Biology Reference
In-Depth Information
The currently available instruments for mea-
suring physicochemical properties in rice grain
can detect differences between
indica
and
japon-
ica
cultivars but do not differentiate well among
japonica
cultivars. On the other hand, rice breed-
ers and consumers can recognize the slight dif-
ferences in eating-quality traits among
japonica
cultivars. For example, two cultivars with the
same amylose content can be differentiated by
sensory test panels and consumers (Fitzgerald
et al. 2003). Improvements in measuring instru-
ments and techniques will be needed to provide
wider measurement ranges and less measure-
ment error. Metabolome analysis is a notable
example: advances in analytical technologies,
combined with dedicated data analysis tools,
are already beginning to show advantages in
the measurement of grain components in rice
(Fitzgerald et al. 2009; Kusano et al. 2007;
Oikawa et al. 2008; Mochida et al. 2009). Com-
prehensive detection of grain components by
metabolome analysis may detect grain-quality
differences not distinguishable by conventional
measurement methods. These novel applications
could enable QTL detection and gene cloning of
novel eating-quality components beyond amy-
lose content, amylopectin structure, and protein
content.
Until recently, the extremely low frequency
of DNA polymorphisms that could be detected
among
japonica
rice cultivars prevented the
molecular genetic analysis of many agronomic
traits. Recently the genome sequences of several
japonica
cultivars, including Nipponbare, Koshi-
hikari, Rikuu 132, Eiko, and Omachi, have made
it possible to detect polymorphisms within this
subspecies (IRGSP 2005; Yamamoto et al. 2010;
Nagasaki et al. 2010; Arai-Kichise et al. 2011).
SNPs have been detected among these cultivars.
The large number of SNPs distributed through-
out the
japonica
rice genome can overcome the
limitations once caused by the extremely low fre-
quency of DNA markers available. These SNPs
have enhanced the genetic dissection of pheno-
typic differences among
japonica
cultivars by
facilitating QTL analysis (Shibaya et al. 2011).
High-density SNP genotyping will be a powerful
tool for the detection and pyramiding of QTLs
for grain-quality traits in
japonica
cultivars.
QTL analysis of naturally occurring pheno-
typic variation has contributed greatly to our
understanding of the genetic control of grain
quality (Kobayashi et al. 2007; Tabata et al. 2007;
Kobayashi and Tomita 2008; Wada et al. 2008;
Takeuchi et al. 2008; Kwon et al. 2011). Genetic
populations used in these studies have played a
crucial role in this progress. Recently a novel
analytical method for QTL detection has been
proposed: the genome-wide association study
(GWAS) (Yu et al. 2006; Iwata et al. 2007) makes
it possible to detect QTLs directly in germplasm
accessions without the construction of genetic
populations and has already been applied suc-
cessfully in analyses of heading date and grain
yield, two agronomically important traits (Zhao
et al. 2011; Huang et al. 2012). Although the
sensitivity of GWAS is sometimes insufficient
to detect QTLs that are strongly correlated with
population structure (Iwata et al. 2007; Zhao
et al. 2011), its application may be suitable for
japonica
cultivars because of the relatively sim-
ple population structure within this subspecies.
GWAS could reduce many of the labor-intensive
and time-consuming aspects of QTL mapping
and facilitate genetic analysis of naturally occur-
ring variation in grain-quality traits.
Reverse-genetic approaches are facilitated
by the extensive genomic sequence informa-
tion available for rice, and such approaches are
already providing useful results. For example,
introduction of artificial microRNAs has been
successfully used to induce post-transcriptional
gene silencing in rice with unprecedented speci-
ficity, resulting in the modulation of agronom-
ically important traits such as plant height and
tillering (Warthmann et al. 2008). In particular,
extensive knowledge of regulatory and biochem-
ical pathways that are involved in trait expres-
sion has facilitated successful biofortification
of rice grain (Bekaert et al. 2008; Storozhenko
et al. 2007). TILLING (Targeting Induced Local
Lesions in Genomes) is a non-transgenic reverse
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