Flower shape and colour are key plant traits which are often strongly correlated with pollinator choice and reproductive isolation. To understand the genetic changes underlying variation in these traits, we performed the first QTL analyses of these traits in Streptocarpus (Gesneriaceae) using a segregating backcross (BC) population of (S. rexii × S. grandis) × S. grandis. Composite traits of floral dimensions were dissected into smallest definable subtraits to examine the efficiency of QTL mapping and correlation between composite and subtrait-specific QTLs. Strong dominance effects were observed in the F1 for many S. rexii traits but for few S. grandis traits. In the BC plants new phenotypes appeared that may be the result of transgressive segregation. Many phenotypic correlations were found between floral dimension traits, which was probably due to the co-localisation of QTLs on the linkage groups. Two regions were associated with large numbers of size and shape traits (17 linked on LG1 and eight linked on LG12), to which the first principal component was also mapped. QTLs of composite traits were mostly overlapping with subtraits, although a few QTLs were newly discovered in subtrait mapping. Strong QTLs were detected for time to flowering and for floral pigmentation traits, ventral lobe pigmentation and the yellow spot. The absence of linkage of floral dimension traits and flower pigmentation suggests that genetic regulation of floral form in Streptocarpus allows versatility, perhaps allowing fast response to changing selective pressures from pollinators.
This is a preview of subscription content, access via your institution.
Buy single article
Instant access to the full article PDF.
Tax calculation will be finalised during checkout.
Subscribe to journal
Immediate online access to all issues from 2019. Subscription will auto renew annually.
Tax calculation will be finalised during checkout.
Availability of data and materials
QTL data used in this study are included in the manuscript and supplementary materials.
Albert NW, Davies KM, Lewis DH, Zhang H, Montefiori M, Brendolise C, Boase MR, Ngo H, Jameson PE, Schwinn KE (2014) A conserved network of transcriptional activators and repressors regulates anthocyanin pigmentation in eudicots. Plant Cell 26:962–980
Alexandre H, Vrignaud J, Mangin B, Joly S (2015) Genetic architecture of pollination syndrome transition between hummingbird-specialist and generalist species in the genus Rhytidophyllum (Gesneriaceae). PeerJ 3:e1028
Best DJ, Roberts DE (1975) Algorithm AS 89: the upper tail probabilities of Spearman’s rho. J R Stat Soc C 24:377–379
Broman KW (2003) Mapping quantitative trait loci in the case of a spike in the phenotype distribution. Genetics 163:1169–1175
Broman KW, Sen Ś (2009) A guide to QTL mapping with R/qtl. Springer, Berlin
Cao Z, Guo Y, Yang Q, He Y, Fetouh MI, Warner RM, Deng Z (2019) Genome-wide identification of quantitative trait loci for important plant and flower traits in petunia using a high-density linkage map and an interspecific recombinant inbred population derived from Petunia integrifolia and P. axillaris. Hortic Res 6:27
Chen YY, Nishii K, Barber S, Hackett C, Kidner CA, Gharbi K, Nagano AJ, Iwamoto A, Möller M (2018) A first genetic map in the genus Streptocarpus generated with RAD sequencing based SNP markers. S Afr J Bot 117:158–168
Chiara M, Horner DS, Spada A (2013) De novo assembly of the transcriptome of the non-model plant Streptocarpus rexii employing a novel heuristic to recover locus-specific transcript clusters. PLoS ONE 8:e80961
Chou SP (2008) Genetic analysis of pollination-related floral shape in Streptocarpus (Gesneriaceae). MSc Dissertation. National Taiwan University
Conner JK (2002) Genetic mechanisms of floral trait correlations in a natural population. Nature 420:407–410
Cui JJ, Cheng JW, Wang GP, Tang X, Wu ZM, Lin MB, Li LF, Hu KL (2015) QTL analysis of three flower-related traits based on an interspecific genetic map of Luffa. Euphytica 202:45–54
Davies KM, Albert NW, Schwinn KE (2012) From landing lights to mimicry: the molecular regulation of flower colouration and mechanisms for pigmentation patterning. Funct Plant Biol 39:619–638
De Villiers MJ, Pirie MD, Hughes M, Möller M, Edwards TJ, Bellstedt DU (2013) An approach to identify putative hybrids in the ‘coalescent stochasticity zone’, as exemplified in the African plant genus Streptocarpus (Gesneriaceae). New Phytol 198:284–300
Dunn OJ (1964) Multiple comparisons using rank sums. Technometrics 6:241–252
Feenstra B, Skovgaard IM, Broman KW (2006) Mapping quantitative trait loci by an extension of the Haley-Knott regression method using estimating equations. Genetics 173:2269–2282
Feng C, Yang L, Kang M, Rausher MD (2019) Genetic architecture of quantitative flower and leaf traits in a pair of sympatric sister species of Primulina. Heredity 122:864–876
Georgiadis P (2005) Developmental and genetic dissection of floral morphology in Streptocarpus. MSc Dissertation, The University of Edinburgh
Haldane JS (1919) The combination of linkage values, and the calculation of distances between the loci of linked factors. J Genet 8:299–309
Harrison J, Möller M, Cronk QCB (1999) Evolution and development of floral diversity in Streptocarpus and Saintpaulia. Ann Bot 84:49–60
Hermann K, Klahre U, Moser M, Sheehan H, Mandel T, Kuhlemeier C (2013) Tight genetic linkage of prezygotic barrier loci creates a multifunctional speciation island in Petunia. Curr Biol 23:873–877
Hilliard OM, Burtt BL (1971) Streptocarpus: an african plant study. University of Kwazulu Natal Press. Pietermaritzburg. South Africa
Hollander M, Wolfe DA (1973) Nonparametric statistical methods. Wiley, New York
Juenger T, Purugganan M, Mackay TFC (2000) Quantitative trait loci for floral morphology in Arabidopsis thaliana. Genetics 156:1379–1392
Kelly JK, Mojica JP (2011) Interactions among flower-size QTL of Mimulus guttatus are abundant but highly variable in nature. Genetics 189:1461–1471
Kostyun JL, Gibson MJS, King CM, Moyle LC (2019) A simple genetic architecture and low constraint allow rapid floral evolution in a diverse and recently radiating plant genus. New Phytol 223:1009–1022
Kramer EM (2019) Plus ça change, plus c’est la même chose: the developmental evolution of flowers. Curr Top Dev Biol 131:211–238
Kruglyak L, Lander ES (1995) A nonparametric approach for mapping quantitative trait loci. Genetics 139:1421–1428
Lawrence WJC (1957) Studies on Streptocarpus IV. Genetics of flower colour patterns. Heredity 11:337–357
Lawrence WJC (1958) Studies on Streptocarpus Lindl. V. Speciation and gene systems. Heredity 12:333–356
Lawrence WJC, Sturgess VC (1957) Studies on Streptocarpus III. Genetics and chemistry of flower colour in the garden forms. Heredity 11:303–336
Lawrence WJC, Scott-Moncrieff R, Sturgess VC (1939) Studies on Streptocarpus. I. Genetics and chemistry of flower colour in the garden strains. J Genet 38:299–306
Lynch M, Walsh B (1998) Genetics and analysis of quantitative traits. Sinauer Associates Incorporated, Oxford University Press, Oxford
Mangin B, Thoquet P, Grimsley N (1998) Pleiotropic QTL analysis. Biometrics 54:88–99
Manichaikul A, Dupuis J, Sen Ś, Broman KW (2006) Poor performance of bootstrap confidence intervals for the location of a quantitative trait locus. Genetics 174:481–489
Möller M (2019) Nuclear DNA C-values are correlated with pollen size at tetraploid but not diploid level and linked to phylogenetic descent in Streptocarpus (Gesneriaceae). S Afr J Bot 114:323–344
Möller M, Barber S, Atkins HJ, Purvis DA (2019) The living collection at the Royal Botanic Garden Edinburgh illustrates the floral diversity in Streptocarpus (Gesneriaceae). Sibbaldia 17:155–175
Oehlkers F (1942) Faktorenanalytische Ergebnisse an Artbastarden. Biol Zbl 62:280–289
Oehlkers F (1966) Der gelbe Fleck in der Blüte der Gesneriaceae Streptocarpus Lindl. und seine Vererbung. I. Z Vererbungsl 98:127–136
Oehlkers F (1967) Der gelbe Fleck in der Blüte der Gesneriaceae Streptocarpus Lindl. und seine Vererbung. II. Mol Gen Genet 99:62–68
R Development Core Team (2008) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna
Rieseberg LH, Archer MA, Wayne RK (1999) Transgressive segregation, adaptation and speciation. Heredity 83:363–372
Schneider CA, Rasband WS, Eliceiri KW (2012) NIH image to imageJ: 25 years of image analysis. Nat Methods 9:671–675
Smith SD (2016) Pleiotropy and the evolution of floral integration. New Phytol 209:80–85
Stevens PF (2001) Angiosperm Phylogeny Website. Version 14, July 2017 [and more or less continuously updated since]. http://www.mobot.org/MOBOT/research/APweb/. Accessed 4 June 2020
Stuurman J, Hoballah ME, Broger L, Moore J, Basten C, Kuhlemeier C (2004) Dissection of floral pollination syndromes in Petunia. Genetics 168:1585–1599
Taft RJ, Pheasant M, Mattick JS (2007) The relationship between non-protein-coding DNA and eukaryotic complexity. BioEssays 29:288–299
The Tomato Genome Consortium (2012) The tomato genome sequence provides insights into fleshy fruit evolution. Nature 485:635–641
Vallejo-Marín M (2018) Buzz pollination: studying bee vibrations on flowers. New Phytol 224:1068–1074
Weiss J, Delgado-Benarroch L, Egea-Cortines M (2005) Genetic control of floral size and proportions. Int J Dev Biol 49:513–525
Wessinger CA, Hileman LC (2016) Accessibility, constraint, and repetition in adaptive floral evolution. Dev Biol 419:175–183
Wessinger CA, Hileman LC, Rausher MD (2014) Identification of major quantitative trait loci underlying floral pollination syndrome divergence in Penstemon. Philos Trans R Soc Lond B Biol Sci 369:20130349
Xu S, Atchley WR (1996) Mapping quantitative trait loci for complex binary diseases using line crosses. Genetics 143:1417–1424
The authors would like to thank Sadie Barber, Nathan Kelso, and Andrew Ensoll for growing the plant material at the Royal Botanic Garden Edinburgh (RBGE). We also thank Michelle Hart, Laura Forrest, and Ruth Holland for supporting the molecular laboratory work, and Duncan Reddish for ICT support of the analysis servers at RBGE. Prof. Pete Hollingsworth (RBGE) for general support and facilitating the research associateship for KN at RBGE, and Prof. Andrew Hudson (University of Edinburgh) and Hao-Chun Hhu (National Taiwan University) for discussions on analytical methods. KN received supports from the Edinburgh Botanic Garden (Sibbald) Trust [2018#18], the Japan Society for the Promotion of Science [JSPS KAKENHI Grant Number 15K18593; 18K06375], and the Sumitomo Foundation . Computations were partially performed on the NIG supercomputer at ROIS National Institute of Genetics in Japan. RBGE and Biomathematics and Statistics Scotland are supported by the Rural and Environment Science and Analytical Services Division (RESAS) of the Scottish Government.
PhD scholarship at the University of Edinburgh for Yun-Yu Chen. Edinburgh Botanic Garden (Sibbald) Trust [2018#18], the Japan Society for the Promotion of Science [JSPS KAKENHI Grant Number 15K18593; 18K06375], and the Sumitomo Foundation  for Kanae Nishii.
Conflict of interest
The authors declare that they have no conflict of interest.
R/qtl v1.39-5 package code used here was obtained from https://rqtl.org/download/.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Electronic supplementary material
Below is the link to the electronic supplementary material.
About this article
Cite this article
Chen, YY., Nishii, K., Kidner, C. et al. QTL dissection of floral traits in Streptocarpus (Gesneriaceae). Euphytica 216, 110 (2020). https://doi.org/10.1007/s10681-020-02647-1
- Flower dimension
- Floral traits
- QTL mapping
- Standard interval mapping