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Single-step genomic BLUP (ssGBLUP) is a method for genomic prediction that integrates matrices of pedigree (A) and genomic (G) relationships into a single unified additive relationship matrix whose inverse is incorporated into a set of mixed model equations (MME) to compute genomic predictions. Pedigree information in dairy cattle is often incomplete. Missing pedigree potentially causes biases and inflation in genomic estimated breeding values (GEBV) obtained with ssGBLUP. Three major issues are associated with missing pedigree in ssGBLUP, namely biased predictions by selection, missing inbreeding in pedigree relationships, and incompatibility between G and A in level and scale. These issues can be solved using a proper model for unknown-parent groups (UPG). The theory behind the use of UPG is well established for pedigree BLUP, but not for ssGBLUP. This study reviews the development of the UPG model in pedigree BLUP, the properties of UPG models in ssGBLUP, and the effect of UPG on genetic trends and genomic predictions. Similarities and differences between UPG and metafounder (MF) models, a generalized UPG model, are also reviewed. A UPG model (QP) derived using a transformation of the MME has a good convergence behavior. However, with insufficient data, the QP model may yield biased genetic trends and may underestimate UPG. The QP model can be altered by removing the genomic relationships linking GEBV and UPG effects from MME. This altered QP model exhibits less bias in genetic trends and less inflation in genomic predictions than the QP model, especially with large data sets. Recently, a new model, which encapsulates the UPG equations into the pedigree relationships for genotyped animals, was proposed in simulated purebred populations. The MF model is a comprehensive solution to the missing pedigree issue. This model can be a choice for multibreed or crossbred evaluations if the data set allows the estimation of a reasonable relationship matrix for MF. Missing pedigree influences genetic trends, but its effect on the predictability of genetic merit for genotyped animals should be negligible when many proven bulls are genotyped. The SNP effects can be back-solved using GEBV from older genotyped animals, and these predicted SNP effects can be used to calculate GEBV for young-genotyped animals with missing parents.
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http://dx.doi.org/10.3168/jds.2021-20293 | DOI Listing |
J Appl Oral Sci
September 2025
Universidade Federal de Minas Gerais, Instituto de Ciências Biológicas, Departamento de Genética, Ecologia e Evolução, Belo Horizonte, MG, Brasil.
Background: Amelogenesis imperfecta (AI) encompasses a group of conditions characterized by abnormalities in the development or function of tooth enamel. Clinical manifestations include different forms and degrees of enamel frailty, associated with sensitivity, tooth fractures, stains, abnormal tooth morphology, missing teeth, etc. AI is genetically heterogeneous, with over 70 genes associated with autosomal dominant, autosomal recessive, X-linked, and oligogenic inheritance.
View Article and Find Full Text PDFJ Cereb Blood Flow Metab
August 2025
Glenn Biggs Institute for Alzheimer's & Neurodegenerative Diseases, University of Texas Health Sciences Center at San Antonio, San Antonio, Texas, USA.
Cerebral small vessel disease (cSVD) is a major contributor to stroke, dementia, and cognitive decline. Despite significant progress through large-scale genome-wide association studies (GWAS) for cSVD and stroke, the genetic architecture underlying these conditions remains poorly understood. This review highlights recent advancements in statistical tools and provides a comprehensive overview of current insights into the genetic underpinnings of cSVD and stroke.
View Article and Find Full Text PDFBioinform Adv
July 2025
Department of Biostatistics Harvard T.H. Chan School of Public Health, Boston, MA 02115, United States.
Motivation: Reliable tools and software for penetrance (age-specific risk among those who carry a genetic variant) estimation are critical to improving clinical decision making and risk assessment for hereditary syndromes. However, there is a lack of easily usable software for penetrance estimation in family-based studies that implements a Bayesian estimation approach.
Results: We introduce , an open-source R package available on CRAN, to estimate age-specific penetrance using family-history pedigree data.
Behav Genet
July 2025
Wake Forest University, Winston-Salem, USA.
Mitochondrial DNA (mtDNA) plays a crucial role in numerous cellular processes, yet its impact on human complex behavior remains underexplored. The current paper proposes a novel covariance structure model with seven parameters to specifically isolate and quantify mtDNA effects on human complex traits. This approach uses extended pedigrees to obtain estimates of mtDNA variance while controlling for other genetic and environmental influences.
View Article and Find Full Text PDFmedRxiv
May 2025
Vanderbilt University Medical Center, Division of Genetic Medicine, Department of Medicine, 1211 Medical Center Drive, Nashville, TN 37232.
Objective: To develop and implement a pipeline for integrated breast cancer risk assessment using the BOADICEA model within the eMERGE study, incorporating polygenic risk scores (PRS), monogenic variants, family history, and clinical factors.
Materials And Methods: A pipeline was deployed across ten eMERGE clinical sites, integrating data from REDCap surveys, PRS reports, monogenic reports, and pedigrees via CanRisk Application Programming Interface (API). The process included design, customization, technical implementation, testing, and refinement.