Biology subjects

Laayouni, H.

Publications and source records attributed to Laayouni, H..

6 recordsLinked to original sources

bioRxiv2025

A phylogenetic protein-coding genome-phenome map of complex traits across 224 primate species.

Complex traits arise from networks of coding and regulatory loci, making it difficult to resolve their genetic basis. Macroevolutionary studies leverage tens of millions of years of divergence across species to uncover fixed genomic changes invisible to within-species approaches, such as GWAS, offering a complementary framework for generating hypotheses in biomedical research. Here, we present the first phylogenetic protein-coding primate-wide genome-phenome map (P3GMap), spanning 200 curated traits across 224 primate species, which we release through the Primate Genome-Phenome Archive (PGA, https://pgarchive.github.io). Using two complementary approaches, convergent amino acid substitutions and relative evolutionary rates, we linked protein-coding variation to complex phenotypes and identified thousands of candidate gene-trait associations, including lineage-specific signals related to diet, immunity, and lifespan. One sentence summaryCross-species genome-phenome mapping in primates reveals thousands of protein-coding variants linked to the evolution of complex traits.

evolutionary biology↗

bioRxiv2021

Chromosome X-wide analysis of positive selection in human populations: from common and private signals to selection impact on inactivated genes and enhancers-like signatures

The ability of detecting adaptive (positive) selection in the genome has opened the possibility of understanding the genetic bases of population-specific adaptations genome-wide. Here we present the analysis of recent selective sweeps specifically in the X chromosome in different human populations from the third phase of the 1000 Genomes Project using three different haplotype-based statistics. We describe numerous instances of genes under recent positive selection that fit the regimes of hard and soft sweeps, showing a higher amount of detectable sweeps in sub-Saharan Africans than in non-Africans (Europe and East Asia). A global enrichment is seen in neural-related processes while numerous genes related to fertility appear among the top candidates, reflecting the importance of reproduction in human evolution. Commonalities with previously reported genes under positive selection are found, while particularly strong new signals are reported in specific populations or shared across different continental groups. We report an enrichment of signals in genes that escape X chromosome inactivation, which may contribute to the differentiation between sexes. We also provide evidence of a widespread presence of soft-sweep-like signatures across the chromosome and a global enrichment of highly scoring regions that overlap potential regulatory elements. Among these, enhancers-like signatures seem to present putative signals of positive selection that might be in concordance with selection in their target genes. Also, particularly strong signals appear in regulatory regions that show differential activities, which might point to population-specific regulatory adaptations.

evolutionary biology↗

bioRxiv2021

Signatures of genetic variation in human microRNAs point to processes of positive selection related to population-specific disease risks

The occurrence of natural variation in human microRNAs has been the focus of numerous studies during the last twenty years. Most of them have been dedicated to study the role of specific mutations in diseases, like cancer, while a minor fraction seek to analyse the diversity profiles of microRNAs in the genomes of human populations. In the present study we analyse the latest human microRNA annotations in the light of the most updated catalog of genetic variation provided by the 1000 Genomes Project. We show by means of the in silico analysis of noncoding variation of microRNAs that the level of evolutionary constraint of these sequences is governed by the interplay of different factors, like their evolutionary age or the genomic location where they emerged. The role of mutations in the shaping of microRNA-driven regulatory interactions is emphasized with the acknowledgement that, while the whole microRNA sequence is highly conserved, the seed region shows a pattern of higher genetic diversity that appears to be caused by the dramatic frequency shifts of a fraction of human microRNAs. We highlight the participation of these microRNAs in population-specific processes by identifying that not only the seed, but also the loop, are particularly differentiated regions among human populations. The quantitative computational comparison of signatures of population differentiation showed that candidate microRNAs with the largest differences are enriched in variants implicated in gene expression levels (eQTLs), selective sweeps and pathological processes. We explore the implication of these evolutionary-driven microRNAs and their SNPs in human diseases, such as different types of cancer, and discuss their role in population-specific disease risk.

evolutionary biology↗

bioRxiv2020

Intronic enhancers regulate the expression of genes involved in tissue-specific functions and homeostasis

Tissue function and homeostasis reflect the gene expression signature by which the combination of ubiquitous and tissue-specific genes contribute to the tissue maintenance and stimuli-responsive function. Enhancers are central to control this tissue-specific gene expression pattern. Here, we explore the correlation between the genomic location of enhancers and their role in tissue-specific gene expression. We found that enhancers showing tissue-specific activity are highly enriched in intronic regions and regulate the expression of genes involved in tissue-specific functions, while housekeeping genes are more often controlled by intergenic enhancers. Notably, an intergenic-to-intronic active enhancers continuum is observed in the transition from developmental to adult stages: the most differentiated tissues present higher rates of intronic enhancers, while the lowest rates are observed in embryonic stem cells. Altogether, our results suggest that the genomic location of active enhancers is key for the tissue-specific control of gene expression.

genomics↗

bioRxiv2018

Fast and accurate large multiple sequence alignments using root-to-leave regressive computation

Inferences derived from large multiple alignments of biological sequences are critical to many areas of biology, including evolution, genomics, biochemistry, and structural biology. However, the complexity of the alignment problem imposes the use of approximate solutions. The most common is the progressive algorithm, which starts by aligning the most similar sequences, incorporating the remaining ones following the order imposed by a guide-tree. We developed and validated on protein sequences a regressive algorithm that works the other way around, aligning first the most dissimilar sequences. Our algorithm produces more accurate alignments than non-regressive methods, especially on datasets larger than 10,000 sequences. By design, it can run any existing alignment method in linear time thus allowing the scale-up required for extremely large genomic analyses.\n\nOne Sentence SummaryInitiating alignments with the most dissimilar sequences allows slow and accurate methods to be used on large datasets

bioinformatics↗

bioRxiv2018

Influence of pathway topology and functional class on the molecular evolution of human metabolic genes

Metabolic networks comprise thousands of enzymatic reactions functioning in a controlled manner and have been shaped by natural selection. Thanks to the genome data, the footprints of adaptive (positive) selection are detectable, and the strength of purifying selection can be measured. This has made possible to know where, in the metabolic network, adaptive selection has acted and where purifying selection is more or less strong and efficient. We have carried out a comprehensive molecular evolutionary study of all the genes involved in the human metabolism. We investigated the type and strength of the selective pressures that acted on the enzyme-coding genes belonging to metabolic pathways during the divergence of primates and rodents. Then, we related those selective pressures to the functional and topological characteristics of the pathways. We have used DNA sequences of all enzymes (956) of the metabolic pathways comprised in the HumanCyc database, using genome data for humans and five other mammalian species.\n\nWe have found that the evolution of metabolic genes is primarily constrained by the layer of the metabolism in which the genes participate: while genes encoding enzymes of the inner core of metabolism are much conserved, those encoding enzymes participating in the outer layer, mediating the interaction with the environment, are evolutionarily less constrained and more plastic, having experienced faster functional evolution. Genes that have been targeted by adaptive selection are endowed by higher out-degree centralities than non-adaptive genes, while genes with high in-degree centralities are under stronger purifying selection. When the position along the pathway is considered, a funnel-like distribution of the strength of the purifying selection is found. Genes at bottom positions are highly preserved by purifying selection, whereas genes at top positions, catalyzing the first steps, are open to evolutionary changes.\n\nThese results show how functional and topological characteristics of metabolic pathways contribute to shape the patterns of evolutionary pressures driven by natural selection and how pathway network structure matters in the evolutionary process that shapes the evolution of the system.

systems biology↗