As high-throughput genomic tools, such as the DNA microarray platform, have lead to the development of novel genotyping procedures, such as Diversity Arrays Technology (DArT) and Single Nucleotide Polymorphisms (SNPs), it is likely that, in the future, high density linkage maps will be constructed from both dominant and co-dominant markers. Recently, a strictly genetic approach was described for estimating recombination frequency (r) between co-dominant markers in full-sib families. The complete set of maximum likelihood estimators for r in full-sib families was almost obtained, but unfortunately, one particular configuration involving dominant markers, segregating in a 3:1 ratio and co-dominant markers, was not considered. Here we add nine further estimators to the previously published set, thereby making it possible to cover all combinations of molecular markers with two to four alleles (without epistasis) in a full-sib family. This includes segregation in one or both parents, dominance and all linkage phase configurations.
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http://dx.doi.org/10.1590/S1415-47572010000300021 | DOI Listing |
Evol Dev
March 2025
Department of Integrative Biology, University of Guelph, Guelph, Ontario, Canada.
The evolution of adaptive phenotypic divergence requires heritable genetic variation. However, it is underappreciated that trait heritability is molded by developmental processes interacting with the environment. We hypothesized that the genetic architecture of divergent functional traits was dependent on age and foraging environment.
View Article and Find Full Text PDFSheng Wu Gong Cheng Xue Bao
December 2024
College of Fisheries, Guangdong Ocean University, Zhanjiang 524088, Guangdong, China.
To clarify the genetic diversity and structure of the nucleus population of F1-generation , this study utilized 15 pairs of highly polymorphic microsatellite primers to analyze the simple sequence repeat (SSR) markers and genetic diversity in 15 full-sib families of . . A total of 112 alleles () and 60.
View Article and Find Full Text PDFJ Anim Breed Genet
December 2024
Key Laboratory (Nanjing) for Evaluation and Utilization of Pigs Resources, College of Animal Science & Technology, Nanjing Agricultural University, Nanjing, People's Republic of China.
Both selection and mating systems are essential tools for breeders to conserve the genetic variance and improve the performance of livestock animals. How to effectively balance the genetic gain and inbreeding has always been an important issue in quantitative genetics research. In this study, a total of 11 selection methods, including random and truncation selection, six conventional selection methods, three different optimal contribution selection (OCS) methods and three mating strategies including random mating, minimum-coancestry mating based on pedigree (MCPed) and genomic information (MCmarker), were performed using stochastic simulations.
View Article and Find Full Text PDFFront Plant Sci
October 2024
Instituto Nacional de Tecnología Agropecuaria (INTA), Instituto de Recursos Biológicos, Centro de Investigación en Recursos Naturales, Buenos Aires, Argentina.
Genomic Selection (GS) in tree breeding optimizes genetic gains by leveraging genomic data to enable early selection of seedlings without phenotypic data reducing breeding cycle and increasing selection intensity. Traditional assessments of the potential of GS in forest trees have typically focused on model performance using cross-validation within the same generation but evaluating effectively realized predictive ability (RPA) across generations is crucial. This study estimated RPAs for volume growth (VOL), wood density (WD), and pulp yield (PY) across four generations breeding of .
View Article and Find Full Text PDFGenet Sel Evol
November 2024
Center for Quantitative Genetics and Genomics, Aarhus University, C. F. Møllers Allé 3, 8000, Aarhus, Denmark.
Background: The aim of this study was to compare genetic gain and rate of inbreeding for different mass selection breeding programs with the aim of increasing larval body weight (LBW) in black soldier flies. The breeding programs differed in: (1) sampling of individuals for phenotyping (either random over the whole population or a fixed number per full sib family), (2) selection of adult flies for breeding (based on an adult individual's phenotype for LBW or random from larvae preselected based on LBW), and (3) mating strategy (mating in a group with unequal male contributions or controlled between two females and one male). In addition, the numbers of phenotyped and preselected larvae were varied.
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