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Phytochemical Analysis and In Vitro Assessment of Extracts of Rhodobryum roseum for Antioxidant, Antibacterial and Anti-Inflammatory Activities
Integrated multi‐omics analysis reveals drought stress response mechanism in chickpea (Cicer arietinum L.)
Abstract
Drought is one of the major constraints limiting chickpea productivity. To unravel complex mechanisms regulating drought response in chickpea, we generated transcriptomics, proteomics, and metabolomics datasets from root tissues of four contrasting drought-responsive chickpea genotypes: ICC 4958, JG 11, and JG 11+ (drought-tolerant), and ICC 1882 (drought-sensitive) under control and drought stress conditions. Integration of transcriptomics and proteomics data identified enriched hub proteins encoding isoflavone 4′-O-methyltransferase, UDP-d-glucose/UDP-d-galactose 4-epimerase, and delta-1-pyrroline-5-carboxylate synthetase. These proteins highlighted the involvement of pathways such as antibiotic biosynthesis, galactose metabolism, and isoflavonoid biosynthesis in activating drought stress response mechanisms. Subsequently, the integration of metabolomics data identified six metabolites (fructose, galactose, glucose, myoinositol, galactinol, and raffinose) that showed a significant correlation with galactose metabolism. Integration of root-omics data also revealed some key candidate genes underlying the drought-responsive “QTL-hotspot” region. These results provided key insights into complex molecular mechanisms underlying drought stress response in chickpea.
Spatial variation of soil characteristics affected by biochar materials from traditional slash and burn agriculture in Sabah, Malaysia
Grass sward cover improves soil organic carbon and nitrogen in a vineyard
Identification of stable restorer lines developed through inter‐sub‐specific hybridization in rice (Oryza sativa) using multi‐trait stability index
Abstract
Inter-sub-specific hybridization between indica and tropical japonica rice germplasm is the most efficient approach for broadening the genetic base of hybrid rice parental lines and enhancing the heterotic potential of hybrids in a tropical country like India. In the present study, 106 indica/tropical–japonica derived lines were developed through inter-sub-specific hybridization and screened using functional markers with respect to the major fertility restorer genes, Rf3 and Rf4, and the wide compatibility gene, S5n. The fertility restoration ability of newly developed restorers was validated through test cross nursery performance. The functional markers were observed to accurately predict the trait of fertility restoration. From the present study, the decreasing order of efficiency of different gene combinations on fertility restoration ability are as follows: Rf4/S5n > Rf4/Rf3/S5n > Rf4 > Rf4/Rf3 > Rf3/S5n > Rf3. Based on multi-trait stability index (MTSI) analysis, the four newly identified restorers, that is, RP6388-90, RP6382-49, RP6375-81 and RP6368-38, were selected as the top best performing genotypes with high stability for multiple traits, and these genotypes will be useful for the development of superior rice hybrids in India.
Genetic control of grain amino acid composition in a UK soft wheat mapping population
Abstract
Wheat (Triticum aestivum L.) is a major source of nutrients for populations across the globe, but the amino acid composition of wheat grain does not provide optimal nutrition. The nutritional value of wheat grain is limited by low concentrations of lysine (the most limiting essential amino acid) and high concentrations of free asparagine (precursor to the processing contaminant acrylamide). There are currently few available solutions for asparagine reduction and lysine biofortification through breeding. In this study, we investigated the genetic architecture controlling grain free amino acid composition and its relationship to other traits in a Robigus × Claire doubled haploid population. Multivariate analysis of amino acids and other traits showed that the two groups are largely independent of one another, with the largest effect on amino acids being from the environment. Linkage analysis of the population allowed identification of quantitative trait loci (QTL) controlling free amino acids and other traits, and this was compared against genomic prediction methods. Following identification of a QTL controlling free lysine content, wheat pangenome resources facilitated analysis of candidate genes in this region of the genome. These findings can be used to select appropriate strategies for lysine biofortification and free asparagine reduction in wheat breeding programs.
Whole genome resequencing and phenotyping of MAGIC population for high resolution mapping of drought tolerance in chickpea
Abstract
Terminal drought is one of the major constraints to crop production in chickpea (Cicer arietinum L.). In order to map drought tolerance related traits at high resolution, we sequenced multi-parent advanced generation intercross (MAGIC) population using whole genome resequencing approach and phenotyped it under drought stress environments for two consecutive years (2013–14 and 2014–15). A total of 52.02 billion clean reads containing 4.67 TB clean data were generated on the 1136 MAGIC lines and eight parental lines. Alignment of clean data on to the reference genome enabled identification of a total, 932,172 of SNPs, 35,973 insertions, and 35,726 deletions among the parental lines. A high-density genetic map was constructed using 57,180 SNPs spanning a map distance of 1606.69 cM. Using compressed mixed linear model, genome-wide association study (GWAS) enabled us to identify 737 markers significantly associated with days to 50% flowering, days to maturity, plant height, 100 seed weight, biomass, and harvest index. In addition to the GWAS approach, an identity-by-descent (IBD)-based mixed model approach was used to map quantitative trait loci (QTLs). The IBD-based mixed model approach detected major QTLs that were comparable to those from the GWAS analysis as well as some exclusive QTLs with smaller effects. The candidate genes like FRIGIDA and CaTIFY4b can be used for enhancing drought tolerance in chickpea. The genomic resources, genetic map, marker-trait associations, and QTLs identified in the study are valuable resources for the chickpea community for developing climate resilient chickpeas.
Evaluation of eight Bayesian genomic prediction models for three micronutrient traits in bread wheat (Triticum aestivum L.)
Abstract
In wheat, genomic prediction accuracy (GPA) was assessed for three micronutrient traits (grain iron, grain zinc, and β-carotenoid concentrations) using eight Bayesian regression models. For this purpose, data on 246 accessions, each genotyped with 17,937 DArT markers, were utilized. The phenotypic data on traits were available for 2013–2014 from Powerkheda (Madhya Pradesh) and for 2014–2015 from Meerut (Uttar Pradesh), India. The accuracy of the models was measured in terms of reliability, which was computed following a repeated cross-validation approach. The predictions were obtained independently for each of the two environments after adjusting for the local effects and across environments after adjusting for the environmental effects. The Bayes ridge regression (BayesRR) model outperformed the other seven models, whereas BayesLASSO (BayesL) was the least efficient. The GPA increased with an increase in the size of the training set as well as with an increase in marker density. The GPA values differed for the three traits and were higher for the best linear unbiased estimate (BLUE) (obtained after adjusting for the environmental effects) relative to those for the two environments. The GPA also remained unaffected after accounting for the population structure. The results of the present study suggest that only the best model should be used for the estimations of genomic estimated breeding values (GEBVs) before their use for genomic selection to improve the grain micronutrient contents.