The fate of deleterious variants in a barley genomic prediction population

1. The fate of deleterious
variants in a barley genomic
prediction population
What happens when heterosis is not an option?
barleyworld.org

2. The fate of deleterious
variants
• How common are dSNPs in elite barley lines and what is
their fate through rounds of selection?
• Are dSNPs uniformly distributed in the genome or
concentrated in regions of low recombination?
• Does any class of SNPs explain a larger proportion of
phenotypic variance?
Questions

3. dSNPs in genomic
prediction experiment
21 exomes
01 genome
5,215 genotyped
676 phenotyped
7 UMN 8 ND 6 BA
F3
98 Selected 300 Random
F3
105 Selected 101 Random
F3
48 Selected 49 Random
21 Parents
(Cycle 0)
1,872 F3 Progeny
(Cycle 1)
1,904 F3 Progeny
(Cycle 2)
1,439 F3 Progeny
(Cycle 3)
78 Crosses/Families
Yield Trials
Yield Trials
Yield Trials
33 Families, 20 Parents
33 Families, 41 Parents
30 Families, 40 Parents
47 Families, 58 Parents
16 Families, 30 Parents 32 Families, 55 Parents
80 Crosses/Families
60 Crosses/Families
Kono et al. 2018 - bioRxiv

4. What is a deleterious
variant (dSNP)?
• A variant that reduces fitness
• Typical inferred based on sequence conservation
• In humans, validated by association with Mendelian
disorders
Species dSNPs/genome Method Publication
human 800 Conservation Chun & Fay 09
human 400 Disease Causing Xeu et al. 12
barley 1000 Conservation Kono et al. 16
soybean 800 Conservation Kono et al. 16

5. How are deleterious
variants identified?
A•••••••T••A••T ... Banana
••T••••A•••A••A ... Switchgrass
••••••••••••••C ... Purple False Brome
••T•••••••••••A ... Foxtail Millet
•••••••••••A••A ... Maize
•••••C•••••T••C ... Wild Red Einkorn
••••••••••••••T ... Cutgrass
•••••C••••••••C ... Goatgrass
••••••••••••••T ... Asian Rice
•••••••••••A••A ... Milo
Barley
GTCCCTTTCCCGCTM ... Consensus
•••••••C••••••C ...
N D DDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDDD
H Y CCCCYY--YYYCCCCCCCCCCCCCCCCCCCCCCCCCCC
C F FFFFFFF-FFFFFFFFFFFFFFFFFFFFFFFFFFFFFF
R T TTTMTTTTTTTTTTTTTTTDTTTTTTTTTTTTTTTTTT
A T VVAAVVVAVAAAVSVVVTVVVVIVAAAALATTTVVVVV
A V VVVVVIVVVIIIIIVVVV-VVV-VVVVVVVVVVVVVVV
D E EDDEEEEEEEE-EEEEEEEEEEEEEEEVVEEEEEEEEE
Q L LLLLLLL-LMLLLLLLLLLLLL-LLLLLLLLLLLLLLL
D N NDDDNNNNNDDDDNDNNNNDDDDDDDDDDNNNNNNDNN
V I VVLVVVMMVVVVVVVSVIIIIVMVVVVVIVVVVVIVVV
A V AAAAAAAAAAAAAAAAAA-AVT-TA-SAAATTTTTAAT
D E DDDDDDDN-DDDDDDDDDNEDD-EEEEEEEDDDDDDDD
A P EKSKEEEKEENAENEEEEDAAPAAAEKKEEGGEEEEEE
E D RNKKKRK-KKKKKNSSKDPESSPS-KS-SN---KKHHN
E D EEEEEEQDDEEEEEEEDEEEDEEDDDDEEEEEEEEEED
E A TATTMTTSTTTTATSSCA-SPPMASREECGSSSMTAAT
Deleterious
Tolerated
https://github.com/MorrellLAB/BAD_Mutations
Predict!
All Variants
SNPs
Coding SNPs
Nonsynonymous
SNPs
Length Polymorphisms
Noncoding SNPs
Synonymous SNPs
Kono et al. 2016 - MBE

6. Distribution of fitness
effects
Neher 2013 - Ann. Rev. Ecol. Syst.

7. Do annotation tools work?
• Chun & Fay 2009 likelihood
ratio test (LRT) approach
controls for local variation in
divergence rate
• LRT outperforms other
approaches, all better with
deeper alignments
• LRT implemented in
BAD_Mutations Python
program
Kono et al. 2018 - G3

8. Genomic prediction
retrospective
• Selection on unfavorably
correlated quantitative traits
• Realistic scenario for
understanding role of dSNPs

9. Site frequency spectrum of
founders
• dSNPs are mostly rare
• SFS impacted by family
structure of breeding
programs
Kono et al. 2018 - bioRxiv
[0,0.1] (0.2,0.3] (0.4,0.5] (0.6,0.7] (0.8,0.9]
Derived Allele Frequency
Proportion
0.00.10.20.30.40.50.6
[0,0.1] (0.2,0.3] (0.4,0.5] (0.6,0.7] (0.8,0.9]
Noncoding
Synonymous
Nonsynonymous
Deleterious

10. Distribution of variants
• Blue - exome capture
density
• Green - recombination
rate cM/Mb
• blue lines - exome
capture SNPs
• purple triangles -
genotyped SNPs
Kono et al. 2019 - in review
chr1H
chr2H
chr3H
chr4H
chr5H
chr6H
chr7H
0 50 100 150 200 250 300 350 400 450 500 550 600 650 700
0
5
10
0
5
10
0
5
10
0
5
10
0
5
10
0
5
10
0
5
10
Physical Position (Mb)

11. Imputation of genotypes in
progeny
• 497,754 SNPs in parents
• 3,885 dSNPs
• 384 SNPs genotyped in
progeny
• AlphaPeel can us complex
pedigree in imputing
genotypic state & phase
• Imputation subject to
multiple rounds of Mendel
testing - Plink 1.9
Whalen et al. 2018 - Genet Sel Evol
www.yonka.com/fr

12. Genomic prediction
• Grain yield and
fungal disease
resistance 5 year-
locations
• Unfavorably
correlated
quantitative
traits
• Lines selected
based on GEBV -
have improved
disease resistance,
stable yield
Kono et al. 2018 - bioRxiv; Tiede & Smith 2018 Mol Breeding

13. Proportion of phenotypic
variance explained
• Linear mixed model in GEMMA
software
• “SNP heritability” for SNPs
genotyped and imputed from
parents to progeny
• Yield heritability 0.198 genotyped,
0.250 imputed SNPs
• Association finds regions
associated w/ better disease
resistance, poorer yield!
• Linkage in population precludes
estimation of variance explained by
SNP classes
Fang et al. 2013 - G3

14. dSNPs & phenotypes
• Number of homozygous
dSNPs reduced over
cycles
• Other classes of variants
also become more
homozygous
Kono et al. 2019 - bioRxiv
150 200 250 300
40005000600070008000
Yield
Homozygous Derived Deleterious SNPs
YieldBLUE(kg/ha)
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C0 r=−0.01
C1 r=−0.04
C2 r=−0.02
C3 r= −0.11
150 200 250 300
05101520253035
DON Conc.
Homozygous Derived Deleterious SNPs
DONBLUE(ppm)
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C0 r=−0.3
C1 r=0
C2 r=−0.06
C3 r= −0.13
150 200 250 300
5060708090100110
Height
Homozygous Derived Deleterious SNPs
HeightBLUE(cm)
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C0 r=0.13
C1 r=0.15
C2 r=0.04
C3 r= 0.2

15. Fate of dSNPs
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DAF in Parents
ProportionofVariantsFixedforAncestralAllele
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0.00.10.20.30.40.5
[0,0.1] (0.2,0.3] (0.4,0.5] (0.6,0.7] (0.8,0.9]
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Noncoding
Synonymous
Nonsynonymous
Deleterious
Cycle
NumberofHomozygousDeleteriousSNPs
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Random
Selected
Parents C1 C2 C3
150200250300
Kono et al. 2019 - bioRxiv

16. SFS all SNPs
• dSNPs are rare and get rarer
over breeding cycles
• Other classes more frequently
approaching fixation
[0,0.05] (0.1,0.15] (0.2,0.25] (0.3,0.35] (0.4,0.45] (0.5,0.55] (0.6,0.65] (0.7,0.75] (0.8,0.85] (0.9,0.95]
Cycle 1
Derived Allele Frequency
Proportion
0.00.10.20.30.40.50.60.7
[0,0.05] (0.1,0.15] (0.2,0.25] (0.3,0.35] (0.4,0.45] (0.5,0.55] (0.6,0.65] (0.7,0.75] (0.8,0.85] (0.9,0.95]
Noncoding
Synonymous
Nonsynonymous
Deleterious
[0,0.05] (0.1,0.15] (0.2,0.25] (0.3,0.35] (0.4,0.45] (0.5,0.55] (0.6,0.65] (0.7,0.75] (0.8,0.85] (0.9,0.95]
Cycle 2
Derived Allele Frequency
Proportion
0.00.10.20.30.40.50.60.7
[0,0.05] (0.1,0.15] (0.2,0.25] (0.3,0.35] (0.4,0.45] (0.5,0.55] (0.6,0.65] (0.7,0.75] (0.8,0.85] (0.9,0.95]
Noncoding
Synonymous
Nonsynonymous
Deleterious
[0,0.05] (0.1,0.15] (0.2,0.25] (0.3,0.35] (0.4,0.45] (0.5,0.55] (0.6,0.65] (0.7,0.75] (0.8,0.85] (0.9,0.95]
Cycle 3
Derived Allele Frequency
Proportion
0.00.10.20.30.40.50.60.7
[0,0.05] (0.1,0.15] (0.2,0.25] (0.3,0.35] (0.4,0.45] (0.5,0.55] (0.6,0.65] (0.7,0.75] (0.8,0.85] (0.9,0.95]
Noncoding
Synonymous
Nonsynonymous
Deleterious
1872 progeny
1,904 progeny
Kono et al. 2019 - bioRxiv
1,439 progeny