Anterior Interhemispheric Approach for the Surgical Treatment of Azygos Anterior Cerebral Artery Aneurysms: A Case Series.

The azygos artery is an uncommon vascular variant of the anterior cerebral artery (ACA). This anomaly is associated in a high percentage with aneurysms. Management of azygos ACA aneurysms represents a surgical challenge. We present five patients who underwent microsurgical treatment for distal azygos ACA aneurysms with complex morphology. Four patients showed subarachnoid hemorrhage (SAH) and one complained of sentinel headache. Early preoperative digital subtraction angiography (DSA) or computerized tomography angiography (CTA) was performed. All patients were treated by surgical clipping via an anterior interhemispheric approach. During follow-up, all patients had a satisfactory outcome, with postoperative angiograms showing complete resolution of aneurysms.

Maintenance of genetic diversity in subdivided populations using genomic coancestry matrices.

For both undivided and subdivided populations, the consensus method to maintain genetic diversity is the Optimal Contribution (OC) method. For subdivided populations, this method determines the optimal contribution of each candidate to each subpopulation to maximize global genetic diversity (which implicitly optimizes migration between subpopulations) while balancing the relative levels of coancestry between and within subpopulations. Inbreeding can be controlled by increasing the weight given to within-subpopulation coancestry (λ). Here we extend the original OC method for subdivided populations that used pedigree-based coancestry matrices, to the use of more accurate genomic matrices. Global levels of genetic diversity, measured as expected heterozygosity and allelic diversity, their distributions within and between subpopulations, and the migration pattern between subpopulations, were evaluated via stochastic simulations. The temporal trajectory of allele frequencies was also investigated. The genomic matrices investigated were (i) the matrix based on deviations of the observed number of alleles shared by two individuals from the expected number under Hardy-Weinberg equilibrium; and (ii) a matrix based on a genomic relationship matrix. The matrix based on deviations led to higher global and within-subpopulation expected heterozygosities, lower inbreeding and similar allelic diversity than the second genomic and pedigree-based matrices when a relatively high weight was given to the within-subpopulation coancestries (λ ≥ 5). Under this scenario, allele frequencies moved only slightly away from the initial frequencies. Therefore, the recommended strategy is to use the former matrix in the OC methodology giving a high weight to the within-subpopulation coancestry.

A comparison of marker-based estimators of inbreeding and inbreeding depression.

BACKGROUND: The availability of genome-wide marker data allows estimation of inbreeding coefficients (F, the probability of identity-by-descent, IBD) and, in turn, estimation of the rate of inbreeding depression (ΔID). We investigated, by computer simulations, the accuracy of the most popular estimators of inbreeding based on molecular markers when computing F and ΔID in populations under random mating, equalization of parental contributions, and artificially selected populations. We assessed estimators described by Li and Horvitz (FLH1 and FLH2), VanRaden (FVR1 and FVR2), Yang and colleagues (FYA1 and FYA2), marker homozygosity (FHOM), runs of homozygosity (FROH) and estimates based on pedigree (FPED) in comparison with estimates obtained from IBD measures (FIBD). RESULTS: If the allele frequencies of a base population taken as a reference for the computation of inbreeding are known, all estimators based on marker allele frequencies are highly correlated with FIBD and provide accurate estimates of the mean ΔID. If base population allele frequencies are unknown and current frequencies are used in the estimations, the largest correlation with FIBD is generally obtained by FLH1 and the best estimator of ΔID is FYA2. The estimators FVR2 and FLH2 have the poorest performance in most scenarios. The assumption that base population allele frequencies are equal to 0.5 results in very biased estimates of the average inbreeding coefficient but they are highly correlated with FIBD and give relatively good estimates of ΔID. Estimates obtained directly from marker homozygosity (FHOM) substantially overestimated ΔID. Estimates based on runs of homozygosity (FROH) provide accurate estimates of inbreeding and ΔID. Finally, estimates based on pedigree (FPED) show a lower correlation with FIBD than molecular estimators but provide rather accurate estimates of ΔID. An analysis of data from a pig population supports the main findings of the simulations. CONCLUSIONS: When base population allele frequencies are known, all marker-allele frequency-based estimators of inbreeding coefficients generally show a high correlation with FIBD and provide good estimates of ΔID. When base population allele frequencies are unknown, FLH1 is the marker frequency-based estimator that is most correlated with FIBD, and FYA2 provides the most accurate estimates of ΔID. Estimates from FROH are also very precise in most scenarios. The estimators FVR2 and FLH2 have the poorest performances.

Genomic Prediction Methods Accounting for Nonadditive Genetic Effects.

The use of genomic information for prediction of future phenotypes or breeding values for the candidates to selection has become a standard over the last decade. However, most procedures for genomic prediction only consider the additive (or substitution) effects associated with polymorphic markers. Nevertheless, the implementation of models that consider nonadditive genetic variation may be interesting because they (1) may increase the ability of prediction, (2) can be used to define mate allocation procedures in plant and animal breeding schemes, and (3) can be used to benefit from nonadditive genetic variation in crossbreeding or purebred breeding schemes. This study reviews the available methods for incorporating nonadditive effects into genomic prediction procedures and their potential applications in predicting future phenotypic performance, mate allocation, and crossbred and purebred selection. Finally, a brief outline of some future research lines is also proposed.

A specific structure and high richness characterize intestinal microbiota of HIV-exposed seronegative individuals.

Intestinal microbiota facilitates food breakdown for energy metabolism and influences the immune response, maintaining mucosal homeostasis. Overall, HIV infection is associated with intestinal dysbiosis and immune activation, which has been related to seroconversion in HIV-exposed individuals. However, it is unclear whether microbiota dysbiosis is the cause or the effect of immune alterations and disease progression or if it could modulate the risk of acquiring the HIV infection. We characterize the intestinal microbiota and determine its association with immune regulation in HIV-exposed seronegative individuals (HESN), HIV-infected progressors (HIV+), and healthy control (HC) subjects. For this, feces and blood were collected. The microbiota composition of HESN showed a significantly higher alpha (p = 0.040) and beta diversity (p = 0.006) compared to HC, but no differences were found compared to HIV+. A lower Treg percentage was observed in HESN (1.77%) than HC (2.98%) and HIV+ (4.02%), with enrichment of the genus Butyrivibrio (p = 0.029) being characteristic of this profile. Moreover, we found that Megasphaera (p = 0.017) and Victivallis (p = 0.0029) also are enriched in the microbiota composition in HESN compared to HC and HIV+ subjects. Interestingly, an increase in Succinivibrio and Prevotella, and a reduction in Bacteroides genus, which is typical of HIV-infected individuals, were observed in both HESN and HIV+, compared to HC. Thus, HESNs have a microbiota profile, similar to that observed in HIV+, most likely because HESN are cohabiting with their HIV+ partners.

The value of genomic relationship matrices to estimate levels of inbreeding.

BACKGROUND: Genomic relationship matrices are used to obtain genomic inbreeding coefficients. However, there are several methodologies to compute these matrices and there is still an unresolved debate on which one provides the best estimate of inbreeding. In this study, we investigated measures of inbreeding obtained from five genomic matrices, including the Nejati-Javaremi allelic relationship matrix (FNEJ), the Li and Horvitz matrix based on excess of homozygosity (FL&H), and the VanRaden (methods 1, FVR1, and 2, FVR2) and Yang (FYAN) genomic relationship matrices. We derived expectations for each inbreeding coefficient, assuming a single locus model, and used these expectations to explain the patterns of the coefficients that were computed from thousands of single nucleotide polymorphism genotypes in a population of Iberian pigs. RESULTS: Except for FNEJ, the evaluated measures of inbreeding do not match with the original definitions of inbreeding coefficient of Wright (correlation) or Malécot (probability). When inbreeding coefficients are interpreted as indicators of variability (heterozygosity) that was gained or lost relative to a base population, both FNEJ and FL&H led to sensible results but this was not the case for FVR1, FVR2 and FYAN. When variability has increased relative to the base, FVR1, FVR2 and FYAN can indicate that it decreased. In fact, based on FYAN, variability is not expected to increase. When variability has decreased, FVR1 and FVR2 can indicate that it has increased. Finally, these three coefficients can indicate that more variability than that present in the base population can be lost, which is also unreasonable. The patterns for these coefficients observed in the pig population were very different, following the derived expectations. As a consequence, the rate of inbreeding depression estimated based on these inbreeding coefficients differed not only in magnitude but also in sign. CONCLUSIONS: Genomic inbreeding coefficients obtained from the diagonal elements of genomic matrices can lead to inconsistent results in terms of gain and loss of genetic variability and inbreeding depression estimates, and thus to misleading interpretations. Although these matrices have proven to be very efficient in increasing the accuracy of genomic predictions, they do not always provide a useful measure of inbreeding.

Pseudoirreversible slow-binding inhibition of trypanothione reductase by a protein-protein interaction disruptor.

BACKGROUND AND PURPOSE: Peptide P4 was described as a dimerization disruptor of trypanothione reductase (TryR), a homodimeric enzyme essential for survival of trypanosomatids. Determination of the true inhibitory constant (Ki ) for P4 was not achieved because reaction rates continuously decreased with time, even when substrate concentration was kept constant. The aim of this study was to find a suitable kinetic model that could allow characterization of the complex pattern of TryR inhibition caused by P4. EXPERIMENTAL APPROACH: After showing the slow-binding and pseudoirreversible activity of P4 against Leishmania infantum trypanothione reductase (Li-TryR), analysis of the curvatures of the reaction progress curves at different inhibitor concentrations allowed us to define the apparent inhibitory constants (Kiapp ) at five different substrate concentrations. Analysis of the changes in Kiapp values allowed precise definition of the type of inhibition. KEY RESULTS: Li-TryR inhibition by P4 requires two sequential steps that involve rapid generation of a reversible enzyme-inhibitor complex followed by a pseudoirreversible slow inactivation of the enzyme. Recovery of enzyme activity after inhibitor dissociation is barely detectable. P4 is a non-competitive pseudoirreversible inhibitor of Li- TryR that displays an overall inhibition constant (Ki* ) smaller than 0.02 µM. CONCLUSION AND IMPLICATIONS: Li-TryRdimer disruption by peptide P4 is a pseudoirreversible time-dependent process which is non-competitive with respect to the oxidized trypanothione (TS2 ) substrate. Therefore, unlike reversible Li-TryR competitive inhibitors, enzyme inhibition by P4 is not affected by the TS2 accumulation observed during oxidant processes such as the oxidative burst in host macrophages.

The concept of effective population size loses its meaning in the context of optimal management of diversity using molecular markers.

Effective population size is a key parameter in conservation genetics. In the management of conservation programs using pedigree information, there is a consensus that the optimal method for maximizing effective population size is to calculate the contribution of each potential parent (the number of offspring that each individual leaves to the next generation) by minimizing the global pedigree-based coancestry between potential parents weighted by their contributions. When using molecular data, the optimal method for managing genetic diversity will remain the same but now the molecular coancestry calculated from markers will replace the pedigree-based coancestry. However, in this situation, the concept of effective population size loses its meaning because with optimal molecular management, genetic diversity increases in early generations and therefore effective population size takes negative values. Furthermore, in the long term, the molecular effective population size does not attain an asymptotic value but it shows an unpredictable behaviour.

Trypanothione reductase inhibition and anti-leishmanial activity of all-hydrocarbon stapled α-helical peptides with improved proteolytic stability.

Trypanothione reductase (TryR) is a well-established target in the search for novel antitrypanosomal and antileishmanial agents. We have previously identified linear and lactam-bridged 13-residue peptides derived from an α-helical region making up part of the dimeric interface of Leishmania infantum TryR (Li-TryR) which prevent trypanothione reduction by disrupting enzyme dimerization. We now show that i,i + 4 side-chain cross-linking with an all-hydrocarbon staple stabilizes the helical structure of these peptides and significantly improves their resistance to protease cleavage relative to previous linear and cyclic lactam analogues. Interestingly, replacement of the amide bridge by the hydrocarbon staple at the same cyclization positions generates derivatives (2 and 3) that similarly inhibit oxidoreductase activity of the enzyme but unexpectedly stabilize the TryR homodimer. The most proteolytically stable peptide 2 covalently linked to oligoarginines displayed potent in vitro leishmanicidal activity against L. infantum parasites.

Non-additive Effects in Genomic Selection.

In the last decade, genomic selection has become a standard in the genetic evaluation of livestock populations. However, most procedures for the implementation of genomic selection only consider the additive effects associated with SNP (Single Nucleotide Polymorphism) markers used to calculate the prediction of the breeding values of candidates for selection. Nevertheless, the availability of estimates of non-additive effects is of interest because: (i) they contribute to an increase in the accuracy of the prediction of breeding values and the genetic response; (ii) they allow the definition of mate allocation procedures between candidates for selection; and (iii) they can be used to enhance non-additive genetic variation through the definition of appropriate crossbreeding or purebred breeding schemes. This study presents a review of methods for the incorporation of non-additive genetic effects into genomic selection procedures and their potential applications in the prediction of future performance, mate allocation, crossbreeding, and purebred selection. The work concludes with a brief outline of some ideas for future lines of that may help the standard inclusion of non-additive effects in genomic selection.

Improved proteolytic stability and potent activity against Leishmania infantum trypanothione reductase of α/ß-peptide foldamers conjugated to cell-penetrating peptides.

The objective of the current study was to enhance the proteolytic stability of peptide-based inhibitors that target critical protein-protein interactions at the dimerization interface of Leishmania infantum trypanothione reductase (Li-TryR) using a backbone modification strategy. To achieve this goal we carried out the synthesis, proteolytic stability studies and biological evaluation of a small library of α/ß3-peptide foldamers of different length (from 9-mers to 13-mers) and different αâ†’ß substitution patterns related to prototype linear α-peptides. We show that several 13-residue α/ß3-peptide foldamers retain inhibitory potency against the enzyme (in both activity and dimerization assays) while they are far less susceptible to proteolytic degradation than an analogous α-peptide. The strong dependence of the binding affinities for Li-TryR on the length of the α,ß-peptides is supported by theoretical calculations on conformational ensembles of the resulting complexes. The conjugation of the most proteolytically stable α/ß-peptide with oligoarginines results in a molecule with potent activity against L. infantum promastigotes and amastigotes.

Orthogonal Estimates of Variances for Additive, Dominance, and Epistatic Effects in Populations.

Genomic prediction methods based on multiple markers have potential to include nonadditive effects in prediction and analysis of complex traits. However, most developments assume a Hardy-Weinberg equilibrium (HWE). Statistical approaches for genomic selection that account for dominance and epistasis in a general context, without assuming HWE (e.g., crosses or homozygous lines), are therefore needed. Our method expands the natural and orthogonal interactions (NOIA) approach, which builds incidence matrices based on genotypic (not allelic) frequencies, to include genome-wide epistasis for an arbitrary number of interacting loci in a genomic evaluation context. This results in an orthogonal partition of the variances, which is not warranted otherwise. We also present the partition of variance as a function of genotypic values and frequencies following Cockerham's orthogonal contrast approach. Then we prove for the first time that, even not in HWE, the multiple-loci NOIA method is equivalent to construct epistatic genomic relationship matrices for higher-order interactions using Hadamard products of additive and dominant genomic orthogonal relationships. A standardization based on the trace of the relationship matrices is, however, needed. We illustrate these results with two simulated F1 (not in HWE) populations, either in linkage equilibrium (LE), or in linkage disequilibrium (LD) and divergent selection, and pure biological dominant pairwise epistasis. In the LE case, correct and orthogonal estimates of variances were obtained using NOIA genomic relationships but not if relationships were constructed assuming HWE. For the LD simulation, differences were smaller, due to the smaller deviation of the F1 from HWE. Wrongly assuming HWE to build genomic relationships and estimate variance components yields biased estimates, inflates the total genetic variance, and the estimates are not empirically orthogonal. The NOIA method to build genomic relationships, coupled with the use of Hadamard products for epistatic terms, allows the obtaining of correct estimates in populations either in HWE or not in HWE, and extends to any order of epistatic interactions.

First example of peptides targeting the dimer interface of Leishmania infantum trypanothione reductase with potent in vitro antileishmanial activity.

A series of 9-mer and 13-mer amide-bridged cyclic peptides derived from the linear prototype Ac-PKIIQSVGIS-Nle-K-Nle-NH2 (Toro et al. ChemBioChem2013) has been designed and synthesized by introduction of the lactam between amino acid side chains that are separated by one helical turn (i, i+4). All of these compounds were tested in vitro as both dimerization and enzyme inhibitors of Leishmania infantum trypanothione reductase (Li-TryR). Three of the 13-mer cyclic peptide derivatives (3, 4 and 6) inhibited the oxidoreductase activity of Li-TryR in the low micromolar range and they also disrupted enzyme dimerization. Cyclic analogues 3 and 4 were more resistant to proteases than was the linear prototype. Furthermore, the most potent TryR inhibitors in the linear and cyclic series displayed potent in vitro activity against Leishmania infantum upon conjugation with cationic cell-penetrating peptides. To date, these conjugated peptides can be considered the first example of TryR dimerization inhibitors that are active in cell culture.

Past, present, and future of epigenetics applied to livestock breeding.

This article reviews the concept of Lamarckian inheritance and the use of the term epigenetics in the field of animal genetics. Epigenetics was first coined by Conrad Hal Waddington (1905-1975), who derived the term from the Aristotelian word epigenesis. There exists some controversy around the word epigenetics and its broad definition. It includes any modification of the expression of genes due to factors other than mutation in the DNA sequence. This involves DNA methylation, post-translational modification of histones, but also linked to regulation of gene expression by non-coding RNAs, genome instabilities or any other force that could modify a phenotype. There is little evidence of the existence of transgenerational epigenetic inheritance in mammals, which may commonly be confounded with environmental forces acting simultaneously on an individual, her developing fetus and the germ cell lines of the latter, although it could have an important role in the cellular energetic status of cells. Finally, we review some of the scarce literature on the use of epigenetics in animal breeding programs.

Do Molecular Markers Inform About Pleiotropy?

The availability of dense panels of common single-nucleotide polymorphisms and sequence variants has facilitated the study of statistical features of the genetic architecture of complex traits and diseases via whole-genome regressions (WGRs). At the onset, traits were analyzed trait by trait, but recently, WGRs have been extended for analysis of several traits jointly. The expectation is that such an approach would offer insight into mechanisms that cause trait associations, such as pleiotropy. We demonstrate that correlation parameters inferred using markers can give a distorted picture of the genetic correlation between traits. In the absence of knowledge of linkage disequilibrium relationships between quantitative or disease trait loci and markers, speculating about genetic correlation and its causes (e.g., pleiotropy) using genomic data is conjectural.

Optimizing the creation of base populations for aquaculture breeding programs using phenotypic and genomic data and its consequences on genetic progress.

The success of an aquaculture breeding program critically depends on the way in which the base population of breeders is constructed since all the genetic variability for the traits included originally in the breeding goal as well as those to be included in the future is contained in the initial founders. Traditionally, base populations were created from a number of wild strains by sampling equal numbers from each strain. However, for some aquaculture species improved strains are already available and, therefore, mean phenotypic values for economically important traits can be used as a criterion to optimize the sampling when creating base populations. Also, the increasing availability of genome-wide genotype information in aquaculture species could help to refine the estimation of relationships within and between candidate strains and, thus, to optimize the percentage of individuals to be sampled from each strain. This study explores the advantages of using phenotypic and genome-wide information when constructing base populations for aquaculture breeding programs in terms of initial and subsequent trait performance and genetic diversity level. Results show that a compromise solution between diversity and performance can be found when creating base populations. Up to 6% higher levels of phenotypic performance can be achieved at the same level of global diversity in the base population by optimizing the selection of breeders instead of sampling equal numbers from each strain. The higher performance observed in the base population persisted during 10 generations of phenotypic selection applied in the subsequent breeding program.

Improving the inference of population genetic structure in the presence of related individuals.

It is well known that the presence of related individuals can affect the inference of population genetic structure from molecular data. This has been verified, for example, on the unsupervised Bayesian clustering algorithm implemented in the software STRUCTURE. This methodology assumes, among others, Hardy-Weinberg and linkage equilibrium within subpopulations. The existence of groups of close relatives, such as full-sib families, may prevent these assumptions to be fulfilled, causing the algorithm to work suboptimally. The purpose of this study was to evaluate the effect of the presence of related individuals on a different methodology (implemented in CLUSTER_DIST) for population genetic structure inference. This approach arranges individuals to maximize the genetic distance between groups and does not make Hardy-Weinberg and linkage equilibrium assumptions. We study the robustness of this approach to the presence of close relatives in a sample using simulated scenarios involving combinations of several factors, including the number of subpopulations, the level of differentiation between them, the number, size and type (full or half-sibs) of families in a sample, and the type and number of molecular markers available for clustering analysis. Results indicate that the methodology that maximizes the genetic distance between subpopulations is less influenced by the presence of related individuals than the program STRUCTURE. Therefore, the former can be used, in combination with the program STRUCTURE, to analyse population genetic structure when related individuals are suspected to be present in a sample.

Cumulative cultural evolution: the role of teaching.

In humans, cultural transmission occurs usually by cumulative inheritance, generating complex adaptive behavioral features. Cumulative culture requires key psychological processes (fundamentally imitation and teaching) that are absent or impoverished in non-human primates. In this paper we analyze the role that teaching has played in human cumulative cultural evolution. We assume that a system of cumulative culture generates increasingly adaptive behaviors, that are also more complex and difficult to imitate. Our thesis is that, as cultural traits become more complex, cumulative cultural transmission requires teaching to ensure accurate transmission from one generation to the next. In an increasingly complex cultural environment, we consider that individuals commit errors in imitation. We develop a model of cumulative cultural evolution in a changing environment and show that these errors hamper the process of cultural accumulation. We also show that a system of teaching between parents and offspring that increases the fidelity of imitation unblocks the accumulation and becomes adaptive whenever the gain in fitness compensates the cost of teaching.