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      Doubled haploid based parental lines are most suitable in predicting heterosis using microsatellites and in development of highly heterotic F1 hybrids in Brassica oleracea

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          Abstract

          In Brassica oleracea, heterosis is one of the most efficient tools giving impetus to hybrid vegetable industry. In this context, we presented the first report on identifying superior heterotic crosses for yield and commercial traits in cauliflower involving cytoplasmic male sterile (CMS) and doubled haploid (DH) lines as parents. We studied the suitability of SSR and EST-SSRs based genetic distance (GD) and morphological markers based phenotypic distance (PD) in prediction of heterosis when DH based genotypes are used as parents in developing F1 hybrids. Overall 120 F1 hybrids derived from twenty Ogura cybrid CMS lines and six DH based testers were evaluated for 16 phenotypic traits along with their 26 parental lines and 4 commercial standard checks, in 10 × 15 alpha lattice design. The genomic SSR and EST-SSRs based genetic structure analysis grouped 26 parental lines into 4 distinct clusters. The CMS lines Ogu118-6A, Ogu33A, Ogu34-1A were good general combiner for developing short duration hybrids. The SCA effects were significantly associated with heterosis suggesting non-additive gene effects for heterotic response of hybrids. Less than unity value of σ2A/D coupled with σ2gca/σ2sca indicated the predominance of non-additive gene action in the expression of studied traits. The genetic distance estimates among 26 parents ranged from 0.44 to 0.98 and were significantly associated with heterosis for important commercial traits, suggesting the utility of microsatellite based genetic distance in prediction of heterosis in B. oleracea.

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          Author and article information

          Journal
          bioRxiv
          January 03 2019
          Article
          10.1101/511055
          8706031b-85ca-4a88-be3e-dd846c6ed710
          © 2019
          History

          Quantitative & Systems biology,Plant science & Botany
          Quantitative & Systems biology, Plant science & Botany

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