Advancements in Genotype Technology and Their Breeding Applications

A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Crop Genetics, Genomics and Breeding".

Deadline for manuscript submissions: 31 March 2025 | Viewed by 789

Special Issue Editor


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Guest Editor
Department of Crop Science, Chungbuk National University, Cheongju, Republic of Korea
Interests: crop breeding; crop genetics and genomics; seed production; genotyping technology; soybeans; legumes

Special Issue Information

Dear Colleagues,

Crop breeding has witnessed numerous advancements throughout history, evolving from conventional selective breeding to modern techniques based on molecular markers. The integration of molecular markers has revolutionized the speed and accuracy of plant genetic analysis for the purpose of crop improvement. Furthermore, revolutionary next-generation sequencing (NGS) technology has significantly enhanced crop breeding, evolving into a powerful tool for generating genomic data. NGS technologies introduce innovative tools and concepts that can enhance the accuracy and effectiveness of crop breeding. This includes the development of cost-efficient, high-throughput genotyping technologies as well as their diverse applications in sustainable agriculture.

Systematic data analytics within genotyping approaches—based on principles, applications, and decision scenarios—along with supporting software have revealed that the revolution in genotyping technology has resulted in an explosion of data. This data expansion has driven a breakthrough in integrating artificial intelligence with automation, enabling plant breeders to genotype a large number of samples within a short period of time. This is crucial for implementing genome-wide association studies (GWAS) and genomic selection (GS), paving the way for next-generation breeding programs.

This Special Issue focuses on discussing technological advancements associated with breeding during the big data era, including breeding models, genotyping technologies, and future intelligent breeding. Therefore, the articles included will highlight the potential of smart breeding technologies driven by advances in genotyping/sequencing technology along with advanced data analytics tools.

Dr. Ju-Kyung Yu
Guest Editor

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Keywords

  • genotyping
  • next-generation sequencing (NGS)
  • molecular markers
  • genotyping by sequencing (GbS)
  • marker-assisted breeding
  • genomics assisted breeding
  • genome-wide association studies
  • genomic selection
  • AI-based data analytics
  • phenomics

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Published Papers (1 paper)

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Research

18 pages, 2643 KiB  
Article
Genetic Diversity Patterns Within and Among Varieties of Korean Italian Ryegrass (Lolium multiflorum) and Perennial Ryegrass (Lolium perenne) Based on Simple Sequence Repetition
by Dong-Geon Nam, Eun-Seong Baek, Eun-Bin Hwang, Sang-Cheol Gwak, Yun-Ho Lee, Seong-Woo Cho, Ju-Kyung Yu and Tae-Young Hwang
Agriculture 2025, 15(3), 244; https://doi.org/10.3390/agriculture15030244 - 23 Jan 2025
Viewed by 398
Abstract
Italian ryegrass (Lolium multiflorum, IRG) and perennial ryegrass (Lolium perenne L., PRG) are widely cultivated as forage grasses in Korea using heterogeneous and polycross techniques, which promote genetic diversity within varieties. However, their genetic diversity patterns in Korea remain underexplored. [...] Read more.
Italian ryegrass (Lolium multiflorum, IRG) and perennial ryegrass (Lolium perenne L., PRG) are widely cultivated as forage grasses in Korea using heterogeneous and polycross techniques, which promote genetic diversity within varieties. However, their genetic diversity patterns in Korea remain underexplored. This study evaluated the genetic diversity of IRG (eight varieties, including one exotic) and PRG (two exotic varieties) using 66 simple sequence repeat (SSR) markers. Across 87 samples (nine IRG and two PRG varieties), 655 alleles were identified, averaging 9.9 per locus. Key genetic parameters included heterozygosity (0.399), observed heterozygosity (0.675), fixation index (0.4344), and polymorphic informative content (0.6428). The lowest within-variety genetic distance was observed in ‘Hwasan 104ho’ (0.469), while ‘IR901’ had the highest (0.571). Between varieties, the closest genetic distance was between ‘Greencall’ and ‘Greencall 2ho’ (0.542), and the furthest was between ‘Kowinmaster’ and ‘Aspire’ (0.692). Molecular variance analysis showed 90% variation within varieties and 10% among varieties. Five clusters (I–V) were identified, with cluster I primarily including diploid IRG varieties and the tetraploid ‘Hwasan 104ho.’ Structural analysis differentiated diploid from tetraploid varieties (K = 2) and further separated tetraploid IRG and PRG (K = 3). Principal component analysis confirmed these groupings, with ‘Greencall’ and ‘Greencall 2ho’ exhibiting the closest genetic distance (0.227) and ‘Greencall’ and ‘Aspire’ the furthest (0.384). These findings provide a foundational resource for marker-assisted breeding to improve agronomic traits and enhance the efficiency of ryegrass breeding programs. Full article
(This article belongs to the Special Issue Advancements in Genotype Technology and Their Breeding Applications)
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