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Poster Full Abstracts - Techniques and Functional Genomics
Poster board number is above title. The first author is the presenter
358
848B
FlyExpress: A Platform for Discovering Co-expressed Genes via Comparative Image Analysis of Spatial Patterns in Drosophila Embryogenesis.
Michael E. McCutchan
2
, Sudhir Kumar
1,2
, Stuart J Newfeld
1,2
. 1) School of Life Sciences, Arizona State Univ, Tempe, AZ; 2) Center for Evolutionary
Medicine and Informatics, Biodesign Institute, Arizona State Univ, Tempe, AZ.
Images containing spatial expression patterns illuminate the roles of different genes during embryogenesis. Overlaps in expression patterns are frequently
an initial clue to genetic regulatory interactions. FlyExpress is a web resource that facilitates the discovery of putatively interacting genes during Drosophila
embryogenesis. It contains a library of >100,000 standardized expression images from >4500 genes from two high throughput sources (BDGP and FlyFISH)
and from >2,600 peer-reviewed publications. All images have been uniformly oriented, aligned, and scaled allowing direct comparison by gene across stages
and anatomical views. FlyExpress provides tools to automatically identify co-expressed and, thus potentially co-regulated, genes by searching for other
genes with similar expression profiles. Our search tool directly compares expression pattern images and emulates biologists’ practices of manual inspection.
The image atlas can now be searched for fly genes that are homologenes of other species, and results can now be exported to CSV files for offline browsing
and analysis. In addition, FlyExpress provides global views of gene activity across each developmental stage through Genomewide-Expression-Maps
(GEMs). GEMs are two-dimensional heat maps that synthesize individual spatial patterns into genomic summaries. By simple point-and-click, one can query
GEMs directly to produce a list of genes expressed or not expressed in any region of the embryo or to display all publications reporting gene expression at
any given embryo coordinate. Users can also create GEMs for their own list of genes. Therefore, the FlyExpress platform is designed to meet needs of
biologists to identify genes with similar expression patterns, judge the biological relevance of these matches within the complexities and subtlety of the
developmental process, generate novel gene interaction hypotheses, and visualize genome-scale summary of gene expression relevant to development.
849C
Machine Learning Approaches for Drosophila Expression Image Analysis.
Lei Yuan, Cheng Pan, Shuiwang Ji, Sudhir Kumar, Jieping Ye. Arizona
State University, Tempe, AZ.
Today, more than a hundred thousand images of spatial patterns of gene expression have recently become available in a canonical model organism
(Drosophila melanogaster) for understanding how a single cell, through gene expression and interaction, transforms into a complex organism. Efficient and
accurate analyses of these images will provide the next generation of scientists biological insights into gene functions, interactions, and networks. Currently,
many tasks in biological image analysis including the developmental stage and term annotation are conducted manually by domain experts. This manual
practice does not scale with the continuously expanding collection of images, and it proves to be a major impediment in making discoveries. Therefore, we
developed novel computational methods for the automated annotation of expression images. For stage annotation, we obtained a collection of about 5000
images annotated with precise stages by expert biologists. Gabor filters were adopted for feature extraction, and sparse structure of the feature space was
exploited using a group lasso formulation for predicting the developmental time at the stage level. In the context of developmental term annotation, we
employed state-of-the-art sparse learning techniques to construct robust representation of the expression images, overcoming the limitations of prior
schemes. The proposed computational systems achieve promising results for both developmental stage and term annotation tasks.
850A
Targeted Gene Conversion, an efficient method to engineer endogenous genes.
Manasi Apte
1
, Victoria Moran
1
, Richard Kelley
2
, Victoria Meller
1
. 1)
Biological Sciences, Wayne State University,MI; 2) Molecular and Human Genetics, Baylor College of Medicine,TX.
Engineering
Drosophila
genes at their endogenous location is quite challenging. Techniques such as ends-in and ends-out recombination are widely used
but labor intensive. We have tested a relatively simple and efficient genome engineering technique that we call ‘Targeted Gene Conversion'. This multi-step
approach starts with creation of a template P-element containing the engineered target sequence and a phenotypic marker, such as
w
+mC
. The template is
moved close to the site of desired change by targeted transposition, using an existing P-element as a target. Once the template is in place, it is re-mobilized to
create a dsDNA break. If gap repair occurs using a sister chromatid template, a gene conversion that substitutes the engineered template for sequence near
the break site can result.
w
+mC
is eliminated when repair utilizes homology between the engineered target sequence and the region surrounding the break site.
Our technique requires the presence of a P-element in the vicinity of the site to be engineered. However, our preliminary studies suggest that sites 0.5 to 1kb
from an existing P-element may be engineered with reasonable efficiency. As a proof of principle, we have introduced a tag of six tandem MS2 loops into
the
roX1
gene.
roX1
is a long non-coding RNA that assembles with the Male Specific Lethal (MSL) proteins to facilitate X-chromosome dosage
compensation in male flies. MS2 loops interact with MS2 coat protein (MCP) in the MS2 bacteriophage. MS2 loop tagged RNAs can be visualized with an
MCP-GFP fusion protein. We found that 10% of re-mobilized chromosomes that had lost
w
+mC
had incorporated MS2 loops into the endogenous
roX1
gene.
The 322 bp MS2 loops are over 400 bp from the point of insertion, suggesting that repair tracts capable of incorporating large amounts of non-homologous
sequence occur frequently. To assess the generality of this technique, we are currently engineering mutated and tagged versions of the autosomal
CTCF
gene.
851B
Comparing TALENS with Zinc Finger Nucleases in Drosophila.
Kelly J. Beumer
1
, Michelle Christian
2
, Jon Trautman
1
, Daniel F. Voytas
2
, Dana Carroll
1
.
1) Dept Biochem, Univ Utah, Salt Lake City, UT; 2) Dept GCD, Univ Minnesota, Minneapolis, MI.
Introduction of a double-strand break (DSB) in chromosomal DNA stimulates repair by recombination in the vicinity of the break. We have previously
shown that zinc finger nucleases can be used to create targeted breaks in the Drosophila genome that are repaired either through non-homologous end
joining, or through homologous recombination. However, design of effective ZFNs remains complicated and somewhat empirical. Recently, a new class of
DNA binding domains, transcription activator-like effectors (TALE), has been described and used to target the FokI nuclease (TALENs). Each TALE repeat
binds a single base pair in the DNA target, thereby simplifying design, and there seem to be fewer context effects than with zinc fingers. We are testing the
function of TALENs in Drosophila, and comparing their use and effectiveness to our previously described ZFNs. We will report on TALENs targeting the
ry
and
y
genes of Drosophila.
852C