Biology subjects

Lopez de Heredia, U.

Publications and source records attributed to Lopez de Heredia, U..

5 recordsLinked to original sources

bioRxiv2024

SIMHYB 2: a software tool to explore and illustrate evolutionary forces in Population Genetics teaching and research. Application to Conservation Genetics

Practical approaches have become a standard in many scientific disciplines, including population genetics. By analyzing properly selected datasets, the students can calculate parameters and draw conclusions about genetic diversity, differentiation and evolution of populations with higher efficiency than if based exclusively on theoretical lessons. However, preparing the appropriate datasets is a hard task and a wrong selection can spoil a well-aimed practice. Here we present SO_SCPLOWIMC_SCPLOWHO_SCPLOWYBC_SCPLOW 2, a software tool specifically intended to ease the full understanding of evolutionary forces by the students and to help the teacher to prepare adequate datasets and examples for the practices. It simulates the course of a mixed population under user-defined reproductive and evolutionary conditions. Outputs can be easily adapted for downstream analysis with other popular tools as GO_SCPLOWENC_SCPLOWAO_SCPLOWLC_SCPLOWEO_SCPLOWXC_SCPLOW or SO_SCPLOWTRUCTUREC_SCPLOW. Thus, SO_SCPLOWIMC_SCPLOWHO_SCPLOWYBC_SCPLOW 2 is very suitable for project-based-learning approaches: students can produce their own datasets in different scenarios of genetic drift, migration, selective advantage, reproductive success... Additionally, SO_SCPLOWIMC_SCPLOWHO_SCPLOWYBC_SCPLOW 2 is the only simulation software available to date providing traceable pedigrees of individuals, being therefore very convenient for preparing datasets for parentage analysis, spatial genetic structure or conservation genetics study cases. Satisfactory results from its ongoing utilization in higher education and research are reported.

scientific communication and education↗

bioRxiv2023

Rhytidome- and cork-type barks of holm oak, cork oak and their hybrids highlight processes leading to cork formation

The periderm is basic for land plants due to its protective role during radial growth, which is achieved by the polymers deposited in the cell walls. In most trees, like holm oak, the periderm is frequently replaced by subsequent internal periderms yielding a heterogeneous outer bark made of a mixture of periderms and phloem tissues, known as rhytidome. Exceptionally, cork oak forms a persistent or long-lived periderm which results in a homogeneous outer bark of thick phellem cell layers known as cork. Here we use the outer bark of cork oak, holm oak, and their natural hybrids to analyse the chemical composition, the anatomy and the transcriptome, and further understand the mechanisms underlying periderm development. The inclusion of hybrid samples showing rhytidome-type and cork-type barks is valuable to approach to cork and rhytidome development, allowing an accurate identification of candidate genes and processes. The present study underscores that biotic stress and cell death signalling are enhanced in rhytidome-type barks whereas lipid metabolism and cell cycle are enriched in cork-type barks. Development-related DEGs, showing the highest expression, highlight cell division, cell expansion, and cell differentiation as key processes leading to cork or rhytidome-type barks.

cell biology↗

bioRxiv2022

DEGoldS: a workflow to assess the accuracy of differential expression analysis pipelines through gold-standard construction

RNA sequencing (RNA-seq) is a high throughput sequencing method that has become one the most employed tools in transcriptomics. The implementation of optimal bioinformatic analyses required in RNA-seq experiments may be complicated due to the large amounts of data generated by the sequencing platforms, along with the intrinsic nature of these data types. In the last years many programs and pipelines have been developed for differential expression (DE) analyses, but their effectiveness can be reduced when working with non-model species lacking public genomic resources. Moreover, there is not a universal recipe for all the experiments and datasets and the modification of standard RNA-seq bioinformatic pipelines through parameter tuning and the use of alternative software may have a strong impact in the outcome of DE analysis. Therefore, although the selection of the most accurate DE pipeline configuration and the evaluation of how these changes could affect the final DE results in RNA-seq experiments is mandatory to reduce bias, the lack of gold-standard datasets with known expression patterns hampers its implementation. In the present manuscript we present DEGoldS, a workflow consisting on sequential Bash and R scripts to construct gold-standards for simulation-based benchmarking of user selected pipelines for DE analysis and the computation of the accuracy of the pipelines. We validated the workflow with a case study consisting on real RNA-seq libraries of radiata pine, an important forest tree species with no publicly available reference genome. The results showed that slight pipeline modifications produced remarkable differences in the outcome of DE analysis.

bioinformatics↗

bioRxiv2022

Qualitative and quantitative analysis of the constitutive bark of Q. ilex x Q. suber hybrids

Hybridization and introgression between cork oak (Quercus suber) and holm oak (Q. ilex) have traditionally been reckoned as undesirable processes, since hybrid individuals lack the profitable bark characteristics of cork oak. Nevertheless, a systematic and quantitative description of the bark of these hybrids at the microscopic level based on a significant number of individuals was not available to date. In this work we provide such a qualitative and quantitative description, identifying the most relevant variables for their classification. Hybrids show certain features intermediate between those of the parent species, as well as other unique features, as the general suberization of inactive phloem, reported here for the first time. These results suggest a relevant hybridization-induced modification of the genetic expression patterns. Therefore, hybrid individuals provide a valuable material to disentangle the molecular mechanisms underpinning bark development in angiosperms.

plant biology↗

bioRxiv2020

NGScloud2: optimized bioinformatic analysis using Amazon Web Services

NGScloud was a bioinformatic system developed to perform de novo RNAseq analysis of non-model species by exploiting the cloud computing capabilities of Amazon Web Services. The rapid changes undergone in the way this cloud computing service operates, along with the continuous release of novel bioinformatic applications to analyze next generation sequencing data, have made the software obsolete. NGScloud2 is an enhanced and expanded version of NGScloud that permits the access to ad hoc cloud computing infrastructure, scaled according to the complexity of each experiment. NGScloud2 presents major technical improvements, such as the possibility of running spot instances and the most updated AWS instances types, that can lead to significant cost savings. As compared to its initial implementation, this improved version updates and includes common applications for de novo RNAseq analysis, and incorporates tools to operate workflows of bioinformatic analysis of reference-based RNAseq, RADseq and functional annotation. NGScloud2 optimizes the access to Amazons large computing infrastructures to easily run popular bioinformatic software applications, otherwise inaccessible to non-specialized users lacking suitable hardware infrastructures. The correct performance of the pipelines for de novo RNAseq, reference-based RNAseq, RADseq and functional annotation was tested with real experimental data. NGScloud2 code, instructions for software installation and use are available at https://github.com/GGFHF/NGScloud2. NGScloud2 includes a companion package, NGShelper that contains python utilities to post-process the output of the pipelines for downstream analysis at https://github.com/GGFHF/NGShelper.

bioinformatics↗