Skip to main content

Advertisement

SpringerLink
Log in

cDNA-AFLP-based genetical genomics in cotton fibers

  • Original Paper
  • Published:
Theoretical and Applied Genetics Aims and scope Submit manuscript

Abstract

Genetical genomics, or genetic analysis applied to gene expression data, has not been widely used in plants. We used quantitative cDNA-AFLP to monitor the variation in the expression level of cotton fiber transcripts among a population of inter-specific Gossypium hirsutum × G. barbadense recombinant inbred lines (RILs). Two key fiber developmental stages, elongation (10 days post anthesis, dpa), and secondary cell wall thickening (22 dpa), were studied. Normalized intensity ratios of 3,263 and 1,201 transcript-derived fragments (TDFs) segregating over 88 RILs were analyzed for quantitative trait loci (QTL) mapping for the 10 and 22 dpa fibers, respectively. Two-thirds of all TDFs mapped between 1 and 6 eQTLs (LOD > 3.5). Chromosome 21 had a higher density of eQTLs than other chromosomes in both data sets and, within chromosomes, hotspots of presumably trans-acting eQTLs were identified. The eQTL hotspots were compared to the location of phenotypic QTLs for fiber characteristics among the RILs, and several cases of co-localization were detected. Quantitative RT-PCR for 15 sequenced TDFs showed that 3 TDFs had at least one eQTL at a similar location to those identified by cDNA-AFLP, while 3 other TDFs mapped an eQTL at a similar location but with opposite additive effect. In conclusion, cDNA-AFLP proved to be a cost-effective and highly transferable platform for genome-wide and population-wide gene expression profiling. Because TDFs are anonymous, further validation and interpretation (in silico analysis, qPCR gene profiling) of the eQTL and eQTL hotspots will be facilitated by the increasing availability of cDNA and genomic sequence resources in cotton.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4

Similar content being viewed by others

References

  • Adams KL, Percifield R, Wendel JF (2004) Organ-specific silencing of duplicated genes in a newly synthesized allotetraploid. Genetics 168:2217–2226

    Article  PubMed  CAS  Google Scholar 

  • Al-Ghazi Y, Boutrot S, Arioli T, Dennis ES, Llewellyn D (2009) Transcript profiling during fiber development identifies pathways in secondary metabolism and cell wall structure that may contribute to cotton fiber quality. Plant Cell Physiol 50:1364–1381

    Article  PubMed  CAS  Google Scholar 

  • Alabady M, Youn E, Wilkins TA (2008) Double feature selection and cluster analyses in mining of microarray data from cotton. BMC Genomics 9:295

    Article  PubMed  Google Scholar 

  • Albertini E, Marconi G, Barcaccia G, Raggi L, Falcinelli M (2004) Isolation of candidate genes for apomixis in Poa pratensis L. Plant Mol Biol 56:879–894

    Article  PubMed  CAS  Google Scholar 

  • Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (1990) Basic local alignment search tool. J Mol Biol 215:403–410

    PubMed  CAS  Google Scholar 

  • An C, Saha S, Jenkins JN, Ma DP, Scheffler B, Kohel RJ, Yu J, Stelly DM (2008) Cotton (Gossypium spp.) R2R3-MYB transcription factors SNP identification, phylogenomic characterization, chromosome, and linkage mapping. Theor Appl Genet 116:1015–1026

    Article  PubMed  CAS  Google Scholar 

  • Argout X, Fouet O, Wincker P, Gramacho K, Legavre T, Sabau X, Risterucci AM, Da Silva C, Cascardo J, Allegre M, Kuhn D, Verica J, Courtois B, Loor G, Babin R, Sounigo O, Ducamp M, Guiltinan MJ, Ruiz M, Alemanno L, Machado R, Phillips W, Schnell R, Gilmour M, Rosenquist E, Butler D, Maximova S, Lanaud C (2008) Towards the understanding of the cocoa transcriptome: production and analysis of an exhaustive dataset of ESTs of Theobroma cacao L. generated from various tissues and under various conditions. BMC Genomics 9:512

    Article  PubMed  Google Scholar 

  • Bachem CW, van de Hoevan RS, de Bruijn SM, Vreugdenhil D, Zabeau M, Visser RG (1996) Visualization of differential gene expression using a novel method of RNA fingerprinting based on AFLP: analysis of gene expression during potato tuber development. Plant J 9:745–753

    Article  PubMed  CAS  Google Scholar 

  • Basra AS, Malik CP (1984) Development of the cotton fiber. Int Rev Cytol 89:65–113

    Article  CAS  Google Scholar 

  • Basten CJ, Weir BS, Zeng ZB (2003) QTL Cartographer Version 1.17: a reference manual and tutorial for QTL mapping. Department of Statistics. North Carolina State University, Raleigh

    Google Scholar 

  • Beavis WD (1998) QTL analyses: power, precision and accuracy. In: Paterson AH (ed) Molecular dissection of complex traits. CRC Press, New York, pp 145–162

    Google Scholar 

  • Breitling R, Li Y, Tesson BM, Fu J, Wu C, Wiltshire T, Gerrits A, Bystrykh LV, de Haan G, Su AI, Jansen RC (2008) Genetical genomics: spotlight on QTL hotspots. PLoS Genet 4:e1000232

    Article  PubMed  Google Scholar 

  • Brem RB, Yvert G, Clinton R, Kruglyak L (2002) Genetic dissection of transcriptional regulation in budding yeast. Nat Genet 296:752–754

    Article  CAS  Google Scholar 

  • Breyne P, Dreesen R, Cannoot B, Rombaut D, Vandepoele K, Rombauts S, Vanderhaeghen R, Inzé Z, Zabeau M (2003) Quantitative cDNA-AFLP analysis for genome-wide expression studies. Mol Genet Genomics 269:173–179

    PubMed  CAS  Google Scholar 

  • Chen X, Hackett CA, Niks RE, Hedley PE, Booth C, Druka A, Marcel TC, Vels A, Bayer M, Milne I, Morris J, Ramsay L, Marshall D, Cardle L, Waugh R (2010) An eQTL analysis of partial resistance to Puccinia hordei in barley. PLoS One 5:e8598

    Article  PubMed  Google Scholar 

  • Doebley JF, Gaut BS, Smith BD (2006) The molecular genetics of crop domestication. Cell 127:1309–1321

    Article  PubMed  CAS  Google Scholar 

  • Donson J, Fang Y, Espiritu-Santo G, Xing W, Salazar A, Miyamoto S, Armendarez V, Volkmuth W (2002) Comprehensive gene expression analysis by transcript profiling. Plant Mol Biol 48:75–97

    Article  PubMed  CAS  Google Scholar 

  • Druka A, Potokina E, Luo Z, Bonar N, Druka I, Zhang L, Marshall DF, Steffenson BJ, Close TJ, Wise RP, Kleinhofs A, Williams RW, Kearsey MJ, Waugh R (2008) Exploiting regulatory variation to identify genes underlying quantitative resistance to the wheat stem rust pathogen Puccinia graminis f. sp. tritici in barley. Theor Appl Genet 117:261–272

    Article  PubMed  CAS  Google Scholar 

  • Gibson G, Weir B (2005) The quantitative genetics of transcription. Trends Genet 21:616–623

    Article  PubMed  CAS  Google Scholar 

  • Gilad Y, Rifkin SA, Pritchard JK (2008) Revealing the architecture of gene regulation: the promise of eQTL studies. Trends Genet 24:408–415

    Article  PubMed  CAS  Google Scholar 

  • Guo S, Zheng Y, Joung JG, Liu S, Zhang Z, Crasta OR, Sobral BW, Xu Y, Huang S, Fei Z (2010) Transcriptome sequencing and comparative analysis of cucumber flowers with different sex types. BMC Genomics 11:384

    Article  PubMed  Google Scholar 

  • Hansen BG, Halkier BA, Kliebenstein DJ (2007) Identifying the molecular basis of QTLs: eQTLs add a new dimension. Trends Plant Sci 13:72–77

    Article  Google Scholar 

  • Holloway B, Li B (2010) Expression QTLs: applications for crop improvement. Mol Breed 26:381–391

    Article  Google Scholar 

  • Hovav R, Chaudhary B, Udall JA, Flagel L, Wendel JF (2008a) Parallel domestication, convergent evolution and duplicated gene recruitment in allopolyploid cotton. Genetics 179:1725–1733

    Article  PubMed  Google Scholar 

  • Hovav R, Udall JA, Chaudhary B, Rapp R, Flagel LE, Wendel JF (2008b) Partitioned expression of duplicated genes during development and evolution of a single cell in a polyploid plant. Proc Natl Acad Sci USA 105:6191–6195

    Article  PubMed  CAS  Google Scholar 

  • Hovav R, Udall JA, Hovav E, Rapp R, Flagel LE, Wendel JF (2008c) A majority of cotton genes are expressed in single-celled fiber. Planta 227:319–329

    Article  PubMed  CAS  Google Scholar 

  • Hsieh Y-L (1999) Structural development of cotton fibers and linkages to fiber quality. In: Basra AS (ed) Cotton fibers. Food Products Press, Binghampton, pp 137–166

    Google Scholar 

  • Hubner N, Yagil C, Yagil Y (2006) Novel integrative approach to the identification of candidate genes in hypertension. Hypertension 47:1–5

    Article  PubMed  CAS  Google Scholar 

  • Jansen RC, Nap JP (2001) Genetical genomics: the added value from segregation. Trends Genet 17:388–391

    Article  PubMed  CAS  Google Scholar 

  • Jordan MC, Somers DJ, Banks TW (2007) Identifying regions of the wheat genome controlling seed development by mapping expression quantitative trait loci. Plant Biotechnol J 5:442–453

    Google Scholar 

  • Kang HM, Ye C, Eskin E (2008) Accurate discovery of expression quantitative trait loci under confounding from spurious and genuine regulatory hotspots. Genetics 180:1909–1925

    Article  PubMed  CAS  Google Scholar 

  • Keurenjes JJB, Fu J, Terpstra IR, Garcia JM, van den Ackerveken G, Snoek LB, Peeters AJM, Vreugdenhill D, Koorneef M, Jansen RC (2007) Regulatory network construction in Arabidopsis by using genome-wide gene expression quantitative trait loci. Proc Natl Acad Sci USA 104:1708–1713

    Article  Google Scholar 

  • Kirst M, Basten CJ, Myburg AA, Zeng ZB, Sederoff RR (2005) Genetic architecture of transcript-level variation in differentiating xylem of a Eucalyptus hybrid. Genetics 169:2295–2303

    Article  PubMed  CAS  Google Scholar 

  • Kirst M, Myburg AA, De Leon JPG, Kirst ME, Scott J, Sederoff RR (2004) Coordinated genetic regulation of growth and lignin revealed by quantitative trait locus analysis of cDNA microarray data in an interspecific backcross of Eucalyptus. Plant Physiol 135:2368–2378

    Article  PubMed  CAS  Google Scholar 

  • Kliebenstein DJ (2008) Quantitative genomics: analyzing intraspecific variation using global gene expression polymorphims or eQTLs. Ann Rev Plant Biol 60:93–114

    Article  Google Scholar 

  • Kliebenstein DJ, West MA, van Leeuwen H, Loudet O, Doerge RW, St Clair DA (2006) Identification of QTLs controlling gene expression networks defined a priori. BMC Bioinf 7:308

    Article  Google Scholar 

  • Lacape J-M, Jacobs J, Arioli T, Derijcker R, Forestier-Chiron JeanJ, Llewellyn D, Thomas E, Viot C (2009) A new inter-specific, Gossypium hirsutum × G. barbadense, RIL population: towards a unified consensus linkage map of tetraploid cotton. Theor Appl Genet 119:281–292

    Article  PubMed  CAS  Google Scholar 

  • Lacape J-M, Llewellyn D, Jacobs J, Al-Ghazi Y, Liu S, Arioli T, Palai O, Georges S, Giband M, de Asunção H, Viot C, Jean J, Claverie M, Gawryziak G, Vialle M (2010) Meta-analysis of cotton fiber quality QTL across diverse environments in an inter-specific Gossypium hirsutum × G barbandense RIL population. BMC Plant Biol 10:132

    Article  PubMed  Google Scholar 

  • Leng C, Li F, Chen G, Liu C (2007) cDNA-AFLP analysis of somatic embryogenesis at early stage in TM-1 (Gossypium hirsutum L.). Acta Bot Boreal Occid Sin 27:233–237

    CAS  Google Scholar 

  • Lin L, Pierce GJ, Bowers JE, Estill JC, Compton RO, Rainville LK, Kim C, Lemke C, Rong J, Tang H, Wang X, Braidotti M, Chen AH, Chicola K, Collura K, Epps E, Golser W, Grover C, Ingles J, Karunakaran S, Kudrna D, Olive J, Tabassum N, Um E, Wissotski M, Yu Y, Zuccolo A, ur Rahman M, Peterson DG, Wing RA, Wendel JF, Paterson AH (2010) A draft physical map of a D-genome cotton species (Gossypium raimondii). BMC Genomics 11:395

    Article  PubMed  Google Scholar 

  • Liu R, Wang B, Guo W, Wang L, Zhang T (2011) Differential gene expression and associated QTL mapping for cotton yield based on a cDNA-AFLP transcriptome map in an immortalized F(2). Theor Appl Genet 123:439–454

    Article  PubMed  CAS  Google Scholar 

  • Ma X, Xing C, Guo L, Gong Y, Wang H, Zhao Y, Wu J (2008) Analysis of differentially expressed genes in genic male sterility cotton (Gossypium hirsutum L.) using cDNA-AFLP. J Genet Genomics 34:536–543

    Article  Google Scholar 

  • May LO (1999) Genetic variation in fiber quality. In: Basra AS (ed) Cotton fibers. Food Products Press, Binghampton, pp 183–229

    Google Scholar 

  • Michaelson JJ, Loguercio S, Beyer A (2009) Detection and interpretation of expression quantitative trait loci (eQTL). Methods 48:265–276

    Article  PubMed  CAS  Google Scholar 

  • Paterson AH, Rong J, Gingle AR, Chee P, Dennis ES, Llewellyn D, Dure LS III, Haigler C, Myers GO, Peterson DG, Rahman M, Zafar Y, Reddy U, Saranga Y, Mc Stewart J, Udall JA, Waghmare VN, Wendel JF, Wilkins T, Wright RJ, Zaki E, Hafez EE, Zhu J (2010) Sequencing and utilization of the Gossypium genomes. Trop Plant Biol 3:71–74

    Article  CAS  Google Scholar 

  • Pérez-Enciso M, Quevedo JR, Bahamonde A (2007) Genetical genomics: use all data. BMC Genomics 8:69

    Article  PubMed  Google Scholar 

  • Ponsuksili S, Murani E, Phatsara C, Schwerin M, Schellander K, Wimmers K (2010) Expression quantitative trait loci analysis of genes in porcine muscle by quantitative real-time RT-PCR compared to microarray data. Heredity 1:1–9

    Article  Google Scholar 

  • Potokina E, Druka A, Luo Z, Wise R, Waugh R, Kearsey M (2008) Gene expression quantitative trait locus analysis of 16 000 barley genes reveals a complex pattern of genome-wide transcriptional regulation. Plant J 53:90–101

    Article  PubMed  CAS  Google Scholar 

  • Qin L, Prins P, Helder J (2006) 8. Linking cDNA-AFLP-based gene expression patterns and ESTs. In: Liang P, Meade JD, Pardee AB (eds) Methods in molecular biology, vol 317: differential display methods and protocols. Humana Press Inc., Totowa, pp 123–138

    Google Scholar 

  • Reijans M, Lascaris R, Groeneger AO, Wittenberg A, Wesselink E, van Oeveren J, de Wit E, Boorsma A, Voetdijk B, van der Spek H, Grivell LA, Simons G (2003) Quantitative comparison of cDNA-AFLP, microarrays, and GeneChip expression data in Saccharomyces cerevisiae. Genomics 82:606–618

    Article  PubMed  CAS  Google Scholar 

  • Rombauts S, Van de Peer Y, Rouzé P (2003) AFLPinSilico, simulating AFLP fingerprints. Bioinformatics 19:776–777

    Article  PubMed  CAS  Google Scholar 

  • Rong J, Feltus FA, Waghmare VN, Pierce GJ, Chee P, Draye X, Saranga Y, Wright RJ, Wilkins TA, May LO, Smith CW, Gannaway JR, Wendel JF, Paterson AH (2007) Meta-analysis of polyploid cotton QTL shows unequal contributions of subgenomes to a complex network of genes and gene clusters implicated in lint fiber development. Genetics 176:2577–2588

    Article  PubMed  CAS  Google Scholar 

  • Salvi S, Tuberosa R (2005) To clone or not to clone plant QTLs: present and future challenges. Trends Plant Sci 10:297–304

    Article  PubMed  CAS  Google Scholar 

  • Schadt EE, Monks SA, Drake DA, Lusis AL, Che N, Colinayo V, Ruff TG, Milligan SB, Lamb JR, Cavet G, Linsley PS, Mao M, Stoughton RB, Friend SH (2003) Genetics of gene expression surveyed in maize, mouse and human. Nature 422:297–302

    Article  PubMed  CAS  Google Scholar 

  • Shi C, Uzarowska A, Ouzunova M, Landbeck M, Wenzel G, Luebberstedt T (2007) Identification of candidate genes associated with cell wall digestibility and eQTL (expression quantitative trait loci) analysis in a Flint × Flint maize recombinant inbred line population. BMC Genomics 8:22

    Article  PubMed  Google Scholar 

  • Torres TT, Metta M, Ottenwälder B, Schlötterer C (2010) Gene expression profiling by massively parallel sequencing. Genome Res 18:172–177

    Google Scholar 

  • Vuylsteke M, Daele H, Vercauteren A, Zabeau M, Kuiper M (2006) Genetic dissection of transcriptional regulation by cDNA-AFLP. Plant J 45:439–446

    Article  PubMed  CAS  Google Scholar 

  • Vuylsteke M, Peleman J, van Eijk MJT (2007) AFLP-based transcript profiling (cDNA-AFLP) for genome-wide expression analysis. Nat Protoc 2:1399–1413

    Article  PubMed  CAS  Google Scholar 

  • Wan CY, Wilkins TA (1994) A modified hot borate method significantly enhances the yield of high-quality RNA from cotton (Gossypium hirsutum L.). Anal Biochem 223:7–12

    Article  PubMed  CAS  Google Scholar 

  • Wang J, Yu H, Xie W, Xing Y, Yu S, Xu C, Li X, Xiao J, Zhang Q (2010) A global analysis of QTLs for expression variations in rice shoots at the early seedling stage. Plant J 63:1063–1074

    Article  PubMed  CAS  Google Scholar 

  • Wendel JF, Cronn RC (2003) Polyploidy and the evolutionary history of cotton. Adv Agron 78:140–186

    Google Scholar 

  • West MA, Kim K, Kliebenstein DJ, van Leeuwen H, Michelmore RW, Doerge RW, St Clair DA (2007) Global eQTL mapping reveals the complex genetic architecture of transcript level variation in Arabidopsis. Genetics 175:1441–1450

    Article  PubMed  CAS  Google Scholar 

  • Xu Z, Kohel RJ, Song GL, Cho JM, Alabady M, Yu J, Koo P, Chu J, Yu SX, Wilkins TA, Zhu YX, Yu JZ (2008) Gene-rich islands for fiber development in the cotton genome. Genomics 92:173–183

    Article  PubMed  CAS  Google Scholar 

  • Zhu C, Gore M, Buckler ES, Yu J (2008) Status and prospects of association mapping in plants. Plant Genome 1:5–20

    Article  CAS  Google Scholar 

Download references

Acknowledgments

The French National Research Agency, ANR, through its program specialized in plant genomics, Génoplante, has sponsored this research (project nr ANR-06-GPLA-018).

Author information

Authors and Affiliations

  1. UMR AGAP, CIRAD, Avenue Agropolis, 34398, Montpellier, France

    Michel Claverie, Marlène Souquet, Vincent Lepitre, Martial Pré & Jean-Marc Lacape

  2. UR SCA, CIRAD, Avenue Agropolis, 34398, Montpellier, France

    Janine Jean & Nelly Forestier-Chiron

  3. Bayer BioScience N.V., Technologiepark 38, Ghent, Belgium

    John Jacobs

  4. CSIRO Plant Industry, P.O. Box 1600, Canberra, ACT, Australia

    Danny Llewellyn

Authors
  1. Michel Claverie
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Marlène Souquet
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Janine Jean
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Nelly Forestier-Chiron
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Vincent Lepitre
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Martial Pré
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. John Jacobs
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Danny Llewellyn
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Jean-Marc Lacape
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jean-Marc Lacape.

Additional information

Communicated by G. Bryan.

Electronic supplementary material

Below is the link to the electronic supplementary material.

ESM1 (esm1.doc) – cDNA-AFLP protocol (DOC 44 kb)

122_2011_1738_MOESM2_ESM.doc

ESM2 (esm2.doc) - List of TDFs selected from the 10 dpa experiment for validation by quantitative RT-PCR. The TDF size, Genbank accession hit and its corresponding (putative) function, as well as the primers used for qPCR are indicated. In the cases where Blast results of the TDF sequence suggested several possible candidates, each accession was tested in qPCR (* indicates the 3 accessions/TDF combinations that showed congruence in the qPCR-derived and AFLP-derived eQTL mapping experiments) (DOC 47 kb)

122_2011_1738_MOESM3_ESM.pdf

ESM3 (esm3.pdf) - Same title and legend as Fig. 3 - Comparative localization of eQTLs with meta-clusters for fiber phenotypic QTLs Localization of eQTLs from fibers at 10 (blue bars) and 22 dpa (red bars) are compared with regions containing meta-clusters of fiber phenotypic QTLs (phQTLs) for major fiber quality trait categories, including fineness (FIN), length (LEN), strength (STR), elongation (ELO) and color (COL) as reported in Lacape et al. (2010). The observed parental effect (either Gh or Gb) of each meta-cluster of phQTLs, as indicated in the legends, corresponds to an improvement of the trait value, higher length, strength, and elongation or lower fineness and yellowness. The horizontal lines represent the 1000 permutation-based (P < 0.05) thresholds in the 10 and 22 dpa experiments. (PDF 82 kb)

122_2011_1738_MOESM4_ESM.pdf

ESM4 (esm4.pdf) - List of the 227 AFLP-derived transcript fragments mapping an eQTL in the 10 dpa and/or in the 22 dpa eQTL experiment and which matched with a TDF predicted from the AFLP-in silico digestion of the annotated EST unigene displaying differential (digital) expression between the 2 genotypes (fold change larger than 2) for the same stage of fiber development (either 10 and/or 22 dpa). (PDF 100 kb)

Rights and permissions

Reprints and permissions

About this article

Cite this article

Claverie, M., Souquet, M., Jean, J. et al. cDNA-AFLP-based genetical genomics in cotton fibers. Theor Appl Genet 124, 665–683 (2012). https://doi.org/10.1007/s00122-011-1738-x

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00122-011-1738-x

Keywords

Search

Navigation