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Construction of Genetic Linkage Map Based on SSR Markers in Peanut (Arachis hypogaea L.)
Agricultural Sciences in China
August 2008
2008, 7(8): 915-921
Construction of Genetic Linkage Map Based on SSR Markers in Peanut (Arachis hypogaea L.) HONG Yan-bin, LIANG Xuan-qiang, CHEN Xiao-ping, LIU Hai-yan, ZHOU Gui-yuan, LI Shao-xiong and WEN Shi-jie Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, P.R.China
Abstract Molecular genetic maps of crop species can be used in a variety of ways in breeding and genomic research such as identification and mapping of genes and quantitative trait loci (QTLs) for morphological, physiological and economic traits of crop species. However, a comprehensive genetic linkage map for cultivated peanut has not yet been developed due to the extremely low frequency of DNA polymorphism in cultivated peanut. In this study, 142 recombinant inbred lines (RILs) derived from a cross between Yueyou 13 and Zhenzhuhei were used as mapping population in peanut (Arachis hypogaea L.). A total 652 pairs of genomic-SSR primer and 392 pairs of EST-SSR primer were used to detect the polymorphisms between the two parents. 141 SSR primer pairs, 127 genomic-SSR and 14 EST-SSR ones, which can be used to detect polymorphisms between the two parents, were selected to analyze the RILs population. Thus, a linkage genetic map which consists of 131 SSR loci in 20 linkage groups, with a coverage of 679 cM and an average of 6.12 cM of inter-maker distance was constructed. The putative functions of 12 EST-SSR markers located on the map were analyzed. Eleven showed homology to gene sequences deposited in GenBank. This is the first report of construction of a comprehensive genetic map with SSR markers in peanut (Arachis hypogaea L.). The map presented here will provide a genetic framework for mapping the qualitative and quantitative trait in peanut. Key words: peanut (Arachis hypogaea L.), SSR, genetic linkage map
INTRODUCTION Cultivated peanut (Arachis hypogaea L.) is an important economic crop, being grown on 25.5 million hectares with a total global production of about 35 million tons and thus ranking among the top five oilseed crops in the world. Developing molecular maps for peanut is critical for identifying linkage relationships, since its complex genome structure is not well understood and defined. Furthermore a comprehensive molecular map for peanut genome is essential for the comparative mapping using the ge-
nomic information from other model legumes, and should be valuable to utilize the genetic resources within the cultivated peanuts and related species. In contrast to the multiple morphological variations being observed among different accessions of cultivated peanut, extremely low levels of molecular polymorphism were observed between different genotypes (Kochert et al. 1991; Subramanian et al. 2000; Milla et al. 2005). Even efforts have been made in several research groups (Herselman et al. 2004), a desirable genetic linkage map is still not available for the cultivated peanut. However, recent reports showed that SSR can detect more polymorphism in peanut than RFLP, RAPD, and AFLP (Ferguson et al. 2004), indicating that
Received 22 April, 2008 Accepted 1 July, 2008 HONG Yan-bin, Master, Tel: +86-20-87511794, E-mail: [email protected]; Correspondence LIANG Xuan-qiang, Tel: +86-20-87597315, E-mail: [email protected]
© 2008, CAAS. All rights reserved. Published by Elsevier Ltd.
916
SSR markers have great potential for genetic studies of the cultivated peanut (Jiang et al. 2007). In this study, a linkage map containing 131 SSR loci in 20 linkage groups has been developed by using genomic-SSRs and ESTSSRs. This is the first genetic linkage map which consisted of 20 linkage groups in cultivated peanut. It would be a milestone of peanut genetic improvement by molecular approaches.
MATERIALS AND METHODS Mapping population Yueyou 13, an accession of Spanish type with its characteristic of high yield, was crossed with Zhenzhuhei, an accession of Virginia type with its characteristic of darker purple testa and high content of protein in the kernel, so as to generate an F6 RILs population, which consists of 142 lines which were derived by single seed descent. The RILs population has been maintained in the Crops Research Institute, Guangdong Academy of Agricultural Sciences, China.
DNA extraction Total genomic DNA was extracted from young leaves using the protocol described by Grattapaglia and Sederoff (1994), which was modified by an additional precipitation step. Based on agarose gel electrophoresis DNA concentration was estimated by comparing the fluorescence intensities of the ethidium bromide stained samples to those of ODNA standards.
SSR markers analysis 290 new EST-SSR markers developed in our lab, plus 754 SSR markers developed by other institutions (Hopkins et al. 1999; Palmieri et al. 2002, 2005; He et al. 2003; Ferguson et al. 2004; Moretzsohn et al. 2004,2005; Martins et al. 2006), were used for polymorphism analysis. Among them, 652 SSR markers were derived from genomic DNA and 392 from cDNA. All primer pairs were first screened for their polymorphism between the parents of mapping population. The selected polymorphic markers were then used to genotype the individuals of mapping
HONG Yan-bin et al.
population. PCR reactions were conducted with 25 ng of template DNA, 5 pmol of each primer, 10 × of Taq polymerase buffer [500 mM KCl, 100 mM Tris-HCI (pH 8.5), and 1 mg mL-1 gelatin], 1.0 mM of MgCl2, 0.5 mM of dNTPs and 0.25 U of Taq polymerase in total volume of 12.5 L. PCR was performed in 96well plates in PTC-200 thermocyclers (MJ Research, Watertown, Mass), using the following profile: 95°C for 10 min, 30 cycles of 1 min at 95°C, 1 min at 55°C and 1 min at 72°C, and a final extension step of 10 min at 72°C. The PCR products were analyzed by running on 6% non-denaturing polyacrilamide gel (PAGE) and electrophoresed in 1×TBE at 150 V for 1 h using DYCZ30b gel rig (Beijing Liuyi, China). Then the amplified products were visualized using silver staining method.
Map construction Linkage analysis was performed with JoinMap 3.0 (van Oojen and Voorips 2001). The “Locus genotype frequency” function was applied to calculate chi-square values for each marker to test for expected 1:1 segregation. Markers were placed into linkage groups with the “LOD groupings” and “Create groups for mapping” command using the Kosmabi map function (Kosmabi 1994). Calculation parameters were set for a minimum LOD threshold of 3.0, and recombination fraction of 0.45. Markers order in groups was established by “Calculate Map” command. The map presented was drawn using MapChart for Windows (Voorips 2002).
Functional annotation of EST sequences The ESTs containing polymorphic SSRs were searched against the GenBank non-redundant (nr) database using the BLAST algorithm (http://www.ncbi.nlm.nih.gov/ BLAST). The putative functions of ESTs were inferred from sequences of strongest homology (lowest E-value).
RESULTS Polymorphism of SSR markers A total 1 044 SSR primer pairs were screened against the parents, Yueyou 13 and Zhenzhuhei. Among them,
© 2008, CAAS. All rights reserved. Published by Elsevier Ltd.
Construction of Genetic Linkage Map Based on SSR Markers in Peanut (Arachis hypogaea L.)
919
Table 2 Functional annotation of 12 EST-SSR markers located on the linkage map by tBLASTx Marker EM-42 EM-88 RN9C02 gi-832 ML1G04 RI1F06 RN0x615 EM-87 RN17B08 RI2A06 EM-90 EM-30
Repeat region 3´UTR 3´UTR Coding 5´UTR Coding 5´UTR 3´UTR 5´UTR Coding Coding Coding 3´UTR
region region
region region region
E-value
Accession no.
2.00E-47 1.00E-19 5.00E-59 1.00E-84 2.00E-34 2.00E-10 9.10E + 00 2.00E-25 3.00E-50
AAK64025 AAZ20291 AAQ84167 BAD11657 AAN15510 CAN84007 XP_425714 ABO79334 CAN70485
2.00E-102 3.00E-07
CAB71135 NP_565167
signed putative function on the map and their highly transferable nature, the roles of the genes with which they are physically associated can be studied in both the diploid and tetaploid genetic backgrounds. In this way, they will provide valuable tools for a candidate gene approach to elucidate the underlying mechanisms of important morphological and physiological traits within Arachis.
DISCUSSION Segregation distortion Segregation distortion has been reported in many plants including rice, wheat, barley, and maize. Explanations for distortion of segregation ratios in plants have been put forth, including such factors as chromosome loss (Kasha and Kao 1970), genetic isolation mechanisms (Zamir and Tadmor 1986), and the presence of viability genes (Bradshaw and Stettler 1994). Nonbiological factors such as scoring errors (Nikaido et al. 1999) and sampling errors (Echt and Nelson 1997) can also lead to distortion in segregation ratios. The proportions of distorted markers found in this study (22.3%) are lower than the 25% found for the two RFLP-based maps and much lower than the 51% in the SSR-based map of Arachis (Halward et al. 1993; Burow et al. 2001; Moretzsohn et al. 2005). This is consistent with the reports in other plants that the levels of segregation distortion were usually higher in inter-specific crosses when compared to intra-specific crosses (Myburg et al. 2003). Generally, large differences in genotypes between species can cause hybrid incompatibility and induce high distortion proportion.
Function
Organism
Putative dihydroxyacid dehydratase Metallothionein-like protein Isopentenyl pyrophosphate isomerase Coated vesicle membrane protein-like Expressed protein Hypothetical protein Similar to Foxc1 protein NAD-binding site Hypothetical protein No hits found Putative imbibition protein Senescence-associated protein-related
Arabidopsis thaliana Arabidopsis thaliana Pueraria montana var. lobata Oryza sativa Arabidopsis thaliana Vitis vinifera Gallus gallus Medicago truncatula Vitis vinifera Cicer arietinum Arabidopsis thaliana
Map construction In this work, construction of the first comprehensive genetic map with SSR markers in Arachis hypogaea L. is reported. The map presented here will provide a genetic framework for mapping the qualitative and quantitative trait in peanut. In this map, markers distribution on the linkage groups was not uniform. Four linkage groups contained more than 10 markers and seven contained 5 to 10 markers, whereas the remaining nine linkage groups contained only 2 or 3 markers. Some of the small linkage groups could be possibly derived from the same chromosome with other linkage groups for the less density of the map. The genetic map distance (679 cM) was much shorter than the one of the synthetic tetraploid map with RFLP markers (map distance = 2 210 cM) (Burow et al. 2001), also shorter than that of the AA genome map with RFLP (1 063 cM) (Halward et al. 1993) and the SSR genetic map of AA genome in Arachis (1230.89 cM) (Moretzsohn et al. 2005). There were several factors that could account for the reduced length of the map in Arachis hypogaea L. The first factor could be that the markers on the map were far from saturated. 131 SSR loci distributed on the map were much fewer than the synthetic tetraploid map which consists of 370 RFLP markers. The second factor could be the different mapping software used in linkage analysis. In general, maps constructed with JoinMap were shorter than those constructed with a multilocus-likelihood package such as Mapmaker or OUTMAP (Sewell et al. 1999; Butcher et al. 2001; Gosselin et al. 2002). In this study, the map was also constructed from Mapmaker (data not shown). The result also showed that the map constructed with JoinMap was shorter than constructed with Mapmaker.
© 2008, CAAS. All rights reserved. Published by Elsevier Ltd.
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The multilocus-likelihood method used by Mapmaker assumes an absence of crossover interference; so when interference is present, JoinMap correctly produces shorter maps, even though both programs use the Kosambi mapping function (Stam 1993). This difference was also observed in barley and was attributed to how each program calculated map distance when the actual interference differed from that assumed (Qi et al. 1996).
HONG Yan-bin et al.
source of SSR-containing sequences that may be easily and inexpensively exploited. However, even in species with large EST collections, relatively few informative SSR loci are likely to result from this source.
Acknowledgements This research was partially funded by a grant from the National Natural Science Foundation of China (30571179), and National 863 Program of China (2006AA0Z156, 2006AA10A115).
Low polymorphism of EST-SSR References In this study, only 4.3% of EST-SSRs produced useful polymorphic markers in the mapping population. In contrast, when genomic DNA sequences were used as the source of SSR-containing sequences, 23.1% yielded markers were polymorphic. The striking difference of polymorphism between peanut SSRs derived from two sources is consistent with the differences reported in rice (Cho et al. 2000), sugarcane (Cordeiro et al. 2001), tomato (Areshchenkova and Ganal 2002), wheat (Nicot et al. 2004), and barley (Thiel et al. 2003). Generally, markers derived from genomic libraries contained more repeat units as well as a greater range of allele sizes and genetic diversity than markers isolated from EST libraries. For example, Arshchenkova and Ganal (2002) reported that only 20 of 27 000 tomato ESTs contained microsatellites of more than ten repeat units. EST-derived microsatellites were shorter (7.3 repeat units) than genomic DNA-derived microsatellites (22.7 repeat units) in barley (Ramsay et al. 2000). The average number of repeats from EST-derived and genomic DNA-derived SSRs was 6.1 versus 13.7 in sugarcane (Cordeiro et al. 2001). The expansion or contraction of di-nucleotide repeat length in exons may likely be suppressed due to the deleterious nature of the frame-shift mutation that would frequently result in translated regions. Microsatellite markers derived from small repeat arrays in genes were reported to be significantly less polymorphic than markers generated from longer arrays (Smulders et al. 1997). Other factors such as selection against large alterations in coding DNA or even a closely associated sequence that may play a role in gene expression could constrain microsatellite expansion or contraction. Such constraints could contribute to the reduced polymorphism of microsatellites in ESTs. Obviously, EST-sequence data provide a convenient
Areshchenkova T, Ganal M W. 2002. Comparative analysis of polymorphism and chromosomal location of tomato microsatellite markers isolated from different sources. Theoretical and Applied Genetics, 104, 229-235. Bradshaw H D, Stettler R F. 1994. Molecular genetics of growth and development in Populus. II. Segregation distortion due to genetics load. Theoretical and Applied Genetics, 89, 551558. Burow M D, Simpson C E, Starr J L, Paterson A H. 2001. Transmission genetics of chromatin from a synthetic amphidiploids to cultivated peanut (Arachis hypogaea L.): broadening the gene pool of a monophyletic polyploid species. Genetics, 159, 823-837. Butcher P A, Williams E R, Whitaker D, Kiene K L, Temesgen B. 2001. Improving linkage analysis in outcrossed forest treesan example from Acacia mangium. Theoretical and Applied Genetics, 104, 1185-1191. Cho Y G, Ishii T, Temnykh S, Chen X, Lipovich L, McCouch S R, Park W D, Ayres N, Cartinhour S. 2000. Diversity of microsatellites derived from genomic libraries and GenBank sequences in rice (Oryza Sativa L.). Theoretical and Applied Genetics, 100, 713-722. Cordeiro G M, Casu R, McIntyre C L, Manners J M, Henry R J. 2001. Microsatellite markers from sugarcane (Saccharum spp.) ESTs cross transferable to erianthus and sorghum. Plant Sciences, 160, 1115-1123. Echt C S, Nelson C D. 1997. Linkage mapping and genome length in eastern white pine (Pinus strobes L.). Theoretical and Applied Genetics, 94, 1031-1037. Ferguson M E, Burow M D, Schulze S R, Bramel P J, Paterson A H, Kresovich S, Mitchell S. 2004. Microsatellite identification and characterization in peanut (A. hypogaea L.). Theoretical and Applied Genetics, 108, 1064-1070. Gosselin I, Zhou Y, Bousquet J, Isabel N. 2002. Megagametophyte-derived linkage maps of white spruce (Picea glauca) based on RAPD, SCAR and ESTP markers. Theoretical and Applied Genetics, 104, 987-997. Grattapaglia D, Sederoff R. 1994. Genetic linkage maps of Eucalyptus grandis and Eucalyptus urophylla using a pseudotestcross: Mapping strategy and RAPD markers. Genetics, 137, 1121-1137.
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Construction of Genetic Linkage Map Based on SSR Markers in Peanut (Arachis hypogaea L.)
Guo B Z, Chen X P, Dang P, Scully B T, Liang X Q, Holbrook C C, Yu J J, Culbreath A K. 2008. Peanut gene expression profiling in developing seeds at different reproduction stages during Aspergillus parasiticus infection. BMC Developmental Biology, 8, 1-16. Halward T M, Stalker H T, Kochert G. 1993. Development of an RFLP linkage map in diploid peanut species. Theoretical and Applied Genetics, 87, 379-384. He G, Meng R, Newman M, Gao G, Pittman R N, Prakash C S. 2003. Microsatellites as DNA markers in cultivated peanut (A. hypogaea L.). BMC Plant Biology, 3, 3. Herselman L, Thwaites R, Kimmins F M, Courtois B, van der Merwe P J, Seal S E. 2004. Identification and mapping of AFLP markers linked to peanut (Arachis hypogaea L.) resistance to the aphid vector of groundnut rosette disease. Theoretical and Applied Genetics, 109, 1426-1433. Hopkins M S, Casa A M, Wang T, Mitchell S E, Dean R E, Kochert G D, Kresovich S. 1999. Discovery and characterization of polymorphic simple sequence repeats (SSRs) in peanut. Crop Science, 39, 1243-1247. Jiang H F, Chen B Y, Ren X P, Liao B S, Lei Y, Fu T D, Ma C Z, Mace E, Crouch J H. 2007. Identification of SSR markers linked to bacterial wilt resistance of peanut with RILs. Chinese Journal of Oil Crop Sciences, 29, 26-30. (in Chinese) Kasha K J, Kao K N. 1970. High frequency haploid production in barley (Hordeum vulgare L.). Nature, 225, 874-876. Kochert G, Halward T, Branch W D, Simpson C E. 1991. RFLP variability in peanut (Arachis hypogaea L.) cultivars and wild species. Theoretical and Applied Genetics, 81, 565-570. Kosmabi D D. 1994. The estimation of map distance from recombination values. Annals of Eugenetics, 12, 172-175. Martins W, Sousa D D, Proite K, Guinaraes P, Moretzsohn M, Bertioli D. 2006. New softwares for automated microsatellite marker development. Nucleic Acids Research, 34, 1-4. Milla S R, Isleib T G, Stalker H T. 2005. Taxonomic relationships among Arachis sect. Arachis species as revealed by AFLP markers. Genome, 8, 1-11. Moretzsohn M C, Hopkins M S, Mitchell S E, Kresovich S, Valls J F, Ferreira M E. 2004. Genetic diversity of peanut (Arachis hypogaea L.) and its wild relatives based on the analysis of hypervariable regions of the genome. BMC Plant Biology, 4, 11. Moretzsohn M C, Leoi L, Proite K, Guimaras P M, Leal-Bertioli S C M, Gimenes M A, Martins W S, Valls J F M, Grattapaglia D, Bertioli D J. 2005. A microsatellite-based, gene-rich linkage map for the AA genome of Arachis (Fabaceae). Theoretical and Applied Genetics, 111, 1060-1071. Myburg A A, Griffin A R, Sederoff R R, Whetten R W. 2003. Comparative genetic linkage maps of Eucalyptus grandis, Eucalyptus globules and their F1 hybrid based on a double pseudo-backcross mapping approach. Theoretical and Applied Genetics, 107, 1028-1042. Nicot N, Chiquet V, Gandon B, Amilhat L, Legeai F, Leroy P, Bernard M, Sourdille P. 2004. Study of simple sequence repeat (SSR) markers from wheat expressed sequences tags
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(ESTs). Theoretical and Applied Genetics, 109, 800-805. Nikaido A, Yoshimaru H, Tsumura Y, Suyama Y, Murai M. 1999. Segregation distortion of AFLP markers in Cryptomeria japonica. Genes & Genetic System, 74, 55-59. van Oojen J W, Voorips R E. 2001. JoinMap 3.0, Software for the calculation of genetic linkage maps. Plant Research International, Wageningen, The Netherlands. Palmieri D A, Hoshino A A, Bravo J P, Lopes C R, Gimenes M A. 2002. Isolation and characterization of microsatellite loci from the forage species Arachis Pintoi (Genus Arachis). Molecular Ecology Notes, 2, 551-553. Palmieri D A, Bechara M D, Curi R A, Gimenes M A, Lopes C R. 2005. Novel polymorphic microsatellite markers in section Caulorrhizae (Arachis, Fabaceae). Molecular Ecology Notes, 5, 77-79. Qi X, Stam P, Lindhout P. 1996. Comparison and integration of four barley genetic maps. Genome, 39, 379-394. Ramsay L, Macaulay M, Ivanissivich S, MacLean K, Cardle L, Fuller J, Edwards K, Tuvesson S, Morgante M, Massari A, Maestri E, Marniorlin N, Sjakste T, Ganal M, Powell W, Powell W, Waugh R. 2000. A simple sequence repeat-based linkage map of barley. Genetics, 156, 1997-2005. Sewell M M, Sherman B K, Neale D B. 1999. A consensus map for loblolly (Pinus taeda L.). I. Construction and intergration of individual linkage maps from two outbred three-generation pedigree. Genetics, 151, 321-330. Smulders M J M, Bredemeijer G, Rus-Kortekaas W, Arens P, Vosman B. 1997. Use of short microsatellites from database sequences to generate polymorphisms among Lycopersicon esculentum cultivars and accessions of other Lycopersicon species. Theoretical and Applied Genetics, 94, 264-272. Stam P. 1993. Construction of integrated genetic linkage maps by means of a new computer package JoinMap. The Plant Journal, 3, 739-744. Subramanian V, Gurtu S, Rao R C N, Nigam S N. 2000. Identification of DNA polymorphism in cultivated groundnut using random amplified polymorphic DNA (RAPD) assay. Genome, 43, 656-660. Thiel T, Michalek W, Varshney R K, Graner A. 2003. Exploiting EST databases for the development and characterization of gene-derived SSR-markers in barley (Hordeum vulgare L.). Theoretical and Applied Genetics, 106, 411-422. Tian A G, Wang J, Cui P, Han Y J, Xu H, Cong L J, Huang X G, Wang X L, Jiao Y Z, Wang B J, Wang Y J, Zhang J S, Chen S Y. 2004. Characterization of soybean genomic features by analysis of its expressed sequence tags. Theoretical and Applied Genetics, 108, 903-913. Varshney R K, Graner A, Sorrells M E. 2005. Genetic microsatellite markers in plants: features and applications. Trends in Biotechnology, 23, 48-55. Voorips R E. 2002. Mapchart: software for the graphical presentation of linkage maps and QTLs. Journal of Heredity, 93, 77-78. Zamir D, Tadmor Y. 1986. Unequal segregation of nuclear genes in plants. Botanical Gazette, 147, 355-358. (Edited by ZHAO Qi)
© 2008, CAAS. All rights reserved. Published by Elsevier Ltd.
August 2008
2008, 7(8): 915-921
Construction of Genetic Linkage Map Based on SSR Markers in Peanut (Arachis hypogaea L.) HONG Yan-bin, LIANG Xuan-qiang, CHEN Xiao-ping, LIU Hai-yan, ZHOU Gui-yuan, LI Shao-xiong and WEN Shi-jie Crops Research Institute, Guangdong Academy of Agricultural Sciences, Guangzhou 510640, P.R.China
Abstract Molecular genetic maps of crop species can be used in a variety of ways in breeding and genomic research such as identification and mapping of genes and quantitative trait loci (QTLs) for morphological, physiological and economic traits of crop species. However, a comprehensive genetic linkage map for cultivated peanut has not yet been developed due to the extremely low frequency of DNA polymorphism in cultivated peanut. In this study, 142 recombinant inbred lines (RILs) derived from a cross between Yueyou 13 and Zhenzhuhei were used as mapping population in peanut (Arachis hypogaea L.). A total 652 pairs of genomic-SSR primer and 392 pairs of EST-SSR primer were used to detect the polymorphisms between the two parents. 141 SSR primer pairs, 127 genomic-SSR and 14 EST-SSR ones, which can be used to detect polymorphisms between the two parents, were selected to analyze the RILs population. Thus, a linkage genetic map which consists of 131 SSR loci in 20 linkage groups, with a coverage of 679 cM and an average of 6.12 cM of inter-maker distance was constructed. The putative functions of 12 EST-SSR markers located on the map were analyzed. Eleven showed homology to gene sequences deposited in GenBank. This is the first report of construction of a comprehensive genetic map with SSR markers in peanut (Arachis hypogaea L.). The map presented here will provide a genetic framework for mapping the qualitative and quantitative trait in peanut. Key words: peanut (Arachis hypogaea L.), SSR, genetic linkage map
INTRODUCTION Cultivated peanut (Arachis hypogaea L.) is an important economic crop, being grown on 25.5 million hectares with a total global production of about 35 million tons and thus ranking among the top five oilseed crops in the world. Developing molecular maps for peanut is critical for identifying linkage relationships, since its complex genome structure is not well understood and defined. Furthermore a comprehensive molecular map for peanut genome is essential for the comparative mapping using the ge-
nomic information from other model legumes, and should be valuable to utilize the genetic resources within the cultivated peanuts and related species. In contrast to the multiple morphological variations being observed among different accessions of cultivated peanut, extremely low levels of molecular polymorphism were observed between different genotypes (Kochert et al. 1991; Subramanian et al. 2000; Milla et al. 2005). Even efforts have been made in several research groups (Herselman et al. 2004), a desirable genetic linkage map is still not available for the cultivated peanut. However, recent reports showed that SSR can detect more polymorphism in peanut than RFLP, RAPD, and AFLP (Ferguson et al. 2004), indicating that
Received 22 April, 2008 Accepted 1 July, 2008 HONG Yan-bin, Master, Tel: +86-20-87511794, E-mail: [email protected]; Correspondence LIANG Xuan-qiang, Tel: +86-20-87597315, E-mail: [email protected]
© 2008, CAAS. All rights reserved. Published by Elsevier Ltd.
916
SSR markers have great potential for genetic studies of the cultivated peanut (Jiang et al. 2007). In this study, a linkage map containing 131 SSR loci in 20 linkage groups has been developed by using genomic-SSRs and ESTSSRs. This is the first genetic linkage map which consisted of 20 linkage groups in cultivated peanut. It would be a milestone of peanut genetic improvement by molecular approaches.
MATERIALS AND METHODS Mapping population Yueyou 13, an accession of Spanish type with its characteristic of high yield, was crossed with Zhenzhuhei, an accession of Virginia type with its characteristic of darker purple testa and high content of protein in the kernel, so as to generate an F6 RILs population, which consists of 142 lines which were derived by single seed descent. The RILs population has been maintained in the Crops Research Institute, Guangdong Academy of Agricultural Sciences, China.
DNA extraction Total genomic DNA was extracted from young leaves using the protocol described by Grattapaglia and Sederoff (1994), which was modified by an additional precipitation step. Based on agarose gel electrophoresis DNA concentration was estimated by comparing the fluorescence intensities of the ethidium bromide stained samples to those of ODNA standards.
SSR markers analysis 290 new EST-SSR markers developed in our lab, plus 754 SSR markers developed by other institutions (Hopkins et al. 1999; Palmieri et al. 2002, 2005; He et al. 2003; Ferguson et al. 2004; Moretzsohn et al. 2004,2005; Martins et al. 2006), were used for polymorphism analysis. Among them, 652 SSR markers were derived from genomic DNA and 392 from cDNA. All primer pairs were first screened for their polymorphism between the parents of mapping population. The selected polymorphic markers were then used to genotype the individuals of mapping
HONG Yan-bin et al.
population. PCR reactions were conducted with 25 ng of template DNA, 5 pmol of each primer, 10 × of Taq polymerase buffer [500 mM KCl, 100 mM Tris-HCI (pH 8.5), and 1 mg mL-1 gelatin], 1.0 mM of MgCl2, 0.5 mM of dNTPs and 0.25 U of Taq polymerase in total volume of 12.5 L. PCR was performed in 96well plates in PTC-200 thermocyclers (MJ Research, Watertown, Mass), using the following profile: 95°C for 10 min, 30 cycles of 1 min at 95°C, 1 min at 55°C and 1 min at 72°C, and a final extension step of 10 min at 72°C. The PCR products were analyzed by running on 6% non-denaturing polyacrilamide gel (PAGE) and electrophoresed in 1×TBE at 150 V for 1 h using DYCZ30b gel rig (Beijing Liuyi, China). Then the amplified products were visualized using silver staining method.
Map construction Linkage analysis was performed with JoinMap 3.0 (van Oojen and Voorips 2001). The “Locus genotype frequency” function was applied to calculate chi-square values for each marker to test for expected 1:1 segregation. Markers were placed into linkage groups with the “LOD groupings” and “Create groups for mapping” command using the Kosmabi map function (Kosmabi 1994). Calculation parameters were set for a minimum LOD threshold of 3.0, and recombination fraction of 0.45. Markers order in groups was established by “Calculate Map” command. The map presented was drawn using MapChart for Windows (Voorips 2002).
Functional annotation of EST sequences The ESTs containing polymorphic SSRs were searched against the GenBank non-redundant (nr) database using the BLAST algorithm (http://www.ncbi.nlm.nih.gov/ BLAST). The putative functions of ESTs were inferred from sequences of strongest homology (lowest E-value).
RESULTS Polymorphism of SSR markers A total 1 044 SSR primer pairs were screened against the parents, Yueyou 13 and Zhenzhuhei. Among them,
© 2008, CAAS. All rights reserved. Published by Elsevier Ltd.
Construction of Genetic Linkage Map Based on SSR Markers in Peanut (Arachis hypogaea L.)
919
Table 2 Functional annotation of 12 EST-SSR markers located on the linkage map by tBLASTx Marker EM-42 EM-88 RN9C02 gi-832 ML1G04 RI1F06 RN0x615 EM-87 RN17B08 RI2A06 EM-90 EM-30
Repeat region 3´UTR 3´UTR Coding 5´UTR Coding 5´UTR 3´UTR 5´UTR Coding Coding Coding 3´UTR
region region
region region region
E-value
Accession no.
2.00E-47 1.00E-19 5.00E-59 1.00E-84 2.00E-34 2.00E-10 9.10E + 00 2.00E-25 3.00E-50
AAK64025 AAZ20291 AAQ84167 BAD11657 AAN15510 CAN84007 XP_425714 ABO79334 CAN70485
2.00E-102 3.00E-07
CAB71135 NP_565167
signed putative function on the map and their highly transferable nature, the roles of the genes with which they are physically associated can be studied in both the diploid and tetaploid genetic backgrounds. In this way, they will provide valuable tools for a candidate gene approach to elucidate the underlying mechanisms of important morphological and physiological traits within Arachis.
DISCUSSION Segregation distortion Segregation distortion has been reported in many plants including rice, wheat, barley, and maize. Explanations for distortion of segregation ratios in plants have been put forth, including such factors as chromosome loss (Kasha and Kao 1970), genetic isolation mechanisms (Zamir and Tadmor 1986), and the presence of viability genes (Bradshaw and Stettler 1994). Nonbiological factors such as scoring errors (Nikaido et al. 1999) and sampling errors (Echt and Nelson 1997) can also lead to distortion in segregation ratios. The proportions of distorted markers found in this study (22.3%) are lower than the 25% found for the two RFLP-based maps and much lower than the 51% in the SSR-based map of Arachis (Halward et al. 1993; Burow et al. 2001; Moretzsohn et al. 2005). This is consistent with the reports in other plants that the levels of segregation distortion were usually higher in inter-specific crosses when compared to intra-specific crosses (Myburg et al. 2003). Generally, large differences in genotypes between species can cause hybrid incompatibility and induce high distortion proportion.
Function
Organism
Putative dihydroxyacid dehydratase Metallothionein-like protein Isopentenyl pyrophosphate isomerase Coated vesicle membrane protein-like Expressed protein Hypothetical protein Similar to Foxc1 protein NAD-binding site Hypothetical protein No hits found Putative imbibition protein Senescence-associated protein-related
Arabidopsis thaliana Arabidopsis thaliana Pueraria montana var. lobata Oryza sativa Arabidopsis thaliana Vitis vinifera Gallus gallus Medicago truncatula Vitis vinifera Cicer arietinum Arabidopsis thaliana
Map construction In this work, construction of the first comprehensive genetic map with SSR markers in Arachis hypogaea L. is reported. The map presented here will provide a genetic framework for mapping the qualitative and quantitative trait in peanut. In this map, markers distribution on the linkage groups was not uniform. Four linkage groups contained more than 10 markers and seven contained 5 to 10 markers, whereas the remaining nine linkage groups contained only 2 or 3 markers. Some of the small linkage groups could be possibly derived from the same chromosome with other linkage groups for the less density of the map. The genetic map distance (679 cM) was much shorter than the one of the synthetic tetraploid map with RFLP markers (map distance = 2 210 cM) (Burow et al. 2001), also shorter than that of the AA genome map with RFLP (1 063 cM) (Halward et al. 1993) and the SSR genetic map of AA genome in Arachis (1230.89 cM) (Moretzsohn et al. 2005). There were several factors that could account for the reduced length of the map in Arachis hypogaea L. The first factor could be that the markers on the map were far from saturated. 131 SSR loci distributed on the map were much fewer than the synthetic tetraploid map which consists of 370 RFLP markers. The second factor could be the different mapping software used in linkage analysis. In general, maps constructed with JoinMap were shorter than those constructed with a multilocus-likelihood package such as Mapmaker or OUTMAP (Sewell et al. 1999; Butcher et al. 2001; Gosselin et al. 2002). In this study, the map was also constructed from Mapmaker (data not shown). The result also showed that the map constructed with JoinMap was shorter than constructed with Mapmaker.
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The multilocus-likelihood method used by Mapmaker assumes an absence of crossover interference; so when interference is present, JoinMap correctly produces shorter maps, even though both programs use the Kosambi mapping function (Stam 1993). This difference was also observed in barley and was attributed to how each program calculated map distance when the actual interference differed from that assumed (Qi et al. 1996).
HONG Yan-bin et al.
source of SSR-containing sequences that may be easily and inexpensively exploited. However, even in species with large EST collections, relatively few informative SSR loci are likely to result from this source.
Acknowledgements This research was partially funded by a grant from the National Natural Science Foundation of China (30571179), and National 863 Program of China (2006AA0Z156, 2006AA10A115).
Low polymorphism of EST-SSR References In this study, only 4.3% of EST-SSRs produced useful polymorphic markers in the mapping population. In contrast, when genomic DNA sequences were used as the source of SSR-containing sequences, 23.1% yielded markers were polymorphic. The striking difference of polymorphism between peanut SSRs derived from two sources is consistent with the differences reported in rice (Cho et al. 2000), sugarcane (Cordeiro et al. 2001), tomato (Areshchenkova and Ganal 2002), wheat (Nicot et al. 2004), and barley (Thiel et al. 2003). Generally, markers derived from genomic libraries contained more repeat units as well as a greater range of allele sizes and genetic diversity than markers isolated from EST libraries. For example, Arshchenkova and Ganal (2002) reported that only 20 of 27 000 tomato ESTs contained microsatellites of more than ten repeat units. EST-derived microsatellites were shorter (7.3 repeat units) than genomic DNA-derived microsatellites (22.7 repeat units) in barley (Ramsay et al. 2000). The average number of repeats from EST-derived and genomic DNA-derived SSRs was 6.1 versus 13.7 in sugarcane (Cordeiro et al. 2001). The expansion or contraction of di-nucleotide repeat length in exons may likely be suppressed due to the deleterious nature of the frame-shift mutation that would frequently result in translated regions. Microsatellite markers derived from small repeat arrays in genes were reported to be significantly less polymorphic than markers generated from longer arrays (Smulders et al. 1997). Other factors such as selection against large alterations in coding DNA or even a closely associated sequence that may play a role in gene expression could constrain microsatellite expansion or contraction. Such constraints could contribute to the reduced polymorphism of microsatellites in ESTs. Obviously, EST-sequence data provide a convenient
Areshchenkova T, Ganal M W. 2002. Comparative analysis of polymorphism and chromosomal location of tomato microsatellite markers isolated from different sources. Theoretical and Applied Genetics, 104, 229-235. Bradshaw H D, Stettler R F. 1994. Molecular genetics of growth and development in Populus. II. Segregation distortion due to genetics load. Theoretical and Applied Genetics, 89, 551558. Burow M D, Simpson C E, Starr J L, Paterson A H. 2001. Transmission genetics of chromatin from a synthetic amphidiploids to cultivated peanut (Arachis hypogaea L.): broadening the gene pool of a monophyletic polyploid species. Genetics, 159, 823-837. Butcher P A, Williams E R, Whitaker D, Kiene K L, Temesgen B. 2001. Improving linkage analysis in outcrossed forest treesan example from Acacia mangium. Theoretical and Applied Genetics, 104, 1185-1191. Cho Y G, Ishii T, Temnykh S, Chen X, Lipovich L, McCouch S R, Park W D, Ayres N, Cartinhour S. 2000. Diversity of microsatellites derived from genomic libraries and GenBank sequences in rice (Oryza Sativa L.). Theoretical and Applied Genetics, 100, 713-722. Cordeiro G M, Casu R, McIntyre C L, Manners J M, Henry R J. 2001. Microsatellite markers from sugarcane (Saccharum spp.) ESTs cross transferable to erianthus and sorghum. Plant Sciences, 160, 1115-1123. Echt C S, Nelson C D. 1997. Linkage mapping and genome length in eastern white pine (Pinus strobes L.). Theoretical and Applied Genetics, 94, 1031-1037. Ferguson M E, Burow M D, Schulze S R, Bramel P J, Paterson A H, Kresovich S, Mitchell S. 2004. Microsatellite identification and characterization in peanut (A. hypogaea L.). Theoretical and Applied Genetics, 108, 1064-1070. Gosselin I, Zhou Y, Bousquet J, Isabel N. 2002. Megagametophyte-derived linkage maps of white spruce (Picea glauca) based on RAPD, SCAR and ESTP markers. Theoretical and Applied Genetics, 104, 987-997. Grattapaglia D, Sederoff R. 1994. Genetic linkage maps of Eucalyptus grandis and Eucalyptus urophylla using a pseudotestcross: Mapping strategy and RAPD markers. Genetics, 137, 1121-1137.
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Construction of Genetic Linkage Map Based on SSR Markers in Peanut (Arachis hypogaea L.)
Guo B Z, Chen X P, Dang P, Scully B T, Liang X Q, Holbrook C C, Yu J J, Culbreath A K. 2008. Peanut gene expression profiling in developing seeds at different reproduction stages during Aspergillus parasiticus infection. BMC Developmental Biology, 8, 1-16. Halward T M, Stalker H T, Kochert G. 1993. Development of an RFLP linkage map in diploid peanut species. Theoretical and Applied Genetics, 87, 379-384. He G, Meng R, Newman M, Gao G, Pittman R N, Prakash C S. 2003. Microsatellites as DNA markers in cultivated peanut (A. hypogaea L.). BMC Plant Biology, 3, 3. Herselman L, Thwaites R, Kimmins F M, Courtois B, van der Merwe P J, Seal S E. 2004. Identification and mapping of AFLP markers linked to peanut (Arachis hypogaea L.) resistance to the aphid vector of groundnut rosette disease. Theoretical and Applied Genetics, 109, 1426-1433. Hopkins M S, Casa A M, Wang T, Mitchell S E, Dean R E, Kochert G D, Kresovich S. 1999. Discovery and characterization of polymorphic simple sequence repeats (SSRs) in peanut. Crop Science, 39, 1243-1247. Jiang H F, Chen B Y, Ren X P, Liao B S, Lei Y, Fu T D, Ma C Z, Mace E, Crouch J H. 2007. Identification of SSR markers linked to bacterial wilt resistance of peanut with RILs. Chinese Journal of Oil Crop Sciences, 29, 26-30. (in Chinese) Kasha K J, Kao K N. 1970. High frequency haploid production in barley (Hordeum vulgare L.). Nature, 225, 874-876. Kochert G, Halward T, Branch W D, Simpson C E. 1991. RFLP variability in peanut (Arachis hypogaea L.) cultivars and wild species. Theoretical and Applied Genetics, 81, 565-570. Kosmabi D D. 1994. The estimation of map distance from recombination values. Annals of Eugenetics, 12, 172-175. Martins W, Sousa D D, Proite K, Guinaraes P, Moretzsohn M, Bertioli D. 2006. New softwares for automated microsatellite marker development. Nucleic Acids Research, 34, 1-4. Milla S R, Isleib T G, Stalker H T. 2005. Taxonomic relationships among Arachis sect. Arachis species as revealed by AFLP markers. Genome, 8, 1-11. Moretzsohn M C, Hopkins M S, Mitchell S E, Kresovich S, Valls J F, Ferreira M E. 2004. Genetic diversity of peanut (Arachis hypogaea L.) and its wild relatives based on the analysis of hypervariable regions of the genome. BMC Plant Biology, 4, 11. Moretzsohn M C, Leoi L, Proite K, Guimaras P M, Leal-Bertioli S C M, Gimenes M A, Martins W S, Valls J F M, Grattapaglia D, Bertioli D J. 2005. A microsatellite-based, gene-rich linkage map for the AA genome of Arachis (Fabaceae). Theoretical and Applied Genetics, 111, 1060-1071. Myburg A A, Griffin A R, Sederoff R R, Whetten R W. 2003. Comparative genetic linkage maps of Eucalyptus grandis, Eucalyptus globules and their F1 hybrid based on a double pseudo-backcross mapping approach. Theoretical and Applied Genetics, 107, 1028-1042. Nicot N, Chiquet V, Gandon B, Amilhat L, Legeai F, Leroy P, Bernard M, Sourdille P. 2004. Study of simple sequence repeat (SSR) markers from wheat expressed sequences tags
921
(ESTs). Theoretical and Applied Genetics, 109, 800-805. Nikaido A, Yoshimaru H, Tsumura Y, Suyama Y, Murai M. 1999. Segregation distortion of AFLP markers in Cryptomeria japonica. Genes & Genetic System, 74, 55-59. van Oojen J W, Voorips R E. 2001. JoinMap 3.0, Software for the calculation of genetic linkage maps. Plant Research International, Wageningen, The Netherlands. Palmieri D A, Hoshino A A, Bravo J P, Lopes C R, Gimenes M A. 2002. Isolation and characterization of microsatellite loci from the forage species Arachis Pintoi (Genus Arachis). Molecular Ecology Notes, 2, 551-553. Palmieri D A, Bechara M D, Curi R A, Gimenes M A, Lopes C R. 2005. Novel polymorphic microsatellite markers in section Caulorrhizae (Arachis, Fabaceae). Molecular Ecology Notes, 5, 77-79. Qi X, Stam P, Lindhout P. 1996. Comparison and integration of four barley genetic maps. Genome, 39, 379-394. Ramsay L, Macaulay M, Ivanissivich S, MacLean K, Cardle L, Fuller J, Edwards K, Tuvesson S, Morgante M, Massari A, Maestri E, Marniorlin N, Sjakste T, Ganal M, Powell W, Powell W, Waugh R. 2000. A simple sequence repeat-based linkage map of barley. Genetics, 156, 1997-2005. Sewell M M, Sherman B K, Neale D B. 1999. A consensus map for loblolly (Pinus taeda L.). I. Construction and intergration of individual linkage maps from two outbred three-generation pedigree. Genetics, 151, 321-330. Smulders M J M, Bredemeijer G, Rus-Kortekaas W, Arens P, Vosman B. 1997. Use of short microsatellites from database sequences to generate polymorphisms among Lycopersicon esculentum cultivars and accessions of other Lycopersicon species. Theoretical and Applied Genetics, 94, 264-272. Stam P. 1993. Construction of integrated genetic linkage maps by means of a new computer package JoinMap. The Plant Journal, 3, 739-744. Subramanian V, Gurtu S, Rao R C N, Nigam S N. 2000. Identification of DNA polymorphism in cultivated groundnut using random amplified polymorphic DNA (RAPD) assay. Genome, 43, 656-660. Thiel T, Michalek W, Varshney R K, Graner A. 2003. Exploiting EST databases for the development and characterization of gene-derived SSR-markers in barley (Hordeum vulgare L.). Theoretical and Applied Genetics, 106, 411-422. Tian A G, Wang J, Cui P, Han Y J, Xu H, Cong L J, Huang X G, Wang X L, Jiao Y Z, Wang B J, Wang Y J, Zhang J S, Chen S Y. 2004. Characterization of soybean genomic features by analysis of its expressed sequence tags. Theoretical and Applied Genetics, 108, 903-913. Varshney R K, Graner A, Sorrells M E. 2005. Genetic microsatellite markers in plants: features and applications. Trends in Biotechnology, 23, 48-55. Voorips R E. 2002. Mapchart: software for the graphical presentation of linkage maps and QTLs. Journal of Heredity, 93, 77-78. Zamir D, Tadmor Y. 1986. Unequal segregation of nuclear genes in plants. Botanical Gazette, 147, 355-358. (Edited by ZHAO Qi)
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