Genetic Diversity and Population Structure of F3:6 Nebraska Winter Wheat Genotypes Using Genotyping-By-Sequencing

The availability of information on the genetic diversity and population structure in wheat (Triticum aestivum L.) breeding lines will help wheat breeders to better use their genetic resources and manage genetic variation in their breeding program. The recent advances in sequencing technology provide the opportunity to identify tens or hundreds of thousands of single nucleotide polymorphism (SNPs) in large genome species (e.g., wheat). These SNPs can be utilized for understanding genetic diversity and performing genome wide association studies (GWAS) for complex traits. In this study, the genetic diversity and population structure were investigated in a set of 230 genotypes (F3:6) derived from various crosses as a prerequisite for GWAS and genomic selection. Genotyping-by-sequencing provided 25,566 high-quality SNPs. The polymorphism information content (PIC) across chromosomes ranged from 0.09 to 0.37 with an average of 0.23. The distribution of SNPs markers on the 21 chromosomes ranged from 319 on chromosome 3D to 2,370 on chromosome 3B. The analysis of population structure revealed three subpopulations (G1, G2, and G3). Analysis of molecular variance identified 8% variance among and 92% within subpopulations. Of the three subpopulations, G2 had the highest level of genetic diversity based on three genetic diversity indices: Shannon’s information index (I) = 0.494, diversity index (h) = 0.328 and unbiased diversity index (uh) = 0.331, while G3 had lowest level of genetic diversity (I = 0.348, h = 0.226 and uh = 0.236). This high genetic diversity identified among the subpopulations can be used to develop new wheat cultivars

Genome-Wide Association Study for Identification and Validation of Novel SNP Markers for \u3ci\u3eSr6\u3c/i\u3e Stem Rust Resistance Gene in Bread Wheat

Stem rust (caused by Puccinia graminis f. sp. tritici Erikss. & E. Henn.), is a major disease in wheat (Triticum aestivium L.). However, in recent years it occurs rarely in Nebraska due to weather and the effective selection and gene pyramiding of resistance genes. To understand the genetic basis of stem rust resistance in Nebraska winter wheat, we applied genome-wide association study (GWAS) on a set of 270 winter wheat genotypes (A-set). Genotyping was carried out using genotyping-by-sequencing and ~35,000 high-quality SNPs were identified. The tested genotypes were evaluated for their resistance to the common stem rust race in Nebraska (QFCSC) in two replications. Marker-trait association identified 32 SNP markers, which were significantly (Bonferroni corrected P \u3c 0.05) associated with the resistance on chromosome 2D. The chromosomal location of the significant SNPs (chromosome 2D) matched the location of Sr6 gene which was expected in these genotypes based on pedigree information. A highly significant linkage disequilibrium (LD, r2) was found between the significant SNPs and the specific SSR marker for the Sr6 gene (Xcfd43). This suggests the significant SNP markers are tagging Sr6 gene. Out of the 32 significant SNPs, eight SNPs were in six genes that are annotated as being linked to disease resistance in the IWGSC RefSeq v1.0. The 32 significant SNP markers were located in nine haplotype blocks. All the 32 significant SNPs were validated in a set of 60 different genotypes (V-set) using single marker analysis. SNP markers identified in this study can be used in marker-assisted selection, genomic selection, and to develop KASP (Kompetitive Allele Specific PCR) marker for the Sr6 gene

Genomic HIV RNA Induces Innate Immune Responses through RIG-I-Dependent Sensing of Secondary-Structured RNA

Contains fulltext : 108031.pdf (publisher's version ) (Open Access)BACKGROUND: Innate immune responses have recently been appreciated to play an important role in the pathogenesis of HIV infection. Whereas inadequate innate immune sensing of HIV during acute infection may contribute to failure to control and eradicate infection, persistent inflammatory responses later during infection contribute in driving chronic immune activation and development of immunodeficiency. However, knowledge on specific HIV PAMPs and cellular PRRs responsible for inducing innate immune responses remains sparse. METHODS/PRINCIPAL FINDINGS: Here we demonstrate a major role for RIG-I and the adaptor protein MAVS in induction of innate immune responses to HIV genomic RNA. We found that secondary structured HIV-derived RNAs induced a response similar to genomic RNA. In primary human peripheral blood mononuclear cells and primary human macrophages, HIV RNA induced expression of IFN-stimulated genes, whereas only low levels of type I IFN and tumor necrosis factor alpha were produced. Furthermore, secondary structured HIV-derived RNA activated pathways to NF-kappaB, MAP kinases, and IRF3 and co-localized with peroxisomes, suggesting a role for this organelle in RIG-I-mediated innate immune sensing of HIV RNA. CONCLUSIONS/SIGNIFICANCE: These results establish RIG-I as an innate immune sensor of cytosolic HIV genomic RNA with secondary structure, thereby expanding current knowledge on HIV molecules capable of stimulating the innate immune system

Genetic Diversity and Population Structure of F3:6 Nebraska Winter Wheat Genotypes Using Genotyping-By-Sequencing

The availability of information on the genetic diversity and population structure in wheat (Triticum aestivum L.) breeding lines will help wheat breeders to better use their genetic resources and manage genetic variation in their breeding program. The recent advances in sequencing technology provide the opportunity to identify tens or hundreds of thousands of single nucleotide polymorphism (SNPs) in large genome species (e.g., wheat). These SNPs can be utilized for understanding genetic diversity and performing genome wide association studies (GWAS) for complex traits. In this study, the genetic diversity and population structure were investigated in a set of 230 genotypes (F3:6) derived from various crosses as a prerequisite for GWAS and genomic selection. Genotyping-by-sequencing provided 25,566 high-quality SNPs. The polymorphism information content (PIC) across chromosomes ranged from 0.09 to 0.37 with an average of 0.23. The distribution of SNPs markers on the 21 chromosomes ranged from 319 on chromosome 3D to 2,370 on chromosome 3B. The analysis of population structure revealed three subpopulations (G1, G2, and G3). Analysis of molecular variance identified 8% variance among and 92% within subpopulations. Of the three subpopulations, G2 had the highest level of genetic diversity based on three genetic diversity indices: Shannon’s information index (I) = 0.494, diversity index (h) = 0.328 and unbiased diversity index (uh) = 0.331, while G3 had lowest level of genetic diversity (I = 0.348, h = 0.226 and uh = 0.236). This high genetic diversity identified among the subpopulations can be used to develop new wheat cultivars

Genome-Wide Association Study for Identification and Validation of Novel SNP Markers for \u3ci\u3eSr6\u3c/i\u3e Stem Rust Resistance Gene in Bread Wheat

Stem rust (caused by Puccinia graminis f. sp. tritici Erikss. & E. Henn.), is a major disease in wheat (Triticum aestivium L.). However, in recent years it occurs rarely in Nebraska due to weather and the effective selection and gene pyramiding of resistance genes. To understand the genetic basis of stem rust resistance in Nebraska winter wheat, we applied genome-wide association study (GWAS) on a set of 270 winter wheat genotypes (A-set). Genotyping was carried out using genotyping-by-sequencing and ~35,000 high-quality SNPs were identified. The tested genotypes were evaluated for their resistance to the common stem rust race in Nebraska (QFCSC) in two replications. Marker-trait association identified 32 SNP markers, which were significantly (Bonferroni corrected P \u3c 0.05) associated with the resistance on chromosome 2D. The chromosomal location of the significant SNPs (chromosome 2D) matched the location of Sr6 gene which was expected in these genotypes based on pedigree information. A highly significant linkage disequilibrium (LD, r2) was found between the significant SNPs and the specific SSR marker for the Sr6 gene (Xcfd43). This suggests the significant SNP markers are tagging Sr6 gene. Out of the 32 significant SNPs, eight SNPs were in six genes that are annotated as being linked to disease resistance in the IWGSC RefSeq v1.0. The 32 significant SNP markers were located in nine haplotype blocks. All the 32 significant SNPs were validated in a set of 60 different genotypes (V-set) using single marker analysis. SNP markers identified in this study can be used in marker-assisted selection, genomic selection, and to develop KASP (Kompetitive Allele Specific PCR) marker for the Sr6 gene

Genetic Diversity and Population Structure of F3:6 Nebraska Winter Wheat Genotypes Using Genotyping-By-Sequencing

The availability of information on the genetic diversity and population structure in wheat (Triticum aestivum L.) breeding lines will help wheat breeders to better use their genetic resources and manage genetic variation in their breeding program. The recent advances in sequencing technology provide the opportunity to identify tens or hundreds of thousands of single nucleotide polymorphism (SNPs) in large genome species (e.g., wheat). These SNPs can be utilized for understanding genetic diversity and performing genome wide association studies (GWAS) for complex traits. In this study, the genetic diversity and population structure were investigated in a set of 230 genotypes (F3:6) derived from various crosses as a prerequisite for GWAS and genomic selection. Genotyping-by-sequencing provided 25,566 high-quality SNPs. The polymorphism information content (PIC) across chromosomes ranged from 0.09 to 0.37 with an average of 0.23. The distribution of SNPs markers on the 21 chromosomes ranged from 319 on chromosome 3D to 2,370 on chromosome 3B. The analysis of population structure revealed three subpopulations (G1, G2, and G3). Analysis of molecular variance identified 8% variance among and 92% within subpopulations. Of the three subpopulations, G2 had the highest level of genetic diversity based on three genetic diversity indices: Shannon’s information index (I) = 0.494, diversity index (h) = 0.328 and unbiased diversity index (uh) = 0.331, while G3 had lowest level of genetic diversity (I = 0.348, h = 0.226 and uh = 0.236). This high genetic diversity identified among the subpopulations can be used to develop new wheat cultivars

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<p>The availability of information on the genetic diversity and population structure in wheat (Triticum aestivum L.) breeding lines will help wheat breeders to better use their genetic resources and manage genetic variation in their breeding program. The recent advances in sequencing technology provide the opportunity to identify tens or hundreds of thousands of single nucleotide polymorphism (SNPs) in large genome species (e.g., wheat). These SNPs can be utilized for understanding genetic diversity and performing genome wide association studies (GWAS) for complex traits. In this study, the genetic diversity and population structure were investigated in a set of 230 genotypes (F_3:6) derived from various crosses as a prerequisite for GWAS and genomic selection. Genotyping-by-sequencing provided 25,566 high-quality SNPs. The polymorphism information content (PIC) across chromosomes ranged from 0.09 to 0.37 with an average of 0.23. The distribution of SNPs markers on the 21 chromosomes ranged from 319 on chromosome 3D to 2,370 on chromosome 3B. The analysis of population structure revealed three subpopulations (G1, G2, and G3). Analysis of molecular variance identified 8% variance among and 92% within subpopulations. Of the three subpopulations, G2 had the highest level of genetic diversity based on three genetic diversity indices: Shannon’s information index (I) = 0.494, diversity index (h) = 0.328 and unbiased diversity index (uh) = 0.331, while G3 had lowest level of genetic diversity (I = 0.348, h = 0.226 and uh = 0.236). This high genetic diversity identified among the subpopulations can be used to develop new wheat cultivars.</p