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      Mapping Quantitative Trait Loci for Resistance to Fall Armyworm (Lepidoptera: Noctuidae) Leaf-Feeding Damage in Maize Inbred Mp705

      1 , 1 , 1 , 1 , 2
      Journal of Economic Entomology
      Oxford University Press (OUP)

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          Abstract

          The fall armyworm, Spodoptera frugiperda (J. E. Smith), is an agronomically important pest that severely limits maize (Zea mays (Linnaeus) [Poales: Poaceae]) production. This migrant insect devastates maize plants in many countries threatening the livelihood of millions. Quantitative trait loci (QTL) were mapped to identify chromosomal regions that control resistance to fall armyworm leaf-feeding and to identify molecular markers linked to the target loci for use in marker-assisted selection (MAS). A bi-parental mapping population, comprising 243 F2:3 families from the cross Mp705 (resistant) × Mp719 (susceptible), was evaluated for fall armyworm leaf-feeding damage under artificial infestation over 3 yr. A linkage map comprised of 1,276 single-nucleotide polymorphism and simple sequence repeat molecular markers was constructed. Quantitative trait loci analyses identified two major QTL in bins 4.06 and 9.03 that when combined, explained 35.7% of the phenotypic variance over all environments. Mp705 was responsible for the leaf-feeding damage reducing alleles for both large effect QTL and most of the small effect QTL identified in this study. The QTL identified in bin 9.03 co-locates with a previously identified QTL that controls resistance to leaf-feeding damage in maize by fall armyworm and other lepidopteran insects. The QTL in bin 4.06 is a new source of resistance identified in this study. Beneficial alleles derived from Mp705 for the application of an integrated QTL-MAS approach could accelerate breeding efforts to minimize fall armyworm leaf-feeding in maize.

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          Precision mapping of quantitative trait loci.

          Adequate separation of effects of possible multiple linked quantitative trait loci (QTLs) on mapping QTLs is the key to increasing the precision of QTL mapping. A new method of QTL mapping is proposed and analyzed in this paper by combining interval mapping with multiple regression. The basis of the proposed method is an interval test in which the test statistic on a marker interval is made to be unaffected by QTLs located outside a defined interval. This is achieved by fitting other genetic markers in the statistical model as a control when performing interval mapping. Compared with the current QTL mapping method (i.e., the interval mapping method which uses a pair or two pairs of markers for mapping QTLs), this method has several advantages. (1) By confining the test to one region at a time, it reduces a multiple dimensional search problem (for multiple QTLs) to a one dimensional search problem. (2) By conditioning linked markers in the test, the sensitivity of the test statistic to the position of individual QTLs is increased, and the precision of QTL mapping can be improved. (3) By selectively and simultaneously using other markers in the analysis, the efficiency of QTL mapping can be also improved. The behavior of the test statistic under the null hypothesis and appropriate critical value of the test statistic for an overall test in a genome are discussed and analyzed. A simulation study of QTL mapping is also presented which illustrates the utility, properties, advantages and disadvantages of the method.
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            First Report of Outbreaks of the Fall Armyworm Spodoptera frugiperda (J E Smith) (Lepidoptera, Noctuidae), a New Alien Invasive Pest in West and Central Africa

            The fall armyworm Spodoptera frugiperda is a prime noctuid pest of maize on the American continents where it has remained confined despite occasional interceptions by European quarantine services in recent years. The pest has currently become a new invasive species in West and Central Africa where outbreaks were recorded for the first time in early 2016. The presence of at least two distinct haplotypes within samples collected on maize in Nigeria and São Tomé suggests multiple introductions into the African continent. Implications of this new threat to the maize crop in tropical Africa are briefly discussed.
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              A Large Maize (Zea mays L.) SNP Genotyping Array: Development and Germplasm Genotyping, and Genetic Mapping to Compare with the B73 Reference Genome

              SNP genotyping arrays have been useful for many applications that require a large number of molecular markers such as high-density genetic mapping, genome-wide association studies (GWAS), and genomic selection. We report the establishment of a large maize SNP array and its use for diversity analysis and high density linkage mapping. The markers, taken from more than 800,000 SNPs, were selected to be preferentially located in genes and evenly distributed across the genome. The array was tested with a set of maize germplasm including North American and European inbred lines, parent/F1 combinations, and distantly related teosinte material. A total of 49,585 markers, including 33,417 within 17,520 different genes and 16,168 outside genes, were of good quality for genotyping, with an average failure rate of 4% and rates up to 8% in specific germplasm. To demonstrate this array's use in genetic mapping and for the independent validation of the B73 sequence assembly, two intermated maize recombinant inbred line populations – IBM (B73×Mo17) and LHRF (F2×F252) – were genotyped to establish two high density linkage maps with 20,913 and 14,524 markers respectively. 172 mapped markers were absent in the current B73 assembly and their placement can be used for future improvements of the B73 reference sequence. Colinearity of the genetic and physical maps was mostly conserved with some exceptions that suggest errors in the B73 assembly. Five major regions containing non-colinearities were identified on chromosomes 2, 3, 6, 7 and 9, and are supported by both independent genetic maps. Four additional non-colinear regions were found on the LHRF map only; they may be due to a lower density of IBM markers in those regions or to true structural rearrangements between lines. Given the array's high quality, it will be a valuable resource for maize genetics and many aspects of maize breeding.
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                Author and article information

                Journal
                Journal of Economic Entomology
                Oxford University Press (OUP)
                0022-0493
                1938-291X
                April 2020
                April 06 2020
                January 08 2020
                April 2020
                April 06 2020
                January 08 2020
                : 113
                : 2
                : 956-963
                Affiliations
                [1 ]USDA-ARS CHPRRU, Mississippi State, MS
                [2 ]Corteva Agriscience™, Johnston, IA
                Article
                10.1093/jee/toz357
                31914176
                c7ef0de4-0c9d-46ba-940f-ff4610d8bd9d
                © 2020
                History

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