Summary of 8th lesson

• Exotic microbes have a reduced level of genetic variability

• If genotypes fall on clades separated by long branches, it may be an indication there is no sex going on between individuals belonging to the two branches. Formal tests like the Index of association can test for that

• Anonymous multilocus analysis can be done without any knowledge of the genome using markers such as RAPDs or AFLPs

• Need to eliminate co-segregant markers and to use Jaccard;s

Dealing with dominant anonymous multilocus markers

• Need to use large numbers (linkage)

• Repeatability

• Graph distribution of distances

• Calculate distance using Jaccard’s similarity index

Jaccard’s

• Only 1-1 and 1-0 count, 0-0 do not count

1010011

1001011

1001000

Jaccard’s

• Only 1-1 and 1-0 count, 0-0 do not count

A: 1010011 AB= 0.6 0.4 (1-AB)

B: 1001011 BC=0.5 0.5

C: 1001000 AC=0.2 0.8

Now that we have distances….

• Plot their distribution (clonal vs. sexual)

Now that we have distances….

• Plot their distribution (clonal vs. sexual)

• Analysis: – Similarity (cluster analysis); a variety of

algorithms. Most common are NJ and UPGMA

Now that we have distances….

• Plot their distribution (clonal vs. sexual)

• Analysis: – Similarity (cluster analysis); a variety of

algorithms. Most common are NJ and UPGMA– AMOVA; requires a priori grouping

AMOVA groupings

• Individuals within population

• Among populations

• Among regions

AMOVA: partitions molecular variance amongst a priori defined groupings

Results: Jaccard similarity coefficients

0.3

0.90 0.92 0.94 0.96 0.98 1.00

00.10.2

0.40.50.60.7

Coefficient

Fre

quen

cy

P. nemorosa

P. pseudosyringae: U.S. and E.U.

0.3

Coefficient0.90 0.92 0.94 0.96 0.98 1.00

00.10.2

0.40.50.60.7

Fre

quen

cy

Fre

quen

cy

0.9 0.91 0.92 0.93 0.94 0.95 0.96 0.97 0.98 0.99

Pp U.S.

Pp E.U.

0.0

0.1

0.2

0.3

0.4

0.5

0.6

Jaccard coefficient of similarity

0.7

P. pseudosyringae genetic similarity patterns are different in U.S. and E.U.

0.1

4175A

p72

p39

p91

1050

p7

2502

p51

2055.2

2146.1

5104

4083.1

2512

2510

2501

2500

2204

2201

2162.1

2155.3

2140.2

2140.1

2134.1

2059.2

2052.2

HCT4

MWT5

p114

p113

p61

p59

p52

p44

p38

p37

p13

p16

2059.4

p115

2156.1

HCT7

p106

P. nemorosa

P. ilicisP. pseudosyringae

Results: Results: P. nemorosaP. nemorosa

Results: Results: P. pseudosyringaeP. pseudosyringae

0.1

4175A2055.2p44

FC2DFC2E

GEROR4 FC1B

FCHHDFCHHCFC1A

p80FAGGIO 2FAGGIO 1FCHHBFCHHAFC2FFC2CFC1FFC1DFC1Cp83p40

BU9715 p50

p94p92

p88p90

p56Bp45

p41p72p84p85p86p87p93p96p39p118p97p81p76p73p70p69p62p55p54

HELA2HELA 1

P. nemorosaP. ilicis

P. pseudosyringae

= E.U. isolate

Have we sampled enough?

• Resampling approaches

• Saturation curves

– A total of 30 polymorphic alleles– Our sample is either 10 or 20– Calculate whether each new sample is

characterized by new alleles

Saturation curves

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

NoOf Newalleles

If we have codominant markers how many do I need

• IDENTITY tests = probability calculation based on allele frequency… Multiplication of frequencies of alleles

• 10 alleles at locus 1 P1=0.1

• 5 alleles at locus 2 P2=0,2

• Total P= P1*P2=0.02

White mangroves:Corioloposis caperata

White mangroves:Corioloposis caperata

Coco Solo Mananti Ponsok DavidCoco Solo 0Mananti 237 0Ponsok 273 60 0David 307 89 113 0

Distances between study sites

Coriolopsis caperataCoriolopsis caperata on on Laguncularia racemosaLaguncularia racemosa

Forest fragmentation can lead to loss of gene flow among previously contiguous populations. The negative repercussions of such genetic isolation should most severely affect highly specialized organisms such as some plant-parasitic fungi.

AFLP study on single spores

Site # of isolates # of loci % fixed alleles

Coco Solo 11 113 2.6

David 14 104 3.7

Bocas 18 92 15.04

Distances =PhiST between pairs ofpopulations. Above diagonal is the ProbabilityRandom distance > Observed distance (1000iterations).

Coco Solo Bocas David

Coco Solo 0.000 0.000 0.000

Bocas 0.2083 0.000 0.000

David 0.1109 0.2533 0.000

Using DNA sequences

• Obtain sequence

• Align sequences, number of parsimony informative sites

• Gap handling

• Picking sequences (order)

• Analyze sequences (similarity/parsimony/exhaustive/bayesian

• Analyze output; CI, HI Bootstrap/decay indices

Using DNA sequences

• Testing alternative trees: kashino hasegawa • Molecular clock• Outgroup• Spatial correlation (Mantel)

• Networks and coalescence approaches

Good chromatogram!

Bad chromatogram…

Pull-up (too much signal) Loss of fidelity leads to slips, skips and mixed signals

Reverse reaction suffers same problems in opposite direction

Alignments (Se-Al)

Distance vs. parsimony

• Distance simply calculates at how many positions sequences are similar or differen

– (Matteo) ACGTAACGTT-AG– (Amanda) AGTTAACGTTAAG– (Patrick) ACTTAACGTTAAG

Distance vs. Parsimony

• Patrick

Amanda Matteo

Matteo

Patrick

Amanda

OUTGROUP can allow us to pick Matteo as ancestral

Confidence

• Bootstrap (resampling approcah) Decay indices (threshold approach)

• Consistency index

• Homoplasy index

QuickTime™ and aTIFF (LZW) decompressor

are needed to see this picture.

Pacifico

Caribe

The “scale” of disease

• Dispersal gradients dependent on propagule size, resilience, ability to dessicate, NOTE: not linear

• Important interaction with environment, habitat, and niche availability. Examples: Heterobasidion in Western Alps, Matsutake mushrooms that offer example of habitat tracking

• Scale of dispersal (implicitely correlated to metapopulation structure)---

From Garbelotto and Chapela, From Garbelotto and Chapela, Evolution and biogeography of matsutakesEvolution and biogeography of matsutakes

Biodiversity within speciesBiodiversity within speciesas significant as betweenas significant as betweenspeciesspecies

Other important types of markers (co-dominant)

• Restriction Fragment Length Polymorphisms (RFLP) of a locus

• Single Nucleotide Polymorphisms (SNPs)

• Microsatellites (SSR)

Restriction Fragment Length Polymorphisms (RFLP) of a

locus

aacccacgtcaataaaaa

aacccac +

gtcaataaaaa

One restriction site

aacccaggtcaataaaaa

aacccaggtcaataaaaa

No restriction sites

Restriction Fragment Length Polymorphisms (RFLP) of a

locus

Two alternate alleles= codominant marker

Single Nucleotide Polymorphisms (SNPs)

• nnACGTnnnnnnTAAGnnnnnn

• nnAGGTnnnnnnTATGnnnnnn

Dept. of Energy / Joint Genome InstituteDept. of Energy / Joint Genome Institute(www.JGI.gov)(www.JGI.gov)

Shotgun sequencingShotgun sequencing

Completed May 2004 Completed May 2004 - 7x coverage- 7x coverage66 MB………..much larger than first calculated66 MB………..much larger than first calculated

Used 445,030 reads (FASTA format)Used 445,030 reads (FASTA format) - 3x coverage- 3x coverage

FASTA format

1. SSR detection1. SSR detection

* batch search* batch search

* di and tri-nucleotide repeats* di and tri-nucleotide repeats

* differ in repeat length* differ in repeat length

CCGAAATCGGACCTTGAGTGCGGAGAGAGAGAGAGACTGTACGAGCCCGAGTCTCGCAT

repeatmicro_gt_0135.seq0 gt(6)micro_gt_0135.seq01 gt(6)micro_ac_0462.seq012 ac(6)micro_ac_0312.seq ac(7)micro_gt_0067.seq gt(6)micro_gt_0594.seq gt(7)micro_ag_0145.seq ag(8)micro_ac_0689.seq ac(6)micro_gt_0382.seq012 gt(7)micro_gt_0396.seq0 gt(7)micro_ag_0316.seq ag(12)micro_ct_0079.seq ct(6)micro_ct_0639.seq0 ct(6)micro_ac_0478.seq012 ac(7)micro_ctg_0109.seq ctg(6)micro_ag_0305.seq ag(7)micro_cg_0053.seq cg(6)micro_ct_0541.seq ct(6)

Tm length forw sequence rev sequence60 100 0 AGCGCGTGACACACACTAAG 0 CACAACACACGCGCTCTATC60 100 0 AGCGCGTGACACACACTAAG 0 CACAACACACGCGCTCTATC61 101 0 ACCCACCACCACTCTTCACC 0 TATGATGGGGTGGGTGATTG60 101 0 GAACAGCCTCGTTCAAGAGC 0 GGGGTGATTTTACTGGCTGC60 101 0 GAAATGGGGCCAGCTCTAAC 0 CGGGGTCAAATTTACGAATG60 101 0 GGAGTACGCGGACGAAGC 0 ACACCACGACACACAACACC60 103 0 TTCTACACGCCTGCCCTTAC 0 TTATCCAGCCCTTCGTCATC60 104 0 CCATCCTCTCTCTTCTCTCGC 0 ACAATATGCCCTCCCTCCTC60 104 0 TGGTATGTTGTGTGTGTGCG 0 ACCACATCCGCGTAGAGAAC60 104 0 CTGTTGCTCGTGTTTGATGG 0 AAAGCACGCCAAAACCATAC60 106 0 CCAGCTCTCTCTGCTGCAC 0 ATTGATTGGGGCAAACAGTG60 106 0 AGCCTCTCCCAGAGCATACC 0 ACAGAGCCATCGACTTGACC60 107 0 CTTGCTCTTCTCCTTCCGTG 0 GAGATGAGGAGTCGACGAGC60 110 0 CAAAACTCCACTCATCCCCC 0 TTTGTTGGTTGTTGTGGTGG60 110 0 TTGAGCTCGTGAGCCTTCTC 0 CAACAACCCAGACAACCACC60 112 0 GAAGAGGGGGAAAGAGGGAG 0 CGCGTGCTTTTCTTCTTCTC60 112 0 ACGAAGGCTGTTCTGGACAC 0 GTTTGCTGCTGCTCTCCAAG60 112 0 TTCCTCCCACTCTGTCGTTC 0 CACAGAAGCGGAAGAGAAGC

locus ct 0070locus ct 0070

Microsatellites (SSR)

• Supposed to be neutral• Stepwise mutation model• Very sensitive because loci are prone to mutation• Allele is af fragment of DNA that includes the

flanking regions of the microsatellite and then a certain number of tandem repeats (variation in size should be in multiple of SSR(