Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

Genome-skimming provides accurate quantification for pollen mixtures Authors

Dandan Lang, Min Tang, Jiahui Hu, Xin Zhou
doi: https://doi.org/10.1101/408039
Dandan Lang
1Beijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, Beijing,100193, People’s Republic of China
2College of Food Science and Nutritional Engineering, China Agricultural University, Beijing, 100083, People’s Republic of China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Min Tang
1Beijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, Beijing,100193, People’s Republic of China
3College of Plant Protection, China Agricultural University, Beijing, 100193, People’s Republic of China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jiahui Hu
1Beijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, Beijing,100193, People’s Republic of China
3College of Plant Protection, China Agricultural University, Beijing, 100193, People’s Republic of China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Xin Zhou
1Beijing Advanced Innovation Center for Food Nutrition and Human Health, China Agricultural University, Beijing,100193, People’s Republic of China
3College of Plant Protection, China Agricultural University, Beijing, 100193, People’s Republic of China
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • For correspondence: xinzhou@cau.edu.cn
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

In the face of global pollinator declines, plant-pollinator interaction networks have been studied to guide ecological conservation and restoration. In order to obtain more comprehensive and unbiased knowledge of these networks, perspectives of both plants and pollinators need to be considered integratively. Metabarcoding has seen increasing applications in characterizing pollen transported by pollinators. However, amplification bias across taxa could lead to unpredictable artefacts in pollen compositions. We examined the efficacy of a PCR-free genome-skimming method in quantifying mixed pollen, using mock samples constructed with known pollen species (5 mocks of flower pollen and 14 mocks of bee pollen). The results demonstrated a high level of repeatability and accuracy in identifying pollen from mixtures of varied species ratios. All pollen species were detected in all mock samples, and pollen frequencies estimated from the number of sequence reads of each species were significantly correlated with pollen count proportions (linear model, R2 =86.7%, P = 2.2e- 16). For >97% of the mixed taxa, pollen proportion could be quantified by sequencing to the correct order of magnitude, even for species which constituted only 0.2% of the total pollen. We also showed that DNA extracted from pollen grains equivalent to those collected from a single honeybee corbicula was sufficient for the genome-skimming pipeline. We conclude that genome-skimming is a feasible approach to identifying and quantifying pollen compositions for mixed pollen samples. By providing reliable and sensitive taxon identification and relative abundance, this method is expected to improve the understanding of pollen diversity transported by pollinators and their ecological roles in the plant-pollinator networks.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
Back to top
PreviousNext
Posted September 04, 2018.
Download PDF

Supplementary Material

Email

Thank you for your interest in spreading the word about bioRxiv.

NOTE: Your email address is requested solely to identify you as the sender of this article.

Enter multiple addresses on separate lines or separate them with commas.
Genome-skimming provides accurate quantification for pollen mixtures Authors
(Your Name) has forwarded a page to you from bioRxiv
(Your Name) thought you would like to see this page from the bioRxiv website.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Genome-skimming provides accurate quantification for pollen mixtures Authors
Dandan Lang, Min Tang, Jiahui Hu, Xin Zhou
bioRxiv 408039; doi: https://doi.org/10.1101/408039
Digg logo Reddit logo Twitter logo Facebook logo Google logo LinkedIn logo Mendeley logo
Citation Tools
Genome-skimming provides accurate quantification for pollen mixtures Authors
Dandan Lang, Min Tang, Jiahui Hu, Xin Zhou
bioRxiv 408039; doi: https://doi.org/10.1101/408039

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
  • Tweet Widget
  • Facebook Like
  • Google Plus One

Subject Area

  • Ecology
Subject Areas
All Articles
  • Animal Behavior and Cognition (4113)
  • Biochemistry (8815)
  • Bioengineering (6519)
  • Bioinformatics (23462)
  • Biophysics (11789)
  • Cancer Biology (9209)
  • Cell Biology (13322)
  • Clinical Trials (138)
  • Developmental Biology (7436)
  • Ecology (11409)
  • Epidemiology (2066)
  • Evolutionary Biology (15150)
  • Genetics (10436)
  • Genomics (14043)
  • Immunology (9171)
  • Microbiology (22154)
  • Molecular Biology (8812)
  • Neuroscience (47569)
  • Paleontology (350)
  • Pathology (1428)
  • Pharmacology and Toxicology (2491)
  • Physiology (3730)
  • Plant Biology (8080)
  • Scientific Communication and Education (1437)
  • Synthetic Biology (2221)
  • Systems Biology (6037)
  • Zoology (1253)