Interlocus Gene Conversion, Natural Selection, and Paralog Homogenization.

Following a duplication, the resulting paralogs tend to diverge. While mutation and natural selection can accelerate this process, they can also slow it. Here, we quantify the paralog homogenization that is caused by point mutations and interlocus gene conversion (IGC). Among 164 duplicated teleost genes, the median percentage of postduplication codon substitutions that arise from IGC rather than point mutation is estimated to be between 7% and 8%. By differentiating between the nonsynonymous codon substitutions that homogenize the protein sequences of paralogs and the nonhomogenizing nonsynonymous substitutions, we estimate the homogenizing nonsynonymous rates to be higher for 163 of the 164 teleost data sets as well as for all 14 data sets of duplicated yeast ribosomal protein-coding genes that we consider. For all 14 yeast data sets, the estimated homogenizing nonsynonymous rates exceed the synonymous rates.

Scalable Bayesian Divergence Time Estimation With Ratio Transformations.

Divergence time estimation is crucial to provide temporal signals for dating biologically important events from species divergence to viral transmissions in space and time. With the advent of high-throughput sequencing, recent Bayesian phylogenetic studies have analyzed hundreds to thousands of sequences. Such large-scale analyses challenge divergence time reconstruction by requiring inference on highly correlated internal node heights that often become computationally infeasible. To overcome this limitation, we explore a ratio transformation that maps the original $N-1$ internal node heights into a space of one height parameter and $N-2$ ratio parameters. To make the analyses scalable, we develop a collection of linear-time algorithms to compute the gradient and Jacobian-associated terms of the log-likelihood with respect to these ratios. We then apply Hamiltonian Monte Carlo sampling with the ratio transform in a Bayesian framework to learn the divergence times in 4 pathogenic viruses (West Nile virus, rabies virus, Lassa virus, and Ebola virus) and the coralline red algae. Our method both resolves a mixing issue in the West Nile virus example and improves inference efficiency by at least 5-fold for the Lassa and rabies virus examples as well as for the algae example. Our method now also makes it computationally feasible to incorporate mixed-effects molecular clock models for the Ebola virus example, confirms the findings from the original study, and reveals clearer multimodal distributions of the divergence times of some clades of interest.

The association of obesity with euploidy rates in women undergoing in vitro fertilization with preimplantation genetic testing.

PURPOSE: The purpose of this study was to determine the impact of body mass index (BMI) on euploidy rates for in vitro fertilization (IVF) cycles with preimplantation genetic testing (PGT) utilizing primarily next-generation sequencing (NGS). METHODS: This retrospective cohort study included women aged ≤ 45 years who underwent IVF/PGT between September 2013 and September 2020 at a single university-affiliated fertility center. The primary outcome was euploidy rate. Secondary outcomes included peak serum estradiol (E2), number of oocytes retrieved, oocyte maturation rate, high-quality blastulation rate, clinical loss rate (CLR), clinical pregnancy rate (CPR), and ongoing pregnancy/live birth rate (OPR/LBR). RESULTS: The study included 1335 IVF cycles that were stratified according to BMI (normal, n = 648; overweight, n = 377; obese, n = 310). The obese group was significantly older with significantly lower baseline FSH, peak E2, high-quality blastulation rate, and number of embryos biopsied than the normal group. Overall euploidy rates were not significantly different between BMI groups (normal 36.4% ± 1.3; overweight 37.3% ± 1.8; obese 32.3% ± 1.8; p = 0.11), which persisted after controlling for covariates (p = 0.82) and after stratification of euploidy rate by age group and by number of oocytes retrieved per age group. There were no significant differences in CLR, CPR, and OPR/LBR across BMI groups. CONCLUSIONS: Despite a lower high quality blastulation rate with obesity, there is not a significant difference in euploidy rates across BMI groups in women undergoing IVF/PGT.

Correlations between alignment gaps and nucleotide substitution or amino acid replacement.

To assess the conventional treatment in evolutionary inference of alignment gaps as missing data, we propose a simple nonparametric test of the null hypothesis that the locations of alignment gaps are independent of the nucleotide substitution or amino acid replacement process. When we apply the test to 1,390 protein alignments that are informed by protein tertiary structure and use a 5% significance level, the null hypothesis of independence between amino acid replacement and gap location is rejected for ∼65% of datasets. Via simulations that include substitution and insertion-deletion, we show that the test performs well with true alignments. When we simulate according to the null hypothesis and then apply the test to optimal alignments that are inferred by each of four widely used software packages, the null hypothesis is rejected too frequently. Via further simulations and analyses, we show that the overly frequent rejections of the null hypothesis are not solely due to weaknesses of widely used software for finding optimal alignments. Instead, our evidence suggests that optimal alignments are unrepresentative of true alignments and that biased evolutionary inferences may result from relying upon individual optimal alignments.

Exome sequencing of hepatocellular carcinoma in lemurs identifies potential cancer drivers: A pilot study.

Background and objectives: Hepatocellular carcinoma occurs frequently in prosimians, but the cause of these liver cancers in this group is unknown. Characterizing the genetic changes associated with hepatocellular carcinoma in prosimians may point to possible causes, treatments and methods of prevention, aiding conservation efforts that are particularly crucial to the survival of endangered lemurs. Although genomic studies of cancer in non-human primates have been hampered by a lack of tools, recent studies have demonstrated the efficacy of using human exome capture reagents across primates. Methodology: In this proof-of-principle study, we applied human exome capture reagents to tumor-normal pairs from five lemurs with hepatocellular carcinoma to characterize the mutational landscape of this disease in lemurs. Results: Several genes implicated in human hepatocellular carcinoma, including ARID1A, TP53 and CTNNB1, were mutated in multiple lemurs, and analysis of cancer driver genes mutated in these samples identified enrichment of genes involved with TP53 degradation and regulation. In addition to these similarities with human hepatocellular carcinoma, we also noted unique features, including six genes that contain mutations in all five lemurs. Interestingly, these genes are infrequently mutated in human hepatocellular carcinoma, suggesting potential differences in the etiology and/or progression of this cancer in lemurs and humans. Conclusions and implications: Collectively, this pilot study suggests that human exome capture reagents are a promising tool for genomic studies of cancer in lemurs and other non-human primates. Lay Summary: Hepatocellular carcinoma occurs frequently in prosimians, but the cause of these liver cancers is unknown. In this proof-of-principle study, we applied human DNA sequencing tools to tumor-normal pairs from five lemurs with hepatocellular carcinoma and compared the lemur mutation profiles to those of human hepatocellular carcinomas.

Convergent evolution of polyploid genomes from across the eukaryotic tree of life.

By modeling the homoeologous gene losses that occurred in 50 genomes deriving from ten distinct polyploidy events, we show that the evolutionary forces acting on polyploids are remarkably similar, regardless of whether they occur in flowering plants, ciliates, fishes, or yeasts. We show that many of the events show a relative rate of duplicate gene loss before the first postpolyploidy speciation that is significantly higher than in later phases of their evolution. The relatively weak selective constraint experienced by the single-copy genes these losses produced leads us to suggest that most of the purely selectively neutral duplicate gene losses occur in the immediate postpolyploid period. Nearly all of the events show strong evidence of biases in the duplicate losses, consistent with them being allopolyploidies, with 2 distinct progenitors contributing to the modern species. We also find ongoing and extensive reciprocal gene losses (alternative losses of duplicated ancestral genes) between these genomes. With the exception of a handful of closely related taxa, all of these polyploid organisms are separated from each other by tens to thousands of reciprocal gene losses. As a result, it is very unlikely that viable diploid hybrid species could form between these taxa, since matings between such hybrids would tend to produce offspring lacking essential genes. It is, therefore, possible that the relatively high frequency of recurrent polyploidies in some lineages may be due to the ability of new polyploidies to bypass reciprocal gene loss barriers.

Measuring Phylogenetic Information of Incomplete Sequence Data.

Widely used approaches for extracting phylogenetic information from aligned sets of molecular sequences rely upon probabilistic models of nucleotide substitution or amino-acid replacement. The phylogenetic information that can be extracted depends on the number of columns in the sequence alignment and will be decreased when the alignment contains gaps due to insertion or deletion events. Motivated by the measurement of information loss, we suggest assessment of the effective sequence length (ESL) of an aligned data set. The ESL can differ from the actual number of columns in a sequence alignment because of the presence of alignment gaps. Furthermore, the estimation of phylogenetic information is affected by model misspecification. Inevitably, the actual process of molecular evolution differs from the probabilistic models employed to describe this process. This disparity means the amount of phylogenetic information in an actual sequence alignment will differ from the amount in a simulated data set of equal size, which motivated us to develop a new test for model adequacy. Via theory and empirical data analysis, we show how to disentangle the effects of gaps and model misspecification. By comparing the Fisher information of actual and simulated sequences, we identify which alignment sites and tree branches are most affected by gaps and model misspecification. [Fisher information; gaps; insertion; deletion; indel; model adequacy; goodness-of-fit test; sequence alignment.].

Pedigree-based and phylogenetic methods support surprising patterns of mutation rate and spectrum in the gray mouse lemur.

Mutations are the raw material on which evolution acts, and knowledge of their frequency and genomic distribution is crucial for understanding how evolution operates at both long and short timescales. At present, the rate and spectrum of de novo mutations have been directly characterized in relatively few lineages. Our study provides the first direct mutation-rate estimate for a strepsirrhine (i.e., the lemurs and lorises), which comprises nearly half of the primate clade. Using high-coverage linked-read sequencing for a focal quartet of gray mouse lemurs (Microcebus murinus), we estimated the mutation rate to be among the highest calculated for a mammal at 1.52 × 10-8 (95% credible interval: 1.28 × 10-8-1.78 × 10-8) mutations/site/generation. Further, we found an unexpectedly low count of paternal mutations, and only a modest overrepresentation of mutations at CpG sites. Despite the surprising nature of these results, we found both the rate and spectrum to be robust to the manipulation of a wide range of computational filtering criteria. We also sequenced a technical replicate to estimate a false-negative and false-positive rate for our data and show that any point estimate of a de novo mutation rate should be considered with a large degree of uncertainty. For validation, we conducted an independent analysis of context-dependent substitution types for gray mouse lemur and five additional primate species for which de novo mutation rates have also been estimated. These comparisons revealed general consistency of the mutation spectrum between the pedigree-based and the substitution-rate analyses for all species compared.

Incorporating Nearest-Neighbor Site Dependence into Protein Evolution Models.

Evolutionary models of proteins are widely used for statistical sequence alignment and inference of homology and phylogeny. However, the vast majority of these models rely on an unrealistic assumption of independent evolution between sites. Here we focus on the related problem of protein structure alignment, a classic tool of computational biology that is widely used to identify structural and functional similarity and to infer homology among proteins. A site-independent statistical model for protein structural evolution has previously been introduced and shown to significantly improve alignments and phylogenetic inferences compared with approaches that utilize only amino acid sequence information. Here we extend this model to account for correlated evolutionary drift among neighboring amino acid positions. The result is a spatiotemporal model of protein structure evolution, described by a multivariate diffusion process convolved with a spatial birth-death process. This extended site-dependent model (SDM) comes with little additional computational cost or analytical complexity compared with the site-independent model (SIM). We demonstrate that this SDM yields a significant reduction of bias in estimated evolutionary distances and helps further improve phylogenetic tree reconstruction. We also develop a simple model of site-dependent sequence evolution, which we use to demonstrate the bias resulting from the application of standard site-independent sequence evolution models.

Pregnancy outcomes after frozen-thawed single euploid blastocyst transfer following IVF cycles using GNRH agonist or HCG trigger for final oocyte maturation.

PURPOSE: To assess whether GnRH agonist trigger impacts the implantation potential of euploid embryos. METHODS: Retrospective cohort study done at an academic IVF center evaluating frozen-thawed embryo transfer (FET) cycles in which single-euploid blastocysts were transferred between 2014 and 2019. All embryos were generated in an IVF cycle which used GnRHa or hCG trigger and then were transferred in a programmed or natural FET cycle. Only the first FET cycle was included for each patient. Primary outcome was ongoing pregnancy rate or live birth rate (OPR/LBR). Secondary outcomes were implantation rate (IR), clinical pregnancy rate (CPR), clinical loss rate (CLR), and multiple pregnancy rate (MPR). Logistic regression was performed to control for confounding variables. A p value of < 0.05 was considered statistically significant. RESULTS: Two hundred sixty-three FET cycles were included for analysis (GnRHa = 145; hCG = 118). The GnRHa group was significantly younger (35.2 vs. 37.5 years) and had higher AMH values (4.50 ng/ml vs. 2.03 ng/ml) than the hCG group, respectively (p < 0.05). There was no significant difference in OPR/LBR (64.1% (93/145) vs. 65.3% (77/118); p = 0.90) between the GnRHa and hCG groups, respectively. There was also no significant difference in IR, CPR, CLR, or MPR between groups. After controlling for confounding variables, the adjusted odds ratio for OPR/LBR was 0.941 (95% CI, 0.534-1.658); p = 0.83) comparing GnRHa to hCG. Pregnancy outcomes did not significantly differ when groups were stratified by age (< 35 vs. > 35 years old). CONCLUSIONS: Our findings confirm that euploid embryos created after hCG or GnRHa trigger have the same potential for pregnancy.

Improving Cancer Drug Discovery by Studying Cancer across the Tree of Life.

Despite a considerable expenditure of time and resources and significant advances in experimental models of disease, cancer research continues to suffer from extremely low success rates in translating preclinical discoveries into clinical practice. The continued failure of cancer drug development, particularly late in the course of human testing, not only impacts patient outcomes, but also drives up the cost for those therapies that do succeed. It is clear that a paradigm shift is necessary if improvements in this process are to occur. One promising direction for increasing translational success is comparative oncology-the study of cancer across species, often involving veterinary patients that develop naturally-occurring cancers. Comparative oncology leverages the power of cross-species analyses to understand the fundamental drivers of cancer protective mechanisms, as well as factors contributing to cancer initiation and progression. Clinical trials in veterinary patients with cancer provide an opportunity to evaluate novel therapeutics in a setting that recapitulates many of the key features of human cancers, including genomic aberrations that underly tumor development, response and resistance to treatment, and the presence of comorbidities that can affect outcomes. With a concerted effort from basic scientists, human physicians and veterinarians, comparative oncology has the potential to enhance the cost-effectiveness and efficiency of pipelines for cancer drug discovery and other cancer treatments.

Independent serum markers of corpora lutea function after gonadotropin-releasing hormone agonist trigger and adjuvant low dose human chorionic gonadotropin in in vitro fertilization.

OBJECTIVE: To characterize corpora lutea (CL) function after gonadotropin-releasing hormone agonist (GnRHa) trigger with the use of adjuvant human chorionic gonadotropin (hCG). DESIGN: Secondary analysis of serum from prospective randomized clinical trial. SETTING: University-based fertility center. PATIENT(S): Women under 40 years of age at risk of ovarian hyperstimulation syndrome (OHSS) with serum E2 level <4,000 pg/mL. INTERVENTIONS(S): All subjects underwent ovarian stimulation with the use of a GnRH antagonist protocol. Within a larger study, subjects were randomized to receive 1,000 IU hCG at the time of GnRHa trigger and placebo at the time of vaginal oocyte retrieval (VOR) or placebo at the time of GnRHa trigger and 1,500 IU hCG at the time of VOR. MAIN OUTCOME MEASURE(S): Luteal phase and early pregnancy curves of serum prorenin and 17α-hydroxyprogesterone (17OH-P). RESULT(S): Thirty subjects enrolled in this secondary analysis. Serum 17OH-P peaked in the early luteal phase, 5 days after GnRHa trigger, with a nadir in the mid-luteal phase 9 days after trigger. Serum prorenin peaked in the luteal phase 2 days after GnRHa trigger, independently from adjuvant hCG timing, and reached a nadir at 9 days after trigger. CL function appears higher when adjuvant hCG is given at VOR compared with adjuvant hCG given at the time of trigger. CONCLUSION(S): CL function, as interpreted by proxy measures of serum prorenin and 17OH-P with pregnancy, continues despite GnRHa trigger. Both options for adjuvant hCG timing are sufficient for CL rescue and successful pregnancy, so the potential for OHSS risk with increased CL activity after hCG at VOR should be considered. CLINICAL TRIAL REGISTRATION NUMBER: NCT01815138.

Euploidy rates between cycles triggered with gonadotropin-releasing hormone agonist and human chorionic gonadotropin.

OBJECTIVE: To evaluate differences in euploidy rates between IVF cycles triggered with either GnRH agonist (GnRHa) or hCG. DESIGN: Retrospective cohort study. SETTING: University-affiliated fertility center. PATIENT(S): A total of 366 patients performing 539 IVF cycles utilizing preimplantation genetic testing for aneuploidy (PGT-A). INTERVENTION(S): Gonadotropin-releasing hormone agonist or hCG trigger of oocyte maturation during IVF cycles. MAIN OUTCOME MEASURE(S): Rate of euploid embryos. RESULT(S): Patients in the GnRHa trigger arm were younger, with a lower body mass index and higher antimüllerian hormone level, and they had a higher number of oocytes retrieved and embryos biopsied. Euploid rate per embryo biopsied was higher after GnRHa trigger than after hCG trigger (37.8% ± 2.1% vs. 30.3% ± 1.8%), but multivariate regression analysis controlling for potential confounding factors did not show any differences between the two groups. Moreover, the euploid rate per oocyte retrieved was not significantly different overall (GnRHa vs. hCG: 33.9% ± 2.2% vs. 28.0% ± 1.9%). The anticipated decline in the rate of euploid embryos per oocyte retrieved went from 15.8% ± 1.2% for age <35 years to 4.3% ± 0.9% for patients aged ≥41 years. There were no significant differences between the two groups after stratifying by age and controlling for PGT-A testing modality. CONCLUSION(S): Both GnRHa and hCG trigger result in comparable euploid rates. Trigger with GnRHa should therefore be considered a valid option for trigger modality in freeze-all PGT-A cycles, in view of its demonstrated effectiveness and known safety enhancement.

Information Criteria for Comparing Partition Schemes.

When inferring phylogenies, one important decision is whether and how nucleotide substitution parameters should be shared across different subsets or partitions of the data. One sort of partitioning error occurs when heterogeneous subsets are mistakenly lumped together and treated as if they share parameter values. The opposite kind of error is mistakenly treating homogeneous subsets as if they result from distinct sets of parameters. Lumping and splitting errors are not equally bad. Lumping errors can yield parameter estimates that do not accurately reflect any of the subsets that were combined whereas splitting errors yield estimates that did not benefit from sharing information across partitions. Phylogenetic partitioning decisions are often made by applying information criteria such as the Akaike information criterion (AIC). As with other information criteria, the AIC evaluates a model or partition scheme by combining the maximum log-likelihood value with a penalty that depends on the number of parameters being estimated. For the purpose of selecting an optimal partitioning scheme, we derive an adjustment to the AIC that we refer to as the AIC$^{(p)}$ and that is motivated by the idea that splitting errors are less serious than lumping errors. We also introduce a similar adjustment to the Bayesian information criterion (BIC) that we refer to as the BIC$^{(p)}$. Via simulation and empirical data analysis, we contrast AIC and BIC behavior to our suggested adjustments. We discuss these results and also emphasize why we expect the probability of lumping errors with the AIC$^{(p)}$ and the BIC$^{(p)}$ to be relatively robust to model parameterization.

Frozen blastocyst transfer outcomes in immediate versus delayed subsequent cycles following GnRH agonist or hCG triggers.

PURPOSE: The aim of this study is to analyze clinical pregnancy rates (CPR) and ongoing pregnancy rates (OPR) for frozen embryo transfers (FET) performed with blastocysts in the cycle immediately after GnRH agonist (GnRHa) versus human chorionic gonadotropin (hCG) triggers, with outcomes of delayed FET for comparison. METHODS: Retrospective cohort study at a university-affiliated in vitro fertilization (IVF) clinic, including patients undergoing IVF between 2013-16 with a blastocyst FET performed within two menstrual cycles of a previous stimulation cycle and vaginal oocyte retrieval (VOR). FETs included programmed and natural endometrial preparation. Outcome measures were clinical and ongoing pregnancy rates. RESULTS: CPR and OPR for 344 FET cycles were similar when comparing immediate and delayed transfer overall (crude CPR 67.5 versus 76.5%, p = 0.11; OPR 57.5 versus 66.7%, p = 0.13), and after stratifying by cycles following hCG trigger (OPR 62.5 versus 66.3%, p = 0.61) and GnRHa trigger (OPR 55.6 versus 64.5%, p = 0.17). When considering a number of predictors for OPR, an adjusted odds ratio (OR) of 1.74 [95% CI 1.00-3.03] approached significance in favor of delayed FET. CONCLUSIONS: Regardless of trigger modality, patients can be reassured that pregnancy rates with FET are high in immediate and delayed cycles. However, our study suggests a potential benefit in delaying a cycle before proceeding with FET.

Detection of an Inherited Deletion in Products of Conception in a Patient With Recurrent Losses and Normal Karyotype.

BACKGROUND: Microarray analysis testing on products of conception can provide valuable information in the evaluation of recurrent pregnancy loss beyond ploidy status. CASE: A maternally inherited deletion on the X chromosome was detected by microarray analysis performed on products of conception in a couple with recurrent pregnancy loss. The mother had a previously demonstrated normal karyotype with standard cytogenetic analysis but was subsequently determined to have the same X chromosome deletion by oligonucleotide single-nucleotide polymorphism (SNP) microarray analysis. CONCLUSION: Direct testing of products of conception using oligonucleotide SNP microarray identified a maternally inherited microdeletion on the X chromosome in a patient with recurrent losses and normal karyotype. Going forward, the couple may use preimplantation genetic diagnosis testing to identify embryos free of this deletion for transfer.

A Phylogenetic Approach Finds Abundant Interlocus Gene Conversion in Yeast.

Interlocus gene conversion (IGC) homogenizes repeats. While genomes can be repeat-rich, the evolutionary importance of IGC is poorly understood. Additional statistical tools for characterizing it are needed. We propose a composite likelihood strategy for incorporating IGC into widely-used probabilistic models for sequence changes that originate with point mutation. We estimated the percentage of nucleotide substitutions that originate with an IGC event rather than a point mutation in 14 groups of yeast ribosomal protein-coding genes, and found values ranging from 20% to 38%. We designed and applied a procedure to determine whether these percentages are inflated due to artifacts arising from model misspecification. The results of this procedure are consistent with IGC having had an important role in the evolution of each of these 14 gene families. We further investigate the properties of our IGC approach via simulation. In contrast to usual practice, our findings suggest that the IGC should and can be considered when multigene family evolution is investigated.