Diversity Of Germplasm Resources Research Articles

Genetic diversity of grain yield traits and identification of a grain weight gene SiTGW6 in foxtail millet.

Agronomic traits were evaluated in 1250 foxtail millet accessions, and a crucial gene SiTGW6 governing grain yield was identified. Elite haplotypes and dCAPS markers developed for SiTGW6 facilitate molecular breeding. A comprehensive evaluation of phenotypic characteristics and genetic diversity in germplasm resources are important for gene discovery and breeding improvements. In this study, we conducted a comprehensive evaluation of 1250 foxtail millet varieties, assessing seven grain yield-related traits and fourteen common agronomic traits over two years. Principal component analysis, correlation analysis, and cluster analysis revealed a strong positive correlation between 1000-grain weight and grain width with grain yield, emphasizing their importance in foxtail millet breeding. Additionally, we found that panicle weight positively correlated with 1000-grain weight but negatively correlated with branch and tiller numbers, indicating selection factors during domestication and breeding. Using this information, we identified 27 germplasm resources suitable for high-yield foxtail millet breeding. Furthermore, through an integration of haplotype variations and phenotype association analysis, we pinpointed a crucial gene, SiTGW6, responsible for governing grain yield in foxtail millet. SiTGW6 encodes an IAA-glucose hydrolase, primarily localized in the cytoplasm and predominantly expressed in flowering panicles. Employing RNAseq analysis, we identified 1439 differentially expressed genes across various SiTGW6 haplotypes. Functional enrichment analysis indicating that SiTGW6 regulates grain yield through the orchestration of auxin and glucan metabolism, as well as plant hormone signaling pathways. Additionally, we have identified elite haplotypes and developed dCAPS markers for SiTGW6, providing valuable technical tools to facilitate molecular breeding efforts in foxtail millet.

Genetic diversity analysis in sunflower (Helianthus annuus L.) germplasms

Evaluating genetic diversity in germplasm resources is a prerequisite for any effective breeding program. To classify sixty-six sunflower germplasm and seven checks, the study was conducted during 2020. The analysis of variance revealed significant differences among the genotypes for all characters. Divergence analysis using hierarchical cluster analysis (HCA) has been performed to effectively determining genetically distant parents, which could be used for hybridization. The HCA based on first three PCs grouped the lines into 8 clusters, where cluster IV had maximum number of genotypes. Additionally, it signifies that cluster I and cluster VIII are highly diverse, whereas cluster V and VI are less diverse.

Assessment of genetic diversity for quantitative traits in sunflower germplasm

Evaluating genetic diversity in germplasm resources is a prerequisite for any effective breeding program. In this context, an investigation was carried out for analyzing genetic diversity in a set of 18 sunflower lines, which were grown at Oilseeds Section, Agriculture Research Institute, Tandojam, Sindh, Pakistan. Results demonstrated that mean squares were highly significantly different (P< 0.01) for days to flowering, days to maturity, plant height, head diameter, seeds head-1, seed index and grain yield plant-1. It represents that studied sunflower germplasm tend to have useful genetic resources for further breeding programs. In respect to genetic distance, a number of pairs were identified, which possess wide as well as narrow genetic distance; hence these pairs may be utilized for heterosis and backcross breeding purpose, respectively. Principal component analysis depicted that first three components showed a very high percentage of genetic variance (91.60%), indicating a great amount of genetic diversity in studied germplasm. Considering cluster analysis, diverse parents have also been identified through different clusters, signifying their importance for upcoming hybridization programs in sunflower. Keywords: Genetic diversity; Sunflower; Cluster analysis; Quantitative traits http://dx.doi.org/10.19045/bspab.2017.60022