Kassa Semagn

Bio: Kassa Semagn is an academic researcher from University of Alberta. The author has contributed to research in topics: Population & Quantitative trait locus. The author has an hindex of 34, co-authored 76 publications receiving 4230 citations. Previous affiliations of Kassa Semagn include International Maize and Wheat Improvement Center & Norwegian University of Life Sciences.

Single nucleotide polymorphism genotyping using Kompetitive Allele Specific PCR (KASP): overview of the technology and its application in crop improvement

Abstract: Single nucleotide polymorphism (SNP) data can be obtained using one of the numerous uniplex or multiplex SNP genotyping platforms that combine a variety of chemistries, detection methods, and reaction formats. Kompetitive Allele Specific PCR (KASP) is one of the uniplex SNP genotyping platforms, and has evolved to be a global benchmark technology. However, there are no publications relating either to the technology itself or to its application in crop improvement programs. In this review, we provide an overview of the different aspects of the KASP genotyping platform, discuss its application in crop improvement, and compare it with the chip-based Illumina GoldenGate platform. The International Maize and Wheat Improvement Center routinely uses KASP, generating in excess of a million data points annually for crop improvement purposes. We found that (1) 81 % of the SNPs used in a custom-designed GoldenGate assay were transferable to KASP; (2) using KASP, negative controls (no template) consistently clustered together and rarely produced signals exceeding the threshold values for allele calling, in contrast to the situation observed using GoldenGate assays; (3) KASP’s average genotyping error in positive control DNA samples was 0.7–1.6 %, which is lower than that observed using GoldenGate (2.0–2.4 %); (4) KASP genotyping costs for marker-assisted recurrent selection were 7.9–46.1 % cheaper than those of the BeadXpress and GoldenGate platforms; and (5) KASP offers cost-effective and scalable flexibility in applications that require small to moderate numbers of markers, such as quality control analysis, quantitative trait loci (QTL) mapping in bi-parental populations, marker-assisted recurrent selection, marker-assisted backcrossing, and QTL fine mapping.

An overview of molecular marker methods for plants

Abstract: The development and use of molecular markers for the detection and exploitation of DNA polymorphism is one of the most significant developments in the field of molecular genetics. The presence of various types of molecular markers, and differences in their principles, methodologies, and applications require careful consideration in choosing one or more of such methods. No molecular markers are available yet that fulfill all requirements needed by researchers. According to the kind of study to be undertaken, one can choose among the variety of molecular techniques, each of which combines at least some desirable properties. This article provides detail review for 11 different molecular marker methods: restriction fragment length polymorphism (RFLP), random amplified polymorphic DNA (RAPD), amplified fragment length polymorphism (AFLP), inter-simple sequence repeats (ISSRs), sequence characterized regions (SCARs), sequence tag sites (STSs), cleaved amplified polymorphic sequences (CAPS), microsatellites or simple sequence repeats (SSRs), expressed sequence tags (ESTs), single nucleotide polymorphisms (SNPs), and diversity arrays technology (DArT).

Effectiveness of Genomic Prediction of Maize Hybrid Performance in Different Breeding Populations and Environments

Abstract: Genomic prediction is expected to considerably increase genetic gains by increasing selection intensity and accelerating the breeding cycle. In this study, marker effects estimated in 255 diverse maize (Zea mays L.) hybrids were used to predict grain yield, anthesis date, and anthesis-silking interval within the diversity panel and testcross progenies of 30 F2-derived lines from each of five populations. Although up to 25% of the genetic variance could be explained by cross validation within the diversity panel, the prediction of testcross performance of F2-derived lines using marker effects estimated in the diversity panel was on average zero. Hybrids in the diversity panel could be grouped into eight breeding populations differing in mean performance. When performance was predicted separately for each breeding population on the basis of marker effects estimated in the other populations, predictive ability was low (i.e., 0.12 for grain yield). These results suggest that prediction resulted mostly from differences in mean performance of the breeding populations and less from the relationship between the training and validation sets or linkage disequilibrium with causal variants underlying the predicted traits. Potential uses for genomic prediction in maize hybrid breeding are discussed emphasizing the need of (1) a clear definition of the breeding scenario in which genomic prediction should be applied (i.e., prediction among or within populations), (2) a detailed analysis of the population structure before performing cross validation, and (3) larger training sets with strong genetic relationship to the validation set.

Genetic Gains in Grain Yield Through Genomic Selection in Eight Bi-parental Maize Populations under Drought Stress

Abstract: Genomic selection incorporates all the available marker information into a model to predict genetic values of breeding progenies for selection. The objective of this study was to estimate genetic gains in grain yield from genomic selection (GS) in eight bi-parental maize populations under managed drought stress environments. In each population, 148 to 300 F₂:₃ (C₀) progenies were derived and crossed to a single-cross tester from a complementary heterotic group. The resulting testcrosses of each population were evaluated under two to four managed drought stress and three to four well-watered conditions in different locations and genotyped with 191 to 286 single nucleotide polymorphism (SNP) markers. The top 10% families were selected from C₀ using a phenotypic selection index and were intermated to form C₁. Selections both at C₁ and C₂ were based on genomic estimated breeding values (GEBVs). The best lines from C₀ were also advanced using a pedigree selection scheme. For genetic gain studies, a total of 55 entries representing the eight populations were crossed to a single-cross tester, and evaluated in four managed drought stress environments. Each population was represented by bulk seed containing equal amounts of seed of C₀, C₁, C₂, C₃, parents, F₁s, and lines developed via pedigree selection. Five commercial checks were included for comparison. The average gain from genomic selection per cycle across eight populations was 0.086 Mg ha–¹. The average grain yield of C₃–derived hybrids was significantly higher than that of hybrids derived from C₀. Hybrids derived from C₃ produced 7.3% (0.176 Mg ha–¹) higher grain yield than those developed through the conventional pedigree breeding method. The study demonstrated that genomic selection is more effective than pedigree-based conventional phenotypic selection for increasing genetic gains in grain yield under drought stress in tropical maize.

Distribution of DArT, AFLP, and SSR markers in a genetic linkage map of a doubled-haploid hexaploid wheat population.

Abstract: A genetic linkage mapping study was conducted in 93 doubled-haploid lines derived from a cross between Triticum aestivum L. em. Thell 'Arina' and a Norwegian spring wheat breeding line, NK93604, using diversity arrays technology (DArT), amplified fragment length polymorphism (AFLP), and simple sequence repeat (SSR) markers. The objective of this study was to understand the distribution, redundancy, and segregation distortion of DArT markers in comparison with AFLP and SSR markers. The map contains a total of 624 markers with 189 DArTs, 165 AFLPs and 270 SSRs, and spans 2595.5 cM. All 3 marker types showed significant (p 0.98) and multicollinearity among the clustered markers. The present study is the first to compare the utility of DArT with AFLP and SSR markers, and the present map has been successfully used to identify novel QTLs for resistance to Fusarium head blight and powdery mildew and for anther extrusion, leaf segment incubation, and latency.

Human biochemical genetics

Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to

Genetical genomics : the added value from segregation

Abstract: The recent successes of genome-wide expression profiling in biology tend to overlook the power of genetics. We here propose a merger of genomics and genetics into ‘genetical genomics’. This involves expression profiling and marker-based fingerprinting of each individual of a segregating population, and exploits all the statistical tools used in the analysis of quantitative trait loci. Genetical genomics will combine the power of two different worlds in a way that is likely to become instrumental in the further unravelling of metabolic, regulatory and developmental pathways.