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Principles of Plant Genetics and Breeding

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BREEDING SOYBEAN 525<br />

An advantage <strong>of</strong> using parent–<strong>of</strong>fspring regression to estimate heritability is that it is straightforward (Hanson 1963, p. 129).<br />

However, F2 individuals <strong>and</strong> derived F3 progenies are grown in separate environments (years), with no estimate <strong>of</strong> environmental<br />

variance <strong>and</strong> no estimate <strong>of</strong> genotype × environment interaction. Depending on the variability <strong>of</strong> the trait measured, biases can be<br />

significant (Hanson 1963, p. 129).<br />

In summary, the development <strong>and</strong> utilization <strong>of</strong> multiple generations (P1 , P2 , F1 , F2 , F3 , BC1P1 , BC1P2 , BC1P1S1 , BC1P2S1 , etc.)<br />

can provide flexibility <strong>and</strong> opportunities for multiple estimates <strong>of</strong> inheritance factors, both qualitative <strong>and</strong> quantitative. Such<br />

populations are also complementary for developing breeding populations.<br />

In conjunction with the above early generation studies, F2 plants were grown for the purpose <strong>of</strong> producing recombinant inbred<br />

lines (RILs) by single-seed descent. The use <strong>of</strong> RILs in genetic studies requires that the finished inbred lines be an unselected sample<br />

<strong>of</strong> the F2 population; ideally, an inbred line for each F2 plant grown (Hallauer & Mir<strong>and</strong>a 1981, p. 89). If inbreeding depression<br />

is a problem, resulting in the death <strong>of</strong> some plants before becoming inbred, a r<strong>and</strong>om non-selected RIL population may be<br />

difficult to obtain. However, this is usually not the case with self-pollinated crops such as soybean. The net result <strong>of</strong> using RILs to<br />

estimate inheritance, as opposed to an F2 population, is that the Φ2 A among RILs is twice as large as the Φ2 A among F3 families<br />

or among F2 individuals. Because each RIL is theoretically completely inbred, Φ2 D is zero (there are no intralocus genotypic interactions),<br />

which also means that there are no unusable Φ2 AD interactions. Hence, selection among RILs is expected to be more<br />

effective than selection among F2:3 families (Bernardo 2002, p. 180).<br />

However, Hallauer <strong>and</strong> Mir<strong>and</strong>a (1981, p. 91) noted that the use <strong>of</strong> RILs has two serious h<strong>and</strong>icaps. First, as already noted, RILs<br />

require the development <strong>of</strong> a set <strong>of</strong> unselected inbred lines that are representative <strong>of</strong> genotypes <strong>of</strong> a reference population (the F2 ).<br />

This can be difficult if, during the selfing process, inbreeding produces weak plants that die <strong>and</strong> if high disease pressure kills<br />

plants. Second, the time required to develop RILs is much greater than that for developing <strong>and</strong> testing F3 progeny rows. Hence, it<br />

is wise to make early generation estimates <strong>of</strong> predicted gain from selection so as to determine if early generation selection can be<br />

pr<strong>of</strong>itable. Early generation selection can be highly desirable, if it is possible, enabling a greater allocation <strong>of</strong> resources to the most<br />

promising families (Bernardo 2002, pp. 119, 180, <strong>and</strong> 181).<br />

However, where heritabilities are low (due to environment, genotype × environment interactions, Φ2 D , etc.), RILs can provide<br />

useful estimates <strong>of</strong> genetic parameters <strong>and</strong> can be complementary to the breeding program. Replicated field trials across multiple<br />

locations <strong>and</strong> years with RILs will likely result in better estimates <strong>of</strong> heritability, better estimates <strong>of</strong> genetic gain from selection,<br />

<strong>and</strong> in the potential development <strong>of</strong> improved lines.<br />

The development <strong>and</strong> utilization <strong>of</strong> RILs can facilitate the construction <strong>of</strong> a genetic map based on molecular marker linkages in<br />

the RIL population. If sufficient markers are located at enough strategic points, markers can be detected that are linked to genetic<br />

factors controlling the expression <strong>of</strong> quantitative traits. This was an important consideration in the development <strong>of</strong> RILs segregating<br />

for tolerance to charcoal rot <strong>and</strong> will allow for the development <strong>and</strong> release <strong>of</strong> charcoal rot-tolerant varieties, along with the<br />

release <strong>of</strong> molecular markers tightly linked to genetic factors affecting tolerance. Breeders can then create populations <strong>and</strong> test<br />

them in their own unique environments, while selecting for charcoal rot tolerance using molecular markers.<br />

The most cost-effective way to reduce losses from plant diseases <strong>and</strong> stresses is through the use <strong>of</strong> cultivars with tolerance to the<br />

appropriate stresses. It is anticipated that this will be the case with charcoal rot <strong>of</strong> soybean. However, at this time, insufficient<br />

information is available to determine how tolerance to charcoal rot is inherited: as a single gene, as multiple genes with high heritability,<br />

or as multiple genes with low heritability. But, because <strong>of</strong> proper planning <strong>and</strong> execution, sufficient quantities <strong>of</strong> the<br />

appropriate segregating populations have been developed to effectively determine the inheritance <strong>of</strong> tolerance to charcoal rot<br />

<strong>and</strong> to maximize the available genetic potential for developing improved soybean varieties with tolerance to charcoal rot.<br />

References<br />

Bernardo, R. 2002. <strong>Breeding</strong> for quantitative traits in plants. Stemma Press, Woodbury, MN.<br />

Campbell, K.W., A.M. Hamblin, <strong>and</strong> D.G. White. 1997. Inheritance <strong>of</strong> resistance to aflatoxin production in the cross between<br />

corn inbreds B73 <strong>and</strong> LB31. Phytopathology 87:1144–1147.<br />

Campbell, K.W., <strong>and</strong> D.G. White. 1995. Inheritance <strong>of</strong> resistance to Aspergillus ear rot <strong>and</strong> aflatoxin in corn genotypes.<br />

Phytopathology 85:886–896.<br />

Hallauer, A.R., <strong>and</strong> J.B. Mir<strong>and</strong>a. 1981. Quantitative genetics in maize breeding. Iowa State University Press, Ames, IA.<br />

Hamblin, A.M., <strong>and</strong> D.G. White. 2000. Inheritance <strong>of</strong> resistance to Aspergillus ear rot <strong>and</strong> aflatoxin production in corn from<br />

Tex6. Phytopathology 90:292–296.<br />

Hanson, W.D. 1963. Heritability. In: Statistical genetics <strong>and</strong> plant breeding (Hanson, W.D., <strong>and</strong> H.F. Robinson, eds),<br />

pp. 125–140. National Academy <strong>of</strong> Sciences <strong>and</strong> National Research Council, Washington, DC.<br />

Mansur, L.M., A.L. Carriquiry, <strong>and</strong> A.P. Rao-Arelli. 1993. Generation mean analysis <strong>of</strong> resistance to race 3 <strong>of</strong> soybean cyst nematode.<br />

Crop Sci. 33:1249–1253.<br />

Mather, K., <strong>and</strong> J. Jinks. 1971. Biometrical genetics, the study <strong>of</strong> continuous variation, 2nd edn. Cornell Univeristy Press, Ithaca,<br />

NY.<br />

Moll, R.H., D.L. Thompson, <strong>and</strong> P.H. Harvey. 1963. A quantitative genetic study <strong>of</strong> the inheritance <strong>of</strong> resistance to brown spot<br />

(Physoderma maydis) <strong>of</strong> corn. Crop Sci. 3:389–391.

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