↓ Skip to main content

A molecular method to identify species of fine roots and to predict the proportion of a species in mixed samples in subtropical forests

Overview of attention for article published in Frontiers in Plant Science, May 2015
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

twitter
4 X users

Readers on

mendeley
38 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
A molecular method to identify species of fine roots and to predict the proportion of a species in mixed samples in subtropical forests
Published in
Frontiers in Plant Science, May 2015
DOI 10.3389/fpls.2015.00313
Pubmed ID
Authors

Weixian Zeng, Bo Zhou, Pifeng Lei, Yeling Zeng, Yan Liu, Cong Liu, Wenhua Xiang

Abstract

Understanding of belowground interactions among tree species and the fine root (≤2 mm in diameter) contribution of a species to forest ecosystem production are mostly restricted by experimental difficulties in the quantification of the species composition. The available approaches have various defects. By contrast, DNA-based methods can avoid these drawbacks. Quantitative real-time polymerase chain reaction (PCR) is an advanced molecular technology, but it is difficult to develop specific primer sets. The method of next-generation sequencing has several limitations, such as inaccurate sequencing of homopolymer regions, as well as being time-consuming, and requiring special knowledge for data analysis. This study evaluated the potential of the DNA-sequence-based method to identify tree species and to quantify the relative proportion of each species in mixed fine root samples. We discriminated the species by isolating DNA from individual fine roots and amplifying the plastid trnL(UAA; i.e., tRNA-Leu-UAA) intron using the PCR. To estimate relative proportions, we extracted DNA from fine root mixtures. After the plastid trnL(UAA) intron amplification and TA-cloning, we sequenced the positive clones from each mixture. Our results indicated that the plastid trnL(UAA) intron spacer successfully distinguished tree species of fine roots in subtropical forests. In addition, the DNA-sequence-based approach could reliably estimate the relative proportion of each species in mixed fine root samples. To our knowledge, this is the first time that the DNA-sequence-based method has been used to quantify tree species proportions in mixed fine root samples in Chinese subtropical forests. As the cost of DNA-sequencing declines and DNA-sequence-based methods improve, the molecular method will be more widely used to determine fine root species and abundance.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Chile 1 3%
Unknown 37 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 24%
Student > Master 8 21%
Researcher 7 18%
Professor 3 8%
Professor > Associate Professor 3 8%
Other 3 8%
Unknown 5 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 50%
Environmental Science 10 26%
Biochemistry, Genetics and Molecular Biology 2 5%
Earth and Planetary Sciences 1 3%
Chemistry 1 3%
Other 0 0%
Unknown 5 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 23 May 2015.
All research outputs
#14,223,874
of 22,803,211 outputs
Outputs from Frontiers in Plant Science
#8,139
of 20,080 outputs
Outputs of similar age
#138,786
of 264,554 outputs
Outputs of similar age from Frontiers in Plant Science
#102
of 275 outputs
Altmetric has tracked 22,803,211 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 20,080 research outputs from this source. They receive a mean Attention Score of 4.0. This one has gotten more attention than average, scoring higher than 55% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 264,554 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 44th percentile – i.e., 44% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 275 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.