<p>Several mutations of the sorghum [<i>Sorghum bicolor</i> (L.) Moench] <i>GRANULE-BOUND STARCH SYNTHASE</i> (<i>GBSS</i>) gene [<i>Sobic.010G022600</i>; commonly known as <i>Waxy</i> (<i>Wx</i>)] result in a low amylose:amylopectin starch ratio. Recessive <i>waxy</i> (<i>wx</i>) alleles improve starch digestibility in ethanol production, human foods and beverages, and animal feed. However, breeding waxy sorghum is challenging due to reliance on traditional PCR markers for genotyping, which are not amenable to next-generation sequencing (NGS). Most commercial breeding programs use high-throughput genotyping and genomic selection in large, segregating populations prior to flowering. This study provides the first published NGS markers for the two most commonly used <i>waxy</i> (<i>wx</i>) alleles of sorghum and is the first to fully sequence the large insertion that is causal of the <i>wx</i><sup><i>a</i></sup> allele. In the absence of a pangenome including <i>wx</i><sup><i>a</i></sup> genotypes, we constructed an in silico B.Tx623 <i>wx</i><sup><i>a</i></sup> genome assembly from the B.Tx623 reference genome (v3.1.1) including the insertion, a ~ 5-kb-long terminal repeat (LTR) retrotransposon of the copia superfamily. The in silico<i> wx</i><sup><i>a</i></sup> assembly improved read mapping at <i>Sobic.010G022600</i> in <i>wx</i><sup><i>a</i></sup> individuals, identified 78 new uniquely mapped reads, and made it possible to distinguish different <i>Waxy</i> genotypes using short-read sequencing data. Functional PACE-PCR markers, suitable for marker-assisted selection and multiplexed, low-to-mid-density genomic selection, were developed for <i>Wx</i>, <i>wx</i><sup><i>a</i></sup>, and <i>wx</i><sup><i>b</i></sup> alleles. The PACE markers were validated in segregating populations of three public and private breeding programs. These new molecular breeding resources comprise a toolkit that will improve the efficiency of developing commercial waxy sorghum hybrids using genomics-assisted approaches.</p>

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An updated molecular toolkit for genomics-assisted breeding of waxy sorghum [Sorghum bicolor (L.) Moench]

  • Melinda K. Yerka,
  • Zhiyuan Liu,
  • Scott Bean,
  • Deepti Nigam,
  • Chad Hayes,
  • Diego Druetto,
  • Gabriel Krishnamoorthy,
  • Shelley Meiwes,
  • Gonzalo Cucit,
  • Gunvant B. Patil,
  • Yinping Jiao

摘要

Several mutations of the sorghum [Sorghum bicolor (L.) Moench] GRANULE-BOUND STARCH SYNTHASE (GBSS) gene [Sobic.010G022600; commonly known as Waxy (Wx)] result in a low amylose:amylopectin starch ratio. Recessive waxy (wx) alleles improve starch digestibility in ethanol production, human foods and beverages, and animal feed. However, breeding waxy sorghum is challenging due to reliance on traditional PCR markers for genotyping, which are not amenable to next-generation sequencing (NGS). Most commercial breeding programs use high-throughput genotyping and genomic selection in large, segregating populations prior to flowering. This study provides the first published NGS markers for the two most commonly used waxy (wx) alleles of sorghum and is the first to fully sequence the large insertion that is causal of the wxa allele. In the absence of a pangenome including wxa genotypes, we constructed an in silico B.Tx623 wxa genome assembly from the B.Tx623 reference genome (v3.1.1) including the insertion, a ~ 5-kb-long terminal repeat (LTR) retrotransposon of the copia superfamily. The in silico wxa assembly improved read mapping at Sobic.010G022600 in wxa individuals, identified 78 new uniquely mapped reads, and made it possible to distinguish different Waxy genotypes using short-read sequencing data. Functional PACE-PCR markers, suitable for marker-assisted selection and multiplexed, low-to-mid-density genomic selection, were developed for Wx, wxa, and wxb alleles. The PACE markers were validated in segregating populations of three public and private breeding programs. These new molecular breeding resources comprise a toolkit that will improve the efficiency of developing commercial waxy sorghum hybrids using genomics-assisted approaches.