Institut für Pflanzenzüchtung, Saatgutforschung und Populationsgenetik

Permanent URI for this collectionhttps://hohpublica.uni-hohenheim.de/handle/123456789/13

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Capturing wheat phenotypes at the genome level
(2022) Hussain, Babar; Akpınar, Bala A.; Alaux, Michael; Algharib, Ahmed M.; Sehgal, Deepmala; Ali, Zulfiqar; Aradottir, Gudbjorg I.; Batley, Jacqueline; Bellec, Arnaud; Bentley, Alison R.; Cagirici, Halise B.; Cattivelli, Luigi; Choulet, Fred; Cockram, James; Desiderio, Francesca; Devaux, Pierre; Dogramaci, Munevver; Dorado, Gabriel; Dreisigacker, Susanne; Edwards, David; El-Hassouni, Khaoula; Eversole, Kellye; Fahima, Tzion; Figueroa, Melania; Gálvez, Sergio; Gill, Kulvinder S.; Govta, Liubov; Gul, Alvina; Hensel, Goetz; Hernandez, Pilar; Crespo-Herrera, Leonardo Abdiel; Ibrahim, Amir; Kilian, Benjamin; Korzun, Viktor; Krugman, Tamar; Li, Yinghui; Liu, Shuyu; Mahmoud, Amer F.; Morgounov, Alexey; Muslu, Tugdem; Naseer, Faiza; Ordon, Frank; Paux, Etienne; Perovic, Dragan; Reddy, Gadi V. P.; Reif, Jochen Christoph; Reynolds, Matthew; Roychowdhury, Rajib; Rudd, Jackie; Sen, Taner Z.; Sukumaran, Sivakumar; Ozdemir, Bahar Sogutmaz; Tiwari, Vijay Kumar; Ullah, Naimat; Unver, Turgay; Yazar, Selami; Appels, Rudi; Budak, Hikmet
Recent technological advances in next-generation sequencing (NGS) technologies have dramatically reduced the cost of DNA sequencing, allowing species with large and complex genomes to be sequenced. Although bread wheat (Triticum aestivum L.) is one of the world’s most important food crops, efficient exploitation of molecular marker-assisted breeding approaches has lagged behind that achieved in other crop species, due to its large polyploid genome. However, an international public–private effort spanning 9 years reported over 65% draft genome of bread wheat in 2014, and finally, after more than a decade culminated in the release of a gold-standard, fully annotated reference wheat-genome assembly in 2018. Shortly thereafter, in 2020, the genome of assemblies of additional 15 global wheat accessions was released. As a result, wheat has now entered into the pan-genomic era, where basic resources can be efficiently exploited. Wheat genotyping with a few hundred markers has been replaced by genotyping arrays, capable of characterizing hundreds of wheat lines, using thousands of markers, providing fast, relatively inexpensive, and reliable data for exploitation in wheat breeding. These advances have opened up new opportunities for marker-assisted selection (MAS) and genomic selection (GS) in wheat. Herein, we review the advances and perspectives in wheat genetics and genomics, with a focus on key traits, including grain yield, yield-related traits, end-use quality, and resistance to biotic and abiotic stresses. We also focus on reported candidate genes cloned and linked to traits of interest. Furthermore, we report on the improvement in the aforementioned quantitative traits, through the use of (i) clustered regularly interspaced short-palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9)-mediated gene-editing and (ii) positional cloning methods, and of genomic selection. Finally, we examine the utilization of genomics for the next-generation wheat breeding, providing a practical example of using in silico bioinformatics tools that are based on the wheat reference-genome sequence.
Genetic dissection of hybrid performance and heterosis for yield-related traits in maize
(2021) Li, Dongdong; Zhou, Zhiqiang; Lu, Xiaohuan; Jiang, Yong; Li, Guoliang; Li, Junhui; Wang, Haoying; Chen, Shaojiang; Li, Xinhai; Würschum, Tobias; Reif, Jochen C.; Xu, Shizhong; Li, Mingshun; Liu, Wenxin
Heterosis contributes a big proportion to hybrid performance in maize, especially for grain yield. It is attractive to explore the underlying genetic architecture of hybrid performance and heterosis. Considering its complexity, different from former mapping method, we developed a series of linear mixed models incorporating multiple polygenic covariance structures to quantify the contribution of each genetic component (additive, dominance, additive-by-additive, additive-by-dominance, and dominance-by-dominance) to hybrid performance and midparent heterosis variation and to identify significant additive and non-additive (dominance and epistatic) quantitative trait loci (QTL). Here, we developed a North Carolina II population by crossing 339 recombinant inbred lines with two elite lines (Chang7-2 and Mo17), resulting in two populations of hybrids signed as Chang7-2 × recombinant inbred lines and Mo17 × recombinant inbred lines, respectively. The results of a path analysis showed that kernel number per row and hundred grain weight contributed the most to the variation of grain yield. The heritability of midparent heterosis for 10 investigated traits ranged from 0.27 to 0.81. For the 10 traits, 21 main (additive and dominance) QTL for hybrid performance and 17 dominance QTL for midparent heterosis were identified in the pooled hybrid populations with two overlapping QTL. Several of the identified QTL showed pleiotropic effects. Significant epistatic QTL were also identified and were shown to play an important role in ear height variation. Genomic selection was used to assess the influence of QTL on prediction accuracy and to explore the strategy of heterosis utilization in maize breeding. Results showed that treating significant single nucleotide polymorphisms as fixed effects in the linear mixed model could improve the prediction accuracy under prediction schemes 2 and 3. In conclusion, the different analyses all substantiated the different genetic architecture of hybrid performance and midparent heterosis in maize. Dominance contributes the highest proportion to heterosis, especially for grain yield, however, epistasis contributes the highest proportion to hybrid performance of grain yield.

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