Premium
Molecular identification of roots from a grassland community using size differences in fluorescently labelled PCR amplicons of three cpDNA regions
Author(s) -
TAGGART JOHN M.,
CAHILL JR JAMES F.,
McNICKLE GORDON G.,
HALL JOCELYN C.
Publication year - 2011
Publication title -
molecular ecology resources
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.96
H-Index - 136
eISSN - 1755-0998
pISSN - 1755-098X
DOI - 10.1111/j.1755-0998.2010.02893.x
Subject(s) - biology , amplicon , grassland , intergenic region , internal transcribed spacer , botany , polymerase chain reaction , genetics , ecology , ribosomal rna , gene , genome
Elucidating patterns of root growth is essential for a better understanding of the functioning of plant‐dominated ecosystems. To this end, reliable and inexpensive methods are required to determine species compositions of root samples containing multiple species. Previous studies use a range of PCR‐based approaches, but none have examined a species pool greater than 10 or 30 when evaluating mixed and single species samples, respectively. We present a method that evaluates size differences in fluorescently labelled PCR amplicons (fluorescent fragment length polymorphism) of the trn L intron and the trn T‐ trn L and trn L‐ trn F intergenic spacers . Amplification success of the trn T‐ trn L spacer was limited, but variation in the trn L intron and the trn L‐ trn F spacer was sufficient to distinguish over 80% of the 95 species (97% of the 77 genera) evaluated from a diverse fescue grassland community. Moreover, we identified species known to be present in mixed samples of 4, 8, 12, and 16 species on average 82% of the time. However, this approach is sensitive to detecting species known to be absent (false positives) when using our key of 95 species. Comparing unknowns to a limited species pool ameliorates this problem, comparable to a researcher using prior knowledge of what species could be found in a sample to constrain the identification of species. Comparisons to other methods and future improvements are discussed. This method is efficient, cost‐ effective and broadly applicable to many ecosystems.