Person:
Semagn, K.

Loading...
Profile Picture
Email Address
Birth Date
Research Projects
Organizational Units
Job Title
Last Name
Semagn
First Name
K.
Name
Semagn, K.

Search Results

Now showing 1 - 10 of 28
  • Identification of disease resistance parents and genome-wide association mapping of resistance in spring wheat
    (MDPI, 2022) Iqbal, M.; Semagn, K.; Jarquin, D.; Randhawa, H.S.; McCallum, B.D.; Howard, R.; Aboukhaddour, R.; Ciechanowska, I.; Strenzke, K.; Crossa, J.; Cerón-Rojas, J.J.; N’Diaye, A.; Pozniak, C.; Spaner, D.
    Publication
  • Identification of spring wheat with superior agronomic performance under contrasting nitrogen managements using linear phenotypic selection indices
    (MDPI, 2022) Iqbal, M.; Semagn, K.; Cerón-Rojas, J.J.; Crossa, J.; Jarquin, D.; Howard, R.; Beres, B.L.; Strenzke, K.; Ciechanowska, I.; Spaner, D.
    Publication
  • Genomic predictions for common bunt, FHB, stripe rust, leaf rust, and leaf spotting resistance in spring wheat
    (MDPI, 2022) Semagn, K.; Iqbal, M.; Jarquin, D.; Crossa, J.; Howard, R.; Ciechanowska, I.; Henríquez, M.A.; Randhawa, H.S.; Aboukhaddour, R.; McCallum, B.D.; Brûlé-Babel, A.L.; Navabi, A.; N’Diaye, A.; Pozniak, C.; Spaner, D.
    Publication
  • Genetic gains in grain yield through genomic selection in eight bi-parental maize populations under drought stress
    (CSSA, 2015) Beyene, Y.; Semagn, K.; Mugo, S.N.; Tarekegne, A.T.; Babu, R.; Meisel, B.; Sehabiague, P.; Makumbi, D.; Magorokosho, C.; Oikeh, S.O.; Gakunga, J.; Vargas Hernández, M.; Olsen, M.; Prasanna, B.M.; Banziger, M.; Crossa, J.
    Publication
  • Molecular diversity and selective sweeps in maize inbred lines adapted to African highlands
    (Nature Publishing Group, 2019) Dagne Wegary Gissa; Chere, A.T.; Prasanna, B.M.; Tadesse, B.; Alachiotis, N.; Negera, D.; Awas, G.; Abakemal, D.; Ogugo, V.; Gowda, M.; Semagn, K.
    Little is known on maize germplasm adapted to the African highland agro-ecologies. In this study, we analyzed high-density genotyping by sequencing (GBS) data of 298 African highland adapted maize inbred lines to (i) assess the extent of genetic purity, genetic relatedness, and population structure, and (ii) identify genomic regions that have undergone selection (selective sweeps) in response to adaptation to highland environments. Nearly 91% of the pairs of inbred lines differed by 30–36% of the scored alleles, but only 32% of the pairs of the inbred lines had relative kinship coefficient <0.050, which suggests the presence of substantial redundancy in allelic composition that may be due to repeated use of fewer genetic backgrounds (source germplasm) during line development. Results from different genetic relatedness and population structure analyses revealed three different groups, which generally agrees with pedigree information and breeding history, but less so by heterotic groups and endosperm modification. We identified 944 single nucleotide polymorphic (SNP) markers that fell within 22 selective sweeps that harbored 265 protein-coding candidate genes of which some of the candidate genes had known functions. Details of the candidate genes with known functions and differences in nucleotide diversity among groups predicted based on multivariate methods have been discussed.
    Publication
  • Discovery, Validation and Deployment of Major QTL for Resistance to Maize Lethal Necrosis
    (CIMMYT, 2018) Olsen, M.; Gowda, M.; Tadesse, B.; Murithi, A.; Semagn, K.; Nganga, M.; Ogugo, V.; Dhugga, K.
    Publication
  • Discovery and validation of genomic regions associated with resistance to maize lethal necrosis in four biparental populations
    (Springer Verlag, 2018) Gowda, M.; Beyene, Y.; Makumbi, D.; Semagn, K.; Olsen, M.; Jumbo, M.B; Das, B.; Mugo, S.N.; Suresh, L.M.; Prasanna, B.M.
    In sub-Saharan Africa, maize is the key determinant of food security for smallholder farmers. The sudden outbreak of maize lethal necrosis (MLN) disease is seriously threatening the maize production in the region. Understanding the genetic basis of MLN resistance is crucial. In this study, we used four biparental populations applied linkage mapping and joint linkage mapping approaches to identify and validate the MLN resistance-associated genomic regions. All populations were genotyped with low to high density markers and phenotyped in multiple environments against MLN under artificial inoculation. Phenotypic variation for MLN resistance was significant and heritability was moderate to high in all four populations for both early and late stages of disease infection. Linkage mapping revealed three major quantitative trait loci (QTL) on chromosomes 3, 6, and 9 that were consistently detected in at least two of the four populations. Phenotypic variance explained by a single QTL in each population ranged from 3.9% in population 1 to 43.8% in population 2. Joint linkage association mapping across three populations with three biometric models together revealed 16 and 10 main effect QTL for MLN-early and MLN-late, respectively. The QTL identified on chromosomes 3, 5, 6, and 9 were consistent with the QTL identified by linkage mapping. Ridge regression best linear unbiased prediction with five-fold cross-validation revealed high accuracy for prediction across populations for both MLN-early and MLN-late. Overall, the study discovered and validated the presence of major effect QTL on chromosomes 3, 6, and 9 which can be potential candidates for marker-assisted breeding to improve the MLN resistance.
    Publication
  • High-resolution genetic mapping of maize pan-genome sequence anchors
    (Nature Research, 2015) Fei Lu; Romay, M.C.; Glaubitz, J.C.; Bradbury, P.; Elshire, R.; Wang, T.; Yu Li; Yongxiang Li; Semagn, K.; Xuecai Zhang; Hernandez, A.; Mikel, M.A.; Soifer, I.; Barad, O.; Buckler, E.
    In addition to single-nucleotide polymorphisms, structural variation is abundant in many plant genomes. The structural variation across a species can be represented by a ‘pan-genome’, which is essential to fully understand the genetic control of phenotypes. However, the pan-genome’s complexity hinders its accurate assembly via sequence alignment. Here we demonstrate an approach to facilitate pan-genome construction in maize. By performing 18 trillion association tests we map 26 million tags generated by reduced representation sequencing of 14,129 maize inbred lines. Using machine-learning models we select 4.4 million accurately mapped tags as sequence anchors, 1.1 million of which are presence/absence variations. Structural variations exhibit enriched association with phenotypic traits, indicating that it is a significant source of adaptive variation in maize. The ability to efficiently map ultrahigh-density pan-genome sequence anchors enables fine characterization of structural variation and will advance both genetic research and breeding in many crops.
    Publication
  • Genome‑wide association and genomic prediction of resistance to maize lethal necrosis disease in tropical maize germplasm
    (Springer, 2015) Gowda, M.; Das, B.; Makumbi, D.; Babu, R.; Semagn, K.; Mahuku, G.; Olsen, M.; Jumbo, M.B; Beyene, Y.; Prasanna, B.M.
    The maize lethal necrosis disease (MLND) caused by synergistic interaction of Maize chlorotic mottle virus and Sugarcane mosaic virus, and has emerged as a serious threat to maize production in eastern Africa since 2011. Our objective was to gain insights into the genetic architecture underlying the resistance to MLND by genome-wide association study (GWAS) and genomic selection. We used two association mapping (AM) panels comprising a total of 615 diverse tropical/subtropical maize inbred lines. All the lines were evaluated against MLND under artificial inoculation. Both the panels were genotyped using genotyping-by-sequencing. Phenotypic variation for MLND resistance was significant and heritability was moderately high in both the panels. Few promising lines with high resistance to MLND were identified to be used as potential donors. GWAS revealed 24 SNPs that were significantly associated (P < 3 × 10−5) with MLND resistance. These SNPs are located within or adjacent to 20 putative candidate genes that are associated with plant disease resistance. Ridge regression best linear unbiased prediction with five-fold cross-validation revealed higher prediction accuracy for IMAS-AM panel (0.56) over DTMA-AM (0.36) panel. The prediction accuracy for both within and across panels is promising; inclusion of MLND resistance associated SNPs into the prediction model further improved the accuracy. Overall, the study revealed that resistance to MLND is controlled by multiple loci with small to medium effects and the SNPs identified by GWAS can be used as potential candidates in MLND resistance breeding program.
    Publication
  • Genetic diversity among selected elite CIMMYT maize hybrids in East and Southern Africa
    (Crop Science Society of America, 2017) Masuka, B.; Biljon, A.; Cairns, J.E.; Das, B.; Labuschagne, M.; MacRobert, J.; Makumbi, D.; Magorokosho, C.; Zaman-Allah, M.; Ogugo, V.; Olsen, M.; Prasanna, B.M.; Tarekegne, A.T.; Semagn, K.
    Genetic gain within the CIMMYT Eastern and Southern Africa (ESA) hybrid maize (Zea mays L.) breeding program from 2000 to 2010 was recently estimated at 0.85 to 2.2% yr−1 under various environmental conditions. Over 100 varieties were disseminated from CIMMYT to farmers in ESA, hence the need to check genetic diversity and frequency of use of parents to avoid potential narrowing down of the genetic base. Fifty-five parents from CIMMYT ESA used in the hybrids were fingerprinted using genotyping-by-sequencing. Data analysis in TASSEL and MEGA6 generated pairwise genetic distances between parents of 0.004 to 0.4005. Unweighted pair group method with arithmetic mean (UPGMA) analysis produced two clusters (I and II) with two subclusters each (A and B) and two sub-subclusters (IAi and IAii). Principal coordinate analysis produced three clusters where IAi and IIA from the UPGMA analysis formed independent clusters while IAii, IB, and IIB clustered together. Lines were separated by pedigree and origin. Ninety-five percent frequency of pairwise genetic distances ranged between 0.2001 and 0.4000. However, only four of the 55 parents (CML444, CML395, CML312, and CML442) were each used in 15 to 30 of the 52 hybrids evaluated in the genetic gain study. The remaining 51 were used in one to four hybrids. Frequent use of the four parents gave 29 to 58% of the hybrids a narrow genetic base, posing risk in case of pest or disease outbreaks. Parents evaluated do not represent the genetic base of CIMMYT ESA but parents of the best-performing hybrids selected from 2000 to 2010. Breeders should ensure a wide genetic base for released varieties to avoid breakdown in case of pest or disease outbreaks.
    Publication