Association mapping identifies quantitative trait loci (QTL) for digestibility in rice straw.
Association mapping identifies quantitative trait loci (QTL) for digestibility in rice straw.
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DOI：
10.1186/s13068-020-01807-8
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发表时间：
2020
影响因子：
6.3
通讯作者：
McQueen-Mason SJ
中科院分区：
文献类型：
--
作者：
Nguyen DT;Gomez LD;Harper A;Halpin C;Waugh R;Simister R;Whitehead C;Oakey H;Nguyen HT;Nguyen TV;Duong TX;McQueen-Mason SJ
将农业废物中的木质纤维素生物质转化为生物燃料和化学品被认为是在不损害粮食安全的情况下提供可持续低碳产品的有前途的方法。然而，木质纤维素生物质在生物燃料和化学品生产中的使用受到生产过程的成本效益的限制，因为它不耐酶水解和可发酵糖释放（即糖化）。稻草是一种特别有吸引力的原料，因为目前每年有数百万吨稻草在田间燃烧进行处置。本研究的目的是探索影响水稻（Oryza sativa）秸秆对酶促糖化的抗性的潜在自然遗传变异。最终，我们想要研究是否可以识别可用于水稻育种的遗传标记，以改进该性状的商业品种。在这里，我们描述了越南水稻全基因组关联面板的开发和表征、稻草糖化和木质素含量的高通量分析，以及组合数据集的初步全基因组关联研究（GWAS）的结果。我们鉴定了可能对稻草糖化产生影响的 QTL 和可能的候选基因。我们组建了一个多样性小组，其中包括 151 个水稻基因型（籼稻和粳稻类型），这些水稻基因型来自越南种植的商业品种、历史优良品种和传统地方品种。使用基因型测序 (GBS) 方法对多样性组进行基因分型，共产生 328,915 个单核苷酸多态性 (SNP)。我们从这 151 个基因型的茎中收集了生物质糖化和木质素含量的表型数据。两年多来，我们对籼稻基因型进行了 GWAS，确定了 10 个与糖化（消化率）相关的显着 QTL 和 7 个与木质素相关的显着 QTL。 11 号染色体上的一个 QTL 出现在消化率和木质素的 GWAS 中。在研究的两年中，观察到了 CH2、CH6、CH7、CH8 和 CH11 上的 7 个消化率 QTL。糖化的 QTL 区域包括三个潜在的候选基因，此前已报道这些基因会影响消化率：OsAT10； OsIRX9;和 OsMYB58/63-L。尽管对新种质的复杂性状进行多相分析存在困难，但中等分辨率的 GWAS 成功地鉴定了包含已知和/或新基因的遗传关联，这些基因涉及确定稻秆的糖化潜力和木质素含量。 QTL 区域内的合理候选物，特别是那些在细胞壁生物合成中起作用的候选物，已被确定，但需要验证以确认其在水稻育种中的应用价值。
The conversion of lignocellulosic biomass from agricultural waste into biofuels and chemicals is considered a promising way to provide sustainable low carbon products without compromising food security. However, the use of lignocellulosic biomass for biofuel and chemical production is limited by the cost-effectiveness of the production process due to its recalcitrance to enzymatic hydrolysis and fermentable sugar release (i.e., saccharification). Rice straw is a particularly attractive feedstock because millions of tons are currently burned in the field each year for disposal. The aim of this study was to explore the underlying natural genetic variation that impacts the recalcitrance of rice (Oryza sativa) straw to enzymatic saccharification. Ultimately, we wanted to investigate whether we could identify genetic markers that could be used in rice breeding to improve commercial cultivars for this trait. Here, we describe the development and characterization of a Vietnamese rice genome-wide association panel, high-throughput analysis of rice straw saccharification and lignin content, and the results from preliminary genome-wide association studies (GWAS) of the combined data sets. We identify both QTL and plausible candidate genes that may have an impact on the saccharification of rice straw. We assembled a diversity panel comprising 151 rice genotypes (Indica and Japonica types) from commercial, historical elite cultivars, and traditional landraces grown in Vietnam. The diversity panel was genotyped using genotype by sequencing (GBS) methods yielding a total of 328,915 single nucleotide polymorphisms (SNPs). We collected phenotypic data from stems of these 151 genotypes for biomass saccharification and lignin content. Using GWAS on the indica genotypes over 2 years we identified ten significant QTL for saccharification (digestibility) and seven significant QTL for lignin. One QTL on chromosome 11 occurred in both GWAS for digestibility and for lignin. Seven QTL for digestibility, on CH2, CH6, CH7, CH8, and CH11, were observed in both years of the study. The QTL regions for saccharification include three potential candidate genes that have been previously reported to influence digestibility: OsAT10; OsIRX9; and OsMYB58/63-L. Despite the difficulties associated with multi-phasic analysis of complex traits in novel germplasm, a moderate resolution GWAS successfully identified genetic associations encompassing both known and/or novel genes involved in determining the saccharification potential and lignin content of rice straw. Plausible candidates within QTL regions, in particular those with roles in cell wall biosynthesis, were identified but will require validation to confirm their value for application in rice breeding.
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影响因子：
6.1
作者：
Bunzel, Mirko;Schuessler, Anne;Saha, Gerard Tchetseubu
通讯作者：
Saha, Gerard Tchetseubu
影响因子：
6.3
作者：
Allwright MR;Payne A;Emiliani G;Milner S;Viger M;Rouse F;Keurentjes JJ;Bérard A;Wildhagen H;Faivre-Rampant P;Polle A;Morgante M;Taylor G
通讯作者：
Taylor G
影响因子：
13.8
作者：
Daly P;McClellan C;Maluk M;Oakey H;Lapierre C;Waugh R;Stephens J;Marshall D;Barakate A;Tsuji Y;Goeminne G;Vanholme R;Boerjan W;Ralph J;Halpin C
通讯作者：
Halpin C
DOI：
10.1073/pnas.1202079109
发表时间：
2012-10-16
影响因子：
11.1
作者：
Chiniquy, Dawn;Sharma, Vaishali;Ronald, Pamela C.
通讯作者：
Ronald, Pamela C.
影响因子：
5.8
作者：
Bradbury, Peter J.;Zhang, Zhiwu;Buckler, Edward S.
通讯作者：
Buckler, Edward S.