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

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 ensu...

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Autores principales:	Juan Lobaton, Rose Andrew, Jorge Duitama, Lindsey Kirkland, Sarina Macfadyen, Romina Rader
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/0568729d0a444842b7c683a63e80403e
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spelling	oai:doaj.org-article:0568729d0a444842b7c683a63e80403e2021-12-02T11:45:01ZUsing RNA-seq to characterize pollen–stigma interactions for pollination studies10.1038/s41598-021-85887-y2045-2322https://doaj.org/article/0568729d0a444842b7c683a63e80403e2021-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-021-85887-yhttps://doaj.org/toc/2045-2322Abstract 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.Juan LobatonRose AndrewJorge DuitamaLindsey KirklandSarina MacfadyenRomina RaderNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 11, Iss 1, Pp 1-12 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Juan Lobaton Rose Andrew Jorge Duitama Lindsey Kirkland Sarina Macfadyen Romina Rader Using RNA-seq to characterize pollen–stigma interactions for pollination studies
description	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.
format	article
author	Juan Lobaton Rose Andrew Jorge Duitama Lindsey Kirkland Sarina Macfadyen Romina Rader
author_facet	Juan Lobaton Rose Andrew Jorge Duitama Lindsey Kirkland Sarina Macfadyen Romina Rader
author_sort	Juan Lobaton
title	Using RNA-seq to characterize pollen–stigma interactions for pollination studies
title_short	Using RNA-seq to characterize pollen–stigma interactions for pollination studies
title_full	Using RNA-seq to characterize pollen–stigma interactions for pollination studies
title_fullStr	Using RNA-seq to characterize pollen–stigma interactions for pollination studies
title_full_unstemmed	Using RNA-seq to characterize pollen–stigma interactions for pollination studies
title_sort	using rna-seq to characterize pollen–stigma interactions for pollination studies
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/0568729d0a444842b7c683a63e80403e
work_keys_str_mv	AT juanlobaton usingrnaseqtocharacterizepollenstigmainteractionsforpollinationstudies AT roseandrew usingrnaseqtocharacterizepollenstigmainteractionsforpollinationstudies AT jorgeduitama usingrnaseqtocharacterizepollenstigmainteractionsforpollinationstudies AT lindseykirkland usingrnaseqtocharacterizepollenstigmainteractionsforpollinationstudies AT sarinamacfadyen usingrnaseqtocharacterizepollenstigmainteractionsforpollinationstudies AT rominarader usingrnaseqtocharacterizepollenstigmainteractionsforpollinationstudies
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Using RNA-seq to characterize pollen–stigma interactions for pollination studies

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