construction of a microsatellite linkage map with two sequenced rice varieties

9
3 # % a Actu Genetica Sinica, February 2006, 33 (2): 152-160 ISSN 0379-4172 Construction of a Microsatellite Linkage Map with Two Se- quenced Rice Varieties ZHANG Qi-Jun 1,3*, YE Shao-Ping'*, LI Jie-Qin', ZHAO Bing', LIANG Yong-Shu', PENG Yong', LI Ping ' s2, ' 1. Rice Research Institute of Sichuan Agricultural University, Wenjiang 61 1130,China; 2. Key Laboratory of Ministry of Education of Southwest Crop Genetic Resources and Improvement (Sichuan Agricultural Univer- sity), Ya'an 625014, China; 3. Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Nanjing 21 0014,China Abstract: Based on the successful development of new microsatellite markers from the data of two whole-sequenced rice varieties, japonica variety Nipponbare and indica variety 931 1, an F2 population of 90 lines, which was derived from a single cross between Nipponbare and 9311, was applied to construct a genetic linkage framework map. The map covered 2 455.7 cM of total genomic length, and consisted of 152 simple sequence repeats (SSRs) loci including 46 pairs of new SSR primers developed by our research institute. The average genetic distance between two markers was 16.16 cM. In addition, markers RM345 and RM494, which have not been mapped on the Temnykh's map et al. (2001) were anchored on the sixth chromosome of this map. We compared this research with maps of Temnykh et a1.(2001) and LAN et al. (2003) regarding the aspects of type and size of population, type and quantity of markers, and the marker arrangement order on chromosome, etc. Results indicated that the similarity of marker linear alignment was 93.81% between this map and T-map. Finally, the important significance of using sequenced rice varieties to con- struct linkage map was also discussed. Key words: sequenced rice (Oryza sativu L.) varieties; microsatellite marker; genetic linkage map The development of the construction of rice link- age maps using molecular markers is very rapid. Since McCouch et al. "' constructed the first rice molecular linkage map in 1988, many maps have been published utilizing different kinds of populations and many types of molecular markers '2-61. In the past fifteen years the most often used marker types were RFLP '5-91 or a mix- ture of several lunds of markers '102111. Recently, with the implementation and accomplishment of rice genomic sequence project, more and more reports about con- structing rice genetic maps with SSR markers have been published. Temnykh et al. '123131 constructed a linkage map including more than 500 SSR markers with a dou- ble haploid (DH) population of IR64/Azucena, LAN et al. [14' published a SSR linkage map containing 122 markers using a DH population of Pei'ai64sE32, and McCouch et al. '15' drew a SSR linkage map including 2 740 markers with the method of electronic poly- merase chain reaction (e-PCR) based on the results of rice genomic sequence project. These maps facilitate high-resolution genetic mapping and positional cloning of important genes, allow genetic dissection of quanti- tative trait loci, assist in local comparisons of synteny, and provide an ordered scaffold on which complete physical maps can be assembled ['". However, among the researches, only few were completely using SSR markers to construct rice linkage maps '14,15'. Maybe there were three reasons. ~~~ ~ Received: 2004-1 1 -25; Accepted: 2005-05-08 This work was supported by Chinese National Programs for High Technology Research and Development (863 Program) (No. 2003AA212030) and the Program for Changjiang Scholars and Innovative Research Team in University (No. IRT 0453). * Contributed equally to this study 0 Corresponding author. E-mail: [email protected]; Tel: +86-28-8272 2497,Fax:+86-28-8272 6875

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Page 1: Construction of a Microsatellite Linkage Map with Two Sequenced Rice Varieties

3 # % a Actu Genetica Sinica, February 2006, 33 (2): 152-160 ISSN 0379-4172

Construction of a Microsatellite Linkage Map with Two Se- quenced Rice Varieties

ZHANG Qi-Jun 1,3*, YE Shao-Ping'*, LI Jie-Qin', ZHAO Bing', LIANG Yong-Shu', PENG Yong',

LI Ping ' s2,' 1 . Rice Research Institute of Sichuan Agricultural University, Wenjiang 61 1 130, China;

2. Key Laboratory of Ministry of Education of Southwest Crop Genetic Resources and Improvement (Sichuan Agricultural Univer-

sity), Ya'an 625014, China;

3. Institute of Food Crops, Jiangsu Academy of Agricultural Sciences, Nanjing 21 0014,China

Abstract: Based on the successful development of new microsatellite markers from the data of two whole-sequenced rice varieties, japonica variety Nipponbare and indica variety 931 1, an F2 population of 90 lines, which was derived from a single cross between Nipponbare and 9311, was applied to construct a genetic linkage framework map. The map covered 2 455.7 cM of total genomic length, and consisted of 152 simple sequence repeats (SSRs) loci including 46 pairs of new SSR primers developed by our research institute. The average genetic distance between two markers was 16.16 cM. In addition, markers RM345 and RM494, which have not been mapped on the Temnykh's map et al. (2001) were anchored on the sixth chromosome of this map. We compared this research with maps of Temnykh et a1.(2001) and LAN et al. (2003) regarding the aspects of type and size of population, type and quantity of markers, and the marker arrangement order on chromosome, etc. Results indicated that the similarity of marker linear alignment was 93.81% between this map and T-map. Finally, the important significance of using sequenced rice varieties to con- struct linkage map was also discussed. Key words: sequenced rice (Oryza sativu L.) varieties; microsatellite marker; genetic linkage map

The development of the construction of rice link- age maps using molecular markers is very rapid. Since McCouch et al. "' constructed the first rice molecular linkage map in 1988, many maps have been published utilizing different kinds of populations and many types of molecular markers '2-61. In the past fifteen years the most often used marker types were RFLP '5-91 or a mix- ture of several lunds of markers '102111. Recently, with the implementation and accomplishment of rice genomic sequence project, more and more reports about con- structing rice genetic maps with SSR markers have been published. Temnykh et al. '123131 constructed a linkage map including more than 500 SSR markers with a dou- ble haploid (DH) population of IR64/Azucena, LAN et

al. [14' published a SSR linkage map containing 122 markers using a DH population of Pei'ai64sE32, and McCouch et al. '15' drew a SSR linkage map including 2 740 markers with the method of electronic poly- merase chain reaction (e-PCR) based on the results of rice genomic sequence project. These maps facilitate high-resolution genetic mapping and positional cloning of important genes, allow genetic dissection of quanti- tative trait loci, assist in local comparisons of synteny, and provide an ordered scaffold on which complete physical maps can be assembled ['".

However, among the researches, only few were completely using SSR markers to construct rice linkage maps '14,15'. Maybe there were three reasons.

~~~ ~

Received: 2004-1 1 -25; Accepted: 2005-05-08

This work was supported by Chinese National Programs for High Technology Research and Development (863 Program) (No. 2003AA212030) and the Program for Changjiang Scholars and Innovative Research Team in University (No. IRT 0453). * Contributed equally to this study

0 Corresponding author. E-mail: [email protected]; Tel: +86-28-8272 2497,Fax:+86-28-8272 6875

Page 2: Construction of a Microsatellite Linkage Map with Two Sequenced Rice Varieties

ZHANG Qi-Jun ef d.: Construction of a Microsatellite Linkage Map with Two Sequenced Rice Varieties 153

First, microsatellites are asymmetrically distributed in therefore, when only using SSR markers

to construct rice linkage map, it may make the marker distribution uneven on the map and some intervals between two markers are too big. Second, some SSR primers filtering software have not been applied because the rice genomic sequence project was just accom- plished “9,201. Third, up to now, only two rice varieties (Nipponbare and 93 1 1 ) have been completely se- quenced; rice varieties Guangluai-4 and Pei’ai64s were partly sequenced; and the SSR markers that were based on the data of these sequenced genomic production must be validated by other materials or populations. All of these questions limited the applica- tions of rice SSR markers, especially the new exploited SSR markers. So, choosing whole-sequenced rice varieties as mapping parents to construct microsatellite linkage map may solve these problems.

It is expected to find the common joints between the map research and the achievement of rice genome project (RGP) using the sequenced rice varieties as mapping parents, because it is easy to develop new molecular markers utilizing the data of rice genomic sequence project. This provides great prospects for locating and cloning of genes, especially the quantitative trait genes, and it can also make some functional remarks on the current genomic data’*”.Hence, the use of whole-sequenced varieties as mapping parents have important theoretical significance and potential applied values but have not been reported in literatures yet. Using the SSR rnarkers published by Cornell University, and the SSR primers developped in our laboratory based on the data of RGP, this research selected an F2 mapping population derived from a single cross between two whole-sequenced rice varieties, japonica variety Nipponbare and indica variety 9311, to construct a linkage map with 152 SSK markers, and anchored 46 new SSR markers.

1 Methods and Materials

1.1 Materials and planting

In Oct. 2003, at Linshui county, Hainan Province, we planted the F2 population derived from the cross

Nipponbare (9) x 9311 (8) (total 90 lines) and their parents in the paddy field at a density of 30 cm x 30 cm with conventional plant management subsequently. Genomic DNA were isolated from the leaves at the tiller flourishing stage.

1.2 Synthesis of SSR primers

The SSR primers in this research partly originated

from the Japanese rice genome project (OSR numbers); some came from the research results of Cornell University (RM numbers); and the rest, RP numbers, were developed by our laboratory, based on the genomic data of Nipponbare and 9311. All these primers were synthesized by the Shanghai Bioasia Bio-tech. Co., Ltd.

1.3 Analysis of SSR

Genomic DNA were extracted from fresh leaves

following the protocol described by Causse et a1 “ I .

PCR total volume was 20 pL including: 2 pL 10 x PCR buffer, 0.25 mmolL dNTP, 4 pmoVL primer mixtures,

1 U DNA polymerase, 50-100 ng DNA. PCR was

performed in a PTC200 thermocycler (MJ Research) or PX2 thermocycler (ThermoHybaid Corporation) as described by Temnykh et a1‘l3’. The basic profile was:

5 min at 94”c, 35 cycles of 45 s at 94”C, 45 s at 55”c,

1 min at 72”C, and 7 min at 72°C for final extension.

PCR products were separated on 3% agarose gels and marker bands were revealed using the EtBr staining protocol as described by Dieffenbach et a1 ‘**I.

1.4 Construction of molecular genetic map

Based on the results of 3% agarose gel electropho- resis, among the Nipponbare x 93 1 1 -F2 populations, the band types identical with mother-Nipponbare’s were recorded as A, those identical with father-93 11‘s recorded as B, those identical with FI recorded as H, and those indistinct or lacking band recorded as -. MAPMAKEREXP 3.0‘231 was run on a MS-DOS computer using the Kosambi function. At first the “anchor” command to anchor two markers per chromosome based on the linkage map”3’ was used. then the “assign” command to group, and the “compare” and “ripple” test were used to confirm the marker order

Page 3: Construction of a Microsatellite Linkage Map with Two Sequenced Rice Varieties

154 sd*%%$ Acta Genetica Sinica Vo1.33 No.2 2006

as determined by two or multipoint analysis. Markers with a ripple of LOLb2.0 were integrated into the framework maps. Finally, using the software of GENEMAP, the ordered linkage groups were drawn.

2 Results

2.1 Construction of a microsatellite linkage map

The level of polymorphism between Nipponbare and 931 1 using our synthesized 756 pairs of SSR primers (including 505 pairs of RM# primers, 7 pairs of OSR# primers, and 244 pairs of RP# primers) was 33.07% (35.05%, 28.57% and 29.1% for RM#, OSR# and RP# respectively). This research randomly chose 166 SSR markers which had polymorphism between Nipponbare and 93 11, to construct a framework map, which covered 2 455.7 cM of the total genomic length, and included 152 SSR loci (Fig.1). The average ge- netic distance between two markers was 16.16 cM, while in the marker-dense regions the nearest markers were <20 cM apart and were 58% of the total, and there were 16 regions where the distance between ad- jacent markers was >30 cM. If we assume that this map covers the whole rice genome (haploid 4.3 x 10’ bp ‘241), the markers must be located every 2.83 Mb on average. Because these markers were evenly dis- tributed on the rice chromosomes, the population and the new microsatellite map could be used to identify quantitative trait genes.

Forty-six pairs of new SSR primers (numbered as RP# series) exploited by our research institute were anchored on this map (these primer sequences, chromosome locations and their PCR-product sizes in Nipponbare and 9311 are presented in Table 1). The exploitation and application of these new markers greatly enriched the number of rice microsatellites, and had important significance to further saturate the linkage map and gene map, and to improve the mo- lecular marker-assistant selection breeding.

2. 2 A comparison between this and other re- searches

Recently, a distinct progress made in the rice microsatellite linkage mapping was the research of

Temnykh et al ‘I3’. They constructed a more than 500 SSR markers linkage map using the DH population of IR64/Azucena. Primarily we compared this research with their research (marked as ‘T-map’). In addition, we compared this research with LAN’s et al. [14’, who drew a 122 SSR markers linkage map with the DH population of Pei’ai64sE32 (marked as ‘L-map’). The main results are as follows:

(1) Type and size of population: T-map used a DH population of 96 lines, L-map also a DH population of 86 lines, while in this research an F2 population of 90 lines were used. Therefore, the type of our population was different from the former two, and the population size straddled the middle of their populations.

(2) Type and quantity of markers: T-map had more than 500 SSRs and 145 RFLP markers; L-map only had 122 RM# SSR markers; while in this research 106 RM# and 46 RP# markers were used. Compared with T-map, there were two new additional RM# primers in this map (RM345 and RM494, their poly- morphized fragment size in Nipponbare were 155 bp and 203 bp, in 9311 were 168 bp and 176 bp respec- tively, and both of them were anchored on chromo- some 6).

(3) Compared with T-map, this map had 104 pairs of same RM# primers. Besides 7 SSR markers anchored on different linkage groups, the identity reached to 93.27%. Twelve pairs of RM# primers were located on different positions in the chromsome linear alignment among the 97 RM# primers, and the similarity of linear alignment was 93.81%. This indicated that our con- structed linkage map was correct and reliable.

(4) Though the number of markers and the genomic length covered by this map were larger than that of the L-map, there were still more gaps in our map than in L-map, 8 versus 1, respectively. Furthermore, there were some distant regions between two markers, such as on chromosome 3, the genetic distance of RM168-RM565 is 46.3 cM, and RM570-RM535 is 45.4 cM. Accounting for the gap formation, possibly there are three reasons. First, the population parents are different; indica variety PA64S and E32 have the japonica consanguinity. However, in our research,

Page 4: Construction of a Microsatellite Linkage Map with Two Sequenced Rice Varieties

ZHANG Qi-Jun et ul.: Construction of a Microsatellite Linkage Map with Two Sequenced Rice Varieties 155

-Rp129

-RM19

-RM247

-RP164

-RP297

-RM101

-RM519

-RP257

C h r . l Chr .2 Chr .3 Chr .4 Chr.5 Chr .6 Dis t . (cM)Marker Di s t . ( cM)Marke r Di s t . ( cM)Marke r Di s t . ( cM)Marke r Di s t . ( cM)Marke r Di s t . ( cM)Marke r

RM495

RM428 RM 1 RP119

RM259

RM490

RM243

-RM185

-RP194

- RM489

- RP14

- RP135 - RM7

.- RM347

--RM426

.-RP188

. - u s 1 2

.-RP57 I

RM307

RM288

RP207

RM349

3 2 . 4 0

30.00

27 .60

3 1 .40

RP299

RM267 16.30

28 .60

RM587 28 .10

RM485

RM2 11 16.10-

33.80-

25 .90-

15.80-

25.10-

12 .80-

25 .30

14 .50 14 .30 16 .40

22 .30

26 .00

36.40-1 I RM297 RP245

RM430 20 .70 RM7 1

RM214

13.60-

20 .70 - 28 .00 1 I RP162

RM541

11 .80

17 .10

28 .40 -

29 .70 -

32 .10 -

2 9 . 7 0 -

RM575 RM577 RM576 RM583

RM580

RM525

RM240 2 2 . 3 0 -

17 .10

RM406 2 3 . 7 0

2 3 . 8 0 4 I

RP171

20 .60

26 .50

RM466 RM449 RM493

RM9

26 .50 -

13.20 - 14.70 -

24.40 -

27.90 -

25 .50 4 1 3 0 . 7 0 4 1 / RM280 RM405

3 6 . 5 0

RM492 RM262 RM168

RM535

4 6 . 3 0

4 5 . 4 0

RP258

36 .90

2 2 . 6 0 -

RP145 22 .30

RM340

RM494

32 .50

30.90

RP360

RM289 x RM 102

15 .80 18.00

26 .50 1 RM472

Chr .7 Chr .8 Chr .9 Chr . 10 Chr . 11 Chr .12 Di s t . ( cM)Marke r Di s t . ( cM)Marke r Di s t . ( cM)Marke r Di s t . ( cM)Marke r Di s t . ( cM)Marke r Dis t . (

RM542 30.80

RP 105 20 1 0

14 .80 RM556

RM566

14 .90 A

RP363 RP165 10.60 RP222 4:88 RP305

RP252 10 .30 1 5 . 4 0 -

1 1 . 0 0 - RM427 11 '70#RP190 RM258 30.00

17.30

12 .90

2 8 . 7 0 1 22 .20

31 .50 -

RP230 1 RP53 24 .20 -

RM501 27 .80 RM167

19 .10

RM496 6 . 6 0 4 RM333

19.10

RM242

RM107

OSRZX 9.60

RM552 13 .70

RP2 17 22 .90

21 .40 -

10.20 - 15.00

RM205

19 .50 35 .30 2 1 . 5 0 4 1 13.60

RM234 RP320 w 11.80-

17.00

1 RM224

36 .20

Fig. 1 The SSR linkage map with Nipponbare x Y311-F2 population

Page 5: Construction of a Microsatellite Linkage Map with Two Sequenced Rice Varieties

156 %&?f3W Acta Genetica Sinica Vo1.33 No.2 2006

Table 1 The RP# microsatellite markers anchored on this map

Name

RPl2 RP14 RP53 RP54 RP57 RP62 RP68 RPlO5 RPI 19 RP128 RP 129 RP135 RP 145 RP151 RP 162 RPl64 RPl65 RP166 RP171 RP174 RP178 RPl85 RP188 RP190 RP192 RPI 94 RP207 RP2 17 RP222 RP230 RP245 RP249 RP252 RP257 RP2.58 RP288 RP296 RP297 RP298 RP299 RP305 RP3 13 RP320 RP329 RP360 RP363

Forward-primer sequence Reverse-primer sequence Size in 93 1 I1 Nipponbare (bp 1 Chromosome (5'+3') (5' -33 ' )

gtcgttggtcgtcgttgg gcagtgaggtaggacgagtc gccatc ttggattaggattagg acagcagcagacagcaac gtcgctaatctgtgtattgtac caccacgcagtttgacgac ccactctgtagccactgtaag cgtgctcctcttcgtcaag acctacaacaagataagcgtac ccatgcggcgtgtatatcg ccgtatccgattcctgttgg cgtgataatctcctctccttgc gtgcttgcattatcggttgatc tctatcagccgaacacactttc

ggaaggagaggaggaggagac tgatgattgaccaacctgc tgcttcttcggtggtgtgg gccaagtttatgtatcggtctg cctcgtgttgtgttgtgcc tactcgtcactcactcactcag atagtggtgtagcaaataggag gaaagaaattccagcccatcc tgtggattgttgacctggttc ttcaccaactgagcaacataag ctgtacgacacgcagcac acctcttctgctcttcttcctc ggaggtctctaccagcgatg tcgagagcgtttataggatacc cgagcgtgcgttagcttg acttgtctccctaaccttcttg cctgacatgcttaatcgaactg cgctgttcatcctcacatatcg actgggctccttaatcttaatg tcaccaggagagttggctag aacctgtttacccatgtagttc cgccgtgaccacatctatatc gcacacactctctgactctc tgtggacggataagctggtag ctgctagtcccattgtacttc ggcgtgtgctcagaatcatc ggcacatcctaactcacattac caccgtgatctgactgactg ggacatcaaactctatgaatgc aggcgacgacactacactatc ataggtccttagagccacttag gcttcacgctggctactg

acgttactcccaccttccc

aggaggaggagaggagacag atcaaccaccatgtgtactatc tacaacacgtacacgcctg ggttgtaatggaggtgaactc

gcgtggttgagtcagtgtg gacgatcaaggcggaaataaag cggtactcgaaacggagag atgatgacgacgatgaagaag gaggaccaacaagtgcgac ttgtcgtcgtcgtggtaac c tgtagcgagatccacaatgc ctgctgctcctgctctacc

gacggacggagaaggcag acctgacctgaccacctgag cagaatcacgagcacaagtc tgcgggagtcaatcggatg gcggcttatgatgatgatgatg accgaaagtggagatggatcag tgaccatttacactgcgtttcc attgtcacgcactataggttc gactgtccacttgacttcattc

gtggagaggaggaatgagagg catgattcacggctaacacg accacagtccacccgtttc aacattggcacaggcatacg gaggctcttgttgacaggttg gcactacaagtatgtggatacc ggacgtacagaatttgcgaatc cctcaatgtttgctaccttgc

gagaagaagaagaggaggaagg acctgtcgtacctgccaatc gtttggattggtttgtagtgag

ggtgaagatgctgtgcttgg aattagccactctgtttgtctg atatggcaaggttggatcagtc gatacaccaacaccacatcttg tatctgttgctggcattctgag tctttattgattgattggtgcg cgcttcaacgactttatgcttg atccattgtacatgtcatctgc ggaggaggacgaccgaatc gcaggtactcgtcatcaag

cgacgacgtgtggagtagg c ttggtggatatggatgatgag

1781249 1791197 1731161 169J150 1801168 1511135 1231135 1711155 2 1 01 I 79 1581149 1691208 1551238 1.581219 1491177 1651138 1681433 17911 5 1 1171158 1531206 1521476 1751995 1511113 180J222 1461171 13511 74 2861254 1801147 1791208 144180 1461 1 76 1361173 1501188 1541370 160198 139199 12511 68 162J191 1 6 1 I277 1671206 1741223 17 1 121 0 18011 14 1641114 13511 05 15 11193

8 3 8 2 3 9 4

9 1 1 12 3 1 4 6 12 11 8 5 5 2 3 3 7 6 3 4 11 11

8 5 6 10 12 6 4 7 12 6 5 10 5 7 5 1

- _ _ - aataccttgagttggagtctgg 1741226 11

Page 6: Construction of a Microsatellite Linkage Map with Two Sequenced Rice Varieties

ZHANG Qi-Jun et a/.: Construction of a Microsatellite Linkage Map with Two Sequenced Rice Varieties 157

93 1 1 is a classical indica variety while Nipponbare is a classical japonica variety. Second, the RM# marker selection in this research was random whereas RP# markers in this research and microsatillites in L-map selection were not. Third, the seperation methods were also different. In L-map, PCR products were seperated by 4% polyacrylamide denaturing gels (PAG) and marker bands were revealed by the silver staining protocol. However, in this research, PCR products were seperated by 3% agarose gels and marker bands were revealed by the EtBr staining method. Apparently, the resolution power and the polymorphism detection of 4% PAG is higher than those of 3% agarose gels.

3 Discussion

Microsatellites are tandemly arranged repeats of short DNA motifs (1-6 bp in length) that frequently exhibit variation in the number of repeats at a locus. Because of their abundance and inherent potential for variation, these SSRs have become a valuable source of genetic markers ‘ I 3 ’ . There are many advantages in using SSR markers to construct linkage map for the molecular marker-assistant selection breeding over other molecular markers Most of the SSR markers, like RFLP markers, are co-dominant, which can be used to distinguish the hybrids. Compared to RFLP markers, however, SSR marker is easy to han- dle, avoiding restriction enzyme incision and hy- bridization procedures, and just general PCR steps are needed “8,251.

Along with the accomplishment of rice genomic sequence project and the application of a series of marker selecting software, the numbers of markers have been greatly enriched. For example, McCouch et d.“” constructed a SSR linkage map including 2 740 mark- ers with the method of electronic polymerase chain reaction (e-PCR) based on the data of RGP. There are about 3 000 pairs of SSR primers identified on the network at present. In our laboratory, about 14 000 pairs of SSR primers were filtered out using the SSR primers filtering software, which had polymorphisms between Nipponbare and 93 1 1. With these SSR

primers, the average genetic distance between two markers is about 0.05 cM (corresponding to 10 kb genomic DNA length). This can provide a good foundation for a saturation genetic linkage map of rice, even for a regional physical map, and it is also suitable for gene mapping and cloning. Moreover, in our research, part of RP# markers were integrated into the linkage map, indicating that our SSR primer filtering software was correct.

The usefulness of genetic maps largely depends on their density. For a genetic map, if the loci of markers are adequately dense and their distribution is correspondingly even, its applicable value will be high. In this research randomly chosen 166 SSR primers were used and 152 loci were anchored. Compared with the T-map, there were 9 markers anchored on different linkage groups in this map.Supposedly, the reasons are a5 follows: First, it is related to the different parent, type and size of the population, because same microsatellite motif may have different sites in different rice varieties ‘ I 3 ] ; Second, microsatellites are asymmetrically distributed in genome , and when analyzing data, the software of MAPMAKEREXP 3.0 itself has some errors Third, in this map only SSR markers were used, but in T-map there were additional 145 RFLP markers. All these factors may affect the linkage genetic distance among markers. Therefore, we are now continuing to further saturate the linkage map, increasing the lines of population and adding the numbers of markers.

There are many advantages of using sequenced rice varieties to construct a genetic map, as they are mainly representing the trait analysis combined with the genetic map. It maybe a convenient, fast and high efficient way to locate, clone and functionally remark plant genes (specially the quantitative trait genes) based on existing genomic sequenced data”’], and there are some successful examples of QTL cloning

. In particular, there is no need to construct high density genetic map when only one QTL was detected within an interval. Compared with some functionally known genes and their interval bioinformative analysis, itis relatively easy to get the canditate gene, then to validate the function of canditate gene by

[ 16- IS]

126.321

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158 B{$y% Acta Genetica Sinica Vo1.33 No.2 2006

co-complementary testing, and finally to clone this QTL [''I. According to the above-mentioned approach in one QTL detection, different traits controlled by varied QTL intervals can be revealed, and we may achieve a higher efficiency. In our research, an attempt following this method was also made and resulted in some significant outcomes (will be reported by other papers).

Another function of using sequenced rice varieties to construct linkage map and analyze QTLs is that some unknown functional genomic regions could be noted. Analyzing the QTL mapping complexion on the network of Gramene, it was easy to find that the existing natural mutating genes were not included in the mapped QTL intervals. In other words, it may be a fast and highly efficient way to remark some function of unknown genes using sequenced rice varieties to construct linkage map and analyze QTLs ['l]. Most of the crop traits are quanti- tative in nature, which are controlled by polygene, so it is very important for crop improvement to map QTLs. We may lose sight of some other contributing genes, especially the micro-effect genes, because the traditional genetic dissection of genes is mainly aimed at the quality trait genes. After finding one trait controlled by one or more chromosome intervals, we can analyze these chromosome intervals with the database of sequenced rice varieties, and may remark some annotations on these chromosome intervals combining the related function-known genes of this kind of trait [''I.

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