Agriculture Reference
In-Depth Information
3. Detecting QTLs for Resistance to Rice Stripe Necrosis Virus (RSNV)
and Yield Components.
Using a population of interspeci
c lines carry-
ing introgressions from
Oryza glaberrima
(acc. MG12) in an
Oryza sativa
(acc. Caiapo) genetic background (see Section IV.C.2), we detected QTLs
for resistance to Rice stripe necrosis virus (RSNV) and for yield compo-
nents. Transgressive segregation was observed for several traits meas-
ured in the population. Fourteen QTLs for plant height, tiller number per
plant, panicle length, sterility percentage, 1000 grain weight, and grain
yield were located on chromosomes 1, 3, 4, 6, and 9. A highly signi
cant
major QTL controlling resistance to RSNV was located between SSR
markers RM202 and RM26406 (44.5
44.8 cM) on chromosome 11
(Gutierrez et al. 2010). It is interesting to note that RSNV, which is
present in LAC, actually originates from Africa (F. Morales, pers.
comm.), as does
O. glaberrima
. These results emphasize how the use
of exotic germplasm can bene
-
t rice breeding.
4. Genome-Wide Association Studies.
In plants, association mapping,
or linkage disequilibrium mapping, has several advantages over tradi-
tional linkage mapping: It offers higher resolution, samples a larger
population of alleles, and may be faster, as no mapping population
development is required. However, selection and inbreeding of lines to
construct the association mapping panel takes time. In GWAS, markers
across the genome are used to estimate kinship among individuals
and to directly estimate population structure and background marker
effects (Bernardo 2013). In GWAS performed on rice landraces, loci
may be mapped close to the gene resolution level, indicating that GWAS
can provide an effective approach for gene identi
cation (Huang et al.
2010; Famoso et al. 2011; Zhao et al. 2011). The power of GWAS is highly
dependent on marker density, distribution, and allele frequencies at
marker loci; and the appropriate number of markers for any GWAS is
de
ned by the level of linkage disequilibrium in the germplasm being
examined. Markers are also used to estimate and control population
substructure and avoid spurious marker-trait associations. Finally, the
size and composition of the germplasm panel, as well as the density of
markers used in GWAS, will signi
cantly affect the number and identity
of genotype
phenotype associations found in the study.
At CIAT, we have participated in various projects inwhich association
panels are evaluated for a number of traits of interest and are densely
genotyped. We are currently assessing a
tropical japonica
diversity
panel that was evaluated under drought conditions as part of a project
led by CIRAD on GWAS. We are also involved within GRiSP in the
evaluation of an
indica
diversity panel for mapping genes related to
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