Genomics and Applied Biology 2024, Vol.15, No.3, 162-171 http://bioscipublisher.com/index.php/gab 164 Figure 1 Development of the wild Macrocystis x Lessonia progeny in culture (Adopted from Murúa et al., 2020) Image caption: (a) Emergence of early embryo from unicellular to few-celled female gametophytes. Scale bar: 14 µm. Inset: Germination pattern of the hybrid spores showing an empty embryospore and a primary cell of the gametophyte. Scale bar 8 µm. (b) Juvenile individual with fused-haptera holdfast (arrowhead). Scale bar: 1 cm. (c) Growth tendency of the hybrid progeny until 27 weeks, time point where they all suddenly died off. Segment = mean. (d) Corrected relative growth rate (RGRc) for the progeny from M. pyrifera (Mp), L. spicata (Ls) and the field hybrid (hyb). Boxes show median (horizontal bold line) ± 1.5 times the interquartile range (whiskers). Dots represent deemed outliers, and asterisks represent statistical groups after a Tukey’s test (p < 0.05). (e,f) Morphology of juvenile M. pyrifera (e) and L. spicata (f) from Mar Brava after 40 weeks, showing their characteristic holdfast morphology (arrowheads). Scale bars: 2.5 cm. Insets: holdfast morphology of the same species at 15 weeks. Scale bars: 350 µm (Adopted from Murúa et al., 2020) 3.2 Marker-assisted selection (MAS) in kelp breeding Marker-assisted selection (MAS) is a modern breeding technique that uses molecular markers to select for desirable traits, thereby accelerating the breeding process and improving accuracy. In kelp breeding, MAS has been employed to map and introgress genes associated with economically important traits. For instance, in Saccharina japonica, SSR markers have been used to construct genetic linkage maps and identify QTLs for traits like blade length and width, facilitating the selection of superior genotypes (Wang et al., 2023). MAS helps in the precise transfer of targeted QTLs, as demonstrated in other crops like cotton, where it has led to the development of cultivars with improved fiber quality (Darmanov et al., 2022). 3.3 Application of genomics and bioinformatics in kelp breeding The integration of genomics and bioinformatics in kelp breeding represents a significant advancement over traditional methods. Genomic selection (GS) uses genome-wide markers to predict complex phenotypes, thereby accelerating breeding cycles and improving selection accuracy. This approach has been successfully applied in other fields, such as animal and tree breeding, and holds promise for kelp as well (Meuwissen et al., 2016; Grattapaglia et al., 2018). High-throughput genotyping and phenotyping, combined with machine learning and bioinformatics tools, can enhance the prediction models and facilitate the development of robust kelp cultivars (Sandhu et al., 2022). The enrichment of high-quality annotated reference genomes and functional analysis of trait-associated markers further supports the application of genomics in kelp breeding (Hu et al., 2023). 3.4 Challenges and opportunities in hybrid kelp breeding Hybrid kelp breeding faces several challenges, including the management of germplasm diversity, technological innovations, and regional cooperation. Issues such as genetic erosion, loss of heterozygosity, and inter-cultivar accidental admixing need to be addressed to ensure sustainable breeding practices. However, there are also
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