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Proceedings of the National Academy of... May 2024Measuring inbreeding and its consequences on fitness is central for many areas in biology including human genetics and the conservation of endangered species. However,...
Measuring inbreeding and its consequences on fitness is central for many areas in biology including human genetics and the conservation of endangered species. However, there is no consensus on the best method, neither for quantification of inbreeding itself nor for the model to estimate its effect on specific traits. We simulated traits based on simulated genomes from a large pedigree and empirical whole-genome sequences of human data from populations with various sizes and structures (from the 1,000 Genomes project). We compare the ability of various inbreeding coefficients ([Formula: see text]) to quantify the strength of inbreeding depression: allele-sharing, two versions of the correlation of uniting gametes which differ in the weight they attribute to each locus and two identical-by-descent segments-based estimators. We also compare two models: the standard linear model and a linear mixed model (LMM) including a genetic relatedness matrix (GRM) as random effect to account for the nonindependence of observations. We find LMMs give better results in scenarios with population or family structure. Within the LMM, we compare three different GRMs and show that in homogeneous populations, there is little difference among the different [Formula: see text] and GRM for inbreeding depression quantification. However, as soon as a strong population or family structure is present, the strength of inbreeding depression can be most efficiently estimated only if i) the phenotypes are regressed on [Formula: see text] based on a weighted version of the correlation of uniting gametes, giving more weight to common alleles and ii) with the GRM obtained from an allele-sharing relatedness estimator.
Topics: Humans; Inbreeding Depression; Models, Genetic; Pedigree; Genetics, Population; Inbreeding; Alleles
PubMed: 38687793
DOI: 10.1073/pnas.2315780121 -
Molecular Biology Reports Nov 2023Sindhi is a dual-purpose breed adapted to tropical environments. However, this breed has the smallest total population among indicine breeds in Brazil and the smallest...
BACKGROUND
Sindhi is a dual-purpose breed adapted to tropical environments. However, this breed has the smallest total population among indicine breeds in Brazil and the smallest effective number. In addition, the inbreeding coefficient is higher than 6.25% in ~ 60% of the population. Therefore, alternatives to increase genetic diversity are important. Within this context, the PRDM9 gene is particularly interesting since it is involved in meiotic recombination events, consequently enhancing genetic variability in the population by increasing the number of circulating haplotypes. Each allele of the gene induces recombination at a different hotspot. The larger the number of circulating alleles, the higher the recombination rate and the greater the genetic variability.
METHODS
The aim of this study was to characterize alleles of the PRDM9 gene in Sindhi cattle. The region of the zinc finger domains of the gene was amplified by PCR, genotyped, and sequenced for allele identification in 50 Sindhi animals.
RESULTS
Three alleles (A-cattle1, B-cattle14, and C-cattle19) and six genotypes (AA, BB, CC, AB, AC, and BC) were identified.
CONCLUSION
The allele variation of the PRDM9 gene in the Sindhi breed enables to guide the mating of animals with different genotypes/alleles and to promote genetic variability by recombination if there is intralocus variability.
Topics: Cattle; Animals; Genotype; Homologous Recombination; Haplotypes; Zinc Fingers; Base Sequence; Alleles
PubMed: 37658931
DOI: 10.1007/s11033-023-08778-7 -
Molecular Biology and Evolution Aug 2023Wang et al. (2023) recently proposed an approach to infer the history of human generation intervals from changes in mutation profiles over time. As the relative...
Wang et al. (2023) recently proposed an approach to infer the history of human generation intervals from changes in mutation profiles over time. As the relative proportions of different mutation types depend on the ages of parents, binning variants by the time they arose allows for the inference of changes in average paternal and maternal generation intervals. Applying this approach to published allele age estimates, Wang et al. (2023) inferred long-lasting sex differences in average generation times and surprisingly found that ancestral generation times of West African populations remained substantially higher than those of Eurasian populations extending tens of thousands of generations into the past. Here, we argue that the results and interpretations in Wang et al. (2023) are primarily driven by noise and biases in input data and a lack of validation using independent approaches for estimating allele ages. With the recent development of methods to reconstruct genome-wide gene genealogies, coalescence times, and allele ages, we caution that downstream analyses may be strongly influenced by uncharacterized biases in their output.
Topics: Humans; Female; Male; Uncertainty; Mutation; Alleles
PubMed: 37450583
DOI: 10.1093/molbev/msad160 -
Science China. Life Sciences Dec 2023Male sterility is an important trait in rice for hybrid rice (Oryza sativa) breeding. However, the factors involved in dominant male sterility are largely unknown. Here,...
Male sterility is an important trait in rice for hybrid rice (Oryza sativa) breeding. However, the factors involved in dominant male sterility are largely unknown. Here, we identified a gene from Sanming dominant genic male sterile rice, named Sanming dominant male sterility (SMS), and reported that an epi-allele of this locus contributes to male sterility. Segregation analysis attributed dominant male sterility to a single locus, SMS, which we characterized using a male-sterile near isogenic line (NIL) of rice cultivar 93-11. The SMS locus was heterozygous in the male-sterile 93-11 NIL, containing an epi-allele identical to that in 93-11, and an epi-allele identical to that in rice cultivar Nipponbare, which we refer to as SMS and SMS, respectively. SMS is silent and hyper-methylated, whereas SMS is expressed and hypo-methylated in the 93-11 NIL. Overexpressing SMS led to male sterility. Mutations in SMS rescued the male sterility of the 93-11 NIL. Interestingly, we observed the duplication of SMS in Nipponbare, but did not observe the duplication of SMS in 93-11. Together, these findings suggest that the reduced methylation and enhanced expression of the SMS epi-allele in the 93-11 NIL is responsible for its role in conferring dominant male sterility.
Topics: Alleles; Oryza; Phenotype; Plant Breeding; Plant Infertility
PubMed: 37930474
DOI: 10.1007/s11427-023-2457-7 -
Medicina (Kaunas, Lithuania) Aug 2023: Specific Learning Disorder (SLD) is a complex neurobiological disorder characterized by a persistent difficult in reading (dyslexia), written expression (dysgraphia),...
: Specific Learning Disorder (SLD) is a complex neurobiological disorder characterized by a persistent difficult in reading (dyslexia), written expression (dysgraphia), and mathematics (dyscalculia). The hereditary and genetic component is one of the underlying causes of SLD, but the relationship between genes and the environment should be considered. Several genetic studies were performed in different populations to identify causative genes. : Here, we show the analysis of 9 multiplex families with at least 2 individuals diagnosed with SLD per family, with a total of 37 persons, 21 of whom are young subjects with SLD, by means of Next-Generation Sequencing (NGS) to identify possible causative mutations in a panel of 15 candidate genes: , , , , , , , , , , , , , , and . We detected, in eight families out nine, SNP variants in the , , , and genes, even if in silico analysis did not show any causative effect on this behavioral condition. In all cases, the mutation was transmitted by one of the two parents, thus excluding the case of de novo mutation. Moreover, the parent carrying the allelic variant transmitted to the children, in six out of seven families, reports language difficulties. : Although the present results cannot be considered conclusive due to the limited sample size, the identification of genetic variants in the above genes can provide input for further research on the same, as well as on other genes/mutations, to better understand the genetic basis of this disorder, and from this perspective, to better understand also the neuropsychological and social aspects connected to this disorder, which affects an increasing number of young people.
Topics: Child; Humans; Adolescent; Specific Learning Disorder; Nerve Tissue Proteins; Receptors, Immunologic; Alleles; High-Throughput Nucleotide Sequencing; Microtubule-Associated Proteins
PubMed: 37629793
DOI: 10.3390/medicina59081503 -
The Journal of Allergy and Clinical... Aug 2023Nearly 50 pathogenic genes and hundreds of pathogenic variants have been identified in monogenic autoinflammatory diseases (AIDs). Nonetheless, there are still many...
BACKGROUND
Nearly 50 pathogenic genes and hundreds of pathogenic variants have been identified in monogenic autoinflammatory diseases (AIDs). Nonetheless, there are still many genes for which the pathogenic mechanisms are poorly understood, and the pathogenicity of many candidate variants needs to be determined.
OBJECTIVE
Monogenic AIDs are a group of rare genetic diseases characterized by inflammation as the phenotype. With the development of next-generation sequencing, pathogenic genes have been widely reported and used for clinical screening and diagnosis. The International Society for Systemic Autoinflammatory Diseases has recognized approximately 50 pathogenic genes and hundreds of related pathogenic variants in monogenic AIDs. We plan to investigate these pathogenic variants by conducting a variant burden analysis to determine whether or not there are consistent characteristics.
METHODS
We performed a variant burden analysis on the Genome Aggregation Database cohort using the currently reported genetic variants in monogenic AIDs, analyzing the enrichment of allelic signatures and deleterious predictions at the variants. Allelic signatures were extracted from Genome Aggregation Database, and the deleterious predictions were extracted from existing tools. The features obtained from the variant burden analysis were applied to the Random Forest model to classify the pathogenicity of novel mutations.
RESULTS
Functional enrichment and network analysis of AID pathogenic genes have hinted at the possible involvement of unsuspected signals. The variant burden analysis demonstrated that the pathogenicity of a variant could not be reliably classified using only its allele frequency and deleterious predictions. However, variants of varying classifications of pathogenicity exhibited strikingly different patterns of the allelic signature in the upstream and downstream regions surrounding the variants. Furthermore, the distribution of deleterious variants surrounding the variants in the cohort varied significantly across pathogenicity categories. Finally, the cohort-based features extracted from the alleles were applied to the prediction of pathogenicity in monogenic AIDs, achieving superior prediction performance compared with other tools. The cohort-based features have potential applications across a more extensive variety of disease categories.
CONCLUSIONS
The pathogenicity of a variant can be effectively classified on the basis of variant frequency and deleterious prediction of the allele in the cohort, and this information can be used to improve the accuracy of the current classification of the pathogenicity of the variant.
Topics: Humans; Virulence; Gene Frequency; Phenotype; Alleles; Rare Diseases; Hereditary Autoinflammatory Diseases
PubMed: 37030591
DOI: 10.1016/j.jaci.2023.03.028 -
Genetics, Selection, Evolution : GSE May 2024Metafounders are a useful concept to characterize relationships within and across populations, and to help genetic evaluations because they help modelling the means and...
Metafounders are a useful concept to characterize relationships within and across populations, and to help genetic evaluations because they help modelling the means and variances of unknown base population animals. Current definitions of metafounder relationships are sensitive to the choice of reference alleles and have not been compared to their counterparts in population genetics-namely, heterozygosities, F coefficients, and genetic distances. We redefine the relationships across populations with an arbitrary base of a maximum heterozygosity population in Hardy-Weinberg equilibrium. Then, the relationship between or within populations is a cross-product of the form with being vectors of allele frequencies at markers in populations and . This is simply the genomic relationship of two pseudo-individuals whose genotypes are equal to twice the allele frequencies. We also show that this coding is invariant to the choice of reference alleles. In addition, standard population genetics metrics (inbreeding coefficients of various forms; F differentiation coefficients; segregation variance; and Nei's genetic distance) can be obtained from elements of matrix .
Topics: Animals; Gene Frequency; Models, Genetic; Genetics, Population; Heterozygote; Alleles; Genomics; Genotype; Genome
PubMed: 38698373
DOI: 10.1186/s12711-024-00891-w -
HLA Oct 2023Recently, haplo-identical transplantation with multiple HLA mismatches has become a viable option for stem cell transplants. Haplotype sharing detection requires the...
Recently, haplo-identical transplantation with multiple HLA mismatches has become a viable option for stem cell transplants. Haplotype sharing detection requires the imputation of donor and recipient. We show that even in high-resolution typing when all alleles are known, there is a 15% error rate in haplotype phasing, and even more in low-resolution typings. Similarly, in related donors, the parents' haplotypes should be imputed to determine what haplotype each child inherited. We propose graph-based family imputation (GRAMM) to phase alleles in family pedigree HLA typing data, and in mother-cord blood unit pairs. We show that GRAMM has practically no phasing errors when pedigree data are available. We apply GRAMM to simulations with different typing resolutions as well as paired cord-mother typings, and show very high phasing accuracy, and improved allele imputation accuracy. We use GRAMM to detect recombination events and show that the rate of falsely detected recombination events (false-positive rate) in simulations is very low. We then apply recombination detection to typed families to estimate the recombination rate in Israeli and Australian population datasets. The estimated recombination rate has an upper bound of 10%-20% per family (1%-4% per individual).
Topics: Child; Humans; Alleles; Australia; Haplotypes; Tissue Donors
PubMed: 37102220
DOI: 10.1111/tan.15075 -
American Journal of Human Genetics Oct 2023Pharmacogenomics (PGx) is an integral part of precision medicine and contributes to the maximization of drug efficacy and reduction of adverse drug event risk. Accurate...
Pharmacogenomics (PGx) is an integral part of precision medicine and contributes to the maximization of drug efficacy and reduction of adverse drug event risk. Accurate information on PGx allele frequencies improves the implementation of PGx. Nonetheless, curating such information from published allele data is time and resource intensive. The limited number of allelic variants in most studies leads to an underestimation of certain alleles. We applied the Pharmacogenomics Clinical Annotation Tool (PharmCAT) on an integrated 200K UK Biobank genetic dataset (N = 200,044). Based on PharmCAT results, we estimated PGx frequencies (alleles, diplotypes, phenotypes, and activity scores) for 17 pharmacogenes in five biogeographic groups: European, Central/South Asian, East Asian, Afro-Caribbean, and Sub-Saharan African. PGx frequencies were distinct for each biogeographic group. Even biogeographic groups with similar proportions of phenotypes were driven by different sets of dominant PGx alleles. PharmCAT also identified "no-function" alleles that were rare or seldom tested in certain groups by previous studies, e.g., SLCO1B131 in the Afro-Caribbean (3.0%) and Sub-Saharan African (3.9%) groups. Estimated PGx frequencies are disseminated via the PharmGKB (The Pharmacogenomics Knowledgebase: www.pharmgkb.org). We demonstrate that genetic biobanks such as the UK Biobank are a robust resource for estimating PGx frequencies. Improving our understanding of PGx allele and phenotype frequencies provides guidance for future PGx studies and clinical genetic test panel design, and better serves individuals from wider biogeographic backgrounds.
Topics: Humans; Pharmacogenetics; Alleles; Biological Specimen Banks; Precision Medicine; Gene Frequency; Liver-Specific Organic Anion Transporter 1
PubMed: 37757824
DOI: 10.1016/j.ajhg.2023.09.001 -
PeerJ 2024Whereas undetected species contribute to estimation of species diversity, undetected alleles have not been used to estimated genetic diversity. Although random sampling...
Whereas undetected species contribute to estimation of species diversity, undetected alleles have not been used to estimated genetic diversity. Although random sampling guarantees unbiased estimation of allele frequency and genetic diversity measures, using undetected alleles may provide biased but more precise estimators useful for conservation. We newly devised kernel density estimation (KDE) for allele frequency including undetected alleles and tested it in estimation of allele frequency and nucleotide diversity using population generated by coalescent simulation as well as well as real population data. Contrary to expectations, nucleotide diversity estimated by KDE had worse bias and accuracy. Allele frequency estimated by KDE was also worse except when the sample size was small. These might be due to finity of population and/or the curse of dimensionality. In conclusion, KDE of allele frequency does not contribute to genetic diversity estimation.
Topics: Gene Frequency; Alleles; Genetic Variation; Humans; Models, Genetic; Computer Simulation; Genetics, Population
PubMed: 38666077
DOI: 10.7717/peerj.17248