High-Resolution Recombination Patterns in a Region of Human Chromosome 21 Measured by Sperm Typing

For decades, classical crossover studies and linkage disequilibrium (LD) analysis of genomic regions suggested that human meiotic crossovers may not be randomly distributed along chromosomes but are focused instead in “hot spots.” Recent sperm typing studies provided data at very high resolution and accuracy that defined the physical limits of a number of hot spots. The data were also used to test whether patterns of LD can predict hot spot locations. These sperm typing studies focused on several small regions of the genome already known or suspected of containing a hot spot based on the presence of LD breakdown or previous experimental evidence of hot spot activity. Comparable data on target regions not specifically chosen using these two criteria is lacking but is needed to make an unbiased test of whether LD data alone can accurately predict active hot spots. We used sperm typing to estimate recombination in 17 almost contiguous ~5 kb intervals spanning 103 kb of human Chromosome 21. We found two intervals that contained new hot spots. The comparison of our data with recombination rates predicted by statistical analyses of LD showed that, overall, the two datasets corresponded well, except for one predicted hot spot that showed little crossing over. This study doubles the experimental data on recombination in men at the highest resolution and accuracy and supports the emerging genome-wide picture that recombination is localized in small regions separated by cold areas. Detailed study of one of the new hot spots revealed a sperm donor with a decrease in recombination intensity at the canonical recombination site but an increase in crossover activity nearby. This unique finding suggests that the position and intensity of hot spots may evolve by means of a concerted mechanism that maintains the overall recombination intensity in the region

The Molecular Anatomy of Spontaneous Germline Mutations in Human Testes

The frequency of the most common sporadic Apert syndrome mutation (C755G) in the human fibroblast growth factor receptor 2 gene (FGFR2) is 100–1,000 times higher than expected from average nucleotide substitution rates based on evolutionary studies and the incidence of human genetic diseases. To determine if this increased frequency was due to the nucleotide site having the properties of a mutation hot spot, or some other explanation, we developed a new experimental approach. We examined the spatial distribution of the frequency of the C755G mutation in the germline by dividing four testes from two normal individuals each into several hundred pieces, and, using a highly sensitive PCR assay, we measured the mutation frequency of each piece. We discovered that each testis was characterized by rare foci with mutation frequencies 103 to >104 times higher than the rest of the testis regions. Using a model based on what is known about human germline development forced us to reject (p < 10−6) the idea that the C755G mutation arises more frequently because this nucleotide simply has a higher than average mutation rate (hot spot model). This is true regardless of whether mutation is dependent or independent of cell division. An alternate model was examined where positive selection acts on adult self-renewing Ap spermatogonial cells (SrAp) carrying this mutation such that, instead of only replacing themselves, they occasionally produce two SrAp cells. This model could not be rejected given our observed data. Unlike the disease site, similar analysis of C-to-G mutations at a control nucleotide site in one testis pair failed to find any foci with high mutation frequencies. The rejection of the hot spot model and lack of rejection of a selection model for the C755G mutation, along with other data, provides strong support for the proposal that positive selection in the testis can act to increase the frequency of premeiotic germ cells carrying a mutation deleterious to an offspring, thereby unfavorably altering the mutational load in humans. Studying the anatomical distribution of germline mutations can provide new insights into genetic disease and evolutionary change

Family reunion via error correction: an efficient analysis of duplex sequencing data

Background Duplex sequencing is the most accurate approach for identification of sequence variants present at very low frequencies. Its power comes from pooling together multiple descendants of both strands of original DNA molecules, which allows distinguishing true nucleotide substitutions from PCR amplification and sequencing artifacts. This strategy comes at a cost—sequencing the same molecule multiple times increases dynamic range but significantly diminishes coverage, making whole genome duplex sequencing prohibitively expensive. Furthermore, every duplex experiment produces a substantial proportion of singleton reads that cannot be used in the analysis and are thrown away. Results In this paper we demonstrate that a significant fraction of these reads contains PCR or sequencing errors within duplex tags. Correction of such errors allows “reuniting” these reads with their respective families increasing the output of the method and making it more cost effective. Conclusions We combine an error correction strategy with a number of algorithmic improvements in a new version of the duplex analysis software, Du Novo 2.0. It is written in Python, C, AWK, and Bash. It is open source and readily available through Galaxy, Bioconda, and Github: https://github.com/galaxyproject/dunovo

Massively Parallel Haplotyping on Microscopic Beads for the High-Throughput Phase Analysis of Single Molecules

In spite of the many advances in haplotyping methods, it is still very difficult to characterize rare haplotypes in tissues and different environmental samples or to accurately assess the haplotype diversity in large mixtures. This would require a haplotyping method capable of analyzing the phase of single molecules with an unprecedented throughput. Here we describe such a haplotyping method capable of analyzing in parallel hundreds of thousands single molecules in one experiment. In this method, multiple PCR reactions amplify different polymorphic regions of a single DNA molecule on a magnetic bead compartmentalized in an emulsion drop. The allelic states of the amplified polymorphisms are identified with fluorescently labeled probes that are then decoded from images taken of the arrayed beads by a microscope. This method can evaluate the phase of up to 3 polymorphisms separated by up to 5 kilobases in hundreds of thousands single molecules. We tested the sensitivity of the method by measuring the number of mutant haplotypes synthesized by four different commercially available enzymes: Phusion, Platinum Taq, Titanium Taq, and Phire. The digital nature of the method makes it highly sensitive to detecting haplotype ratios of less than 1∶10,000. We also accurately quantified chimera formation during the exponential phase of PCR by different DNA polymerases

Evaluating the Evidence for Transmission Distortion in Human Pedigrees

Children of a heterozygous parent are expected to carry either allele with equal probability. Exceptions can occur, however, due to meiotic drive, competition among gametes, or viability selection, which we collectively term “transmission distortion” (TD). Although there are several well-characterized examples of these phenomena, their existence in humans remains unknown. We therefore performed a genome-wide scan for TD by applying the transmission disequilibrium test (TDT) genome-wide to three large sets of human pedigrees of European descent: the Framingham Heart Study (FHS), a founder population of European origin (HUTT), and a subset of the Autism Genetic Resource Exchange (AGRE). Genotyping error is an important confounder in this type of analysis. In FHS and HUTT, despite extensive quality control, we did not find sufficient evidence to exclude genotyping error in the strongest signals. In AGRE, however, many signals extended across multiple SNPs, a pattern highly unlikely to arise from genotyping error. We identified several candidate regions in this data set, notably a locus in 10q26.13 displaying a genome-wide significant TDT in combined female and male transmissions and a signature of recent positive selection, as well as a paternal TD signal in 6p21.1, the same region in which a significant TD signal was previously observed in 30 European males. Neither region replicated in FHS, however, and the paternal signal was not visible in sperm competition assays or as allelic imbalance in sperm. In maternal transmissions, we detected no strong signals near centromeres or telomeres, the regions predicted to be most susceptible to female-specific meiotic drive, but we found a significant enrichment of top signals among genes involved in cell junctions. These results illustrate both the potential benefits and the challenges of using the TDT to study transmission distortion and provide candidates for investigation in future studies

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

Fine Scale Analysis of Crossover and Non-Crossover and Detection of Recombination Sequence Motifs in the Honeybee (Apis mellifera)

BACKGROUND: Meiotic exchanges are non-uniformly distributed across the genome of most studied organisms. This uneven distribution suggests that recombination is initiated by specific signals and/or regulations. Some of these signals were recently identified in humans and mice. However, it is unclear whether or not sequence signals are also involved in chromosomal recombination of insects. METHODOLOGY: We analyzed recombination frequencies in the honeybee, in which genome sequencing provided a large amount of SNPs spread over the entire set of chromosomes. As the genome sequences were obtained from a pool of haploid males, which were the progeny of a single queen, an oocyte method (study of recombination on haploid males that develop from unfertilized eggs and hence are the direct reflect of female gametes haplotypes) was developed to detect recombined pairs of SNP sites. Sequences were further compared between recombinant and non-recombinant fragments to detect recombination-specific motifs. CONCLUSIONS: Recombination events between adjacent SNP sites were detected at an average distance of 92 bp and revealed the existence of high rates of recombination events. This study also shows the presence of conversion without crossover (i. e. non-crossover) events, the number of which largely outnumbers that of crossover events. Furthermore the comparison of sequences that have undergone recombination with sequences that have not, led to the discovery of sequence motifs (CGCA, GCCGC, CCGCA), which may correspond to recombination signals

Genetic Crossovers Are Predicted Accurately by the Computed Human Recombination Map

Hotspots of meiotic recombination can change rapidly over time. This instability and the reported high level of inter-individual variation in meiotic recombination puts in question the accuracy of the calculated hotspot map, which is based on the summation of past genetic crossovers. To estimate the accuracy of the computed recombination rate map, we have mapped genetic crossovers to a median resolution of 70 Kb in 10 CEPH pedigrees. We then compared the positions of crossovers with the hotspots computed from HapMap data and performed extensive computer simulations to compare the observed distributions of crossovers with the distributions expected from the calculated recombination rate maps. Here we show that a population-averaged hotspot map computed from linkage disequilibrium data predicts well present-day genetic crossovers. We find that computed hotspot maps accurately estimate both the strength and the position of meiotic hotspots. An in-depth examination of not-predicted crossovers shows that they are preferentially located in regions where hotspots are found in other populations. In summary, we find that by combining several computed population-specific maps we can capture the variation in individual hotspots to generate a hotspot map that can predict almost all present-day genetic crossovers

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 Meiotic Recombination Products from Human Sperm

Traditional methods for surveying meiotic recombination in humans are limited to pedigree and linkage disequilibrium analyses. We have developed assays that allow the direct detection of crossover and gene conversion molecules in batches of sperm DNA. To date, we have characterized 26 recombination hotspots by allele-specific PCR and selectively amplified recombinant DNA molecules from these regions. These analyses have revealed that meiotic crossover hotspots in humans are highly localized and flanked by DNA segments where recombination is suppressed. The centers of crossover hotspots are also active in noncrossover recombination, displaying short conversion tracts