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Taiwanese Journal of Obstetrics &... Mar 2022To investigate the phenotypes, biochemical features and genotypes for 244 pedigrees with methylmalonic aciduria (MMA) in China, and to perform the prenatal genetic...
OBJECTIVES
To investigate the phenotypes, biochemical features and genotypes for 244 pedigrees with methylmalonic aciduria (MMA) in China, and to perform the prenatal genetic diagnosis by chorionic villus for these pedigrees.
MATERIALS AND METHODS
Gene analyses were performed for 244 pedigrees. There are 130 pedigrees, chorionic villus sampling was performed on the pregnant women to conduct the prenatal diagnosis.
RESULTS
Among 244 patients, 168 (68.9%) cases were combined methylmalonic aciduria and homocystinuria, 76 (31.1%) cases were isolated methylmalonic aciduria. All the patients were diagnosed with MMA by their clinical manifestation, elevated blood propionylcarnitine, propionylcarnitine to acetylcarnitine ratio, and/or urine/blood methylmalonic acid with or without homocysteine. MMACHC, MMUT, SUCLG1 and LMBRD1 gene variants were found in 236 (96.7%) pedigrees included 6 probands with only one heterozygous variant out of 244 cases. For the 130 pedigrees who received a prenatal diagnosis, 22 fetuses were normal, 69 foetuses were carriers of heterozygous variants, and the remaining 39 foetuses harboured compound heterozygous variants or homozygous variants. The follow-up results were consistent with the prenatal diagnosis.
CONCLUSION
The present study indicates genetic heterogeneity in MMA patients. Genetic analysis is a convenient method for prenatal diagnosis that will aid in avoiding the delivery of MMA patients.
Topics: Amino Acid Metabolism, Inborn Errors; China; Female; Genotype; Humans; Nucleocytoplasmic Transport Proteins; Oxidoreductases; Pedigree; Pregnancy; Prenatal Diagnosis
PubMed: 35361390
DOI: 10.1016/j.tjog.2022.02.017 -
Molecular Ecology Oct 2018The concept of kinship permeates many domains of fundamental and applied biology ranging from social evolution to conservation science to quantitative and human...
The concept of kinship permeates many domains of fundamental and applied biology ranging from social evolution to conservation science to quantitative and human genetics. Until recently, pedigrees were the gold standard to infer kinship, but the advent of next-generation sequencing and the availability of dense genetic markers in many species make it a good time to (re)evaluate the usefulness of genetic markers in this context. Using three published data sets where both pedigrees and markers are available, we evaluate two common and a new genetic estimator of kinship. We show discrepancies between pedigree values and marker estimates of kinship and explore via simulations the possible reasons for these. We find these discrepancies are attributable to two main sources: pedigree errors and heterogeneity in the origin of founders. We also show that our new marker-based kinship estimator has very good statistical properties and behaviour and is particularly well suited for situations where the source population is of small size, as will often be the case in conservation biology, and where high levels of kinship are expected, as is typical in social evolution studies.
Topics: Genetic Markers; Genetics, Population; Humans; Models, Genetic; Pedigree
PubMed: 30107060
DOI: 10.1111/mec.14833 -
Human Heredity 2009Haplotypes provide valuable information in the study of diseases, complex traits, population histories, and evolutionary genetics. With the dramatic increase in the... (Review)
Review
Haplotypes provide valuable information in the study of diseases, complex traits, population histories, and evolutionary genetics. With the dramatic increase in the number of available single nucleotide polymorphism (SNP) markers, haplotype inference (haplotyping) using observed genotype data has become an important component of genetic studies in general and of statistical gene mapping in particular. Existing haplotyping methods include (1) population-based methods, (2) methods for pooled DNA samples, and (3) methods for family and pedigree data. The methods and computer programs for population data and pooled DNA samples were reviewed recently in the literature. As several authors noted, family and pedigree datasets are abundant and have unique advantages. In the past twenty years, many haplotyping methods for family and pedigree data have been developed. Therefore, in this contribution we review haplotyping methods and the corresponding computer programs suitable for family and pedigree data and discuss their applications and limitations. We explore the connections among these methods, and describe the challenges that remain to be addressed.
Topics: Algorithms; Animals; Bayes Theorem; Chromosome Mapping; Computer Simulation; Haplotypes; Humans; Likelihood Functions; Pedigree; Polymorphism, Single Nucleotide
PubMed: 19172084
DOI: 10.1159/000194978 -
BMC Bioinformatics Dec 2020Pedigree files are ubiquitously used within bioinformatics and genetics studies to convey critical information about relatedness, sex and affected status of study...
BACKGROUND
Pedigree files are ubiquitously used within bioinformatics and genetics studies to convey critical information about relatedness, sex and affected status of study samples. While the text based format of ped files is efficient for computational methods, it is not immediately intuitive to a bioinformatician or geneticist trying to understand family structures, many of which encode the affected status of individuals across multiple generations. The visualization of pedigrees into connected nodes with descriptive shapes and shading provides a far more interpretable format to recognize visual patterns and intuit family structures. Despite these advantages of a visual pedigree, it remains difficult to quickly and accurately visualize a pedigree given a pedigree text file.
RESULTS
Here we describe ped_draw a command line and web tool as a simple and easy solution to pedigree visualization. Ped_draw is capable of drawing complex multi-generational pedigrees and conforms to the accepted standards for depicting pedigrees visually. The command line tool can be used as a simple one liner command, utilizing graphviz to generate an image file. The web tool, https://peddraw.github.io , allows the user to either: paste a pedigree file, type to construct a pedigree file in the text box or upload a pedigree file. Users can save the generated image file in various formats.
CONCLUSIONS
We believe ped_draw is a useful pedigree drawing tool that improves on current methods due to its ease of use and approachability. Ped_draw allows users with various levels of expertise to quickly and easily visualize pedigrees.
Topics: Computational Biology; Humans; Pedigree; Software
PubMed: 33297934
DOI: 10.1186/s12859-020-03917-4 -
BMC Genetics Jul 2015Levels of inbreeding in cattle populations have increased in the past due to the use of a limited number of bulls for artificial insemination. High levels of inbreeding...
BACKGROUND
Levels of inbreeding in cattle populations have increased in the past due to the use of a limited number of bulls for artificial insemination. High levels of inbreeding lead to reduced genetic diversity and inbreeding depression. Various estimators based on different sources, e.g., pedigree or genomic data, have been used to estimate inbreeding coefficients in cattle populations. However, the comparative advantage of using full sequence data to assess inbreeding is unknown. We used pedigree and genomic data at different densities from 50k to full sequence variants to compare how different methods performed for the estimation of inbreeding levels in three different cattle breeds.
RESULTS
Five different estimates for inbreeding were calculated and compared in this study: pedigree based inbreeding coefficient (F(PED)); run of homozygosity (ROH)-based inbreeding coefficients (F(ROH)); genomic relationship matrix (GRM)-based inbreeding coefficients (F(GRM)); inbreeding coefficients based on excess of homozygosity (F(HOM)) and correlation of uniting gametes (F(UNI)). Estimates using ROH provided the direct estimated levels of autozygosity in the current populations and are free effects of allele frequencies and incomplete pedigrees which may increase in inaccuracy in estimation of inbreeding. The highest correlations were observed between F(ROH) estimated from the full sequence variants and the F(ROH) estimated from 50k SNP (single nucleotide polymorphism) genotypes. The estimator based on the correlation between uniting gametes (F(UNI)) using full genome sequences was also strongly correlated with F(ROH) detected from sequence data.
CONCLUSIONS
Estimates based on ROH directly reflected levels of homozygosity and were not influenced by allele frequencies, unlike the three other estimates evaluated (F(GRM), F(HOM) and FU(NI)), which depended on estimated allele frequencies. F(PED) suffered from limited pedigree depth. Marker density affects ROH estimation. Detecting ROH based on 50k chip data was observed to give estimates similar to ROH from sequence data. In the absence of full sequence data ROH based on 50k can be used to access homozygosity levels in individuals. However, genotypes denser than 50k are required to accurately detect short ROH that are most likely identical by descent (IBD).
Topics: Algorithms; Alleles; Animals; Cattle; Gene Frequency; Genomics; Genotype; High-Throughput Nucleotide Sequencing; Inbreeding; Models, Genetic; Pedigree; Polymorphism, Single Nucleotide
PubMed: 26195126
DOI: 10.1186/s12863-015-0227-7 -
Molecular Ecology Resources Nov 2022Genealogical relationships are fundamental components of genetic studies. However, it is often challenging to infer correct and complete pedigrees even when genome-wide...
Genealogical relationships are fundamental components of genetic studies. However, it is often challenging to infer correct and complete pedigrees even when genome-wide information is available. For example, inbreeding can obscure genetic differences between individuals, making it difficult to even distinguish first-degree relatives such as parent-offspring from full siblings. Similarly, genotyping errors can interfere with the detection of genetic similarity between parents and their offspring. Inbreeding is common in natural, domesticated, and experimental populations and genotyping of these populations often has more errors than in human data sets, so efficient methods for building pedigrees under these conditions are necessary. Here, we present a new method for parent-offspring inference in inbred pedigrees called specific parent-offspring relationship estimation (spore). spore is vastly superior to existing pedigree-inference methods at detecting parent-offspring relationships, in particular when inbreeding is high or in the presence of genotyping errors, or both. spore therefore fills an important void in the arsenal of pedigree inference tools.
Topics: Genome; Humans; Inbreeding; Models, Genetic; Pedigree
PubMed: 35770342
DOI: 10.1111/1755-0998.13680 -
Hereditas May 2020R is a multi-platform statistical software and an object oriented programming language. The package archive network for R provides CRAN repository that features over...
BACKGROUND
R is a multi-platform statistical software and an object oriented programming language. The package archive network for R provides CRAN repository that features over 15,000 free open source packages, at the time of writing this article (https://cran.r-project.org/web/packages, accessed in October 2019). The package ggroups is introduced in this article. The purpose of this package is providing functions for checking and processing the pedigree, calculation of the additive genetic relationship matrix and its inverse, which are used to study the population structure and predicting the genetic merit of animals. Calculation of the dominance relationship matrix and its inverse are also covered. A concept in animal breeding is genetic groups, which is about the inequality of the average genetic merits for groups of unknown parents. The package provides functions for the calculation of the matrix of genetic group contributions (Q). Calculating Q is computationally demanding, and depending on the size of the pedigree and the number of genetic groups, it might not be feasible using personal computers. Therefore, a computationally optimised function and its parallel processing alternative are provided in the package.
RESULTS
Using sample data, outputs from different functions of the package were presented to illustrate a real experience of working with the package.
CONCLUSIONS
The presented R package is a free and open source tool mainly for quantitative geneticists and ecologists, who deal with pedigree data. It provides numerous functions for handling pedigree data, and calculating various pedigree-based matrices. Some of the functions are computationally optimised for large-scale data.
Topics: Animals; Genetics, Population; Pedigree; Software
PubMed: 32366304
DOI: 10.1186/s41065-020-00124-2 -
G3 (Bethesda, Md.) Feb 2023This paper proposes a solution to a long-standing problem concerning the joint distribution of allelic identity by descent between two individuals at two linked loci....
This paper proposes a solution to a long-standing problem concerning the joint distribution of allelic identity by descent between two individuals at two linked loci. Such distributions have important applications across various fields of genetics, and detailed formulas for selected relationships appear scattered throughout the literature. However, these results were obtained essentially by brute force, with no efficient method available for general pedigrees. The recursive algorithm described in this paper, and its implementation in R, allow efficient calculation of two-locus identity coefficients in any pedigree. As a result, many existing procedures and techniques may, for the first time, be applied to complex and inbred relationships. Two such applications are discussed, concerning the expected likelihood ratio in forensic kinship testing, and variances in realized relatedness.
Topics: Humans; Pedigree; Algorithms; Alleles; Models, Genetic
PubMed: 36525359
DOI: 10.1093/g3journal/jkac326 -
American Journal of Human Genetics Jan 2021The proportion of samples with one or more close relatives in a genetic dataset increases rapidly with sample size, necessitating relatedness modeling and enabling...
The proportion of samples with one or more close relatives in a genetic dataset increases rapidly with sample size, necessitating relatedness modeling and enabling pedigree-based analyses. Despite this, relatives are generally unreported and current inference methods typically detect only the degree of relatedness of sample pairs and not pedigree relationships. We developed CREST, an accurate and fast method that identifies the pedigree relationships of close relatives. CREST utilizes identity by descent (IBD) segments shared between a pair of samples and their mutual relatives, leveraging the fact that sharing rates among these individuals differ across pedigree configurations. Furthermore, CREST exploits the profound differences in sex-specific genetic maps to classify pairs as maternally or paternally related-e.g., paternal half-siblings-using the locations of autosomal IBD segments shared between the pair. In simulated data, CREST correctly classifies 91.5%-100% of grandparent-grandchild (GP) pairs, 80.0%-97.5% of avuncular (AV) pairs, and 75.5%-98.5% of half-siblings (HS) pairs compared to PADRE's rates of 38.5%-76.0% of GP, 60.5%-92.0% of AV, 73.0%-95.0% of HS pairs. Turning to the real 20,032 sample Generation Scotland (GS) dataset, CREST identified seven pedigrees with incorrect relationship types or maternal/paternal parent sexes, five of which we confirmed as mistakes, and two with uncertain relationships. After correcting these, CREST correctly determines relationship types for 93.5% of GP, 97.7% of AV, and 92.2% of HS pairs that have sufficient mutual relative data; the parent sex in 100% of HS and 99.6% of GP pairs; and it completes this analysis in 2.8 h including IBD detection in eight threads.
Topics: Female; Genetic Linkage; Genome, Human; Genotype; Humans; Male; Models, Genetic; Pedigree; Scotland
PubMed: 33385324
DOI: 10.1016/j.ajhg.2020.12.004 -
American Journal of Human Genetics Jul 2016Accurate estimation of shared ancestry is an important component of many genetic studies; current prediction tools accurately estimate pairwise genetic relationships up...
Accurate estimation of shared ancestry is an important component of many genetic studies; current prediction tools accurately estimate pairwise genetic relationships up to the ninth degree. Pedigree-aware distant-relationship estimation (PADRE) combines relationship likelihoods generated by estimation of recent shared ancestry (ERSA) with likelihoods from family networks reconstructed by pedigree reconstruction and identification of a maximum unrelated set (PRIMUS), improving the power to detect distant relationships between pedigrees. Using PADRE, we estimated relationships from simulated pedigrees and three extended pedigrees, correctly predicting 20% more fourth- through ninth-degree simulated relationships than when using ERSA alone. By leveraging pedigree information, PADRE can even identify genealogical relationships between individuals who are genetically unrelated. For example, although 95% of 13(th)-degree relatives are genetically unrelated, in simulations, PADRE correctly predicted 50% of 13(th)-degree relationships to within one degree of relatedness. The improvement in prediction accuracy was consistent between simulated and actual pedigrees. We also applied PADRE to the HapMap3 CEU samples and report new cryptic relationships and validation of previously described relationships between families. PADRE greatly expands the range of relationships that can be estimated by using genetic data in pedigrees.
Topics: Algorithms; Female; Haplotypes; Humans; Male; Models, Genetic; Pedigree; Reproducibility of Results
PubMed: 27374771
DOI: 10.1016/j.ajhg.2016.05.020