Download Proteins with Annotated

Cornelia M Hooper, Ian R Castleden, Nader Aryamanesh, Richard P Jacoby and A Harvey Millar
ARC Centre of Excellence Plant Energy Biology, The University of Western Australia, Crawley, Australia
Where crop proteins go and why it matters
What does protein subcellular location mean?
What is cropPAL?
Proteins in our food crops have specific functions and locations within cells. These proteins are vital for human
nutrition and the industrial use of plant agricultural products. The genomes of these crops encode 10,000s of
different proteins, but the location of >80% of these proteins inside cells is not known. Finding protein function
and location of crop proteins will significantly aid crop improvement in the future.
Where is our work place?
How do we get in?
?
Cytosol
dria
chon
Mito
le
!
!
!
?
How to determine subcellular location?
Subcellular location can be determined by different types of experiments
1. proteins can be fluorescently labelled and observed in cells
2. parts of cells can be purified and the protein found identified using mass spectrometry
3. computer programs can predict location based on the amino acid sequence of proteins.
Scientists around the world investigate proteins and publish those locations in scholarly journal articles. Proteins can be
quite similar between different plants so knowledge can be shared across-species.
How cropPAL was built?
How cropPAL will grow
Proteome
coverage
We obtained Reference proteomes
(Ensembl Plant)
Enhanced data interpretation
gap filling
focal point identification
cropPAL
Collation and linking of data
links to enrich description
open access to researchers
USA
corn
Germany
barley
7.4%
10%
7%
Japan, China
rice
Europe, Australia
wheat
5.2%
we searched and
we computed
read 100s of studies 10,000s of predictions
Publications
Computational tools
SUBA database
expansion
15%
5%
Scientists
cropPAL connects global researchers
projected cropPAL
expansion
25%
20%
Research data
The Compendium of Crop Proteins with Annotated Locations (cropPAL) combines experimental data from >600 studies, from >300 research institutes in 33 countries with seven
pre-computed subcellular predictions for wheat (Triticum
aestivum), barley (Hordeum vulgare), rice (Oryza sativa), and
maize (Zea mays) protein sets.
The data collection, including meta-data for proteins
and studies, can be accessed through the search portal
http://crop-PAL.org. Comparison of protein sequences between the different plants (reciprocal BLAST, TreeBeST)
allows the search for protein location data across species
and provides sophisticated inter-species data filling.
This information helps represent plant cells as interacting protein networks that can be investigated to improve
product generation in crops and to propose new biotechnological solutions to agricultural challenges; the latter is in
particular important in wheat and barley which are a major
strategic focus of the Australian agricultural industry.
Who are our team members?
How do we maximise
working together?
o
Vacu
?
Find out at cropPAL: http://crop-pal.org/
1.3%
Arabidopsis
0.6%
0%
2005
year
year
2015
2025
cropPAL connects >1,000,000 data points from computation and experimental work.
Over 600 research studies from > 300 institutions from > 33 countries were integrated
and are now searchable posing possible collaborations for multi-crop research.
With improvind technology the data available for integration into cropPAL will grow
exponentially similar to the data in model plants (e.g SUBA over the last 10 years)
cropPAL data mining accelerates crop research output
A
B
Subcellular Proteome Sizes
we linked data to Ensembl Plant index system
40000
70%
60%
50%
40%
30%
Arabidopsis Barley
Wheat
Rice
Corn
10%
Commercial importance of subcellular locations
Many nutritional and bioindustrial plant products are proteins
(or are made by proteins) in specific locations in crop cells
Recombinant
medical proteins
Vaccines, Antibodies
agree
MLOC_54831.1
Wheat
(unknown)
-
plastid
Barley
Arabidopsis: AT4G03520.1
(Thioredoxin) plastid ( experimental evidence)
Rice
OS12T0188700-02 (Thioredoxin) - plastid
Arabidopsis
Corn (no homologue)
ts
Monoco
tree branches are not to scale
A: We can now estimate the number of proteins in each location of the cell and investigate how they vary in the different crops. Across evolution the protein sets in different locations of the plant cell
have increased or decreased in size but not to the same extend. B: When comparing crop proteins to similar proteins in the model plant Arabidopsis, their locations can agree but also disagree, highlighting the importance of using comparative data such as in cropPAL. C. Direct comparison of crop proteins and model plants increases our understanding of unknown proteins and proteome to
protein-function evolution.
http://crop-pal.org/
Vacuole
partially
agree
20%
0%
Animal feed & additives
(Xylanase, Cellulases)
Cellulosic Bio fuels
disagree
cots
Eudi
20000
80%
with Arabidopsis protein locations
vacuole
plastid
plasma membrane
peroxisome
nucleus
mitochondrion
Golgi
extracellular
endoplasmic reticulum
cytosol
60000
Cell Walls/
Extracellular Matrix
Using cropPAL to learn more about an unknown wheat protein recently sequenced:
90%
80000
0
C
Traes_7DL_9EB5503A9.1
cropPAL data predicts its location in the plastid
100000
we generated the collection and
built the user interface
% protein locations of
Using cropPAL to aid breeding outcomes
Stress tolerant phenotypes
(drought, salinity, frost, heat)
Sequencing genomes
Golgi
Product channeling
to cell wall
Proteins are the products of genes
Endoplasmic
Reticulum
Locating proteins and their functions give us tools to
breed plants for more favorable responses
Product maturation,
protein folding and structure
Peroxisome
Protein-groups form functional units
located in different areas of the cell
Pharmaceuticals
(anti-cancer agents)
Chloroplast
Bakery products (starch, amylases)
Bio fuels (lipids, fatty acids)
Essential amino acids
Thiamin (vit B1), vit K1 and vit E
Chemotherapy agents (terpenoids)
Where cropPAL helps with
crop breeding:
Mitochondrion
Biotin (Vit H), Folate (vit B12)
Ascorbate (vit C),
Biobleaching agents (redox enzymes)
Knowing Location Allows:
1. Extraction processes to be optimized for a specific plant product
2. The right crop variety to be selected to obtain maximum yield
3. New crop varieties to be bred for high yield production of a desired product
Functional units generate building blocks for the
mechanisms of survival, growth and stress response
cropPAL can identify new target
proteins, estimate their functions
and aid development of strategies
to accelerate successful breeding
outcomes
The support of ANDS realized the generation of the cropPAL data collection as an open resource. The data was derived from computational
tools and experimental data and is now easily accessable, searchable, reusable and stored in two repository libraries for data permanence.
Contact:
Cornelia Hooper:
[email protected]
Harvey Millar:
[email protected]
http://creativecommons.org/licenses/by/3.0/au/
Poster Report cropPAL v1, © (CM Hooper)
ARC Centre of Excellence Plant Energy Biology 2015