Morphological and microsatellite marker-based characterization and diversity analysis of novel vegetable soybean [Glycine max (L.) Merrill].

BACKGROUND: Vegetable soybean seeds are among the most popular and nutrient-dense beans in the world due to their delicious flavor, high yield, superior nutritional value, and low trypsin content. There is significant potential for this crop that Indian farmers do not fully appreciate because of the limited germplasm range. Therefore, the current study aims to identify the diverse lines of vegetable soybean and explore the diversity produced by hybridizing grain and vegetable-type soybean varieties. Indian researchers have not yet published work describing and analysing novel vegetable soybean for microsatellite markers and morphological traits. METHODS AND RESULTS: Sixty polymorphic SSR markers and 19 morphological traits were used to evaluate the genetic diversity of 21 newly developed vegetable soybean genotypes. A total of 238 alleles, ranging from 2 to 8, were found, with a mean of 3.97 alleles per locus. The polymorphism information content varied from 0.05 to 0.85, with an average of 0.60. A variation of 0.25-0.58 with a mean of 0.43 was observed for Jaccard's dissimilarity coefficient. CONCLUSION: The diverse genotypes identified can be helpful to understand the genetics of vegetable soybean traits and can be used in improvement programs; study also explains the utility of SSR markers for diversity analysis of vegetable soybean. Here, we identified the highly informative SSRs with PIC > 0.80 (satt199, satt165, satt167, satt191, satt183, satt202, and satt126), which apply to genetic structure analysis, mapping strategies, polymorphic marker surveys, and background selection in genomics-assisted breeding.

Unraveling the Relationship Between Seed Yield and Yield-Related Traits in a Diversity Panel of Brassica juncea Using Multi-Traits Mixed Model.

The response to selection in any crop improvement program depends on the degree of variance and heritability. The objective of the current study was to explain variance and heritability components in Indian mustard Brassica juncea (L). Czern & Coss to recognize promising genotypes for effective breeding. Two hundred and eighty-nine diverse accessions of Indian mustard belonging to four continents were analyzed for yield and yield-related traits (20 traits) over two seasons (2017-2018 and 2018-2019) using an alpha lattice design. The genetic variance was found to be significant (P ≤ 0.01) for the individual and under pooled analysis for all of the evaluated traits, demonstrating the presence of significant genetic variability in the diversity panel, which bids greater opportunities for utilizing these traits in future breeding programs. High heritability combined with high genetic advance as percent of mean and genotypic coefficient of variation was observed for flowering traits, plant height traits, seed size, and seed yield/plant; hence, a better genetic gain is expected upon the selection of these traits over subsequent generations. Both correlation and stepwise regression analysis indicated that the main shoot length, biological yield, total seed yield, plant height up to the first primary branch, seed size, total siliqua count, days to flowering initiation, plant height at maturity, siliquae on the main shoot, main shoot length, and siliqua length were the most significant contributory traits for seed yield/plant. Also, promising genotypes were identified among the diversity panel, which can be utilized as a donor to improve Indian mustard further. These results indicated a greater scope for improving seed yield per plant directly through a selection of genotypes having the parsimonious combination of these nine traits.