rapidly mapping genes related to soy- bean seed …...populati ons total number of seeds seeds with...
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Rapidly mapping genes related to soy-
bean seed characters by NGS-based BSA
mapping strategy
Yong Guo
Institute of Crop Science,
Chinese Academy of Agricultural Sciences
June 19th, 2018
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Outline
Background
Case study I: mapping genes controlling
soybean cotyledon color
Case Study II: mapping QTLs related to
soybean seed weight
Conclusions
Acknowledgements
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Soybean is an important legume crops in the world. It provide important
sources of vegetable oil and plant proteins.
1. Background
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The duplicated genome restrict gene isolation in soybean
Schmutz et al. nature, 2010, 463(7278): 178-183.
13MYA 59MYA
Stem growth habit: Dt1、Dt2
Flowering and maturity: E1-E4
SCN resistance: Rhg1、Rhg4
Salt tolerance: GmSALT3, GmCHX1
Leaflet shape: Ln
Pod shattering: qPDH1、SHAT1-5
Seed-hardness: GmHs1-1
Paleopolyploid genome
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Methods for identifying genes involved in specific traits
(Takeda et al., Nature Reviews Genetics, 2008, 9(6): 444-457)
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Low-throughput and time-consuming of classical approaches
Segregating population
development
Genome-wide investigation of
polymorphic molecular markers
Identification of the most relevant
candidate regions
Fine-mapping by increasing
marker density in target region
Development of physical maps
Candidate gene isolation and
validation
Jeong et al. Plant Cell 2012;24:4807-4818
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Next generation sequencing make the sequencing
costs dramatically reduced
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Methods for identifying genes involved in specific traits
Lindner et al., Genetics, 2012, 191(4): 1381-1386.
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Methods for identifying genes involved in specific traits
Abe et al., Nature biotechnology, 2012, 30(2): 174-178
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There are limit mutant resources in soybean
Rice:tens of thousand of mutants available
1536 mutants
Two soybean mutant libraries:
Fast Neutron: Bolon et al., 2011
EMS: Tsuda et al., 2015
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G.max
G.soja
Resequencing
1 G.soja + 1 G.max
Resequencing
25 G.sojia+30 G.max
De novo seq
7 G.soja
250M ? 19.6M ? ? ? 712 ?
510M ? 70M ? ? ? ? ?
510M 480M 85M 15M 726 1179 16 338
Kim et al. PNAS, 2010; Li et al. BMC Genomics, 2013; Li et al. NB 2014
High genetic diversity among different soybean accessions
SNP SNP missed
in Re-seq
Small
InDel
Large
InDel CNV-gain CNV-loss G.max-
specific
G.soja-
specific
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The objective of this study
Development of NGS-based BSA mapping approach in
soybean using segregating population derived from
germplasm
Validation of the reliability and efficiency of BSA-seq in
fine mapping of genes/QTLs in species with particularly
sizeable or complex genomes
Mapping of genes regulating soybean cotyledon color
and seed weight using developed NGS-based mapping
method
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2. Case study I: Mapping genes controlling cotyledon color
Cotyledon color is an important morphological trait for breeding and
germplasm classification
Most of cultivated soybean showed yellow cotyledon color and only a
few exhibited green one
Qualitative trait: three inheritance patterns--maternal inheritance,
double and single gene inheritance
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Yellow Green
A segregating population derived from two parental lines with distinct
cotyledon colors was developed
Development of segregating population
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Populati
ons
Total
number of
seeds
Seeds with
Yellow
Cotyledon
Seeds with
Green
Cotyledon
Observat
ion Ratio
χ2
(15:1) P-value
130028-1 314 295 19 15.5:1 0.0008 0.8841503
130028-3 341 319 22 14.5:1 0.0018 0.8777637
130028-4 247 234 13 18.0:1 0.2594 0.5217025
130029-1 270 251 19 13.2:1 0.1669 0.5931627
130029-2 252 232 20 11.6:1 0.9524 0.2687178
130030-1 248 234 14 16.7:1 0.0688 0.6939535
130030-2 374 347 27 12.9:1 0.4456 0.4387141
130030-3 247 231 16 14.4:1 0.0003 0.8824539
130030-4 258 244 14 17.4:1 0.1747 0.5846935
130034-1 337 316 21 15.0:1 0.0097 0.9887781
130034-2 302 277 25 11.1:1 1.7881 0.1453782
separation ratio of cotyledon color in F1 all fit 15:1
Investigation of seed cotyledon color in 11 different plants
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Soybean cotyledon color is controlled by two genes
Yellow Green
all yellow 3:1 15:1 all green
Cotyledon color in this cross was controlled by two genes and the
green cotyledon trait carried from Jiyu102 was recessive.
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Construction of BSA pools for next gerneration seqeucing
Yellow Green
all yellow 3:1 15:1 all green
YC-bulk GC-bulk
ZH30 JY102
30 lines 30 lines
Four DNA samples were used to construct libraries and subjected for
whole genome sequencing using Illumina HiSeq 2500 platform
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Sample ID YC-bulk GC-bulk ZH30 JY102
Clean Reads 486,749,106 467,745,622 108,602,086 84,534,592
Clean Base 61,327,351,325 58,897,998,134 13,683,105,387 10,650,695,091
Q20(%) 91.6 91.4 91.5 92.6
Q30(%) 85.1 85.0 85.1 85.7
Mapped
ratio(%) 94.7 93.8 94.8 94.6
Average depth 59X 53X 12X 9X
Coverage_ratio
_1X(%) 95.2 93.5 93.2 89.7
Coverage_ratio
_5X(%) 90.9 85.0 76.8 69.2
Coverage_ratio
_10X(%) 87.9 80.0 57.4 44.1
Summary of Illumina sequencing data
A total of 1,084,921 SNPs and 157,839 small InDel were identified between
the parental lines ZH30 and JY102
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Calculation of SNP index and Δ (SNP-index)
SNP filtering: quality score >=100
read depth >=10
SNP index = Count of alternate base (JY102)/Count of reads aligned
Δ (SNP-index) = SNP index in GC-bulk - SNP index in YC-bulk
P-value in Fisher’s exact test for the each SNP locus between GC-
and YC- bulks was also calculated.
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Sliding window analysis of SNP index and Δ (SNP-index)
Average SNP-index, Δ (SNP-index) and P value were calculated across
a 2-Mb genomic interval using a 10-kb sliding window
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Two candidate regions with statistically significant were identified
qCC1: 54.15-56.83Mb on Chromosome 1
qCC2: 0-2.68Mb on Chromosome 11
Average SNP-index of GC-bulk
>0.9, average P-value<0.05
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SNP analysis of candidate regions
qCC1 locus: 2.68 Mb interval region
2,843 SNPs between parental lines
2,284 SNPs had an index of 1.0 in the GC-bulk
251 SNPs result in changes of the coding sequences
qCC2 locus: 2.68 Mb interval region
1,237 SNPs between parental lines
870 SNPs had an index of 1.0 in the GC-bulk
102 SNPs result in changes of the coding sequences
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Fine mapping of qCC1 to a 30.7-kb region
Four annotated genes
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Candidate gene analysis in qCC1 region
39 SNPs: 21 in genes ,two synonymous and one non-synonymous variations.
15 small InDels: one in exon of Glyma. 01g214600 and the other in intron of
Glyma. 01g214700
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Fine mapping of qCC2 to a 67.7-kb region
Nine annotated genes
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15 SNPs: All SNPs could not alter amino acid sequence of encoding proteins.
One small InDels: alteration occurs in dominant parental line Zhonghuang30
Candidate gene analysis in qCC2 region
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qCC1/2 are the same as previous identified D1/D2 genes
Fang et al., Plant J, 2014; Nakano et al., PCP, 2014
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3. Case study II: Mapping QTLs related to seed weight
100-Seed weight is a key component of soybean yield trait
Pod number
× Seed weight
Seed size
Seed yield per plant
Seed number
Seed number per pod
Wild soybean Landrace Modern cultivar
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Genetic inheritance of 100-SW in a RIL population
XL ZH28
Year Parent RIL mapping population
Zhonghuang28 Xiaoling Mean S.D Range CV%
2013 20.2 9.8 15.8 2.4 10.3-
23.8 15.4
2014 20.8±1.6 11.4±0.7 15.9 2.3 8.9-24.1 14.6
LS-bulk HS-bulk
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Summary of Illumina sequencing data
A total of 1,216,848 clean SNP were identified between the parental
lines ZH28 and XL
Samples HS-bulk LS-bluk Zhonghuang28 Xiaoling
Clean_Reads 314,489,982 284,619,824 108,190,706 81,497,870
Clean_Base 39,622,603,336 35,856,859,929 13,628,408,688 10,267,871,894
Q20(%) 91.76 91.84 95.04 91.76
Q30(%) 85.45 85.36 89.00 85.42
Mapped ratio(%) 97.83 98.31 96.17 95.81
Ave_depth 35X 31X 12X 9X
Cov_ratio_
1X(%) 98.64 86.99 97.82 94.43
Cov_ratio_
5X(%) 93.48 77.53 90.7 76.46
Cov_ratio_
10X(%) 87.96 70.56 66.48 43.05
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QTL-seq identified major QTLs on chromosome 20 H
SB
S
NP
-In
de
x
LS
B
SN
P-I
nd
ex
LS
B-H
SB
∆
SN
P-I
nd
ex
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The major QTL located on the tail of Chr.20
Δ (
SN
P-i
nd
ex)
Physical position: 34.22-36.75, 40.95-43.35Mb
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SNP marker development for genotyping of RILs
50 SNPs were selected from candidate region and RIL population was
genotyped using Sequenom MassARRAY iPLEX platform
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The QTL was mapped to a 187-kb region
19 genes were annotated in the 187kb candidate region
11 genes have non-synonymous variations between parental lines
Year 2016 2017
Left Marker SNP22 SNP22
Right Marker SNP25 SNP25
LOD 7.4923 6.2975
PVE(%) 16.8764 15.946
Add 0.9881 0.7472
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4. Conclusions
Genome-wide NGS-based BSA mapping approach was
developed in soybean using segregating population
derived from germplasm
Two loci controlling cotyledon color were identified
and fine mapped to 30.7-kb and 67.7-kb interval
Two stay green genes were located in fine mapping
regions and the sequence variant of one gene was
directly identified by whole genome sequencing
A major QTL related to seed weight was identified by
NGS-based mapping method and fine mapped to 187-
kb region,19 annotated genes
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5. Acknowledgements
Prof. Lijuan Qiu
Jian Song
Fulai Zhou