論文

国際誌
2021年10月

From gene banks to farmer's fields: using genomic selection to identify donors for a breeding program in rice to close the yield gap on smallholder farms.

TAG. Theoretical and applied genetics. Theoretische und angewandte Genetik
  • Ryokei Tanaka
  • ,
  • Sarah Tojo Mandaharisoa
  • ,
  • Mbolatantely Rakotondramanana
  • ,
  • Harisoa Nicole Ranaivo
  • ,
  • Juan Pariasca-Tanaka
  • ,
  • Hiromi Kajiya-Kanegae
  • ,
  • Hiroyoshi Iwata
  • ,
  • Matthias Wissuwa

134
10
開始ページ
3397
終了ページ
3410
記述言語
英語
掲載種別
研究論文(学術雑誌)
DOI
10.1007/s00122-021-03909-9

KEY MESSAGE: Despite phenotyping the training set under unfavorable conditions on smallholder farms in Madagascar, we were able to successfully apply genomic prediction to select donors among gene bank accessions. Poor soil fertility and low fertilizer application rates are main reasons for the large yield gap observed for rice produced in sub-Saharan Africa. Traditional varieties that are preserved in gene banks were shown to possess traits and alleles that would improve the performance of modern variety under such low-input conditions. How to accelerate the utilization of gene bank resources in crop improvement is an unresolved question and here our objective was to test whether genomic prediction could aid in the selection of promising donors. A subset of the 3,024 sequenced accessions from the IRRI rice gene bank was phenotyped for yield and agronomic traits for two years in unfertilized farmers' fields in Madagascar, and based on these data, a genomic prediction model was developed. This model was applied to predict the performance of the entire set of 3024 accessions, and the top predicted performers were sent to Madagascar for confirmatory trials. The prediction accuracies ranged from 0.10 to 0.30 for grain yield, from 0.25 to 0.63 for straw biomass, to 0.71 for heading date. Two accessions have subsequently been utilized as donors in rice breeding programs in Madagascar. Despite having conducted phenotypic evaluations under challenging conditions on smallholder farms, our results are encouraging as the prediction accuracy realized in on-farm experiments was in the range of accuracies achieved in on-station studies. Thus, we could provide clear empirical evidence on the value of genomic selection in identifying suitable genetic resources for crop improvement, if genotypic data are available.

リンク情報
DOI
https://doi.org/10.1007/s00122-021-03909-9
PubMed
https://www.ncbi.nlm.nih.gov/pubmed/34264372
ID情報
  • DOI : 10.1007/s00122-021-03909-9
  • PubMed ID : 34264372

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