Genomic Breeding of Green Super Rice Varieties and Their Deployment in Asia and Africa

Abstract

Key message:
The "Green Super Rice" (GSR) project aims to fundamentally transform crop production techniques and promote the development of green agriculture based on functional genomics and breeding of GSR varieties by whole-genome breeding platforms. Rice (Oryza sativa L.) is one of the leading food crops of the world, and the safe production of rice plays a central role in ensuring food security. However, the conflicts between rice production and environmental resources are becoming increasingly acute. For this reason, scientists in China have proposed the concept of Green Super Rice for promoting resource-saving and environment-friendly rice production, while still achieving a yield increase and quality improvement. GSR is becoming one of the major goals for agricultural research and crop improvement worldwide, which aims to mine and use vital genes associated with superior agronomic traits such as high yield, good quality, nutrient efficiency, and resistance against insects and stresses; establish genomic breeding platforms to breed and apply GSR; and set up resource-saving and environment-friendly cultivation management systems. GSR has been introduced into eight African and eight Asian countries and has contributed significantly to rice cultivation and food security in these countries. This article mainly describes the GSR concept and recent research progress, as well as the significant achievements in GSR breeding and its application.

Full text

Vol.:(0123456789)
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Theoretical and Applied Genetics (2020) 133:1427–1442
https://doi.org/10.1007/s00122-019-03516-9
REVIEW
Genomic Breeding ofGreen Super Rice Varieties andTheir Deployment
inAsia andAfrica
SibinYu1 · JauharAli2· ChaopuZhang1· ZhikangLi3,4· QifaZhang1
Received: 12 November 2019 / Accepted: 17 December 2019 / Published online: 8 January 2020
© The Author(s) 2020, corrected publication 2020
Abstract
Key message The “Green Super Rice” (GSR) project aims to fundamentally transform crop production techniques
and promote the development of green agriculture based on functional genomics and breeding of GSR varieties by
whole-genome breeding platforms.
Abstract Rice (Oryza sativa L.) is one of the leading food crops of the world, and the safe production of rice plays a central
role in ensuring food security. However, the conflicts between rice production and environmental resources are becom-
ing increasingly acute. For this reason, scientists in China have proposed the concept of Green Super Rice for promoting
resource-saving and environment-friendly rice production, while still achieving a yield increase and quality improvement.
GSR is becoming one of the major goals for agricultural research and crop improvement worldwide, which aims to mine and
use vital genes associated with superior agronomic traits such as high yield, good quality, nutrient efficiency, and resistance
against insects and stresses; establish genomic breeding platforms to breed and apply GSR; and set up resource-saving and
environment-friendly cultivation management systems. GSR has been introduced into eight African and eight Asian coun-
tries and has contributed significantly to rice cultivation and food security in these countries. This article mainly describes
the GSR concept and recent research progress, as well as the significant achievements in GSR breeding and its application.
Introduction
Rice (Oryza sativa L.) is one of the most important food
crops and is the primary staple food for nearly half of the
world’s population. It is expected that the world population
will continue to grow and exceed nine billion by 2050, which
demands a nearly 70% increase in food production (FAO
2013; http://faost at.fao.org/). Hence, increasing rice yield
is critical to ensuring the world food security and living
standards of everyone. The breeding and cultivation of semi-
dwarf rice and hybrid rice varieties have contributed to two
great leaps in rice productivity (Khush 2001). However, the
breeding and wide adoption of many semi-dwarf, fertilizer-
responsive/tolerant, and high-yielding varieties have also
caused the overuses of chemical fertilizers, pesticides, and
water resources (Hazell etal. 1986). Particularly in Asia, the
overuse of pesticides has caused severe damage to ecological
environments. The application of large amounts of nitrog-
enous fertilizers and the low fertilizer-use efficiency have led
to problems of severe soil degradation and eutrophication
of water bodies. The shortage, low fertilizer-use efficiency,
and uneven distribution of water resources have caused a
series of environmental problems such as the prevalence
Communicated by Lixi Jiang.
Sibin Yu and Jauhar Ali have contributed equally to this work.
Electronic supplementary material The online version of this
article (https ://doi.org/10.1007/s0012 2-019-03516 -9) contains
supplementary material, which is available to authorized users.
* Zhikang Li
zhkli1953@126.com
* Qifa Zhang
qifazh@mail.hzau.edu.cn
1 National Key Laboratory ofCrop Genetic Improvement,
Huazhong Agricultural University, Wuhan430070, China
2 International Rice Research Institute,
DAPOBox7777MetroManila, Philippines
3 Institute ofCrop Sciences, Chinese Academy ofAgricultural
Sciences, Beijing, China
4 College ofAgronomy, Anhui Agricultural University, Hefei,
China
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1428 Theoretical and Applied Genetics (2020) 133:1427–1442
1 3
of drought (Zhang 2007). In addition, because of the fre-
quent occurrences of extreme weather worldwide, the con-
flicts between agricultural production and environmental
resources are becoming increasingly intense (Yorobe etal.
2016). Therefore, ensuring the food security and sustain-
able development of agriculture has become a key strategic
concern worldwide.
Asia contributes significantly with 90% of global rice pro-
duction and its consumption (Elert 2014). Hence, the con-
flicts between rice production and environmental resources
are particularly acute. To enhance rice yields, farmers have
gradually increased the application amounts of fertilizers
to meet the demands of high-yielding varieties for more
nitrogen (Ali etal. 2018). In recent decades, the average
rice productivity in China rose from 2.1tha−1 in 1961 to
6.7tha−1 in 2013, which was accompanied with greatly
increased application of nitrogen fertilizer from 8 to 35%
of total amount of fertilizers used in the world (Wang and
Peng 2017). The overuse of nitrogenous fertilizers and low
fertilizer-use efficiency have caused large residual amounts
of nitrogenous fertilizer to enter the soil and water bodies
around farm lands, leading to severe environmental pollu-
tion (Peng etal. 2002; Ali etal. 2018). Also, the frequent
occurrences of drought are another factor that hinders agri-
cultural development, posing significant threats to world
food security (Luo 2010). China suffers severely from water
deficit, especially for agriculture, and is frequently hit by
droughts. Since the 1990s, about 26 million hectares of its
arable lands have been affected by drought every year, which
directly led to a loss of 70 million tons in food crop produc-
tion (Jing 2007). Meanwhile, the total irrigation water used
for rice production accounts for nearly 70% of the total water
amount used for agricultural production. This limited water
resource can barely meet the demand for rice production in
China (Zhang 2007). Hence, the breeding and cultivation of
new types of varieties with superior resistances/tolerances
to drought and pests, greatly improved water and nutrient
(nitrogen and phosphorus) use efficiency, as well as high-
yield potential and desirable grain quality have become a
crucial goal of rice improvement to increase and/or stabilize
rice productivity, alleviate the water shortage, protect the
ecological environments, and ensure food security of China.
The GSR project andits major research
themes
Facing the increasingly severe resource shortage, environ-
mental pollution, and degradation of ecological systems,
Chinese scientists proposed the GSR project in 2005, which
aims to develop new rice varieties with various green traits,
including resistance to multiple insects and/or diseases, high
use efficiency of fertilizers, water-saving, drought tolerance,
and stress resistance on the basis of high grain yield and
quality (Zhang 2007). Now, the GSR concept not only refers
to new varieties with green traits but also represents the
green “resource-saving and environment-friendly” concep-
tualization of crop breeding technology and “high-yielding,
high-efficient, ecological, and safe” crop management sys-
tems (Zhang 2007; Wing etal. 2018). After the proposal
of the project, it has been strongly supported by the Chi-
nese Government and international funding programs. In
2009, the Bill and Melinda Gates Foundation funded the
international cooperation project on “Green Super Rice for
Resource-poor farmers of Africa and Asia” (OPP1130530).
In 2010, the Ministry of Science and Technology of China
granted the 863 Project, “Breeding and Development of
Green Super Rice,” with extended funding up to 2018
(2014AA10A600).
The GSR project has five main focuses (Zhang etal.
2018): (1) development and improvement of the theoretical
and technical systems for GSR breeding. These systems and
technologies were established at the population, individual,
trait, and genome levels, and the strategies to combine the
genomes and green traits of various germplasm resources
for breeding of the GSR varieties proposed; (2) establish-
ment of whole-genome selection platforms based on the
recent developments/findings in the rice functional genom-
ics research worldwide, including whole-genome breeding
databases for molecular-designed breeding and gene chips;
(3) development of new germplasm resources by pyramid-
ing of genes of green traits, including development of novel
germplasms with improved resistances to multiple abiotic
(primarily drought) and biotic stresses, high water and nutri-
ent-use efficiencies, and high grain yield and quality; (4)
breeding of new GSR cultivars (both inbred and hybrid) with
various combinations of green traits, improved grain yields
and quality; (5) high-yield cultivation and field management
techniques for GSR. The techniques and criteria for assess-
ing green traits were established. In addition, “resource-
saving and environment-friendly” cultivation management
systems were set up and GSR varieties were widely planted.
According to the GSR concept, we tentatively define newly
developed GSR cultivars for a specific target rice ecological
area into one of the following 4 main types: (1) water-saving
and drought-resistant (WDR) cultivars that have the same or
better grain yield and quality as the current check varieties
under the normal irrigated conditions but yield 30% or more
under the water-deficit or drought conditions; (2) nutrient-
use-efficient (NUE) cultivars that show the same or better
grain yield and quality as the current check varieties but
with 30% of less fertilization (nitrogen and/or phosphorus)
application; (3) pest-resistant cultivars that have significantly
enhanced pest resistance to one or more key pests (with a
30% or more reduction in pesticide application); and (4)
stress (salt, alkalinity, cold, heat, etc.)-tolerant cultivars that
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1429Theoretical and Applied Genetics (2020) 133:1427–1442
1 3
have the same or better grain yield and quality as the current
check varieties under the non-stress conditions but yield 30%
or more than the checks under the stress conditions. In the
program, GSR varieties to be developed may carry different
combinations of the green traits depending on yield limiting
factors in any specific environments.
Genomic breeding forGSR
Based on the concept of Green Super Rice with less inputs,
more production, and a better environment, several breed-
ing strategies for developing GSR cultivars were formulated
by integrating germplasm accessions, genomic resources,
and molecular technology and breeding tools (Zhang 2007;
Ali etal. 2018; Wing etal. 2018). Germplasms are essen-
tial materials for the genetic improvement and functional
genomics research of crops and are strategic resources to
support the sustainable development of GSR as well. With
a long planting history, rice is rich in genetic/genomic
diversity with huge numbers of rice germplasm collections,
including both cultivated species and its closely related wild
species maintained in gene banks worldwide (Wing etal.
2018). With the rapid advancement of DNA-sequencing
and multi-omics technology, whole-genome analyses of
gene variations and genome diversity of different types of
rice germplasm resources have become an essential part of
rice germplasm characterization and utilization. These abun-
dant rice germplasm resources provide sufficient materials
for further dissecting the genetic basis of complex traits,
identifying novel genes and their functions for future rice
molecular breeding by design (Xie etal. 2015; Wang etal.
2015b, 2018a).
Based on the research advances in the rice functional
genomics and genomic diversity, different genomics-assisted
breeding strategies have been adopted for the development
of the four major types of GSR cultivars (Wing etal. 2018).
By combining multi-omics such as genomics, phenomics,
epigenetics, metabolomics, proteomics, and transcriptomics,
the desirable genes in the wild and cultivated rice species
were mined and identified through large-scale and high-
throughput phenotypic analyses on the re-sequenced rice
germplasm (including wild species) accessions. A series
of near-isogenic lines (NILs) or introgression lines (ILs)
with the elite genetic backgrounds (widely planted major
rice varieties and hybrid parents) that contain only small
genomic segments (e.g., about 200kb) of target genes
were created through the whole-genome selection platform
(Fig.1). This genome selection platform comprising spe-
cifically designed gene chips (Yu etal. 2014; Chen etal.
2014) and selection systems simultaneous selecting any spe-
cific groups of target genes, non-target ones, and the entire
genome background, which is expected to facilitate the
accurate manipulation and improvement of targeted green
traits (Wing etal. 2018). Another strategy involves an intro-
gression breeding scheme in which large-scale crossing and
massive repeated backcrossing to one (or more) elite parent
are performed to generate NILs with the desirable traits or
genes (Fig.2). Such NIL populations are coupled with geno-
typing and massive phenotyping to identify genetic variation
associated with critical green traits. Then, pre-GSR lines
or GSR varieties were developed in a two-stage process. In
the first stage, elite lines carrying a single gene of interest
were developed and thoroughly evaluated for the green traits,
which by themselves were useful as pre-breeding GSR lines.
Second, the genes introduced into these lines would be com-
bined in a designed way to develop cultivars with favorable
traits. The introgression breeding approach has been used for
developing GSR, and demonstrates being robust in several
successful applications (Li and Ali 2017; Fenget al. 2018;
Liang etal. 2018), because of its advantage with simultane-
ous improvement and genetic dissection of complex traits by
introgressing one or more target genes through the genome
selection system. This approach resulted in many GSR varie-
ties and their adoption across Asia and Africa in the IR64,
Huanghuazhan (HHZ), and Weed Tolerant Rice 1(WTR1)
recipient backgrounds (Ali etal. 2018).
Green genes forthebreeding ofnew GSR
varieties
Currently, more than 3000 genes affecting a wide range
of phenotypes have been cloned and dissected in rice (up
to 2018, www.riced ata.com; Li etal. 2018b; Wing etal.
2018). Of these cloned rice genes, those associated with
resistance to biotic stresses (diseases and insect pests) and
abiotic stresses (drought, salinity, flooding, low inputs), and
traits of high nitrogen- and phosphorus-use efficiency, high
yield, and good grain quality, are mostly “resource-saving
and environment-friendly” and can be referred to as green
genes. These green genes have been the targets for GSR
breeding (Table1).
One important component of the GSR project was to rese-
quence a core collection of 3024 rice germplasm accessions
and phenotype the sequenced lines and GSR parents plus a
large set of chromosomal segment substitution lines (CSSLs)
for many green traits to discover and mine genes/QTLs asso-
ciated with the green traits by genome-wide association
analyses. As a result, a large number of loci associated with
green traits were identified (Sun etal. 2015; Zhu etal. 2015;
Lv etal. 2016; Qiu etal. 2017; Liang etal. 2018). These
newly detected QTLs or the cloned genes provide abundant
genetic resources for the development of new GSR varieties.
To facilitate more efficient and accurate integration of the
genotyping technology in GSR breeding, a pedigree analysis
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1430 Theoretical and Applied Genetics (2020) 133:1427–1442
1 3
Phenomics
Transcriptomics
Epigenomics
Metabolomics
Proteomics
Multi-omicsbased
gene discoveryRice databasesfor
genomevariation
Gene–chipsselection
Genome selection platform
Demonstrationand adoption of GSRvarieties
Green SuperRice(GSR) target
Less pesticide
Lessfertilizer
Lessirrigation
High yield/quality
Disease/insectsresistance
Nutritionefficiency
Resistancestresses
Yield/Grain quality
Green genes
Gene-specific selection
Target
M1
M2
Introgression breeding
a
b
cd
e
f
g
Fig. 1 The target, strategy, and design for the development of Green
Super Rice (GSR). a The goal of GSR was proposed to promote sus-
tainable rice production with less inputs, while still achieving a yield
increase and quality improvement. b Integration of multi-omics (phe-
nomics, genomics, transcriptomics, epigenomics, metabolomics, and
proteomics) to identify and understand green genes (such as high
yield, good grain quality, resistance to stresses, nutrient-use effi-
ciency). c A series of databases for rice genomic variations. d Sche-
matic illustration of introgression lines, each containing a target gene
and that could be combined in various ways to develop GSR. e The
rice gene-chip and the gene-specific selection system. f Adoption of
GSR varieties in various ecosystems
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1431Theoretical and Applied Genetics (2020) 133:1427–1442
1 3
system of rice varieties was built by taking advantage of
high-throughput SNP chips. The system was used for geno-
typic identification of the pedigree and derivative pedigree
materials of a superior rice variety, Huanghuazhan (HHZ)
for GSR development. As a result, a total of 1113 conserved
and traceable chromosomal regions were identified, includ-
ing genes related to many important agronomic traits, such
as sd1 (controlling plant height), Ehd4 (controlling heading
date), htd1 (controlling tiller height and dwarfing), SSIIa
(controlling soluble starch synthesis), GS3 (controlling grain
size), Amy3A (controlling amylase), Gn1a (controlling grain
number), and TAC1 (controlling tillering angle) (Zhou etal.
2016a; Chen etal. 2017).
The sequence analysis of a large number of varieties
resulted in the identification of the selected genomic regions
during breeding and characterized two subpopulations (I and
II) for the Xian (indica) subspecies, which have distinct geo-
graphic origins, resulting from separate breeding activities
of China and the International Rice Research Institute dur-
ing the early “Green Revolution.” In addition, about 200
genomic regions subjected to different selections among
different Xian subpopulations were found (Xie etal. 2015).
These regions cover some genes with known functions and
related to green traits as well as many loci with unknown
functions. These selected loci will provide important targets
for the further improvement of rice.
Many cloned genes with disease resistance have been
widely applied to the breeding and improvement of new
GSR varieties (Jiang etal. 2016; Hu etal. 2016, 2017).
These included introduction of Pi2 (blast resistance
gene) and Xa23 (bacterial blight resistance gene) into the
photo-thermo-sensitive genic male sterile (PTGMS) line
Guangzhan63-4S, which significantly enhanced the resist-
ance of newly developed two-line hybrid breeding lines
to bacterial blight and blast (Jiang etal. 2015a). In addi-
tion, two genes, Bph14 and Bph15 conferring resistance to
~20cultivars
Pyramiding,
newgermplasm
andcultivars
Gene mappingand
identification
2X25 X300 ILs
GenotypingScreeningPerformancetesting
BC
SelectiveILs
withgreen traits
SelectiveILs
with green traits
Donors
a
b
c
Fig. 2 Massive backcrossing strategy for the development of GSR
varieties: a Large-scale cross of diverse donors with elite parents and
massive repeated backcrossing (BC) to one elite parent to generate
near-isogenic lines or introgression lines (IL) with the desirable genes
or traits. b Genotyping and phenotyping of the selective IL popula-
tion to identify genetic variations for the target traits. c Elite lines
carrying a single gene of interest may be combined to develop GSR
cultivars
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1432 Theoretical and Applied Genetics (2020) 133:1427–1442
1 3
brown planthoppers were together introduced into a supe-
rior restorer line, Huahui 93. The resultant NILs carrying
Bph14 and Bph15 showed much improved resistance to
brown planthoppers (Wang etal. 2016). Through marker-
assisted backcross breeding, new 9311 lines carrying differ-
ent combinations of brown planthopper resistance genes/loci
(QBph3, QBph4, Bph6, Bph3, Bph9, Bph10, Bph14, Bph15,
Bph17, Bph18, Bph20, Bph21, and Bph24) were developed,
which showed stronger brown planthopper resistance at the
seedling stage (Xiao etal. 2016). Recently, a novel gene,
Bph38(t) on the long arm of chromosome 1, was mapped to a
small genomic region of 496.2kb explaining the phenotypic
variation of 35.9% in a backcross population derived from
a cross of HHZ and Khazar (Balachiranjeevi etal. 2019).
Breeding of new GSR varieties with high nitrogen-use
efficiency is a critical way to reduce the application of
nitrogenous fertilizer in rice production and is one of the pri-
mary goals of our GSR breeding as well. Jewel etal. (2019a)
reported a unique and systematic breeding approach through
the selection of introgression lines with higher nutrient-use
efficiency (NUE) through the early backcross breeding pro-
gram. The selection of ILs was carried out for four consecu-
tive seasons under different combinations of N, P, and K
dosages of fertilizer. Five promising ILs (Nue-115, Nue-
114, Nue-112, Nue-229, and Nue-230) were identified as
having high grain yield and significantly improved NUE.
These ILs provided valuable materials and information in
rice breeding programs for high NUE. Quantitative trait loci
(QTLs) related to NUE were identified earlier by several
researchers (Liu etal. 2016; Zhou etal. 2017a, b; Feng etal.
2018). Recently, Jewel etal. (2019b) detected a total of 49
main-effect QTLs in six nutrient conditions. These QTLs
explained phenotypic variation ranging from 20.3 to 34.7%
and were located on all 12 chromosomes, except on chromo-
somes 7, 11, and 12. Among these QTLs, four hotspot QTLs
were identified on chromosomes 3, 5, 9, and 11. Interest-
ingly, novel QTLs for partial factor productivity (22 QTLs)
and agronomic efficiency (four QTLs) were detected for –P
and 75% of recommended N conditions. Several candidate
genes were identified in these QTLs regions, and they were
involved in nutrient uptake and transporting mechanisms.
Mahender etal. (2019) identified a total of 19 QTLs associ-
ated with three favorable agronomic traits by using tunable
genotyping-by-sequencing technology. Interestingly, two
QTLs (qLC-II_1 and qLC-II_11) were detected for chloro-
phyll content under zero percentage of N, P, and K fertilizer.
Together, these QTL regions and candidate genes would be
of great value for marker-assisted selection and pyramiding
of multiple QTLs for improving NUE in rice.
Several genes related to high nitrogen-use efficiency have
been cloned. These included OsNRT1 (Lin etal. 2000),
OsDUR3 (Wang etal. 2012a), OsPTR6 (Fan etal. 2014),
qNGR9/DEP1 (Sun etal. 2014), NRT1.1B (Hu etal. 2015a),
OsNRT2.3 (Fan etal. 2016), and GRF4 (Li etal. 2018a).
Among them, NRT1.1B appears to be the most promising
one. The primary function of this gene is its transport activ-
ity of nitrate and is strongly induced by nitrate (Hu etal.
2015a; Zhang etal. 2019). This gene shows apparent differ-
entiation between Xian and Geng (japonica), and NRT1.1B
(the Xian allele) had undergone through strong artificial
selection during domestication. The allelic variation of
NRT1.1B was found to be responsible for the big difference
in nitrogen-use efficiency between Xian and Geng. Thus,
NRT1.1B-Xian has great application value in GSR breed-
ing and production. The introduction of NRT1.1B-Xian into
Xiushui 34, a late-maturing Geng variety in Zhejiang, China,
resulted in the development of several new high-yielding
lines with greatly improved NUE. Of these new lines, the
best one yielded 10.2tha−1 under a moderate rate of nitro-
gen input (a reduction in nitrogen fertilizer per hectare from
180 to 100kg in Hubei, China), exhibiting great potential
for high nitrogen-use efficiency.
Abiotic stresses are the most important factors limiting
rice productivity in many rice ecosystems. Among the vari-
ous abiotic stresses, drought severely affects rice production
and causes substantial yield losses in drought prone areas
of rice (Hu and Xiong 2014). Thus, identification of loci
for stress resistance and the development of GSR varieties
with improved resistance to a single or multiple stresses are
of great significance in solving the proble. In rice, several
genes related to abiotic stress resistance have been cloned
(Table1). These included some loci or candidate genes
associated with drought tolerance (Ren etal. 2005; Redillas
etal. 2012; Uga etal. 2013; Zhu and Xiong 2013; Huang
etal. 2014; Zhang etal. 2016). Several other genes are also
of value for improving rice resistance to abiotic stresses.
These included three cloned genes (COLD1, bZIP73, and
HAN1) for cold tolerance at seedling stage (Ma etal. 2015;
Liu etal. 2018b; Mao etal. 2019), CTB4a for cold toler-
ance at the booting stage (Zhang etal. 2017a) and TT1 for
high-temperature resistance (Li etal. 2015). Although many
genes for stress resistance have been cloned, the most suc-
cessful application of these cloned stress tolerance genes in
rice breeding was SUB1 for submergence tolerance. This
gene has been successfully introgressed into several mega
rice varieties which showed significantly improved yields
under natural flooding (Ismail etal. 2013).
Besides the advantages of resistance to various diseases,
insects, and stresses and high nitrogen-use efficiency, the
newly developed GSR varieties are characterized by high
quality and yield. Currently, several genes related to yield
and grain quality have been cloned in rice (Xing and Zhang
2010; Wang etal. 2012b, 2015a). The elite allele of IPA1
(ipa1-2D) for an ideotype is located in a tandem repeat
sequence upstream of the IPA1 gene, and variation in the
gene structure would lead to a decrease in the methylation
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1433Theoretical and Applied Genetics (2020) 133:1427–1442
1 3
level in the promoter region of IPA1, resulting in increased
expression of IPA1, which contributes to an ideotype and
appropriate tiller number to promote yield (Wang and Wang
2017; Zhang etal. 2017b; Wang etal. 2018b). In addi-
tion, a gene that influences spikelet number can increase
the number of rice grains to elevate yield by more than 5%
(Wu etal. 2016). The grain quality of rice mainly comprises
processing, appearance, and nutritional and cooking quali-
ties, which directly or indirectly determine the value of rice.
At present, several genes related to rice quality have been
Table 1 Representative genes related to green traits from 2014 to 2019
Green trait Gene Accession number Chr. Function causes References
Grain yield/grain quality OsAAP6 LOC_Os01g65670 1 Expression change by variations
in promoter
Peng etal. 2014
GL2/GS2/OsGRF4 LOC_Os02g47280 2 Expression change Che etal. (2015), Duan
etal. (2015) and Hu
etal. (2015b)
GNP1 LOC_Os03g63970 3 Expression change by variations
in promoter
Wu etal. (2016)
lgy3 LOC_Os03g11614 3 Protein structure Liu etal. (2018a)
GL3.3/TGW3/qTGW3 LOC_Os03g62500 3 Premature termination Hu etal. (2018), Xia etal.
(2018) and Ying etal.
(2018)
Chalk5 LOC_Os05g06480 5 Expression change by variations
in promoter
Li etal. (2014)
GW5 LOC_Os05g09520 5 Expression change by variations
in promoter
Liu etal. (2017)
GW7/GL7 LOC_Os07g41200 7 Expression change by variations
in promoter
Wang etal. (2015a, c)
GLW7/OsSPL13 LOC_Os07g32170 7 Expression change by variations
in promoter
Si etal. (2016)
OsOTUB1 LOC_Os08g42540 8 Expression change by variations
in promoter
Wang etal. (2017b)
Disease/insect pest resistance Bsr-d1 LOC_Os03g32230 3 Expression change by variations
in promoter
Li etal. (2017)
Bph3 LOC_Os04g12540 4 Amino acid substitution Liu etal. (2015)
Os04g0202350 4 Premature termination
LOC_Os04g12580 4 Amino acid substitution
BPH6 LOC_Os04g35210 4 Amino acid substitution and
deletion
Guo etal. (2018)
PigmR LOC_Os06g17900 6 Amino acid substitution Deng etal. (2017)
IPA1 LOC_Os08g39890 8 Expression change by variations
in promoter
Wang etal. (2018)
STV11 LOC_Os11g30910 11 Amino acid substitution and
deletion
Wang etal. (2014)
Xa10 LOC_Os11g37620 11 Gene deletion Tian etal. (2014)
BPH9 LOC_Os12g37280 12 Amino acid substitution and
deletion
Zhao etal. (2016)
Nutrient-use efficiency DEP1 LOC_Os09g26999 9 Amino acid substitution Sun etal. (2014)
NRT1.1B LOC_Os10g40600 10 Amino acid substitution Hu etal. (2015a)
GRF4 LOC_Os02g47280 2 Expression change Li etal. (2018a)
Cold resistance LGS1 LOC_Os02g47280 2 Expression change Chen etal. (2019a, 2019b)
COLD1 LOC_Os04g51180 4 Amino acid substitution Ma etal. (2015)
CTB4a LOC_Os04g04330 4 Expression change by variations
in promoter
Zhang etal. (2017a)
bZIP73 LOC_Os09g29820 9 Amino acid substitution Liu etal. (2018b)
HAN1 LOC_Os11g29290 11 Expression change by variations
in promoter
Mao etal. (2019)
Heat resistance OsTT1 LOC_Os03g26970 3 Amino acid substitution Li etal. (2015)
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

1434 Theoretical and Applied Genetics (2020) 133:1427–1442
1 3
cloned (Sano etal. 1986; Gao etal. 2003; Bradbury etal.
2005). For example, Chalk5 loosens the structure and affects
the content of starch granules, causing chalkiness of rice
grains (Li etal. 2014). Two other genes, ssIIIa and wx, can
synergistically regulate rice grain quality, and molecular
markers linked to these two genes have been designed for
their application in breeding (Zhou etal. 2016b).
Establishment ofgenome databases forrice
breeding
During the implementation of the GSR project, several data-
bases for rice genomic variations were established. These
databases provide key platforms for gene functional research
and whole-genome selection breeding for rice. For example,
a core collection of 3024 rice accessions representing nearly
95% of the total genetic diversity of 780 thousand rice germ-
plasm collection maintained in gene banks worldwide were
re-sequenced and analyzed. As a result, a total of 42 million
single nucleotide polymorphisms (SNPs) and more than 100
thousand structural variations (deletion, translocation, inver-
sion, and duplications) were identified, and ~ 20 thousand
new genes were discovered. The 3K Rice Genome Project
established the pan-genome of the Asian cultivated rice and
revealed its population structure (Wang etal. 2018a). Based
on the information on rice genomic variations, a new multi-
functional and comprehensive rice functional genomics
and breeding database (RFGB) has been established, which
included a rice sequence polymorphism information retrieval
system, an explorer visualization system of the genome, and
data output system for specific genome regions (http://www.
rmbre eding .cn/) (Sun etal. 2016).
Currently, the GSR project integrated the re-sequencing
data of more than 6000 rice genomes worldwide, carried out
haplotype analysis on the whole-genome structural varia-
tions, and investigated the selected genomic regions during
the breeding process. As a result, a database of rice SNPs
(http://varia tion.ic4r.org/) was created. A platform for the
marker-assisted molecular breeding of GSR was established
(http://47.92.174.110), which can help to compare genotypes
and predict the performances of breeding materials. In addi-
tion, the database of rice genomic variations RiceVarMap
v2.0 (http://ricev armap .ncpgr .cn/v2/) was improved, inte-
grating all data on genomic variations, annotation of the
functional variations, phenotypes, and genome-wide asso-
ciation studies (Zhao etal. 2015). These databases provide
abundant information resources for molecular design breed-
ing to develop new GSR varieties with high yield, high qual-
ity, and general adaptability and could help to enhance the
efficiency of GSR breeding (Fig.1) and promote the transi-
tion from the conventional “experience-based breeding” to
the highly accurate and efficiently designed breeding.
Software forgenomic selection breeding
Genomic selection (GS) refers to the establishment of a
correlation between marker genotypes and phenotypes
for predicting performances of breeding populations for
unknown phenotypes based on the markers and pheno-
types of related (smaller) reference populations. One of
the advantages of GS is its higher efficiency relative to
the traditional phenotypic selection methods practiced
in the conventional breeding, as it requires phenotyping
fewer hybrids, and is capable of predicting the phenotypes
of hybrids that have not undergone field tests based on
genotypic data (Xu etal. 2014; Spindel etal. 2016; Yang
etal. 2017). The GSR project developed a GS software
gblup.jar based on the new genomic best linear unbiased
prediction (GBLUP-AD) that includes both the additive
and dominance effects. This software can be used to pre-
dict the performances of multiple traits and environmen-
tal effect. The GBLUP-AD has been used to predict the
phenotypes of rice hybrids based on NCII design, and the
predictive ability was significantly improved (Wang etal.
2017a). Also, the project has designed the gblupdesign.
jar software based on Java which is able to predict the
founder parents with the highest breeding values and the
ideal genotypes to be used for molecular design breeding.
The platform ofgenomic selection breeding
ofrice
The platform of genomic selection breeding established
based on the research findings of genomics, breeding
chips, and high-throughput sequencing provided solid
technical support for the genomics-assisted breeding
strategies and rapid development of new GSR varieties
(Fig.1). This GS technology can be applied to commercial
breeding to accelerate the progress of commercialization
of breeding and promote the transition from the conven-
tional breeding to more accurate and efficient genomic
breeding.
The GSR project has also developed three high-
throughput breeding chips of rice based on Illumina’s
Infinium technology, which constitute a GS technical
system in our GSR breeding efforts. The three breeding
chips include a RICE6K chip (Yu etal. 2014), a RICE60K
chip (Chen etal. 2014), and a RICE90K chip, which
comprise 4473, 43,386, and 85,000 high-quality mark-
ers, respectively. Based on the Hiseq 4000, × Ten, and
BGISEQ-500 sequencing platforms, a high-throughput
and low-cost whole-genome selection breeding platform
that is not restricted by any specific reference genomes
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1435Theoretical and Applied Genetics (2020) 133:1427–1442
1 3
was set up. This platform can be used for the construc-
tion of genetic linkage maps, genetic diversity analysis,
variety identification, and gene/QTL mapping. Currently,
the platform has been widely applied to the analysis of
genetic diversity of rice germplasm, genome-wide associa-
tion studies, and molecular breeding activities (Yu etal.
2016; Qiu etal. 2018; Zhang etal. 2018). For example,
the whole-genome breeding technology has been applied
toward the improvement of biotic resistance of elite rice
cultivars that have been widely grown as founder parents.
The perfect introduction of resistance genes for rice blast
and brown planthopper significantly enhanced the disease/
insect resistance of the parents without altering the overall
agronomic traits. The introduction of multiple blast resist-
ance genes into a single parent or variety has contributed
to the generation of NILs with a highly consistent genetic
background (Wing etal. 2018; Zhang etal. 2018). The
combination of various NILs with different blast resistance
genes resulted in the development of varieties with con-
sistent agronomic traits and high and stable resistance. In
addition, the S5-n and/or f5-n from the wide compatibility
variety Dular were introduced into the restorer line 9311,
and the rapid detection of its background with RICE6K
revealed a background recovery rate as high as 99.4%,
resulting in the generation of improved 9311 with wide
compatibility (Mi etal. 2016).
Development ofnew pre‑breeding GSR lines
withpyramided green genes
Based on the information on cloned green genes and loci,
large-scale cross and backcross breeding was conducted
to generate IL populations and lines abundant in green
traits with wild rice, core germplasm, and specific local
varieties as the donors (Fig.2). As a result, a large number
of restorer lines, male sterile lines, and new pre-breeding
lines with the advantages of disease/insect resistance,
weed-competitive ability, high nitrogen- and phosphorus-
use efficiency, water-saving, drought tolerance, and high
yield and quality were bred (Jiang etal. 2015b, 2016;
Xiao etal. 2016; Wang etal. 2016; Dimaano etal. 2017).
Meanwhile, these lines were screened and identified for
their resistance to drought, low phosphorus, low nitrogen,
weed-competitive ability, blast, bacterial blight, rice false
smut, and rice planthopper, creating a batch of new germ-
plasm with multiple green traits such as multi-resistance,
high nutrient-use efficiency, water-saving, drought toler-
ance, and high yield and quality. For example, the superior
indica varieties HHZ and restorer line 9311, which are
widely planted in central and southern China and later
identified as highly adaptable to Asian and African target
locations, were used as the recipients to breed a series
of disease-/insect-resistant NILs with multiple brown
planthopper resistance genes (such as Bph1, Bph14, and
Bph15) and disease resistance genes (such as Pi2, Pi9,
and Pikm). The dominant genic male sterile line Jiafu-
zhanS was used as a facilitator for outcrossing to generate
new lines with several disease resistance genes (such as
Pi1, Pi2, Xa21, and Xa23). Also, two-line hybrid lines
Y58S, Hua1017S, and Hua1037S harboring various dis-
ease/insect resistance genes (such as Pi2, Pi9, Pikm, Bph3,
Bph14, Bph32, Xa7, Xa21, and Xa23) and elite genes of
aroma were generated, and exhibited excellent application
potential. These research findings will provide abundant
necessary materials for the use of important agronomic
traits and crop improvement, and are of guiding signifi-
cance to the molecular design breeding of NILs with the
target traits.
Globally, more than USD 100 billion are spent annually
for weed control of the crops (Appleby etal. 2001). There-
fore, breeding of weed-competitive (WC) rice varieties is a
critical solution to reduce tillage operations and decrease
hand weeding and herbicide inputs in the direct-seeded rice
system. In this regard, the drought pyramiding GSR variety
IR83140-B-11-B performed well in partial weed control
plots, yielding 2850 and 4610kgha−1 in the wet and dry
seasons at the International Rice Research Institute (IRRI),
respectively(Chauhan etal. 2015). At an early stage of the
crop, the trials showed that grain yield in different GSR gen-
otypes was positively correlated with leaf area. We initiated
the systematic breeding of rice varieties with weed-com-
petitive ability by standardizing the phenotypic screening
protocol to identify the weed-competitive traits related to
early seed germination, early seedling vigor, and weed-com-
petitive components. The breeding materials were developed
from four early-generation backcross populations derived
from one common recipient parent, WTR-1, and four differ-
ent donors, Y134, Zhong 143, Khazar, and Cheng Hui-448.
These ILs were evaluated in three rounds of selection in
upland weed-free, upland-weedy, and lowland-weedy condi-
tions. Five ILs (G-6-L2-WL-3, G-6-RF6-WL-3, G-6-L15-
WU-1, G-6-Y16-WL-2, and G-6-L6-WU-3) were found to
be promising ILs in lowland-weedy conditions, whereas
four ILs (G-6-Y7-WL-3, G-6-Y6-WU-3, G-6-Y3-WL-3, and
G-6-Y8-WU-1) were found to have the highest grain yield
under upland-weedy conditions (Dimaano etal. 2017). For
the molecular genetics of weed-competitive rice cultivars, a
total of 44 QTLs were mapped on 12 chromosomes, except
on chromosomes 4 and 8, by using 677 high-quality SNP
markers. Interestingly, 29 novel genetic loci were associated
with early seed germination and early seedling vigor traits
on chromosomes 1, 3, 5, 6, 7, 10, 11, and 12. The hotspot
regions of chromosomes 11 and 12 were associated with
multiple traits (Dimaano etal. 2019, unpublished). Many of
these QTLs were co-localized with previous reported QTLs,
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1436 Theoretical and Applied Genetics (2020) 133:1427–1442
1 3
which were related to germination rate, germination index,
germination percentage, and germination time in different
genetic backgrounds of mapping populations (Mahender
etal. 2015).
Demonstration andapplication ofGSR
varieties inChina
Based on the latest findings in genomics and bioinformat-
ics research, oriented transfer and pyramiding of the favora-
ble genes associated with rice yield, quality, disease/insect
resistance, drought tolerance, and nutrient-use efficiency
were carried out by using different techniques such as pedi-
gree breeding, backcross breeding, combining ability breed-
ing, marker-assisted selection, and whole-genome selection
breeding (Fig.1), resulting in the generation of new materi-
als with multiple elite genes and GSR varieties with various
desirable traits.
As of the end of 2018, a total of 66 new varieties devel-
oped by the GSR project had been registered in China
(TableS1). The cumulative planting area of these cultivars
over five main rice-growing regions exceeded 6.67 million
hectares from 2014 to 2018, laying a solid foundation for
promoting the sustainable development of rice production.
For instance, in a two-year experiment on nitrogen ferti-
lizer reduction, the partial factor productivity of applied
N of hybrid variety Huiliangyou 630 increased by 10.2%
compared with that of the control; in addition, this variety
is characterized by high quality and resistance to blast and
bacterial blight. Overall, it has reached the standards of a
GSR variety (10% increases in the use efficiency of nitrogen
fertilizer, phosphorus fertilizer, and water, respectively, and
with moderate resistance to one or more main diseases or
insects). The cumulative planting area of Huiliangyou 630
reached 210 thousand hectares during 2015–2018. Under
the reduction of 30% in nitrogen fertilizer, the partial factor
productivity of applied N of Jingliangyouhuazhan in two
years increased by 23.2% relative to that of the control. This
variety also has the characteristics of disease resistance, high
nitrogen-use efficiency, low cadmium accumulation, high
yield and quality, and wide adaptability. The cumulative
planting area of Jingliangyouhuazhan reached 530 thou-
sand hectares during 2016–2018, increasing rice yield by
320 thousand tons and decreasing the input of pesticide and
fertilizer by 160 million yuan (about USD 22.86 million).
Owing to its high grain quality and multiple resistances, the
variety Wushansimiao has been planted on a cumulative area
of 730 thousand hectares in southern China. One new vari-
ety, Wushansizhan, which was derived from Wushansimiao,
is characterized by the advantages of high resistance to blast;
moderate resistance to bacterial blight, lodging, and cold;
and high grain quality.
International popularization andapplication
ofGSR varieties
The demonstration and popularization of new GSR vari-
eties have strongly promoted the development of supe-
rior rice production in the target regions. GSR materials
were systematically introduced to 16 African and Asian
countries with IRRI and AfricaRice for helping in the
adaptation testing, breeding, and capacity building of
local national agricultural research and extension system
(NARES) partners. The GSR project involved 32 Chinese
institutions, universities, academies, and seed companies
partnering in the massive development and deployment
of GSR products (Fig.3). This led to the release of 59
GSR varieties that were adapted to the rice production
areas of Africa and Asia (TableS2). Other 97 GSR culti-
vars were identified as promising and entered into national
cooperative yield trials for their release in different tar-
get countries (TableS3). Among the 59 GSR varieties,
HHZ was released in Mozambique, Indonesia, and India,
demonstrating its wide-adaptation features. Further, HHZ
provided an excellent base recipient parent for introgres-
sion breeding that led to the identification and release of
15 varieties with multiple stress tolerance (with GSR IR1
prefix) across different target countries in Asia and Africa.
Interestingly, GSR variety HHZ was released in Punjab
State in India as PR126 in 2017, which was of short dura-
tion (123days) and yielded on a par with a dominant long-
duration variety (Pusa 44), fitting well in the rice-potato
cropping system. The average productivity per day over a
hectare of PR126 was 61kg vis-à-vis 46.9kg of Pusa 44.
Due to the earliness of PR126, Punjab saved on irrigation
water and fertilizer while keeping the same yield levels
of Pusa 44. PR126 is fast replacing predominant variety
Pusa 44, especially in the rice-potato cropping belt, with
a current adoption area of 31.6% (Veettil etal. 2019). This
variety alone has created enormous socioeconomic and
environmental impacts and is currently being studied. We
have now created several hundred introgression lines with
multiple abiotic stress tolerance in an HHZ background
derived from different donors that outperform the recipient
parent in grain yield and maturity. Soon, these lines may
replace HHZ to create more significant socioeconomic
impacts. Among them, 74 promising derivatives (with
GSR IR1 prefix) in an HHZ background are being evalu-
ated in national cooperative trials in India, Bangladesh,
Pakistan, Indonesia, the Philippines, Mozambique, and
Uganda (TableS3).
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1437Theoretical and Applied Genetics (2020) 133:1427–1442
1 3
An excellent socioeconomic performance has been
achieved by the popularization of GSR varieties in the
target African and Asian countries. Socioeconomic assess-
ment of some GSR varieties bred for rainfed and irrigated
lowland environments in the Philippines and Bangladesh
showed that GSR varieties contribute significantly to the
yield and net income of farmers (Ali etal. 2012; Yorobe
etal. 2016). Compared with conventional rice, GSR vari-
eties showed significantly enhanced yield and economic
output (by 0.89–1.83 tons and USD 230.90 per hectare,
respectively) and disease/insect resistance (Yorobe etal.
2016). Currently, 59 varieties have passed regional tests
and variety approval in countries in South Asia (Bang-
ladesh, India, Pakistan, and Sri Lanka), Southeast Asia
(Indonesia, Laos, Cambodia, the Philippines, and Viet-
nam), and Africa (Mozambique, Uganda, Rwanda, Nige-
ria, Senegal, and Mali) (TableS3). The cumulative area of
the demonstration and popularization of GSR varieties in
African, South Asian, and Southeast Asian countries has
reached about 2.34 million hectares, which marked signifi-
cant contributions to rice production and food security in
these countries (Wang etal. 2018c).
Identication criteria ofGSR varieties
andhighly ecient cultivation systems
The breeding of superior varieties is a genetic approach,
while improved cultivation techniques are non-genetic
approaches to achieve higher grain yield and higher
efficiency. The GSR project has established a complete
assessment system for evaluating the green traits of GSR
varieties and clarifying the related mechanisms. The
establishment of a cultivation and field management sys-
tem for GSR and a comprehensive prevention and con-
trol system for the primary diseases and insects provides
essential support for the promotion of resource-use effi-
ciency based on higher grain yield and stability, and for
ChineseAcademy of Agricultural Sciences (CAAS)
Huazhong Agricultural University (HAU)
ShanghaiAgrobiological Gene Center (SAGC)
ChineseAcademy of Sciences (CAS)
Peking University (PU)
SichuanAcademy of Agricultural Sciences (SAAS)
Guangdong AcademyofAgricultural Sciences (GDAAS)
GuangxiAcademy of Agricultural Sciences (GXAAS)
Helongjiang AcademyofAgriculturalSciences(HLJAAS)
Yunnan AcademyofAgriculturalSciences(YA AS)
Anhui AcademyofAgriculturalSciences(AAAS)
JiangxiAcademy of Agricultural Sciences (JAAS)
ChinaNationalRiceResearchInstitute (CNRRI)
Fujian AcademyofAgriculturalSciences(FAAS)
GuizhouAcademy of Agricultural Sciences (GZAAS)
Ningxia AcademyofAgriculturalSciences(NAAS)
HunanNationalHybridRiceCenter(HNHRC)
Nanjin Agricultural University (NAU)
IRRI AfricaRice
NARES
Tanzania
Ethiopia
Mozambique
Uganda
Rwanda
Bangladesh
India
SriLanka
Pakistan
Indonesia
Vietnam
Laos
Philippines
NARES
Nigeria
Mali
Senegal
32 Chineseinstitutions/companies+26 NARESand partners
Chineseseedcompanies (7)
Chinese-built-agriculturaldemonstrationcenters in
Africancountries(2)
Underlinedare focus
countriesinthird
phaseofproject
CHINA
Fig. 3 The GSR project participants in China, Asia, and Africa in collaboration with IRRI and AfricaRice
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

1438 Theoretical and Applied Genetics (2020) 133:1427–1442
1 3
the environment-friendly and sustainable development of
rice production.
The GSR project also successfully developed a series
of key cultivation techniques for GSR varieties, such as
site-specific nutrient management, precise water-saving
irrigation technology, straw incorporation, and direct seed-
ing (Wang and Peng 2017; Zhou etal. 2017a, b). During
2014–2018, the cumulative application area of GSR cul-
tivation reached 3.48 million hectares (Zhang etal. 2018),
thereby reducing the cost of fertilizer, pesticide, and water
by 12.34 billion yuan (about USD 1.76 billion) in China
alone.
The component “High-Yielding and Efficient Cultivation
Technology of Ratooned Rice with Main Crop Harvested
Mechanically” of the GSR project integrates ratoon rice
varieties of high quality and yield and a series of key culti-
vation techniques. This project has implemented the dem-
onstration and application of ratooned rice in large areas
of Hubei Province, China, with a demonstration area of
nearly 270 thousand hectares. In Hunan Province, a high-
efficiency and high-yield cultivation technical system has
been assembled, which is characterized by resistance to cold,
high temperature, lodging, and banded sclerotial blight, and
enhanced seedling regeneration ability. During 2014–2018,
the cumulative application area of GSR cultivation was 110
thousand hectares. In Guangdong Province, the demonstra-
tion and application of “water- and fertilizer-saving” culti-
vation were conducted. During 2014–2016, the cumulative
application area of this cultivation technique in this province
reached 2.67 million hectares, reducing the cost of fertilizer
and pesticide by 1.97 billion yuan (about USD 28 million),
and increasing rice grain yield by 1.84 million tons and
income by 7.31 billion yuan (about USD 1.04 billion).
Prospects ofGSR development
The world population is expected to reach nine billion in
2050. The rapid increase in population demands corre-
sponding increases in rice production in a sustainable way,
which will be a great challenge to global rice breeders in
future decades. GSR is therefore a vital concept proposed
to meet this challenge since GSR varieties can maintain
stable and higher yield with less inputs, and have stronger
resistance and recoverability features when facing the fre-
quent occurrence of extreme stresses caused by climate
changes. The practice in the past decade has demonstrated
that the combination of GSR varieties and corresponding
improved cultivation techniques can contribute to more
stable and higher yields, and at the same time reduce the
application of pesticide and fertilizer by more than 30%,
as well as irrigation water by at least 30% in irrigated
rice production areas. GSR may become a vital pattern to
lead the green development of agriculture, and its goals
and whole-genome breeding strategies may provide pat-
terns or set examples for the development of other crops.
The implementation of the GSR project has led to and
promoted the transition of breeding goals and production
modes of crops in China, and across the world (Wing etal.
2018).
The strategies to breed GSR varieties using multiple-
omics not only greatly promote breeding accuracy and
efficiency but also accelerate the commercialization and
all-around transition and upgrading of crop breeding. By
combining the abundant germplasm accessions, functional
genomics, and molecular breeding with whole-genome
selection, a large number of new varieties and accessions
were used in the pyramiding of elite genes in pedigree breed-
ing and backcross breeding. These varieties and accessions
harbor various elite genes associated with high yield, supe-
rior grain quality, disease/insect resistance, drought toler-
ance, and higher nutrient efficiency. Genome-editing tech-
nology is becoming a key technology for genomic breeding
owing to its advantages of high efficiency, low cost, and
safety. For example, CRISPR/Cas technology provides effi-
cient and versatile tools for efficient targeted modification
of the genes of agricultural importance in crops and pre-
cision crop breeding (Chen etal. 2019a). Compared with
conventional breeding, it greatly promotes the efficiency
of pyramiding elite genes, and can create more abundant
genetic resources with high yield, superior grain quality, and
tolerance to various stresses.
During the demonstration and popularization of GSR
varieties, technical training programs have conveyed the
green concept and cultivation techniques of high quality,
high yield, and efficiency to farmers, which significantly
improves the technical quality of the workers or farmers in
these areas. Also, the integration and innovation of green
varieties and cultivation techniques have optimized rice
production techniques, enhanced per unit area yield, and
increased the income of farmers. An international network
for cooperation involving the IRRI and AfricaRice, along
with NARES partners in Africa and Asia, was established.
In the short term, more and better GSR varieties with high
adaptability to climate changes should be bred, alongside the
development of corresponding green yield- and efficiency-
promoting cultivation techniques. These goals require active
cooperation among various fields of breeding, agronomy,
agricultural machinery, and agricultural economics, with the
sole purpose of increasing the income of small farm house-
holds in the target countries, ensuring food security, and pro-
moting the sustainable development of global agriculture.
Acknowledgements This research was supported by grants from
National High Technology Research and Development of China
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1439Theoretical and Applied Genetics (2020) 133:1427–1442
1 3
(2014AA10A600) and the Bill and Melinda Gates Foundation
(OPP1130530).
Author contributions QZ had the idea for the review. CZ performed
the literature collection. SY and JA drafted the manuscript. QZ and ZL
revised the manuscript.
Compliance with ethical standards
Conflict of interest The authors declare that they have no conflict of
interest.
Open Access This article is licensed under a Creative Commons Attri-
bution 4.0 International License, which permits use, sharing, adapta-
tion, distribution and reproduction in any medium or format, as long
as you give appropriate credit to the original author(s) and the source,
provide a link to the Creative Commons licence, and indicate if changes
were made. The images or other third party material in this article are
included in the article’s Creative Commons licence, unless indicated
otherwise in a credit line to the material. If material is not included in
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References
Ali J, Xu JL, Gao YM, Fontanillo MA (2012) Innovative Green Super
Rice (GSR) molecular breeding strategy: achievements and
advances. Philipp J Crop Sci 37:49
Ali J, Jewel ZA, Mahender A, Anandan A, Hernandez J, Li ZK (2018)
Molecular genetics and breeding for nutrient use efficiency in
rice. Int J Mol Sci 19:1762
Appleby AP, Müller F, Carpy S (2001) Weed control. Ullmann’s Ency-
clopedia of Industrial Chemistry. Wiley–VCH Verlag GmbH &
Co. KGaA, New York
Balachiranjeevi CH, Prahalada GD, Mahender A, Jamaloddin Md,
Sevilla MAL, Marfori-Nazarea CM, Vinarao R etal (2019) Iden-
tification of a novel locus, BPH38(t), conferring resistance to
brown planthopper (Nilaparvata lugens Stal.) using early back-
cross population in rice (Oryza sativa L.). Euphytica 215:185
Bradbury LMT, Fitzgerald TL, Henry RJ, Jin QS, Waters DLE (2005)
The gene for fragrance in rice. Plant Biotechnol J 3:363–370
Chauhan BS, Opeña J, Ali J (2015) Response of 10 elite “Green Super
Rice” genotypes to weed infestation in aerobic rice systems.
Plant Prod Sci 18:228–233
Che RH, Tong HN, Shi BH, Liu YQ, Fang SR, Liu DP, Xiao YH etal
(2015) Control of grain size and rice yield by GL2-mediated
brassinosteroid responses. Nat Plants 2:15195
Chen HD, Xie WB, He H, Yu HH, Chen W, Li J, Yu RB etal (2014) A
high-density SNP genotyping array for rice biology and molecu-
lar breeding. Mol Plant 7:541–553
Chen SX, Lin ZC, Zhou DG, Wang CR, Li H, Yu RB, Deng HC etal
(2017) Genome-wide study of an elite rice pedigree reveals a
complex history of genetic architecture for breeding improve-
ment. Sci Rep 7:45685
Chen K, Wang Y, Zhang R, Zhang H, Gao C (2019a) CRISPR/Cas
genome editing and precision plant breeding in agriculture. Annu
Rev Plant Biol 70:667–697
Chen XL, Jiang LR, Zheng JS, Chen FY, Wang TS, Wang ML, Tao Y
etal (2019b) A missense mutation in LGS1 increases grain size
and enhances cold tolerance in rice. J Exp Bot 70:3851–3866
Deng YW, Zhai K, Xie Z, Yang DY, Zhu XD, Liu JZ, Wang X etal
(2017) Epigenetic regulation of antagonistic receptors confers
rice blast resistance with yield balance. Science 355:962–965
Dimaano NGB, Ali J, Cruz PCS, Baltazar AM, Diaz MGQ, Acero BL
Jr, Li ZK (2017) Performance of newly developed weed-compet-
itive rice cultivars under lowland and upland weedy conditions.
Weed Sci 65:798–817
Duan PG, Ni S, Wang JM, Zhang BL, Xu R, Wang YX, Chen HQ etal
(2015) Regulation of OsGRF4 by OsmiR396 controls grain size
and yield in rice. Nat Plants 2:15203
Elert E (2014) Rice by the numbers: a good grain. Nature 514:50–51
Fan XR, Xie D, Chen JG, Lu HY, Xu YL, Ma C, Xu GH (2014) Over-
expression of OsPTR6 in rice increased plant growth at different
nitrogen supplies but decreased nitrogen use efficiency at high
ammonium supply. Plant Sci 227:1–11
Fan XR, Tang Z, Tan YW, Zhang Y, Luo BB, Yang M, Lian XM
etal (2016) Overexpression of a pH-sensitive nitrate trans-
porter in rice increases crop yields. Proc Natl Acad Sci USA
113:7118–7123
FAO (2013) FAOSTAT. http://www.fao.org/faost at/en/
Feng B, Chen K, Cui YR, Wu ZC, Zheng TQ, Zhu YJ, Ali J etal
(2018) Genetic dissection and simultaneous improvement of
drought and low nitrogen tolerances by designed QTL pyra-
miding in rice. Front Plant Sci 9:306
Gao ZY, Zeng DL, Cui X, Zhou YH, Yan MX, Huang DN, Li JY etal
(2003) Map-based cloning of the ALK gene, which controls
the gelatinization temperature of rice. Sci China Ser C: Life
Sci 46:661–668
Guo JP, Xu CX, Wu D, Zhao Y, Qiu YF, Wang XX, Ouyang YD etal
(2018) Bph6 encodes an exocyst-localized protein and confers
broad resistance to planthoppers in rice. Nat Genet 50:297–306
Hazell P, Pomerada C, Valdez A (1986) Crop insurance for agri-
cultural development: issues and experience. J Risk Insur
54:832–833
Hu HH, Xiong LZ (2014) Genetic engineering and breeding of
drought-resistant crops. Annu Rev Plant Biol 65:715–741
Hu B, Wang W, Ou SJ, Tang JY, Li H, Che RH, Zhang ZH etal (2015a)
Variation in NRT1.1B contributes to nitrate-use divergence
between rice subspecies. Nat Genet 47:834–838
Hu J, Wang YX, Fang YX, Zeng LJ, Xu J, Yu HP, Shi ZY etal (2015b)
A rare allele of GS2 enhances grain size and grain yield in rice.
Mol Plant 8:1455–1465
Hu J, Xiao C, He YQ (2016) Recent progress on the genetics and
molecular breeding of brown planthopper resistance in rice. Rice
9:30
Hu KM, Cao JB, Zhang J, Xia F, Ke YG, Zhang HT, Xie WY etal
(2017) Improvement of multiple agronomic traits by a disease
resistance gene via cell wall reinforcement. Nat Plants 3:17009
Hu ZJ, Lu SJ, Wang MJ, He HH, Sun L, Wang HR, Liu XH etal (2018)
A novel QTL qTGW3 encodes the GSK3/SHAGGY-like kinase
OsGSK5/OsSK41 that interacts with OsARF4 to negatively regu-
late grain size and weight in rice. Mol Plant 11:736–749
Huang LY, Zhang F, Zhang F, Wang WS, Zhou YL, Fu BY, Li ZK
(2014) Comparative transcriptome sequencing of tolerant rice
introgression line and its parents in response to drought stress.
BMC Genom 15:1026
Ismail AM, Singh US, Singh S, Dar MH, Mackill DJ (2013) The con-
tribution of submergence-tolerant (Sub1) rice varieties to food
security in flood-prone rainfed lowland areas in Asia. Field Crops
Res 152:83–93
Jewel ZA, Ali J, Mahender A, Hernandez J, Pang YL, Li ZK (2019a)
Identification of quantitative trait loci associated with nutrient
use efficiency traits, using SNP markers in an early backcross
population of rice (Oryza sativa L). Int J Mol Sci 20:900
Jewel ZA, Ali J, Pang YL, Mahender A, Acero B, Hernandez JE, Xu
JL etal (2019b) Developing green super rice varieties with high
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

1440 Theoretical and Applied Genetics (2020) 133:1427–1442
1 3
nutrient use efficiency by phenotypic selection under varied
nutrient conditions. Crop J 3:368–377
Jiang JF, Mou TM, Yu HH, Zhou FS (2015a) Molecular breeding of
thermo-sensitive genic male sterile (TGMS) lines of rice for blast
resistance using Pi2 gene. Rice 8:11
Jiang JF, Yang DB, Ali J, Mou TM (2015b) Molecular marker-assisted
pyramiding of broad-spectrum disease resistance genes, Pi2 and
Xa23, into GZ63-4S, an elite thermo-sensitive genic male-sterile
line in rice. Mol Breed 35:83
Jiang JF, Mi JM, Ali J, Mu TM (2016) Development of broad-spectrum
bacterial blight resistance into thermo-sensitive genic male ster-
ile lines. Plant Breed 135:73–79
Jing RL (2007) Advances of research on drought resistance and water
use efficiency in crop plants. Rev China Agric Sci Technol 9:1–5
Khush GS (2001) Green revolution: the way forward. Nat Rev Genet
2:815–822
Li ZK, Ali J (2017) Breeding green super rice (GSR) varieties for
sustainable rice cultivation. Burleigh Dodds Science Publishing,
Washington. https ://doi.org/10.19103 /AS.2016.0003.05
Li YB, Fan CC, Xing YZ, Yun P, Luo LJ, Yan B, Peng B etal (2014)
Chalk5 encodes a vacuolar H + –translocating pyrophosphatase
influencing grain chalkiness in rice. Nat Genet 46:398–404
Li XM, Chao DY, Wu Y, Huang XH, Chen K, Cui LG, Su L etal
(2015) Natural alleles of a proteasome α2 subunit gene contribute
to thermo tolerance and adaptation of African rice. Nat Genet
47:827–833
Li WT, Zhu ZW, Chern MS, Yin JJ, Yang C, Ran L, Cheng MP etal
(2017) A natural allele of a transcription factor in rice confers
broad-spectrum blast resistance. Cell 170:114–126
Li S, Tian YH, Wu K, Ye YF, Yu JP, Zhang JQ, Liu Q etal (2018a)
Modulating plant growth–metabolism coordination for sustain-
able agriculture. Nature 560:595–600
Li Y, Xiao JH, Chen LL, Huang XH, Cheng ZK, Han B, Zhang Q
etal (2018b) Rice functional genomics research: past decade and
future. Mol Plant 11:1–22
Liang YT, Meng LJ, Lin XY, Cui YR, Pang YL, Xu JL, Li ZK (2018)
QTL and QTL networks for cold tolerance at the reproductive
stage detected using selective introgression in rice. PLoS ONE
13:e0200846
Lin CM, Koh S, Stacey G, Yu SM, Lin TY, Tsay YF (2000) Clon-
ing and functional characterization of a constitutively expressed
nitrate transporter gene, OsNRT1, from rice. Plant Physiol
122:379–388
Liu YQ, Wu H, Chen H, Liu YL, He J, Kang HY, Sun ZG etal (2015)
A gene cluster encoding lectin receptor kinases confers broad-
spectrum and durable insect resistance in rice. Nat Biotechnol
33:301–305
Liu ZY, Zhu CS, Jiang Y, Tian YL, Yu J, An HZ, Tang WJ etal (2016)
Association mapping and genetic dissection of nitrogen use effi-
ciency-related traits in rice (Oryza sativa L.). Funct Int Genom
16:323–333
Liu JF, Chen J, Zheng XM, Wu FQ, Lin QB, Heng YQ, Tian P etal
(2017) GW5 acts in the brassinosteroid signalling pathway to
regulate grain width and weight in rice. Nat Plants 3:17043
Liu CT, Shujun O, Mao BG, Tang JY, Wang W, Wang HR, Cao SY
etal (2018a) Early selection of bZIP73 facilitated adaptation of
japonica rice to cold climates. Nat Commun 9:3302
Liu Q, Han RX, Wu K, Zhang JQ, Ye YF, Wang SS, Chen JF etal
(2018b) G-protein βγ subunits determine grain size through
interaction with MADS–domain transcription factors in rice.
Nat Commun 9:852
Luo LJ (2010) Breeding for water-saving and drought-resistance rice
(WDR) in China. J Exp Bot 61:3509–3517
Lv Y, Guo ZL, Li XK, Ye HY, Li XH, Xiong LZ (2016) New insights
into the genetic basis of natural chilling and cold shock tolerance
in rice by genome-wide association analysis. Plant, Cell Environ
39:556–570
Ma Y, Dai XY, Xu YY, Luo W, Zheng XM, Zeng DL, Pan YJ
etal (2015) COLD1 confers chilling tolerance in rice. Cell
160:1209–1221
Mahender A, Anandan A, Pradhan SK (2015) Early seedling vig-
our, an imperative trait for direct-seeded rice: an overview on
physio-morphological parameters and molecular markers. Planta
241:1027–1050
Mahender A, Ali J, Prahalada GD, Sevilla MAL, Balachiranjeevi CH,
Md J, Maqsood U etal (2019) Genetic dissection of develop-
mental responses of agro-morphological traits under different
doses of nutrient fertilizers using high-density SNP markers.
PLoS ONE 14:e0220066
Mao DH, Xin YY, Tan YJ, Hu XJ, Bai JJ, Liu ZY, Yu YL etal (2019)
Natural variation in the HAN1 gene confers chilling tolerance
in rice and allowed adaptation to a temperate climate. Proc Natl
Acad Sci USA 116:3494–3501
Mi JM, Li GW, Huang JY, Yu HH, Zhou FS, Zhang Q, Ouyang YD
etal (2016) Stacking S5-n and f5-n to overcome sterility in
indica–japonica hybrid rice. Theor Appl Genet 129:563–575
Peng SB, Huang JL, Zhong XH, Yang JC, Wang GH, Zou YB, Zhang
FS etal (2002) Research strategy in improving fertilizer nitro-
gen use efficiency of irrigated rice in China. Agric Sci China
35:1095–1103
Peng B, Kong H, Li Y, Zhong M, Sun L, Gao GJ, Zhang QL etal
(2014) OsAAP6 functions as an important regulator of grain
protein content and nutritional quality in rice. Nat Commun
5:4847
Qiu XJ, Chen K, Lv WK, Ou XX, Zhu YJ, Xing DY, Yang LW etal
(2017) Examining two sets of introgression lines reveals back-
ground independent and stably expressed QTL that improve
grain appearance quality in rice (Oryza sativa L.). Theor Appl
Genet 130:951–967
Qiu SQ, Lu Q, Yu HH, Ni XM, Zhang GY, He H, Xie WB etal
(2018) The development and application of rice whole genome
selection breeding platform. Chin Bull Life Sci 30:1120–1128
Redillas MC, Jeong JS, Kim YS, Jung H, Bang SW, Choi YD, Ha
SH etal (2012) The overexpression of OsNAC9 alters the
root architecture of rice plants enhancing drought resistance
and grain yield under field conditions. Plant Biotechnol J
10:792–805
Ren ZH, Gao JP, Li LG, Cai XL, Huang W, Chao DY, Zhu MZ etal
(2005) A rice quantitative trait locus for salt tolerance encodes a
sodium transporter. Nat Genet 37:1141–1146
Sano Y, Katsumata M, Okuno K (1986) Genetic studies of speciation
in cultivated rice. 5. inter- and intraspecific differentiation in the
waxy gene expression of rice. Euphytica 35:1–9
Si LZ, Chen JY, Huang XH, Gong H, Luo JH, Hou QQ, Zhou TY etal
(2016) OsSPL13 controls grain size in cultivated rice. Nat Genet
48:447–456
Spindel JE, Begum H, Akdemir D, Collard B, Redoña E, Jannink JL,
McCouch S (2016) Genome-wide prediction models that incor-
porate de novo GWAS are a powerful new tool for tropical rice
improvement. Heredity 116:395–408
Sun HY, Qian Q, Wu K, Luo JJ, Wang SS, Zhang CW, Ma YF etal
(2014) Heterotrimeric G proteins regulate nitrogen-use efficiency
in rice. Nat Genet 46:652–656
Sun WQ, Zhou QL, Yao Y, Qiu XJ, Xie K, Yu SB (2015) Identification
of genomic regions and the isoamylase gene for reduced grain
chalkiness in rice. PLoS ONE 10:e0122013
Sun C, Hu ZQ, Zheng TQ, Lu KC, Zhao Y, Wang W, Shi J etal (2016)
RPAN: rice pan-genome browser for ~ 3000 rice genomes. Nucl
Acids Res 45:597–605
Tian DS, Wang JX, Zeng X, Gu KY, Qiu CX, Yang XB, Zhou ZY
etal (2014) The rice TAL effector–dependent resistance protein
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

1441Theoretical and Applied Genetics (2020) 133:1427–1442
1 3
XA10 triggers cell death and calcium depletion in the endoplas-
mic reticulum. Plant Cell 26:497–515
Uga Y, Sugimoto K, Ogawa S, Rane J, Ishitani M, Hara N, Kitomi
Y etal (2013) Control of root system architecture by DEEPER
ROOTING 1 increases rice yield under drought conditions. Nat
Genet 45:1097–1102
Veettil PC, Gupta, I, Ali J (2019) “GSR adoption and impacts in Pun-
jab, India.” Paper presented at the achieving improved income
and livelihood by adopting Green Super Rice in Asia and Africa:
the conclusion meeting of the Green Super Rice Project, Beijing,
China. April 1–3, 2019
Wang F, Peng SB (2017) Yield potential and nitrogen use efficiency of
China’s super rice. J Int Agric 16:60345–60347
Wang BB, Wang HY (2017) IPA1: a new “green revolution” gene?
Mol Plant 10:779–781
Wang SK, Wu K, Yuan QB, Liu XY, Liu ZB, Lin XY, Zeng RZ etal
(2012a) Control of grain size, shape and quality by OsSPL16 in
rice. Nat Genet 44:950–954
Wang WH, Kohler B, Cao FQ, Liu GW, Gong YY, Sheng S, Song QC
etal (2012b) Rice DUR3 mediates high-affinity urea transport
and plays an effective role in improvement of urea acquisition
and utilization when expressed in Arabidopsis. New Phytol
193:432–444
Wang Q, Liu YQ, He J, Zheng XM, Hu JL, Liu YL, Dai HM etal
(2014) STV11 encodes a sulphotransferase and confers durable
resistance to rice stripe virus. Nat Commun 5:4768
Wang SK, Li S, Liu Q, Wu K, Zhang JQ, Wang SS, Wang Y etal
(2015a) The OsSPL16-GW7 regulatory module determines grain
shape and simultaneously improves rice yield and grain quality.
Nat Genet 47:949–954
Wang WS, Fu BY, Ali J, Xu JL, Gao YM, Zheng TQ, Zhang F etal
(2015b) Genome wide responses to selection and genetic net-
works underlying submergence tolerance in rice. Plant Genom
8:1–13
Wang YX, Xiong GS, Hu J, Jiang L, Hu Y, Xu J, Fang YX etal (2015c)
Copy number variation at the GL7 locus contributes to grain size
diversity in rice. Nat Genet 47:944–948
Wang HB, Ye ST, Mou TM (2016) Molecular breeding of rice restorer
lines and hybrids for brown planthopper (BPH) resistance using
the Bph14 and Bph15 genes. Rice 9:53
Wang SS, Wu K, Qian Q, Liu Q, Li Q, Pan YY, Ye YF etal (2017a)
Non-canonical regulation of SPL transcription factors by a
human OTUB1-like deubiquitinase defines a new plant type
rice associated with higher grain yield. Cell Res 27:1142–1156
Wang X, Li L, Yang Z, Zheng X, Yu S, Xu C, Zhu Z (2017b) Pre-
dicting rice hybrid performance using univariate and multivari-
ate GBLUP models based on North Carolina mating design II.
Heredity 118:302–310
Wang J, Zhou L, Shi H, Chern M, Yu H, Yi H, He M etal (2018a) A
single transcription factor promotes both yield and immunity in
rice. Science 361:1026–1028
Wang WS, Gao YM, Li ZK, Xu JL (2018b) “Green Super Rice” achiev-
ing sustainable development of agricultural production in Asian
and African countries. Chin Bull Life Sci 30:1090–1099
Wang WS, Mauleon R, Hu ZQ, Chebotarov D, Tai SH, Wu ZC, Li M
etal (2018c) Genomic variation in 3,010 diverse accessions of
Asian cultivated rice. Nature 557:43–49
Wing RA, Purugganan MD, Zhang Q (2018) The rice genome revolu-
tion: from an ancient grain to Green Super Rice. Nat Rev Genet
19:505–517
Wu Y, Wang Y, Mi XF, Shan JX, Li XM, Xu JL, Lin HX (2016) The
QTL GNP1 encodes GA20ox1, which increases grain number
and yield by increasing cytokinin activity in rice panicle meris-
tems. PLoS Genet 12:e1006386
Xia D, Zhou H, Liu RJ, Dan WH, Li PB, Wu B, Chen JX etal (2018)
GL3.3, a novel QTL encoding a GSK3/SHAGGY-like kinase,
epistatically interacts with GS3 to produce extra-long grains in
rice. Mol Plant 11:754–756
Xiao C, Hu J, Ao YT, Cheng XM, Gao GJ, Zhang QL, He GC (2016)
Development and evaluation of near-isogenic lines for brown
planthopper resistance in rice cv. 9311. Sci Rep 6:38159
Xie WB, Wang GW, Yuan M, Yao W, Lv K, Zhao H, Yang M (2015)
Breeding signatures of rice improvement revealed by a genomic
variation map from a large germplasm collection. Proc Natl Acad
Sci USA 112:5411–5419
Xing YZ, Zhang Q (2010) Genetic and molecular bases of rice yield.
Annu Rev Plant Biol 61:421–442
Xu SZ, Zhu D, Zhang Q (2014) Predicting hybrid performance in rice
using genomic best linear unbiased prediction. Proc Natl Acad
Sci USA 111:12456–12461
Yang J, Mezmouk S, Baumgarten A, Buckler ES, Guill KE, McMullen
MD, Mumm MH etal (2017) Incomplete dominance of deleteri-
ous alleles contributes substantially to trait variation and hetero-
sis in maize. PLoS Genet 13:e1007019
Ying JZ, Ma M, Bai C, Huang XH, Liu JL, Fan YY, Song XJ (2018)
TGW3, a major QTL that negatively modulates grain length and
weight in rice. Mol Plant 11:750–753
Yorobe JM, Ali J, Pede VO, Rejesusd RM, Velarde OP (2016) Yield
and income effects of rice varieties with tolerance of multiple
abiotic stresses: the case of green super rice (GSR) and flooding
in the Philippines. Agric Econ 47:261–271
Yu HH, Xie WB, Li J, Zhou FS, Zhang Q (2014) A whole genome SNP
array (RICE6K) for genomic breeding in rice. Plant Biotechnol
J 12:28–37
Yu SB, Tang XX, Luo LJ (2016) Recent advances in rice functional
genomics and Green Super Rice development. Chin Bull Life
Sci 28:1287–1294
Zhang Q (2007) Strategies for developing Green Super Rice. Proc Natl
Acad Sci USA 104:16402–16409
Zhang F, Zhang F, Huang LY, Cruz CV, Ali J, Xu JL, Zhou YL etal
(2016) Overlap between signaling pathways responsive to Xan-
thomonas oryzae pv. oryzae infection and drought stress in rice
introgression line revealed by RNA-Seq. J Plant Growth Regul
35:345–356
Zhang L, Yu H, Ma B, Liu GF, Wang JJ, Wang JM, Gao RC etal
(2017a) A natural tandem array alleviates epigenetic repres-
sion of IPA1 and leads to superior yielding rice. Nat Commun
8:14789
Zhang ZY, Li JJ, Pan YH, Li JH, Zhou L, Shi HL, Zeng YW etal
(2017b) Natural variation in CTB4a enhances rice adaptation to
cold habitats. Nat Commun 8:14788
Zhang CP, Yu SB, Zhang Q (2018) Recent advances in Green Super
Rice development. Chin Bull Life Sci 30:1083–1089
Zhang JY, Liu YX, Zhang N, Hu B, Jin T, Xu HR, Qin Y etal (2019)
NRT1.1B is associated with root microbiota composition and
nitrogen use in field-grown rice. Nat Biotechnol 37:676–684
Zhao H, Yao W, Ouyang YD, Yang WN, Wang GW, Lian XM, Xing
YZ etal (2015) RiceVarMap: a comprehensive database of rice
genomic variations. Nucl Acids Res 43:1018–1022
Zhao Y, Huang J, Wang ZZ, Jing SL, Wang Y, Ouyang YD, Cai BD
etal (2016) Allelic diversity in an NLR gene BPH9 enables
rice to combat planthopper variation. Proc Natl Acad Sci USA
113:12850–12855
Zhou DG, Chen W, Lin ZC, Che HD, Wang CR, Li H, Yu RB etal
(2016a) Pedigree-based analysis of derivation of genome seg-
ments of an elite rice reveals key regions during its breeding.
Plant Biotechnol J 14:638–848
Zhou HJ, Wang LJ, Liu GF, Meng XB, Jing YH, Shu XL, Kong XL
etal (2016b) Critical roles of soluble starch synthase SSIIIa and
Content courtesy of Springer Nature, terms of use apply. Rights reserved.

1442 Theoretical and Applied Genetics (2020) 133:1427–1442
1 3
granule-bound starch synthase Waxy in synthesizing resistant
starch in rice. Proc Natl Acad Sci USA 113:12844–12849
Zhou Q, Ju CX, Wang ZQ, Zhang H, Liu LJ, Yang JC, Zhang JH
(2017a) Grain yield and water use efficiency of super rice under
soil water deficit and alternate wetting and drying irrigation. J
Int Agric 16:1028–1043
Zhou Y, Tao YJ, Tang DN, Wang J, Zhong J, Wang Y, Yuan QM etal
(2017b) Identification of QTL associated with nitrogen uptake
and nitrogen use efficiency using high throughput genotyped
CSSLs in rice (Oryza sativa L.). Front Plant Sci 8:1166
Zhu XY, Xiong LZ (2013) Putative megaenzyme DWA1 plays
essential roles in drought resistance by regulating stress-
induced wax deposition in rice. Proc Natl Acad Sci USA
110:17790–17795
Zhu YJ, Chen K, Mi XF, Chen TX, Ali J, Ye GY, Xu JL etal (2015)
Identification and fine mapping of a stably expressed QTL for
cold tolerance at the booting stage using an interconnected breed-
ing population in rice. PLoS ONE 10:e0145704
Publisher’s Note Springer Nature remains neutral with regard to
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Content courtesy of Springer Nature, terms of use apply. Rights reserved.

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