Abstract Title

Species identification of root samples using gene sequencing

Abstract

Tree species are typically identified using leaf and bark traits but identifying species by roots is extremely challenging and would not be feasible by morphological features. Currently, our lab is in the process of identifying roots from mixed species forests to compare belowground productivity between species. We will be using polymerase chain reaction (PCR) and sequencing to identify tree root presence. Four different genes (Matk, psb-trn, Rbcl, and ITS) have been identified as possible candidates for PCR identification. To test these genes, sequences have been downloaded from NCBI and compared using BioEdit. Not enough sequences were found for psb-trn in NCBI, so tests were unable to be run on this gene. Matk had very poor distinguishing ability and therefore was excluded from further testing.Using a single gene, Rbcl had the best ability to distinguish between species alone. There was one genus, Carya, could not be distinguished. Using a combination of ITS and Rbcl for single tree specimen samples 35/41 species could be identified. Four of the six that were unidentifiable were within the genus Carya. These results will be validated by sequencing our own tree samples with primers Rbcla-F and Rbcla-R, ITS-p5 and ITS-u2, and psbA3 and trnHf_05. Results for psb-trn genes will then be able to be compared with Rbcl and ITS. This information will then be used to test our larger hypothesizes to better understand positive and negative feedback loops within different tree species.

Modified Abstract

Tree species are typically identified using leaf and bark traits but identifying species by roots is not feasible. Currently, our lab is in the process of identifying roots from mixed species forests. We will use gene sequencing to identify tree roots. Four different genes (Matk, psb-trn, Rbcl, and ITS) have been identified as possible candidates for sequence identification. To test these genes, sequences have been downloaded from NCBI and analyzed. Using a combination of ITS and Rbcl for single tree specimen samples 35/41 species were able to be identified. These results will be validated by additional sequencing. Results of this sequencing will then be compared like the downloaded sequences. This information will then be used to conduct our larger experiment.

Research Category

Biology/Ecology

Primary Author's Major

Biotechnology

Mentor #1 Information

Dr. Christopher

Blackwood

Presentation Format

Poster

Start Date

April 2019

Research Area

Terrestrial and Aquatic Ecology

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Apr 9th, 1:00 PM

Species identification of root samples using gene sequencing

Tree species are typically identified using leaf and bark traits but identifying species by roots is extremely challenging and would not be feasible by morphological features. Currently, our lab is in the process of identifying roots from mixed species forests to compare belowground productivity between species. We will be using polymerase chain reaction (PCR) and sequencing to identify tree root presence. Four different genes (Matk, psb-trn, Rbcl, and ITS) have been identified as possible candidates for PCR identification. To test these genes, sequences have been downloaded from NCBI and compared using BioEdit. Not enough sequences were found for psb-trn in NCBI, so tests were unable to be run on this gene. Matk had very poor distinguishing ability and therefore was excluded from further testing.Using a single gene, Rbcl had the best ability to distinguish between species alone. There was one genus, Carya, could not be distinguished. Using a combination of ITS and Rbcl for single tree specimen samples 35/41 species could be identified. Four of the six that were unidentifiable were within the genus Carya. These results will be validated by sequencing our own tree samples with primers Rbcla-F and Rbcla-R, ITS-p5 and ITS-u2, and psbA3 and trnHf_05. Results for psb-trn genes will then be able to be compared with Rbcl and ITS. This information will then be used to test our larger hypothesizes to better understand positive and negative feedback loops within different tree species.