Mapping of Quantitative Trait Loci Controlling Adaptive Traits in coastal Douglas-fir....
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Transcript of Mapping of Quantitative Trait Loci Controlling Adaptive Traits in coastal Douglas-fir....
Mapping of Quantitative Trait Loci Controlling Adaptive Traits in coastal Douglas-fir.
Cold-Hardiness QTL Verification and Candidate Gene Mapping
N.C. Wheeler, K.D. Jermstad, K.V. Krutovsky, S.N. Aitken, G.T. Howe,
J. Krakowski, and D.B. Neale
Major Messages
• QTL Maps can be very informative• Size does matter (for predicting number, effects,
and location of QTL)• Practice is good (verification has value)• QTL studies may guide candidate gene
prioritization
QTL Studies Are Informative and Useful
• Complex trait dissection / genetic architecture– Number of QTL influencing a trait– Size of the QTL effects (PVE)– Location of the QTL (gross)– Parental contribution of allelic effects– QTL by environment/site interaction effects
• Provide a foundation for MAS• Provide a framework for positional selection of
candidate genes
ABc
aBC
aBC
ABc
aBC
aBc
Abc
Abc
Abc
abC
abC
Abc
Abc
aBC
A
B
c
abC
aBc
Abc
Quantitative Trait Locus Mapping
ABC
ABC
abc
abc
F1 F1
X
ABC
ABC
abc
abc
Parent 1 Parent 2
X
HEIG
HT
GENOTYPEBBBbbb
Bb
Bb BbBbBB BB BBbb bb bb
QTL Study Requirements
• An appropriate population– Pedigreed, large, replicated
• Appropriate markers– Co-dominant, multi-allelic, fully informative
• Framework map with complete genome coverage• Good phenotypes• Analytical tools
The problem is, most studies have failed to meet all requirements well, and are seldom repeated; esp the population
A Case for Verification
• To assess the robustness of QTL it is necessary to verify them in time, space, and/ or genetic background.
Definition: the repeated detection, at a similar position on the genetic map, of a QTL controlling a trait under more than one set of experimental conditions (Brown et al. 2003. Genetics 164:1537-1546)
Historical Reference
• Jermstad K.D. et al. 1998. A sex-averaged genetic linkage map in coastal Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco var ‘menziesii’) based on RFLP and RAPD markers. Theor. Appl. Genet. 97: 797-802.
• Jermstad K.D. et al. 2001a. Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas-fir. I. Spring bud flush. Theor. Appl. Genet. 102: 1142-1151.
• Jermstad K.D. et al.. 2001b. Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas-fir. II. Spring and fall cold-hardiness. Theor. Appl. Genet. 102: 1152-1158.
• Jermstad K.D. et al. 2003. Mapping of quantitative trait loci controlling adaptive traits in coastal Douglas-fir. III. QTL by environment interactions. Genetics 165: 1489-1506.
Maternal Grandmother(late flushing)
Maternal Grandfather
(early flushing)
Paternal Grandmother(late flushing)
Paternal Grandfather
(early flushing)
F1 Parent F1 Parent
(1991) (1994)
clonally replicated progeny linkage map (Jermstad et al. 1998)
Turner,OR test site (n=78)(Jermstad et al.
2001a)
clonally replicated progeny
Bud flush experiment(n=429)
Field Experiment
Longview, WAtest site (n=408)
Springfield, ORtest site (n=408)
750 NDL EDL
Moisture stress (MS)
10 15 20 MS NMS MS NMS
Twin Harbors, WAtest site (n=224)(Jermstad et al. 2001a, 2001b)
(WC
75
0_F
T10)
(WC
75
0_F
T15
)
(WC
75
0_F
T20
)
(WC
15
00_
FT
15
)
(WC
15
00_
FT
20
)
ND
L_
NM
S
ND
L_
MS
ED
L_
NM
S
ED
L_
MS
Flushing temperature (FT) oC
3-generation pedigree and mapping populations3-generation pedigree and mapping populations
Daylength (DL) Winter chill (WC) hours
1500
10 15 20(WC
15
00_
FT
20
)
Growth cessation experiment
(357< n <407)
The Other Requirements
• Markers and genome coverage– 74 evenly spaced, highly informative RFLP markers– Map length of ~900 cM, density ~ every 12 cM
• Phenotypes– Spring cold hardiness (1997, 2003)– Bud flush etc (annually 96’-2001’)
• Analytical Tools– Haley-Knott multiple marker interval mapping
approach; scanned LG at 5 cM intervals, 1 and 2 QTL models
Fig. 2 Bud flush QTLS in Douglas-fir
Verification pop.Detection pop.
LG17 LG16
LG15 LG14LG13 LG12
LG1 LG2 LG3 LG4 LG5 LG6 LG7 LG8 LG9 LG10 LG11
ofl 1*
wfl 1*
ofl 1*
wfl 1*
wfl 1*ofl 1*wfl 1*
ofl 1*
wfl 1*ofl 1*
wfl 1*
wfl 1*wfl 1*ofl 1*
wfl 1*ofl 1*
wfl 1*
wfl 1*ofl 1*
wfl 1*ofl 1*
gfl 9*
gc 9*
gfl 9*
gfl 9*gc 9*
gfl 9*
gc 9*gh 9*
gfl 9*
gfl 9*
gc 9*
gfl 9*
gfl 9*
gfl 9*gc 9*gh 9*
oqy*
wqy*
qs 8*
wfl 8*
qs 5*
wqy*qs 8
wqy*
qs 6*8*
oqy*wqy
qs 5*
qs 8*
qs 8*
qs 6*wqy
oqy
otr 6
wlt 6
wlt 6,7*
wtr 5
wfl 8*wtr 7*
wlt 5*
wtr 5*
wlt 5,7
wfl 8*wtr 6*
wlt 6*
otr 6wtr 5
wlt 5,6*7
wfl 8*wtr 5,6*
wlt 5*6*7*
wfl 8*wtr 5*6*
wlt 5*
wlt 5*
wlt 7wlt 7
ofl 8
wtr 7
wlt 5*6*
wfl 8*wtr 5*
wtr 5*
wlt 6*
wfl 8*wtr 5*
ofl 8*wlt 7
ofl 8*wfl 8*
wfl 8*
wlt 7ofl 8*
ofl 8
wfl 8*
ofl 8
ofl 8
wlt 5*wlt 5*
otr 6wtr 6*
otr 6wtr 6*
wlt 7*
wtr 7*
Jermstad et al 2003. Genetics 165: 1489-1506
Cold Hardiness in Douglas-fir• Genetics of cold hardiness well documented.
– Traditional quantitative and genecological tests– Freeze testing
• Fall and spring cold hardiness controlled by different genes
• Spring ch under stronger genetic control• Deacclimation synchronized in all tissues (buds,
needles, shoots)• QTL studies support all these findings.
Cold Hardiness Evaluation
• Cohort 1: – Shoot tips (4) from each of 2 ramets in each of 2 field blocks– Frozen in a temperature controlled chamber, multiple test temps– Evaluated using visual assessment of tissue necrosis (3 tissues)
• Cohort 2 – Single shoot tip from each of 2 ramets in each of 2 blocks– 20 diced needles, frozen in controlled chamber, multiple test
temps.– Evaluated using electrolytic conductivity (needles only)
Fig. 3 Cold-hardiness QTLS in Douglas-fir
fch-s
fch-n*
fch-n*
fch-b*
fch-b*
fch-b*
fch-s
fch-s*
fch-s*
fch-s*
fch-s*
sch-s*
sch-s*
sch-bsch-s
sch-n*
sch-b*
sch-n*sch-b*
sch-n*
sch-s*sch-b*
sch-s*
sch-s*sch-n*
sch-b*sch-n*
sch-n*
sch-n*
Spring cold-hardiness Fall cold-hardiness
LG17 LG16
LG15 LG14LG13 LG12
LG1 LG2 LG3 LG4 LG5 LG6 LG7 LG8 LG9 LG10 LG11
Validation?
• Of eight unique spring needle cold hardiness QTL in Cohort 2, four co-located with QTL in Cohort 1
• Two of the eight on new LGs, others on LGs with QTL in other locations.
• Thus, all genomic regions containing QTL for sch were verified, even given: – Different cohorts, 5 years apart
– Different test sites, 6 years apart
– Different methods of detection
Cumulative Proportion of Variation Explained
Cohort 1 Cohort 2
Phenotypic 24.9%
(H²=0.45)
15.2%
(H²=0.29)
Genotypic 55.0% 52.4%
What has QTL mapping taught us
• Virtually all traits tested are controlled by a finite number of detectable genes (QTL), with known genomic positions (kind of)
• In Douglas-fir, the majority of Sch_QTL are repeated in time (yr to yr) and space (environment). Bud flush same
• Most QTL explain 2-10% of the phenotypic variation of a trait (a few notable exceptions)
• Family size is very important (>250 desirable), as is clonal replication. More trees, more QTL with smaller effect, and smaller CI.
But, we still do not know what the relevant genes are!
Candidate Genes: Targets for AssociationLG Candidate genes mapped
in Douglas-firSimilar genes from other species
Abbreviation Gene product Function Gene expression reference 3
1 PtIFG_2006_a;PtIFG_2006_b
CABBP2 Chlorophyll a/b-binding protein type 2
Component of the photosynthetic light-harvesting complex
Dubos et al. 2003
1 estPpINR_RN01G08_b 4 DER1-like Unknown protein with DER1-motif
Degradation of misfolded proteins in the yeast endoplasmic reticulum
Binh and Oono 1992
1 estPaTUM_PA0006_a PmIFG_1592_a
40S-RPS2 40S ribosomal protein S2
Aids in protein synthesis as a structural component of ribosomes
–
1 estPpINR_RS01G05_a 4 ACRE146 Avr9/Cf-9 rapidly elicited protein
ACRE proteins are induced by fungal pathogens and other stresses
–
17
estPmIFG_102G09_cestPmIFG_102G09_b
Alpha tubulin
Alpha tubulin Major constituent of microtubules and cytoskeleton
–
1 estPpINR_AS01D10_b 4 TBE Thiazole biosynthetic enzyme
Biosynthesis of the thiamine precursor thiazole
–
1 PmIFG_1162_a UGT Uridine diphosphate glycosyltransferases
Transfer of glycosyl residues from activated nucleotide sugars to aglycones
Fowler and Thomashow 2002