The Biotechnology Roadmap for Sugarcane Improvement
Carlos T. Hotta & Carolina G. Lembke & Douglas S. Domingues & Edgar A. Ochoa &
Guilherme M. Q. Cruz & Danila M. Melotto-Passarin & Thiago G. Marconi &
Melissa O. Santos & Marcelo Mollinari & Gabriel R. A. Margarido &
Augusto César Crivellari & Wanderley D. dos Santos & Amanda P. de Souza &
Andrea A. Hoshino & Helaine Carrer & Anete P. Souza & Antônio A. F. Garcia &
Marcos S. Buckeridge & Marcelo Menossi & Marie-Anne Van Sluys & Glaucia M. Souza
Received: 7 December 2009 /Accepted: 11 March 2010 /Published online: 8 April 2010
# Springer Science+Business Media, LLC 2010
Abstract Due to the strategic importance of sugarcane to
Brazil, FAPESP, the main São Paulo state research funding
agency, launched in 2008 the FAPESP Bioenergy Research
Program (BIOEN, http://bioenfapesp.org). BIOEN aims to
generate new knowledge and human resources for the
improvement of the sugarcane and ethanol industry. As part
of the BIOEN program, a Workshop on Sugarcane
Improvement was held on March 18th and 19th 2009 in
São Paulo, Brazil. The aim of the workshop was to explore
present and future challenges for sugarcane improvement
and its use as a sustainable bioenergy and biomaterial
feedstock. The workshop was divided in four sections that
represent important challenges for sugarcane improvement:
a) gene discovery and sugarcane genomics, b) transgenics
and controlled transgene expression, c) sugarcane physiol-
ogy (photosynthesis, sucrose metabolism, and drought) and
d) breeding and statistical genetics. This report summarizes
the roadmap for the improvement of sugarcane.
Keywords Sugarcane . Breeding . Transgenics . Genome .
Physiology
Communicated by: Ray Ming
C. T. Hotta : C. G. Lembke : G. M. Souza (*)
Departamento de Bioquímica, Instituto de Química, Universidade
de São Paulo,
Av. Prof. Lineu Prestes 748, CEP 05508-000,
São Paulo, SP, Brazil
e-mail: glmsouza@iq.usp.br
D. S. Domingues : E. A. Ochoa : G. M. Q. Cruz :
A. C. Crivellari : W. D. dos Santos : A. P. de Souza :
M. S. Buckeridge : M.-A. Van Sluys
Departamento de Botânica, Instituto de Biociências,
Universidade de São Paulo,
Rua do Matão, 277, CEP 05508-090,
São Paulo, SP, Brazil
D. M. Melotto-Passarin : H. Carrer
Departamento de Ciências Biológicas, Escola Superior de
Agricultura Luiz de Queiroz, Universidade de São Paulo,
CEP 13418-900,
Piracicaba, SP, Brazil
T. G. Marconi : M. O. Santos : A. P. Souza
Departamento de Biologia Vegetal, Instituto de Biologia,
Universidade Estadual de Campinas,
CEP 13083-970,
Campinas, SP, Brazil
T. G. Marconi : M. O. Santos : A. P. Souza
Centro de Biologia Molecular e Engenharia Genética,
Universidade Estadual de Campinas,
CP 6010, CEP 13083-970,
Campinas, SP, Brazil
M. Mollinari : G. R. A. Margarido : A. A. Hoshino : M. Menossi
Departamento de Genética, Evolução e Bioagentes, Instituto de
Biologia, Universidade Estadual de Campinas,
CEP 13083-862,
Campinas, SP, Brasil
A. A. F. Garcia
Departamento de Genética, Escola Superior de Agricultura Luiz
de Queiroz, Universidade de São Paulo,
CEP 13400-970,
Piracicaba, SP, Brasil
Tropical Plant Biol. (2010) 3:75–87
DOI 10.1007/s12042-010-9050-5

Abbreviations
BIOEN FAPESP bioenergy research program
EST Expressed sequence tag
SUCEST The sugarcane EST project
SAS Sugarcane assembled sequences
BAC Bacterial artificial chromosome
TE Transposable element
NADP-ME NADP+−malic enzyme
NAD-ME NAD+−malic enzyme
PCK Phosphoenolpyruvate carboxykinase
MAS Marker assisted selection
SNP Single nucleotide polymorphism
NGS Next generation sequencing
QTL Quantitative trait loci
Gene Discovery and Sugarcane Genomics
Gene discovery and genomics are essential tools for the
future of sugarcane improvement. However, gaps in our
knowledge and technical constrains prevent us to take full
advantage of these tools. Polyploidy and aneuploidy are the
major factors that make molecular characterization of
Saccharum genomes difficult. The genome of sugarcane
hybrid cultivars is generally a mosaic of the genomes of
two to four Saccharum species. Hybrids are estimated to
contain 100–120 chromosomes constituted with a total of
10 Gbp of DNA (D’Hont and Glaszmann 2001; D’Hont
2005). In the sugarcane cultivar R570, 80% of the
chromosomes are inherited from Saccharum officinarum,
10% are inherited from S. spontaneum, and the remaining
10% are a combination of the two species (D’Hont et al.
1996). Ribosomal DNA cytogenetic mapping (D’Hont et
al. 1998) suggests that S. officinarum has a basic
chromosome number of x=10 and S. spontanenum has a
basic number of x=8, with ploidy levels between 5 and 16
(Ha et al. 1999).
Although there has been a considerable increase in
knowledge about the sugarcane genome, there are many
areas that are not yet adequately addressed. For example,
sugarcane chromatin structure and methylation have not
been well studied. It is already known from other plant
species that there are rapid changes in chromatin modifica-
tion and transcriptional regulation in synthetic allopoly-
ploids (Chen and Ni 2006) but such studies have not been
performed in sugarcane.
Sequencing of sugarcane ESTs greatly contributed to the
gene discovery process. Prior to June 1996, the public
databases of DNA sequences had only 28 sequences from
sugarcane compared to the 250,000 sugarcane sequences
that are deposited to date (R.E. Casu, personal communi-
cation). EST collections have been developed by research
groups in South Africa (Carson and Botha 2000), Australia
(Casu et al. 2003) and United States (Ma et al. 2004). The
largest program of sugarcane EST sequencing was done in
Brazil under the SUCEST initiative (Vettore et al. 2003).
SUCEST allows a global evaluation of sugarcane gene
expression, as it covers 26 cDNA libraries from roots,
plantlets, stems, leaves, flowers and seeds, as well as calli
subjected to abiotic stresses and plantlets infected with
endophytic nitrogen fixing bacteria. As a result, a total of
237,954 sugarcane ESTs were sequenced by the SUCEST
group and assembled into 42,982 Sugarcane Assembled
Sequences (SASs), which were estimated to represent over
30,000 unique genes—probably around 90% of sugarcane
genes (Vettore et al. 2003). Sugarcane EST projects others
than that of SUCEST focused on stem maturation and
sucrose accumulation.
Present knowledge about sugarcane gene regulation
lacks sufficient genomic resources to understand tran-
scriptomic variation among sugarcane genotypes or even
among different copies of the same gene in the same
individual. The greatest effort in sugarcane applied
genomics is based on characterization of the sugarcane
genes discovered in ESTs, especially from the expression
patterns analyzed by macro- and microarrays and quantita-
tive RT-PCR. However, these findings must be considered
preliminary as most expression analyses were restricted to
only one sugarcane cultivar for each treatment and it has
been shown that gene expression is not the same among
cultivars (Camargo et al. 2007, D.S. Domingues, unpub-
lished data) nor even among progeny from the same
segregating population (Casu et al. 2005; Papini-Terzi et
al. 2009). In silico EST analyses were also used for
selection of sugar transporters that are apparently modulat-
ed during stem maturation as validated by northern blot
hybridization (Casu et al. 2003, 2004). In a macroarray
analysis of randomly selected sugarcane cDNAs, it was
possible to identify candidate genes whose expression was
modulated by low temperature, methyl-jasmonate and ABA
treatment of the plants (Nogueira et al. 2003; Rosa et al.
2005; Schlögl et al. 2008). Similarly, Rocha et al. (2007)
used a signal transduction-oriented microarray analysis to
better understand phytohormones and environmental chal-
lenges in sugarcane and found 179 differentially regulated
genes. Gene regulation studies in sugarcane may also be
useful to characterize promoter elements. For example, a
cDNA microarray was used to profile transcript variation
and abundance in six plant organs of sugarcane plants
cultivated in the field. From 1,280 distinct putative genes
analyzed, 217 (17%) presented differential expression in
two biological samples of at least one of the tissues tested.
The expression data presented could aid in future tissue-
specific promoter characterization (Papini-Terzi et al.
2005).
76 Tropical Plant Biol. (2010) 3:75–87

Gene characterization based on cDNA does not give
information about regulatory sequences and it is known that
major traits are manifested by non-transcribed sequences
(Messing 2009). Furthermore, isolated sugarcane promoters
have not generally retained the expected patterns of reporter
transgene expression, suggesting that the sugarcane gene
silencing machinery is highly efficient (Mudge et al. 2009).
The highest levels of sugarcane transgene expression are
usually achieved by using heterologous promoters (Wu and
Birch 2007), indicating that a major effort is still necessary
to uncover sugarcane promoters and to understand the
biology of genetic manipulation of this crop.
One way to speed the discovery of promoter sequences
would be to sequence sugarcane euchromatin. However, to
date, only two sugarcane BACs have been deposited in
public databases (Jannoo et al. 2007). R570 is the only
sugarcane cultivar that has a publicly available BAC
library. The sugarcane genomics community needs to
expand resources for sugarcane genome analyses by the
development of additional BAC libraries from other
cultivars and parental species (S. officinarum and S.
spontaneum) as well as producing a detailed physical map
from one reference cultivar, probably R570. Detailed
analysis of the sugarcane BACs will provide crucial
information for understanding sugarcane genome structure.
Comparative grass genomics will be an important tool to
evaluate the impact of intergenic spaces in the sugarcane
genome. The sequencing of the sorghum genome (Paterson
et al. 2009) disclosed that the proportion of repetitive
sequences in that diploid genome is intermediate between
the rice compact genome and the maize highly repetitive
genome. Sugarcane EST data and macroarray analyses
showed that transposable elements (TEs), the most abun-
dant component of the repetitive sequences, are transcrip-
tionally active, especially in callus tissue (Rossi et al. 2001;
Araújo et al. 2005). Mutator-like elements, the most
prevalent transposon class in the SUCEST database is
highly distributed throughout the sugarcane genome, with
two subgroups of bonna fide transposons and two sub-
groups of “domesticated transposases” (Saccaro et al.
2007). Although there are studies on characterization of
Ac-like elements and LTR retrotransposons in sugarcane
(M.A. Van Sluys, personal communication), the contribu-
tion of repetitive sequences to trait expression, especially
transposable elements, remains to be investigated in
sugarcane. Furthermore, since sugarcane cultivars have a
recent hybrid and polyploid genome, information about
methylation and epigenetic regulation of sugarcane gene
expression will undoubtedly reveal uncharacterized mech-
anisms involved in gene transcription and silencing in this
highly polyploid crop.
Gene discovery in sugarcane will benefit from genome
sequencing efforts over the next few years using high
throughput next generation sequencing. The attribution of
function to genes will increase with the optimization of
methods to generate transgenic sugarcane lines. Expression
of sugarcane genes in different species may also be useful.
Our understanding of the sugarcane transcription apparatus
will also benefit from system biology approaches that will
identify key elements in gene networks. The problem of the
polyploidy and aneuploidy of sugarcane will be slowly
solved using these techniques, which will lead to a greater
understanding of how plants with complex genome work,
and the generation of new molecular markers and candidate
genes to improve sugarcane productivity.
Transgenics and Controlled Transgene Expression
Classical plant breeding has been the main approach
towards sugarcane improvement. However, the complexity
of the sugarcane genome, its narrow genetic base (Roach
1989; Lima et al. 2002), and the time required for a new
variety to reach commercialization (12–15 years) are
constraints of this method. Although it is not clear whether
sugarcane improvement through classical breeding is reach-
ing a yield limit, there are specific desired traits, such as
enzymes that would allow the use of sugarcane as a
biofactory, that cannot be introduced into sugarcane by
traditional breeding. Thus, many advances on sugarcane
improvement will depend on sugarcane transformation.
Nevertheless, stable transformation is far from being
routine in this crop. Current constraints of high-thoughtput
sugarcane transformation include the low transformation
efficiency, transgene inactivation, somaclonal variation, and
the long time required for regeneration and its commercial
release. Transformation and tissue culture-induced
somaclonal variation remains a significant bottleneck in
exploiting gene technology for sugarcane improvement
(Arencibia et al. 1999), and considerable refinements of
current transformation systems are required to ensure clonal
fidelity of transgenic cultivars. In addition, there is also the
matter of a so-called “yield lag” which relates to the time
required from the generation of a transgenic variety to its
commercial release. This may be so long that sugarcane
varieties generated through conventional breeding may
have made sufficient yield gains to outcompete the
transgenic ones based on an earlier generation variety (J.
C. Bespalhok, personal communication). The yield lag
problem is amplified by the fact that different regions of the
world use different commercial varieties, each of which
would need to be transformed and each may have different
transformation and regeneration capacity.
Success in the transformation of sugarcane (Bower and
Birch 1992) followed the development of a microprojectile
system. Initially, efforts were directed towards engineering
Tropical Plant Biol. (2010) 3:75–87 77

economically important traits into commercially grown
sugarcane varieties. It has been estimated that 44 field
trials were done with sugarcane transgenic plants contain-
ing traits that include herbicide resistance, disease and
insect resistance, drought tolerance, increased sucrose
accumulation, and delayed flowering time (Table 1). There
are a few reports about the development of transgenic
sugarcane with improved resistance to a number of
microbial pathogens (Joyce et al. 1998a, b; Ingelbrecht et
al. 1999; Zhang et al. 1999; Rangel et al. 2003; Gilbert et
al. 2005; McQualter et al. 2004a), with resistance to pests
such as sugarcane stem borer (Arencibia et al. 1999; Braga
et al. 2003), and herbicide resistance (Gallo-Meagher and
Irvine 1996; Enriquez-Obregon et al. 1998; Leibbrandt
Table 1 Examples of markers and traits engineered into sugarcane (updated from Lakshmanan et al. 2005)
Traits Gene Transformation method Reference
Reporter and selection systems
Neomycin phosphotransferase npt-II Microprojectile Bower and Birch 1992
β-Glucuronidase uid-A Microprojectile Bower and Birch 1992
Electroporation Arencibia et al. 1995
Agrobacterium Arencibia et al. 1998
Hygromycin phosphotransferase hpt Agrobacterium Arencibia et al. 1998
Green fluorescent protein gfp Agrobacterium Elliott et al. 1998
Phosphinothricin acetyl transferase bar Agrobacterium Elliott et al. 1998
Phosphinothricin acetyl transferase bar Agrobacterium Manickavasagam et al. 2004
Herbicide resistance
Bialaphos bar Microprojectile Gallo-Meagher and Irvine 1996
Phosphinothricine bar Agrobacterium Enriquez-Obregon et al. 1998
Phosphinothricine bar Microprojectile Falco et al. 2000
Glufosinate ammonium pat Microprojectile Leibbrandt and Snyman 2003
Disease resistance
SCMV SCMV-CP Microprojectile Joyce et al. 1998a, b
Sugarcane leaf scald albD Microprojectile Zhang et al. 1999
SrMV SrMV-CP Microprojectile Ingelbrecht et al. 1999
Puccinia melanocephala Glucanase, chitanase and ap24 Agrobacterium Enriquez et al. 2000
Sugarcane yellow leaf virus SCYLV-CP Microprojectile Rangel et al. 2003
Sugarcane yellow leaf virus SCYLV-CP Microprojectile Gilbert et al. 2009
Fiji leaf gall FDVS9 ORF 1 Microprojectile McQualter et al. 2004a
Pest resistance
Sugarcane stem borer cry1A Electroporation Arencibia et al. 1999
Sugarcane stem borer cry1Ab Microprojectile Braga et al. 2003
Sugarcane canegrub resistance gna or pinII Microprojectile Nutt et al. 1999
Mexican rice borer gna Microprojectile Legaspi and Mirkov 2000
Sugarcane stem borer and Mexican rice borer gna Microprojectile Setamou et al. 2002
Metabolic engineering/alternative products
Sucrose accumulation Antisense soluble acid invertase Microprojectile Ma et al. 2000
Soluble acid invertase Microprojectile Botha et al. 2001
Fructo oligosaccharide lsdA Agrobacterium Enriquez et al. 2000
Polyphenol oxidase ppo Microprojectile Vickers et al. 2005
Polyhydroxybytyrate phaA, phaB and phaC Microprojectile Brumbley et al. 2003
ρ-Hydroxybenzoic acid hchl and cpl Microprojectile McQualter et al. 2004b
Tripsin inhibitors Kunitz and Bower-Birch Microprojectile Falco and Silva-Filho 2003
Mannose manA Microprojectile Jain et al. 2007
Isomaltulose SI Microprojectile Wu and Birch 2007
Proline production P5CS Microprojectile Molinari et al. 2007
78 Tropical Plant Biol. (2010) 3:75–87

and Snyman 2003). Efforts are also under way to engineer
sugarcane for increased sugar accumulation (Ma et al.
2000; Wu and Birch 2007; G. Souza, personnal commu-
nication), low color raw sugar (Roberts et al. 1996;
Vickers et al. 2005) and high-value products (Groenewald
et al. 1995; Brumbley et al. 2003; McQualter et al. 2004b;
Petrasovits et al. 2007). Although thousands of inde-
pendent transgenic sugarcane lines have been tested in
field trials, there is not yet a commercially released
transgenic sugarcane cultivar (J.C. Bespalhok, personal
communication).
One noteworthy example of sugarcane manipulation was
the introduction of a sucrose isomerase gene tailored for
vacuolar compartmentalization in sugarcane plants (Wu and
Birch 2007). Transgenic plants showed increased total
sugar concentration due to normal levels of sucrose plus
the accumulation of isomaltulose, a high-value sugar. These
transgenic lines also showed increased photosynthesis,
sucrose transport and sink strength (Wu and Birch 2007).
Another example is the increase of drought tolerance in
transgenic sugarcane that synthesized proline in response to
stress. Transformed plants were protected against the
oxidative stress caused by water deficit. The higher
tolerance of those transgenic plants was assessed by higher
biomass yields after 12 days of withholding water (Molinari
et al. 2007).
A key limitation to the generation of new transgenic
lines has been the silencing of inserted transgenes. Mudge
et al. (2009) isolated eight distinct promoters associated to a
MYB transcription factor gene. At least three of these
promoters were associated with alleles that are known to be
expressed. When constructs of a reporter gene driven by
each of these promoters were inserted into sugarcane,
expression of the reporter was successfully detected soon
after transformation, but not later in the mature stem of
regenerated plants. In addition, the silencing pattern was
unpredictable, an undesirable trait in a commercial line as
plants with adequate and stable transgene expression under
field conditions are needed to bring to sugarcane market the
practical benefits of transgenic technology.
More than 10 years ago, Finnegan and McElroy (1994)
reviewed possible mechanisms of transgene inactivation.
Firstly, integrated transgenic DNA may be recognized by its
disruption of normal chromatin structure or by the different
sequence characteristics from that of the surrounding
integration site. The integration of duplicated sequences
may result in chromatin restructuring, DNA methylation
and the inhibition of mRNA processing, transport, export or
translation. Post transcriptional silencing may be directed
by RNA-directed de novo methylation of transgene
sequences (Finnegan and McElroy 1994). There is also
evidence that silencing may be related to the transgene
sequence so that there is the possibility of developing
transgene design rules that may minimize transgene
silencing.
Although microparticle bombardment has been the main
method of sugarcane transformation (Birch 1997; Moore
1999), other methods for transgene incorporation into
sugarcane are needed. For example, genetic transformation
mediated by Agrobacterium tumefaciens should be studied
and applied to sugarcane more frequently (Arencibia et al.
1998; Elliott et al. 1998; Enriquez-Obregon et al. 1998;
Elliott et al. 1999; Manickavasagam et al. 2004). A.
tumefaciens-mediated transformation has the potential to
become more efficient with appropriate manipulation and in
vitro culture conditions, selection of the best age of the
calli, type and stage of embryogenic culture, and improve-
ment in the virulence of A. tumefaciens. Compared to other
methods, transformation mediated by A. tumefaciens is a
simple and low cost method. Furthermore, it can transfer
relatively long segments of DNA with little rearrangement
and at a relatively low number of integrated copies. Another
important transformation technique is the transformation of
chloroplasts. Chloroplast genetic engineering offers a num-
ber of unique advantages compared to conventional trans-
genic technologies, including high protein expression levels
(De Cosa et al. 2001), integration into the plastome via
homologous recombination without position effects or gene
silencing (Daniell et al. 2001), and the expression of several
transgenes in a single transcriptional unit due to the
chloroplast’s prokaryotic origin (Bock 2001).
Over the next few years, the first generation of
commercial sugarcane transgenics, with herbicide and
insect resistance, will be available as the result of improved
transformation efficiency, the design of new transformation
vectors, and new transgene design rules to avoid silencing.
The development of strategies for incorporating polygenic
traits, hyperexpression of transgenes, containment of trans-
genes within the transgenic plants (Daniell 1999; Daniell et
al. 2001; Maliga 2004), together with the possibility of
engineering native genes without significant genetic rear-
rangements (Beetham et al. 1999) are valuable innovations
that could be utilized for improvement of sugarcane in the
near future.
For successful release of transgenic sugarcane, various
scientific, legislative, and public perception issues must
also be addressed. Transformation systems that do not
incorporate any non-transgene DNA into the plant, utilize
non-antibiotic selection and plant gene-based selection
strategies would be a good start towards overcoming
regulatory and public perception issues. In addition, the
ability to control transgene expression through induction,
developmental control, or tissue specificity will provide a
platform for the production of a range of new compounds in
sugarcane at commercially useful levels (Lakshmanan et al.
2005).
Tropical Plant Biol. (2010) 3:75–87 79

Sugarcane Physiology
To optimize sugarcane improvement, it is necessary to
know the impact a selected trait will have on the general
physiology of the plant. However, this is not yet possible as
there are too many gaps in our knowledge of the unique
development and physiology of sugarcane. Such gaps
impair our ability to enhance desired agronomical traits.
For example, selection for sugarcane varieties with
increased photosynthetic capacity may be useless if sugar
accumulation is constrained by temperature, water deficit,
or nutrient availability (Inman-Bamber et al. 2002). It may
prove difficult to consistently increase sucrose levels in the
culm without first knowing the factors that affect sugarcane
yield and carbon partitioning.
A key aspect to increase sugarcane yield is the regulation
of its photosynthetic apparatus. Sugarcane C4 metabolism
concentrates CO2 in photosynthetically active tissues, a
strategy that has an energy cost that may be offset by the
reduction in photorespiration rates. There are at least three
distinct forms of C4 metabolism that can be identified by
the decarboxylation enzymes they use: NADP+−malic
enzyme (NADP-ME), NAD+−malic enzyme (NAD-ME)
and phosphoenolpyruvate carboxykinase (PCK). There is
evidence that sugarcane has both NADP-ME and PCK
(Calsa and Figueira 2007), which suggests the two types of
C4 metabolism might complement each other (Christin et
al. 2007). The physiological implications of the presence of
both pathways and how they could be explored to increase
sugarcane yield is still unknown.
It is also important to detail how carbon demands in the
culm affect photosynthetic rates. Photosynthetic rates
decrease with plant age, which could be a result of
physiological limitations to sucrose accumulation in the
culms (McCormick et al. 2006). This regulation is mediated
by hexose, but little is known about the downstream
pathways of this signal (McCormick et al. 2008a).
The relationship between sink and source is a key step in
the identification of targets that can be changed in order to
improve sucrose accumulation. Sucrose production and
storage is associated with the demand imposed by sink
organs (McCormick et al. 2008b). For example, when the
leaf growth is reduced, sucrose content tends to increase in
culm (Inman-Bamber and Smith 2005). Furthermore,
transgenic varieties that express an enzyme that converts
sucrose into isomaltulose showed increased photosynthesis,
probably due to introduction of this new carbon sink (Wu
and Birch 2007). Finally, the reduction of leaf elongation
induced by water deficit redirects the carbon partition and
provides an increase in sucrose content (Inman-Bamber
2004). Experiments showed that water stress reduced whole
plant photosynthesis by 18% and plant extension rate by
41% resulting in a 19% reduction in total biomass.
However, water stress increased the sucrose mass gain by
27% and increased sucrose content of the dry mass by 37%,
confirming that water deficit reduced the demand for photo-
assimilate for producing fiber and tops so that excess
assimilate was allowed to accumulate in the form of sucrose
(Inman-Bamber et al. 2008).
The impact of water deficit on physiological or
developmental processes and on gene expression are also
under study on six different sugarcane varieties in four
regions of Brazil. As expected, preliminary physiological
measures showed that different cultivars utilize different
mechanisms to survive water stress. For example, one
cultivar utilized leaf rolling to reduce water loss whereas a
different variety increased root to shoot growth to reduce
water loss and to increase water uptake (L. Endres,
personal communication).
Over the next decades, climate change and increased
CO2 levels are projected to impact the productivity of all
crops. CO2 levels are predicted to increase from about
379 ppm in 2005 to 730–1,020 ppm by the end of the
century (IPCC 2007). To design sugarcane crops for
maximum productivity in such a changed environment, it
is necessary to study how the increase of CO2 levels affects
sugarcane physiology. Increases in the level of CO2 will
reduce the rate of photorespiration in all plants, but
considerably more in C3 plants than C4 plants. Neverthe-
less, C4 plants do increase their biomass when CO2 levels
are increased from 370 ppm to 720 ppm. This increase in
biomass of C4 plants is associated more with the increase in
water use efficiency (WUE) than in the reduction of
photorespiration (Vu et al. 2006; de Souza et al. 2008).
An efficient use of water leads to a lower rate of water
depletion in the soil, which increases resistance to drought
(Vu and Allen 2009). Higher CO2 levels change both the
metabolites and transcript levels of a number of sugarcane
genes (Vu et al. 2006; de Souza et al. 2008), but how each
change impacts sugarcane physiology remains unknown.
Yield increases of 60% were observed on sugarcane grown
in open top chambers under 720 ppm CO2, which indicates
that yield potential may increase under those conditions (de
Souza et al. 2008).
Many other physiological traits need to be detailed
before a strategy can be designed to improve them. For
example, numerous details of sugarcane C4 photosynthesis
and other metabolic pathways are needed to detect which
steps constrain sugarcane yield. Understanding the mecha-
nisms regulating the transition from vegetative to repro-
ductive growth would allow the control of flowering for
breeding and reduce the loss of fixed carbon for reproduc-
tion. In addition, little is known about what limits the
capacity of sugarcane to store high concentration of sucrose
in the parenchyma tissue of the stalk (McCormick et al.
2008a). Sucrose content variation depends on the morphol-
80 Tropical Plant Biol. (2010) 3:75–87

ogy of the plant, such as size of the canopy and responses
to ripening stimuli such as mild water stress and how these
traits influence the supply and demand for photo-assimilate
(Inman-Bamber et al. 2009). The photomorphogenic con-
trol of sugarcane development can be modified by
treatment with gibberellic acid (GA3). This phytohormone
induces a significant increase in stem cell elongation which
increases the capacity for sucrose storage in sugarcane
seedlings (A. Brandão and M. Buckeridge, unpublised).
In the next few years, many physiological puzzles have
to be solved. Initially, results obtained in more controlled
greenhouse conditions will need to be confirmed under
varying field conditions. Sugarcane transgenics, either
overexpressing or silencing specific candidate genes will
allow the testing of many hypotheses while physiology
experiments will help identify new candidate genes.
Systems biology coupled with yet to be developed models
will integrate physiological data with massive amounts of
proteomic, metabolomic and transcriptomic data to allow a
more targeted approach towards understanding the limits of
sugarcane productivity.
Breeding and Statistical Genetics
If the long-term goal for the use of molecular biology tools
for sugarcane improvement is the generation of transgenic
varieties, the use of molecular markers for enhancing the
breeding and selection of improved varieties can be
considered its short-term goal. The sugarcane maps cover
only about one third of the sugarcane genome (Grivet and
Arruda 2002), even though most sugarcane genetic maps
have around 1,000 markers (as reviewed by Casu et al.
2005), which is comparable to the genetic maps in other
plants. In addition, current mapping methods are restricted
to the use primarily of single-dose markers. Consequently,
many if not most of the polymorphic loci obtained in
sugarcane mapping populations are not useful (Garcia et al.
2006).
Markers are already being used for the selection of
parental plants for crosses (McIntyre and Jackson 2001;
Wenzel 2006; Snyman et al. 2008), assessment of sugar-
cane resistance to diseases like brown rust (Daugrois et al.
1996; Asnaghi et al. 2001; Hoarau et al. 2001; Rossi et al.
2003) and yellow spot (Al-Janabi et al. 2007), evaluation of
genetic diversity (Selvi et al. 2003; Lima et al. 2002),
construction of genetic maps (Aitken et al. 2005, 2007;
Raboin et al. 2006; Garcia et al. 2006; Oliveira et al. 2007)
and mapping of Quantitative Trait Loci (QTL) (McIntyre et
al. 2006; Al-Janabi et al. 2007; Piperidis et al. 2008; Aitken
et al. 2008).
In some diploid crop species like maize, soybean,
barley and rice, molecular markers already play a critical
role in breeding through Marker Assisted Selection
(MAS) of yield components, and disease and pest
resistance (for a detailed review, see Francia et al.
2005). Several statistical genetic models have been proven
and are helping breeders to better understand the inheri-
tance of quantitative traits in these species. Efficient
identification and use of molecular markers through the
use of appropriate statistical models are matters of great
importance in sugarcane.
There is a recent trend to use single nucleotide
polymorphism (SNP) markers to replace other marker types
in many species, as they are frequently common in the
genome—both within and between genes (Bundock et al.
2009). SNPs are responsible for most of the genetic
variation within species and explain the occurrence of
many important traits in plants such as rice (Umemoto et al.
2004; Bryan et al. 2000). The high frequency of SNPs in
many plant species such as maize (Tenaillon et al. 2001),
barley (Kanazin et al. 2002) and rice (Yu et al. 2002) makes
it the new marker of choice for disease diagnostics, marker
assisted selection, high resolution genetic mapping assess-
ment of genetic purity (Batley et al 2003), and association
mapping. Particular effort has been devoted to the devel-
opment of SNPs as high-throughput markers.
One of the strategies for SNP discovery is the use of
public EST databases. The problem is that sometimes the
polymorphism present in the available sequences is not
present in the current population of interest. As an
alternative, the re-sequencing of the identified SNP regions
in the population of interest can be used. Conventional
re-sequencing is complicated in sugarcane because it is
highly heterozygous and polyploid. To deal with these
issues, it may be necessary to sequence a high number of
clones to represent all the variation, even thought this
approach is expensive and time consuming (Bundock
et al. 2009).
Recent advances in sequencing technology have enabled
the production of great amounts of data and reduction of the
cost per base (Imelfort et al. 2009). Bundock et al (2009)
showed that the use of next generation sequencing (NGS)
such as 454 Life Sciences Genome Sequencer™ FLX, is
more cost effective than earlier sequencing for SNP
identification and can significantly increase the identifica-
tion of SNPs in sugarcane. Another problem with polyploid
sugarcane is the validation, selection for mapping, and
genotyping of the SNPs, which are successfully being done
using the Sequenom Mass ARRAY® system (Bundock et
al. 2009). Sequenom technology also enables the estimation
of the number of copies of each SNP allele, which is ideal
for polyploid species. In addition to the importance of NGS
for re-sequencing, these technologies will also have a great
impact in sequencing of cDNA, gene rich regions, and the
whole-genome of sugarcane, providing more information
Tropical Plant Biol. (2010) 3:75–87 81

for the development of a higher number of molecular
markers, such as new SSRs, EST-SSRs and SNPs for
further application in breeding programs. In this context,
data generation is well addressed, since tremendous
amounts of data are being generated by high-throughput
techniques, primarily based on single nucleotide polymor-
phism discovery (Syvänem 2001).
Despite the evolution of more precise and faster
molecular techniques, data analysis has lagged behind and
still needs a lot more effort. At the present time, the
majority of statistical techniques used for genetic and QTL
mapping in the complex genome of sugarcane are adapta-
tions of ideas used in diploid organisms. Due to this
limitation, a large amount of data that does not fit these
models cannot be included in the analysis (e.g. markers
segregating in fashions other than 1:1 and 3:1). However,
the importance of key QTL that might not fit the diploid
model cannot be ruled out.
The presence of markers with higher allele doses, as well
as combinations of markers with different doses (da Silva
and Sorrells 1996; Ripol et al. 1999) makes it imperative
that additional segregation patterns be considered. Given
the current data and tools available, it is imperative to
conduct thorough studies before MAS can become routine.
Another issue that deserves attention is sample size. To
construct reliable linkage maps and achieve adequate
statistical power for QTL detection, larger samples have
to be used, which can raise several operational and
computational issues. In addition, as larger samples are
used, technical and financial limitations must be considered
when phenotyping large numbers of individuals.
More efficient and powerful statistical tools must be
made available to researchers to analyze the rapidly
accumulating sugarcane genomic data. Importantly, these
new methodologies must be created with a polyploid
mindset, as opposed to simple adaptations from models
for diploid systems. Association mapping studies based on
haplotype data have proven very useful for the identifica-
tion of markers co-segregating with quantitative characters
and can speed up the localization of important genes
(Lakshmanan et al. 2005; McIntyre et al. 2005; Wei et al.
2006; Raboin et al. 2008). QTL mapping studies will also
play a major role in better understanding the genetic
architecture of quantitative traits, providing basic informa-
tion to be used by plant breeders in designing breeding
programs (Zeng et al. 1999).
In addition to QTL mapping, expression quantitative
trait loci (eQTL) mapping has the potential to be useful to
integrate information from genomics, transcriptomics and
phenotype, providing links between gene expression and
phenotype determination (Jansen and Nap 2001; Schadt et
al. 2003). However, eQTL will only be useful once major
challenges are overcome, such as the development of
models for polyploid systems, the development of a robust
RNA profiling platform and the characterization of genetic
map populations.
Finally, it is known that sugarcane has a relatively
narrow genetic basis, as a consequence of using only a few
selected clones for base population generation (Roach
1989; Lima et al. 2002). Also, only a few generations
separate modern cultivars and ancestors (Raboin et al.
2008), providing high linkage disequilibrium. Conventional
sugarcane breeding programs have relied on high levels of
heterozygosity of commercial clones and the instability of
the polyploid genome as a source of genetic variability,
since a small number of individuals can store considerable
allelic variability, compared to diploid species. However,
sucrose and fiber content have not sustained substantial
improvements with current breeding efforts, because of the
low genetic variability effectively used (Jackson 2005).
Most yield gains are due to exploiting genotype by
environment interaction, which is not well understood for
sugarcane. With the view to assure long term improvements
arising from genetic breeding, new (exotic) germplasm
should be incorporated into current programs, e.g., through
pre-breeding programs to accelerate the mobilization of
non-adapted material (Ramdoyal and Badaloo 2002;
Hemaprabha et al. 2005)
In the next years, high-throughput sequencing will
exponentially increase the amount of molecular markers
available for molecular breeding. Initial efforts in se-
quencing the sugarcane genome will be used as a scaffold
for resequencing projects that will make SNPs identifica-
tion cheaper and faster. At the same time, new statistical
models, designed specifically for polyploid genomes, will
allow the sequencing data to be fully used. The introduc-
tion of molecular biology tools will help the classical
breeding programs to identify traits of interest faster and
with greater precision. This will probably increase the
expected limit of sugarcane improvement to its theoretical
potential using classical breeding. The great challenge
over the next several years will be to convey the fundamental
information generated in academia to applications by the
breeders.
Final Remarks
The BIOEN Workshop on Sugarcane Improvement gath-
ered over 250 researchers to discuss the challenges for
sugarcane improvement and the role of biotechnology in
solving these challenges (Fig. 1). Among the main points
discussed were how to identify the current gaps in
sugarcane knowledge and how to apply emerging new
knowledge to the process of designing new sugarcane
varieties. Recognition was given to new high-throughput
82 Tropical Plant Biol. (2010) 3:75–87

technologies that have the potential to quickly fill these
gaps once they have been identified.
Sugarcane improvement can be achieved by the integra-
tion of improved crop management practices, traditional
breeding, and the generation of transgenic improved lines.
Gene discovery and sugarcane physiology will provide the
knowledge required to develop a new sugarcane crop to be
used as source for energy or as a biofactory (energy cane).
Information about sugarcane is expected to increase
exponentially over the next few years in response to
financial incentives directed towards sugarcane improve-
ment. In particular, the emergence of enormous amounts of
sequencing data will require large bioinformatics teams and
good data management platforms. These requirements will
be the same for new systems biology approaches. Data
management will be especially crucial when integrating
data from different methodologies and from different
groups. Furthermore, shared experiences, including the
negative ones that are rarely published, will help over-
lapping efforts.
Sugarcane is a complex model organism. Its genome is
highly poliploid and aneuploid, it has a long generation
time and transformation is difficult. The advantage of
dealing with such complex organism is that the research
community realizes that any real advance in sugarcane
knowledge requires collaboration with other groups and
organization at an international level. Although sugarcane
has a high economic value, each country has to develop
different commercial varieties that are adapted to specific
regional problems which reduces competition among
research groups of different countries. Examples of such
common efforts are the International Consortium for
Sugarcane Biotechnology (ICSB), the sugarcane nomencla-
ture committee, which is unifying the nomenclature in
genetic databases and the Sugarcane Genome Sequencing
Initiative (SUGESI, http://sugarcanegenome.org). The
BIOEN Workshop on Sugarcane Improvement was just
another step towards a fully integrated sugarcane research
community.
Invited Speakers and Debate Leaders
Paul Moore (Hawaii Agriculture Research Center Cellular
and Molecular Biology Research Unit, Aiea, USA);
Rosanne E. Casu and Graham D. Bonnett (CSIRO Plant
Industry, Queensland Bioscience Precinct, St Lucia, Aus-
tralia; Cooperative Research Centre for Sugar Industry
Innovation through Biotechnology, University of Queens-
land, St. Lucia, Australia); Derek A Watt (South African
Sugarcane Research Institute, Crop Biology Resource
Centre, Mt Edgecombe, South Africa; School of Biological
and Conservation Sciences, University of KwaZulu-Natal,
Durban, South Africa); Manuel B Sainz (Syngenta Centre
for Sugarcane Biofuels Development, Queensland Univer-
sity of Technology, Brisbane, Australia); Paulo Arruda
(Centro de Biologia Molecular e Engenharia Genética,
Universidade Estadual de Campinas, Campinas, Brazil);
Robert G Birch (School of Integrative Biology, The
University of Queensland, Brisbane, Australia); João Carlos
Bespalhok-Filho (Departamento de Fitotecnia e Fitossani-
tarismo, Universidade Federal do Paraná, Curitiba, Brazil);
Hugo Mollinari (EMBRAPA Recursos Genéticos e Bio-
tecnologia, Brasília, Brazil); Eugenio Ulian (Monsanto, São
Fig. 1 Roadmap for sugarcane improvement. The interplay between
research on Gene Discovery and Genomics and on Sugarcane
Physiology, will generate basic knowledge about potential targets for
improvement (1). Knowledge on Sugarcane Physiology may be
directly applied to improve crop management (2). In parallel, Gene
Discovery and Genomics will identify new molecular markers to be
used for Breeding and Statistical Genetics (3). These markers will be
applied to new statistical models in order to breed improved sugarcane
(4). Gene Discovery and Genomics will also identify genes and
regulatory sequences to generate new transgenic plants (5) to be used
either in research, to gain new insights into Sugarcane Physiology (6)
or in the design of commercial transgenic varieties (7). The interplay
of improved sugarcane with improved crop management will
approximate sugarcane yield to its theoretical potential (8)
Tropical Plant Biol. (2010) 3:75–87 83

Paulo, Brazil); Rowan F Sage (Department of Ecology and
Evolutionary Biology, University of Toronto, Toronto,
Canada); Lauricio Endres (Centro de Ciências Agrárias,
Universidade Federal de Alagoas, Rio Largo, Brazil); Katia
C Scortecci (Centro de Biociências, Universidade Federal
do Rio Grande do Norte, Natal, Brazil); Marcos AS Vieira
(Centro de Ciências Agrárias, Universidade Federal de São
Carlos, Araras, Brazil); Robert J Henry (Centre for Plant
Conservation Genetics, Southern Cross University, Lis-
more, Australia); Jorge AG da Silva (Texas Agricultural
Experiment Station, Texas A and M University, Weslaco,
USA);Walter Maccheroni Junior (Canaviallis, Campinas,
Brazil); Marcos GA Landell (Centro Avançado de Pesquisa
Tecnológica do Agronegócio de Cana-de-açúcar, IAC,
Ribeirão Preto, Brazil); William L Burniquist (Centro de
Tecnologia Canavieira, Piracicaba, Brasil); Hermann P
Hoffmann (Centro de Ciências Agrárias, Universidade
Federal de São Carlos, Araras, Brazil).
The workshop presentations can be found at: http://
bioenfapesp.org/index.php?option=com_jdownloads&
Itemid=108&task=viewcategory&catid=8&lang=en
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