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The structure of eukaryotic genes is generally a combination of exons interrupted by intragenic non-coding DNA regions (introns) removed by RNA splicing to generate the mature mRNA. A fraction of genes, however, comprise a single coding exon with introns in their untranslated regions or are intronless genes (IGs), lacking introns entirely. The latter code for essential proteins involved in development, growth, and cell proliferation and their expression has been proposed to be highly specialized for neuro-specific functions and linked to cancer, neuropathies, and developmental disorders. The abundant presence of introns in eukaryotic genomes is pivotal for the precise control of gene expression. Notwithstanding, IGs exempting splicing events entail a higher transcriptional fidelity, making them even more valuable for regulatory roles. This work aimed to infer the functional role and evolutionary history of IGs centered on the mouse genome. IGs consist of a subgroup of genes with one exon including coding genes, non-coding genes, and pseudogenes, which conform approximately 6% of a total of 21,527 genes. To understand their prevalence, biological relevance, and evolution, we identified and studied 1,116 IG functional proteins validating their differential expression in transcriptomic data of embryonic mouse telencephalon. Our results showed that overall expression levels of IGs are lower than those of MEGs. However, strongly up-regulated IGs include transcription factors (TFs) such as the class 3 of POU (HMG Box), Neurog1, Olig1, and BHLHe22, BHLHe23, among other essential genes including the ß-cluster of protocadherins. Most striking was the finding that IG-encoded BHLH TFs fit the criteria to be classified as microproteins. Finally, predicted protein orthologs in other six genomes confirmed high conservation of IGs associated with regulating neural processes and with chromatin organization and epigenetic regulation in Vertebrata. Moreover, this study highlights that IGs are essential modulators of regulatory processes, such as the Wnt signaling pathway and biological processes as pivotal as sensory organ developing at a transcriptional and post-translational level. Overall, our results suggest that IG proteins have specialized, prevalent, and unique biological roles and that functional divergence between IGs and MEGs is likely to be the result of specific evolutionary constraints.
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A detailed knowledge of gene function in the monarch butterfly is still lacking. Here we generate a genome assembly from a Mexican nonmigratory population and used RNA-seq data from 14 biological samples for gene annotation and to construct an atlas portraying the breadth of gene expression during most of the monarch life cycle. Two thirds of the genes show expression changes, with long noncoding RNAs being particularly finely regulated during adulthood, and male-biased expression being four times more common than female-biased. The two portions of the monarch heterochromosome Z, one ancestral to the Lepidoptera and the other resulting from a chromosomal fusion, display distinct association with sex-biased expression, reflecting sample-dependent incompleteness or absence of dosage compensation in the ancestral but not the novel portion of the Z. This study presents extended genomic and transcriptomic resources that will facilitate a better understanding of the monarch's adaptation to a changing environment.
Asunto(s)
Mariposas Diurnas/genética , Compensación de Dosificación (Genética) , Transcriptoma , Animales , Femenino , Genoma , Masculino , ARN Largo no Codificante/fisiologíaRESUMEN
Gene regulatory factors (GRFs), such as transcription factors, co-factors and histone-modifying enzymes, play many important roles in modifying gene expression in biological processes. They have also been proposed to underlie speciation and adaptation. To investigate potential contributions of GRFs to primate evolution, we analyzed GRF genes in 27 publicly available primate genomes. Genes coding for zinc finger (ZNF) proteins, especially ZNFs with a Krüppel-associated box (KRAB) domain were the most abundant TFs in all genomes. Gene numbers per TF family differed between all species. To detect signs of positive selection in GRF genes we investigated more than 3,000 human GRFs with their more than 70,000 orthologs in 26 non-human primates. We implemented two independent tests for positive selection, the branch-site-model of the PAML suite and aBSREL of the HyPhy suite, focusing on the human and great ape branch. Our workflow included rigorous procedures to reduce the number of false positives: excluding distantly similar orthologs, manual corrections of alignments, and considering only genes and sites detected by both tests for positive selection. Furthermore, we verified the candidate sites for selection by investigating their variation within human and non-human great ape population data. In order to approximately assign a date to positively selected sites in the human lineage, we analyzed archaic human genomes. Our work revealed with high confidence five GRFs that have been positively selected on the human lineage and one GRF that has been positively selected on the great ape lineage. These GRFs are scattered on different chromosomes and have been previously linked to diverse functions. For some of them a role in speciation and/or adaptation can be proposed based on the expression pattern or association with human diseases, but it seems that they all contributed independently to human evolution. Four of the positively selected GRFs are KRAB-ZNF proteins, that induce changes in target genes co-expression and/or through arms race with transposable elements. Since each positively selected GRF contains several sites with evidence for positive selection, we suggest that these GRFs participated pleiotropically to phenotypic adaptations in humans.
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Two errors in the article Best Match Graphs (Geiß et al. in JMB 78: 2015-2057, 2019) are corrected. One concerns the tacit assumption that digraphs are sink-free, which has to be added as an additional precondition in Lemma 9, Lemma 11, Theorem 4. Correspondingly, Algorithm 2 requires that its input is sink-free. The second correction concerns an additional necessary condition in Theorem 9 required to characterize best match graphs. The amended results simplify the construction of least resolved trees for n-cBMGs, i.e., Algorithm 1. All other results remain unchanged and are correct as stated.
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BACKGROUND: Many of the commonly used methods for orthology detection start from mutually most similar pairs of genes (reciprocal best hits) as an approximation for evolutionary most closely related pairs of genes (reciprocal best matches). This approximation of best matches by best hits becomes exact for ultrametric dissimilarities, i.e., under the Molecular Clock Hypothesis. It fails, however, whenever there are large lineage specific rate variations among paralogous genes. In practice, this introduces a high level of noise into the input data for best-hit-based orthology detection methods. RESULTS: If additive distances between genes are known, then evolutionary most closely related pairs can be identified by considering certain quartets of genes provided that in each quartet the outgroup relative to the remaining three genes is known. A priori knowledge of underlying species phylogeny greatly facilitates the identification of the required outgroup. Although the workflow remains a heuristic since the correct outgroup cannot be determined reliably in all cases, simulations with lineage specific biases and rate asymmetries show that nearly perfect results can be achieved. In a realistic setting, where distances data have to be estimated from sequence data and hence are noisy, it is still possible to obtain highly accurate sets of best matches. CONCLUSION: Improvements of tree-free orthology assessment methods can be expected from a combination of the accurate inference of best matches reported here and recent mathematical advances in the understanding of (reciprocal) best match graphs and orthology relations. AVAILABILITY: Accompanying software is available at https://github.com/david-schaller/AsymmeTree.
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A wide variety of problems in computational biology, most notably the assessment of orthology, are solved with the help of reciprocal best matches. Using an evolutionary definition of best matches that captures the intuition behind the concept we clarify rigorously the relationships between reciprocal best matches, orthology, and evolutionary events under the assumption of duplication/loss scenarios. We show that the orthology graph is a subgraph of the reciprocal best match graph (RBMG). We furthermore give conditions under which an RBMG that is a cograph identifies the correct orthlogy relation. Using computer simulations we find that most false positive orthology assignments can be identified as so-called good quartets-and thus corrected-in the absence of horizontal transfer. Horizontal transfer, however, may introduce also false-negative orthology assignments.
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Evolución Molecular , Especiación Genética , Modelos Genéticos , Filogenia , Algoritmos , Biología Computacional , Gráficos por Computador , Simulación por Computador , Eliminación de Gen , Duplicación de Gen , Transferencia de Gen Horizontal , Conceptos MatemáticosRESUMEN
Best match graphs arise naturally as the first processing intermediate in algorithms for orthology detection. Let T be a phylogenetic (gene) tree T and [Formula: see text] an assignment of leaves of T to species. The best match graph [Formula: see text] is a digraph that contains an arc from x to y if the genes x and y reside in different species and y is one of possibly many (evolutionary) closest relatives of x compared to all other genes contained in the species [Formula: see text]. Here, we characterize best match graphs and show that it can be decided in cubic time and quadratic space whether [Formula: see text] derived from a tree in this manner. If the answer is affirmative, there is a unique least resolved tree that explains [Formula: see text], which can also be constructed in cubic time.