c Indian Academy of Sciences
RESEARCH ARTICLE
Construction of an EST-SSR-based interspecific transcriptome linkage
map of fibre development in cotton
CHUANXIANG LIU, DAOJUN YUAN and ZHONGXU LIN∗
National Key Laboratory of Crop Genetic Improvement and National Centre of Plant Gene Research (Wuhan),
Huazhong Agricultural University, Wuhan 430070, Hubei, People’s Republic of China
Abstract
Quantitative trait locus (QTL) mapping is an important method in marker-assisted selection breeding. Many studies on the
QTLs focus on cotton fibre yield and quality; however, most are conducted at the DNA level, which may reveal null QTLs.
Hence, QTL mapping based on transcriptome maps at the cDNA level is often more reliable. In this study, an interspecific
transcriptome map of allotetraploid cotton was developed based on an F2 population (Emian22 × 3-79) by amplifying cDNA
using EST-SSRs. The map was constructed using cDNA obtained from developing fibres at five days post anthesis (DPA).
A total of 1270 EST-SSRs were screened for polymorphisms between the mapping parents. The resulting transcriptome
linkage map contained 242 markers that were distributed in 32 linkage groups (26 chromosomes). The full length of this
map is 1938.72 cM with a mean marker distance of 8.01 cM. The functions of some ESTs have been annotated by exploring
homologous sequences. Some markers were related to the differentiation and elongation of cotton fibre, while most were
related to the basic metabolism. This study demonstrates that constructing a transcriptome linkage map by amplifying cDNAs
using EST-SSRs is a simple and practical method as well as a powerful tool to map eQTLs for fibre quality and other traits in
cotton.
[Liu C., Yuan D. and Lin Z. 2014 Construction of an EST-SSR-based interspecific transcriptome linkage map of fibre development in cotton.
J. Genet. 93, 689–697]
Introduction
Cotton is one of the most important crops in the world,
providing natural fibre used in many facets of daily life.
The most extensively cultivated cotton species are the allotetraploid Gossypium hirsutum and G. barbadense, which
account for ∼95 and 2% of total production worldwide
(National Cotton Council, http://www.cotton.org). G. hirsutum and G. barbadense are known for their high yield
and high fibre quality, respectively (Pang et al. 2012). The
contrasting traits of two species make them ideal for studying the genetic basis of yield and fibre quality in cotton (Mei
et al. 2004; Lacape et al. 2005, 2010; He et al. 2007; Yu et al.
2013). However, since yield and fibre quality in cotton are
complex quantitative traits, studies on the genetic basis of
these traits rely on genetic linkage maps.
The first interspecific linkage map was constructed with
restriction fragment length polymorphism (RFLP) markers
∗ For correspondence. E-mail: [email protected].
(Reinisch et al. 1994). However, a shortage of RFLP probes
restricts worldwide use. Fortunately, the development of
PCR-based markers, especially simple sequence repeats
(SSRs), has increased rapidly. There are now 17,448 publicly available SSR markers in cotton (http://www.cottongen.
org), which facilitate linkage map development and QTL
mapping in cotton worldwide. EST-SSRs account for
nearly half of all SSRs. Several high-density interspecific
linkage maps (Rong et al. 2004; Yu et al. 2011; Zhao
et al. 2012; Fang and Yu 2012) and intraspecific linkage
maps have been developed in cotton. In addition, many
QTL mapping studies for yield and fibre quality have
been conducted with both interspecific (Mei et al. 2004;
Lacape et al. 2005, 2010; He et al. 2007; Yu et al. 2013)
and intraspecific populations (Ulloa et al. 2005; Zhang et al.
2005, 2009, 2012; Shen et al. 2006; Wang et al. 2006; Qin
et al. 2008; Wu et al. 2009; He et al. 2011; Liu et al. 2012;
Sun et al. 2012). These studies contribute much to the understanding of the complexity of genetic control of cotton yield
and fibre quality.
Recently, the focus on QTL mapping has shifted to the
transcriptional level in cotton. Liu et al. (2009) applied
Keywords. cotton; EST-SSR; transcriptome linkage map; fibre development.
Journal of Genetics, Vol. 93, No. 3, December 2014
689
Chuanxiang Liu et al.
cDNA-amplified fragment length polymorphisms (AFLPs)
to construct fibre transcriptome groups at the secondary cell
wall (SCW) thickening stage, based on an interspecific backcross (BC1 ) of G. hirsutum × G. barbadense. They mapped
78 transcript-derived fragments (TDFs) into eight transcriptome groups, and detected two significant QTLs, FS1 and
FS2, which explained 16.08 and 15.87% of the fibre strength
variance, respectively. Liu et al. (2011) constructed a
transcriptome map based on cDNA-AFLPs, using an immortalized F2 (IF2 ) population of the cotton hybrid Xiangzamian 2 (G. hirsutum). A total of 302 TDFs were mapped
onto 26 linkage groups, and 71 QTLs for yield and yield
component traits were detected, based on four environments,
with 13 QTLs identified in at least two environments.
Claverie et al. (2012) used quantitative cDNA-AFLP to monitor variation in the expression level of cotton fibre elongation and secondary cell wall thickening transcripts in a
population of interspecific G. hirsutum × G. barbadense
recombinant inbred lines (RILs). Two-thirds of the normalized intensity ratios of TDFs were mapped between 1 and 6
eQTLs.
Genomewide transcriptome maps form the foundation of
gene mapping and cloning as well as comparative genomics.
Usually, transcriptome maps are constructed using cDNAAFLPs since direct mapping of transcripts with the cDNAAFLP technique is a rapid and practical method of direct
mapping of expressed genes (Brugmans et al. 2002). Transcriptome maps have been successfully constructed in Arabidopsis and potato (Brugmans et al. 2002; Ritter et al. 2008)
as well as in cotton (Liu et al. 2009, 2011; Claverie et al.
2012) by cDNA-AFLP. The cDNA-AFLP technique is highthroughput, however, the procedure is complex. cDNASRAP has been applied for the construction of a transcriptome map in B. oleracea (Li et al. 2003); this technique is
similar to but simpler than cDNA-AFLP.
Compared to these two techniques, constructing transcriptome maps using EST-SSRs is also a practical method
of directly mapping expressed genes. Although EST-SSRs
are developed from ESTs, EST-SSRs are typically applied
in DNA research as they are simpler and easier to work
with. In fact, EST-SSRs can be directly used to amplify
cDNA to construct SSR-based transcriptome linkage maps.
There are many EST-SSRs in different plants, with more
than 8000 EST-SSRs in cotton (http://www.cottongen.org).
Thus, EST-SSRs are a valuable resource for constructing transcriptome maps. Generally, EST-SSRs were first
applied in DNA-based genetic maps, implying that they
have been mapped to chromosomes. When they are applied
in transcriptome maps, the linkage groups can easily be
assigned to corresponding chromosomes. However, most
TDFs from cDNA-AFLPs and -SRAPs have not been
mapped to chromosomes, since it is hard to assign them
to chromosomes (Brugmans et al. 2002; Li et al. 2003; Ritter
et al. 2008; Liu et al. 2009, 2011).
In this study, we utilized the cDNA samples obtained from
developing fibres from an F2 population of Emian22 × 3-79
690
at five days post anthesis (DPA) as templates to explore
the possibility that a transcriptome map could be constructed by amplifying cDNA using EST-SSRs. We have
shown that this practical and simple method for constructing transcriptome linkage maps will facilitate eQTL mapping in cotton, which will help to analyse the genetic
basis of economically desirable traits at the transcriptional
level.
Materials and methods
The mapping parents were the G. hirsutum cultivar
‘Emian22’ and the G. barbadense accession ‘3-79’, which
are described in the previous work with the BC1 mapping
population (Yu et al. 2011). To construct a transcriptome
linkage map, a new F2 population was developed. The F2
population (∼200 individuals) was planted in the experimental field of Huazhong Agriculture University, Wuhan,
Hubei, China in 2009. However, only 69 plants were used
to construct the map as it was possible to obtain enough
samples for RNA extraction from these plants. In the previous study, it was found that the differences in developing
fibres at five DPA were obvious between the mapping parents
(Liu et al. 2013). Therefore, RNA was extracted from developing fibres at five DPA using the method described by
Zhu et al. (2005). First-strand cDNA was synthesized using
3 µg of RNA from each sample, following the protocol proR
III RT kit (Invitrogen, Carlsbad,
vided with the Superscript
USA).
Polymorphism screening
All the markers used in this study were obtained from
the previously published BC1 linkage map (Yu et al.
2011), which have been mapped to chromosomes. Since
the markers on the BC1 map included gSSRs and ESTSSRs, the EST-SSRs were directly used to screen for
polymorphisms in the cDNA of developing fibres at five
DPA; the sequences of the gSSRs were blasted against
the cotton ESTs to identify SSRs derived from the transcribed sequences. Next, these SSRs were used to screen for
polymorphisms.
PCR amplification and electrophoresis
Polymerase chain reaction (PCR) was conducted in
20 µL volume containing 25 ng DNA, 0.2 µmol L−1 forward primers, 0.2 µmol L−1 reverse primers, 1× buffer,
1.5 mmol L−1 MgCl2 , 0.3 mmol L−1 dNTPs and 0.5 units
of Taq polymerase. The PCR profile consisted of an initial denaturation at 94◦ C for 2 min followed by 30 cycles
of denaturation at 94◦ C for 1 min, annealing at 55◦ C for
1 min, and an extension at 72◦ C for 1 min, with a final incubation at 72◦ C for 10 min. First, the amplification products obtained with all of the primers were genotyped using
Journal of Genetics, Vol. 93, No. 3, December 2014
EST-SSR-based transcriptome map in cotton
Table 1. Polymorphisms of different SSRs in developing fibres at five DPA between mapping parents.
SSR
EST-SSRs
Transcript-derived gSSRs
Primer
Total
Primers with products
Primers with polymorphism
HAU
NAU
MUSS
MUCS
MGHES
STV
JESPR
BNL
CM
TMB
CIR
DPL
Gh
MUSB
460
648
36
16
19
20
4
16
1
14
1
21
8
6
186 (40.4%)
327 (50.4%)
11 (30.7%)
9 (56.3%)
10 (52.6%)
5 (25.0%)
2 (50.0%)
6 (37.5%)
1 (100%)
5 (35.7%)
1 (100%)
6 (28.6%)
0 (0)
1 (16.7%)
95 (20.7%)
179 (27.6%)
5 (13.9%)
8 (50.0%)
8 (42.1%)
2 (10.0%)
1 (25.0%)
3 (18.8%)
1 (100%)
1 (7.1%)
0 (0)
0 (0)
0 (0)
0 (0)
1270
570 (44.9%)
303 (23.86%)
Total
Table 2. Basic information on the F2 transcriptome linkage map based on developing fibres at five DPA.
Linkage group
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
AT -genome
19
20
21
22
23
24
25
26
27
28
29
30
31
32
DT -genome
Total
Chromosome
Length (cM)
Total loci
Average distance
Largest gap (cM)
Chr01
Chr02
Chr03
Chr04
Chr05
Chr06
Chr06
Chr07
Chr08
Chr08
Chr09
Chr09
Chr09
Chr10
Chr10
Chr11
Chr12
Chr13
78.53
47.38
76.10
115.23
132.74
33.16
30.58
30.03
56.63
28.16
36.12
50.74
22.18
18.8
50.81
108.68
57.02
68.79
1041.68
104.41
64.14
25.92
24.43
82.83
92.42
52.53
116.19
74.77
43.72
88.86
33.25
2.33
91.34
897.04
8
4
10
10
15
6
3
2
9
3
2
4
2
2
5
16
6
7
114
11
15
2
3
8
15
6
17
9
5
18
3
2
14
128
9.82
11.85
7.61
11.52
8.85
5.53
10.19
15.02
6.29
9.39
18.06
12.69
11.09
9.40
10.16
6.79
9.50
9.83
9.14
9.49
4.28
12.96
8.14
10.35
6.16
8.76
6.83
8.31
8.74
4.94
11.08
1.17
6.52
7.01
16.46
33.65
20.67
22.44
23.59
16.08
15.57
30.03
14.06
23.74
36.12
26.74
22.18
18.81
14.39
19.75
21.05
17.02
36.12
24.13
11.58
25.92
12.75
25.27
11.56
19.85
32.31
17.78
15.36
20.49
18.14
2.33
13.00
36.12
1938.72
242
8.01
36.12
Chr14
Chr15
Chr16
Chr17
Chr18
Chr19
Chr20
Chr21
Chr22
Chr23
Chr24
Chr25
Chr25
Chr26
the SSR analysis protocol on 6% denaturing polyacrylamide gels at room temperature (Lin et al. 2005). Next,
the monomorphic PCR products were separated based on
single-strand conformation polymorphisms (SSCPs) on 6%
nondenaturing polyacrylamide gels at a constant 8 W for
∼16 h at 4◦ C.
Journal of Genetics, Vol. 93, No. 3, December 2014
691
Chuanxiang Liu et al.
Transcriptome linkage map construction
After polymorphism screening, all the polymorphic markers
were used to genotype the entire F2 population. If a primer
detected multiple loci, letters (a, b, c...) were assigned to the
loci according to the descending fragment size. The linkage
map was constructed with JoinMap 3.0 (Stam 1993) using
a logarithm of odds (LOD) threshold of 4.0 and a maximum recombination fraction of 0.4. Map distances were calculated in centi-Morgans (cM) using the Kosambi mapping
function (Kosambi 1944). Linkage groups were assigned to
LG01/Chr01
LG02/Chr02
NAU3384
MGHES10
9.03
LG03/Chr03
NAU3839
0.23
7.37
2.09
NAU5134
HAU2154
HAU2102
HAU1980a
NAU3533b
NAU2741
9.81
1.14
4.45
11.52
17.37
LG04/Chr04
5.71
5.81
HAU2138
HAU0877b
NAU3592
16.72
NAU5233
HAU1782b
NAU3671
15.36
HAU0992
12.10
NAU5443b
NAU3083
NAU3309b
6.03
HAU0877a
15.10
11.64
11.29
3.59
The SSR sequences were functionally annotated using
Blast2GO (Conesa et al. 2005; Götz et al. 2008) with default
parameters. First, blastx analysis was carried out with an
E-value of 10−5 against the nr protein database in GenBank; and the sequences with >80% identity were retained.
Next, GO-mapping, annotation analysis, InterPro Scan and
20.67
33.65
16.46
8.21
Functional annotation of SSR-ESTs
NAU4035b
NAU4073b
12.58
NAU4891
the corresponding chromosomes using mapped SSRs (http://
www.cottongen.org).
NAU3491
HAU2085b
NAU5180b
20.67
HAU3176b
HAU0883a
NAU2363b
22.44
NAU2363a
12.07
4.13
LG06/Chr06
LG05/Chr05
3.77
NAU3828
HAU0968
10.78
NAU3402
8.21
4.64
2.71
3.43
NAU5255
NAU1137
NAU3197b
NAU3569
11.65
2.30
0.09
3.04
LG08/Chr07
HAU1488a
HAU1488b
HAU2119
NAU5433
NAU5434
NAU4956
HAU3346b
HAU2086b
MUCS148b
HAU2756
HAU0996a
15.09
4.30
1.91
5.64
14.06
16.08
NAU4969
LG09/Chr08
8.96
30.03
HAU1056
HAU2085a
2.69
0.72
12.76
HAU2738a
NAU3207a
NAU3201a
NAU3558
HAU1496
NAU5387
9.89
NAU3424
23.53
7.82
1.82
6.08
MUSS106
HAU0996b
HAU1782a
NAU2630
LG07/Chr06
4.42
HAU0504
23.74
15.01
16.97
HAU2313
HAU2738b
HAU1739
15.57
NAU3427a
23.59
NAU3014
Figure 1 (continues)
692
LG10/Chr08
NAU3677b
Journal of Genetics, Vol. 93, No. 3, December 2014
NAU2602a
EST-SSR-based transcriptome map in cotton
InteProScan GOs were performed. Finally, GO-Slim (http://
www.geneontology.org/GO.slims.shtml) was then carried
out to acquire specific GO terms.
Results and discussion
Marker polymorphism
In this study, the mapping parents were the same as those
used to construct the DNA-based linkage map (Yu et al.
LG11/Chr09
LG14/Chr10
HAU2496a
2011). The EST-SSRs in the DNA-based linkage map were
directly used to construct the transcriptome map. To map
more markers, genomic SSRs in the map were blasted against
the cotton ESTs to identify transcribed markers. Finally, 1270
transcript-derived SSRs were included in this study (table 1).
The samples used for transcriptome map construction were
cDNAs from developing fibres at five DPA, as it was confirmed that a great number of TDFs differed between the
mapping parents at this stage (Liu et al. 2013). After polymorphism detection, only 303 primers (23.86%) showed
LG16/Chr11
NAU3574b
HAU2624
36.12
NAU5419
NAU5212a
13.57
18.80
LG17/Chr12
21.05
NAU2602b
19.75
HAU0361
LG12/Chr09
NAU5454
LG15/Chr10
13.47
HAU3150
NAU4008
10.53
MGHES70
12.45
0.01
9.45
3.96
2.25
4.16
7.96
10.52
1.04
1.93
0.09
6.46
11.81
NAU3665b
9.72
26.74
HAU0949
HAU2067a
7.44
NAU3115
NAU1148
MUSS123
NAU3367
NAU2661
NAU3621
NAU2877
NAU4086
NAU3234b
NAU3234a
NAU2094
NAU5480
6.04
NAU3778
11.96
HAU2229
LG18/Chr13
NAU3017a
10.45
15.72
NAU5107a
NAU2016b
14.66
NAU5438
LG13/Chr09
NAU1301
NAU2672b
10.53
NAU3770a
14.39
HAU1454
HAU3220
14.26
17.02
HAU1968
NAU3570
HAU1966
8.55
HAU2224
8.86
22.18
NAU5345
9.25
NAU3967
LG19/Chr14
HAU1455
24.13
NAU3225
10.93
NAU3913
10.52
4.15
8.65
HAU1741
NAU3308
HAU0438
9.15
NAU2845
NAU3307
LG20/Chr15
1.54
11.58
NAU4073a
NAU3496
7.44
7.35
1.71
2.74
8.81
1.33
5.61
0.37
3.28
5.97
1.51
4.91
NAU3714
HAU2490
NAU3680
NAU5107c
NAU2814
NAU3922
NAU3533a
MUCS410
HAU1740
MUCS422
MUCS141
NAU3574a
MUCS152
LG21/Chr16
HAU1399b
NAU3161
12.76
25.92
3.89
7.47
NAU3906
LG22/Chr17
NAU5443a
HAU1922
19.45
3.44
HAU2850
NAU3398
NAU3589
NAU3309a
11.68
HAU3176a
NAU3312
NAU3130
NAU3943
10.55
12.75
8.34
7.42
LG23/Chr18
25.27
NAU3534
HAU1980b
11.80
NAU4009
9.32
NAU3733
Figure 1 (contd)
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693
Chuanxiang Liu et al.
polymorphism, 267 (21.02%) produced amplification products, but lacked polymorphism, and 700 (55.12%) did not
amplify the target (table 1) The failed amplification is likely
to be the reason as these SSRs could not target tissue-specific
transcripts in developing fibres at five DPA.
Transcriptome linkage map construction
The cDNA samples obtained from the F2 population were
genotyped with the 303 polymorphic primers; however,
some primers generated ambiguous gel bands and were discarded in subsequent analyses. Subsequently, 244 primers
produced clearly scorable gel bands with 279 polymorphic
loci; among them, 58 (20.79%) were 3-79 dominant loci,
18 (6.45%) were Emian22 dominant, and 203 (72.76%)
were codominant loci. Generally, SSRs are codominant.
The corresponding genes of the codominant markers are
all expressed in the parents. However, variations in the
LG24/Chr19
6.65
NAU3110
HAU0558b
8.31
HAU1097
5.42
7.49
9.48
7.24
8.91
1.42
7.09
NAU2650
NAU3664
NAU3652
NAU4896
11.56
9.04
1.12
2.60
8.44
7.98
4.81
6.08
LG25/Chr20
NAU3574c
HAU3156
HAU2178
NAU3813
11.46
NAU3665a
LG26/Chr21
2.33
1.03
13.96
6.04
6.02
6.77
6.41
19.85
HAU3366
NAU3096
NAU6406
NAU3024
MGHES21
microsatellite region could occasionally cause alterations in
the translated products, which could result in trait variations. The corresponding genes of dominant markers are only
expressed in one parent, which could alter the gene network
of the trait and result in trait variations.
After linkage analyses, 242 loci were mapped into 32 linkage groups, with 37 remaining loci unmapped. The total
length of the transcriptome linkage map was 1938.72 cM
(table 2; figure 1). The longest linkage group was 132.74 cM
with 15 loci (LG05/Chr05), while the shortest linkage group
was 2.33 cM with two loci (LG31/Chr25); generally, the
average length of a linkage group was 60.58 cM. The
average marker interval distance was 8.01 cM, while it varied from 0.01 (LG16/Chr11) to 36.12 cM (LG11/Chr09).
The AT genome included 18 linkage groups with a total of
114 loci; the total length was 1041.68 cM, and the average
marker interval distance was 9.14 cM. Comparatively, the DT
genome included 14 linkage groups with a total of 128 loci;
NAU5307
NAU5330
NAU3674
HAU2008
9.99
3.63
5.44
0.53
7.84
1.52
6.87
5.50
NAU3284
NAU3354b
NAU3341a
LG27/Chr22
7.10
5.63
0.65
NAU5212b
NAU4865
NAU3354a
17.33
HAU1295
NAU2758
17.78
NAU3341b
NAU4026
NAU3770b
JESPR158
NAU2016a
HAU2004
NAU3740
NAU3731
1.41
NAU3791b
MUSS124
NAU2235
HAU2570
HAU0558a
NAU2291
NAU3591
14.98
NAU5180a
9.89
NAU4058
32.31
NAU3156
LG28/Chr23
NAU3763
8.74
NAU2567
9.73
NAU6130
9.89
HAU2067b
15.36
NAU3732
LG29/Chr24
9.00
2.34
4.62
1.73
1.55
8.57
1.75
1.33
0.64
4.15
6.65
2.74
1.24
5.02
3.16
13.78
NAU2619
NAU3988
NAU3207b
HAU2086a
HAU3346a
MUCS148a
HAU3293
MUCS113
NAU3499
NAU2169
HAU3247
MUSS250
NAU2439
NAU3201b
NAU3071
NAU3158
NAU3287
20.49
LG30/Chr25
LG32/Chr26
HAU2759
HAU2587
10.88
15.11
HAU1783a
5.65
HAU3121
10.65
1.87
7.24
18.14
7.47
LG31/Chr25
2.33
HAU1919
NAU3677a
NAU4091
6.75
4.14
8.83
3.28
5.28
NAU5425
NAU2356
NAU3961
HAU0908
NAU3236
HAU0723
NAU5321
HAU2137
NAU3876
NAU4905b
NAU3905
13.00
6.30
NAU2251
NAU4905a
Figure 1. Interspecific transcriptome linkage map of fibre development in cotton constructed using EST-SSRs.
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EST-SSR-based transcriptome map in cotton
Table 3. Distribution of dominant markers in the transcriptome map.
Chr.
01
01
01
03
03
03
05
05
05
05
05
06
06
06
06
Marker
Chr.
Marker
Chr.
Marker
Chr.
Marker
HAU2102
NAU3384
NAU4891
HAU0992
NAU3083
NAU5233
NAU2630
NAU3197b
NAU3569
NAU5255
NAU5387
HAU1488b
HAU2119
NAU3427a
NAU3677b
07
08
09
10
10
10
11
11
11
11
12
12
13
13
14
NAU4956
NAU2602a
NAU5454
NAU3574b
HAU0949
NAU4008
NAU2661
NAU3115
NAU3234a
NAU3234b
HAU2229
NAU3778
NAU3017a
NAU3307
HAU0438
14
15
15
15
15
15
15
15
15
15
18
18
19
19
19
NAU3733
HAU1740
MUCS141
MUCS152
MUCS410
MUCS422
NAU3496
NAU3714
NAU3922
NAU3574a
HAU1922
NAU3161
HAU1097
HAU2008
MGHES21
19
20
20
22
22
22
23
24
24
24
24
26
26
26
26
NAU4896
NAU3574c
NAU5307
NAU3591
NAU3791b
NAU4058
NAU6130
NAU2169
NAU3071
NAU3158
NAU3287
HAU2587
HAU0723
NAU3961
NAU4905a
the total length was 897.04 cM and the average marker interval distance was 7.01 cM. The genomewide distribution of
EST-SSRs implied that the fibre development in cotton
involves genes distributed throughout the entire genome.
We found that dominant markers were absent on Chr02,
Chr04, Chr16, Chr17, Chr21 and Chr25 (table 3). Obviously,
there were more chromosomes lacking dominant markers in
the DT genome than in the AT genome; however, there were
more dominant markers overall in the DT genome, indicating
that the dominant markers were clustered on particular chromosomes of the DT genome, especially Chr15. The uneven
distribution of EST-SSRs on the chromosomes implied that
different chromosomes played different roles in developing
fibres at five DPA. This result also provided evidence for the
existence of tissue-specific transcriptomes.
This map is suitable for mapping eQTLs. Unfortunately,
most of the cotton bolls were sampled for RNA extraction
to construct the transcriptome map; thus, not enough bolls
remained to phenotype the fibre quality. However, when transcriptome maps are constructed from permanent populations,
it is feasible to map eQTL to understand the genetic basis
unknown 16%
of cotton fibre traits at the transcriptional level. We can also
compare the eQTLs with previous QTLs based on DNA
markers to uncover those reliable QTLs.
Functional annotation of SSR-ESTs
After blasting against the nr protein database, 53 of the
242 SSR-ESTs with >80% identity were functionally annotated, and they were classified into 10 categories (figure 2).
Except for the 16% with unknown function, the top functions
were transcription activity (15%) and transportation activity (14%). Some SSR-ESTs were involved in fibre differentiation (e.g. NAU3495), fibre initiation (e.g. NAU3496)
and fibre elongation (e.g. MUSS250). These results were in
accordance with the sampling phase (developing fibres at
five DPA) as five DPA is the overlapping period of fuzz
cell differentiation, lint initiation and elongation (Lee et al.
2007).
In conclusion, an EST-SSR-based interspecific transcriptome linkage map of fibre development in cotton was
catalytic activity
10%
enzyme regulator
activity 8%
other 11%
ion binding 10%
molecular structure
8%
transportation
activity 14%
nutrient activity 3%
translation regulator
5%
transcription activity
15%
Figure 2. Functional annotation of mapped SSR-ESTs.
Journal of Genetics, Vol. 93, No. 3, December 2014
695
Chuanxiang Liu et al.
constructed. This innovative new tool for constructing transcriptome linkage maps can be easily used to assign linkage groups to chromosomes and facilitate eQTL mapping in
plants.
Acknowledgement
This work was financially supported by the National Basic Research
Program (no. 2011CB109303 and 2010CB126001).
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Received 3 December 2013, in final revised form 24 April 2014; accepted 20 May 2014
Unedited version published online: 24 June 2014
Final version published online: 22 September 2014
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