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Bermuda Land Snails make up a genus called Poecilozonites that is endemic to Bermuda and is extensively present in its fossil record. These snails were also integral to the creation of the theory of punctuated equilibrium. The DNA of mollusks is difficult to sequence because of a class of proteins called mucopolysaccharides that are present in high concentrations in mollusk tissue, and are not removed with standard DNA extraction methods. They inhibit Polymerase Chain Reactions (PCRs) and interfere with Next Generation Sequencing methods. This paper will discuss the DNA extraction methods that were designed to remove the inhibitory proteins that were tested on another gastropod species (Pomacea canaliculata). These were chosen because they are invasive and while they are not pulmonates, they are similar enough to Bermuda Land Snails to reliably test extraction methods. The methods that were tested included two commercially available kits: the Qiagen Blood and Tissue Kit and the Omega Biotek Mollusc Extraction Kit, and one Hexadecyltrimethylammonium Bromide (CTAB) Extraction method that was modified for use on mollusk tissue. The Blood and Tissue kit produced some DNA, the mollusk kit produced almost none, and the CTAB Extraction Method produced the highest concentrations on average, and may prove to be the most viable option for future extractions. PCRs attempted with the extracted DNA have all failed, though it is likely due to an issue with reagents. Further spectrographic analysis of the DNA from the test extractions has shown that they were successful at removing mucopolysaccharides. When the protocol is optimized, it will be used to extract DNA from the tissue from six individuals from each of the two extant species of Bermuda Land Snails. This DNA will be used in several experiments involving Next Generation Sequencing, with the goal of assembling a variety of genome data. These data will then be used to a construct reference genome for Bermuda Land Snails. The genomes generated by this project will be used in population genetic analyses between individuals of the same species, and between individuals of different species. These analyses will then be used to aid in conservation efforts for the species.
This can make mutation detection difficult; and while increasing sequencing depth
can often help, sequence-specific errors and other non-random biases cannot be de-
tected by increased depth. The problem of accurate genotyping is exacerbated when
there is not a reference genome or other auxiliary information available.
I explore several methods for sensitively detecting mutations in non-model or-
ganisms using an example Eucalyptus melliodora individual. I use the structure of
the tree to find bounds on its somatic mutation rate and evaluate several algorithms
for variant calling. I find that conventional methods are suitable if the genome of a
close relative can be adapted to the study organism. However, with structured data,
a likelihood framework that is aware of this structure is more accurate. I use the
techniques developed here to evaluate a reference-free variant calling algorithm.
I also use this data to evaluate a k-mer based base quality score recalibrator
(KBBQ), a tool I developed to recalibrate base quality scores attached to sequencing
data. Base quality scores can help detect errors in sequencing reads, but are often
inaccurate. The most popular method for correcting this issue requires a known
set of variant sites, which is unavailable in most cases. I simulate data and show
that errors in this set of variant sites can cause calibration errors. I then show that
KBBQ accurately recalibrates base quality scores while requiring no reference or other
information and performs as well as other methods.
Finally, I use the Eucalyptus data to investigate the impact of quality score calibra-
tion on the quality of output variant calls and show that improved base quality score
calibration increases the sensitivity and reduces the false positive rate of a variant
calling algorithm.