Jo Dicks John Innes Centre Analysis of crop plant genomes [email protected]
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Transcript of Jo Dicks John Innes Centre Analysis of crop plant genomes [email protected]
Jo DicksJohn Innes Centre
Analysis of crop plant genomes
[email protected]://jic-bioinfo.bbsrc.ac.uk/bioinformatics-
research/
DataWe want to compare the genomes
of crop plants (e.g. wheat, rice, maize, millets, barley, pea)
At present, we mainly compare:Whole genome sequencesGenetic markers (comparative
mapping)Transposable elements
What can we learn from the data?
Understand evolutionary processes in crop plants.
Use comparative mapping to predict gene/marker location and function across species.
Use transposable elements to maximise diversity within a subset of a germplasm collection (core collection).
Whole genome sequencesLinear streams of data, where each
element is represented of one of four letters (A, C, G or T).
Streams can be long – billions of letters.Blocks of sequence can be meaningful
(e.g. they encode genes or transposable elements) or are deemed ‘junk’.
Species 1: caggaaaacacacactcacatacatgaacaatatctc ||||| || ||||| |||||||| |||| || ||Species 2: caggataatgcacac catacatgcacaaaat tc
Comparative mapping data
1 2 4 5Species 2
1 23 45Species 1
In most data sets, links (homologies) may be spread across chromosomes
Markers have a location and an orientation.When markers in two species are related by descent from a common ancestor, they are called homologues.Comparative mapping data are combinatorial.
Retrotransposons
1
1
2 3 4
2 4
Accession 1
Accession 2
Retrotransposons are a type of transposable element.There are various locations in a genome where they are either present or absent.An entry in a germplasm collection (called an accession) is therefore essentially a barcode representing multiple retrotransposon locations.
Evolution
Data change in time due to errors known as mutations (there are several distinct types of mutation).
Differences between species are often quantified in terms of the number and type of such mutations.
The relationship between species is often represented as a tree of evolution (often called a phylogenetic tree).
An evolutionary tree
Species 1 Species 2 Species 3 Species 4
Ancestral species
Mutations occur through time, along the tree branches
Data problemsIn comparative mapping studies,
there may be elements between the markers that are important but of which we know nothing (i.e. missing data) and erroneous links between data items (i.e. data errors).
Missing data will be largely alleviated by whole genome sequences (when will this be though?) but there will still be errors in the data.
Projects
UK CropNet (data)CHROMTREE (analysis)
GENE-MINE (data)Germinate (analysis)
JIC are also involved in Arabidopsis and Brassica IGF projects
UK CropNet databasesUK CropNet curates and develops
databases and data analysis tools for:
Arabidopsis thaliana (AGR)Brassicas (BrassicaDB)Cereals (BarleyDB, CeResDB and MilletGenes)Forage grasses (FoggDB)Potato (SpudBase)
as well as developing a database for:Comparative mapping data (CropSeqDB and
ComapDB)
Problems
To get hold of comparative mapping data from the crop plant community, we need to access disparate data sources of differing quality (not necessarily electronic).
We need to link the data sources to form a single, queriable entity.
BarleyDB
BrassicaDB
CerealsDB FoggDB
MilletGenes
SpudBase
AGR
The UK CropNet single- and related-species databases
ComapDB
ARCADE
Will the GRID be a better solution than ARCADE?
Analysing chromosomal evolution
Chromosomes evolve over time
Inversion
Inversion
InversionTranslocation
Mutations events can be mathematically modelled and used to construct a phylogenetic
tree
ProblemsUnlike DNA sequences, data are
combinatorial, not linear.Algorithms are very slow (many require
optimisation over a multi-dimensional space) and analysis of large data sets is not currently possible on JIC machines.
Parallelisation of algorithms may help, as it has done for DNA sequence phylogenetic analysis. However, is the only answer?
In some cases (due to mutations such as allo-polyploidy) we may wish to consider phylogenetic networks instead of trees – an even harder computational problem.
Analysing germplasm collections
GENE-MINE and GERMINATE
Germplasm projectsGENE-MINE: An EU-funded project to
develop a data-management and analysis computer system for plant germplasm collections
GERMINATE: A BBSRC-funded project allied to GENE-MINE and another EU project TEGERM, to develop specialist tools for analysis of the TEGERM data.
The problems seen in these projects are essentially the same as those of UK CropNet and CHROMTREE.
Retrotransposon insertion
1 2 3
Like chromosomal mutations, retrotransposon insertion can be mathematically modelled
Relationship between accessions
INS
INS
INS
Again, sometimes we may need to estimate a phylogenetic network (due to introgression between
accessions)