Articles written in Journal of Genetics

    • Population structure and association mapping studies for important agronomic traits in soybean

      Bhupender Kumar Akshay Talukdar Indu Bala Khushbu Verma Sanjay Kumar Lal Ramesh Lal Sapra B. Namita Subhash Chander Reshu Tiwari

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      The present study was carried out with a set of 96 diverse soybean genotypes with the objectives of analysing the population structure and to identify molecular markers associated with important agronomic traits. Large phenotypic variability was observed for the agronomic traits under study indicating suitability of the genotypes for association studies. The maximum values for plant height, pods per plant, seeds per pod, 100-seed weight and seed yield per plant were approximately two and half to three times more than the minimum values for the genotypes. Seed yield per plant was found to be significantly correlated with pods per plant ($r = 0.77$), 100-seed weight ($r = 0.35$) and days to maturity ($r = 0.23$). The population structure studies depicted the presence of seven subpopulations which nearly corresponded with the source of geographical origin of the genotypes. Linkage disequilibrium (LD) between the linked markers decreased with the increased distance, and a substantial drop in LD decay values was observed between 30 and 35 cM. Genomewide marker-traits association analysis carried out using general linear (GLM) and mixed linear models (MLM) identified six genomic regions (two of them were common in both) on chromosomes 6, 7, 8, 13, 15 and 17, which were found to be significantly associated with various important traits viz., plant height, pods per plant, 100-seed weight, plant growth habit, average number of seeds per pod, days to 50% flowering and days to maturity. The phenotypic variation explained by these loci ranged from 6.09 to 13.18% and 4.25 to 9.01% in the GLM and MLM studies, respectively. In conclusion, association mapping (AM) in soybean could be a viable alternative to conventional QTL mapping approach.

    • Skim sequencing: an advanced NGS technology for crop improvement


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      High-throughput genotyping has become more convenient and cost-effective due to recent advancements in next-generation sequencing (NGS) techniques. Numerous approaches exploring sequencing advances for genotyping have been developed over the past decade, which includes different variants of genotyping-by-sequencing (GBS), and restriction-site associated DNA sequencing (RAD-seq). Most of these methods are based on the reduced representation of the genome, which ultimately reduces the cost of sequencing by many folds. However, continuously lowering the cost of sequencing makes it more convenient to use whole genome-based approaches. In this regard, skim sequencing, where low coverage whole-genome sequencing is used for the identification of large numbers of polymorphic markers cost-effectively. In the present review, we have discussed recent technological advancements, applicability, and challenges of skim sequencing-based genotypic approaches for crop improvement programmes. Skim sequencing is being extensively used for genotyping indiverse plant species and has a wide range of applications, particularly in quantitative trait loci (QTL) mapping, genomewide association studies (GWAS), fine genetic map construction, and identification of recombination and gene conversion events in various breeding programmes. The cost-effectiveness, simplicity, and genomewide coverage will increase the application of skims sequencing-based genotyping. The article summarizes the protocol, uses, bioinformatics tools, its application, and future prospects of skim sequencing in crop improvement.

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