Boxes surrounded by a solid line are for bottleneck parameters size and time , open boxes are for population size between bottleneck events, and boxes surrounded by a dashed line are for admixture rates and times. C Sketch of the demographic model used for SFS-based demographic inferences. The model includes three possible bottlenecks of a fixed duration of generations in the direct ancestry of the sampled population, and it allows some sampled genes a fraction p ADM to have ancestors coming from an unsampled ghost population at any time T ADM since its divergence from the sampled population T DIV generations ago.
Note also that the ghost population is used here to allow for some gene flow from some unspecified source, and so to account for the non-isolated nature of human populations. Using a simple demographic model of a focal population going through three successive bottlenecks and receiving some migrants from surrounding populations modelled as a ghost population for simplicity Figure 3C , we can fit almost perfectly the three SFSs Figure 3—figure supplement 2.
Yet, the inferred parameters differ considerably Supplementary file 3 - Table S3. With the neutral SFS, we nevertheless infer a more recent last bottleneck dated at the end of the Last Glacial Maximum LGM , a more pronounced and more recent admixture event from surrounding populations.
The ancient demography is markedly different with a significantly more ancient second bottleneck and a significantly lower ancient population size inferred from both synonymous and NTR kb SFS. The Japanese demography inferred from the three data sets shows more similarity over the last ky but the demography inferred from the neutral data set suggests a stronger recent bottleneck pre LGM and no population expansion as compared to what is inferred from the synonymous SFS neutral data set.
Our results thus clearly show that very different demographies can be inferred from neutral and non-neutral SFSs. However, even though BGS and gBGC affect the SFS of populations with distinct histories in a qualitatively similar way, they have different consequences on their reconstructed demography.
It thus appears difficult to predict how demographic parameters will be biased when using non-neutral SFS. To confirm that our observed patterns were compatible with background selection, we ran individual-based forward simulations implementing BGS with SLiM v.
Overall, the simulated BGS patterns qualitatively match the observation very well Figure 4 , Figure 4—figure supplement 1 , and Figure 4—figure supplement 2. Forward simulations of diploid individuals were performed with SLiM v. We simulated the evolution of a chromosome of 50 Mb made up of 5 kb regions, each consisting of a 1 kb region experiencing purifying selections followed by a 4 kb region with neutral mutations.
Solid and dashed lines correspond to simulations performed with and without BGS, respectively. The transition to effective neutrality occurs between a recombination rate of 1e—8 blue curve and 1e—7 orange curve , a range that includes our proposed threshold of 1.
Delineating the neutrally evolving part of the human genome remains a challenge, as variation in the intensity of recombination, mutation, and selection are increasingly recognised as having a strong effect on observable genomic diversity in humans Corbett-Detig et al. Elyashiv et al.
These two processes, which both depend on recombination, strongly affect observed measures of genetic diversity along the genome and can lead to biased demographic inference if not properly taken into account Figure 3.
For instance, a mutagenic effect of recombination could lead to an increased diversity in regions of high recombination Hellmann et al. The examination of extremely low-frequency mutations, which should be enriched for new mutations, did not reveal any association between recombination rate and the density of new mutations in a large human sample Schaibley et al.
Alternatively, a correlation between mutation and recombination rates could occur if these rates were both affected by the same process, such as replication timing Stamatoyannopoulos et al. However, a mere correlation between mutation and recombination rates cannot explain two key aspects of our observations. Second, we find a significant difference in the shape of SFS computed in regions of low and high recombination Figure 2A , even though mutation rate should have no effect on the shape of the SFS.
We find that the B -statistics inferred by McVicker et al. This pattern remains if we only consider subsets of SNPs e. Therefore, these results suggest that in addition to BGS and gBGC, some correlation between mutation and recombination rate is required to best explain our observed patterns.
The occurrence of pervasive positive selection, either in the form of soft or hard sweeps Kern and Hahn, or of positive selection on polygenic traits Boyle et al. However, positive selection should lead to an increase of both low- and high-frequency variants in the SFS Fay et al. The exact proportion of the genome that is influenced by selection is still the source of an intense debate Bernstein et al.
Even though our estimate of the fraction of the human genome influenced by BGS matches relatively well with that reported to be biochemically functional by the ENCODE consortium Bernstein et al. As expected, the effect of BGS is clearly mediated by local recombination rate, but it extends well beyond coding regions in humans Hernandez et al.
Our results also show that the influence of gBGC is not restricted to recombination hotspots Spencer et al. These regions represent about Interestingly, our neutral SNPs are found in both transcribed and non-transcribed-regions Figure 2C , and they are enriched close to telomeric regions Figure 1—figure supplement 10 , where BGS is predicted to be weaker Charlesworth, Indeed, our way of identifying selection and biased gene conversion is indirect and operates on arbitrarily defined recombination-rate categories.
A more precise mapping of selected genomic segments could use information on the positions of known functional elements Siepel et al. It thus seems that recombination hotspots still play a role in decoupling selected from neutral sites, and that sites furthest away from hotspots might still be slightly sensitive to BGS.
Purifying selection in phastCons conserved elements Siepel et al. Contrastingly, being further than 0. For instance, we found that they lead to an underestimation of the age of a bottleneck and an overestimation of the magnitude of a demographic expansion in the Yoruba population, but we do not observe such strong biases in the Japanese population. It therefore appears difficult to predict the specific biases introduced by these evolutionary forces on demographic inference, except perhaps under simple evolutionary scenarios Ewing and Jensen, We therefore suggest that future studies of demographic history should be based on a set of markers that is minimally influenced by these non-neutral forces.
We have also computed the observed SFS for subsets of neutral SNPs with various values of the covariates mentioned above Figure 1—figure supplement 9. SNPs in the 1st and 4th distance-quartiles to hotspot show similar SFS, with a slight excess of singletons and high-frequency variants for the sites furthest to hotspots Figure 2—figure supplement 3A.
It is interesting to compare our neutral set of SNPs to another previously defined set of neutral regions of the human genome that has been used as a reference for demographic inferences in a series of studies e.
Gronau et al. The SFS computed on this alternative neutral set departs significantly from our neutral set, with a significant excess of singletons, a deficit of sites with intermediate allele frequencies, and an excess of nearly fixed variants, a pattern that can be explained by the action of both BGS and gBGC Figure 3—figure supplement 3A.
Since a large B-statistic is also indicative of relaxed BGS, one could be tempted to use regions associated with B values larger than 0. However, we see that its SFS also departs from that of our neutral set, with a small deficit of singleton and an excess of other frequency classes in Yoruba, and a slight excess of high-frequency variants in Japan Figure 3—figure supplement 3A.
These differences in SFS shapes also lead to inferred demographies that are markedly different from that inferred from our own neutral set, and this especially for the Yoruba population Figure 3—figure supplement 3B. Methods of demographic inference based on whole genomes e. Li and Durbin, ; Sheehan et al. In this respect, the history of human populations as well as that of other species might be more readily inferred from methods that can conveniently analyze restricted sets of neutrally evolving sites interspersed across the genome.
Similarly, other types of inference using a biased neutral SFS as a reference could also be affected, such as inferences of the distributions of fitness effects DFE Keightley and Eyre-Walker, ; Kim et al. Contrary to previously used sets of SNPs, these sites should lead to essentially unbiased demographic inferences and serve as a reference for future demographic reconstructions in humans. Due to its simplicity, our approach can be readily applied to any species for which a recombination map is available.
We analyzed two distinct whole genome datasets. The first one consisted of individuals from ten G populations Auton et al. These individuals were selected from ten SGDP populations that were geographically close to those analyzed for the G project. We removed all sites with any missing data and kept only diallelic sites from autosomal chromosomes. The ancestral state of each variant in these genomes was set to the chimpanzee reference genome panTro4 genome assembly to avoid any discrepancy between African and non-African populations.
Only diallelic SNPs for which one of the variants observed in the G or SGDP datasets corresponded to the chimpanzee ancestral state were kept for later analyses. In addition, we removed the CpG sites that present a peculiar mutation profile and are correlated with recombination rate Arbeithuber et al.
The B-statistic McVicker et al. We finally retrieved 37, potentially neutral regions of 1 kb e. We show in the following that this statistic is ideally suited to evidence the potential effect of selection or mutation , as difference in the demography of the populations from which individuals are sampled should not translate into different values of this statistic among individuals. This trend was observed in a wide range of species.
The proportion of solo LTR significantly differed between individual chromosomes of the same plant species Figure 3. Figure 3. Total count of solo LTRs is indicated. Nesting is an absolute measure of relative age — the nested element is always younger than the original and thus the similarity of the nested younger element should always be higher than the original older element.
Negative delta LTR similarity can be a result of processes that affect the LTRs after insertion, such as the homology-driven form of recombination reshaping LTRs - gene conversion. By filtering the original LTR retrotransposons for the presence of TSDs we minimized the possibility of improper element delineation by TE-greedy-nester. We performed this analysis on fifteen plant species and, surprisingly, we found that the delta LTR similarity was often negative i. To rule out the possibility that the observed negative results were simply due to random mutations, we simulated a pair of LTRs with BBMap mutate.
For each pair of sequences we calculated the similarity of their global alignment and plotted the distribution of these values as simulated delta LTR similarity gray area, Figure 4.
Figure 4. Plant species were divided into four subfigures for better readability. Plotted values represent probability density function based on kernel density estimation. The simulated nested structure was then further mutated with mutate. This suggests that factors other than age have contributed to the similarity of the LTRs. Figure 5. LTR retrotransposon families labeled with different colors of fifteen plant species. Most abundant families are labeled within the plot. In order to find a possible explanation for the anomalies described above, we analyzed the extent of potential gene conversion along the long terminal repeats of LTR retrotransposons using GENECONV software.
After quality filtering we calculated i the number of LTR retrotransposon containing gene converted regions in dependence on genome size of host species Figure 6A and measured ii the length of converted regions Figure 6B. Both the number of elements with converted regions and the length of converted region differed among plant species. The length of converted regions i varied most often between and bp and ii was higher in the case of gene conversion between LTRs of the same element intra-element conversion than for conversion between LTRs of different elements inter-element conversion.
The highest lengths of converted regions were found in O. Figure 6. Total count of elements with GCE is indicated. Each filled circle corresponds to one chromosome, plant species are labeled by different colors. When linear trendline was used, the slope after the removal of converted regions decreased Supplementary Figure S4. However, the strong increase of LTR at the highest LTR similarities was not affected by the removal of converted regions.
This possibly suggests that the increase of LTR similarity with length can be caused by other factors or by an unknown technical issue.
Figure 7. The removal of converted regions from the LTRs has shifted the curve to the left resulting in an increase of LTR retrotransposon age estimates. For each mutation level we found that the distribution of the longer LTRs were always more homogenous than the shorter ones Supplementary Figure S5 demonstrated mutation level 0. Such a finding suggests that this technical phenomenon, in addition to gene conversion, can explain the increase of LTR similarity in longer LTRs as observed in Figure 5.
Our further analysis was motivated by the speculation that homogenization of retrotransposon families by gene conversion could accelerate ectopic recombination. Such a process would respond to family expansion threatening the host. We found that the number of LTR retrotransposons exhibiting signs of gene conversion negatively correlated with the proportion of solo LTRs i. The remarkable position in the plot showed genomes of Physcomitrella patens , Solanum lycopersicum , and S.
On the other hand, the genome of Chlamydomonas reinhardtii contained LTR retrotransposon strongly affected by gene conversion but having very low proportion of solo LTRs. Both extremes support the view that gene conversion and ectopic recombination interfere. Figure 8. Relationship between gene conversion and solo LTR formation. The graph shows that chromosomes containing high proportions of gene converted element LTRs contain low proportions of solo LTRs.
Our results show that i evolutionary dynamics of individual LTR retrotransposons differ among retrotransposon families and plant species, ii the commonly used LTR retrotransposon age estimation method based on LTR divergence is not absolute, probably due to the influence of gene conversion, iii families exhibiting signs of gene conversion less readily form solo LTRs, and iv the proportion of solo LTRs did not change with genome size, indicating a similar intensity of ectopic recombination in small and large genomes.
Our LTR retrotransposon age estimates were lower than estimates published by Bennetzen et al. This difference can be explained by the fact that i we used a much higher number of elements hundreds and thousands compared to tens of elements in most species used by Bennetzen et al. The age distribution of a range of LTR retrotransposon families in fifteen plant species indicates that retrotransposon activity differed among families, probably as a result of an interplay of various genomic and environmental factors.
Such an observation is in accordance with the concept of the genome as an ecosystem of varied elements exhibiting a spectrum of interactions from parasitism via competition to collaboration.
Nevertheless, despite the differences in age distribution patterns, some similarities of the expansion profiles in several LTR retrotransposon families of the same species were evident and could reflect stresses that a species underwent when selected retrotransposon families were simultaneously activated. Some of our results are necessarily affected by technical issues. While we used reasonable settings of TE-greedy-nester and subsequent filtering for minimal full-length TE structure and TSDs as evidence of real insertions, these settings and filtering steps are currently notoriously error-prone and could affect our results.
Also, the age estimates Table 1 could be affected by the quality of genome assembly. Namely, the average age of LTR retrotransposons in Solanum species tomato and potato plants was higher compared to other analyzed species here. High number of phylogenetically older retroelements e.
This putatively false higher age determination could be explained by the worse quality of LTR retrotransposon assembly e. Our assumption is supported by recent report on lower quality of tomato assembly Hosmani et al. Our finding that LTR similarity depends not only on the retrotransposon age but also on the LTR length Figure 5 could be partially explained by absence of older longer LTRs, since they are more prone to unequal recombination Du et al. The potential involvement of other factors affecting LTR retrotransposon age estimation is also supported by the lower LTR similarity of nested elements compared to the pre-existing ones.
Our results are in accordance with the finding of Cossu et al. We also showed that gene conversion negatively correlates with the formation of solo LTRs. Compared to Cossu et al. The importance of LTR length in an intensity of gene conversion was previously proposed by Du et al.
The potential role of gene conversion in homogenization of transposable elements was suggested decades ago for yeast Ty elements Roeder and Fink, , primate SINE elements Kass et al.
Gene conversion of LTR retrotransposons was proposed to be stronger on non-recombining Y chromosomes than on other chromosomes Kejnovsky et al. Gene conversion has also been observed in satellite DNA Krzywinski et al. The non-allelic gene conversion among long terminal repeats has been studied in human endogenous retroviruses recently Trombetta et al. The authors suggest that ectopic recombination among LTRs is rather common and could also take place between elements occupying different chromosomes.
The negative correlation between gene conversion and solo LTR formation indicates that gene conversion does not accelerate ectopic recombination by homogenizing LTRs of the same elements, as we expected, but rather that both processes gene conversion and ectopic recombination probably are influential.
Therefore, homologous LTRs susceptible to recombination events, are responsive to either ectopic recombination or gene conversion. Both processes are homology-driven and differ in whether or not they resolve in crossing-over. The presence of gene conversion has almost certainly led to underestimations of LTR retrotransposon age in many studies using the LTR divergence method. Recently, Maumus and Quesneville cast doubt on the popular dating approach that only assesses the LTR divergence widely applied in plants and stressed the need to use alternative methods based on e.
These authors evidenced such an approach by providing a higher age estimation of TEs in A. Similarly, Giordano et al. Retrotransposon age underestimation obtained by the LTR divergence method also agrees with the conclusion that LTR retrotransposons in Drosophila are much younger than the host species in which they reside Bowen and McDonald, Taken together, the optimization of methods for LTR retrotransposon age estimation should be a subject of further research.
The extent of gene conversion can be affected not only by the LTR length but also possibly by the distance between LTRs, as was shown for duplicated genes Ezawa et al. Since reversely transcribed cDNA molecules are often used as templates in gene conversion Doolittle, ; Derr and Strathern, ; Benovoy and Drouin, , and RNA molecules participate in gene conversion Doolittle, ; Derr et al. Thus, the expression of genome, induced by environmental or endogenous factors, can change the genome structure by homogenization of repetitive DNA.
The interplay between gene conversion and ectopic recombination can oppose LTR retrotransposon amplifications and lead to genome size reduction. This way, gene conversion can fulfill an important regulatory role in genome repeat expansions and contractions as well as related genome rearrangements.
Since the activity of transposable elements is epigenetically regulated Fedoroff, , both gene conversion and ectopic recombination may respond to environmental challenges and thus contribute to eukaryotic evolvability and a higher genome dynamism in plants Kejnovsky et al.
LTR retrotransposons have colonized plant genomes throughout the whole course of evolution. Estimation of LTR retrotransposon age is thus of great importance for the study of plant genome evolution as well as for understanding transposable element biology. Recent research indicates that the traditional age estimation method based on the LTR divergence has some limits, mostly due to the action of gene conversion.
Here, we have extended the available knowledge and showed that i LTR similarity depends on LTR length and ii nested elements often have lower LTR similarity that pre-existing original ones. We have found regions in LTR with signs of gene conversion responsible for both phenomena. Negative correlation between the extent of gene conversion and the abundance of solo LTRs indicates that gene conversion probably interferes with the ectopic recombination between LTRs.
Our findings demonstrate that the LTR divergence method should be used carefully keeping in mind the effect of other factors such as gene conversion. We conclude that more methods should be combined for a more reliable LTR retrotransposon age estimation, using e. Adaptive evolution is substantially impeded by Hill—Robertson interference in Drosophila.
Comeron JM , Kreitman M. Population, evolutionary and genomic consequences of interference selection. Genetics 1 : — Consortium ICGS. Sequence and comparative analysis of the chicken genome provide unique perspectives on vertebrate evolution. Nature : Natural selection constrains neutral diversity across a wide range of species. Determinants of the efficacy of natural selection on coding and noncoding variability in two passerine species.
Genome Biol Evol. OrthoMaM v8: a database of orthologous exons and coding sequences for comparative genomics in mammals. Biased clustered substitutions in the human genome: the footprints of male-driven biased gene conversion.
Genome Res. A new perspective on isochore evolution. Gene : 71 — Duret L , Galtier N. Biased gene conversion and the evolution of mammalian genomic landscapes. Annu Rev Genomics Hum Genet. Emms DM , Kelly S. OrthoFinder: solving fundamental biases in whole genome comparisons dramatically improves orthogroup inference accuracy.
Genome Biol. GC-biased gene conversion impacts ribosomal DNA evolution in vertebrates, angiosperms, and other eukaryotes. Eyre-Walker A. Recombination and mammalian genome evolution. Evidence of selection on silent site base composition in mammals: potential implications for the evolution of isochores and junk DNA. Genetics 2 : — Estimating the rate of adaptive molecular evolution in the presence of slightly deleterious mutations and population size change.
The distribution of fitness effects of new deleterious amino acid mutations in humans. A second generation human haplotype map of over 3. Galtier N. Adaptive protein evolution in animals and the effective population size hypothesis. Galtier N , Duret L. Adaptation or biased gene conversion? Extending the null hypothesis of molecular evolution.
Trends Genet. GC-biased gene conversion promotes the fixation of deleterious amino acid changes in primates. GC-content evolution in mammalian genomes: the biased gene conversion hypothesis. Codon usage bias in animals: disentangling the effects of natural selection, effective population size and GC-biased gene conversion.
Gillespie JH. The causes of molecular evolution. Oxford: Oxford University Press on Demand. Google Preview. Surprising fitness consequences of GC-biased gene conversion: I.
Mutation load and inbreeding depression. Genetics 3 : — Quantification of GC-biased gene conversion in the human genome. Full-length transcriptome assembly from RNA-Seq data without a reference genome. Nat Biotechnol.
The genomic determinants of adaptive evolution in a fungal pathogen. A high-density SNP-based linkage map of the chicken genome reveals sequence features correlated with recombination rate. Unbiased estimate of synonymous and non-synonymous substitution rates with non-stationary base composition.
The rate of meiotic gene conversion varies by sex and age. Nat Genet. Hill WG , Robertson A. The effect of linkage on limits to artificial selection.
Genet Res. Huang X , Madan A. Whole-genome patterns of linkage disequilibrium across flycatcher populations clarify the causes and consequences of fine-scale recombination rate variation in birds.
Mol Ecol. Joint inference of the distribution of fitness effects of deleterious mutations and population demography based on nucleotide polymorphism frequencies. Genetics 4 : — High mutational rates of large-scale duplication and deletion in Daphnia pulex. Kimura M. The neutral theory of molecular evolution. Cambridge: Cambridge University Press. Kliman RM , Hey J. Reduced natural selection associated with low recombination in Drosophila melanogaster. The role of GC-biased gene conversion in shaping the fastest evolving regions of the human genome.
Lachance J , Tishkoff SA. Biased gene conversion skews allele frequencies in human populations, increasing the disease burden of recessive alleles.
Am J Hum Genet. Lartillot N. Interaction between selection and biased gene conversion in mammalian protein-coding sequence evolution revealed by a phylogenetic covariance analysis. The Red Queen model of recombination hot-spot evolution: a theoretical investigation. Philos Trans R Soc B. The red queen model of recombination hotspots evolution in the light of archaic and modern human genomes. GC-biased gene conversion in yeast is specifically associated with crossovers: molecular mechanisms and evolutionary significance.
Li H , Durbin R. Fast and accurate short read alignment with Burrows—Wheeler transform. Biased gene conversion: implications for genome and sex evolution. Trends Genet. Galtier, N. Gene conversion drives GC content evolution in mammalian histones. Spencer, C. The influence of recombination on human genetic diversity.
Human polymorphism around recombination hotspots. Hernandez, R. Context-dependent mutation rates may cause spurious signatures of a fixation bias favoring higher GC-content in humans.
Teich, N. This paper reports a unique gene-conversion event that occurred between two functional genes, resulting in a gain of function. Lorson, C. A single nucleotide in the SMN gene regulates splicing and is responsible for spinal muscular atrophy.
USA 96 , — Gupta, P. Gene conversions are a common cause of von Willebrand disease. Linardopoulou, E. Human subtelomeres are hot spots of interchromosomal recombination and segmental duplication. Nature , 94— Rudd, M.
Elevated rates of sister chromatid exchange at chromosome ends. Lee-Chen, G. Allen, L. A novel loss of function mutation in exon 10 of the FSH receptor gene causing hypergonadotrophic hypogonadism: clinical and molecular characteristics.
Pop, R. A homozygous nonsense mutation in SOX9 in the dominant disorder campomelic dysplasia: a case of mitotic gene conversion. This work reports the first fully characterized somatic interallelic gene-conversion event in the context of human inherited disease.
Hauptschein, R. An apparent interlocus gene conversion-like event at a putative tumor suppressor gene locus on human chromosome 6q27 in a Burkitt's lymphoma cell line. DNA Res. Zhang, J. Cancer Res. Auclair, J. Chambers, S. The mismatch repair system reduces meiotic homeologous recombination and stimulates recombination-dependent chromosome loss. Romano, M. Vyletal, P. Jonkman, M. Revertant mosaicism in epidermolysis bullosa caused by mitotic gene conversion. Cell 88 , — Ogino, S.
Fichou, Y. The potential of oligonucleotides for therapeutic applications. Trends Biotechnol. Shinohara, A. Rad51 protein involved in repair and recombination in S.
Cell 69 , — Masson, J. Identification and purification of two distinct complexes containing the five RAD51 paralogs. Genes Dev. RAD51C is required for Holliday junction processing in mammalian cells. Lisby, M. DNA repair: keeping it together.
De Jager, M. Cell 8 , — Moreno-Herrero, F. Scully, R. Sharan, S. Chen, J. Cell 2 , — Yuan, S. BRCA2 is required for ionizing radiation-induced assembly of Rad51 complex in vivo. CAS Google Scholar. Esashi, F. Nature Struct. Davies, O. Roy, A. Potential gene conversion and source genes for recently integrated Alu elements. Zhi, D. Sequence correlation between neighboring Alu instances suggests post-retrotransposition sequence exchange due to Alu gene conversion.
Gene , — Sen, S. Human genomic deletions mediated by recombination between Alu elements. Tremblay, A. Wurtele, H.
Characterization of in vivo recombination activities in the mouse embryo. Genomics , — Myers, J. A comprehensive analysis of recently integrated human Ta L1 elements.
Vincent, B. Mechanism of Alu integration into the human genome. Genome Med. Khan, H. Molecular evolution and tempo of amplification of human LINE-1 retrotransposons since the origin of primates.
Maizels, N. Immunoglobulin gene diversification. Tang, E. Immunoglobulin gene conversion: Synthesizing antibody diversification and DNA repair. DNA Repair 27 Jun doi D'Avirro, N.
Sequence transfers between variable regions in a mouse antibody transgene can occur by gene conversion. Darlow, J. Gene conversion in human rearranged immunoglobulin genes. Immunogenetics 58 , — Hayakawa, T.
A human-specific gene in microglia. This work describes a human-specific gene-conversion event that might have been significant in the evolution of the Homo genus. Heinen, S. De novo gene conversion in the RCA gene cluster 1q32 causes mutations in complement factor H associated with atypical hemolytic uremic syndrome. Lee, H. Diversity of the CYP21A2 gene: a 6. Friaes, A. CYP21A2 mutations in Portuguese patients with congenital adrenal hyperplasia: identification of two novel mutations and characterization of four different partial gene conversions.
Higashi, Y. Aberrant splicing and missense mutations cause steroid hydroxylase [P C21 ] deficiency in humans: possible gene conversion products. USA 85 , — Fardella, C. Nicod, J. Sarhadi, V. De Marco, P. Folate pathway gene alterations in patients with neural tube defects. Hatton, C.
0コメント