This document summarizes research from a project aiming to identify genes responsible for phosphorus (P) use efficiency in maize. The project involves researchers from various institutions. The objectives are to identify maize orthologs of the rice Pup1 gene, map QTL for P use efficiency in maize, study inheritance of root architecture under high and low P, and validate candidate genes. Six putative maize Pup1 orthologs were identified. QTL mapping was conducted using field and hydroponic studies. Co-localization of QTL for P efficiency traits and root traits was found. Expression analysis of orthologs found ZmPSTOL1 to be the best candidate gene.

1. GCP Project Number: G7010.03.01:
Cloning, characterization and validation
of PUP1/P efficiency in maize
PI: Leon Kochian, USDA-ARS/Cornell University, USA
Co-Pi’s: Claudia Guimaraes, Sidney Parentoni, Jurandir
Magalhães, Vera Alves, Maria José Vasconcelos, Sylvia
Sousa, Roberto Noda, Embrapa Maize and Sorghum,
Sete Lagoas, Brazil
Lyza Maron, Miguel Pineros, Jiping Liu, Randy Clark, Ed
Buckler, Jon Shaff, USDA-ARS/Cornell, USA
Sam Gudu, Moi University/KARI, Eldoret, Kenya
Mathias Wissuwa, JIRCAS, Tsukuba, Ibaraki, Japan

2. • Identification of OsPSTOL1 (Pup-1)
orthologs in maize
• QTL/gene mapping for P use efficiency in
maize in the field and in hydroponics
• Inheritance studies on maize root
architecture under high and low P
• Validation of maize PSTOL1 candidate
genes and if necessary, novel P efficiency QTL
(if maize PSTOL1 homologues are not
functional in P efficiency)
Project Objectives

3. Gene Identification Physical position
Identity
(%)
Coverage (%) E-value
GRMZM2G451147 ZmPSTOL1 Chr8: 152.043.859 70 97 3.4e-131
GRMZM2G164612 ZmPSTOL2 Chr8: 152.100.275 70 97 2.3e-127
AC193632.2_FGP002 ZmPSTOL3 Chr4: 39.792.602 69 95 2.0e-105
GRMZM2G448672 ZmPSTOL4 Chr3: 206.918.421 66 97 4.7e-186
GRMZM2G412760 ZmPSTOL5 Chr3: 20.172.140 55 99 5.1e-104
GRMZM2G172396 ZmPSTOL6 Chr8: 13.267.001 55 99 9.6e-123
OsPSTOL1 Ortholog Identification in Maize
• Using OsPSTOL1 as a query, six predicted genes were found in the maize genome
sharing more than 55% of amino acid sequence identity with OsPSTOL1.
• These genes were located on chromosomes 3, 4 and 8, at physical positions
described in Table below.
• Genetic markers for the six ZmPSTOL genes were generated and mapped on a
linkage map for a L3 (P efficient) x L22 (P inefficient) RIL population.

4. Phylogeny of Maize PSTOL1 Orthologs
• Phylogenetic tree of OsPSTOL1
related sequences, including
predicted protein sequences
from maize, rice and
Arabidopsis.
• The predicted maize proteins
share more than 55% sequence
identity with OsPSTOL1.
• These predicted maize
proteins cluster together with
OsPSTOL1 and Arabidopsis SNC4
and PR5, suggesting like
OsPSTOL1 they are
serine/threonine receptor-like
kinases of the LRK10L-2
subfamily.

5. Maize Test Cross Hybrids Derived from Embrapa
Elite Diversity Panel Phenotyped for P efficiency
•321 testcross hybrids were evaluated in the field over two years under low and high P.
• High variability in yield under low & high P was observed as well as a significant
differences in grain yield under high vs. low P
• Phenotypic data will be used for association analysis and genomic selection
Low P High P

6. QTL Mapping of Maize P Efficiency in the Field
• RIL population derived from L3 (P efficient) x L53 (P inefficient) was
backcrossed to the parental lines and then phenotyped for P efficiency
traits in the field on low P and sufficient P field sites.
• P efficiency traits determined and mapped were P acquisition
efficiency (PAE; grain produced/amount soil available P), P use efficiency
(PUE; amount plant P/amount soil available P), and P utilization
efficiency (PUTIL; grain produced/amount plant P).
• Six QTLs were identified for PUE, six for PAE and five for PUTIL .
• Most of the QTLs mapped for PUE were coincident with the genomic
regions mapped for PAE. This agrees with the high correlation (0.89)
between these traits, which were also highly correlated with grain yield
under low P, 0.96 and 0.85, respectively.
• This result indicates that P use efficiency is mainly due to P acquisition
efficiency, as was also found by Parentoni et al. (Maydica 55:1; 2010).
• None of the QTLs for P utilization efficiency were coincident with the
other P efficiency indexes, suggesting that different genes are involved in
P utilization.

7. QTL Mapping of Maize P Efficiency in the Field (con’t)

8. QTL Mapping of Maize P Efficiency
and 2D Root Traits in Hydroponics
•The L3 x L22 maize RIL population was grown in paper pouches
moistened with low P and sufficient P nutrient solution and roots
were digitally imaged and root traits quantified using our
RootReader 2D platform (Clark et al, Plant Cell Envir 36: 454; 2013).
•Root and shoot dry weight and P accumulation were also
quantified and QTL mapping was conducted on P efficiency traits
(PUE, PAE, PUTIL) and root traits.
•Out of 32 root traits, four were selected for mapping analysis
based on De Sousa et al. (Functional Plant Biol; 2012): length (cm),
volume (cm3), volume of fine roots (1.0<d≤2.0 mm) (cm3) and root
surface area (cm2).

9. Root Phenotyping Tools
Growth:
Hydroponics (Al tolerance)
Agar Plates (Zn nutrition)
Pouches (P nutrition, Salinity stress)
Sand Pots (RSA validation, P nutrition)
Capture and Analysis:
Digital Photography (Single images)
RootReader2D Software calculates range of
root growth traits on both whole root system
and specific traits
 Visit: www.plantmineralnutrition.net
Overall Efficiency:
1000’s of plants per day
2D Phenotyping Platform 3D Phenotyping Platform
Clark et al., Plant Physiol2012
Growth:
Gel Cylinders (RSA - root system architecture)
*New: Hydroponics (RSA, Stress/functional studies)
Capture and Analysis:
Digital Photography (Image sequences)
RootReader3D Software reconstructs series of 2D
images into a 3D RSA and computes specific root traits
Overall Efficiency:
~100 plants per day
Clark et al., Plant, Cell & Envir2011

10. Root Imaging Pipeline – Imaging RSA in 2-D
Root Growth & Imaging
RootReader 2D Software
Clark et al. 2012. High-throughput
2D root system phenotyping platform
facilitates genetic analysis of root
growth and development. Plant Cell
Environ.

11. QTL Mapping of Maize P Efficiency
and 2D Root Traits in Hydroponics
•The L3 x L22 maize RIL population was grown in paper pouches
moistened with low P and sufficient P nutrient solution and roots
were digitally imaged and root traits quantified using our
RootReader 2D platform (Clark et al, Plant Cell Envir 36: 454; 2013).
•Root and shoot dry weight and P accumulation were also
quantified and QTL mapping was conducted on P efficiency traits
(PUE, PAE, PUTIL) and root traits.
•Out of 32 root traits, four were selected for mapping analysis
based on De Sousa et al. (Functional Plant Biol; 2012): length (cm),
volume (cm3), volume of fine roots (1.0<d≤2.0 mm) (cm3) and root
surface area (cm2).

12. Co-localization of P Efficiency QTL from Field Studies with P
Efficiency and Root Trait QTL from Nutrient Solution Phenotyping
Hydroponics Hydroponics
Field Field

13. A B
Co-localization of P Efficiency QTL from Field Studies with P
Efficiency and Root Trait QTL from Nutrient Solution Phenotyping
Chr 7
Chr 7
Hydroponics Hydroponics
Chr 8
Field Field

14. •A region from 209 to 272 cM on chromosome 1: Co-localization
of QTLs controlling PUE, PAE and P utilization efficiency (PUTIL) in
the field with a multiple-trait QTL for root morphology and PAE in
nutrient solution
•A region spanning 82 - 95 cM on chromosome 3: Co-localization
of QTL controlling PUE and PAE in the field with a multiple-trait QTL
for root morphology and PAE in nutrient solution.
•A region from 77 to 83 cM on chromosome 7: Co-localization of
QTL controlling PUE and PAE in the field with a QTL for root
diameter.
•A region spanning 100 – 127 cM on chromosome 8: Co-
localization of QTL controlling PUE and PAE in the field with QTLs
for PAE, root length and root surface area in nutrient solution.
The Combined Analysis of QTL Mapping for Root Traits
and P Efficiency Indices in the Field Based On Grain
Yield Has Led Us To Focus on Four Genomic Regions

15. Colocalization of ZmPSTOL1 Orthologs with
Maize P Efficiency and/or Root Trait QTL

16. ZmPSTOL Expression in Roots & Shoots of
P Efficient (L3) and P Inefficient (L22) Maize
• ZmPSTOL1, 4 and 6 preferentially expressed in roots.
• ZmPSTOL1 and 4 expression increases in response to P deficiency.
• ZmPSTOL4 preferentially expressed in roots of P efficient L3 -
colocalizes with root traits and not P efficiency traits.
• ZmPSTOL1 only rice Pup1 homolog that colocalizes with PAE and PUE.
It’s expression is specific to roots and is induced by low P plant status.
• ZmPSTOL1 expression is exclusively in roots of P inefficient L22, but the
superior allele for this chr 8 PAE and PUE QTL donated by L22.
• ZmPSTOL1 is most similar in sequence of the maize orthologs to
OsPSTOL1.

17. Shallow Intermediate Deep
What Is the Ideal Root Architecture P Efficiency in Low P Soils?
[P]
[H+]
P Efficient Soybean Line
Dr. Hong Liao’s group, Root Biology Center, SCAU, Guangzhou

18. 3D RSA Imaging System
• Stationary camera with fixed capture settings that is synchronized to a
turntable via a LabVIEW interface and digital controller
• 100 images captured per root system, 3.6° of rotation between images
• Capture time of approximately 10 minutes per root system

19. 3D Reconstruction Process via RootReader 3D
Thresholded rotational image sequence
consisting of 40-100 2D images Perspective back projection of 2D root points from
each 2D image into a temporary 3D voxel volume
Transformation of each temporary
voxel into a final voxel volume
Adaptive thresholding of each horizontal cross section
through final voxel volume to generate 3D root model

20. Germplasm and Screening Mapping Results
Genetic Mapping of RSA
Peak SNP
-66kb -33kb 0 +33kb +66kb
“A” “B”
SNP Allele SNP Allele
n=39 n=118 QTL
QTL

21. Germplasm and Screening Mapping Results
Genetic Mapping of RSA
Peak SNP
-66kb -33kb 0 +33kb +66kb
“A” “B”
SNP Allele SNP Allele
n=44 n=107 QTL
QTL

22. Germplasm and Screening Mapping Results
Genetic Mapping of RSA
• Subpopulation SNPs selected from within 3kb of the
peak Indica SNP
Aus Indica
Temperate Japonica Tropical Japonica
All Subpops
n=211 n=360 n=9 n=80 n=44 n=107
n=10 n=169 n=7 n=162
QTL
QTL

23. The Gel-Based Root Growth
System Has Its Limitations
• Roots of some plant species such as maize &
sorghum as well as fine rooted species such as
canola don’t grow well in the gel cylinders
• Labor and cost intensive
• Can’t easily impose different nutrient regimes
• Limited to work with fairly small root systems
(young plants)

24. Transition From Gel to Hydroponics
M8 Rice line Nipponbare parent
12 day old rice
grown in low P
nutrient solution

25. 3D Imaging/Analysis of
RSA in Hydroponics
•We can use the hydroponic systems for 3-D imaging because our
software subtracts out the mesh and reconstructs the images
•Are using this hydroponic system with 3D black plastic mesh to
screen sorghum populations (270 lines) and to correlate RSA traits
with physiological data.
•Can use much larger vessels than with the gel and still maintain
rapid throughput.
• Important design for longer growth periods, as crown roots may
be important for water acquisition and they don’t appear until
around 12 days.
Dr. Alexandre Falcão
computer wizard

26. 3 D Printers

28. The growth system is created
from ABS plastic mesh circles
made with a 3-D printer.
The mesh system serves
to constrain the roots,
but not to impede their
growth.

29. Three-D RSA Reconstruction of 100 Two-D
Sorghum Root Images (15 Day Old Plant)
• Barbara Hufnagel from Jurandir Magalhaes’s lab is currently in our lab working with
our staff to phenotype and quantify RSA 3D traits for the sorghum association panel.
• We will be set up to phenotype maize RSA for this project in early 2014.

30. Products
•Due to the more upstream nature of this project, the products
are still in the pipeline and will be forthcoming starting later in
2014.
•Claudia is generating NILs for specific P efficiency QTL for
verification of QTL effects and as a breeding resource. Pyramiding
of multiple QTL in NILs will have greater potential for impact.
•Work ongoing to validate via association mapping analysis and
more in depth molecular physiological investigations of candidate
ZmPSTOL1 genes to identify OsPSTOL1 orthologs involved in maize
P efficiency.
•Ultimately will have breeding lines for improved P efficiency.
•Catalog of bi-parental and GWA QTL & markers for root system
architecture traits that may play a role in maize P efficiency.