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Current Microbiology

, Volume 71, Issue 6, pp 650–657 | Cite as

New Primers Targeting Full-Length Ciliate 18S rRNA Genes and Evaluation of Dietary Effect on Rumen Ciliate Diversity in Dairy Cows

  • Jun Zhang
  • Shengguo Zhao
  • Yangdong Zhang
  • Peng Sun
  • Dengpan Bu
  • Jiaqi Wang
Article

Abstract

Analysis of the full-length 18S rRNA gene sequences of rumen ciliates is more reliable for taxonomical classification and diversity assessment than the analysis of partial hypervariable regions only. The objective of this study was to develop new oligonucleotide primers targeting the full-length 18S rRNA genes of rumen ciliates, and to evaluate the effect of different sources of dietary fiber (corn stover or a mixture of alfalfa hay and corn silage) and protein (mixed rapeseed, cottonseed, and/or soybean meals) on rumen ciliate diversity in dairy cows. Primers were designed based on a total of 137 previously reported ciliate 18S rRNA gene sequences. The 3′-terminal sequences of the newly designed primers, P.1747r_2, P.324f, and P.1651r, demonstrated >99 % base coverage. Primer pair D (P.324f and P.1747r_2) was selected for the cloning and sequencing of ciliate 18S rRNA genes because it produced a 1423-bp amplicon, and did not amply the sequences of other eukaryotic species, such as yeast. The optimal species-level cutoff value for distinguishing between the operational taxonomic units of different ciliate species was 0.015. The phylogenetic analysis of full-length ciliate 18S rRNA gene sequences showed that distinct ciliate profiles were induced by the different sources of dietary fiber and protein. Dasytricha and Entodinium were the predominant genera in the ruminal fluid of dairy cattle, and Dasytricha was significantly more abundant in cows fed with corn stover than in cows fed with alfalfa hay and corn silage.

Keywords

rRNA Gene Sequence Corn Stover Cottonseed Meal Corn Silage Ruminal Fluid 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This study was funded by grants from the National Natural Science Foundation of China (Grant No. 31261140365), the National Key Basic Research Program of China (Grant No. 2011CB100804), and Agricultural Science and Technology Innovation Program (Grant No. ASTIP-IAS07).

Compliance with Ethical Standards

Conflict of interest

No conflict of interest declared.

Supplementary material

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Supplementary material 1 (DOC 40 kb)
284_2015_898_MOESM2_ESM.docx (33 kb)
Supplementary material 2 (DOCX 33 kb)
284_2015_898_MOESM3_ESM.tif (1.2 mb)
Supplementary material 3 (TIFF 1253 kb)

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.State Key Laboratory of Animal Nutrition, Institute of Animal SciencesChinese Academy of Agricultural SciencesBeijingPeople’s Republic of China
  2. 2.CAAS-ICRAF Joint Laboratory on Agroforestry and Sustainable Animal Husbandry (ASAH)World Agroforestry Centre, East and Central AsiaBeijingPeople’s Republic of China
  3. 3.Synergetic Innovation Center of Food Safety and NutritionHarbinPeople’s Republic of China

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