When man got his mtDNA deletions?

Somatic mtDNA mutations and deletions in particular are known to clonally expand within cells, eventually reaching detrimental intracellular concentrations. The possibility that clonal expansion is a slow process taking a lifetime had prompted an idea that founder mutations of mutant clones that cause mitochondrial dysfunction in the aged tissue might have originated early in life. If, conversely, expansion was fast, founder mutations should predominantly originate later in life. This distinction is important: indeed, from which mutations should we protect ourselves – those of early development/childhood or those happening at old age? Recently, high-resolution data describing the distribution of mtDNA deletions have been obtained using a novel, highly efficient method (Taylor et al., 2014). These data have been interpreted as supporting predominantly early origin of founder mutations. Re-analysis of the data implies that the data actually better fit mostly late origin of founders, although more research is clearly needed to resolve the controversy.mtDNA mutations, and in particular deletions, progressively increase with age and are suspected culprits of several age-related degenerative processes. Because there are hundreds or even thousands of mtDNA genomes per cell, increase in mutational load may include not only the increase in the number of cells containing mutant genomes, but also increase in the fraction of mutant mtDNA in each cell. Studies of mutational composition of individual cells showed that accumulation of mutations within a cell usually does not occur via accrual of random hits. Instead, mtDNA mutations ‘clonally expand’, that is, a single initial mutation multiplies within cell, replaces normal mtDNAs, eventually takes over the cell, and may impair its mitochondrial function. Expansion is possible because mtDNA molecules in a cell are persistently replicated, even in nondividing cells, where some of them are destroyed and replaced by replication of others. Half-life of murine mtDNA is on the order of several weeks (Korr et al., 1998). The result of clonal expansion is that different cells typically contain different types of mutations, while mutant genomes within a cell carry the same mutation. Mechanisms of expansion are still debated; possibilities range from neutral genetic drift to selection within the ‘population’ of intracellular mitochondria. In this commentary, we do not assume any particular mechanism and concentrate on the kinetics of expansion.Because expansion takes time, it is possible that founder mutations of expanded mutant clones that compromise mitochondria at old age might have occurred early in life. Indeed, if expansion was a slow process taking about a lifetime to conclude (Fig. ​(Fig.1A,1A, upper panel), then only those mutations that were generated early in life would have enough time to reach harmful intracellular concentration. In an utmost version of this scenario, there is little de novo mutagenesis and increase in mutations with age is mostly driven by clonal expansion of early founder mutations. The ‘slow’ scenario implies that, as far as mtDNA mutagenesis is concerned, we need to preserve mtDNA during early years or even during development and to be less worried about mutations that arise in older individuals.Open in a separate windowFigure 1The ‘slow’ and the ‘fast’ expansion scenarios and the predicted changes in the diversity and extent of expansion of mtDNA mutations with age. Diversity and extent of expansion can be directly measured and used to distinguish between the two scenarios. mtDNA molecules with different deletions are depicted by small circles of different bright colors. Wild-type mtDNA molecules and cells that never get mutations are not shown for simplicity. Of course in a real tissue, mutant cells are surrounded by a great majority of nonmutant cells.If, on the other hand, clonal expansion was rapid (Fig. ​(Fig.1B1B upper panel), then expanding mutations would swiftly fill up the cells in which founders had arisen and therefore stop expanding. Consequently, overall mutation load would soon ‘plateau off’ if mutants were not continuously occurring. So, in this scenario, the observed persistent increase in mutations with age must be driven by de novo mutagenesis, and most impairment in this scenario is caused by ‘late in life’ mutations, which therefore should be of primary concern. Despite importance of this question, there is still no consensus on which scenario is correct (Payne et al., 2011), (Khrapko, 2011), although the ‘early mutations’ hypothesis appeared more than a decade ago (Elson et al., 2001), (Khrapko et al., 2003).Figure ​Figure11 schematically depicts two characteristics of the mutational dynamics that distinguish between the two scenarios. First, the diversity, that is, number of different types of deletions (Supplemental Note 0), remains constant in the slow scenario (Fig. ​(Fig.1A),1A), but steadily increases in the fast scenario (Fig. ​(Fig.1B).1B). Second, the extent of expansion, that is, the average number of mutant mtDNA molecules per clonal expansion, should increase steadily throughout the lifespan in the slow, early mutations scenario. In contrast, in the fast scenario, extent of expansion should increase rapidly early in life, up to the point when the earliest mutations had enough time to expand to the limits of their host cells and increase much slower thereafter.Recent paper by Taylor et al. (Taylor et al., 2014) describes a new method called Digital Deletion Detection, based on enrichment of deletions by wild-type specific restriction digestion, massive single-molecule PCR in microdroplets, followed by next generation sequencing of the PCR products. This ‘3D’ approach for the first time provided a detailed frequency distribution for a large set of different deleted mtDNA molecules in human brain as a function of age. These data are sufficient to estimate diversity and level of expansion of mutations and therefore promise to help to distinguish between the fast and the slow scenarios. The authors found that a) the number of different types of deletions per sample (used as proxy of diversity) does not increase with age, while b) the ratio of total deletion frequency over the number of deletion types (used as proxy of expansion) does steadily increase with age. Consequently, the authors concluded that ‘diversity of unique deletions remains constant’ and that the ‘data supported the hypothesis that expansion of pre-existing mutations is the primary factor contributing to age-related accumulation of mtDNA deletions’, that is, the slow expansion scenario. We believe, however, that these data deserve more detailed analysis and more cautious interpretation.A striking feature of the data (Taylor et al., 2014) is that the types of deletions found in any two samples are almost completely different (Supplemental Note 1). The same pattern has been previously observed in muscle (Nicholas et al., 2009). To explain this, consider that deletions originate mostly from individual cells each containing clonal expansion of deletion of a certain type. Because there are very many potential types of deletions and much fewer clonal expansions per sample, only a small proportion of possible types of deletions are found in each sample, which explains why two samples typically have almost no deletions in common. Similarly, any two cells with clonal expansions from the same sample usually carry different types of deletion. With this in mind, we will reconsider interpretation of the data.First, consider diversity of deletions. Unfortunately, number of deletion types per sample normalized against the total number of deletions used by Taylor et al. as proxy of diversity is not an adequate measure. First, normalization against the total number of sampled deletion molecules is not justified because in a sample with clonal expansions, the number of types of deletions is not proportional to the number of sequenced molecules (Supplemental Note 2). Instead, the number of deletion types per sample is proportional to the size of the sample (i.e., the size of the tissue piece actually used for DNA isolation). Indeed, increasing sample size means including proportionally more cells with expansions. As discussed above, these additional cells contain different deletion types, so the number of deletion types will also increase roughly proportionally to the sample size. Sample size must be factored out of a rational measure of deletion diversity. The best proxy of sample size available in the original study (Taylor et al., 2014) is the number of mtDNA copies isolated from each sample. Thus, to factor out the sample size, we used the number of deletion types per 10¹⁰ mtDNA, (Fig. ​(Fig.2A).2A). This corrected measure shows rather strong (P < 0.0003) increase in diversity of mtDNA deletions with age (Supplemental Note 3), which fits the ‘fast’ expansion scenario (Fig. ​(Fig.1B1B).Open in a separate windowFigure 2The observed changes in diversity and extent of expansion of mtDNA mutations in brain with age in Taylor et al. data. (A) Diversity of mtDNA deletions (number of deletion types per 10¹⁰ mtDNA) shows strong increase with age (P < 0.0003), corroborating the ‘fast’ expansion scenario (Fig. ​(Fig.1B).1B). (B) The extent of expansion shows excessive variance and does not seem to support any of the two scenarios (neither ‘fast’ nor ‘slow’) to any significant extent. Interpretation of these data requires more detailed analysis.Next, we revisited the extent of expansion of clonal mutations. As a measure of expansion, we used the average of the actual numbers of deleted molecules per deletion type, same as in Fig 1A,B. Note that this measure is different from ‘expansion index’ (Taylor et al., 2014), defined as deletion frequency per deletion type. This is essentially the same measure we use, additionally divided by the number of all mtDNA molecules in the sample. Unfortunately, ‘expansion index’ so defined systematically increases with decreased sample size. This is because deletion frequency is not expected to systematically increase with sample size, while the number of deletion types is, as shown in the previous paragraph. Thus, in particular because old samples in this set tend to be smaller (Supplemental Fig. 4A), this measure is biased.Extent of expansion of mtDNA mutations is plotted versus age in Fig. ​Fig.2B.2B. Which theoretical expansion pattern, the ‘slow’ (Fig. ​(Fig.1A)1A) or the ‘fast’ (Fig. ​(Fig.1B),1B), better fits the actual data (Fig. ​(Fig.2B)?2B)? It looks like either fit is poor: the data are notoriously variable. We conclude that it is necessary to look beyond the coarse average measure of the expansion to interpret the data and explain the excessive variance (Supplemental Note 4).The characteristic biphasic shape of the predicted ‘fast’ plot (Fig. ​(Fig.1B)1B) results from the early large expanded mutations, which are absent in the ‘slow’ scenario (Fig. ​(Fig.1A).1A). We therefore used the data (Taylor et al., 2014) to estimate the size of expansions (Supplemental Note 5, Supplementary Table S1) and in particular, to look for large expansions in young tissue. Indeed, young samples do contain large clonal expansions, and there are four expansions more than 1000 copies in samples 30 years and younger (Table S1). This is consistent with our own observations of large expansions of deletions in single neurons of the young brain using a different approach – single-molecule amplification (Kraytsberg et al., 2006). In other words, although rapid expansion pattern in Fig. ​Fig.2B2B is obscured by large variance of the data, the hallmarks of fast expansion, that is, large early mutant expansions, are present in the tissue.An aspect of the data, however, is at odds either with the fast or the slow scenario. The distribution of expansion sizes at any age is rather gradual; that is, there is a large proportion of expansions of intermediate sizes, ranging from smallest detectable (typically about 10 molecules) up to those more than 1000 molecules. In contrast, according to the ‘slow’ expansion scenario, all expansions should be of approximately the same size, which should increase with age, turning ‘large’ at approximately the same time. The fast scenario, also in contradiction with observations, predicts that proportion of mutants contained in expansions of intermediate sizes markedly decreases with age (Supplemental Note 6).If neither of the scenarios fits the data, what kind of mutational dynamics could be responsible for the observed distribution (Taylor et al., 2014)? We believe that most plausible is a ‘mixed’ scenario, where expansions are fast in some cells and slow in other (‘fast’ and ‘slow expanders’, correspondingly), probably with the whole spectrum of expansion rates in between. Expansion rates may differ between cell types or between cells of the same type differing in individual activity, stress, levels of ROS, length of deletion (Fukui & Moraes, 2009), etc. An example of such a difference is given by myoblasts, which, unlike their descendant myofibers, support only very slow, if any, expansion of mtDNA deletions (Moraes et al., 1989).What does this mean with respect to the question in the title of this commentary – when do mtDNA deletions arise? In fact, if we accept the mixed scenario, then it follows that the share of late mutations is at least significant. Indeed, if late mutations played little role, then accumulation of mutations should have been markedly decelerating with age. This is because ‘fast expander’ cells are saturated with mutations early in life and increase in mutation load at older age is driven by progressively ‘slower expanders’, meaning slower increase in mutational load. In contrast with this prediction, accumulation of deletions observed in most tissues appears to aggressively accelerate with age and is traditionally approximated with an exponent. This is also true for the Taylor et al. (2014), which are better fit by accelerating curves than they are by linear function (Fig. S6). The fraction of deleted mtDNA increases over the lifespan by up to four orders of magnitude in highly affected brain areas such as substantia nigra and about three in less affected, such as cortex (Meissner et al., 2008). In principle, even such a dramatic increase in mutant fraction might be entirely driven by expansion of early founder mutations in slow scenario. Neurons contain thousands of mtDNA copies, so expansion alone could potentially sustain about four orders of magnitude increase in mutant fraction from single founder mutants mtDNA to fully mutant cells. However, accelerated accumulation of (expanded) mutations in mixed scenario can only be explained by generation of de novo mutations at older ages.The reality is probably more complicated than idealized scenarios considered above. For example, cells with expanded mutations may die preferentially. If true, this would make fast scenario/late origin even more plausible. Indeed, that would mean that the actual number of mutations that have reached full expansion at any age is higher than observed (extra mutations being those that had died), implying that mutations expand faster than it appears. Other refinements of the model are certainly possible. However, notable variability of the data makes testing hypotheses, in particular, complex ones, difficult. Excessive variability of data on mtDNA deletions has been observed before, for example Meissner et al., 2008, but have never been duly explored. Lack of replicate analyses hampers understanding of the source of variance and of the shape of the frequency distributions of mutations. The latter are indispensable for interpreting the data. Future studies seeking to explain dynamics of mutations with age must include multiple replicate measurements (Supplemental Note 7).In conclusion, re-analysis of the data (Taylor et al., 2014) challenges the authors’ inference that diversity of unique deletions remains constant with age and that expansion of pre-existing deletions is the primary factor contributing to age-related accumulation of mtDNA deletions. The data are more consistent with increasing diversity of deletions and significant impact of mutagenesis at older age. However, the issue is far from being solved, in part because of high variability of the data, and it awaits more detailed studies (Supplemental Note 7).     

Different ζ globin gene deletions among Black Americans

Summary Four types of chromosomes with a deletion between the human embryonic and globin genes were identified among 2.8% of 321 Black Americans from Georgia. Two deletions of approximately 11 kb which differed by about 300 bp occurred on chromosomes with or without a polymorphic Xba I site 5 to the globin gene [(X⁺) or (X^-)]. The deletions are identifiable in Xba I digests of genomic DNA using an or a globin gene probe which yield fragments of 23 kb from (X⁺)–^* chromosomes or 27 kb from (X^–)–^* chromosomes. Digestion with other enzymes and probing with both and probes gave fragments typical of the two globin gene deletions previously identified in Polynesians. Among Black Americans, these globin gene deletions have been found in combination with globin gene deletions in trans but not in cis. Homozygotes have not been found. Hematologic data on carriers of the globin gene deletions in association with Hb AS, SS, and SC suggest that these deletions have no effect on the function of the adult globin genes.     

Do mtDNA deletions drive premature aging in mtDNA mutator mice?

Deletions in mitochondrial DNA (mtDNA) have long been suspected to be involved in mammalian aging, but their role remains controversial. Recent research has demonstrated that relatively higher levels of mtDNA deletions correlate with premature aging in mtDNA mutator mice, which led to the conclusion that premature aging in these mice is driven by mtDNA deletions. However, it is reported here that the absolute level of deletions in mutator mice is quite low, especially when compared with the level of point mutations in these mice. It is thus argued that the available data are insufficient to conclude that mtDNA mutations drive premature aging in mtDNA mutator mice. It remains possible that clonal expansion of mtDNA deletions may result in sufficiently high levels to play a role in age-related dysfunction in some cells, but assessing this possibility will require studies of the distribution of these deletions among different cell types and in individual cells.     

Congenital heart defects and 22q11 deletions: which genes count?

Hemizygous deletions on the long arm of chromosome 22 (del22q11) are a relatively common cause of congenital heart disease. For some specific heart defects such as interrupted aortic arch type B and tetralogy of Fallot with absent pulmonary valve, del22q11 is probably the most frequent genetic cause. Although extensive gene searches have been successful in discovering many novel genes in the deleted segment, standard positional cloning has so far failed to demonstrate a role for any of these genes in the disease. We show how the use of experimental animal models is beginning to provide an insight into the developmental role of some of these genes, while novel genome manipulation technologies promise to dissect the genetic aspects of this complex syndrome.     

Effect of γ34.5 deletions on oncolytic herpes simplex virus activity in brain tumors

The ICP34.5 protein of herpes simplex virus (HSV) is involved in many aspects of viral pathogenesis; promoting neurovirulence, inhibiting interferon-induced shutoff of protein synthesis, interacting with PCNA and TBK1, inhibiting dendritic cell (DC) maturation, and binding to Beclin 1 to interfere with autophagy. Because of its key role in neuropathogenicity, the γ34.5 gene is deleted in all oncolytic HSVs (oHSVs) currently in clinical trial for treating malignant gliomas. Unfortunately, deletion of γ34.5 attenuates virus replication in cancer cells, especially human glioblastoma stem cells (GSCs). To develop new oHSVs for use in the brain and that replicate in GSCs, we explored the effect of deleting the γ34.5 Beclin 1 binding domain (BBD). To ensure cancer selectivity and safety, we inactivated the ICP6 gene (UL39, large subunit of ribonucleotide reductase), constructing ICP6 mutants with different γ34.5 genotypes: Δ68HR-6, intact γ34.5; Δ68H-6, γ34.5 BBD deleted; and 1716-6, γ34.5 deleted. Multimutated Δ68H-6 exhibited minimal neuropathogenicity in HSV-1-susceptible mice, as opposed to Δ68H and Δ68HR-6. It replicated well in human glioma cell lines and GSCs, effectively killing cells in vitro and prolonging survival of mice bearing orthotopic brain tumors. In contrast, 1716 and 1716-6 barely replicated in GSCs. Infection of glioma cells with Δ68H-6 and 1716-6 induced autophagy and increased phosphorylation of eIF2α, while inhibition of autophagy, by Beclin 1 short hairpin RNA (shRNA) knockdown or pharmacological inhibition, had no effect on virus replication or phosphorylated eIF2α (p-eIF2α) levels. Thus, Δ68H-6 represents a new oHSV vector that is safe and effective against a variety of brain tumor models.     

Molecular characterization and delineation of subtle deletions in de novo “balanced” chromosomal rearrangements

To test the hypothesis that the phenotypic abnormalities seen in cases with apparently balanced chromosomal rearrangements are the result of the presence of cryptic deletions or duplications of chromosomal material near the breakpoints, we analyzed three cases with apparently balanced chromosomal rearrangements and phenotypic abnormalities. We characterized the breakpoints in these cases by using microsatellite analysis by polymerase chain reaction and fluorescence in situ hybridization analysis of yeast artificial chromosome clones selected from the breakpoint regions. Molecular characterization of the translocation breakpoint in patient 1 [46,XY,t(2;6)(p22.2;q23.1)] showed the presence of a 4- to 6-Mb cryptic deletion between markers D6S412 and D6S1705 near the 6q23.1 breakpoint. Molecular characterization of the proximal inversion 7q22.1 breakpoint in patient 2 [46,XY,inv(7)(q22.1q32.1)] revealed the presence of a 4-Mb cryptic deletion between D7S651 and D7S515 markers. No deletion or duplication of chromosomal material was found near the breakpoints in patient 3 [46,XX,t(2;6)(q33.1;p12.2)]. Our study suggests that a systematic molecular study of breakpoints should be carried out in cases with apparently balanced chromosomal rearrangements and phenotypic abnormalities, because cryptic deletions near the breakpoints may explain the phenotypic abnormalities in these cases. Received: 9 March 1998 / Accepted: 24 April 1998     

Analysis of the regulation of Escherichia coli alkaline phosphatase synthesis using deletions and φ80 transducing phages

φ80 transducing phages for the proC², phoA and phoB genes of Escherichia coli have been obtained. Two mutants have been isolated, in which the brnQ, phoA, proC, phoB (and possibly phoR) genes have been deleted. Derivatives of a phoA, phoB deletion strain which are lysogenic for a φ80phoA transducing phage make only very low levels of alkaline phosphatase activity. These results are in agreement with a positive control mechanism for the regulation of alkaline phosphatase synthesis.     

Utero-vaginal aplasia (Mayer-Rokitansky-Küster-Hauser syndrome) associated with deletions in known DiGeorge or DiGeorge-like loci

Background

Persons affected by neurofibromatosis type 1 (NF1) have a decreased survival, yet information on NF1-associated mortality is limited.

Methods/Aim

The National Mortality Database and individual Multiple-Causes-of-Death records were used to estimate NF1-associated mortality in Italy in the period 1995-2006, to compare the distribution of age at death (as a proxy of survival) to that of the general population and to evaluate the relation between NF1 and other medical conditions by determining whether the distribution of underlying causes of NF1-associated deaths differs from that of general population.

Results

Of the nearly 6.75 million deaths in the study period, 632 had a diagnosis of NF1, yet for nearly three-fourths of them the underlying cause was not coded as neurofibromatosis. The age distribution showed that NF1-associated deaths also occurred among the elderly, though mortality in early ages was high. The mean age for NF1-associated death was approximately 20 years lower than that for the general population. The gender differential may suggest that women are affected by more severe NF1-related complications, or they may simply reflect a greater tendency for NF1 to be reported on the death certificates of young women. Regarding the relation with other medical conditions, we found an excess, as the underlying cause of death, for malignant neoplasm of connective and other soft tissue and brain, but not for other sites. We also found an excess for obstructive chronic bronchitis and musculoskeletal system diseases among elderly persons.

Conclusion

This is the first nationally representative population-based study on NF1-associated mortality in Italy. It stresses the importance of the Multiple-Causes-of-Death Database in providing a more complete picture of mortality for conditions that are frequently not recorded as the underlying cause of death, or to study complex chronic diseases or diseases that have no specific International Classification of Diseases code, such as NF1. It also highlights the usefulness of already available data when a surveillance system is not fully operational.     

Detection of disease-associated deletions in case–control studies using SNP genotypes with application to rheumatoid arthritis

Genomic deletions have long been known to play a causative role in microdeletion syndromes. Recent whole-genome genetic studies have shown that deletions can increase the risk for several psychiatric disorders, suggesting that genomic deletions play an important role in the genetic basis of complex traits. However, the association between genomic deletions and common, complex diseases has not yet been systematically investigated in gene mapping studies. Likelihood-based statistical methods for identifying disease-associated deletions have recently been developed for familial studies of parent-offspring trios. The purpose of this study is to develop statistical approaches for detecting genomic deletions associated with complex disease in case–control studies. Our methods are designed to be used with dense single nucleotide polymorphism (SNP) genotypes to detect deletions in large-scale or whole-genome genetic studies. As more and more SNP genotype data for genome-wide association studies become available, development of sophisticated statistical approaches will be needed that use these data. Our proposed statistical methods are designed to be used in SNP-by-SNP analyses and in cluster analyses based on combined evidence from multiple SNPs. We found that these methods are useful for detecting disease-associated deletions and are robust in the presence of linkage disequilibrium using simulated SNP data sets. Furthermore, we applied the proposed statistical methods to SNP genotype data of chromosome 6p for 868 rheumatoid arthritis patients and 1,197 controls from the North American Rheumatoid Arthritis Consortium. We detected disease-associated deletions within the region of human leukocyte antigen in which genomic deletions were previously discovered in rheumatoid arthritis patients.     

Effect of deletions 5′ to the translation initiation sequence on the expression of an mRNA in animal cells

To learn if an mRNA·18S rRNA interaction or a special secondary structure in the mRNA start region is essential for translation in eukaryotic cells, we constructed recombinant plasmids with the SV40 early promoter 5 to part of the Escherichia coli tuf B-lacZ gene. Deletion of bases potentially complementary to the 18S rRNA highly increased the transient -galactosidase expressed in transfected CHO cells. Deletion of bases that fostered formation of potential hairpins with the mRNA 5-terminus or altered the structure of the coding region reduced -galactosidase activity suggesting that these features of the mRNA secondary structure may be essential for initiation of translation. Computer aided analysis of the potential structure of 290 mRNAs suggests these are conserved features of the initiation region.     

Region-specific deletions of RIM1 reproduce a subset of global RIM1α(-/-) phenotypes

The presynaptic protein RIM1α mediates multiple forms of presynaptic plasticity at both excitatory and inhibitory synapses. Previous studies of mice lacking RIM1α (RIM1α(-/-) throughout the brain showed that deletion of RIM1α results in multiple behavioral abnormalities. In an effort to begin to delineate the brain regions in which RIM1 deletion mediates these abnormal behaviors, we used conditional (floxed) RIM1 knockout mice (fRIM1). By crossing these fRIM1 mice to previously characterized transgenic cre lines, we aimed to delete RIM1 selectively in the dentate gyrus (DG), using a specific preproopiomelanocortin promoter driving cre recombinase (POMC-cre) line , and in pyramidal neurons of the CA3 region of hippocampus, using the kainate receptor subunit 1 promoter driving cre recombinase (KA-cre). Neither of these cre driver lines was uniquely selective to the targeted regions. In spite of this, we were able to reproduce a subset of the global RIM1α(-/-) behavioral abnormalities, thereby narrowing the brain regions in which loss of RIM1 is sufficient to produce these behavioral differences. Most interestingly, hypersensitivity to the pyschotomimetic MK-801 was shown in mice lacking RIM1 selectively in the DG, arcuate nucleus of the hypothalamus and select cerebellar neurons, implicating novel brain regions and neuronal subtypes in this behavior.     

A quantitative assay to detect α-thalassemia deletions and triplications using multiplex nested real-time quantitative polymerase chain reaction

Increasing evidence indicates that copy number variants (CNVs) have great relevance to common human diseases. In α-thalassemia, clinical phenotypes are related to genotypes, specifically copy number changes in the human α-globin gene cluster. Assays are available for high-throughput screening of unknown CNVs genome-wide and also for targeted CNV genotyping at loci associated with genetic disorders. Here we describe a universal quantitative approach based on nested real-time quantitative polymerase chain reaction for accurate determination of copy numbers at multiple particular gene loci. We used the α-globin gene as a model system, obtaining the reproducibility and sensitivity to analyze different gene copies and testing 95 DNA samples with 16 different known genotypes. Our results showed that this approach has high sensitivity and low standard deviations for correctly genotyping DNA samples containing different copy numbers of the α1 and α2 globin genes. Our method is rapid, simple, and reliable, and it could be used to simultaneously screen for α-thalassemia deletions or triplications. Moreover, it has potential as a versatile technology for the rapid genotyping of known CNVs in a targeted region.     

The effect of the 3′ → 5′ exonuclease of T7 DNA polymerase on frameshifts and deletions

Both spontaneous frameshift mutation and deletion mutation were measured in a T7 phage deficient in the 3′ → 5′ exonuclease of T7 DNA polymerase. It was found that the absence of this exonuclease caused a marked increase in the revision of both plus one and minus one mutations. The exonuclease deficiency caused essentially no effect on the frequency of deletion between 10-bp direct repeats even when the segment between the direct repeats contained a 25-bp palindrome.     

Analysis of developmental switching in transgenic mice with 5′ and 3′ deletions in the human β globin gene

Our interest in thecis-acting elements that promote the up-regulation of the globin gene has led to a systematic deletion analysis of portions of the globin gene in the context of the HS2 and globin gene using transgenic mice. In constructs that delete the 5 region to only 265 bp, high-level erythroid-specific expression was observed. Further deletion to 122 bp, however, results in significantly reduced expression levels A substitution of a minilocus control region for the single HS2 site was also produced, resulting in increased globin expression over that seen with the HS2 alone. These results are consistent with the presence of an enhancer-like element between –122 and –265. In addition, a construct in which the entire globin gene promoter was replaced by a thymidine kinase promoter was tested. Interestingly, no expression was detected in these transgenic mice. This may indicate the requirement for an erythroid-specific promoter to drive this gene. Finally, the 3 region of the globin gene was deleted in order to examine the effect of a previously defined 3 enhancer region. With deletion of this region, the expression of the human globin gene in transgenic mice is unchanged relative to the parental constructs.     

Parental somatic mosaicism for CNV deletions – A need for more sensitive and precise detection methods in clinical diagnostics settings

To further assess the scale and level of parental somatic mosaicism, we queried the CMA database at Baylor Genetics. We selected 50 unrelated families where clinically relevant apparent de novo CNV-deletions were found in the affected probands. Parental blood samples screening using deletion junction-specific PCR revealed four parents with somatic mosaicism. Droplet digital PCR (ddPCR), qPCR, and amplicon-based next-generation sequencing (NGS) were applied to validate these findings. Using ddPCR levels of mosaicism ranged from undetectable to 18.5%. Amplicon-based NGS and qPCR for the father with undetectable mosaicism was able to detect mosaicism at 0.39%. In one mother, ddPCR analysis revealed 15.6%, 10.6%, 8.2%, and undetectable levels of mosaicism in her blood, buccal cells, saliva, and urine samples, respectively. Our data suggest that more sensitive and precise methods, e.g. CNV junction-specific LR-PCR, ddPCR, or qPCR may allow for a more refined assessment of the potential disease recurrence risk for an identified variant.     

Mutant OmpF porins of Yersinia pseudotuberculosis with deletions of external loops: Structure–functional and immunochemical properties

Recombinant mutant OmpF porins from Yersinia pseudotuberculosis outer membrane were obtained using site-directed mutagenesis. Here we used four OmpF mutants where single extracellular loops L1, L4, L6, and L8 were deleted one at a time. The proteins were expressed in Escherichia coli at levels comparable to full-sized recombinant OmpF porin and isolated from the inclusion bodies. Purified trimers of the mutant porins were obtained after dialysis and consequent ion-exchange chromatography. Changes in molecular and spatial structure of the mutants obtained were studied using SDS–PAGE and optical spectroscopy (circular dichroism and intrinsic protein fluorescence). Secondary and tertiary structure of the mutant proteins was found to have some features in comparison with that of the full-sized recombinant OmpF. As shown by bilayer lipid membrane technique, the pore-forming activity of purified mutant porins was identical to OmpF porin isolated from the bacterial outer membrane. Lacking of the external loops mentioned above influenced significantly upon the antigenic structure of the porin as demonstrated using ELISA.     

α-Globin gene deletions associated with αAand αG Philadelphiagenes in an Algerian family that includes two Hb G homozygotes

Summary An Algerian family with a high degree of consanguinity and including two homozygotes for Hb-G Philadelphia is presented. Whether homozygotes or heterozygotes, all subjects displayed microcytosis (with various degrees of poikilocytosis) and a moderately depressed -globin chain synthesis. Hb H and Heinz bodies were absent. DNA mapping revealed the presence of 3.7 kb deletion resulting from the rightward type of recombination event between ₂ and ₁ genes on both the ^A/and the ^G chromosomes. Such data indicate that the –^A/ and –^G/ haplotypes are involved and suggest that the –^G/ haplotype, which is very rare in Algeria, has an African Black origin. In subjects with genotype (–^A/–^G/) or (–^G/–^G/), the output of the remaining genes is sufficiently high to avoid the appearance of Hb H. This situation contrasts with that reported in an Algerian patient, who had a (–^A/–^A/) genotype but who was producing Hb H (Whitelaw et al. 1980). The data collected from this family suggest that the –^A/ haplotypes are heterogeneous in Algerians.