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American Journal of Human Genetics Jan 2023Pedigree analysis showed that a large proportion of Leber hereditary optic neuropathy (LHON) family members who carry a mitochondrial risk variant never lose vision....
Pedigree analysis showed that a large proportion of Leber hereditary optic neuropathy (LHON) family members who carry a mitochondrial risk variant never lose vision. Mitochondrial haplotype appears to be a major factor influencing the risk of vision loss from LHON. Mitochondrial variants, including m.14484T>C and m.11778G>A, have been added to gene arrays, and thus many patients and research participants are tested for LHON mutations. Analysis of the UK Biobank and Australian cohort studies found more than 1 in 1,000 people in the general population carry either the m.14484T>C or the m.11778G>A LHON variant. None of the subset of carriers examined had visual acuity at 20/200 or worse, suggesting a very low penetrance of LHON. Haplogroup analysis of m.14484T>C carriers showed a high rate of haplogroup U subclades, previously shown to have low penetrance in pedigrees. Penetrance calculations of the general population are lower than pedigree calculations, most likely because of modifier genetic factors. This Matters Arising Response paper addresses the Watson et al. (2022) Matters Arising paper, published concurrently in The American Journal of Human Genetics.
Topics: Humans; Penetrance; DNA, Mitochondrial; Optic Atrophy, Hereditary, Leber; Australia; Mutation; Pedigree
PubMed: 36565701
DOI: 10.1016/j.ajhg.2022.11.014 -
The Plant Genome Nov 2016This paper describes AlphaSim, a software package for simulating plant and animal breeding programs. AlphaSim enables the simulation of multiple aspects of breeding...
This paper describes AlphaSim, a software package for simulating plant and animal breeding programs. AlphaSim enables the simulation of multiple aspects of breeding programs with a high degree of flexibility. AlphaSim simulates breeding programs in a series of steps: (i) simulate haplotype sequences and pedigree; (ii) drop haplotypes into the base generation of the pedigree and select single-nucleotide polymorphism (SNP) and quantitative trait nucleotide (QTN); (iii) assign QTN effects, calculate genetic values, and simulate phenotypes; (iv) drop haplotypes into the burn-in generations; and (v) perform selection and simulate new generations. The program is flexible in terms of historical population structure and diversity, recent pedigree structure, trait architecture, and selection strategy. It integrates biotechnologies such as doubled-haploids (DHs) and gene editing and allows the user to simulate multiple traits and multiple environments, specify recombination hot spots and cold spots, specify gene jungles and deserts, perform genomic predictions, and apply optimal contribution selection. AlphaSim also includes restart functionalities, which increase its flexibility by allowing the simulation process to be paused so that the parameters can be changed or to import an externally created pedigree, trial design, or results of an analysis of previously simulated data. By combining the options, a user can simulate simple or complex breeding programs with several generations, variable population structures and variable breeding decisions over time. In conclusion, AlphaSim is a flexible and computationally efficient software package to simulate biotechnology enhanced breeding programs with the aim of performing rapid, low-cost, and objective in silico comparison of breeding technologies.
Topics: Animals; Computer Simulation; Models, Genetic; Pedigree; Phenotype; Plant Breeding; Polymorphism, Single Nucleotide; Quantitative Trait Loci; Software
PubMed: 27902803
DOI: 10.3835/plantgenome2016.02.0013 -
Blood Mar 2023Familial aggregation of Hodgkin lymphoma (HL) has been demonstrated in large population studies, pointing to genetic predisposition to this hematological malignancy. To...
Familial aggregation of Hodgkin lymphoma (HL) has been demonstrated in large population studies, pointing to genetic predisposition to this hematological malignancy. To understand the genetic variants associated with the development of HL, we performed whole genome sequencing on 234 individuals with and without HL from 36 pedigrees that had 2 or more first-degree relatives with HL. Our pedigree selection criteria also required at least 1 affected individual aged <21 years, with the median age at diagnosis of 21.98 years (3-55 years). Family-based segregation analysis was performed for the identification of coding and noncoding variants using linkage and filtering approaches. Using our tiered variant prioritization algorithm, we identified 44 HL-risk variants in 28 pedigrees, of which 33 are coding and 11 are noncoding. The top 4 recurrent risk variants are a coding variant in KDR (rs56302315), a 5' untranslated region variant in KLHDC8B (rs387906223), a noncoding variant in an intron of PAX5 (rs147081110), and another noncoding variant in an intron of GATA3 (rs3824666). A newly identified splice variant in KDR (c.3849-2A>C) was observed for 1 pedigree, and high-confidence stop-gain variants affecting IRF7 (p.W238∗) and EEF2KMT (p.K116∗) were also observed. Multiple truncating variants in POLR1E were found in 3 independent pedigrees as well. Whereas KDR and KLHDC8B have previously been reported, PAX5, GATA3, IRF7, EEF2KMT, and POLR1E represent novel observations. Although there may be environmental factors influencing lymphomagenesis, we observed segregation of candidate germline variants likely to predispose HL in most of the pedigrees studied.
Topics: Humans; Young Adult; Adult; Hodgkin Disease; Genetic Predisposition to Disease; Germ-Line Mutation; Codon, Nonsense; Whole Genome Sequencing; Pedigree; Cell Cycle Proteins
PubMed: 35977101
DOI: 10.1182/blood.2022016056 -
BMC Bioinformatics May 2021Statistical geneticists employ simulation to estimate the power of proposed studies, test new analysis tools, and evaluate properties of causal models. Although there...
BACKGROUND
Statistical geneticists employ simulation to estimate the power of proposed studies, test new analysis tools, and evaluate properties of causal models. Although there are existing trait simulators, there is ample room for modernization. For example, most phenotype simulators are limited to Gaussian traits or traits transformable to normality, while ignoring qualitative traits and realistic, non-normal trait distributions. Also, modern computer languages, such as Julia, that accommodate parallelization and cloud-based computing are now mainstream but rarely used in older applications. To meet the challenges of contemporary big studies, it is important for geneticists to adopt new computational tools.
RESULTS
We present TraitSimulation, an open-source Julia package that makes it trivial to quickly simulate phenotypes under a variety of genetic architectures. This package is integrated into our OpenMendel suite for easy downstream analyses. Julia was purpose-built for scientific programming and provides tremendous speed and memory efficiency, easy access to multi-CPU and GPU hardware, and to distributed and cloud-based parallelization. TraitSimulation is designed to encourage flexible trait simulation, including via the standard devices of applied statistics, generalized linear models (GLMs) and generalized linear mixed models (GLMMs). TraitSimulation also accommodates many study designs: unrelateds, sibships, pedigrees, or a mixture of all three. (Of course, for data with pedigrees or cryptic relationships, the simulation process must include the genetic dependencies among the individuals.) We consider an assortment of trait models and study designs to illustrate integrated simulation and analysis pipelines. Step-by-step instructions for these analyses are available in our electronic Jupyter notebooks on Github. These interactive notebooks are ideal for reproducible research.
CONCLUSION
The TraitSimulation package has three main advantages. (1) It leverages the computational efficiency and ease of use of Julia to provide extremely fast, straightforward simulation of even the most complex genetic models, including GLMs and GLMMs. (2) It can be operated entirely within, but is not limited to, the integrated analysis pipeline of OpenMendel. And finally (3), by allowing a wider range of more realistic phenotype models, TraitSimulation brings power calculations and diagnostic tools closer to what investigators might see in real-world analyses.
Topics: Aged; Cloud Computing; Computer Simulation; Genetic Testing; Humans; Pedigree; Phenotype
PubMed: 33941078
DOI: 10.1186/s12859-021-04086-8 -
Heredity Jan 2022The two alleles an individual carries at a locus are identical by descent (ibd) if they have descended from a single ancestral allele in a reference population, and the...
The two alleles an individual carries at a locus are identical by descent (ibd) if they have descended from a single ancestral allele in a reference population, and the probability of such identity is the inbreeding coefficient of the individual. Inbreeding coefficients can be predicted from pedigrees with founders constituting the reference population, but estimation from genetic data is not possible without data from the reference population. Most inbreeding estimators that make explicit use of sample allele frequencies as estimates of allele probabilities in the reference population are confounded by average kinships with other individuals. This means that the ranking of those estimates depends on the scope of the study sample and we show the variation in rankings for common estimators applied to different subdivisions of 1000 Genomes data. Allele-sharing estimators of within-population inbreeding relative to average kinship in a study sample, however, do have invariant rankings across all studies including those individuals. They are unbiased with a large number of SNPs. We discuss how allele sharing estimates are the relevant quantities for a range of empirical applications.
Topics: Alleles; Gene Frequency; Humans; Inbreeding; Models, Genetic; Pedigree; Polymorphism, Single Nucleotide
PubMed: 34824382
DOI: 10.1038/s41437-021-00471-4 -
BMC Bioinformatics Jun 2022The ubiquity of pedigrees in many scientific areas calls for versatile and user-friendly software. Previously published online pedigree tools have limited support for...
BACKGROUND
The ubiquity of pedigrees in many scientific areas calls for versatile and user-friendly software. Previously published online pedigree tools have limited support for complex pedigrees and do not provide analysis of relatedness between pedigree members.
RESULTS
We introduce QuickPed, a web application for interactive pedigree creation and analysis. It supports complex inbreeding and comes with a rich built-in library of common and interesting pedigrees. The program calculates all standard coefficients of relatedness, including inbreeding, kinship and identity coefficients, and offers specialised plots for visualising relatedness. It also implements a novel algorithm for describing pairwise relationships in words.
CONCLUSION
QuickPed is a user-friendly pedigree tool aimed at researchers, case workers and teachers. It contains a number of features not found in other similar tools, and represents a significant addition to the body of pedigree software by making advanced relatedness analyses available for non-bioinformaticians.
Topics: Algorithms; Humans; Inbreeding; Pedigree; Software
PubMed: 35672681
DOI: 10.1186/s12859-022-04759-y -
BMC Medical Genomics Oct 2023Oculopharyngodistal myopathy (OPDM) is an autosomal dominant adult-onset degenerative muscle disorder characterized by ptosis, ophthalmoplegia and weakness of the...
BACKGROUND
Oculopharyngodistal myopathy (OPDM) is an autosomal dominant adult-onset degenerative muscle disorder characterized by ptosis, ophthalmoplegia and weakness of the facial, pharyngeal and limb muscles. Trinucleotide repeat expansions in non-coding regions of LRP12, G1PC1, NOTCH2NLC and RILPL1 were reported to be the etiologies for OPDM.
RESULTS
In this study, we performed long-read whole-genome sequencing in a large five-generation family of 156 individuals, including 21 patients diagnosed with typical OPDM. We identified CGG repeat expansions in 5'UTR of RILPL1 gene in all patients we tested while no CGG expansion in unaffected family members. Repeat-primed PCR and fluorescence amplicon length analysis PCR were further confirmed the segregation of CGG expansions in other family members and 1000 normal Chinese controls. Methylation analysis indicated that methylation levels of the RILPL1 gene were unaltered in OPDM patients, which was consistent with previous studies. Our findings provide evidence that RILPL1 is associated OPDM in this large pedigree.
CONCLUSIONS
Our results identified RILPL1 is the associated the disease in this large pedigree.
Topics: Adult; Humans; Muscle, Skeletal; Muscular Dystrophies; Pedigree; Whole Genome Sequencing
PubMed: 37864208
DOI: 10.1186/s12920-023-01586-9 -
Genetic Epidemiology Mar 2019Evaluating the association of multiple genetic variants with a trait of interest by use of kernel-based methods has made a significant impact on how genetic association... (Review)
Review
Evaluating the association of multiple genetic variants with a trait of interest by use of kernel-based methods has made a significant impact on how genetic association analyses are conducted. An advantage of kernel methods is that they tend to be robust when the genetic variants have effects that are a mixture of positive and negative effects, as well as when there is a small fraction of causal variants. Another advantage is that kernel methods fit within the framework of mixed models, providing flexible ways to adjust for additional covariates that influence traits. Herein, we review the basic ideas behind the use of kernel methods for genetic association analysis as well as recent methodological advancements for different types of traits, multivariate traits, pedigree data, and longitudinal data. Finally, we discuss opportunities for future research.
Topics: Algorithms; Genetic Association Studies; Humans; Models, Genetic; Multivariate Analysis; Pedigree; Phenotype; Software
PubMed: 30604442
DOI: 10.1002/gepi.22180 -
Molecular Psychiatry Apr 2019As it is likely that both common and rare genetic variation are important for complex disease risk, studies that examine the full range of the allelic frequency... (Review)
Review
As it is likely that both common and rare genetic variation are important for complex disease risk, studies that examine the full range of the allelic frequency distribution should be utilized to dissect the genetic influences on mental illness. The rate limiting factor for inferring an association between a variant and a phenotype is inevitably the total number of copies of the minor allele captured in the studied sample. For rare variation, with minor allele frequencies of 0.5% or less, very large samples of unrelated individuals are necessary to unambiguously associate a locus with an illness. Unfortunately, such large samples are often cost prohibitive. However, by using alternative analytic strategies and studying related individuals, particularly those from large multiplex families, it is possible to reduce the required sample size while maintaining statistical power. We contend that using whole genome sequence (WGS) in extended pedigrees provides a cost-effective strategy for psychiatric gene mapping that complements common variant approaches and WGS in unrelated individuals. This was our impetus for forming the "Pedigree-Based Whole Genome Sequencing of Affective and Psychotic Disorders" consortium. In this review, we provide a rationale for the use of WGS with pedigrees in modern psychiatric genetics research. We begin with a focused review of the current literature, followed by a short history of family-based research in psychiatry. Next, we describe several advantages of pedigrees for WGS research, including power estimates, methods for studying the environment, and endophenotypes. We conclude with a brief description of our consortium and its goals.
Topics: Alleles; Family; Gene Frequency; Genetic Variation; Genotype; Humans; Mental Disorders; Mental Health; Pedigree; Phenotype; Research Design; Sample Size; Sequence Analysis, DNA; Whole Genome Sequencing
PubMed: 29955165
DOI: 10.1038/s41380-018-0073-x -
Bioinformatics (Oxford, England) Jun 2016Read-based phasing deduces the haplotypes of an individual from sequencing reads that cover multiple variants, while genetic phasing takes only genotypes as input and...
MOTIVATION
Read-based phasing deduces the haplotypes of an individual from sequencing reads that cover multiple variants, while genetic phasing takes only genotypes as input and applies the rules of Mendelian inheritance to infer haplotypes within a pedigree of individuals. Combining both into an approach that uses these two independent sources of information-reads and pedigree-has the potential to deliver results better than each individually.
RESULTS
We provide a theoretical framework combining read-based phasing with genetic haplotyping, and describe a fixed-parameter algorithm and its implementation for finding an optimal solution. We show that leveraging reads of related individuals jointly in this way yields more phased variants and at a higher accuracy than when phased separately, both in simulated and real data. Coverages as low as 2× for each member of a trio yield haplotypes that are as accurate as when analyzed separately at 15× coverage per individual.
AVAILABILITY AND IMPLEMENTATION
https://bitbucket.org/whatshap/whatshap
CONTACT
Topics: Algorithms; Genotype; Haplotypes; Pedigree; Polymorphism, Single Nucleotide; Sequence Analysis, DNA
PubMed: 27307622
DOI: 10.1093/bioinformatics/btw276