Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

A genetic analysis of relative growth rate and underlying components in Hordeum spontaneum


Species from productive and unproductive habitats differ inherently in their relative growth rate (RGR) and a wide range of correlated quantitative traits. We investigated the genetic basis of this trait complex, and specifically assessed whether it is under the control of just one or a few genes that can act as ‘master switches‘ by simultaneously affecting a range of traits in the complex. To address this problem, we crossed two Hordeum spontaneum lines originating from two habitats that differ in productivity. The F3 offspring, in which parental alleles are present in different combinations due to recombination and segregation, was analysed for RGR and its underlying components (leaf area ratio, unit leaf rate, photosynthesis, respiration), as well as a number of other physiological and morphological parameters. For this intra-specific comparison, we found a complex of positively and negatively correlated traits, which was quite similar to what is generally observed across species. A quantitative trait loci (QTL) analysis showed three major and one minor QTL for RGR. Most other variables of the growth-trait complex showed fewer QTLs that were typically scattered over various locations on the genome. Thus, at least in H. spontaneum, we found no evidence for regulation of the trait complex by one or two master switches.

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

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5


  1. Ausubel FM, Brent R, Kingston RE, Moore DD, Seidman JG, Smith JA, Struhl K (1999) In: Short protocols in molecular biology: a compendium of methods from current protocols in molecular biology, 4th edn. Wiley, New York, pp 2.11–2.12

  2. Beavis WD (1994) The power and deceit of QTL experiments: lessons from comparative QTL studies. In: Wilkinson DB (ed) 49th Annual Conference and Sorghum Research Conference. American Seed Trade Association, Chicago, pp 250–266

  3. Becker J, Heun M (1995) Barley microsatellites: allele variation and mapping. Plant Mol Biol 27:835–845

  4. Becker J, Vos P, Kuiper M, Salamini F, Heun M (1995) Combined mapping of AFLP and RFLP markers in barley. Mol Genet Genomics 249:65–73

  5. Biere A (1996) Intra-specific variation in relative growth rate: impact on competitive ability and performance of Lychnis flos-cucili in habitats differing in soil fertility. Plant Soil 182:313–327

  6. Brown AHD, Zohary D, Nevo E (1978) Outcrossing rates and heterozygosity in natural populations of Hordeum spontaneum Koch in Israel. Heridity 41:49–62

  7. Buntjer JB (1999) Cross checker fingerprint analysis software, v. 2.9, Wageningen University and Research Centre, The Netherlands

  8. Cataldo DA, Haroon M, Schrader LF, Youngs VL (1975) Rapid colorimetric determination of nitrate in plant tissue by nitration of salicylic acid. Comm Soil Sci Plant Anal 6:71–80

  9. Causse M, Rocher JP, Henry AM, Charcosset A, Prioul JL, de Vienne D (1995) Genetic dissection of the relationship between carbon metabolism and early growth in maize, with emphasis on key-enzyme loci. Mol Breed 1:259–272

  10. Chapin FS, Groves RH, Evans LT (1989) Physiological determinants of growth rate in response to phosphorous supply in wild and cultivated Hordeum species. Oecologia 79:96–105

  11. Chapin FS, Autumn K, Pugnaire F (1993) Evolution of suites of traits in response to environmental stress. Am Nat 142:s78-s92

  12. Clevering OA (1999) Between- and within-population differences in Phragmites australis 1. The effects of nutrients on seedling growth. Oecologia 121:447–457

  13. Dijkstra P, Reegen HT, Kuiper PJC (1990) Relation between relative growth rate, endogenous gibberellins, and the response to gibberellic acid for Plantago major. Physiol Plant 79:629–634

  14. Elberse I (2002) Genetic analysis of growth characteristics in Hordeum spontaneum under nutrient limitation. PhD thesis, Utrecht University

  15. Ellis RP, Forster BP, Robinson D, Handley LL, Gordon DC, Russel JR, Powell W (2000) Wild barley: a source of genes for crop improvement in the 21st century? J Exp Bot 51:9–17

  16. El-Lithy ME, Clerkx EJM, Ruys GJ, Koornneef M, Vreugdenhil D (2004) Quantitative trait locus analysis of growth-related traits in a new arabidopsis recombinant inbred population. Plant Physiol 135:444–458

  17. Evans GC (1972) The quantitative analysis of plant growth. Blackwell, Oxford

  18. Evans JR (1998) Photosynthetic characteristics of fast- and slow-growing species. In: Lambers H, Poorter H, van Vuuren M (eds) Inherent variation in plant growth, physiological mechanisms and ecological consequences. Backhuys, Leiden, pp 101–119

  19. Farquhar GD, O’Leary MH, Berry JA (1982) On the relationship between carbon isotope discrimination and the intercellular carbon dioxide concentration in leaves. Aust J Plant Physiol 9:121–137

  20. Garnier E (1992) Growth analysis of congeneric annual and perennial grass species. J Ecol 80:665–675

  21. Garnier E, Vancaeyzeele S (1994) Carbon and nitrogen content of congeneric annual and perennial species: relationships with growth. Plant Cell Environ 17:399–407

  22. Grime JP (1979) Plant strategies and vegetation processes. Wiley, Chichester

  23. Grime JP, Hunt R (1975) Relative growth rate: its range and adaptive significance in a local flora. J Ecol 63:393–422

  24. Hervé D, Fabre F, Flores Berrios E, Leroux N, Al Chaarani G, Planchon C, Sarrafi A, Gentzbittel L (2001) QTL analysis of photosynthesis and water status traits in sunflower (Helianthus annuus L.) under greenhouse conditions. J Exp Bot 52:1857–1864

  25. Ivandic V, Hackett CA, Zhang ZJ, Staub JE, Nevo E, Thomas WTB, Forster BP (2000) Phenotypic responses of wild barley to experimentally imposed water stress. J Exp Bot 51:2021–2029

  26. Jaglo-Ottosen KR, Gilmour SJ, Zarka DG, Schabenberger O, Thomashow MF (1998) Arabidopsis CBF1 overexpression induces COR genes and enhances freezing tolerance. Science 280:104–106

  27. Jansen RC, Stam P (1994) High resolution of quantitative traits into multiple loci via interval mapping. Genetics 136:1447–1455

  28. Jurado E, Westoby M (1992) Seedling growth in relation to seed size among species of arid Australia. J Ecol 80:407–416

  29. Kitajima K (1994) Relative importance of photosynthetic traits and allocation patterns as correlates of seedling shade tolerance of 13 tropical trees. Oecologia 98:419–428

  30. Konings H (1989) Physiological and morphological differences between plants with a high NAR or a high LAR as related to environmental conditions. In: Lambers H, Cambridge ML, Konings H, Pons TL (eds) Causes and consequences of variation in growth rate and productivity in plants. SPB, The Hague, pp 101–123

  31. Lambers H, Poorter H (1992) Inherent variation in growth rate between higher plants: a search for physiological causes and ecological consequences. Adv Ecol Res 23:187–261

  32. Lander ES, Botstein D (1989) Mapping Mendelian factors underlying quantitative traits using RFLP linkage maps. Genetics 121:185–199

  33. Maleck K, Levine A, Eulgem T, Morgan A, Schmid J, Lawton KA, Dangl JL, Dietrich RA (2001) The transcriptome of Arabidopsis thaliana during systemic acquired resistance. Nat Genet 26:403–410

  34. Marañón T, Grubb PJ (1993) Physiological basis and ecological significance of the seed size and relative growth rate relationship in Mediterranean annuals. Funct Ecol 7:591–599

  35. Meerts P, Garnier E. (1996) Variation in relative growth rate and its components in the annual Polygonum aviculare in relation to habitat disturbance and seed size. Oecologia 108:438–445

  36. Mian MAR, Ashley DA, Vencill WK, Boerma HR (1998) QTLs conditioning early growth in a soybean population segregating for growth habit. Theor Appl Genet 97:1210–1216

  37. Nagel OW, Konings H, Lambers H (2001) Growth rate and biomass partitioning of wildtype and low-gibberellin tomato (Solanum lycopersicum) plants growing at a high and low nitrogen supply. Physiol Plant 111:33–39

  38. Nevo E (1992) Origin, evolution, population genetics and resources for breeding of wild barley, Hordeum spontaneum in the Fertile Crescent. In: Shewry PR (ed) Barley genetics, biochemistry, molecular biology and biotechnology. CAB International, Wallingford, pp 19–43

  39. Nevo E, Zohary D, Brown AHD, Haber M (1979) Genetic diversity and environmental associations of wild barley, Hordeum spontaneum, in Israel. Evolution 33:815–833

  40. Nevo E, Beiles A, Gutterman Y, Storch N, Kaplan D (1984) Genetic resources of wild cereals in Israel and vicinity. II. Phenotypic variation within and between populations of wild barley Hordeum spontaneum. Euphytica 33:737–756

  41. Poorter L (1999) Growth response of 15 rainforest tree species to a light gradient: the relative importance of morphological and physiological traits. Funct Ecol 13:396–410

  42. Poorter H (2002) Plant growth and carbon economy. In: Encyclopedia of life sciences. Nature Publishing Group. http://www.els.net

  43. Poorter H, Bergkotte M (1992) Chemical composition of 24 wild species differing in relative growth rate. Plant Cell Environ 15:221–229

  44. Poorter H, Evans JR (1998) Photosynthetic nitrogen use efficiency of species that differ inherently in Specific Leaf Area. Oecologia 116:27–36

  45. Poorter H, Farquhar GD (1994) Transpiration, intercellular carbon dioxide concentration and carbon-isotope discrimination of 24 wild species differing in relative growth rate. Aust J Plant Physiol 21:507–516

  46. Poorter H, Garnier E (1999) Ecological significance of inherent variation in relative growth rate and its components. In: Pugnaire FI, Valladares F (eds) Handbook of functional plant ecology. Dekker, New York, pp 81–120

  47. Poorter H, Pothmann P (1992) Growth and carbon economy of a fast-growing and a slow-growing grass species as dependent on ontogeny. New Phytol 120:159–166

  48. Poorter H, Remkes C (1990) Leaf area ratio and net assimilation rate of 24 wild species differing in relative growth rate. Oecologia 83:553–559

  49. Poorter H, Van der Werf A (1998) Is inherent variation in RGR determined by LAR at low irradiance and by NAR at high irradiance? A review of herbaceous species. In: Lambers H, Poorter H, van Vuuren M (eds) Inherent variation in plant growth, Physiological mechanisms and Ecological Consequences. Backhuys, Leiden, pp 309–336

  50. Poorter H, Remkes C, Lambers H (1990) Carbon and nitrogen economy of 24 wild species differing in relative growth rate. Plant Physiol 94:621–627

  51. Prioul JL, Quarrie S, Causse M, de Vienne D (1997) Dissecting complex physiological functions through the use of molecular quantitative genetics. J Exp Bot 48:1151–1163

  52. Prioul JL, Pelleschi S, Séne M, Thévenot C, Causse M, de Vienne D, Leonardi A (1999) From QTLs for enzyme activity to candidate genes in maize. J Exp Bot 50:1281–1288

  53. Qi X, Lindhout P (1997) Development of AFLP markers in barley. Mol Genet Genomics 254:330–336

  54. Qi X, Stam P, Lindhout P (1998) Use of locus-specific AFLP markers to construct a high-density molecular map in barley. Theor Appl Genet 96:376–384

  55. Ramsay L, Macaulay M, degli Ivanissevich S, MacLean K, Cardle L, Fuller J, Edwards KJ, Tuvesson S, Morgante M, Massari A, Maestri E, Marmiroli N, Sjakste T, Ganal M, Powell W, Waugh R (2000) A simple sequence repeat-based linkage map of barley. Genetics 156:1997–2005

  56. Reich PB, Walters MB, Ellsworth DS (1997) From tropics to tundra: global convergence in plant functioning. Proc Natl Acad Sci U S A 94:13730–13734

  57. Reich PB, Walters MB, Tjoelker MG, Vanderklein D, Buschena C (1998) Photosynthesis and respiration rates depend on leaf and root morphology and nitrogen concentration in nine boreal tree species differing in relative growth rate. Funct Ecol 12:395–405

  58. Robinson D, Handley LL, Scrimgeour CM, Gordon DC, Forster BP, Ellis RP (2000) Using stable isotope natural abundances (δ15 N and δ13 C) to integrate the stress responses of wild barley (Hordeum spontaneum C. Koch) genotypes. J Exp Bot 51:41–50

  59. Rood SB, Zanewitch KP, Bray DF (1990) Growth and development of Brassica genotypes differing in endogenous gibberellin content. II. Gibberellin content, growth analysis and cell size. Physiol Plant 79:679–685

  60. Shipley B (2002) Trade-offs between net assimilation rate and specific leaf area in determining relative growth rate: relationship with daily irradiance. Funct Ecol 16:682–689

  61. Spoel SH, Koornneef A, Claessens SMC, Korzelius JP, van Pelt JA, Martin, Mueller J, Buchala AJ, Métraux JP, Brown R, Kazan K, van Loon LC, Dong X, Pieterse CMJ (2003) NPR1 modulates cross-talk between salicylate- and jasmonate-dependent defense pathways through a novel function in the cytosol. Plant Cell 15:760–770

  62. Tanksley SD (1993) Mapping polygenes. Annu Rev Gen 27:205–233

  63. This D, Borries C, Souyris I, Teulat B (2000) QTL study of chlorophyll content as a genetic parameter of drought tolerance in barley. Barley Genet Newsl http://grain.jouy.inra.fr/ggpages/bgn/30/dt2_2.htm

  64. Thomas SG, Sun T (2004) Update on gibberellin signaling. A tale of the tall and the short. Plant Physiol 135:668–676

  65. Van der Werf A, Geerts HEM, Jacobs FHH, Korevaar H, Oomes MJM, De Visser W (1998) The importance of relative growth rate and associated traits for competition between species during vegetation succession. In: Lambers H, Poorter H, van Vuuren M (eds) Inherent variation in plant growth, physiological mechanisms and ecological consequences. Backhuys, Leiden, pp 489–502

  66. Van Ooijen JW, Maliepaard C (1996) MapQTL v. 4.0: software for the calculation of QTL positions on genetic maps. CPRO-DLO, Wageningen, The Netherlands

  67. Van Ooijen JW, Voorrips RE (2000) Joinmap v. 3.0: software for the calculation of genetic linkage maps. Plant Research International, Wageningen, The Netherlands

  68. Van Rijn CPE (2001) A physiological and genetic analysis of growth characteristics in Hordeum spontaneum. PhD thesis, Utrecht University

  69. Van Rijn CPE, Heersche I, Van Berkel YEM, Nevo E, Lambers H, Poorter H (2000) Growth characteristics in Hordeum spontaneum populations from different habitats. New Phytol 146:471–481

  70. Verhoeven KJF, Vanhala TK, Biere A, Nevo E, van Damme JMM (2004) The genetic basis of adaptive population diferentiation: a QTL-analysis of fitness traits in two wild barley populations from contrasting habitats. Evolution 58:270–283

  71. Vos P, Hogers R, Bleeker M, Reijans M, van de Lee T, Hornes M, Frijters A, Pot J, Peleman J, Kuiper M, Zabeau M (1995) AFLP: a new technique for DNA fingerprinting. Nucleic Acids Res 23:4407–4414

  72. Wong SC, Cowan IR, Farquhar GD (1979) Stomatal conductance correlates with photosynthetic capacity. Nature 282:424–426

  73. Wright IJ, Reich PB, Westoby M, Ackerly DD, Baruch Z, Bongers F, Cavender-Bares J, Chapin T, Cornelissen JHC, Diemer M, Flexas J, Garnier E, Groom PK, Gulias J, Hikosaka K, Lamont BB, Lee T, Lee W, Lusk C, Midgley JJ, Navas ML, Niinemets U, Oleksyn J, Osada N, Poorter H, Poot P, Prior L, Pyankov VI, Roumet C, Thomas SC, Tjoelker MG, Veneklaas EJ, Villar R (2004) The worldwide leaf economics spectrum. Nature 428:821–827

  74. Wu RL (1998) Genetic mapping of QTLs affecting tree growth and architecture in Populus: implication for ideotype breeding. Theor Appl Genet 96:447–457

  75. Yin X, Kropff MJ, Stam P (1999) The role of ecophysiological models in QTL analysis: the example of specific leaf area in barley. Heridity 82:415–421

Download references


We thank Arjen Biere, Basten Snoek, Brian Forster, Jos van Damme, Margreet ter Steege, Rens Voesenek and Ton Peeters for valuable suggestions and comments during research and the writing of the manuscript. The Earth and Life Science Foundation (ALW), which is subsidised by the Netherlands Organisation for Scientific Research (NWO), supported this study financially.

Author information

Correspondence to Hendrik Poorter.

Electronic Supplementary Material

Appendix: the H. spontaneum map

Appendix: the H. spontaneum map

AFLP and SSR markers

Seventeen primer combinations were selected: E33M54, E33M61, E35M48, E35M54, E35M61, E38M55, E38M58, E42M51 and E45M55 (Qi and Lindhout 1997), E37M32, E37M33, E40M38, E41M32, E41M40, E42M32, E42M40 (Becker et al. 1995) and E31M55. DNA was isolated from 2-week-old leaves of the 233 F2 plants, using the CTAB method (Ausubel et al. 1999). The AFLP protocol was essentially as described in Vos et al. (1995). The DNA was double digested with the restriction enzymes EcoRI and MseI. The EcoRI-specific primers were labeled with either 700 or 800 nm infra-red dye (IRD700, IRD800) for detection with an automated laser sequencer (Li-Cor). In addition, markers generated by the primer combinations E32 M61, E33 M55, E39 M61, E42 M48 and E38 M54 (Qi and Lindhout 1997) were genotyped co-dominantly by Keygene.

Separately, a set of 13 SSR markers was used (Ramsay et al. 2000). The primers were labelled with either IRD700 or IRD800 for the Li-Cor sequencer. Approximately 20 ng of template DNA was used in the PCR reaction mixture, which further consisted of 1× PCR buffer, 0.5 U Ampli Taq polymerase (Perkin Elmer Inc., Wellesley, Mass., USA), 200 μM dNTPs and 1 pmol forward and reverse primer. The reaction volume was 10 μl. Four different PCR programs were used for amplification as described by Ramsay et al. (2000).

Map construction

The AFLP markers from 17 primer combinations were scored dominantly as the absence or presence of an amplification product. The scoring was done by eye with the help of the Cross Checker program (Buntjer 1999). The markers from five additional primer combinations were generated and scored co-dominantly by Keygene using their QuantarPro software, which enables a distinction between the homozygous and heterozygous state based on band intensity. The AFLP marker names were designated from the primer combination and size of the amplification product. SSRs were scored co-dominantly.

During the crossing process we kept track of the structure of the mapping population. Inspection of the data revealed that some of the F2 sub-families did not segregate for a number of markers, due to partial homozygosity of the parental F1 plant. This resulted from heterozygosity at such a marker for one of the parents of our cross. Neglecting this would affect the mapping results, i.e. by segregation distortion of these markers and an overestimation of recombination frequency between ‘affected’ and ‘non-affected’ markers (P. Stam, unpublished results). Therefore, for each marker we checked its segregation in each F2 sub-family and removed data from non-segregating sub-families.

With the corrected data set, a linkage map was constructed using the JoinMap 3.0 software package (Van Ooijen and Voorrips 2000). Linkage groups were assigned using an LOD threshold of 5.0. Kosambi’s mapping function was used to calculate map distances. To assign the linkage groups to known barley chromosomes, SSR loci (Ramsay et al. 2000) as well as AFLP markers in common with earlier maps from several cultivated barley populations L94 × Vada (Qi et al. 1998), L94 × 115-6 (P. Lindhout, personal communication), Apex × Prisma (Yin et al. 1999) and Proctor × Nudinka (Becker et al. 1995) were used.

Linkage map

The marker data revealed that the Ashqelon parent must have been heterozygous: 59% of the Ashqelon-specific markers did not segregate in at least one F2 sub-family. Heterozygosity was less prominent in the Mehola parent; with 7% of the Mehola-specific markers not segregating in at least one F2 sub-family. As a consequence, 45% of the markers contained no useful linkage information. After adjustment, 202 markers (196 AFLP and six SSR) could be mapped without problems.

The resulting linkage map is shown in Fig. 6. The markers are distributed over 11 linkage groups. Except for group U1, each linkage group contains both dominant and co-dominant markers. These co-dominant markers provided sufficient anchors to enable integration of the parental maps. The total map length equals 445 cM. This makes an average of 18 markers per linkage group, the range being from two to 36. The average distance between two markers was 2.2 cM. No gaps between two adjacent markers were larger than 20 cM.

Fig. 6

The linkage map of wild barley, H. spontaneum. Assignment of linkage groups to barley chromosomes 1H to 7H as described in the text. Linkage groups U1 and U2 are unassigned. AFLP marker identifiers are composed of primer combinations and estimated length of the amplification product. Co-dominant markers are indicated in bold, and markers used in identification of chromosomes are indicated in italics. Clusters of markers mapping to the same position (within 1 cM) are indicated by vertical bars to the left of the clusters

The assignment of linkage groups to barley chromosomes is based on AFLPs and SSRs that are in common with other linkage maps of cultivated barley (Table 6). Seven of the 11 linkage groups could unambiguously be assigned to known barley chromosomes. Three groups (2A, U1 and U2) did not contain any common markers, and one group (6) contained markers that mapped to different chromosomes in other mapping populations. Groups 2A and 6 were tentatively assigned to chromosomes based on weak linkage of some markers that were not mapped in our population, but have been mapped in at least one of the other populations. Linkage groups U1 and U2 remained unassigned, due to lack of markers shared with other maps.

Table 6 The linkage groups, the chromosomes to which they are assigned, number of markers in each linkage group, length of linkage group, the relevant maps the chromosomes were based on and common markers linking the map of H. spontaneum Ashqelon × Mehola to other Hordeum maps

The χ2 values for goodness-of-fit ranged from 0.83 to 1.60 for the 11 linkage groups, indicating a good overall fit. Therefore, even though the current map had to be assembled by removing a substantial number of markers, the remaining data still resulted in a reliable map that can serve as a basis for further linkage and QTL mapping.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Poorter, H., van Rijn, C.P.E., Vanhala, T.K. et al. A genetic analysis of relative growth rate and underlying components in Hordeum spontaneum. Oecologia 142, 360–377 (2005). https://doi.org/10.1007/s00442-004-1705-1

Download citation


  • Specific leaf area
  • Unit leaf rate
  • Quantitative trait loci
  • Trait complex
  • Photosynthesis