Association Mapping of Candidate Genes Associated with Iron and Zinc Content in Rice (Oryza sativa L.) Grains.

Micronutrient deficiencies, particularly of iron (Fe) and zinc (Zn), in the diet contribute to health issues and hidden hunger. Enhancing the Fe and Zn content in globally staple food crops like rice is necessary to address food malnutrition. A Genome-Wide Association Study (GWAS) was conducted using 85 diverse rice accessions from the Democratic Republic of Congo (DRC) to identify genomic regions associated with grain Fe and Zn content. The Fe content ranged from 0.95 to 8.68 mg/100 g on a dry weight basis (dwb) while Zn content ranged from 0.87 to 3.8 mg/100 g (dwb). Using MLM and FarmCPU models, we found 10 significant SNPs out of which one SNP on chromosome 11 was associated with the variation in Fe content and one SNP on chromosome 4 was associated with the Zn content, and both were commonly detected by the two models. Candidate genes belonging to transcription regulator activities, including the bZIP family genes and MYB family genes, as well as transporter activities involved in Fe and Zn homeostasis were identified in the vicinity of the SNP markers and selected. The identified SNP markers hold promise for marker-assisted selection in rice breeding programs aimed at enhancing Fe and Zn content in rice. This study provides valuable insights into the genetic factors controlling Fe and Zn uptake and their transport and accumulation in rice, offering opportunities for developing biofortified rice varieties to combat malnutrition among rice consumers.

Genetic Diversity and Population Structure of Sorghum (Sorghum bicolor (L.) Moench) Landraces Using DArTseq-Derived Single-Nucleotide Polymorphism (SNP) Markers.

Genetic integrity of an accession should be preserved in the conservation of germplasm. Characterization of diverse germplasm based on a molecular basis enhances its conservation and use in breeding programs. The aim of this study was to assess the genetic diversity of 169 sorghum accessions using a total of 6977 SNP markers. The polymorphic information content of the markers was 0.31 which is considered to be moderately high. Structure analysis using ADMIXTURE program revealed a total of 10 subpopulations. Neighbor-joining tree revealed the presence of six main clusters among these subpopulations whereas in principal component analysis, seven clusters were identified. Cluster analysis grouped most populations depending on source of collection although other accessions originating from the same source were grouped under different clusters. Analysis of molecular variance (AMOVA) revealed 30% and 70% of the variation occurred within and among accessions, respectively. Gene flow within the populations was, however, limited indicating high differentiation within the subpopulation. Observed heterozygosity among accessions varied from 0.03 to 0.06 with a mean of 0.05 since sorghum is a self-pollinating crop. High genetic diversity among the subpopulations can be further explored for superior genes to develop new sorghum varieties.

Genome-wide association study reveals that different pathways contribute to grain quality variation in sorghum (Sorghum bicolor).

BACKGROUND: In sorghum (Sorghum bicolor), one paramount breeding objective is to increase grain quality. The nutritional quality and end use value of sorghum grains are primarily influenced by the proportions of tannins, starch and proteins, but the genetic basis of these grain quality traits remains largely unknown. This study aimed to dissect the natural variation of sorghum grain quality traits and identify the underpinning genetic loci by genome-wide association study. RESULTS: Levels of starch, tannins and 17 amino acids were quantified in 196 diverse sorghum inbred lines, and 44 traits based on known metabolic pathways and biochemical interactions amongst the 17 amino acids calculated. A Genome-wide association study (GWAS) with 3,512,517 SNPs from re-sequencing data identified 14, 15 and 711 significant SNPs which represented 14, 14, 492 genetic loci associated with levels of tannins, starch and amino acids in sorghum grains, respectively. Amongst these significant SNPs, two SNPs were associated with tannin content on chromosome 4 and colocalized with three previously identified loci for Tannin1, and orthologs of Zm1 and TT16 genes. One SNP associated with starch content colocalized with sucrose phosphate synthase gene. Furthermore, homologues of opaque1 and opaque2 genes associated with amino acid content were identified. Using the KEGG pathway database, six and three candidate genes of tannins and starch were mapped into 12 and 3 metabolism pathways, respectively. Thirty-four candidate genes were mapped into 16 biosynthetic and catabolic pathways of amino acids. We finally reconstructed the biosynthetic pathways for aspartate and branched-chain amino acids based on 15 candidate genes identified in this study. CONCLUSION: Promising candidate genes associated with grain quality traits have been identified in the present study. Some of them colocalized with previously identified genetic regions, but novel candidate genes involved in various metabolic pathways which influence grain quality traits have been dissected. Our study acts as an entry point for further validation studies to elucidate the complex mechanisms controlling grain quality traits such as tannins, starch and amino acids in sorghum.

Molecular Characterizations of Kenyan Brachiaria Grass Ecotypes with Microsatellite (SSR) Markers.

Brachiaria grass is an emerging forage option for livestock production in Kenya. Kenya lies within the center of diversity for Brachiaria species, thus a high genetic variation in natural populations of Brachiaria is expected. Overgrazing and clearing of natural vegetation for crop production and nonagricultural uses and climate change continue to threaten the natural biodiversity. In this study, we collected 79 Brachiaria ecotypes from different parts of Kenya and examined them for genetic variations and their relatedness with 8 commercial varieties. A total of 120 different alleles were detected by 22 markers in the 79 ecotypes. Markers were highly informative in differentiating ecotypes with average diversity and polymorphic information content of 0.623 and 0.583, respectively. Five subpopulations: International Livestock Research Institute (ILRI), Kitui, Kisii, Alupe, and Kiminini differed in sample size, number of alleles, number of private alleles, diversity index, and percentage polymorphic loci. The contribution of within-the-individual difference to total genetic variation of Kenyan ecotype population was 81%, and the fixation index (F ST = 0.021) and number of migrant per generation (Nm = 11.58) showed low genetic differentiation among the populations. The genetic distance was highest between Alupe and Kisii populations (0.510) and the lowest between ILRI and Kiminini populations (0.307). The unweighted neighbor-joining (NJ) tree showed test ecotypes grouped into three major clusters: ILRI ecotypes were present in all clusters; Kisii and Alupe ecotypes and improved varieties grouped in clusters I and II; and ecotypes from Kitui and Kiminini grouped in cluster I. This study confirms higher genetic diversity in Kenyan ecotypes than eight commercial varieties (Basilisk, Humidicola, Llanero, Marandú, MG4, Mulato II, Piatá and Xaraés) that represent three species and one three-way cross-hybrid Mulato II. There is a need for further collection of local ecotypes and their morphological, agronomical, and genetic characterizations to support Brachiaria grass breeding and conservation programs.