significance of the expression quantitative trait loci

(eQTLs) mapped for the same genes in two different tissues.

P-values of 2081 eQTLs that were significant in one tissue (P < 0.0004) are

plotted for the other tissue.

(a) The 551 eQTLs that were highly significant (P < 0.0004) in both tissues.

(b–c) The 532 eQTLs that were highly significant (P < 0.0004) in one tissue and

that were significant in the second tissue when the threshold was lowered to

P < 0.05.

(d) The 615 eQTLs mapped in embryo but not in leaf tissue.

(e) The 383 eQTLs mapped in leaf tissue but not in embryo tissue.

292 Elena Potokina et al.

ª 2008 The AuthorsJournal compilation ª 2008 Blackwell Publishing Ltd, The Plant Journal, (2008), 56, 287–296

The distribution of functional category frequencies

among leaf-specific cis-eQTLs alone significantly differs

from the distribution of functional categories among the

total number of annotated barley genes (P = 0.010), mostly

because of over-representation of genes involved in electron

transport pathways. This might be expected given the

photosynthetic electron transport processes preferentially

activated in leaf tissue. On the other hand, 23% of the leaf-

specific cis-factors related to electron transport showed

homology to the cytochrome P450 gene family. In plants,

P450s are known to play important roles in many processes,

including the production of hormones, pigments, oils and

defensive compounds (Nguyen et al., 2001).

Discussion

In this paper, we have described the genome-wide occur-

rence of limited pleiotropy of cis-regulatory mutations in

barley. The tissues in this analysis represent two successive

ontogenetic stages of the barley plant: embryo-derived

tissues and leaves from seedlings developed from the

embryonic axis. We showed that polymorphism between

St and Mx in cis-regulatory regions may alter gene tran-

scription for only one of the two developmental stages,

supporting reports that mutations in regulatory regions may

sometimes have few or no pleiotropic consequences

(Carroll, 2005; Stern, 2000).

The limited pleiotropy of cis-regulatory mutations was

recently suggested as one of the possible reasons why

selection could generally operate more efficiently and

flexibly on cis-regulatory mutations than on coding muta-

tions (Wray, 2007). In contrast with the extensive pleiotropic

effects that may arise from mutations within protein-coding

regions, mutations in cis-regulatory regions may affect gene

transcription in just one crucial cell type out of several where

it is expressed. This optimizes the use of genetic variation

while avoiding the extremely deleterious effects on fitness

(Carroll, 2005). One of the well-established examples dis-

cussed in terms of the evolutionary significance of limited

pleiotropy (Wray, 2007) is a cis-regulatory SNP in the DARC

locus (Duffy blood group, chemokine receptor). The cis-

regulatory SNP abolishes the DARC transcription specifically

in red blood cells, whereas in several other tissues and cell

types the DARC locus is still expressed normally (Iwamoto

et al., 1996; Peiper et al., 1995). Individuals lacking DARC

expression in erythrocytes show no adverse health conse-

quences, but become completely resistant to infection with

the malarial parasite. Thus, the single cis-regulatory SNP

results in a phenotype expected to provide a substantial

fitness gain (Wray, 2007).

With the currently available methods of eQTL mapping in

a segregating population, limited pleiotropy could be traced

by tissue (developmental stage)-specific detection of cis-

eQTLs. In our study, we only analysed a fraction of all of the

cis-regulatory factors that could possibly be revealed in

barley with the St/Mx cross. This highly selected set of 2081

genes showed the highest LOD scores for eQTLs compared

with the rest of the genes, providing the opportunity to

confidently identify them as cis-regulated loci. For approx-

imately half (1083) of these genes, the cis-regulatory muta-

tions appeared to work in the embryo of germinating grains

as efficiently as in the leaves of seedlings. For the remaining

998 genes, the cis-factor activity was tissue-specific. The

tissue-specific activity of the cis-factors appeared to be

associated with the cellular processes that were preferen-

tially activated in the corresponding tissue. For example,

in leaf tissue a higher proportion of cis-regulated genes

associated with photosynthetic electron transport processes

was detected. In as few as 35% of the 998 genes, cis-eQTL

variation could not be identified in one of the two tissues

because of the complete suppression of gene expression in

that tissue. For the remaining 65%, the genes were detec-

tably expressed in both tissues, but nucleotide polymor-

phism between St and Mx in cis-regulatory regions caused

dramatic regulatory changes (and, consequently, changes in

the appearance of eQTLs) in only one tissue. Therefore, the

data suggest that the limited pleiotropy of cis-regulatory

mutations is widely distributed in barley.

Assuming that limited pleiotropy is a common feature of

cis-regulatory mutations not only in barley, but also in other

species (e.g. man), one could predict that the phenomenon

would be relevant to some age-related disorders and/or

tissue-specific syndromes in humans, with implications for

‘personalized medicine’. Indeed, the complex genetic com-

ponent of many age-related disorders is well reported (Ruse

and Parker, 2001). If the inheritance of a particular parental

allele in a cis-regulatory region causes dramatic alterations

of gene expression, some of the inherited alleles may be

associated with a significant deleterious effect on fitness.

However, transcription of many genes, particularly in higher

eukaryotes, is dependent upon multiple physiological sig-

nals (Ptashne and Gann, 1997). Thus, the deleterious effect

of the inherited parental allele can be temporarily concealed

until the signal is received at a certain developmental stage.

If negative action of the alleles appears later in life, the

deleterious alleles might be kept in a population, as the

effects of natural selection decline with age (Medawar,

1952).

With the restricted examples of two barley genotypes we

investigated how the natural nucleotide polymorphism of

DNA may modify variation of gene transcription efficiency.

The most common level of transcription regulation is

interaction of a gene promoter with RNA polymerase and

other transcription factors. Consequently, nucleotide substi-

tutions in binding sites upstream of the start-point of

transcription, such as promoter, cis-acting motifs (short

sequences recognizable by transcription factors) or enhanc-

ers (DNA sequences that can activate gene transcription

Tissue-dependent gene expression in barley 293

ª 2008 The AuthorsJournal compilation ª 2008 Blackwell Publishing Ltd, The Plant Journal, (2008), 56, 287–296

from remote positions) would change the level of transcript

abundance. As a consequence, eQTL analysis detects

significant linkage between polymorphism at the genetic

locus and variation in its transcript abundance. In that

situation, the nucleotide polymorphism assigned to one

genotype (e.g. Mx) may favour transcription efficiency,

whereas alleles of the other (e.g. St) may not. Remarkably,

this Morex (+)/Steptoe ()) pattern could be tissue-specific in

cases where nucleotide polymorphism occurs in enhancer

sequences, which are targets for tissue-specific or temporal

regulation (Lewin, 1997). It was previously reported (e.g.

Bilic et al., 2006) that enhancers may recruit either negative

or positive regulators of gene expression, depending on the

developmental stage. In our study, such nucleotide poly-

morphism in enhancer sequences between Steptoe and

Morex genotypes can be hypothesized for the 34 genes in

which we detected a reciprocal change in the parent that

contributes the allele with the most abundant transcript in

the two tissues.

In summary, the number of detected cis-eQTLs is always a

function of nucleotide polymorphism content between

parents in the particular cross. For example, the same cis-

eQTL being mapped in the DH population from barley

genotypes in the St/Mx cross may not be detectable in

mapping populations of other barley genotypes (e.g. Barke/

Mx cross), simply because there is no polymorphism

between Barke and Mx for the particular regions affecting

the transcript abundance of that gene. Certainly, it would not

mean that the gene is not regulated ‘in cis’, because the

promoter and cis-motifs have key impacts on the transcrip-

tion of any gene. In addition, our results showed that

because of limited pleiotropy of cis-regulating mutations,

the number of cis-eQTLs discovered by the genetical

genomics approach is strongly affected by the experimental

situation (e.g. particular tissue, fixed developmental stage).

In the present study, the addition to the eQTL mapping

experiments of a second tissue increased the number of

detected cis-eQTLs by 39% (embryo) and 84% (leaf). Thus,

instead of the question ‘how many genes are regulated in

cis?’ we should ask more accurately ‘how many cis-regula-

tory mutations can be detected with the particular cross for a

given tissue?’.

Experimental procedures

Plant material

We used mRNA from the embryo-derived tissue of germinatinggrains for expression profiling of 30 recombinant lines of a St · MxDH population (Kleinhofs et al., 1993). The same set of DH lines wasinvestigated previously for the purpose of single feature polymor-phisms (SFP) detection (Luo et al., 2007).

Embryo-derived tissues [coleoptile (shoot sheath), plumule(foliage leaves), shoot apical meristem, scutellum, radical (embry-onic root), calyptra (root cap), coleorhiza (root sheath) (see also

http://www.seedbiology.de)] from three grains were dissected as asingle tissue piece and were flash frozen in liquid nitrogen.Germination and tissue collection were repeated for all lines withcomplete randomization of the Petri plates on each of threeoccasions. For each line, tissues from all three occasions werebulked before RNA isolation.

To obtain seedling leaf tissue, 10 sterilized seeds per line weresown in each of three replicate 13-cm2 pots. One pot of everymember of the ‘trial set’ was randomized in each of three random-ized blocks, and each block was placed in a separate Snijdersgrowth cabinet with a 16-h light (400 lE m)1 sec)1)/8-h dark, 17�C/12�C, cycle. After 12 days, leaves of seven or eight seedlings fromeach pot were collected, bulked and flash frozen in liquid nitrogen;tissues from all three replicate pots of each line were bulked for RNAisolation.

The RNA isolated from these bulks was used to hybridize to themicroarray. A single hybridization from each of 30 DH lines wasperformed, but three biological replicate hybridizations were usedfor the parental genotypes Mx and St. RNA was isolated, processedand hybridized to the Barley 1 GeneChip (Affymetrix product#900515 GeneChip� Barley Genome Array; complete descriptionand references can be found at http://www.affymetrix.com/prod-ucts/arrays/specific/barley.affx) using previously described Trizolprocedures (Caldo et al., 2004). The labelling, hybridization andGeneChip data acquisition were conducted at the GeneChip facilityat Iowa State University (http://www.biotech.iastate.edu/facilities/genechip/Genechip.htm ).

Microarray data handling

To estimate the overall tissue effect on the expression of the 22 840genes present on the Affymetrix Barley 1 GeneChip, 72 probe result(CEL) files combining 36 files (30 DH lines plus three replications oftwo parents) for the two tissues under analysis were normalized toeach other using the Robust Multi-assay Average (RMA) normali-zation routine from the Bioconductor packages (Irizarry et al., 2003).A one-way ANOVA was used to compare the expression level of eachof the 22 840 genes on the chip across 36 genotypes and two tissuesusing PERL script developed in-house. An estimation of FDR wasachieved according to the method of Benjamini and Hochberg(1995), following the approach suggested by Benjamini et al. (2001).

In order to compare eQTLs detected with the 30-lines set withthose discovered with all 139 lines, we further followed theprocedure of data handling described previously (Potokina et al.,2007). CEL files were directly loaded into GENESPRING 7.2 and weresubmitted to the RMA file pre-processor. This converts the probe-level expression data into gene-level expression data, which arenormalized to a certain extent. As an additional normalization step,the procedure ‘Per Gene: Normalize to specific samples’ wasapplied, where each gene signal was divided by the correspondingmean of three replications of Mx. The normalized data for bothparents and each of the 30 DH lines were exported for eQTLmapping. To obtain MAS 5.0 presence calls, the ‘mas5calls’ methodfrom the BIOCONDUCTOR package was used.

Data access

All the detailed data and protocols from these experiments havebeen deposited in BarleyBase/PLEXdb (http://barleybase.org; http://plexdb.org/), an MIAME-compliant expression database for plantGeneChips (Shen et al., 2005). Data files have also been depositedin ArrayExpress (http://www.ebi.ac.uk/arrayexpress) as accessionnumbers E-TABM-111 (leaf) and E-TABM-112 (embryo).

294 Elena Potokina et al.

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eQTL mapping

A recently developed transcript derived marker (TDM) map used foreQTL analysis of the St/Mx population of 139 DH lines, and congruentwith the SNP map for the St/Mx cross (Rostoks et al., 2006), was takenas a standard to maintain the marker order. The TDMs included SFPs,as described, and were defined by Borevitz et al. (2003). To developthe genetic map for the 30 DH lines, we used the same markers as forthe map based on 139 lines, but the reduced population size (n = 30)led to a smaller number of recombination bins (209 instead of 512).Thus, all of the markers linked to eQTLs on the 30-line map could bechecked for significant linkage to eQTL on the 139-line map.

The CIM analysis was implemented using WINDOWS QTLCARTOGRAPHER 2.5 (http://statgen.ncsu.edu/qtlcart/WQTLCart.htm)with a 2-cM walk speed and a type-I error rate of 5%. Intervals offive background markers with a window width of 10 cM wereanalysed to control the QTL background effects. To establish athreshold for declaring statistically significant eQTLs, we used theGPT approach (West et al., 2007). A representative null distributionbased on 1 000 000 maximum likelihood ratio test (LRT) statistics(1000 permutations · 1000 randomly selected expression traits) wasemployed for all transcripts detectable for embryo-derived and leaftissues. The GPT was calculated as the 95% upper bound of therepresentative null distribution, giving 14.168. A LOD score for each2-cM interval was compared with the representative null distribu-tion, and was assigned to the corresponding P value (Churchill andDoerge, 1994).

Acknowledgements

This research was supported by a research grant from the UK Bio-technology and Biological Sciences Research Council (BBSRC), andby the Scottish Executive Environment and Rural Affairs Depart-ment (SEERAD) of the United Kingdom.

Supporting Information

Additional Supporting Information may be found in the onlineversion of this article:Figure S1. Significance of cis expression quantitative trait loci(cis-eQTLs) when two tissues are compared.Figure S2. Gene function frequencies in groups of genes withtissue-specific activity of cis-regulators.Table S1. Overall tissue effect on the transcript abundance level of22 840 genes on the Affymetrix Barley 1 GeneChip.Table S2. Co-appearance of 2081 cis expression quantitative traitloci (cis-eQTLs) when two tissues are compared.Table S3. The 34 cis expression quantitative trait loci (cis-eQTLs)that undergo a reciprocal change in the parent that contributes theallele with more abundant transcript.Please note: Wiley-Blackwell are not responsible for the content orfunctionality of any supporting materials supplied by the authors.Any queries (other than missing material) should be directed to thecorresponding author for the article.

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