B. R. Bakheit

Triple test cross and six-population techniques for partitioning the components of genetic variance in faba bean ( Vicia faba )

The efficiency of the triple test cross (TTC) and the six-population biometrical analyses was compared in terms of assessing and quantifying the components of genetic variance for two faba bean crosses: Triple White×Giza 843 and NA112×Giza 429. Several traits were studied including days to first flower, plant height, branches/plant, pods/plant, seeds/pod, 100-seed weight and seed yield/plant. The results supported the triple test cross biometrical approach as it uses first degree statistics and can be applied to any population irrespective of its genetic architecture. Absence of a scalar relationship between triple test cross families (orthogonality) ensures independence between means and variance with no restrictive assumptions. Both methods provided evidence for epistasis, and both additive and dominance genetic components in the genetic control of the studied traits.

Triple test cross analysis in four sesame crosses (Sesamum indicum L.)

The present study was carried out during 1996, 1997 and 1998 to estimate the additive, dominance and epistatic components of genetic variation for yield, yield components and wilt infection by using 90 triple test cross families and their parents, F 1 and F 2 in each of four sesame crosses, i.e. Bengalian x Giza 32 (TTC 1 ), Intro 259 × Giza 25 (TTC 2 ), Intro 413 x Intro 777 (TTC 3 ) and Shandaweel 5 x Line 107 (TTC 4 ). Mean squares from the genetic analysis of variance and the overall epistatic gene effects were highly significant differences for all studied characters. The [i] type (additive x additive) was the most important epistatic effect for height of the first capsule (TTC 4 ), number of branches/plant (TTC 1 and TTC 3 ), length of the fruiting zone (TTC 1 , TTC 2 and TTC 3 ), days to the first flower and number of capsules/plant (TTC 1 , TTC 2 and TTC 4 ), 1000-seed (TTC 3 ), wilt infection percentage (TTC 3 and TTC 4 ) and plant height, capsule length and seed yield/plant in all crosses. The ratio of (H/D) 1/2 confirmed the presence of partial dominance for all studied traits. The highest proportion of recombinant lines was obtained for days to the first flower, number of branches/plant, height of the first capsule and seed yield/plant in TTC 3 and plant height, capsule length, length of the fruiting zone number of capsules/plant, 1000-seed weight and oil percentage in TTC 2 .

Genome-Wide Association Study for Identification and Validation of Novel SNP Markers for Sr6 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 < 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. Highlights Novel SNPs for Sr6 gene, an important stem rust resistant gene, were identified and validated in this study. These SNPs can be used to improve stem rust resistance in wheat.