scholarly journals Large scale variation in the rate of germ-line de novo mutation, base composition, divergence and diversity in humans

PLoS Genetics ◽  
2018 ◽  
Vol 14 (3) ◽  
pp. e1007254 ◽  
Author(s):  
Thomas C. A. Smith ◽  
Peter F. Arndt ◽  
Adam Eyre-Walker
2017 ◽  
Author(s):  
Thomas Smith ◽  
Peter Arndt ◽  
Adam Eyre-Walker

AbstractIt has long been suspected that the rate of mutation varies across the human genome at a large scale based on the divergence between humans and other species. It is now possible to directly investigate this question using the large number of de novo mutations (DNMs) that have been discovered in humans through the sequencing of trios. We show that there is variation in the mutation rate at the 100KB, 1MB and 10MB scale that cannot be explained by variation at smaller scales, however the level of this variation is modest at large scales – at the 1MB scale we infer that ~90% of regions have a mutation rate within 50% of the mean. Different types of mutation show similar levels of variation and appear to vary in concert which suggests the pattern of mutation is relatively constant across the genome and hence unlikely to generate variation in GC-content. We confirm this using two different analyses. We find that genomic features explain less than 50% of the explainable variance in the rate of DNM. As expected the rate of divergence between species and the level of diversity within humans are correlated to the rate of DNM. However, the correlations are weaker than if all the variation in divergence was due to variation in the mutation rate. We provide evidence that this is due the effect of biased gene conversion on the probability that a mutation will become fixed. We find no evidence that linked selection affects the relationship between divergence and DNM density. In contrast to divergence, we find that most of the variation in diversity can be explained by variation in the mutation rate. Finally, we show that the correlation between divergence and DNM density declines as increasingly divergent species are considered.Author summaryUsing a dataset of 40,000 de novo mutations we show that there is large-scale variation in the mutation rate at the 100KB and 1MB scale. We show that different types of mutation vary in concert and in a manner that is not expected to generate variation in base composition; hence mutation bias is not responsible for the large-scale variation in base composition that is observed across human chromosomes. As expected large-scale variation in the rate of divergence between species and the variation within species across the genome, are correlated to the rate of mutation, but the correlation between divergence and the mutation rate is not as strong as they could be. We show that biased gene conversion is responsible for weakening the correlation. In contrast we find that most of the variation across the genome in diversity can be explained by variation in the mutation rate. Finally, we show that the correlation between the rate of mutation in humans and the divergence between humans and other species, weakens as the species become more divergent.


Genetics ◽  
1986 ◽  
Vol 113 (4) ◽  
pp. 897-918
Author(s):  
M Catharine McElwain

ABSTRACT The wings and abdomens of dysgenic and nondysgenic control flies were scored for the presence of clones of cells mutant for first and third chromosome markers. These exceptional clones can arise from mitotic recombination, de novo mutation or deletion, and P-M hybrid dysgenesis has been shown to increase the frequency of parallel processes occurring in germ-line cells. Particular attention was given to careful genetic and molecular characterization of all stocks and to providing adequate and appropriate controls so that even very small increases in somatic clone frequency due to P-M hybrid dysgenesis would be detected. No difference was found in the frequency, size distribution or anatomical distribution of mutant somatic clones correlated to hybrid dysgenesis, confirming previous indications. The potential adaptive significance of a germ-line restriction of P-M hybrid dysgenesis is discussed.


1996 ◽  
Vol 45 (1-2) ◽  
pp. 109-109
Author(s):  
E. Passarge

With a population incidence of about 1 in 15.000 retinoblastoma is the most frequent intraocular tumor in infancy and early childhood. It occurs in a hereditary form due to a germline mutation in about 40% of patients (30% de novo mutation and 10% transmission from an affected parent) and in a non-hereditary form due to a somatic mutation. The retinoblastoma gene is located on chromosome 13q14. This large gene of about 180 kb, consists of 27 exons of rather different sizes and encodes a 4.7 kb transcript with important function in cell cycle regulation. Individuals with bilateral, multifocal tumors are assumed to carry a germline mutation, whereas unilateral and unifocal tumors are generally due to the somatic form. Both copies of the RB1 gene must be in inactivated before a tumor develops. In about half of patients with the germline mutation the second event inactivating the second allele can be shown by loss of heterozygosity in tumor tissues compared to surrounding somatic tissues.Knowledge of the RB1 gene locus affords an opportunity to specify the type of mutation in many patients and arrive at a definitive molecular diagnosis. This is the basis for clinical evaluation and genetic counseling. The types of mutation are large scale deletions, small deletions and insertions, and base substitutions. There is no hot-spot for mutations.During the last several years we have studied more than 200 patients in search for large scale and small deletions and insertions, and missense mutations. Using intragenic polymorphic DNA markers we were able to identify the mutant haplotype in all familial cases. Direct DNA analysis identified a mutation in about 25% of patients. The distribution of lesions will be described in relation to the clinical situation.


2016 ◽  
Author(s):  
Chad Harland ◽  
Carole Charlier ◽  
Latifa Karim ◽  
Nadine Cambisano ◽  
Manon Deckers ◽  
...  

It has recently become possible to directly estimate the germ-line de novo mutation (dnm) rate by sequencing the whole genome of father-mother-offspring trios, and this has been conducted in human1–5, chimpanzee6, mice7, birds8 and fish9. In these studies dnm’s are typically defined as variants that are heterozygous in the offspring while being absent in both parents. They are assumed to have occurred in the germ-line of one of the parents and to have been transmitted to the offspring via the sperm cell or oocyte. This definition assumes that detectable mosaïcism in the parent in which the mutation occurred is negligible. However, instances of detectable mosaïcism or premeiotic clusters are well documented in humans and other organisms, including ruminants10–12. We herein take advantage of cattle pedigrees to show that as much as ∼30% to ∼50% of dnm’s present in a gamete may occur during the early cleavage cell divisions in males and females, respectively, resulting in frequent detectable mosaïcism and a high rate of sharing of multiple dnm’s between siblings. This should be taken into account to accurately estimate the mutation rate in cattle and other species.


2020 ◽  
Author(s):  
Salvador Guardiola ◽  
Monica Varese ◽  
Xavier Roig ◽  
Jesús Garcia ◽  
Ernest Giralt

<p>NOTE: This preprint has been retracted by consensus from all authors. See the retraction notice in place above; the original text can be found under "Version 1", accessible from the version selector above.</p><p><br></p><p>------------------------------------------------------------------------</p><p><br></p><p>Peptides, together with antibodies, are among the most potent biochemical tools to modulate challenging protein-protein interactions. However, current structure-based methods are largely limited to natural peptides and are not suitable for designing target-specific binders with improved pharmaceutical properties, such as macrocyclic peptides. Here we report a general framework that leverages the computational power of Rosetta for large-scale backbone sampling and energy scoring, followed by side-chain composition, to design heterochiral cyclic peptides that bind to a protein surface of interest. To showcase the applicability of our approach, we identified two peptides (PD-<i>i</i>3 and PD-<i>i</i>6) that target PD-1, a key immune checkpoint, and work as protein ligand decoys. A comprehensive biophysical evaluation confirmed their binding mechanism to PD-1 and their inhibitory effect on the PD-1/PD-L1 interaction. Finally, elucidation of their solution structures by NMR served as validation of our <i>de novo </i>design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.<i></i></p>


2020 ◽  
Author(s):  
Salvador Guardiola ◽  
Monica Varese ◽  
Xavier Roig ◽  
Jesús Garcia ◽  
Ernest Giralt

<p>NOTE: This preprint has been retracted by consensus from all authors. See the retraction notice in place above; the original text can be found under "Version 1", accessible from the version selector above.</p><p><br></p><p>------------------------------------------------------------------------</p><p><br></p><p>Peptides, together with antibodies, are among the most potent biochemical tools to modulate challenging protein-protein interactions. However, current structure-based methods are largely limited to natural peptides and are not suitable for designing target-specific binders with improved pharmaceutical properties, such as macrocyclic peptides. Here we report a general framework that leverages the computational power of Rosetta for large-scale backbone sampling and energy scoring, followed by side-chain composition, to design heterochiral cyclic peptides that bind to a protein surface of interest. To showcase the applicability of our approach, we identified two peptides (PD-<i>i</i>3 and PD-<i>i</i>6) that target PD-1, a key immune checkpoint, and work as protein ligand decoys. A comprehensive biophysical evaluation confirmed their binding mechanism to PD-1 and their inhibitory effect on the PD-1/PD-L1 interaction. Finally, elucidation of their solution structures by NMR served as validation of our <i>de novo </i>design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.<i></i></p>


2020 ◽  
Author(s):  
Salvador Guardiola ◽  
Monica Varese ◽  
Xavier Roig ◽  
Jesús Garcia ◽  
Ernest Giralt

<p>NOTE: This preprint has been retracted by consensus from all authors. See the retraction notice in place above; the original text can be found under "Version 1", accessible from the version selector above.</p><p><br></p><p>------------------------------------------------------------------------</p><p><br></p><p>Peptides, together with antibodies, are among the most potent biochemical tools to modulate challenging protein-protein interactions. However, current structure-based methods are largely limited to natural peptides and are not suitable for designing target-specific binders with improved pharmaceutical properties, such as macrocyclic peptides. Here we report a general framework that leverages the computational power of Rosetta for large-scale backbone sampling and energy scoring, followed by side-chain composition, to design heterochiral cyclic peptides that bind to a protein surface of interest. To showcase the applicability of our approach, we identified two peptides (PD-<i>i</i>3 and PD-<i>i</i>6) that target PD-1, a key immune checkpoint, and work as protein ligand decoys. A comprehensive biophysical evaluation confirmed their binding mechanism to PD-1 and their inhibitory effect on the PD-1/PD-L1 interaction. Finally, elucidation of their solution structures by NMR served as validation of our <i>de novo </i>design approach. We anticipate that our results will provide a general framework for designing target-specific drug-like peptides.<i></i></p>


2021 ◽  
Vol 14 (1) ◽  
Author(s):  
Kohei Kitagawa ◽  
Kensuke Matsumura ◽  
Masayuki Baba ◽  
Momoka Kondo ◽  
Tomoya Takemoto ◽  
...  

AbstractAutism spectrum disorder (ASD) is a highly prevalent neurodevelopmental disorder characterized by core symptoms of impaired social behavior and communication. Recent studies have suggested that the oxytocin system, which regulates social behavior in mammals, is potentially involved in ASD. Mouse models of ASD provide a useful system for understanding the associations between an impaired oxytocin system and social behavior deficits. However, limited studies have shown the involvement of the oxytocin system in the behavioral phenotypes in mouse models of ASD. We have previously demonstrated that a mouse model that carries the ASD patient-derived de novo mutation in the pogo transposable element derived with zinc finger domain (POGZWT/Q1038R mice), showed ASD-like social behavioral deficits. Here, we have explored whether oxytocin (OXT) administration improves impaired social behavior in POGZWT/Q1038R mice and found that intranasal oxytocin administration effectively restored the impaired social behavior in POGZWT/Q1038R mice. We also found that the expression level of the oxytocin receptor gene (OXTR) was low in POGZWT/Q1038R mice. However, we did not detect significant changes in the number of OXT-expressing neurons between the paraventricular nucleus of POGZWT/Q1038R mice and that of WT mice. A chromatin immunoprecipitation assay revealed that POGZ binds to the promoter region of OXTR and is involved in the transcriptional regulation of OXTR. In summary, our study demonstrate that the pathogenic mutation in the POGZ, a high-confidence ASD gene, impairs the oxytocin system and social behavior in mice, providing insights into the development of oxytocin-based therapeutics for ASD.


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