Environmental Engineering Reference
In-Depth Information
its tremendous economic importance for food and fuel, progress is being made to develop these
technologies for sugarcane. Molecular markers have been developed for sugarcane, and several
studies have been conducted to assess the genetic diversity of the crop. Jannoo et al. (1999) sur-
veyed a large collection of 109 sugarcane cultivars, mostly from Barbados and Mauritius, and 53
S. officinarum
germplasm clones using low-copy restriction fragment length polymorphism (RFLP)
markers. Aitken et al. (2006) surveyed 270
S. officinarum
clones and 151 Australian cultivars and
breeding lines using amplified fragment length polymorphism (AFLP) markers. The results of both
of these studies were surprisingly similar. All clones tended to produce multiple markers, dem-
onstrating the heterozygous nature of the complex polyploids. Although there was more diversity
in the sugarcane cultivars because of hybridization, the most diversity within
S. officinarum
was
found among accessions from New Guinea by both of the studies, supporting the hypothesis that the
island of New Guinea is the center of origin for
S. officinarum
. Jannoo et al. (1999) identified a set
of
S. officinarum
clones from New Caledonia as a distinct group, whereas Aitken et al. (2006) also
identified a distinct group of
S. officinarum
clones from the South Pacific (Hawaii and Fiji). Both
studies concluded that hybridization must have occurred after
S. officinarum
was disseminated
away from its center of origin. Jannoo et al. (1999) noted that most of these clones had more than 80
chromosomes. A surprising result of both studies was that most of the diversity found within
S. offi-
cinarum
(85%, Jannoo et al. 1999; 90%, Aitken et al. 2006) was retained in the sugarcane cultivars,
although relatively few clones formed the basis for modern sugarcane breeding.
The greatest challenge to molecular mapping in sugarcane is the high ploidy of its genome.
Because of a high degree of homology between subgenomes, a given marker may represent more
than one locus, which complicates mapping. Marker dosage, the number of loci associated with
a particular marker, must be determined to map it. Chi-square tests for Mendelian segregation
ratios are generally accepted as a means to determine marker dosage in polyploids. However, this
approach has limitations because of segregation distortion (departures from expected ratios) and
overdispersion (greater than expected variance in the distribution of marker data), often resulting in
markers that cannot be assigned a dosage. To address these limitations, Baker et al. (2010) advocate
a Bayesian mixture model for assigning marker dosage in the complex polyploids like sugarcane.
Simplex markers, those representing only one locus, are the most informative and are used to con-
struct the framework maps. The positions of duplex markers can be estimated to increase marker
density and consolidate broken linkage groups (Aitken et al. 2007). Ambiguous markers, such as
AFLP, can be used for genetic mapping in sugarcane, but a higher number of simplex markers can
be obtained using functional genomics information such as expressed sequence tag (EST) data. A
large database of sugarcane EST data, named SUCEST, has been developed, which contains over
237,000 ESTs, representing about 43,000 putative transcripts (Vettore et al. 2003). Using RFLP and
simple sequence repeat (SSR) markers derived from sequence information in the SUCEST data-
base, one of the most complete genetic maps for sugarcane was reported by Oliveira et al. (2007).
This map spanned over 6,000 centi-Morgans (cM) and contained 664 markers in 192 cosegregation
groups, which is more than the expected number of chromosomes, indicating that even this map is
not sufficiently saturated.
Despite the low resolution of sugarcane genetic maps, quantitative trait loci (QTL) have been
identified in this crop, which could be useful in marker-assisted selection (MAS). Pinto et al. (2010)
used single marker analysis to identify single-dose markers associated with important traits includ-
ing fiber content, cane yield, Pol (polarization value; a measure of sucrose content), and total sugar
yield. An advantage of single marker analysis is that a linkage map is not required, and associations
between unlinked markers can be detected. However, the probability of identifying false-positive
associations is increased compared with interval mapping approaches that utilize a genetic map.
Alwala et al. (2009) developed genetic maps from an interspecific cross (
S. officinarum
“Louisiana
Striped” ×
S. spontaneum
“SES 147B”) using AFLP, sequence-related amplified polymorphism
(SRAP), and target region amplification polymorphism (TRAP) markers. SRAPs are semiambigu-
ous markers designed to amplify within genes, and TRAPs are targeted to specific genes; in this
