Zobrazeno 1 - 10
of 20
pro vyhledávání: '"Lance F. Merrick"'
Autor:
Karansher S. Sandhu, Adrienne B. Burke, Lance F. Merrick, Michael O. Pumphrey, Arron H. Carter
Publikováno v:
Frontiers in Plant Science, Vol 15 (2024)
Nested association mapping (NAM) populations emerged as a multi-parental strategy that combines the high statistical power of biparental linkage mapping with greater allelic richness of association mapping. Several statistical models have been develo
Externí odkaz:
https://doaj.org/article/edd020771a854d27b680f9159de7f374
Autor:
Shaun J. Clare, Kasia M. Duellman, Jonathan K. Richards, Roshan Sharma Poudel, Lance F. Merrick, Timothy L. Friesen, Robert S. Brueggeman
Publikováno v:
BMC Genomics, Vol 23, Iss 1, Pp 1-17 (2022)
Abstract Background Spot form net blotch (SFNB) caused by the necrotrophic fungal pathogen Pyrenophora teres f. maculata (Ptm) is an economically important disease of barley that also infects wheat. Using genetic analysis to characterize loci in Ptm
Externí odkaz:
https://doaj.org/article/7b3527b203a4402e96abc41d571dfa05
Publikováno v:
Frontiers in Genetics, Vol 13 (2022)
Most genomic prediction models are linear regression models that assume continuous and normally distributed phenotypes, but responses to diseases such as stripe rust (caused by Puccinia striiformis f. sp. tritici) are commonly recorded in ordinal sca
Externí odkaz:
https://doaj.org/article/2ef79a37fe01420aa03f66255347e86f
Publikováno v:
Frontiers in Genetics, Vol 12 (2022)
The last decade witnessed an unprecedented increase in the adoption of genomic selection (GS) and phenomics tools in plant breeding programs, especially in major cereal crops. GS has demonstrated the potential for selecting superior genotypes with hi
Externí odkaz:
https://doaj.org/article/e6af624baf7840ac826762041400d5d5
Publikováno v:
Frontiers in Plant Science, Vol 12 (2022)
Unknown genetic architecture makes it difficult to characterize the genetic basis of traits and associated molecular markers because of the complexity of small effect quantitative trait loci (QTLs), environmental effects, and difficulty in phenotypin
Externí odkaz:
https://doaj.org/article/2c2d7377f4ea41528628d2ee00fce0f8
Autor:
Lance F. Merrick, Arron H. Carter
Publikováno v:
The Plant Genome, Vol 14, Iss 3, Pp n/a-n/a (2021)
Abstract Traits with a complex unknown genetic architecture are common in breeding programs. However, they pose a challenge for selection due to a combination of complex environmental and pleiotropic effects that impede the ability to create mapping
Externí odkaz:
https://doaj.org/article/ab8ab90773c74fa8bc5d80b2d3a9ad3d
Publikováno v:
Frontiers in Plant Science, Vol 12 (2021)
Disease resistance in plants is mostly quantitative, with both major and minor genes controlling resistance. This research aimed to optimize genomic selection (GS) models for use in breeding programs that are needed to select both major and minor gen
Externí odkaz:
https://doaj.org/article/9f209e1842bf46c3a742b6299835a6db
Publikováno v:
Agronomy, Vol 12, Iss 3, p 714 (2022)
Plant geneticists and breeders have used marker technology since the 1980s in quantitative trait locus (QTL) identification. Marker-assisted selection is effective for large-effect QTL but has been challenging to use with quantitative traits controll
Externí odkaz:
https://doaj.org/article/af093caee2224efd8772ab6f6c1d9500
Publikováno v:
Agronomy, Vol 12, Iss 2, p 522 (2022)
Wheat (Triticum aestivum L.) breeding programs can take over a decade to release a new variety. However, new methods of selection, such as genomic selection (GS), must be integrated to decrease the time it takes to release new varieties to meet the d
Externí odkaz:
https://doaj.org/article/ae1166c835cc49eb98b96b60a76ee1e2
Publikováno v:
Frontiers in genetics. 13
Most genomic prediction models are linear regression models that assume continuous and normally distributed phenotypes, but responses to diseases such as stripe rust (caused by
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=pmid________::403b20abae019a6a96a1d6198fe9b41e
https://pubmed.ncbi.nlm.nih.gov/35281841
https://pubmed.ncbi.nlm.nih.gov/35281841