Development of novel EST-derived resistancegene markers in hop (Humulus lupulus L.)

Aljaz Majer • Branka Javornik •

Andreja Cerenak • Jernej Jakse

Received: 15 March 2013 / Accepted: 23 July 2013 / Published online: 9 August 2013

� Springer Science+Business Media Dordrecht 2013

Abstract Although sources of resistance to major

pathogens exist in cultivated hop germplasm, little

effort has been invested to date in developing resis-

tance-linked markers. The aim of this study was to

design and evaluate resistance gene analogs (RGAs)

potentially useful for marker-assisted selection

towards novel resistant hop cultivars. A set of 34

putative hop RGAs was retrieved by screening pub-

licly available hop expressed sequence tags (ESTs) for

conserved sequence motifs of common resistance

protein domains. Seventeen of these were identified as

putative RGAs by BLAST analyses. Exon/intron

boundary prediction enabled re-sequencing of 24

EST-RGAs, allowing the acquisition of approximately

5 kbp of novel intronic sequence and 8 kbp of

re-sequenced exons. Fifteen EST-RGAs exhibited

polymorphisms and were added to a framework

linkage map of hop. In addition to providing EST-

derived markers potentially useful for resistant hop

cultivar development, this study provides valuable

insights into the utility of targeting hop introns for

marker development.

Keywords Humulus lupulus � Resistance gene

analogs � EST � SNP � Exon/intron boundary

prediction

Introduction

Hop (Humulus lupulus L.) is a perennial crop plant

grown in temperate regions worldwide (Neve 1991).

Resins contained in its female inflorescences are the

source of flavour and stability in beer (Goese et al.

1999), and also contain pharmacologically active

substances (Milligan et al. 2002). In 2010, approxi-

mately 50,000 hectares were planted with hops

worldwide, yielding roughly 100,000 metric tonnes

of hop cones (IHGC 2011). Several fungal diseases

result in considerable yield losses, most notably

downy mildew (Pseudoperonospora humuli Miy.

and Takah), powdery mildew (Podosphaera macular-

is Braun), and hop wilt (Verticillium albo-atrum

Reinke and Berthold) (Mahaffee et al. 2009). The

latter fungal disease is notorious, since it cannot be

controlled by phytopharmaceutical measures, making

resistant cultivar breeding the only feasible control

strategy (Darby 2001). Fortunately, for all three

diseases sources of resistant germplasm are available

for breeding programmes (Neve 1991).

Electronic supplementary material The online version ofthis article (doi:10.1007/s11032-013-9934-9) contains supple-mentary material, which is available to authorized users.

A. Majer � B. Javornik � J. Jakse (&)

Agronomy Department, Biotechnical Faculty, University

of Ljubljana, Ljubljana, Slovenia

e-mail: jernej.jakse@bf.uni-lj.si

A. Cerenak

Slovenian Institute for Hop Research and Brewing,

Zalec, Slovenia

123

Mol Breeding (2014) 33:61–74

DOI 10.1007/s11032-013-9934-9

Breeding hop cultivars towards improved resis-

tance is slow and laborious. One beneficial strategy is

the use of marker-assisted selection (MAS), which

requires the availability of a large number of genetic

markers or markers linked directly to the desired trait

(Collard and MacKill 2008). A sizeable number of

markers of anonymous origin in the genome have

already been published for hop, including amplified

fragment length polymorphisms (AFLPs) (Hartl and

Seefelder 1998, Jakse et al. 2001), random amplified

polymorphic DNAs (RAPDs) (e.g., Sustar-Vozlic and

Javornik 1999, Patzak 2001), simple sequence repeats

(SSRs) (e.g., Stajner et al. 2008), and Diversity Arrays

Technologies (DArTs) (Howard et al. 2011). Among

markers derived from the transcribed portions of the

hop genome, a limited number of genes are derived

from sequence tagged site (STS) markers (Patzak et al.

2007), and a sizeable set of expressed sequence tag

(EST)-derived SSR markers (Jakse et al. 2011) are

available. To date, the available markers have been

successfully used to map economically important

yield parameters (Cerenak et al. 2006, 2009; Henning

et al. 2011) and, more recently, in determining the

quantitative trait loci (QTL) involved in hop wilt

resistance (Jakse et al. 2013). Despite the availability

of a considerable number of markers, MAS in hop has

to date only been implemented to the extent of

determining the sex of hop plants (Polley et al. 1997,

Jakse et al. 2008).

Mapping populations segregating for resistance to

major hop diseases are available (Kozjak et al. 2009;

Henning et al. 2011), and efforts towards determining

the segregation patterns of the diseases are underway.

A suitable approach complementary to map saturation

and aimed at positional cloning of QTL is the

candidate gene approach targeting genes involved in

plant resistance, termed resistance gene analogs

(RGAs). The plant resistance response to attacking

pathogens is commonly mediated by plant resistance

(R) genes, the majority of which code for the

nucleotide-binding site–leucine-rich repeat (NBS-

LRR) group of proteins (Leister et al. 1996; Eitas

and Dangl 2010). Most NBS-LRR proteins contain

either a TIR (Toll/interleukin-1 receptor-like domain)

or CC (coiled coil) domain at their N-terminus, which

acts as a signal transduction domain. A common

subtype of TIR-NBS-LRR proteins contains a WRKY

domain at the C terminus (McHale et al. 2006). Two

additional classes of R genes are receptor-like proteins

(RLPs) and receptor-like protein kinases (RLPKs),

which consist only of an extracellular LRR domain

and, in the case of RLPKs, a cytoplasmic kinase

domain (Takken et al. 2006).

In sequenced plant genomes, a total of up to several

hundred NBS-LRR genes are distributed mainly as

gene clusters (Meyers et al. 2003; Zhou et al. 2004;

Kohler et al. 2008). In plants whose genome sequence

is not available, a common approach to RGA identi-

fication is PCR with degenerate primers targeting

conserved structural regions, commonly termed NBS

profiling (Leister et al. 1996). This approach has been

used for a large number of plant species, including

hop, for which it yielded only a limited number of

distinct RGA sequences (Kozjak et al. 2009). Since

RGAs have been shown to be tightly linked to

resistance QTL, and are therefore reliable for use in

MAS (Valkonen et al. 2008), developing additional

RGA markers is of considerable interest. Additional

RGA sequences can be obtained by mining the

available EST databases using bioinformatic algo-

rithms in conjunction with known R gene sequences,

or by R-gene-specific sequence motif searches (Dil-

birligi and Gill 2003). Sets of such markers, termed

EST-RGAs, have to date been successfully developed

for sugarcane (Rossi et al. 2003) and wheat (Shang

et al. 2010).

Since hop EST resources are limited to roughly

10,000 available sequences (Nagel et al. 2008; Wang

et al. 2008), maximizing the rate of polymorphism

detection is vital. This can be achieved by determining

the exon/intron boundaries (E/I) prior to designing

PCR primers (Wei et al. 2005), which in effect

prevents PCR failure due to the primers annealing at

the junctions. Additionally, the polymorphism rate is

increased by specifically targeting the exonic

sequences which flank introns, as these areas accu-

mulate considerably more polymorphic events than

exons (Li et al. 2012).

The prediction of E/I has to date been used in the

development of EST-RGA markers in maize and

wheat. More than 900 EST-RGAs were mined using

annotation keyword searches from wheat EST

resources. Intron prediction based on alignment with

the rice genomic sequence enabled the development of

135 putative intron length polymorphism (ILP) mark-

ers for wheat (Shang et al. 2010). In maize, 632 RGAs

containing introns were identified out of a total of 861

RGAs mined by using BLAST with a set of known

62 Mol Breeding (2014) 33:61–74

123

plant R genes, with the aim of developing ILPs using

maize genomic resources (Liu et al. 2012). In silico

determination of putative intron sites in transcribed

sequences is therefore common in primer design for

various EST sets, and markers implementing this

strategy have already been published for Rhododen-

dron (Wei et al. 2005), tomato (Wang et al. 2010), and

rubber tree (Li et al. 2012). EST-PCR primer design

omitting the E/I prediction step may result in a

significantly lower amplification success and ensuing

polymorphism rate (Wei et al. 2005).

The aim of this study was to detect additional

putative hop RGAs by mining hop ESTs with con-

served sequence signatures of typical R gene domains.

Additionally, through careful alignment of the identi-

fied RGA-like transcribed sequences with putative

orthologous genes, E/I were predicted and a consider-

able number of introns subsequently sequenced,

allowing insights into hop gene structure. Relevant

candidate hop R genes were discovered among the

mined EST sequences. Finally, novel polymorphic hop

EST-derived markers were successfully developed,

and their suitability was demonstrated through map-

ping onto a framework genetic map.

Materials and methods

Sample preparation

An F1 pseudo-testcross family between cv. Wye

Target and the male breeding line BL2/1 totalling 144

offspring was used to test the segregation of all of the

markers developed. Wye Target is resistant to both

powdery mildew and Verticillium wilt, and both

resistances have been previously shown to segregate

in its progeny (Darby 2001). DNA was isolated from

young leaf tissue using a common CTAB procedure

(Kump and Javornik 1996). DNA concentration was

determined fluorimetrically (DynaQuant 200, GE

Healthcare) and working dilutions of 4 ng/ll were

prepared.

Identification of R-gene-related ESTs and E/I

prediction

Transcript assemblies of hop EST sequences were

obtained from the Plant Genome Database (Plant-

GDB), release 168 (Duvick et al. 2008), available at

http://www.plantgdb.org/. Current hop EST resources

are the result of multiple hop transcriptome projects,

yielding nearly 25,000 single pass sequences resulting

in 9,789 PlantGDB assemblies (Nagel et al. 2008;

Wang et al. 2008).

Retrieved sequences were translated into all six

possible reading frames using the translate program,

which is part of the EMBOSS package. Further

analyses were performed using HMMER executables

(Finn et al. 2011). Pfam motif alignments, obtained

from the PFAM database (Finn et al. 2010), were used

to build a local database using hmmbuild and hmmc-

alibrate and included PF00560.25 (LRR1), PF07725.4

(LRR_3), PF00931.14 (NBS), PF01582.12 (TIR), and

PF03106.7 (WRKY). No searches were made for the

coiled coil (CC) domain, since no reliable conserved

motifs are available. To identify conserved motifs of R

genes, translated ESTs were screened using the motif

database with hmmpfam at a cut-off E value of 0.001

(Table 1). Original EST names from the PlantGDB

were retained as the names of PCR amplicons and,

subsequently, as EST-RGA marker names.

BLASTx comparison between hop EST-RGA

sequences against a non-redundant protein database

(NCBI blast) was employed to find the most similar

annotated plant protein. This protein was used as a

reference sequence for BLASTp searches, from which

its putative functions were determined and assigned to

corresponding EST-RGAs. Regardless of the putative

gene function, all EST-RGAs were retained in further

analyses.

The complete corresponding DNA sequence was

retrieved for each of the reference proteins. For intron

predictions, the alignment between the putative hop

EST-RGA translated amino acid sequence and the

reference gene sequence was performed using the

Wise2 web programme (EBI Tools), which is an

algorithm optimized for comparing a protein sequence

to a DNA sequence, with an affinity to highlight

possible intronic sequences and frameshift errors in

the aligned DNA sequence (Birney and Durbin 1997).

From the alignment, the exact length of the introns

predicted from the corresponding reference gene

possibly present in the putative EST-RGAs were

calculated.

Primer pairs were designed with the Primer3 web

programme (Rozen and Skaletsky, 2000) using default

values. Special care was taken to design exon-

targeting primers that included the maximum amount

Mol Breeding (2014) 33:61–74 63

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Mol Breeding (2014) 33:61–74 65

123

of sequence and as many introns as possible in the

amplified product. The primer pairs developed are

listed in Supplementary Table 1.

PCR amplification and sequencing

PCR was run on a Biometra TGradient Thermocycler

in 20 ll reaction volumes containing 19 Taq buffer

(109 stock; Fermentas), 1.5 mM MgCl2, 200 lM of

each dNTP, 500 nM of each primer, and 0.5 U Taq

DNA polymerase (Fermentas).

PCR conditions were as follows: an initial 5 min

denaturation step at 94 �C, five cycles at 94 �C for

30 s, touchdown annealing starting at 62 �C and

diminishing by 1 �C per cycle, and extension at

72 �C for 2 min, followed by 30 cycles of 94 �C for

30 s, 57 �C for 45 s, and 72 �C for 2 min, and a final

extension step of 8 min at 72 �C.

Amplification was initially tested on parents and six

progeny from the mapping family. PCR products were

visualized on 1.2 % agarose gels stained with ethi-

dium bromide. PCR products exhibiting successful

amplification were cleaned with ExoSAP following

the manufacturer’s instructions (USB Biochemicals)

and subjected to direct sequencing from both ends

using Big Dye 3.1 chemistry (Applied Biosystems).

Sequencing was performed on an ABI 3130XL

(Applied Biosystems).

E/I determination and polymorphism detection

Amplified EST-RGA sequence traces were edited and

assembled using CodonCode Aligner 3.7.1 (Codon-

Code Corporation). The identity of the retrieved

sequences was confirmed by alignment with the

original ESTs using the BLASTn algorithm, which

also allowed initial visualization of any introns in the

sequences. The precise locations of E/I within the hop

EST-RGA sequences were manually determined in the

CodonCode Aligner by referring to the BLASTn

alignment to pinpoint the base positions of starts (GT)

and ends (AG) of introns.

By manually scanning sets of parental and progeny

sequence traces with the CodonCode Aligner, any

evident sequence polymorphisms were determined. A

polymorphism status was assigned to base locations at

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66 Mol Breeding (2014) 33:61–74

123

indel (evident sequence trace deterioration after a base

location in any of the parents, or a missing base in a

single parent), and sequence traces of the six progeny

confirmed possible segregation of the polymorphism

at that base location.

For EST-RGAs exhibiting polymorphisms, the

polymorphism status of the entire mapping family

(144 plants) was determined after direct sequencing of

the EST-RGA PCR product, using the primer that

allowed the best scoring of the polymorphism in the

sequence trace (Supplementary Table 1).

Intron and polymorphism locations were visualized

using the FancyGene v1.4 web programme (Rambaldi

and Ciccarelli 2009) (Fig. 1).

Marker segregation analysis and mapping

Chi squared (v2) values were calculated (p \ 0.05) to

detect deviations from the expected Mendelian ratios.

All markers, regardless of v2 distortion, were included

in the mapping. A previously constructed microsatel-

lite-based linkage map (Jakse et al. 2011) was extended

with the new EST-RGA markers using JoinMap 3.0

(Van Ooijen and Voorrips 2001), employing a strategy

for pseudo-testcross linkage analysis as described by

Grattapaglia and Sederoff (1994). Linkage groups were

visualized using MapChart 2.2 (Voorrips 2002).

Intron location and length analysis

The total intron number in each EST-RGA sequence

was determined by visualizing sequences in the

CodonCode Aligner. The lengths of any complete

introns (sequenced from the starting GT to the ending

AG) were determined for each EST-RGA sequence.

The intron length ratios between the actual introns

(from the EST-RGA sequence) and the predicted

introns (from the same intron location in the reference

gene) were calculated and a quartile analysis of ratio

values was run in R (R Development Core Team 2008)

to determine the median value and possible outliers.

Results

Identification of EST-RGAs and E/I determination

HMMER searching revealed a total of 35 putative

EST-RGAs, representing 0.4 % of all ESTs in the hop

database. Of these, 24 sequences scored positive for

LRR domain motifs, eight for WRKY domains, two

for TIR domains, and one for the NBS domain. No

single EST sequence contained two different domains

(Table 1).

BLASTp searches of the non-redundant protein

database allowed determination of the predicted

protein function of all but one (HL6022) of the

putative hop EST-RGAs (Table 1). Of the 34 remain-

ing EST-RGAs, 17 (50 %) were found to be putative

genes involved in resistance, either as recognition

molecules or signalling proteins, and the remainder

were found to be proteins with functions outside of

resistance. Both sequences containing TIR domains

were identified as parts of TIR-NBS-LRR genes. Of

the 23 LRR containing EST-RGAs, only 12 were

found to be potentially involved in resistance. The

single NB-ARC and all eight WRKY domain-con-

taining EST-RGAs were found to be part of a vesicle

forming ATPase- and WRKY-containing transcrip-

tion factors, respectively (i.e., proteins not involved in

plant resistance responses) (Table 1).

Reference sequences with a known NCBI gene

model sharing the highest BLAST identity with hop

ESTs were used for constructing alignments for E/I

and intron length predictions using the Wise2 tool.

Reference genes were mainly derived from plants with

well developed and available genomic resources:

Populus trichocarpa (23 cases), Vitis vinifera (nine

cases), Arabidopsis thaliana (one case), and Oryza

sativa (one case) (Table 1).

Reference genes contained up to 21 introns

(Table 1). No introns were evident in eight cases.

Based on intron locations retrieved with Wise2, EST-

RGA amplicons were designed that contained up to six

introns. We were unable to include any predicted

intron locations in 12 of the EST-RGA amplicons

which were designed, since the reference genes did not

contain any in the region in which the EST was aligned

(Table 1).

Fig. 1 Twenty-four sequenced EST-RGA amplicons annotated

with intron positions (horizontal connecting line), exon

positions (box) and sequence polymorphism location (vertical

dash). Total sequence lengths are given in parentheses. Below

the lines denoting introns are given the intron position number

by consecutive order in the reference gene used in intron

prediction and the exact intron location in EST-RGA sequence

(in parentheses). Polymorphism names below vertical dashes

denote polymorphism type (S SNP, I indel) and location in

sequence (bp position from start of sequence)

c

Mol Breeding (2014) 33:61–74 67

123

68 Mol Breeding (2014) 33:61–74

123

PCR amplification and sequencing

Of the 34 putative EST-RGA primer pairs used, 30

(88 %) allowed successful PCR amplification. Direct

sequencing of these amplified PCR products yielded

intelligible sequences in 24 cases (80 % of successful

PCR products, 69 % primer efficiency overall). When

PCR products were visualized on agarose gels, only

single bands were observed.

The length of the retrieved sequences was from 162

to 799 bp, with an average of 579 bp. Sequences were

retrieved from both ends for 13 of the EST-RGA

amplicons. In the remaining 11 cases, sequencing with

one of the primers consistently failed, possibly due to

the presence of primer dimers in the PCR products.

Intron location and length analysis

All introns obtained after cross species prediction with

Wise2 were confirmed to be present in hop amplicons

by sequencing. The predicted locations of the introns

were consistent with the actual sequencing data for all

of the EST-RGAs. In 15 cases, one or more introns

were evident in the sequence. Of the 30 introns

observed in all of the sequenced PCR products, 16

were recovered in their whole length from 13 EST-

RGA sequences. The intron lengths ranged from 84 to

518 bp. The exact intron locations in the EST-RGA

sequences are shown in Fig. 1.

The ratios of hop intron length versus reference

gene intron lengths were calculated using quartile

analysis. Median (1.24) and quartile range (1.04–1.61)

were determined and four ratios were found to be

outliers (Supplementary Table 2).

Sequence polymorphism analysis

All 24 sequenced EST-RGA sequences were screened

for polymorphisms. Overall, 33 polymorphisms were

detected in exons and 23 polymorphisms in introns. A

total of five indels occurred in all of the sequenced

EST-RGAs, of which four were present in introns;

only HL1641 (presumably a WRKY-type transcrip-

tion factor) harboured an indel in the coding region. In

addition, 51 SNPs were evident, of which 14 were

transitions (nine in exons and five in introns) and 37

were transversions (23 in exons and 14 in introns). The

transition to transversion ratio was 0.38 (0.39 in exons

and 0.36 in introns), suggesting a strong bias towards

transversions. If introns were present in the sequence,

then the SNPs or indels were invariably present in

intronic regions. For seven cases (HL1641, HL5290,

HL5623, HL5980, HL6293, HL7319, HL9399), no

introns were observed in sequences, but polymor-

phisms were detected in their exons (Fig. 1).

The cumulative sequenced exon length for all of the

EST-RGA sequences was 8,554 bp, and the cumula-

tive intron length was 5,338 bp. The polymorphism

frequency in sequenced exonic regions was 0.386 %

(one SNP in 259 bp) for exons and 0.431 % (one SNP

in 232 bp) for introns.

Marker segregation and genetic linkage analysis

Sixteen EST-RGAs exhibited SNPs or indels, the

presence of which allowed progeny genotyping suitable

for mapping (Fig. 1). Of these, HL6293 exhibited

sequence polymorphisms only between both parental

sequences (aa 9 bb type) and was therefore unsuitable

for the pseudo-testcross mapping strategy. Segregation of

the remaining 15 EST-RGA markers was determined on

all progeny of the Wye Target 9 BL2/1 mapping family.

Two markers segregated in both parents, seven only in

the maternal parent and six only in the paternal parent.

Chi squared (v2) ratios were calculated to determine

significant deviations from the expected Mendelian

ratios. Eight EST-RGA markers exhibited a signifi-

cantly distorted v2 ratio in the mapping family

(p \ 0.05; Supplementary Table 3).

All 15 segregating EST-RGA markers were included

in the ensuing mapping project. We were able to add 14

markers onto seven out of nine genetic linkage groups

(LGs) of the framework map for the cross Wye

Target 9 BL2/1, previously constructed using SSR

markers (Jakse et al. 2011). Marker HL7050 was

grouped with LG6, but did not exhibit enough linkage

to be successfully mapped. Four markers were added

onto LG1, three onto LG6, two onto LG2 and LG4, and

one onto LG3, LG8 and LG9 (Fig. 2). This addition

resulted in a total map length increase of 14.0 cM (6 %;

from 224.7 to 238.7) and a marker density increase of

0.12 markers/cM (from 1.94 to 1.82).

Discussion

Plant EST databases are an invaluable resource for

orphan crop plants, allowing the development of high-

Mol Breeding (2014) 33:61–74 69

123

CO653957-TCCCA40,0

GT4-K15-15-23,3

HlAGA87,1HlAGA67,6HL12738,6Ho00849,5

EMHL05212,6GA1-N1-3-214,1GA4-013-9 GA4-C9-814,4GA3-G1-614,5GA7-L7-1614,7HL598015,0GT4-F9-1415,3HL5416,3GA5-cDNA-L5-118,211a5918,3GA5-F4-1018,9GA5-cDNA-L5-219,3HlGT1619,7AGA4-H24-13-1 CO653923-ATA420,3

HL19122,4

GA5-K6-11-CONT-230,0

C0653713-ATC535,2

LG1

ACC2-D3-30,0

Ho002210,9

HL939925,3

GA4-G15-829,2GT1-A5-129,4AGA4-D16-12 AGA2-H15-629,7Ho016329,8GA6-N21-14 GT1-A20-129,9CO653941-GA730,1HlGA57 HlGT1430,2ACA1-L4-330,5GT4-K18-1531,0HL871031,4HlGT431,9EMHL01932,5HLGT19-235,2WT3B1236,8

LG2

CO653885-TA60,0GT2-G10-61,3HlGA412,8HlGA53 GA6-N13-14GA6-J18-13 GA7-O7-163,2

HlACA8 5-23,3GA7-E11-153,4X13-II-1-13,6HlGA423,8GA8-H7-174,1HlAGA34,5Ho01345,9

GA5-K6-11-CONT-19,0

HL741816,7

LG3

HlGT19-10,0

AGA4-H24-13-216,0HL955017,0HlGA4417,1HL731917,2GT4-I11-1417,6EMHL02217,8HlGT2718,3GT2-L13-718,5GT1-K1-4 ACA1-K9-319,2HlAGA8-119,4GA2-O17-619,5HlGA2919,6HlACA319,9HlGA3120,67a8223,5

LG4

HL52900,0

HlGT21,9GA6-P20-142,1

HL56233,5

HlGT2414,7

GA4-P11-918,9GA4-K16-820,5GA4-H15-820,8EMHL01521,6GT2-C21-521,7GT1-B13-121,9GA2-L21-522,1GA1-N1-3-123,1HL857023,2GT1-D10-224,6

LG6

HL9310,0

GT4-K15-15-115,3

GT1-N10-417,6GA6-A22-1118,4

HlAGA719,7GT5-B19-1620,5

Ho003821,7

HlGA5823,3RAPD-Y-HOP23,8

LG8

HL16410,0

HlGA239,4Ho01749,8Ho005810,3GA4-F6-8-210,8

EMHL06213,7

LG9

Fig. 2 Addition of 14 hop

EST-RGA markers (in bold

and underlined) onto a SSR-

derived integral linkage map

of Wye Target 9 BL2/1

pseudotestcross. On the left

side of the maps are genetic

distances in cM, with

corresponding marker

names on the right. Linkage

groups LG5 and LG7

remained unchanged (Jakse

et al. 2011) and are not

shown

70 Mol Breeding (2014) 33:61–74

123

quality gene-derived markers employing various

approaches for their utilization, e.g., SSR, SNP, and

length polymorphism mining (Jakse et al. 2011, Wei

et al. 2005, Shang et al. 2010). Using fast alignment

algorithms, ESTs can be enriched into a subset of

candidate genes that are subsequently mapped onto a

framework map. In this study, polymorphism-based

markers from a subset of the R gene motif containing

ESTs were developed and their suitability for mapping

purposes was assessed.

To date, 17 distinct RGA sequences obtained by

NBS profiling are available for hop (Kozjak et al.

2009). The primary goal of this study was to extend

this list of sequences by scanning available sequence

resources for conserved pfam motifs. A relatively

small number of putative EST-RGAs (35 sequences of

9,789, or 0.4 %) were obtained. The annotation of the

retrieved sequences revealed that only 17 of these are

true RGA sequences (0.2 % of ESTs). This is consis-

tent with the findings of Rossi et al. (2003), who

reported a 0.1 % RGA representation in scanned EST

databases. Whole genome sequencing has revealed

that hundreds of RGAs are present in a typical plant

species: for example 149 in thale cress (Meyers et al.

2003), 535 in rice (Zhou et al. 2004), and roughly 400

in white poplar (Kohler et al. 2008), accounting for a

few percent of the total genes in the genome. This

apparent under-representation of NBS-LRR

sequences in the EST databases may be due to the

relatively low expression of these sequences overall,

and possibly lower expression in the tissues from

which ESTs are derived.

Of the 34 hop ESTs used in marker development,

30 (88 %) allowed successful PCR amplification,

which is somewhat higher than that achieved by Wang

et al. (2010), who reported a 65 % amplification

success rate for intron flanking primers in tomato.

Twenty-four of our sequences (69 %) yielded useful

sequence information, and 15 of these (63 %)

contained segregating SNPs or indels and were

subsequently mapped. Li et al. (2012) reported a

higher amplification rate (98 %) and similar (62 %)

polymorphism-generating efficiency of intron flank-

ing markers from a rubber tree EST subset. Other

studies applying intron site prediction and their

inclusion in PCR amplicons consistently report a high

polymorphism rate. Wei et al. (2005) compared the

two approaches and reported a marked increase in the

incidence of intron length polymorphism detection

among several Rhododendron species for amplicons

containing introns (63 %), as opposed to those

designed without an intron site prediction step (20 %).

Typically, in species lacking genomic sequence

resources, E/I are predicted using genomic data from

other species (Wei et al. 2005; Liu et al. 2012; Wang

et al. 2010). In this study the whole non-redundant

protein database at NCBI was screened and the

corresponding genomic sequences of well annotated

genes were subsequently obtained, regardless of

species of origin. The BLASTx analysis of hop EST

sequences revealed that the majority of the most

significant hits belonged to the poplar (68 %) and only

one to the model plant Arabidopsis and rice. The close

phylogenetic relationship between poplar and hops is

well supported, since they both belong to the fabids

clade (being members of orders Malpighiales and

Rosales), while Arabidopsis is in the malvids clade of

the core eudicots (Judd and Olmstead 2004). Hop

intron lengths were found to be 24 % longer than in the

compared sequences, as estimated by the median. Wei

et al. (2005) report consistent underestimation of

intron lengths in Rhododendron ESTs following E/I

prediction with the Arabidopsis genomic sequence.

Similarly, Wang et al. (2010) found consistency in E/I

prediction, but not in intron lengths of tomato

sequences. This finding could be due to a portion of

the markers being lost due to intron length underes-

timation, resulting in amplicon lengths outside of the

Taq DNA polymerase processivity margins (Wang

et al. 2010).

For 16 of the 24 sequenced hop EST-RGAs (67 %;

Table 3), introns were both predicted and confirmed

by sequencing. For tomato ESTs (Wang et al. 2010),

E/I prediction based on Arabidopsis genome data also

resulted in 100 % predicted intron detection. Nine

intron-containing hop sequences exhibited polymor-

phisms within introns, but not in exons. The remaining

seven polymorphic sequences exhibited polymor-

phisms in coding regions and lacked introns within

amplicon boundaries. Of the 33 exonic polymor-

phisms, only one was a 1-bp indel, causing a tentative

frameshift mutation. On the other hand, a total of four

indels occurred in introns. The overall polymorphism

densities for introns and exons were 0.431 and

0.386 %, respectively. This amounts to only a 1.1-fold

higher occurrence of polymorphisms in introns, which

is considerably lower than the common observation of

elevated SNP or indel occurrence in intronic as

Mol Breeding (2014) 33:61–74 71

123

opposed to exonic regions, including the 3.7-fold

occurrence observed in cotton (Chee et al. 2004), 3.4-

fold in rubber tree (Li et al. 2012), and 2.4-fold in

tomato (Wang et al. 2010).

In this study, 15 polymorphic markers were devel-

oped, of which four were derived from sequences

linked to disease resistance. In addition, one WRKY

transcription factor and ten LRR genes not associated

with plant disease resistance were mapped. Eight of 15

markers (53 %) exhibited significantly distorted v2

ratios. Segregation distortion is common in mapping

studies of hop (Seefelder et al. 2000; Cerenak et al.

2006, Jakse et al. 2011). Seefelder et al. (2000)

reported that 54 out of 224 mapped markers exhibited

distortion from Mendelian ratios, and tended to cluster

upon mapping. Segregation distortion is also com-

monly observed in other plant species and distorted

markers are commonly included in published linkage

maps (Mbanjo et al. 2012). The novel SNP markers

exhibited linkage with existing SSR markers of the

framework map and were mapped onto seven of the

nine framework linkage groups (Fig. 1). The addition

of the EST-RGA markers resulted in a significant

increase in map length (6 %), as well as in map

saturation (6 %). Two markers (HL191 and HL5623)

were polymorphic in both parents and their position on

the maps represents a useful anchor point for parental

linkage group fusion in our pseudo-testcross

population.

Despite the low overall rate of R genic sequence

detection, several genes of considerable interest were

found. Most notably, a Verticillium wilt resistance (Ve)-

like protein sequence was detected, along with three

somatic embryogenesis receptor-like kinases (SERK)

and a BRI1-associated receptor kinase (BAK1), which

are known to be involved in downstream signalling of

Ve (Fradin et al. 2009) (Table 1). In addition, three

additional TIR-NBS-LRR class R proteins were

detected, including a TMV resistance protein N homo-

log. Unfortunately, only one of these genes (a SERK,

HL191) could be directly mapped (Fig. 2). Retrieval of

additional EST flanking sequences for these genes

might enable their mapping in the future.

This study used a sound technique for mining

RGAs from public EST sources utilizing characteristic

RGA pfam domain motifs. In the identified sequences,

special care was taken to predict putative intron

sites via a cross-genera approach, using genomic

information from well characterized plant species.

Several valuable hop resistance gene analogs were

detected, two of which were mapped. The remainder

of the mapped markers are a valuable addition to the

existing hop linkage map. In addition to being

valuable for their potential use in MAS towards

resistant hop cultivars, these markers will allow us to

extend and further populate linkage maps of other

available hop crosses, rendering them useful for QTL

analysis of plant resistance to pathogens and possible

subsequent map-based cloning of candidate resistance

genes.

Acknowledgments The authors acknowledge financial support

from the Slovenian Research Agency, grant number P4-0077, and

the support of A.M. by Grant Number 1000-09-310205.

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