You can do WHAT with GenomeQuest? (Almost) 101 things you may not know

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You can do WHAT with GenomeQuest?
(Almost) 101 things you may not know
Ellen Sherin
Sr. Product Manager
GQ Life Sciences
Ellen.Sherin@aptean.com

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Overview

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Query Design

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Anticipatory Searching
In text searching we try to allow for all possibilities: alternate (flavor/flavour) or
mis-spellings, synonyms, other possibilities
N76D, N-76-D, N 76 D, N/76/D, asp76asn, ASP-76-ASN, “position 76 may be
asp (aspartic acid) or asn (asparagine) or it may be deleted”
We do the same for sequence searching, but consider the ways a sequence can
be represented, in both query design and result analysis.

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First the Basics -
Where do Sequences Come From?
How was a sequence described by the inventor?
• In generalities? “Any protease from a micro-organism”
• As a cross-reference “Genbank accession
number ABC12345”
• Was a listing filed? Part of a table? Shown in
an alignment in an image?
• Or is the whole thing very difficult to decipher?
• Are there multiple Markush positions, represented by
Xaa and described in words?
• Are subsequences called out?
If it’s not in the listing, or at least written out as a sequence
somewhere, it’s probably not in any sequence database!

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US 20150087572
In one aspect, an automatic dishwashing detergent composition
comprising a variant protease of a parent protease, said parent
protease amino acid sequence being identical to the amino acid
sequence of SEQ ID NO:1, said variant protease of said parent protease
mutations consisting of one of the following sets of mutations versus
said parent protease:
(i) N76D + S87R + G118R + S128L + P129Q + S130A
Markush Sequences
GQ Motif algorithm can find
sequences IF they are present in
the sequence listing…most variants
ARE NOT!

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Retrieves records and/or sequences by patent
number, so you can:
• Create a saved, searchable virtual database;
• Obtain sequence(s) for download and ultimate use
in sequence listing, IDS prep, other molecular
biology programs;
• Review through GUI or download or both;
• Link out to public patent sources;
• With Platinum subscription, download full text PDF
Patent Number Searches
GenomeQuest Keyword Interface

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Search Setup

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Save Your Preferred Search Settings

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Make Your Own Database
Three Different Ways!
1. Upload your own sequences into GQ
2. Through Keyword Search>browse protein (or
DNA), filter as desired, and make into database
3. From your search results via
Analyses>Extract sequences>Subject sequences
These Virtual Databases (vDBs) can be selected
to search normally as if they were any regular
database like GQ-Pat.

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1. Upload Your Own Sequences into GQ
• Any standard format – GENBANK, EMBL,
FASTA file containing one or many sequences
• Must be just protein or just nucleotide.
• Will show up under MY DATA

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2. Browse Database, Save as vDB
• Just DNA or just protein
• Best way is to “browse” DNA or protein databases then filter for your desired
criteria
• Although a vDB can be created from text search results, if you haven’t “hard-
coded” JUST protein or DNA, it won’t show up in your search database choices

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Result View

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3. Make vDB from Search Results
Results must be just DNA or just protein; don’t use
mixed results.

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CDR Query Setup
• You can design a query to look for CDRs in isolation, or all three in a
single subject, or both!
• If you want the exact CDR sequence (or sequence with specified
variations) MOTIF is the best option, and is the only algorithm that
works for a single query, linking all three CDRs.
• If you want non-specific variability, then GenePast should be used,
limiting number of differences.
• Later on we’ll see how to GROUP results to detect one subject
comprising multiple queries.
• This method is not limited to CDRs; it’s applicable for any group of
subsequences contained in a single, longer sequence.

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MOTIF on full length – Direct Strike
The long sequence gives hits comprising all three CDRs in the specific order
provided. *. Represents “any number of unspecified residues, including zero”. If
there is even a single mismatch, or the order is incorrect, it will not be found. If a
CDR in the database uses Xaa, it will not be found unless specified in the query
sequence as an alternative to the wt amino acid.
>37-motif
DLSIH.*GFDPQDGETIYAQKFQG.*GSSSSWFDP
>9-motif
RASQGISSWLA.*GASNLES.*QQANSFPWT
Note the relationship between
the two long sequences. There
were 27 patents hit, and both
sequences are present in all 27.
LC and HC perhaps?

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Methodology – Searching CDRs
All 3 CDRs in subject or patent
Here we are searching the three CDRs in
isolation. This can be done with either MOTIF
or GenePast. Click on the intersection to see
all 27 patents that contain all three queries.
Extra credit – how many results will you get on
the results view?
The 27 patents will
contain all three
CDRs; however, are
they present in
isolation, in a specific
subject, or both?
81 minimum (3 x 27)

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CDR Query Comments
• We recommend searching all three (or six) CDRs
as individual sequences.
• The concatentated query is very useful for a direct
strike, but shouldn’t be used exclusively, as you will
miss hits to individual CDRs.
• This accomplishes the same thing as grouping by
subject, but it’s more specific and you get a smaller
number of results (1/3 as many in this case).
CDR1 CDR2 CDR3anything anything

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• [KX] equivalent to anything, it will retrieve K or anything else, including X,
in that position.
• Degeneracy characters in subject not found automatically; they have to be
searched explicitly.
– [KV] will find either K or V, but not X.
– [GA] will find either G or A but not R
• Degeneracy characters in query interpreted as what they represent:
[NACGTURYK MSWBDHV][R GA][YTUC][ SGC][WATU]
• Always consider how an inventor might represent a sequence in the
listing, and consider either using degeneracy characters (nucleotide) or
including an explicit X in protein queries.
• There’s a special way to search for that explicit X.
• Tip: look at the query sequence in MOTIF results, it will be written out with
the degeneracy characters expanded (e.g. N will be written as AGCT)
Degeneracy Characters are Difficult!

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For More on Variable Sequences

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SNP Queries
• Use the MOTIF algorithm to search for 100% identity to either allele.
• Reminder: with a single mismatch anywhere, MOTIF will not find the
hit!
• GenePast/Blast are also good choices; use coordinate filters to select
only those results crossing the SNP region(s).

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Results Overview
Intermediate Page

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Lots of Good Information Here
• Correct query sequence count
• Count of sequences that didn’t have hits
• Is your total hit count < your max?
• Be sure to understand the Venn – it is on
the PATENT level, not subject
• For >3 queries, you can use the Statistics
Report functionality

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Intermediate
Page

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Analysis Report for > 3 Queries

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Intermediate Page Analysis
Validate results, look for fundamental issues:
• Do I have at least one hit for each of my query sequences?
• Repeat this overview after applying each filter set
• Did I “max out” my results?
• Set my max for 500 (default) and at least one query has 500 results

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Analysis

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Are All My Queries Present?

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You Can Have Many Analysis Views
• Multiple views can be saved and switching between them is as simple
as a mouse click

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Customized Views for Analysis
Numeric
Bibliographic

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Views are Created by
DEFINE COLUMNS

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• The heart of GQ’s power
• Full Boolean with nesting capabilities
• Just like views, you can save multiple filters
• Very flexible combinations
• GUI allows on-the-fly changes – try it, you don’t like it then try something
else!
– I often use this capability to narrow down large resultsets by finding a
cutoff that affects the majority of results
• The AUDIT TRAIL page (found in exported Excel files) includes the applied
filters.
– I add a screenshot of my filters and paste it into the report for readability.
GenomeQuest Filters

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My Starting Point Nested Boolean Filter
In order to get the most out of GQ, you need to really
understand the different percent identities: query, subject
and alignment!

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Wildcarding Works!
MultipleValuesare“OR”

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Text ANDing

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GenePast Gap Filters
• Huge improvement! Converted me from Blast.
• Prior issue was Query % ID ignored gaps, so you could get hits with
multiple gaps show up as 100% Query ID.

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InDel Detection with Gap Filters
INDEL Type Query
Gaps
Subject
Gaps
Alignment
Insertion
mutant
1 0
Deletion
mutant
0 1
One of each 1 1
Additional use – INDEL detection!
(thanks Bjarne!)

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Can Also Display for InDel Analysis

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SNP Detection – Coordinate Filter
• SNP analysis often focuses on specific position(s), therefore the overall
% identities are frequently irrelevant.
• Only those alignments that cover the region of interest will pass
screening
• Use coordinates to narrow to these regions

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SNP Detection – Coordinate
Filters
Example : SNP is at position 1501
Filter for Query Start <=1500 and Query Stop >=1502

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Viewing Alignments

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• Results can be grouped for immediate feedback
How many families/patents/sequences pass these filters?
Are there any hits (including SIDs) that contain multiple query
sequences?
Which subjects contain:
My three CDRs?
My unique promoter and gene?
Variation 1 but not Variation 2?
Grouping

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Grouping
Find queries (or patents or families) with a disproportionate hit count

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A New Way to Analyze Data
– GQ’s New Result Browser
• Simplified Interface
• Very different viewing and analysis paradigm
• YOU CAN EXPORT ALIGNMENTS (coming right up!)

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Single Step Analysis of
Patent, Family, UFS Distribution

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Universal Family Sequence
A Special Beast
• Purpose is to show distribution of the identical
sequence within a given family
• The identical sequence may have many different
UFS values . Any given UFS value is only unique
for a single family.
• THERE IS NO GUARANTEE THAT THE SEQ ID
NO AND/OR PSL IS IDENTICAL FOR A GIVEN
UFS throughout the family.
• It is extremely useful for studying the distribution of
a sequence hit of interest throughout a family

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UFS PSL, SID variability

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Reporting Tips & Tricks

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Share Your Results
1. Create a folder for
results
2. Make it a shared folder
3. Set Permissions
4. Move Results to Folder

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Reporting Tricks & Tips
• Share results with other GQ users
• Visualize subjects, patents or both containing multiple query
sequences
• View alignments adjacent to full text of claims through LifeQuest
• IDS and ST25 Preparation
• Export alignments
• Family portrait, result analysis
• Excel tips:
– Freeze top row
– Link back from Excel to each alignment and make that link
available to other licensed GQ users
– Prepare Excel pivot tables summarizing search results which
can easily be changed to summarize results by many different
parameters

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Visualize Multiple Queries
Aligned to a Single Subject

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View Claims Adjacent to Alignments

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• Export as FASTA and import into Excel (requires a little
manipulation);
• May want second tabular export for organism and molecule type.
• Be sure to have sequences properly ordered;
• Use Excel formulae to clean up and error check, then convert
into PatentIn import format.
<my-seq-name;moltype;organism>
sequence
• This does take some Excel skill to do right!
GQ Can Help Prepare Sequence Listings

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Generating Sequence Documents for IDS
Prep
• IDS (information disclosure statements) may be filed during
prosecution, either on the initiative of the patent practitioner, or in
response to an Office Action.
• These are essentially citations, and may be journal reference, patents
filings, or sequence documents, or any combination.
• The sequence documents are really easy to prepare from GQ, and
with minimal training, may be done by clerical workers or other
assistants. No knowledge of sequence is needed.

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Sample Genbank-Formatted Export
for IDS
• Uses standard sequence export interface.
• Sequences can be obtained from regular search results or by keyword search.
• Can export multiple sequences but they will need to be broken out into individual
files.

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NRB - Excel Export of Alignments
nrb export.xls

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Family Portrait Report
Click on a family to see the list of patents matching your
sequence

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Analysis Report for > 3 Queries

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Excel Link Backs & Pivot Table
Sample export
for link back.xlsx

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Acknowledgments
• Bjarne Due Larsen
• Mary Jane Reeve
• Steven Altman
• Bob March
• Bill Perkins
• Henk Heus
• Danyu Wu
• Stephen Allen