CROPSR: A new tool to accelerate genetic discoveries
Software speeds up design of CRISPR experiments

Date:
February 17, 2022
Source:
University of Illinois at Urbana-Champaign Institute for
Sustainability, Energy, and Environment
Summary:
Scientists have developed CROPSR, the first open-source software
tool for genome-wide design and evaluation of guide RNA (gRNA)
sequences for CRISPR/Cas9 experiments. This tool significantly
shortens the time required to design a CRISPR experiment and
reduces the challenge of working with complex crop genomes. It
should accelerate bioenergy crop development as well as broader
crop improvements and other gene-editing research.



FULL STORY ========================================================================== Commercially viable biofuel crops are vital to reducing greenhouse gas emissions, and a new tool developed by the Center for Advanced Bioenergy
and Bioproducts Innovation (CABBI) should accelerate their development --
as well as genetic editing advances overall.


==========================================================================
The genomes of crops are tailored by generations of breeding to optimize specific traits, and until recently breeders were limited to selection
on naturally occurring diversity. CRISPR/Cas9 gene-editing technology
can change this, but the software tools necessary for designing and
evaluating CRISPR experiments have so far been based on the needs of
editing in mammalian genomes, which don't share the same characteristics
as complex crop genomes.

Enter CROPSR, the first open-source software tool for genome-wide design
and evaluation of guide RNA (gRNA) sequences for CRISPR experiments,
created by scientists at CABBI, a Department of Energy-funded Bioenergy Research Center (BRC). The genome-wide approach significantly shortens
the time required to design a CRISPR experiment, reducing the challenge
of working with crops and accelerating gRNA sequence design, evaluation,
and validation, according to the study published in BMC Bioinformatics.

"CROPSR provides the scientific community with new methods and a new
workflow for performing CRISPR/Cas9 knockout experiments," said CROPSR developer Hans Mu"ller Paul, a molecular biologist and Ph.D. student with co-author Matthew Hudson, Professor of Crop Sciences at the University
of Illinois Urbana- Champaign. "We hope that the new software will
accelerate discovery and reduce the number of failed experiments."
To better meet the needs of crop geneticists, the team built software that lifts restrictions imposed by other packages on design and evaluation of
gRNA sequences, the guides used to locate targeted genetic material. Team members also developed a new machine learning model that would not avoid
guides for repetitive genomic regions often found in plants, a problem
with existing tools. The CROPSR scoring model provided much more accurate predictions, even in non-crop genomes, the authors said.

"The goal was to incorporate features to make life easier for the
scientist," Mu"ller Paul said.



==========================================================================
Many crops, particularly bioenergy feedstocks, have highly complex
polyploid genomes, with multiple sets of chromosomes. And some
gene-editing software tools based on diploid genomes (like those from
humans) have trouble with the peculiarities of crop genomes.

"It can sometimes take weeks or months to realize that you don't have
the outcome that you expected," Mu"ller Paul said.

For example, a trait may be regulated by a collection of genes,
particularly one involving plant stress where backup systems are
useful. A scientist might design an experiment to knock out one gene and
be unaware of another that performs the same function. The problem may
not be discovered until the plant matures without altering the trait in
any way. It's a particular issue with crops that require specific weather conditions to grow, where missing a season could mean a year-long delay.

Using a genome-wide approach allowed the scientists to tailor CROPSR
for plant use by removing built-in biases found in existing software
tools. Because they are based on human or mouse genomes, where multiple
copies of genes are less common, those tools penalize gRNA sequences that
hit the genome in more than one position, to avoid causing mutations in
places where they're not intended.

But with crops, the goal is often to mutate more than one position to
knock out all copies of a gene. Previously, scientists sometimes had
to design four or five mutation experiments to knock out each gene individually, requiring extra time and effort.

CROPSR can generate a database of usable CRISPR guide RNAs for an entire
crop genome. That process is computationally intensive and time-consuming
-- usually requiring several days -- but researchers only have to do it
once to build a database that can then be used for ongoing experiments.



==========================================================================
So, rather than searching for a targeted gene through an online
database, then using current tools to design separate guides for five
different locations and doing multiple rounds of experiments, scientists
could search for the gene in their own database and see all the guides available. CROPSR would indicate other locations to target in the genome
as well. Researchers could select a guide that hits all of the genes,
making it much easier and quicker to design the experiment.

"You can just hop into the database, fetch all the information you need,
ready to go, and start working," Mu"ller Paul said. "The less time you
spend planning for your experiments, the more time you can spend doing
your experiments." For CABBI scientists, who often work with repetitive
plant genomes, having a gRNA tool that allows them to design functioning
guides with confidence "should be a step forward," he said.

As the name implies, CROPSR was designed with crop genomes in mind,
but it's applicable to any type of genome.

"CROPSR is also based on human genes, as the data availability for crop
genes just isn't there yet," Mu"ller Paul said, "but we're looking
into some collaborations with other BRCs to provide a more capable
prediction based on biophysics to help mitigate some of the issues caused
by the lack of data." Going forward, he hopes researchers will record
their failed results along with successes to help generate the data to
train a crop-specific model. If the collaborations pan out, "we could
be looking at some very interesting advancements in training machine
learning models for CRISPR applications, and potentially to other models
as well." The study's other co-authors are Dave Istanto, former CABBI
graduate student with Hudson in the U of I Department of Crop Sciences;
and Jacob Heldenbrand, former CABBI research programmer with the National Center for Supercomputing Applications at Illinois. Hudson and Mu"ller
Paul are also affiliated with the Illinois Informatics Institute and
the Carle R. Woese Institute for Genomic Biology.

========================================================================== Story Source: Materials provided by University_of_Illinois_at_Urbana-Champaign_Institute_for Sustainability,_Energy,_and_Environment. Original written by Julie
Wurth. Note: Content may be edited for style and length.


========================================================================== Journal Reference:
1. Hans Mu"ller Paul, Dave D. Istanto, Jacob Heldenbrand, Matthew
E. Hudson.

CROPSR: an automated platform for complex genome-wide CRISPR
gRNA design and validation. BMC Bioinformatics, 2022; 23 (1) DOI:
10.1186/s12859-022- 04593-2 ==========================================================================

Link to news story: https://www.sciencedaily.com/releases/2022/02/220217141336.htm

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