Genomic studies of endangered species provide insights into their evolution and demographic history, reveal patterns of genomic erosion that might limit their viability, and offer tools for their effective conservation. The Iberian lynx (Lynx pardinus) is the most endangered felid and a unique example of a species on the brink of extinction. We generate the first annotated draft of the Iberian lynx genome and carry out genome-based analyses of lynx demography, evolution, and population genetics. We identify a series of severe population bottlenecks in the history of the Iberian lynx that predate its known demographic decline during the 20th century and have greatly impacted its genome evolution. We observe drastically reduced rates of weak-to-strong substitutions associated with GC-biased gene conversion and increased rates of fixation of transposable elements. We also find multiple signatures of genetic erosion in the two remnant Iberian lynx populations, including a high frequency of potentially deleterious variants and substitutions, as well as the lowest genome-wide genetic diversity reported so far in any species. The genomic features observed in the Iberian lynx genome may hamper short- and long-term viability through reduced fitness and adaptive potential. The knowledge and resources developed in this study will boost the research on felid evolution and conservation genomics and will benefit the ongoing conservation and management of this emblematic species.

De novo gene origination has been recently established as an important mechanism for the formation of new genes. In organisms with a large genome, intergenic and intronic regions provide plenty of raw material for new transcriptional events to occur, but little is know about how de novo transcripts originate in more densely-packed genomes. Here, we identify 213 de novo originated transcripts in Saccharomyces cerevisiae using deep transcriptomics and genomic synteny information from multiple yeast species grown in two different conditions. We find that about half of the de novo transcripts are expressed from regions which already harbor other genes in the opposite orientation; these transcripts show similar expression changes in response to stress as their overlapping counterparts, and some appear to translate small proteins. Thus, a large fraction of de novo genes in yeast are likely to co-evolve with already existing genes.

Most of the current knowledge on the genetic basis of adaptive evolution is based on the analysis of single nucleotide polymorphisms (SNPs). Despite increasing evidence for their causal role, the contribution of structural variants to adaptive evolution remains largely unexplored. In this work, we analyzed the population frequencies of 1,615 Transposable Element (TE) insertions annotated in the reference genome of Drosophila melanogaster, in 91 samples from 60 worldwide natural populations. We identified a set of 300 polymorphic TEs that are present at high population frequencies, and located in genomic regions with high recombination rate, where the efficiency of natural selection is high. The age and the length of these 300 TEs are consistent with relatively young and long insertions reaching high frequencies due to the action of positive selection. Besides, we identified a set of 21 fixed TEs also likely to be adaptive. Indeed, we, and others, found evidence of selection for 84 of these reference TE insertions. The analysis of the genes located nearby these 84 candidate adaptive insertions suggested that the functional response to selection is related with the GO categories of response to stimulus, behavior, and development. We further showed that a subset of the candidate adaptive TEs affects expression of nearby genes, and five of them have already been linked to an ecologically relevant phenotypic effect. Our results provide a more complete understanding of the genetic variation and the fitness-related traits relevant for adaptive evolution. Similar studies should help uncover the importance of TE-induced adaptive mutations in other species as well. Transposable elements are fragments of genomic DNA that have the ability to move around the genome by creating new copies of themselves. Although there is evidence suggesting that transposable elements play important roles in genome function and genome evolution, our current understanding is based on the analysis of a subset of all transposable element insertions present in the genome, in only a few natural populations. Advances in genome sequencing and bioinformatics tools allow us now to investigate all transposable element insertions in genomes across continents. In this work, we analyzed the age, size, and frequency of 1,615 transposable elements in 91 samples from 60 worldwide natural populations of the model species Drosophila melanogaster. The genomic regions surrounding 84 transposable elements indicate that they could have an adaptive effect for the flies that carry them. These insertions are located nearby genes involved in stress response, behavior and development suggesting that these biological processes are affected by transposable element insertions.

This study examines the potential of next-generation sequencing based ‘genotyping-by-sequencing’ (GBS) of microsatellite loci for rapid and cost-effective genotyping in large-scale population genetic studies. The recovery of individual genotypes from large sequence pools was achieved by PCR-incorporated combinatorial barcoding using universal primers. Three experimental conditions were employed to explore the possibility of using this approach with existing and novel multiplex marker panels and weighted amplicon mixture. The GBS approach was validated against microsatellite data generated by capillary electrophoresis. GBS allows access to the underlying nucleotide sequences that can reveal homoplasy, even in large datasets and facilitates cross laboratory transfer. GBS of microsatellites, using individual combinatorial barcoding, is potentially faster and cheaper than current microsatellite approaches and offers better and more data.

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.