Exploring FGFR3 Mutations in the Male Germline: Implications for Clonal Germline Expansions and Paternal Age-Related Dysplasias.

Delayed fatherhood results in a higher risk of inheriting a new germline mutation that might result in a congenital disorder in the offspring. In particular, some FGFR3 mutations increase in frequency with age, but there are still a large number of uncharacterized FGFR3 mutations that could be expanding in the male germline with potentially early- or late-onset effects in the offspring. Here, we used digital polymerase chain reaction to assess the frequency and spatial distribution of 10 different FGFR3 missense substitutions in the sexually mature male germline. Our functional assessment of the receptor signaling of the variants with biophysical methods showed that 9 of these variants resulted in a higher activation of the receptor´s downstream signaling, resulting in 2 different expansion behaviors. Variants that form larger subclonal expansions in a dissected postmortem testis also showed a positive correlation of the substitution frequency with the sperm donor's age, and a high and ligand-independent FGFR3 activation. In contrast, variants that measured high FGFR3 signaling and elevated substitution frequencies independent of the donor's age did not result in measurable subclonal expansions in the testis. This suggests that promiscuous signal activation might also result in an accumulation of mutations before the sexual maturation of the male gonad with clones staying relatively constant in size throughout time. Collectively, these results provide novel insights into our understanding of the mutagenesis of driver mutations and their resulting mosaicism in the male germline with important consequences for the transmission and recurrence of associated disorders.

Germline selection of PTPN11 (HGNC:9644) variants make a major contribution to both Noonan syndrome's high birth rate and the transmission of sporadic cancer variants resulting in fetal abnormality.

Some spontaneous germline gain-of-function mutations promote spermatogonial stem cell clonal expansion and disproportionate variant sperm production leading to unexpectedly high transmission rates for some human genetic conditions. To measure the frequency and spatial distribution of de novo mutations we divided three testes into 192 pieces each and used error-corrected deep-sequencing on each piece. We focused on PTPN11 (HGNC:9644) Exon 3 that contains 30 different PTPN11 Noonan syndrome (NS) mutation sites. We found 14 of these variants formed clusters among the testes; one testis had 11 different variant clusters. The mutation frequencies of these different clusters were not correlated with their case-recurrence rates nor were case recurrence rates of PTPN11 variants correlated with their tyrosine phosphatase levels thereby confusing PTPN11's role in germline clonal expansion. Six of the PTPN11 exon 3 de novo variants associated with somatic mutation-induced sporadic cancers (but not NS) also formed testis clusters. Further, three of these six variants were observed among fetuses that underwent prenatal ultrasound screening for NS-like features. Mathematical modeling showed that germline selection can explain both the mutation clusters and the high incidence of NS (1/1000-1/2500).

The roles of APOBEC-mediated RNA editing in SARS-CoV-2 mutations, replication and fitness.

During COVID-19 pandemic, mutations of SARS-CoV-2 produce new strains that can be more infectious or evade vaccines. Viral RNA mutations can arise from misincorporation by RNA-polymerases and modification by host factors. Analysis of SARS-CoV-2 sequence from patients showed a strong bias toward C-to-U mutation, suggesting a potential mutational role by host APOBEC cytosine deaminases that possess broad anti-viral activity. We report the first experimental evidence demonstrating that APOBEC3A, APOBEC1, and APOBEC3G can edit on specific sites of SARS-CoV-2 RNA to produce C-to-U mutations. However, SARS-CoV-2 replication and viral progeny production in Caco-2 cells are not inhibited by the expression of these APOBECs. Instead, expression of wild-type APOBEC3 greatly promotes viral replication/propagation, suggesting that SARS-CoV-2 utilizes the APOBEC-mediated mutations for fitness and evolution. Unlike the random mutations, this study suggests the predictability of all possible viral genome mutations by these APOBECs based on the UC/AC motifs and the viral genomic RNA structure.

The Roles of APOBEC-mediated RNA Editing in SARS-CoV-2 Mutations, Replication and Fitness.

During COVID-19 pandemic, mutations of SARS-CoV-2 produce new strains that can be more infectious or evade vaccines. Viral RNA mutations can arise from misincorporation by RNA-polymerases and modification by host factors. Analysis of SARS-CoV-2 sequence from patients showed a strong bias toward C-to-U mutation, suggesting a potential mutational role by host APOBEC cytosine deaminases that possess broad anti-viral activity. We report the first experimental evidence demonstrating that APOBEC3A, APOBEC1, and APOBEC3G can edit on specific sites of SARS-CoV-2 RNA to produce C-to-U mutations. However, SARS-CoV-2 replication and viral progeny production in Caco-2 cells are not inhibited by the expression of these APOBECs. Instead, expression of wild-type APOBEC3 greatly promotes viral replication/propagation, suggesting that SARS-CoV-2 utilizes the APOBEC-mediated mutations for fitness and evolution. Unlike the random mutations, this study suggests the predictability of all possible viral genome mutations by these APOBECs based on the UC/AC motifs and the viral genomic RNA structure.

Quantitative Biology Undergraduate Major at the University of Southern California.

In 2017, the University of Southern California started a new undergraduate major in quantitative biology. This major combines training in the biological sciences, mathematics, and computer science to prepare students for 21st century biology and medicine. In this article I will discuss the curriculum, the first two cohorts of graduates, the current students, and future plans for the major.

The Roles of APOBEC-mediated RNA Editing in SARS-CoV-2 Mutations, Replication and Fitness.

During COVID-19 pandemic, mutations of SARS-CoV-2 produce new strains that can be more infectious or evade vaccines. Viral RNA mutations can arise from misincorporation by RNA-polymerases and modification by host factors. Analysis of SARS-CoV-2 sequence from patients showed a strong bias toward C-to-U mutation, suggesting a potential mutational role by host APOBEC cytosine deaminases that possess broad anti-viral activity. We report the first experimental evidence demonstrating that APOBEC3A, APOBEC1, and APOBEC3G can edit on specific sites of SARS-CoV-2 RNA to produce C-to-U mutations. However, SARS-CoV-2 replication and viral progeny production in Caco-2 cells are not inhibited by the expression of these APOBECs. Instead, expression of wild-type APOBEC3 greatly promotes viral replication/propagation, suggesting that SARS-CoV-2 utilizes the APOBEC-mediated mutations for fitness and evolution. Unlike the random mutations, this study suggests the predictability of all possible viral genome mutations by these APOBECs based on the UC/AC motifs and the viral genomic RNA structure. ONE-SENTENCE SUMMARY: Efficient Editing of SARS-CoV-2 genomic RNA by Host APOBEC deaminases and Its Potential Impacts on the Viral Replication and Emergence of New Strains in COVID-19 Pandemic.

Incorporating antagonistic pleiotropy into models for molecular replicators.

In modern cells, chromosomal genes composed of DNA encode multi-subunit protein/RNA complexes that catalyze the replication of the chromosome and cell. One prevailing theory for the origin of life posits an early stage involving self-replicating macromolecules called replicators, which can be considered genes capable of self-replication. One prevailing theory for the genetics of aging in humans and other organisms is antagonistic pleiotropy, which posits that a gene can be beneficial in one context, and detrimental in another context. We previously reported that the conceptual simplicity of molecular replicators facilitates the generation of two simple models involving antagonistic pleiotropy. Here a third model is proposed, and each of the three models is presented with improved definition of the time variable. Computer simulations were used to calculate the proliferation of a hypothetical two-subunit replicator (AB), when one of the two subunits (B) exhibits antagonistic pleiotropy, leading to an advantage for B to be unstable. In model 1, instability of B yields free A subunits, which in turn stimulate the activity of other AB replicators. In model 2, B is lost and sometimes replaced by a more active mutant form, B'. In model 3, B becomes damaged and loses activity, and its instability allows it to be replaced by a new B. For each model, conditions were identified where instability of B was detrimental, and where instability of B was beneficial. The results are consistent with the hypothesis that antagonistic pleiotropy can promote molecular instability and system complexity, and provide further support for a model linking aging and evolution.

Predicting the Number of Bases to Attain Sufficient Coverage in High-Throughput Sequencing Experiments.

For many types of high-throughput sequencing experiments, success in downstream analysis depends on attaining sufficient coverage for individual positions in the genome. For example, when identifying single-nucleotide variants de novo, the number of reads supporting a particular variant call determines our confidence in that variant call. If sequenced reads are distributed uniformly along the genome, the coverage of a nucleotide position is easily approximated by a Poisson distribution, with rate equal to average sequencing depth. Unfortunately, as has become well known, high-throughput sequencing data are never uniform. The numerous factors contributing to variation in coverage have resisted attempts at direct modeling and change along with minor adjustments in the underlying technology. We propose a new nonparametric method to predict the portion of a genome that will attain some specified minimum coverage, as a function of sequencing effort, using information from a shallow sequencing experiment from the same library. Simulations show our approach performs well under an array of distributional assumptions that deviate from uniformity. We applied this approach to estimate coverage at varying depths in single-cell whole-genome sequencing data from multiple protocols. These resulted in highly accurate predictions, demonstrating the effectiveness of our approach in analyzing complexity of sequencing libraries and optimizing design of sequencing experiments.

AID-RNA polymerase II transcription-dependent deamination of IgV DNA.

Activation-induced deoxycytidine deaminase (AID) initiates somatic hypermutation (SHM) in immunoglobulin variable (IgV) genes to produce high-affinity antibodies. SHM requires IgV transcription by RNA polymerase II (Pol II). A eukaryotic transcription system including AID has not been reported previously. Here, we reconstitute AID-catalyzed deamination during Pol II transcription elongation in conjunction with DSIF transcription factor. C→T mutations occur at similar frequencies on non-transcribed strand (NTS) and transcribed strand (TS) DNA. In contrast, bacteriophage T7 Pol generates NTS mutations predominantly. AID-Pol II mutations are strongly favored in WRC and WGCW overlapping hot motifs (W = A or T, R = A or G) on both DNA strands. Single mutations occur on 70% of transcribed DNA clones. Mutations are correlated over a 15 nt distance in multiply mutated clones, suggesting that deaminations are catalyzed processively within a stalled or backtracked transcription bubble. Site-by-site comparisons for biochemical and human memory B-cell mutational spectra in an IGHV3-23*01 target show strongly favored deaminations occurring in the antigen-binding complementarity determining regions (CDR) compared to the framework regions (FW). By exhibiting consistency with B-cell SHM, our in vitro data suggest that biochemically defined reconstituted Pol II transcription systems can be used to investigate how, when and where AID is targeted.

Single cell lineage tracing reveals a role for TgfßR2 in intestinal stem cell dynamics and differentiation.

Intestinal stem cells (ISCs) are maintained by a niche mechanism, in which multiple ISCs undergo differential fates where a single ISC clone ultimately occupies the niche. Importantly, mutations continually accumulate within ISCs creating a potential competitive niche environment. Here we use single cell lineage tracing following stochastic transforming growth factor ß receptor 2 (TgfßR2) mutation to show cell autonomous effects of TgfßR2 loss on ISC clonal dynamics and differentiation. Specifically, TgfßR2 mutation in ISCs increased clone survival while lengthening times to monoclonality, suggesting that Tgfß signaling controls both ISC clone extinction and expansion, independent of proliferation. In addition, TgfßR2 loss in vivo reduced crypt fission, irradiation-induced crypt regeneration, and differentiation toward Paneth cells. Finally, altered Tgfß signaling in cultured mouse and human enteroids supports further the in vivo data and reveals a critical role for Tgfß signaling in generating precursor secretory cells. Overall, our data reveal a key role for Tgfß signaling in regulating ISCs clonal dynamics and differentiation, with implications for cancer, tissue regeneration, and inflammation.

Estimating Exceptionally Rare Germline and Somatic Mutation Frequencies via Next Generation Sequencing.

We used targeted next generation deep-sequencing (Safe Sequencing System) to measure ultra-rare de novo mutation frequencies in the human male germline by attaching a unique identifier code to each target DNA molecule. Segments from three different human genes (FGFR3, MECP2 and PTPN11) were studied. Regardless of the gene segment, the particular testis donor or the 73 different testis pieces used, the frequencies for any one of the six different mutation types were consistent. Averaging over the C>T/G>A and G>T/C>A mutation types the background mutation frequency was 2.6x10-5 per base pair, while for the four other mutation types the average background frequency was lower at 1.5x10-6 per base pair. These rates far exceed the well documented human genome average frequency per base pair (~10-8) suggesting a non-biological explanation for our data. By computational modeling and a new experimental procedure to distinguish between pre-mutagenic lesion base mismatches and a fully mutated base pair in the original DNA molecule, we argue that most of the base-dependent variation in background frequency is due to a mixture of deamination and oxidation during the first two PCR cycles. Finally, we looked at a previously studied disease mutation in the PTPN11 gene and could easily distinguish true mutations from the SSS background. We also discuss the limits and possibilities of this and other methods to measure exceptionally rare mutation frequencies, and we present calculations for other scientists seeking to design their own such experiments.

Germline Stem Cell Competition, Mutation Hot Spots, Genetic Disorders, and Older Fathers.

Some de novo human mutations arise at frequencies far exceeding the genome average mutation rate. Examples include the common mutations at one or a few sites in the genes that cause achondroplasia, Apert syndrome, multiple endocrine neoplasia type 2B, and Noonan syndrome. These mutations are recurrent, provide a gain of function, are paternally derived, and are more likely to be transmitted as the father ages. Recent experiments have tested whether the high mutation frequencies are due to an elevated mutation rate per cell division, as expected, or to an advantage of the mutant spermatogonial stem cells over wild-type stem cells. The evidence, which includes the surprising discovery of testis mutation clusters, rules out the former model but not the latter. We propose how the mutations might alter spermatogonial stem cell function and discuss how germline selection contributes to the paternal age effect, the human mutational load, and adaptive evolution.

New evidence for positive selection helps explain the paternal age effect observed in achondroplasia.

There are certain de novo germline mutations associated with genetic disorders whose mutation rates per generation are orders of magnitude higher than the genome average. Moreover, these mutations occur exclusively in the male germ line and older men have a higher probability of having an affected child than younger ones, known as the paternal age effect (PAE). The classic example of a genetic disorder exhibiting a PAE is achondroplasia, caused predominantly by a single-nucleotide substitution (c.1138G>A) in FGFR3. To elucidate what mechanisms might be driving the high frequency of this mutation in the male germline, we examined the spatial distribution of the c.1138G>A substitution in a testis from an 80-year-old unaffected man. Using a technology based on bead-emulsion amplification, we were able to measure mutation frequencies in 192 individual pieces of the dissected testis with a false-positive rate lower than 2.7 × 10(-6). We observed that most mutations are clustered in a few pieces with 95% of all mutations occurring in 27% of the total testis. Using computational simulations, we rejected the model proposing an elevated mutation rate per cell division at this nucleotide site. Instead, we determined that the observed mutation distribution fits a germline selection model, where mutant spermatogonial stem cells have a proliferative advantage over unmutated cells. Combined with data on several other PAE mutations, our results support the idea that the PAE, associated with a number of Mendelian disorders, may be explained primarily by a selective mechanism.

Age-dependent germline mosaicism of the most common noonan syndrome mutation shows the signature of germline selection.

Noonan syndrome (NS) is among the most common Mendelian genetic diseases (∼1/2,000 live births). Most cases (50%-84%) are sporadic, and new mutations are virtually always paternally derived. More than 47 different sites of NS de novo missense mutations are known in the PTPN11 gene that codes for the protein tyrosine phosphatase SHP-2. Surprisingly, many of these mutations are recurrent with nucleotide substitution rates substantially greater than the genome average; the most common mutation, c.922A>G, is at least 2,400 times greater. We examined the spatial distribution of the c.922A>G mutation in testes from 15 unaffected men and found that the mutations were not uniformly distributed across each testis as would be expected for a mutation hot spot but were highly clustered and showed an age-dependent germline mosaicism. Computational modeling that used different stem cell division schemes confirmed that the data were inconsistent with hypermutation, but consistent with germline selection: mutated spermatogonial stem cells gained an advantage that allowed them to increase in frequency. SHP-2 interacts with the transcriptional activator STAT3. Given STAT3's function in mouse spermatogonial stem cells, we suggest that this interaction might explain the mutant's selective advantage by means of repression of stem cell differentiation signals. Repression of STAT3 activity by cyclin D1 might also play a previously unrecognized role in providing a germline-selective advantage to spermatogonia for the recurrent mutations in the receptor tyrosine kinases that cause Apert syndrome and MEN2B. Looking at recurrent mutations driven by germline selection in different gene families can help highlight common causal signaling pathways.

Positive selection for new disease mutations in the human germline: evidence from the heritable cancer syndrome multiple endocrine neoplasia type 2B.

Multiple endocrine neoplasia type 2B (MEN2B) is a highly aggressive thyroid cancer syndrome. Since almost all sporadic cases are caused by the same nucleotide substitution in the RET proto-oncogene, the calculated disease incidence is 100-200 times greater than would be expected based on the genome average mutation frequency. In order to determine whether this increased incidence is due to an elevated mutation rate at this position (true mutation hot spot) or a selective advantage conferred on mutated spermatogonial stem cells, we studied the spatial distribution of the mutation in 14 human testes. In donors aged 36-68, mutations were clustered with small regions of each testis having mutation frequencies several orders of magnitude greater than the rest of the testis. In donors aged 19-23 mutations were almost non-existent, demonstrating that clusters in middle-aged donors grew during adulthood. Computational analysis showed that germline selection is the only plausible explanation. Testes of men aged 75-80 were heterogeneous with some like middle-aged and others like younger testes. Incorporating data on age-dependent death of spermatogonial stem cells explains the results from all age groups. Germline selection also explains MEN2B's male mutation bias and paternal age effect. Our discovery focuses attention on MEN2B as a model for understanding the genetic and biochemical basis of germline selection. Since RET function in mouse spermatogonial stem cells has been extensively studied, we are able to suggest that the MEN2B mutation provides a selective advantage by altering the PI3K/AKT and SFK signaling pathways. Mutations that are preferred in the germline but reduce the fitness of offspring increase the population's mutational load. Our approach is useful for studying other disease mutations with similar characteristics and could uncover additional germline selection pathways or identify true mutation hot spots.

Analysis of a single-stranded DNA-scanning process in which activation-induced deoxycytidine deaminase (AID) deaminates C to U haphazardly and inefficiently to ensure mutational diversity.

Enzymes that scan single-stranded (ss) DNA have been studied far less extensively than those that scan double-stranded (ds) DNA. Activation-induced deoxycytidine deaminase (AID) deaminates C to U on single-stranded DNA to initiate immunological diversity. Except for processive deaminations favoring WRC hot motifs (W = (A/T) and R = (G/C)), the rules governing AID scanning remain vague. Here, we examine the patterns of deaminations on naked single-stranded DNA and during transcription of dsDNA by embedding cassettes containing combinations of motifs within a lacZ mutational reporter gene. Deaminations arise randomly, spatially distributed as isolated events and in clusters. The deamination frequency depends on the motif and its surrounding sequence. We propose a random walk model that fits the data well, having a deamination probability of 1-7% per motif encounter. We suggest that inefficient, haphazard deamination produces antibody diversity associated with AID.

A simple algebraic cancer equation: calculating how cancers may arise with normal mutation rates.

BACKGROUND: The purpose of this article is to present a relatively easy to understand cancer model where transformation occurs when the first cell, among many at risk within a colon, accumulates a set of driver mutations. The analysis of this model yields a simple algebraic equation, which takes as inputs the number of stem cells, mutation and division rates, and the number of driver mutations, and makes predictions about cancer epidemiology. METHODS: The equation [p = 1 - (1 - (1 - (1 - u)d)k)Nm ] calculates the probability of cancer (p) and contains five parameters: the number of divisions (d), the number of stem cells (N x m), the number of critical rate-limiting pathway driver mutations (k), and the mutation rate (u). In this model progression to cancer "starts" at conception and mutations accumulate with cell division. Transformation occurs when a critical number of rate-limiting pathway mutations first accumulates within a single stem cell. RESULTS: When applied to several colorectal cancer data sets, parameter values consistent with crypt stem cell biology and normal mutation rates were able to match the increase in cancer with aging, and the mutation frequencies found in cancer genomes. The equation can help explain how cancer risks may vary with age, height, germline mutations, and aspirin use. APC mutations may shorten pathways to cancer by effectively increasing the numbers of stem cells at risk. CONCLUSIONS: The equation illustrates that age-related increases in cancer frequencies may result from relatively normal division and mutation rates. Although this equation does not encompass all of the known complexity of cancer, it may be useful, especially in a teaching setting, to help illustrate relationships between small and large cancer features.

Allele-specific expression assays using Solexa.

BACKGROUND: Allele-specific expression (ASE) assays can be used to identify cis, trans, and cis-by-trans regulatory variation. Understanding the source of expression variation has important implications for disease susceptibility, phenotypic diversity, and adaptation. While ASE is commonly measured via relative fluorescence at a SNP, next generation sequencing provides an opportunity to measure ASE in an accurate and high-throughput manner using read counts. RESULTS: We introduce a Solexa-based method to perform large numbers of ASE assays using only a single lane of a Solexa flowcell. In brief, transcripts of interest, which contain a known SNP, are PCR enriched and barcoded to enable multiplexing. Then high-throughput sequencing is used to estimate allele-specific expression using sequencing counts. To validate this method, we measured the allelic bias in a dilution series and found high correlations between measured and expected values (r>0.9, p < 0.001). We applied this method to a set of 5 genes in a Drosophila simulans parental mix, F1 and introgression and found that for these genes the majority of expression divergence can be explained by cis-regulatory variation. CONCLUSION: We present a new method with the capacity to measure ASE for large numbers of assays using as little as one lane of a Solexa flowcell. This will be a valuable technique for molecular and population genetic studies, as well as for verification of genome-wide data sets.

The ups and downs of mutation frequencies during aging can account for the Apert syndrome paternal age effect.

Apert syndrome is almost always caused by a spontaneous mutation of paternal origin in one of two nucleotides in the fibroblast growth factor receptor 2 gene (FGFR2). The incidence of this disease increases with the age of the father (paternal age effect), and this increase is greater than what would be expected based on the greater number of germ-line divisions in older men. We use a highly sensitive PCR assay to measure the frequencies of the two causal mutations in the sperm of over 300 normal donors with a wide range of ages. The mutation frequencies increase with the age of the sperm donors, and this increase is consistent with the increase in the incidence rate. In both the sperm data and the birth data, the increase is non-monotonic. Further, after normalizing for age, the two Apert syndrome mutation frequencies are correlated within individual sperm donors. We consider a mathematical model for germ-line mutation which reproduces many of the attributes of the data. This model, with other evidence, suggests that part of the increase in both the sperm data and the birth data is due to selection for mutated premeiotic cells. It is likely that a number of other genetic diseases have similar features.

Understanding what determines the frequency and pattern of human germline mutations.

Surprising findings about human germline mutation have come from applying new technologies to detect rare mutations in germline DNA, from analysing DNA sequence divergence between humans and closely related species, and from investigating human polymorphic variation. In this Review we discuss how these approaches affect our current understanding of the roles of sex, age, mutation hot spots, germline selection and genomic factors in determining human nucleotide substitution mutation patterns and frequencies. To enhance our understanding of mutation and disease, more extensive molecular data on the human germ line with regard to mutation origin, DNA repair, epigenetic status and the effect of newly arisen mutations on gamete development are needed.