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1.
BMC Bioinformatics ; 23(1): 254, 2022 Jun 24.
Article in English | MEDLINE | ID: mdl-35751014

ABSTRACT

BACKGROUND: Estimating relatedness is an important step for many genetic study designs. A variety of methods for estimating coefficients of pairwise relatedness from genotype data have been proposed. Both the kinship coefficient [Formula: see text] and the fraternity coefficient [Formula: see text] for all pairs of individuals are of interest. However, when dealing with low-depth sequencing or imputation data, individual level genotypes cannot be confidently called. To ignore such uncertainty is known to result in biased estimates. Accordingly, methods have recently been developed to estimate kinship from uncertain genotypes. RESULTS: We present new method-of-moment estimators of both the coefficients [Formula: see text] and [Formula: see text] calculated directly from genotype likelihoods. We have simulated low-depth genetic data for a sample of individuals with extensive relatedness by using the complex pedigree of the known genetic isolates of Cilento in South Italy. Through this simulation, we explore the behaviour of our estimators, demonstrate their properties, and show advantages over alternative methods. A demonstration of our method is given for a sample of 150 French individuals with down-sampled sequencing data. CONCLUSIONS: We find that our method can provide accurate relatedness estimates whilst holding advantages over existing methods in terms of robustness, independence from external software, and required computation time. The method presented in this paper is referred to as LowKi (Low-depth Kinship) and has been made available in an R package ( https://github.com/genostats/LowKi ).


Subject(s)
Models, Genetic , Software , Computer Simulation , Genotype , Humans , Pedigree , Whole Genome Sequencing
2.
Sci Rep ; 9(1): 4059, 2019 03 11.
Article in English | MEDLINE | ID: mdl-30858532

ABSTRACT

The present study describes the genetic architecture of the isolated populations of Cilento, through the analysis of exome sequence data of 245 representative individuals of these populations. By annotating the exome variants and cataloguing them according to their frequency and functional effects, we identified 347,684 variants, 67.4% of which are rare and low frequency variants, and 1% of them (corresponding to 319 variants per person) are classified as high functional impact variants; also, 39,946 (11.5% of the total) are novel variants, for which we determined a significant enrichment for deleterious effects. By comparing the allele frequencies in Cilento with those from the Tuscan population from the 1000 Genomes Project Phase 3, we highlighted an increase in allele frequency in Cilento especially for variants which map to genes involved in extracellular matrix formation and organization. Furthermore, among the variants showing increased frequency we identified several known rare disease-causing variants. By different population genetics analyses, we corroborated the status of the Cilento populations as genetic isolates. Finally, we showed that exome data of Cilento represents a useful local reference panel capable of improving the accuracy of genetic imputation, thus adding power to genetic studies of human traits in these populations.


Subject(s)
Exome Sequencing , Genetics, Population , Genome, Human/genetics , Exome/genetics , Female , Gene Frequency , Genotype , Human Genome Project , Humans , Italy/epidemiology , Male , Polymorphism, Single Nucleotide/genetics
4.
Neurology ; 63(8): 1527-9, 2004 Oct 26.
Article in English | MEDLINE | ID: mdl-15505184

ABSTRACT

The authors report a family in which two affected first cousins had a severe demyelinating Charcot-Marie-Tooth disease (CMT) phenotype. One had related parents, and there were no other affected relatives, suggesting an autosomal recessive mode of inheritance. Molecular studies showed that a de novo duplication in 17p11.2 and a second mutation in MTMR2 were present.


Subject(s)
Charcot-Marie-Tooth Disease/genetics , Chromosome Aberrations , Chromosomes, Human, Pair 17/genetics , Genetic Predisposition to Disease/genetics , Inheritance Patterns/genetics , Mutation/genetics , Adolescent , DNA Mutational Analysis , Disease Progression , Family Health , Female , Genes, Recessive/genetics , Genetic Testing , Humans , Male , Muscle Weakness/genetics , Muscle Weakness/pathology , Muscle Weakness/physiopathology , Nerve Fibers, Myelinated/pathology , Pedigree , Peripheral Nerves/pathology , Peripheral Nerves/physiopathology , Protein Tyrosine Phosphatases/genetics , Protein Tyrosine Phosphatases, Non-Receptor
5.
Genet Epidemiol ; 21 Suppl 1: S230-5, 2001.
Article in English | MEDLINE | ID: mdl-11793674

ABSTRACT

We analyzed a quantitative trait (serum IgE levels), and a binary trait (asthma), in four Hutterite sub-pedigrees. A genome screen for asthma was performed using GENEHUNTER, and interesting regions were followed up using extended pedigrees and the FASTLINK package. Markov chain Monte Carlo (MCMC) methods were used to assess haplotype sharing among affected individuals (MORGAN/AUTOZYG), and to perform a combined oligogenic segregation and linkage analysis (LOKI) for log10(IgE). We found evidence for at least two susceptibility loci for asthma on chromosome 5, and a QTL for log10(IgE) on chromosome 1. Our analyses demonstrate that using the most complete pedigree structure possible is advisable, with attention to the possibility of heterogeneity among subunits of a very large pedigree.


Subject(s)
Asthma/genetics , Consanguinity , Quantitative Trait, Heritable , Adult , Asthma/epidemiology , Child , Chromosome Mapping/statistics & numerical data , Chromosomes, Human, Pair 1 , Chromosomes, Human, Pair 5 , Female , Genetic Testing , Humans , Immunoglobulin E/blood , Male , Markov Chains , Monte Carlo Method , Pedigree , South Dakota
6.
Am J Hum Genet ; 67(3): 631-46, 2000 Sep.
Article in English | MEDLINE | ID: mdl-10924405

ABSTRACT

Dyslexia is a common and complex disorder with evidence for a genetic component. Multiple loci (i.e., quantitative-trait loci [QTLs]) are likely to be involved, but the number is unknown. Diagnosis is complicated by the lack of a standard protocol, and many diagnostic measures have been proposed as understanding of the component processes has evolved. One or more genes may, in turn, influence these measures. To date, little work has been done to evaluate the mode of inheritance of individual component-as opposed to composite-phenotypes, beyond family or twin correlation studies that initially demonstrate evidence for a genetic basis of such components. Here we use two approaches to segregation analysis in 102 nuclear families to estimate genetic models for component phenotypes associated with dyslexia: digit span and a nonword-repetition task. Both measures are related to phonological skills, one of the key component processes in dyslexia. We use oligogenic-trait segregation analysis to estimate the number of QTLs contributing to each phenotype, and we use complex segregation analysis to identify the most parsimonious inheritance models. We provide evidence in support of both a major-gene mode of inheritance for the nonword-repetition task, with approximately 2.4 contributing QTLs, and for a genetic basis of digit span, with approximately 1.9 contributing QTLs. Results obtained by reciprocal adjustment of measures suggest that genes contributing to digit span may contribute to the nonword-repetition score but that there are additional QTLs involved in nonword repetition. Our study adds to existing studies of the genetic basis of composite phenotypes related to dyslexia, by providing evidence for major-gene modes of inheritance of these single-measure component phenotypes.


Subject(s)
Chromosome Segregation/genetics , Dyslexia/genetics , Dyslexia/physiopathology , Fingers/physiology , Language , Memory/physiology , Age Factors , Environment , Humans , Intelligence Tests , Language Tests , Models, Genetic , Multifactorial Inheritance/genetics , Nuclear Family , Quantitative Trait, Heritable , Sex Factors , Statistics as Topic
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