A Database for Triticeae and Avena
L.J. Wright, D.B Cooper, BARI Ft.
Collins CO; P.M. Hayes, I. Matus, K. Richardson, and J. Von Zitzewits, OSU,
The breeding and selecting process for developing a
new malting barley variety is an arduous process that may take up to 12 years.
It takes that long to determine if an experimental barley line has the agronomic
potential to be accepted by growers and the malting and brewing quality to
be accepted by industry. A successful variety is a unique combination of
genes (a genotype) that is able to perform in a range of production conditions
(environments). Multi-environment testing will always be required to confirm
that a phenotype will indeed have the desired agronomic and quality attributes
(genotype). However, in current practice a significant amount of effort
is devoted to testing selections that simply do not have the genetic potential
to be varieties. Tools for determining the genotype of the experimental
line increases the efficiency of the breeding process by increasing the likelihood
that the experimental lines that are brought forward will have the desired
quality to become a new malting variety. The challenge is to identify efficient
genotype characterization tools and to determine what, and where, the genes
are that determine agronomics and quality. Simple Sequence Repeats (SSRs)
provide fairly comprehensive genomic coverage, they are amenable to automation,
they have locus identity, and they are multi-allelic. Many agronomic and
quality traits show quantitative inheritance, and the genes determining these
traits have been quantified using Quantitative Trait Locus (QTL) tools.
Our objective is to integrate allelic diversity and breeding value information
on breeding lines, as revealed by SSRs and extensive phenotyping, with QTLs
reported in a range of mapping populations. We are interested in determining
if associations between specific alleles and QTLs could be identified, because
these associations could then be used for designing crosses and for marker-assisted
In 2000 BARI and Oregon State University initiated a
joint project to address this question. A sample of 196 six-rowed and two-rowed
BARI experimental barley lines were genotyped with 72 SSR markers using either
an ABI377 or ABI3700 Automated Sequencer. SSR markers were chosen to provide
maximum genome coverage, and most are in the public domain.
The experimental barley lines were rated on a relative
1 – 9 scale (low to high measurement) for several agronomic and quality traits.
Rankings were based on multi-environment agronomic data including heading,
plant height, lodging, maturity, disease resistance and DON content. Quality
data included grain protein, soluble protein, extract, diastatic power, alpha
amylase, and beta glucan.
Genotype:phenotype associations were established by
sorting the data by rating score for each trait. The allele sizes of lines
with high and low scores were then determined for each SSR. Frequency differences
greater than 20% between the two groups were considered significant. These
trait-associated SSR markers were then compared with the QTL summary information
posted at: http://www.barleyworld.org/NABGMP/qtllsum42401.htm.
An example of how this process was done is shown in Table 1.
Putative associations were identified between SSR markers
and phenotypic traits for both six- and two-rowed malting barley. This presentation
will focus on malting quality. Fifty associations were identified between
SSR markers and phenotypic traits for the six-rowed barley lines (Table 2)
and seventy-eight associations were found for the two-rowed barley lines
Of the thirty-four associations for malting quality
traits for the six-rowed barley lines there were twenty-nine agreements with
the known QTLs for malting quality. For the two-rowed barley lines, seventy-eight
associations were identified with quality traits and fifty-seven were correlated
with the known malting QTLs (Table 4). DON associated SSR markers and other
associated traits also presented for six-rowed material (Table 5).
There was remarkably good agreement between trait-associated
SSRs in the BARI germplasm and QTL detection in mapping populations. This
result provides evidence that the QTL detection in mapping populations represent
the effects of genes at which there is also allelic diversity in agronomically-relevant
germplasm arrays. There was greater allelic diversity in the two-rowed that
in the six-row germplasm, and accordingly more associations were identified.
There were more trait:phenotype associations than published QTLs for the
same trait, suggesting the presence of heretofore-undetected loci. Additional
research will be necessary to validate these new QTL. We believe that information
on allelic diversity at SSR loci may be useful for cross design and line
selection in a malting barley variety development program. Further studies
involving additional germplasm arrays, selection experiments, and formal
association analysis are planned.
Table 1. Two-Row SSR Markers - Diastatic Power
Table 2. Six-Rowed Trait-Associated SSR Markers. PCR product size associated with low and high trait value.
Table 3. Two-Rowed Trait Associated SSR Markers. PCR product size associated with low and high trait value.
Table 4. Agreement between Associated SSR Markers and the Corresonding QTLs.
Table 5. Six-Rowed Trait-Associated SSR Markers PCR product size associated with low and high trait value.