Gene duplication is widely regarded as a major mechanism modeling genome evolution and function. However, the mechanisms that drive the evolution of the two, initially redundant, gene copies are still ill defined. Many gene duplicates experience evolutionary rate acceleration, but the relative contribution of positive selection and random drift to the retention and subsequent evolution of gene duplicates, and for how long the molecular clock may be distorted by these processes, remains unclear. Focusing on rodent genes that duplicated before and after the mouse and rat split, we find significantly increased sequence divergence after duplication in only one of the copies, which in nearly all cases corresponds to the novel daughter copy, independent of the mechanism of duplication. We observe that the evolutionary rate of the accelerated copy, measured as the ratio of nonsynonymous to synonymous substitutions, is on average 5-fold higher in the period spanning 4-12 My after the duplication than it was before the duplication. This increase can be explained, at least in part, by the action of positive selection according to the results of the maximum likelihood-based branch-site test. Subsequently, the rate decelerates until purifying selection completely returns to preduplication levels. Reversion to the original rates has already been accomplished 40.5 My after the duplication event, corresponding to a genetic distance of about 0.28 synonymous substitutions per site. Differences in tissue gene expression patterns parallel those of substitution rates, reinforcing the role of neofunctionalization in explaining the evolution of young gene duplicates.
Large-scale evolutionary studies often require the automated construction of alignments of a large number of homologous gene families. The majority of eukaryotic genes can produce different transcripts due to alternative splicing or transcription initiation, and many such transcripts encode different protein isoforms. As analyses tend to be gene centered, one single-protein isoform per gene is selected for the alignment, with the de facto approach being to use the longest protein isoform per gene (Longest), presumably to avoid including partial sequences and to maximize sequence information. Here, we show that this approach is problematic because it increases the number of indels in the alignments due to the inclusion of nonhomologous regions, such as those derived from species-specific exons, increasing the number of misaligned positions. With the aim of ameliorating this problem, we have developed a novel heuristic, Protein ALignment Optimizer (PALO), which, for each gene family, selects the combination of protein isoforms that are most similar in length. We examine several evolutionary parameters inferred from alignments in which the only difference is the method used to select the protein isoform combination: Longest, PALO, the combination that results in the highest sequence conservation, and a randomly selected combination. We observe that Longest tends to overestimate both nonsynonymous and synonymous substitution rates when compared with PALO, which is most likely due to an excess of misaligned positions. The estimation of the fraction of genes that have experienced positive selection by maximum likelihood is very sensitive to the method of isoform selection employed, both when alignments are constructed with MAFFT and with Prank+F. Longest performs better than a random combination but still estimates up to 3 times more positively selected genes than the combination showing the highest conservation, indicating the presence of many false positives. We show that PALO can eliminate the majority of such false positives and thus that it is a more appropriate approach for large-scale analyses than Longest. A web server has been set up to facilitate the use of PALO given a user-defined set of gene families; it is available at http://evolutionarygenomics.imim.es/palo.
The molecular clock hypothesis states that protein-coding genes evolve at an approximately constant rate. However, this is only expected to be true as long as the function and the tertiary structure of the molecule remain unaltered. An important implication of this statement is that significant deviations in the rate of evolution of a gene with respect to the species clock are likely to reflect functional and/or structural alterations. Here, we present a method to identify such deviations and apply it to a data set of 2,929 high-quality coding sequence alignments corresponding to one-to-one orthologous genes from six mammalian species--human, macaque, mouse, rat, cow, and dog. Deviated branches are defined as those that present significant alterations in both the rate of nonsynonymous substitutions (dN) and the selective pressure (dN/dS). Strikingly, we find that as many as 24.5% of the genes show branch-specific deviations in dN and dN/dS, though this is a relatively well-conserved set of genes. Around half of these genes show branch-specific acceleration of evolutionary rates. Positive selection (PS) tests based on divergence data only identify 17.7% of the accelerated branches. Failure to identify PS in accelerated branches with an excess of radical amino acid replacements suggests that these tests are conservative. Interestingly, genes with accelerated branches are significantly enriched in neural proteins, indicating that this type of protein might play a more important role than previously thought in species diversification, although they are generally not detected by PS tests. We discuss in detail several examples of genes that show lineage-specific evolutionary rate acceleration and are involved in synaptic transmission, chemosensory perception, and ubiquitination.
Congenital myasthenic syndrome (CMS) is a heterogeneous disorder that causes fatigable muscle weakness. CMS has been associated with variants in the MuSK gene and, to date, 16 patients have been reported. MuSK-CMS patients present a different phenotypic pattern of limb girdle weakness. Here, we describe four additional patients and discuss the phenotypic and clinical relationship with those previously reported. Two novel damaging missense variants are described: c.1742T > A; p.I581N found in homozygosis, and c.1634T > C; p.L545P found in compound heterozygosis with p.R166*. The reported patients had predominant limb girdle weakness with symptom onset at 12, 17, 18, and 30 years of age, and the majority exhibited a good clinical response to Salbutamol therapy, but not to esterase inhibitors. Meta-analysis including previously reported variants revealed an increased likelihood of a severe, respiratory phenotype with null alleles. Missense variants exclusively affecting the kinase domain, but not the catalytic site, are associated with late onset. These data refine the phenotype associated with MuSK-related CMS.
For the first time in Europe hundreds of rare disease (RD) experts team up to actively share and jointly analyse existing patient’s data. Solve-RD is a Horizon 2020-supported EU flagship project bringing together >300 clinicians, scientists, and patient representatives of 51 sites from 15 countries. Solve-RD is built upon a core group of four European Reference Networks (ERNs; ERN-ITHACA, ERN-RND, ERN-Euro NMD, ERN-GENTURIS) which annually see more than 270,000 RD patients with respective pathologies. The main ambition is to solve unsolved rare diseases for which a molecular cause is not yet known. This is achieved through an innovative clinical research environment that introduces novel ways to organise expertise and data. Two major approaches are being pursued (i) massive data re-analysis of >19,000 unsolved rare disease patients and (ii) novel combined -omics approaches. The minimum requirement to be eligible for the analysis activities is an inconclusive exome that can be shared with controlled access. The first preliminary data re-analysis has already diagnosed 255 cases form 8393 exomes/genome datasets. This unprecedented degree of collaboration focused on sharing of data and expertise shall identify many new disease genes and enable diagnosis of many so far undiagnosed patients from all over Europe.
As whole genome sequencing becomes cheaper and faster, it will progressively substitute targeted next‐generation sequencing as standard practice in research and diagnostics. However, computing cost–performance ratio is not advancing at an equivalent rate. Therefore, it is essential to evaluate the robustness of the variant detection process taking into account the computing resources required. We have benchmarked six combinations of state‐of‐the‐art read aligners (BWA‐MEM and GEM3) and variant callers (FreeBayes, GATK HaplotypeCaller, SAMtools) on whole genome and whole exome sequencing data from the NA12878 human sample. Results have been compared between them and against the NIST Genome in a Bottle (GIAB) variants reference dataset. We report differences in speed of up to 20 times in some steps of the process and have observed that SNV, and to a lesser extent InDel, detection is highly consistent in 70% of the genome. SNV, and especially InDel, detection is less reliable in 20% of the genome, and almost unfeasible in the remaining 10%. These findings will aid in choosing the appropriate tools bearing in mind objectives, workload, and computing infrastructure available.
Insertions and deletions (indels), together with nucleotide substitutions, are major drivers of sequence evolution. An excess of deletions over insertions in genomic sequences-the so-called deletional bias-has been reported in a wide range of species, including mammals. However, this bias has not been found in the coding sequences of some mammalian species, such as human and mouse. To determine the strength of the deletional bias in mammals, and the influence of mutation and selection, we have quantified indels in both neutrally evolving noncoding sequences and protein-coding sequences, in six mammalian branches: human, macaque, ancestral primate, mouse, rat, and ancestral rodent. The results obtained with an improved algorithm for the placement of insertions in multiple alignments, Prank +F , indicate that contrary to previous results, the only mammalian branch with a strong deletional bias is the rodent ancestral branch. We estimate that such a bias has resulted in an~2.5% sequence loss of mammalian syntenic region in the ancestor of the mouse and rat. Further, a comparison of coding and noncoding sequences shows that negative selection is acting more strongly against mutations generating amino acid insertions than against mutations resulting in amino acid deletions. The strength of selection against indels is found to be higher in the rodent branches than in the primate branches, consistent with the larger effective population sizes of the rodents.
Colorectal cancer (CRC) shows aggregation in some families but no alterations in the known hereditary CRC genes. We aimed to identify new candidate genes which are potentially involved in germline predisposition to familial CRC. An integrated analysis of germline and tumor whole-exome sequencing data was performed in 18 unrelated CRC families. Deleterious single nucleotide variants (SNV), short insertions and deletions (indels), copy number variants (CNVs) and loss of heterozygosity (LOH) were assessed as candidates for first germline or second somatic hits. Candidate tumor suppressor genes were selected when alterations were detected in both germline and somatic DNA, fulfilling Knudson’s two-hit hypothesis. Somatic mutational profiling and signature analysis were also performed. A series of germline-somatic variant pairs were detected. In all cases, the first hit was presented as a rare SNV/indel, whereas the second hit was either a different SNV (3 genes) or LOH affecting the same gene (141 genes). BRCA2, BLM, ERCC2, RECQL, REV3L and RIF1 were among the most promising candidate genes for germline CRC predisposition. The identification of new candidate genes involved in familial CRC could be achieved by our integrated analysis. Further functional studies and replication in additional cohorts are required to confirm the selected candidates.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.