Hugo Naya

Predicting Quantitative Traits With Regression Models for Dense Molecular Markers and Pedigree

The availability of genomewide dense markers brings opportunities and challenges to breeding programs. An important question concerns the ways in which dense markers and pedigrees, together with phenotypic records, should be used to arrive at predictions of genetic values for complex traits. If a large number of markers are included in a regression model, marker-specific shrinkage of regression coefficients may be needed. For this reason, the Bayesian least absolute shrinkage and selection operator (LASSO) (BL) appears to be an interesting approach for fitting marker effects in a regression model. This article adapts the BL to arrive at a regression model where markers, pedigrees, and covariates other than markers are considered jointly. Connections between BL and other marker-based regression models are discussed, and the sensitivity of BL with respect to the choice of prior distributions assigned to key parameters is evaluated using simulation. The proposed model was fitted to two data sets from wheat and mouse populations, and evaluated using cross-validation methods. Results indicate that inclusion of markers in the regression further improved the predictive ability of models. An R program that implements the proposed model is freely available.

Small RNAs analysis in CLL reveals a deregulation of miRNA expression and novel miRNA candidates of putative relevance in CLL pathogenesis.

MicroRNAs (miRNAs) are a novel class of small noncoding RNA molecules that regulate gene expression by inducing degradation or translational inhibition of target mRNAs. There are more than 500 miRNA genes reported in the human genome, constituting one of the largest classes of regulatory genes. Increasing experimental evidence supports the idea of aberrant miRNA expression in cancer pathogenesis. We analyzed the pattern of miRNA expression in chronic lymphocytic leukemia (CLL) cells and our results showed a global reduction in miRNA expression levels in CLL cells associated to a consistent underexpression of miR-181a, let-7a and miR-30d. We observed overexpression of miR-155 and a set of five miRNAs that are differentially expressed between patients with different clinical outcomes. Five novel miRNA candidates cloned from leukemic cells are reported. Surprisingly, predicted mRNA targets for these novel miRNA revealed a high proportion of targets located in a small region of chromosome 1, which is frequently altered in human cancer. Additionally, several targets were shared by at least two of miRNA candidates. Predicted targets included several genes recently described as tumor suppressors. These data could afford new avenues for exploring innovative pathways in CLL biology and therapy.

Identification of new microRNAs in paired normal and tumor breast tissue suggests a dual role for the ERBB2/Her2 gene.

To comprehensively characterize microRNA (miRNA) expression in breast cancer, we performed the first extensive next-generation sequencing expression analysis of this disease. We sequenced small RNA from tumors with paired samples of normal and tumor-adjacent breast tissue. Our results indicate that tumor identity is achieved mainly by variation in the expression levels of a common set of miRNAs rather than by tissue-specific expression. We also report 361 new, well-supported miRNA precursors. Nearly two-thirds of these new genes were detected in other human tissues and 49% of the miRNAs were found associated with Ago2 in MCF7 cells. Ten percent of the new miRNAs are located in regions with high-level genomic amplifications in breast cancer. A new miRNA is encoded within the ERBB2/Her2 gene and amplification of this gene leads to overexpression of the new miRNA, indicating that this potent oncogene and important clinical marker may have two different biological functions. In summary, our work substantially expands the number of known miRNAs and highlights the complexity of small RNA expression in breast cancer.

Aerobiosis Increases the Genomic Guanine Plus Cytosine Content (GC%) in Prokaryotes

The huge variation in the genomic guanine plus cytosine content (GC%) among prokar-yotes has been explained by two mutually exclusive hypotheses, namely, selectionist and neutralist. The former proposals have in common the assumption that this feature is a form of adaptation to some ecological or physiological condition. On the other hand, the neutralist interpretation states that the variations are due only to different mutational biases. Since all of the traits that have been proposed by the selectionists either appeared to be limited to certain genera or were invalidated by the availability of more data, they cannot be considered as a selective force influencing the genomic GC% across all prokaryotes. In this report we show that aerobic prokaryotes display a significant increment in genomic GC% in relation to anaerobic ones. This is the first time that a link between a metabolic character and GC% has been found, independently of phylogenetic relationships and with a statistically significant amount of data.

Predictive ability of direct genomic values for lifetime net merit of Holstein sires using selected subsets of single nucleotide polymorphism markers

The objective of the present study was to assess the predictive ability of subsets of single nucleotide polymorphism (SNP) markers for development of low-cost, low-density genotyping assays in dairy cattle. Dense SNP genotypes of 4,703 Holstein bulls were provided by the USDA Agricultural Research Service. A subset of 3,305 bulls born from 1952 to 1998 was used to fit various models (training set), and a subset of 1,398 bulls born from 1999 to 2002 was used to evaluate their predictive ability (testing set). After editing, data included genotypes for 32,518 SNP and August 2003 and April 2008 predicted transmitting abilities (PTA) for lifetime net merit (LNM

Detecting Signatures of Selection Through Haplotype Differentiation Among Hierarchically Structured Populations

), the latter resulting from progeny testing. The Bayesian least absolute shrinkage and selection operator method was used to regress August 2003 PTA on marker covariates in the training set to arrive at estimates of marker effects and direct genomic PTA. The coefficient of determination (R(2)) from regressing the April 2008 progeny test PTA of bulls in the testing set on their August 2003 direct genomic PTA was 0.375. Subsets of 300, 500, 750, 1,000, 1,250, 1,500, and 2,000 SNP were created by choosing equally spaced and highly ranked SNP, with the latter based on the absolute value of their estimated effects obtained from the training set. The SNP effects were re-estimated from the training set for each subset of SNP, and the 2008 progeny test PTA of bulls in the testing set were regressed on corresponding direct genomic PTA. The R(2) values for subsets of 300, 500, 750, 1,000, 1,250, 1,500, and 2,000 SNP with largest effects (evenly spaced SNP) were 0.184 (0.064), 0.236 (0.111), 0.269 (0.190), 0.289 (0.179), 0.307 (0.228), 0.313 (0.268), and 0.322 (0.291), respectively. These results indicate that a low-density assay comprising selected SNP could be a cost-effective alternative for selection decisions and that significant gains in predictive ability may be achieved by increasing the number of SNP allocated to such an assay from 300 or fewer to 1,000 or more.

Correlations between genomic GC levels and optimal growth temperatures in prokaryotes

The detection of molecular signatures of selection is one of the major concerns of modern population genetics. A widely used strategy in this context is to compare samples from several populations and to look for genomic regions with outstanding genetic differentiation between these populations. Genetic differentiation is generally based on allele frequency differences between populations, which are measured by FST or related statistics. Here we introduce a new statistic, denoted hapFLK, which focuses instead on the differences of haplotype frequencies between populations. In contrast to most existing statistics, hapFLK accounts for the hierarchical structure of the sampled populations. Using computer simulations, we show that each of these two features—the use of haplotype information and of the hierarchical structure of populations—significantly improves the detection power of selected loci and that combining them in the hapFLK statistic provides even greater power. We also show that hapFLK is robust with respect to bottlenecks and migration and improves over existing approaches in many situations. Finally, we apply hapFLK to a set of six sheep breeds from Northern Europe and identify seven regions under selection, which include already reported regions but also several new ones. We propose a method to help identifying the population(s) under selection in a detected region, which reveals that in many of these regions selection most likely occurred in more than one population. Furthermore, several of the detected regions correspond to incomplete sweeps, where the favorable haplotype is only at intermediate frequency in the population(s) under selection.

Translational selection shapes codon usage in the GC-rich genome of Chlamydomonas reinhardtii.

In prokaryotes, GC levels range from 25% to 75%, and T opt from ≈0 °C to >100 °C. When all species are considered together, no correlation is found between the two variables. Correlations are found, however, when Families of prokaryotes are analysed. Indeed, when Families comprising at least 10 species were studied (a set of 20 Families), positive correlations are found for 15 of them. Furthermore, a comparative analysis by independent contrasts made within the Families in order to control for phylogenetic non‐independence showed qualitatively equivalent results. We conclude that T opt is one of the factors that influences genomic GC in prokaryotes.

Extracellular vesicles shed by Trypanosoma cruzi are linked to small RNA pathways, life cycle regulation, and susceptibility to infection of mammalian cells.

In unicellular species codon usage is determined by mutational biases and natural selection. Among prokaryotes, the influence of these factors is different if the genome is skewed towards AT or GC, since in AT‐rich organisms translational selection is absent. On the other hand, in AT‐rich unicellular eukaryotes the two factors are present. In order to understand if GC‐rich genomes display a similar behavior, the case of Chlamydomonas reinhardtii was studied. Since we found that translational selection strongly influences codon usage in this species, we conclude that there is not a common pattern among unicellular organisms.

Trends in Codon and Amino Acid Usage in Thermotoga maritima

The protozoan parasite Trypanosoma cruzi has a complex life cycle characterized by intracellular and extracellular forms alternating between invertebrate and mammals. To cope with these changing environments, T. cruzi undergoes rapid changes in gene expression, which are achieved essentially at the posttranscriptional level. At present, expanding families of small RNAs are recognized as key players in novel forms of posttranscriptional gene regulation in most eukaryotes. However, T. cruzi lacks canonical small RNA pathways. In a recent work, we reported the presence of alternate small RNA pathways in T. cruzi mainly represented by a homogeneous population of tRNA-derived small RNAs (tsRNAs). In T. cruzi epimastigotes submitted to nutrient starvation, tsRNAs colocalized with an argonaute protein distinctive of trypanosomatids (TcPIWI-tryp) and were recruited to particular cytoplasmic granules. Using epifluorescence and electronic microscopy, we observed that tsRNAs and the TcPIWI-tryp protein were recruited mainly to reservosomes and other intracellular vesicles including endosome-like vesicles and vesicular structures resembling the Golgi complex. These data suggested that, in T. cruzi, tsRNA biogenesis is probably part of endocytic/exocytic routes. We also demonstrated that epimastigotes submitted to nutrient starvation shed high levels of vesicles to the extracellular medium, which carry small tRNAs and TcPIWI-tryp proteins as cargo. At least a fraction of extracellular vesicle cargo was transferred between parasites and to mammalian susceptible cells. Our data afford experimental evidence, indicating that extracellular vesicles shed by T. cruzi promote not only life cycle transition of epimastigotes to trypomastigote forms but also infection susceptibility of mammalian cells