Is it possible to identify new mutations potentially associated with non-syndromic primary ovarian insufficiency (POI) via whole-exome sequencing (WES)? WES is an efficient tool to study genetic causes of POI as we have identified new mutations, some of which lead to protein destablization potentially contributing to the disease etiology. POI is a frequently occurring complex pathology leading to infertility. Mutations in only few candidate genes, mainly identified by Sanger sequencing, have been definitively related to the pathogenesis of the disease. This is a retrospective cohort study performed on 69 women affected by POI. WES and an innovative bioinformatics analysis were used on non-synonymous sequence variants in a subset of 420 selected POI candidate genes. Mutations in BMPR1B and GREM1 were modeled by using fragment molecular orbital analysis. Fifty-five coding variants in 49 genes potentially related to POI were identified in 33 out of 69 patients (48%). These genes participate in key biological processes in the ovary, such as meiosis, follicular development, granulosa cell differentiation/proliferation and ovulation. The presence of at least two mutations in distinct genes in 42% of the patients argued in favor of a polygenic nature of POI. It is possible that regulatory regions, not analyzed in the present study, carry further variants related to POI. WES and the in silico analyses presented here represent an efficient approach for mapping variants associated with POI etiology. Sequence variants presented here represents potential future genetic biomarkers. This study was supported by the Universidad del Rosario and Colciencias (Grants CS/CIGGUR-ABN062-2016 and 672-2014). Colciencias supported Liliana Catherine Patiño´s work (Fellowship: 617, 2013). The authors declare no conflict of interest.

One hundred and ten novel MHC-DRB gene exon 2 nucleotide sequences were sequenced in 96 monkeys from three owl monkey species (67 from Aotus nancymaae, 30 from Aotus nigriceps and 13 from Aotus vociferans). Owl monkeys, like humans, have high MHC-DRB allele polymorphism, revealing a striking similarity with several human allele lineages in the peptide binding region and presenting major convergence with DRB lineages from several Catarrhini (humans, apes and Old World monkeys) rather than with others New World monkeys (Platyrrhini). The parallelism between human and Aotus MHC-DRB reveals additional similarities regarding variability pattern, selection pressure and physicochemical constraints in amino acid replacements. These observations concerning previous findings of similarity between the Aotus immune system molecules and their human counterparts affirm this specie’s usefulness as an excellent animal model in biomedical research.

Recurrent pregnancy loss is a frequently occurring human infertility-related disease affecting ~1% of women. It has been estimated that the cause remains unexplained in >50% cases which strongly suggests that genetic factors may contribute towards the phenotype. Concerning its molecular aetiology numerous studies have had limited success in identifying the disease’s genetic causes. This might have been due to the fact that hundreds of genes are involved in each physiological step necessary for guaranteeing reproductive success in mammals. In such scenario, next generation sequencing provides a potentially interesting tool for research into recurrent pregnancy loss causative mutations. The present study involved whole-exome sequencing and an innovative bioinformatics analysis, for the first time, in 49 unrelated women affected by recurrent pregnancy loss. We identified 27 coding variants (22 genes) potentially related to the phenotype (41% of patients). The affected genes, which were enriched by potentially deleterious sequence variants, belonged to distinct molecular cascades playing key roles in implantation/pregnancy biology. Using a quantum chemical approach method we established that mutations in MMP-10 and FGA proteins led to substantial energetic modifications suggesting an impact on their functions and/or stability. The next generation sequencing and bioinformatics approaches presented here represent an efficient way to find mutations, having potentially moderate/strong functional effects, associated with recurrent pregnancy loss aetiology. We consider that some of these variants (and genes) represent probable future biomarkers for recurrent pregnancy loss.

A key issue relating to developing multi-component anti-malarial vaccines, lies in studying Plasmodium vivax surface proteins' genetic variation. The present work was aimed at amplifying, cloning and sequencing the gene encoding P. vivax merozoite surface protein 5 (PvMSP5) in samples obtained from infected patients from Colombian areas having varying malaria transmission rates.Nucleotide sequence data reported in this paper are available in the GenBank, EMBL and DDBJ databases under Accessions numbers DQ341586 to DQ341601. Our results have revealed that PvMSP5 is one of the P. vivax surface proteins having greater polymorphism, this being restricted to specific protein regions. The intron and exon II (which includes the GPI anchor and EGF-like domain) were both highly conserved when compared to exon I; exon I displayed the greatest variation and most of the recombination events occurred within it. No geographical grouping was observed. The Nei-Gojobori test revealed significant positive selection in the samples analysed here, whereas Tajima and Fu and Li tests presented a neutral selection pattern. The results reflected a localized variation pattern, recombination between PvMSP5 alleles and also functional and immune pressures, where stronger selective forces might be acting on exon I than on exon II, suggesting that the latter could be an important region to be included in an anti-malarial vaccine.

Hierarchical cluster analysis (HCA) is a widely used classificatory technique in many areas of scientific knowledge. Applications usually yield a dendrogram from an HCA run over a given data set, using a grouping algorithm and a similarity measure. However, even when such parameters are fixed, ties in proximity (i.e. two equidistant clusters from a third one) may produce several different dendrograms, having different possible clustering patterns (different classifications). This situation is usually disregarded and conclusions are based on a single result, leading to questions concerning the permanence of clusters in all the resulting dendrograms; this happens, for example, when using HCA for grouping molecular descriptors to select that less similar ones in QSAR studies. Representing dendrograms in graph theoretical terms allowed us to introduce four measures of cluster frequency in a canonical way, and use them to calculate cluster frequencies over the set of all possible dendrograms, taking all ties in proximity into account. A toy example of well separated clusters was used, as well as a set of 1666 molecular descriptors calculated for a group of molecules having hepatotoxic activity to show how our functions may be used for studying the effect of ties in HCA analysis. Such functions were not restricted to the tie case; the possibility of using them to derive cluster stability measurements on arbitrary sets of dendrograms having the same leaves is discussed, e.g. dendrograms from variations of HCA parameters. It was found that ties occurred frequently, some yielding tens of thousands of dendrograms, even for small data sets. Our approach was able to detect trends in clustering patterns by offering a simple way of measuring their frequency, which is often very low. This would imply, that inferences and models based on descriptor classifications (e.g. QSAR) are likely to be biased, thereby requiring an assessment of their reliability. Moreover, any classification of molecular descriptors is likely to be far from unique. Our results highlight the need for evaluating the effect of ties on clustering patterns before classification results can be used accurately.

The population of malaria-causing parasites is characterized by great genetic diversity. Knowledge of the polymorphism generation mechanism is a central issue for developing effective vaccines against malaria and understanding the parasite population structure. Plasmodium vivax genetic diversity has been explained in terms of two major factors: natural selection and intragenic recombination. A modular organization was found within P. vivax Duffy binding protein in the present work. Four Colombian isolates have identical sequences to Salvador-1 strain amongst dpb regions III–VI analysed, suggesting a high identity between Central and South American isolates. Geographically clustered sectors, corresponding to cysteine-rich regions (II and VI), show a high sequence diversity that could reflect a possible immune response evasion mechanism; both positive and negative selection were detected in these regions. In contrast, other dbp gene regions display a non-geographical clustering pattern, lower sequence diversity and predominant negative selective pressure. Recombination was homogeneously detected all along the molecule. These findings suggest that diversification vs. homogenizing forces, drive dbp gene evolution and determine its mosaic region organization.