Discovering the effector genes of Puccinia striiformis f.sp. tri.ci
John Rathjen The Australian Na;onal University
Stripe rust and Australian wheat produc;on
Annual losses
Control cost
GM Murray & JP Brennan 2009. Grains Research & Development Corpora?on. Australian Government
Stripe rust and Australian wheat produc;on
Annual losses
Control cost
GM Murray & JP Brennan 2009. Grains Research & Development Corpora?on. Australian Government
hAp://www.apsnet.org/edcenter/intropp/lessons/fungi/Basidiomycetes/Pages/StemRust.aspx
Meiosis
Urediniospores (2n)
Teliospores (2n)
Basidiospores (1n)
Pycniospores (1n)
Aeciospores (2n)
Wheat
Barberry
alternate host
Sexual host insignificant in Australia
Dikaryo?c – Two haploid nuclei
Puccinia striiformis f.sp. tri0ci Barley grass yellow rust Psd– grows on Dactylis glomerata (Cocksfoot) Psp – grows on Poa pratensis (Kentucky blue grass) Stripe rust of Phalaris spp., Bromus spp., “wheat grass”, etc, etc
P. striiformis in Australia
Pst-‐1979
Pst-‐WA (2002)
BGYR (2000)
(~20 strains)
(~6 strains)
Psd
Psp
How can we define effector genes?
• Generally, effectors are thought to be small secreted proteins.
• This is sufficient to build a list of such proteins if genomic sequence is available.
• In some cases, amino acid mo?fs such as RxLR or YxC are present…but don’t seem to be diagnos?c.
• Another important criterion is expression of candidate effector genes in planta, where that informa?on is available.
Puccinia genomics
• Pgt (stem rust) genome (Duplessis et al. 2011) is about 90 Mb, encoding about 17,000 genes – Pgt expected to be similar.
• This was assembled with a lot of “last-generation sequencing” which helps with scaffolding and sequence assembly.
• Transposable elements account for about 45% of the genome.
• Calling genes from NGS assemblies can be problematic, and can be difficult to detect expression of fungal genes in infected tissue (but these are the most interesting genes).
• There are ongoing unresolved problems with the dikaryotic nature of rusts.
• Broad Institute (Cuomo) has a good Pst assembly in the pipeline.
Perils and pi`alls of next-‐genera?on sequencing (NGS).
• NGS – boAom up or ‘shotgun’ assembly of millions of small sequence reads, using high-‐performance compu?ng. Technologies include:
• Illumina – millions of very short reads (~100 bp). • Roche-‐454 – fewer numbers of longer reads (~500 bp).
• Tradi?onal (Sanger) sequencing – long reads 800-‐1000 bp.
DNA sequencing; the impossible triangle
Tradi?onal Sanger sequencing of physical con?gs
NGS
Perils and pi`alls of next-‐genera?on sequencing (NGS).
AATATAAAACCAAAGATACTGATATCTTAGCGGCTTTCCGAATGACCCCACAACCTGGAG
Nucleus 1 Nucleus 2
Detec?ons of sequence polymorphisms in small-‐read assemblies
AATATAAAACCAAAGATACTGATATCTTAGCGGCTTTCCGAATGACCCCACAACCTGGAG
X
X
X
X
C/G
Detec?ons of sequence polymorphisms in small-‐read assemblies -‐ II
AATATAAAACCAAAGATACTGATATCTTAGCGGCTTTCCGAATGACCCCACAACCTGGAG
X
X
X
X
C/G
X
X
X
X
T/A
Detec?ons of sequence polymorphisms in small-‐read assemblies -‐ II
AATATAAAACCAAAGATACTGATATCTTAGCGGCTTTCCGAATGACCCCACAACCTGGAG
X
X
X
X
C/G
X
X
X
X
T/A T C A C T A
G G
The “phase” problem
Repeats and mul?copy genes are difficult to assemble from small reads
Repeats (transposons…effectors?) assemble poorly or not at all. This is obvious in NGS genome assemblies. It’s a considerable problem for genomics of Puccinia spp.
Transcriptome
Transcriptome
Illumina mate-‐paired Illumina pair-‐end (2)
454 RNA-‐seq
454 RNA-‐seq
Genome
Illumina RNA-‐seq
Illumina RNA-‐seq
454 mate-‐pair
NGS datasets for stripe rust bioinformatics
16831 contigs
14682 contigs
1299 ORFs-SP
515 ORFs-SP
418 ORFs-SP
100 ORFs-SP
Contamina;on removal
Secreted proteins predic;on Non-‐transmembrane domains
Unique or non-‐overlapping ORFs
Protein length ≤ 300aa
High expression
454 sequencing of isolated haustoria
transcriptome
Lab tests
Illumina sequencing
Prediction of small secreted proteins (SSPs) from the haustorial transcriptome
433 ≤ 300 aa 98 > 300 aa
311 ≤ 4 Cysteines 220 > 4 Cysteines
91 have 1 mo?f , 18 in the ‘correct’ loca?on 42 have 2 mo?ves, 23 correct loca?on
Protein length
Cysteine content
9 have 3 or more mo?ves, 8 correct loca?on Y/F/WxC mo?f
Pgt hypothe?cal protein
Specific hit (most from Pgt)
Not available
e-‐val ≤ 10-‐25
e-‐val > 10-‐25
BLASTn BLASTx
74 211
29 38
291 419
Invertase 1,3-‐β-‐glucosidase Pepsin A Chi?n deacetylase Glucose-‐regulated protein Previous SP from Pst
No memes No clusters/tribes
Validation and investigation of effector candidates
100 sequenced and cloned in TOPO
75
24
Narayana Upadhyaya and Diana Garnica
Ø R-‐AvrR recogni?on assay Ø Inhibi?on of plant cell death Ø Localisa?on Ø Influence on host metabolism
AvrM type-‐III delivery/ P. fluorescens
AvrM
avrM
Agro/AvrM
PST-80 housekeeping genes are not single allele
Housekeeping Gene Copy Number
0
1
2
3
4
5
6
7
8
9
10
221 18 39 60 81 102
123
144
165
186
207
233
254
275
312
333
368
389
418
453
483
521
295
467
443
511
Copy num
ber
Boeva V, et al. (2011) Control-‐FREEC: Bioinforma?cs. 2011 Dec 6
PST-80 Effector genes are present with variable copy number
Effector Allele Number, 6
0
1
2
3
4
5
6
7
1 21
41
308 61
81
101
121
141
161
181
201
221
241
261
281
326
346
366
415
456
494
290
434
486
471
519
Allele Num
ber
PST_80 Effector Allele Number Effector gene copy number
Effector gene, nominal ranking
Copy num
ber
Effector copy number variations between Pst-80 and BGYR
0
1
2
3
4
5
6
7
1 51 101 151 201 251 301 351 401 451 501
Axis Title
Axis Title
Effector Allele Number Effector gene copy number
Effector rank (nominal)
Copy num
ber
Effector copy number variations between Pst-80 and Pst-130 (US)
0
2
4
6
8
10
12
1 13
25
37
49
61
73
85
97
109
121
133
145
157
169
181
193
205
217
229
241
253
265
277
289
301
313
325
337
349
361
373
385
397
409
421
433
445
457
469
481
493
505
517
Allele Num
ber
Effector Number
PST_130 Effector Allele Number
Effector Allele Number
Effector gene copy number
Copy num
ber
Effector number (nominal)
Cantu et al. PLOS One (2011)
Housekeeping genes do not show the same degree of varia?on in copy number
Conserved Gene Copy Number
01234567
1 51 101 151 201 251 301 351 401 451 501
Gene
Pred
icted
Cop
y Num
ber
PST_conBGYR_con
BGYR
Pst-‐80 Control-‐FREEC predic?on of CNVs
Boeva V, et al. (2011) Control-‐FREEC: Bioinforma?cs. 2011 Dec 6
Copy number varia?on in Pst effectors
• Copy number varia?ons are readily apparent in Pst effector genes, with many single copy.
• Sequence polymorphisms are also apparent, but these are harder to annotate because of NGS assemblies.
• Single-‐copy effectors may allow the pathogen to mutate rapidly to virulence.
Barley grass yellow rust (BGYR) – a stripe rust that jumped?
BGYR (2000)
Wheat stripe (1980)
wheat Barley grass
Stripe rust and BGYR 99+% iden?cal in effector genes so far sequenced
Sequencing summary
• We amplified and sequenced the PCR products of 50 candidate effector genes from Pst-80 and BGYR and found 99 single nucleotide polymorphisms (SNPs).
• These were ALWAYS of a particular pattern – twin peak ‘dimorphisms’, rather than clear SNPs (dSNPs).
• 50 of these were'informative' dSNPs - 34 from BGYR, and 16 from Pst-80.
• We amplified and sequenced these alleles from BGYR and Pst-80.
• When we did this, we found that BGYR ALWAYS shared an allele with Pst-80, and the alternative allele was divergent.
• We think that this is related to the dikaryotypic nature of P. striiformis.
1 8 6
2
4 7
5 3
1 8 6
2
4 7
5 3
Pst-‐80
BGYR
1 8 6
2
4 7
5 3
1 8 6
2
4 7
5 3
1 8 6
2
4 7
5 3
BGYR 1
8 6 2
4 7
5 3
Model for the origins of BGYR
Pst
BGYR unknown ancestor Anastamosis + Heterokaryosis
BGYR
Where did BGYR come from?
• One line of evidence suggests that heterokaryosis is an underlying mechanism for the host jump – but we need to address the phase problem.
• In the 1950’s, this was proposed as a mechanism to explain frequent mutation to virulence of stem rust on wheat.
• We have detected four deleted effector genes, and will test these for recognition on barley grass by bacterial delivery.
• Heterokaryosis potentially increases effector hemizygosity, which could both increase the effective effector compliment (for virulence) and allow rapid deletion of recognised effectors.
Acknowledgments • Diana Garnica • William Jackson
• CSIRO Black Mountain • Narayana Upadhyaya • Peter Dodds • Jeff Ellis
• Univ Sydney CobbiAy • Colin Wellings
Robert Park
• Univ Exeter, UK • David Studholme
Ø Take nutrients (sugars and aminoacids) from host Ø Generate precursors of metabolites and energy Ø Biosynthesise compounds necessary for the ul?mate produc?on of spores Ø Secrete pathogenicity factors (effectors)
Ø Use lipid reserves to generate energy Ø Grow (DNA replica?on, cell division) Ø Modify chi?n to avoid recogni?on
Haustoria:
Germinated spores:
0
10
20
30
40
50
60
70
80
0
2
4
6
8
10
12
14
1 23
45
398 69
91
113
135
157
179
201
223
245
267
314
336
358
409
431
492
290
436
517
502
Copy, A
llele and
SNP Num
ber
Effector Number
PST_80 Effector Copy Number, Allele Number and SNP Number
Effector Candidate Copy Number
Many effector genes are single copy
PST_80 effector genes in PST_130 have undergone significant modification
0
20
40
60
80
100
120
0
2
4
6
8
10
12
14
16
1 13
25
38
50
62
74
86
98
110
122
134
146
159
172
185
198
211
223
235
247
259
271
283
295
307
320
332
344
356
368
380
392
404
416
428
440
452
464
476
488
500
512
Copy, A
llele and
SNP Num
ber
Effector Number
PST_130 Effector Gene Variability
Effector Copy Number Effector Allele Number Effector SNP Number
Mapping BGYR genomic reads against 500 ‘conserved’ Pst genes
Conserved Gene Copy Number
01234567
1 51 101 151 201 251 301 351 401 451 501
Gene
Pred
icted
Cop
y Num
ber
PST_conBGYR_con
BGYR
Pst-‐79 Control-‐FREEC predic?on of CNVs
Boeva V, et al. (2011) Control-‐FREEC: Bioinforma?cs. 2011 Dec 6
Mapping BGYR genomic reads against 500 Pst effector candidates Effector Candidate Copy Number
0
2
4
6
8
1 51 101 151 201 251 301 351 401 451 501
Gene
Pred
icted
Cop
y Num
ber PST_e
ffBGYR_eff
BGYR
Pst-‐79 Control-‐FREEC predic?on of CNVs
Boeva V, et al. (2011) Control-‐FREEC: Bioinforma?cs. 2011 Dec 6
ToxA cell death dependent on Tsn1 is suppressed by stripe rust infec;on
+ToxA +H2O
+ToxA + stripe rust stripe rust
Diana Garnica with help from the Solomon lab
PST_79 effector gene Pstv_4835_1 has one copy and two alleles
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