Genomics Applications to Salinity Tolerance Breeding in Rice - Translational Genomics for Crop Breeding: Abiotic Stress, Yield and Quality - page 40

polymorphism (SNP) identification have already
been outlined. Uptake of these technologies for
this purpose is by now pushing rice research
well beyond the SNP diversity knowledge gen-
erated by the OryzaSNP project (McNally et al.
2009). For example, the OryzaSNP project iden-
tified approximately 160,000 SNPs among the 20
varieties sequenced, and

Comparison of the O. sativa varieties shows that
these five indica and aus/ admixed varieties typi-
cally possess 3.1-3.5 million homozygous poly-
morphisms relative to the Nipponbare reference
genome (Table 3.2); other indica and aus vari-
eties might be similar.
This amount of polymorphism is obviously
far higher than is required for typical QTL map-
ping approaches. However, it overcomes a key
limitation of association mapping; due to the
high degree of recombination that has occurred
during the many generations that separate most
varieties, linkage between markers and traits
must be far tighter to produce significant asso-
ciation. Thus, association mapping requires a
far higher marker density than QTL mapping,
which has traditionally limited its usefulness in
plant breeding. The impending availability of
these high-density genotyping data, particularly
if available directly from the parental lines of
a QTL population, makes it a relatively simple
process to extract sufficient polymorphic sites
to allow the construction of a high-density map
using SNP detection platforms such as custom
oligonucleotide arrays from Affymetrix or Illu-
mina. Such SNP information has already been
used in association mapping studies in rice, to
investigate agronomic characters and aluminum
tolerance (Famoso et al. 2011; Zhao et al. 2011).
In many cases, the high SNP density and exten-
sive linkage decay present in natural populations
allowed direct identification of candidate genes;
in some cases, actual candidate mutations can be
identified.
Likewise, the availability of large sets of
SNPs genotyped across diverse germplasm pro-
vides a valuable resource for selecting targeted

100 Mb of reference
genome covered in the resequencing project.
This dataset has been used for a variety of pur-
poses, including the design of high-density SNP
genotyping arrays (Zhao et al. 2011). On the
other hand, the availability of high-throughput,
low-cost Illumina sequencing has allowed the
resequencing of approximately 70 varieties of O.
sativa , 14 accessions from the O. rufipogon - O.
nivara complex, 7 landraces of O. glaberrima ,
and 8 accessions of O. barthii through the Rice
SNP Consortium ( www.ricesnp.org) . The Inter-
national Rice Research Institute (IRRI) is also in
the process of sequencing 3,000 accessions of O.
sativa , chosen for their diversity and relevance
to research, as the initial set in a larger project
to

∼

resequence about 10,000 rice accessions

(K. McNally pers. comm.).
The low cost of this sequencing also allows
even single laboratories on modest budgets to
generate significant quantities of useful informa-
tion. For example, one service provider (Macro-
gen Inc., Korea) currently offers sufficient

sequencing data to provide 24 coverage of the

O. sativa genome for approximately US$3,000
on the Illumina platform. Using this service,
we have resequenced six varieties relevant to
salinity tolerance breeding (Pokkali, Capsule,
FL478, Hasawi, and IR29 from O. sativa and
a highly tolerant accession of O. glaberrima ).

×

Table 3.2. Coverage and polymorphism statistics for four O. sativa accessions resequenced on the Illumina GAIIx and
HiSeq2000 platforms

Accession Species group Coverage (approximate) # homozygous polymorphic sites % polymorphic sites

FL478 indica 25 × 3,214,904 0.86

Capsule indica/ admix 35 × 3,207,701 0.86

Pokkali indica/ admix 55 × 3,507,395 0.94

Hasawi aus/ admix 55 × 3,178,538 0.85