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Identification of successive flowering phases highlights a new genetic control of the flowering pattern in strawberry.

ABSTRACT: The genetic control of the switch between seasonal and perpetual flowering has been deciphered in various perennial species. However, little is known about the genetic control of the dynamics of perpetual flowering, which changes abruptly at well-defined time instants during the growing season. Here, we characterize the perpetual flowering pattern and identify new genetic controls of this pattern in the cultivated strawberry. Twenty-one perpetual flowering strawberry genotypes were phenotyped at the macroscopic scale for their course of emergence of inflorescences and stolons during the growing season. A longitudinal analysis based on the segmentation of flowering rate profiles using multiple change-point models was conducted. The flowering pattern of perpetual flowering genotypes takes the form of three or four successive phases: an autumn-initiated flowering phase, a flowering pause, and a single stationary perpetual flowering phase or two perpetual flowering phases, the second one being more intense. The genetic control of flowering was analysed by quantitative trait locus mapping of flowering traits based on these flowering phases. We showed that the occurrence of a fourth phase of intense flowering is controlled by a newly identified locus, different from the locus FaPFRU, controlling the switch between seasonal and perpetual flowering behaviour. The role of this locus was validated by the analysis of data obtained previously during six consecutive years.

SUBMITTER: Perrotte J

PROVIDER: S-EPMC5066487 | biostudies-literature | 2016 Oct

REPOSITORIES: biostudies-literature

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Identification of successive flowering phases highlights a new genetic control of the flowering pattern in strawberry.

Perrotte Justine J Guédon Yann Y Gaston Amèlia A Denoyes Béatrice B

Journal of experimental botany 20160924 19

The genetic control of the switch between seasonal and perpetual flowering has been deciphered in various perennial species. However, little is known about the genetic control of the dynamics of perpetual flowering, which changes abruptly at well-defined time instants during the growing season. Here, we characterize the perpetual flowering pattern and identify new genetic controls of this pattern in the cultivated strawberry. Twenty-one perpetual flowering strawberry genotypes were phenotyped at ...[more]

PMID: 27664957

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Project description:BACKGROUND: We are studying the regulation of flowering in perennial plants by using diploid wild strawberry (Fragaria vesca L.) as a model. Wild strawberry is a facultative short-day plant with an obligatory short-day requirement at temperatures above 15 degrees C. At lower temperatures, however, flowering induction occurs irrespective of photoperiod. In addition to short-day genotypes, everbearing forms of wild strawberry are known. In 'Baron Solemacher' recessive alleles of an unknown repressor, SEASONAL FLOWERING LOCUS (SFL), are responsible for continuous flowering habit. Although flower induction has a central effect on the cropping potential, the molecular control of flowering in strawberries has not been studied and the genetic flowering pathways are still poorly understood. The comparison of everbearing and short-day genotypes of wild strawberry could facilitate our understanding of fundamental molecular mechanisms regulating perennial growth cycle in plants. RESULTS: We have searched homologs for 118 Arabidopsis flowering time genes from Fragaria by EST sequencing and bioinformatics analysis and identified 66 gene homologs that by sequence similarity, putatively correspond to genes of all known genetic flowering pathways. The expression analysis of 25 selected genes representing various flowering pathways did not reveal large differences between the everbearing and the short-day genotypes. However, putative floral identity and floral integrator genes AP1 and LFY were co-regulated during early floral development. AP1 mRNA was specifically accumulating in the shoot apices of the everbearing genotype, indicating its usability as a marker for floral initiation. Moreover, we showed that flowering induction in everbearing 'Baron Solemacher' and 'Hawaii-4' was inhibited by short-day and low temperature, in contrast to short-day genotypes. CONCLUSION: We have shown that many central genetic components of the flowering pathways in Arabidopsis can be identified from strawberry. However, novel regulatory mechanisms exist, like SFL that functions as a switch between short-day/low temperature and long-day/high temperature flowering responses between the short-day genotype and the everbearing 'Baron Solemacher'. The identification of putative flowering gene homologs and AP1 as potential marker gene for floral initiation will strongly facilitate the exploration of strawberry flowering pathways.

Project description:Brinjal (Solanum melongena), scarlet (S. aethiopicum) and gboma (S. macrocarpon) eggplants are three Old World domesticates. The genomic DNA of a collection of accessions belonging to the three cultivated species, along with a representation of various wild relatives, was characterized for the presence of single nucleotide polymorphisms (SNPs) using a genotype-by-sequencing approach. A total of 210 million useful reads were produced and were successfully aligned to the reference eggplant genome sequence. Out of the 75,399 polymorphic sites identified among the 76 entries in study, 12,859 were associated with coding sequence. A genetic relationships analysis, supported by the output of the FastSTRUCTURE software, identified four major sub-groups as present in the germplasm panel. The first of these clustered S. aethiopicum with its wild ancestor S. anguivi; the second, S. melongena, its wild progenitor S. insanum, and its relatives S. incanum, S. lichtensteinii and S. linneanum; the third, S. macrocarpon and its wild ancestor S. dasyphyllum; and the fourth, the New World species S. sisymbriifolium, S. torvum and S. elaeagnifolium. By applying a hierarchical FastSTRUCTURE analysis on partitioned data, it was also possible to resolve the ambiguous membership of the accessions of S. campylacanthum, S. violaceum, S. lidii, S. vespertilio and S. tomentsum, as well as to genetically differentiate the three species of New World Origin. A principal coordinates analysis performed both on the entire germplasm panel and also separately on the entries belonging to sub-groups revealed a clear separation among species, although not between each of the domesticates and their respective wild ancestors. There was no clear differentiation between either distinct cultivar groups or different geographical provenance. Adopting various approaches to analyze SNP variation provided support for interpretation of results. The genotyping-by-sequencing approach showed to be highly efficient for both quantifying genetic diversity and establishing genetic relationships among and within cultivated eggplants and their wild relatives. The relevance of these results to the evolution of eggplants, as well as to their genetic improvement, is discussed.

Project description:Algorithms for motif identification in sequence space have predominately been focused on recognizing patterns of a fixed length containing regions of perfect conservation with possible regions of unconstrained sequence. Such motifs can be found in everything from proteins with distinct active sites to non-coding RNAs with specific structural elements that are necessary to maintain functionality. In the event that an insertion/deletion has occurred within an unconstrained portion of the pattern, it is possible that the pattern retains its functionality. In such a case the length of the pattern is now variable and may be overlooked when utilizing existing motif detection methods. The Pattern Island Detection Algorithm (PIDA) presented here has been developed to recognize patterns that have occurrences of varying length within sequences of any size alphabet. PIDA works by identifying all regions of perfect conservation (for lengths longer than a user-specified threshold), and then builds those conservation "islands" into fixed-length patterns. Next the algorithm modifies these fixed-length patterns by identifying additional (and different) islands that can be incorporated into each pattern through insertions/deletions within the "water" separating the islands. To provide some benchmarks for this analysis, PIDA was used to search for patterns within randomly generated sequences as well as sequences known to contain conserved patterns. For each of the patterns found, the statistical significance is calculated based upon the pattern's likelihood to appear by chance, thus providing a means to determine those patterns which are likely to have a functional role. The PIDA approach to motif finding is designed to perform best when searching for patterns of variable length although it is also able to identify patterns of a fixed length. PIDA has been created to be as generally applicable as possible since there are a variety of sequence problems of this type. The algorithm was implemented in C++ and is freely available upon request from the authors.

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Identification of successive flowering phases highlights a new genetic control of the flowering pattern in strawberry.

Publications

Identification of successive flowering phases highlights a new genetic control of the flowering pattern in strawberry.

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