- G P Z C o n f e r e n c e D i g i t a l B r e e d i n g , Tu l l n -

Genetic interplay of yield, baking quality and resistance in the

MAGIC Wheat population WM-80012.02.2020

A n t o n i a L i s k e r / W i e b k e S a n n e m a n n

M a r t i n L u t h e r U n i v e r s i t y

H a l l e - W i t t e n b e r g

Aims of the MAGIC-WHEAT pro jec t

• breeding new elite winter wheat varieties with an improvement of

yield, quality, pathogen resistance and nutrient efficiency

• application of SNP marker and multiple linear regression model for

association mapping to estimate genetic regions of interest

→ s u s t a i n a b l e i n c r e a s e o f e f f i c i e n c y f o r c u r r e n t

w h e a t b r e e d i n g

2

Int roduct ion of the MAGIC -WHEAT popula t ion

• WM-800 population based on 8 German modern elite varieties

with contrasting yield, quality and resistance traits

• founders were selected in cooperation with Syngenta and RAGT

Founders BreederQuality group

ReleaseMultiplication area (ha) 2015

(A) Patras DSV A 2012 2,685

(B) Meister RAGT A 2010 1,175

(C) Linus RAGT A 2010 801

(D) JB Asano Breun A 2008 2,186

(E) Tobak WvB B 2011 3,122

(F) Bernstein Syngenta E 2014 537

(G) Safari Syngenta C 2017 -

(H) Julius KWS A 2008 2,844

3

Selection of 800 WM-lines→ representing appr. 25% of the official German seed multiplication area in 2015

Y i e l d c o m p o n e n t s

• heading time (HEA)

• plant height (HEI)

• grain yield (YLD)

• TGW

• kernels/ear (GNE)

• ears/m2 (EAR)

I n d i r e c t q u a l i t y t r a i t s

• sedimentation (SED)

• starch content (STC)

• raw protein (GPC)

• hectoliter weight

(HLW)

• wet gluten (WGC)

R e s i s t a n c e s c r e e n i n g

• stripe rust (Yr)

• leaf rust (Lr)

• Fusarium (FHB)

• powdery mildew

Tra i t complexes of in teres t for today

2 years/4 locations + 2 contrasting N levels (N0/N1)

4

2 years + 5 locations

Descr ip t ive s ta t i s t i cs - yie ld parameters

…based on LSmeans of genotypes across locations, between nitrogen treatments

Trait Treat Mean SD Var CV Min Max h2 N p-value

HEAN0 145.9 1.7 2.9 1.2 141.5 151.5 87.0 800

***N1 146.5 1.8 3.3 1.2 142.0 151.5 88.4 800

HEIN0 77.1 8.4 70.1 10.9 51.6 108.0 94.4 800

***N1 82.0 9.2 85.5 11.3 53.9 110.7 96.0 800

TGWN0 42.7 3.5 12.2 8.2 32.8 52.6 92.0 800

***N1 41.5 4.0 16.2 9.7 29.6 54.1 93.7 800

GNEN0 49.3 5.1 26.2 10.4 32.9 67.1 73.2 800

***N1 51.5 5.7 32.6 11.1 34.6 71.2 82.3 800

EARN0 375.2 47.1 2222.5 12.6 242.7 575.1 31.3 800

***N1 442.9 59.1 3487.8 13.3 297.3 649.8 43.8 800

YLDN0 70.0 5.3 28.4 7.6 48.6 84.2 67.8 800

***N1 81.1 5.9 34.9 7.3 61.4 96.4 71.8 800

→ high variation within the population

6

Desc r i p t ive s t a t i s t i c s – qua l i t y t r a i t s

Trait Treat Mean SD Var CV Min Max h2 N p-value

GPC (%)N0 11.47 0.52 0.27 4.52 9.72 13.33 63.0 800

***N1 14.01 0.66 0.43 4.70 11.64 16.82 83.0 800

SEDN0 37.78 4.27 18.23 11.30 25.96 52.40 71.6 800

***N1 52.24 5.35 28.60 10.24 35.70 68.43 83.8 800

HLW N0 76.55 1.62 2.63 2.12 71.17 80.96 83.1 800

***N1 77.17 1.86 3.46 2.41 69.14 82.18 88.4 800

STC (%)N0 69.51 0.63 0.40 0.91 67.08 70.92 46.7 800

***N1 68.48 0.87 0.75 1.27 64.67 70.61 68.4 800

WGC (%)N0 24.90 1.66 2.76 6.67 20.36 31.66 44.8 800

***N1 31.01 1.86 3.46 6.00 26.17 38.61 67.5 800

7

… based on LSmeans of genotypes across locations, between nitrogen treatments… all quality traits were measured with near infrared spectroscopy method, except SED

→ previous studies proved the correlation between high GPCs and lower STCs with increased N input

Descr ip t ive s ta t i s t i cs – res is tance screening

8

Mean SD CV Min Max N h²

FHB 3.98 0.80 20.10 1.83 6.52 800 86.7

YR 2.61 1.36 52.20 1.00 7.58 800 90.4

LR 3.69 1.26 34.10 1.13 7.08 798 87.0

→ high variation within the population

Br ing ing i t a l l t og e the r

Net plot of correlations between all traits:• LR and YR are not displayed, r ≥ 0.2 to any of the other traits

FHBHEA

HLWHEI

TGW

EAR

GNE

SED

GPCYLD

WGC

STC

9

r2

G e n o m e - w i d e a s s o c i a t i o n s t u d i e s

Genotypic data:

• 27,685 polymorphic SNPs from the 15k iSELECT SNP array

and 135k Affymetrix array

• SNP data was translated into 0/1/2 matrix:

0 = 0 Julius alleles = homozygous non-Julius

1 = 1 Julius allele = heterozygous

2 = 2 Julius alleles = homozygous Julius

• GWAS according to Liu et al. 2011 (Maurer et al. 2015, Sannemann et al. 2018)

• Selection of co-factors with Proc GLMSELECT (SAS 9.4)

• Multiple linear regression with Proc GLM (SAS 9.4)

• p-value ≤ 0.0001

• Five-fold cross validation (20 times replicated)

• Detection rate ≥ 25 % as threshold for significant marker-trait association (DR ≥ 35 % for FHB)

Phenotypic data: LSmeans

• 6 yield and yield components

• 5 indirect baking quality traits

• 3 resistance traits

LSmeans across available environments;

separately for each N treatment

1 http://de.hereisfree.com/materials/download/8650.html2 http://deacademic.com/dic.nsf/dewiki/12922173 https://de.depositphotos.com/13388388/stock-illustration-desktop-pc-computer-workstation.html

1)

GWAS model:

2)

3)

10

Enhancing and reducing effects of Julius allele

QTL ho t spo t s i n th e WM - 800 popu l a t i on :

11

Rht-B1.a*

FHB

HLW

HEI

TGW GNE

GPC (N+)

WGC (N+)

AE

*Julius allele = GA sensitive

**Julius allele = GA insensitive

HEA

Rht-D1.b**

FHB

HLW

HEI

TGW GNE

GPC (N+) WGC

(N+)

SED

AE

EAR HEI

TGW

GNEYLD(N1)

QTL-2BLYR

-0,6

-0,4

-0,2

0

0,2

0,4

0,6

0,8

FHB

eff

ect

in s

cori

ng

nu

mb

ers

GWAS r e su l t s o f Rh t -B1 and Rh t -D1 g ene s

• Rht-B1 and Rht-D1 control plant height and many other complex traits (all effects are significant at p-value ≤ 0.001)

Julius allele effects under N0 treatmentJulius allele effects under N1 treatment

Dev

iati

on

to

po

pu

lati

on

me

an (

%)

-20

-15

-10

-5

0

5

10

15HEI TKW GNE GPC WGC HLW HEA HEI TKW GNE GPC SED WGC HLW

Rht-B1a (Julius allele GA sensitive) Rht-D1b (Julius allele GA insensitive)

12

Rh

t-B

1a

Rh

t-D

1b

FHB

GWAS r e su l t s – QTL ho t spo t on 2 BL

• DR ≥ 72

• same effect directions for yield components and yield (N1)

• significant decrease of grain yield just under N1 treatment

• Julius allele effect on YR

no QTL effects on quality traits-8

-6

-4

-2

0

2

4

6

8

Dev

iati

on

to

po

pu

lati

on

mea

n (

%)

N0 treatment N1 treatment

13

-4

-3

-2

-1

0

1

2

3

4

YR in

sco

rin

g n

um

ber

s

Julius allele effects of QTL on 2BL:

IWGSC RefSeq v1.1:

• TraesCS2B02G615500 (2BL)

• Nitrate transporter 1/peptide transporter family 5.5 protein (NRT1/PTR)

• NRT1/PTR genes are known for the uptake and translocation of nitrates and small peptides

• several NRT1 genes are already described, but not at chromosome 2BL

• TraesCS2B02G618300 (2BL)

Disease resistance protein (NBS-LRR class) family

Back to the a im o f th e p r o j e c t

15

Founders Yield Quality group FHB

(A) Patras 6 A 4

(B) Meister 6 A 4

(C) Linus 7 A 5

(D) JB Asano 6 A 6

(E) Tobak 8 B 7

(F) Bernstein 5 E 4

(G) Safari 7 C 5

(H) Julius 6 A 5

Are there any genotypes, which outperform the eight founders of the WM-800 population?

→ Based on BSL 2018

©unknown

b r e e d i n g n e w e l i t e w i n t e r w h e a t v a r i e t i e s w i t h i m p r o v e d y i e l d , q u a l i t y a n d r e s i s t a n c e t r a i t s

→ f o u n d e r s s h o w c o n t r a s t i n g p e r f o r m a n c e s f o r a l l t r a i t c o m p l e x e s

Compe t i ng t r a i t comp l exe s – y ie ld , qua l i t y and r e s i s t ance

16

To

bak

To

ba

k

• 23 WM lines outperform Tobak• ∆(best WM line – Tobak) = 4.6 dt/ha

• 104 WM lines outperform Bernstein• ∆(best WM line – Bernstein) = 1.3 %

• 83 WM lines outperform Bernstein• ∆(best WM line – Bernstein) = 1.2 score units

Grain yield Grain protein Fusarium

Compe t i ng t r a i t comp l exe s – y ie ld , qua l i t y and r e s i s t ance

16

To

bak

To

ba

k

• 23 WM lines outperform Tobak• ∆(best WM line – Tobak) = 4.6 dt/ha

• 104 WM lines outperform Bernstein• ∆(best WM line – Bernstein) = 1.3 %

• 83 WM lines outperform Bernstein• ∆(best WM line – Bernstein) = 1.2 score units

13 WM lines in common

Grain yield Grain protein Fusarium1 WM line in common

16

AcknowledgmentEbrahim Kazman

Hilmar Cöster

Erhard Ebmeyer, Victor Korzun

Hubert Kempf, Josef Holzapfel

Tanja Gerjets

Prof. Dr. Klaus Pillen

Dr. Wiebke Sannemann

Dr. Andreas Maurer

Dr. Erika Schumann

Roswitha Ende, Markus Hinz, Jana Müglitz

P-32

P-21

P-4