Literature DB >> 33758263

Using RNA-seq to characterize pollen-stigma interactions for pollination studies.

Juan Lobaton1,2, Rose Andrew3, Jorge Duitama4, Lindsey Kirkland3, Sarina Macfadyen5, Romina Rader3.   

Abstract

Insects are essential for the reproduction of pollinator-dependent crops and contribute to the pollination of 87% of wild plants and 75% of the world's food crops. Understanding pollen flow dynamics between plants and pollinators is thus essential to manage and conserve wild plants and ensure yields are maximized in food crops. However, the determination of pollen transfer in the field is complex and laborious. We developed a field experiment in a pollinator-dependent crop and used high throughput RNA sequencing (RNA-seq) to quantify pollen flow by measuring changes in gene expression between pollination treatments across different apple (Malus domestica Borkh.) cultivars. We tested three potential molecular indicators of successful pollination and validated these results with field data by observing single and multiple visits by honey bees (Apis mellifera) to apple flowers and measured fruit set in a commercial apple orchard. The first indicator of successful outcrossing was revealed via differential gene expression in the cross-pollination treatments after 6 h. The second indicator of successful outcrossing was revealed by the expression of specific genes related to pollen tube formation and defense response at three different time intervals in the stigma and the style following cross-pollination (i.e. after 6, 24, and 48 h). Finally, genotyping variants specific to donor pollen could be detected in cross-pollination treatments, providing a third indicator of successful outcrossing. Field data indicated that one or five flower visits by honey bees were insufficient and at least 10 honey bee flower visits were required to achieve a 25% probability of fruit set under orchard conditions. By combining the genotyping data, the differential expression analysis, and the traditional fruit set field experiments, it was possible to evaluate the pollination effectiveness of honey bee visits under orchards conditions. This is the first time that pollen-stigma-style mRNA expression analysis has been conducted after a pollinator visit (honey bee) to a plant (in vivo apple flowers). This study provides evidence that mRNA sequencing can be used to address complex questions related to stigma-pollen interactions over time in pollination ecology.

Entities:  

Year:  2021        PMID: 33758263     DOI: 10.1038/s41598-021-85887-y

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  41 in total

Review 1.  A framework for comparing pollinator performance: effectiveness and efficiency.

Authors:  Gidi Ne'eman; Andreas Jürgens; Linda Newstrom-Lloyd; Simon G Potts; Amots Dafni
Journal:  Biol Rev Camb Philos Soc       Date:  2009-12-09

2.  Quantitative and qualitative assessment of pollen DNA metabarcoding using constructed species mixtures.

Authors:  Karen L Bell; Kevin S Burgess; Jamieson C Botsch; Emily K Dobbs; Timothy D Read; Berry J Brosi
Journal:  Mol Ecol       Date:  2018-09-07       Impact factor: 6.185

Review 3.  Pollen DNA barcoding: current applications and future prospects.

Authors:  Karen L Bell; Natasha de Vere; Alexander Keller; Rodney T Richardson; Annemarie Gous; Kevin S Burgess; Berry J Brosi
Journal:  Genome       Date:  2016-04-13       Impact factor: 2.166

4.  Pollen on stigmas as proxies of pollinator competition and facilitation: complexities, caveats and future directions.

Authors:  Tia-Lynn Ashman; Conchita Alonso; Victor Parra-Tabla; Gerardo Arceo-Gómez
Journal:  Ann Bot       Date:  2020-06-01       Impact factor: 4.357

5.  Stability of pollination services decreases with isolation from natural areas despite honey bee visits.

Authors:  Lucas A Garibaldi; Ingolf Steffan-Dewenter; Claire Kremen; Juan M Morales; Riccardo Bommarco; Saul A Cunningham; Luísa G Carvalheiro; Natacha P Chacoff; Jan H Dudenhöffer; Sarah S Greenleaf; Andrea Holzschuh; Rufus Isaacs; Kristin Krewenka; Yael Mandelik; Margaret M Mayfield; Lora A Morandin; Simon G Potts; Taylor H Ricketts; Hajnalka Szentgyörgyi; Blandina F Viana; Catrin Westphal; Rachael Winfree; Alexandra M Klein
Journal:  Ecol Lett       Date:  2011-08-02       Impact factor: 9.492

Review 6.  Importance of pollinators in changing landscapes for world crops.

Authors:  Alexandra-Maria Klein; Bernard E Vaissière; James H Cane; Ingolf Steffan-Dewenter; Saul A Cunningham; Claire Kremen; Teja Tscharntke
Journal:  Proc Biol Sci       Date:  2007-02-07       Impact factor: 5.349

7.  Increased efficiency in identifying mixed pollen samples by meta-barcoding with a dual-indexing approach.

Authors:  Wiebke Sickel; Markus J Ankenbrand; Gudrun Grimmer; Andrea Holzschuh; Stephan Härtel; Jonathan Lanzen; Ingolf Steffan-Dewenter; Alexander Keller
Journal:  BMC Ecol       Date:  2015-07-22       Impact factor: 2.964

8.  A DNA barcoding approach to characterize pollen collected by honeybees.

Authors:  Andrea Galimberti; Fabrizio De Mattia; Ilaria Bruni; Daniela Scaccabarozzi; Anna Sandionigi; Michela Barbuto; Maurizio Casiraghi; Massimo Labra
Journal:  PLoS One       Date:  2014-10-08       Impact factor: 3.240

9.  Evaluation of pollinator effectiveness based on pollen deposition and seed production in a gynodieocious alpine plant, Cyananthus delavayi.

Authors:  Hao Wang; Guo-Xing Cao; Lin-Lin Wang; Yong-Ping Yang; Zhi-Qiang Zhang; Yuan-Wen Duan
Journal:  Ecol Evol       Date:  2017-09-05       Impact factor: 2.912

10.  Time-Course Transcriptome Analysis of Compatible and Incompatible Pollen-Stigma Interactions in Brassica napus L.

Authors:  Tong Zhang; Changbin Gao; Yao Yue; Zhiquan Liu; Chaozhi Ma; Guilong Zhou; Yong Yang; Zhiqiang Duan; Bing Li; Jing Wen; Bin Yi; Jinxiong Shen; Jinxing Tu; Tingdong Fu
Journal:  Front Plant Sci       Date:  2017-05-03       Impact factor: 5.753

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  1 in total

1.  Imaging Flow Cytometry as a Quick and Effective Identification Technique of Pollen Grains from Betulaceae, Oleaceae, Urticaceae and Asteraceae.

Authors:  Iwona Gierlicka; Idalia Kasprzyk; Maciej Wnuk
Journal:  Cells       Date:  2022-02-09       Impact factor: 6.600

  1 in total

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