Juan I. Montoya‐Burgos

Transcriptome analysis has important applications in many biological fields. However, assembling a transcriptome without a known reference remains a challenging task requiring algorithmic improvements. We present two methods for substantially improving transcriptome de novo assembly. The first method relies on the observation that the use of a single k-mer length by current de novo assemblers is suboptimal to assemble transcriptomes where the sequence coverage of transcripts is highly heterogeneous. We present the Multiple-k method in which various k-mer lengths are used for de novo transcriptome assembly. We demonstrate its good performance by assembling de novo a published next-generation transcriptome sequence data set of Aedes aegypti, using the existing genome to check the accuracy of our method. The second method relies on the use of a reference proteome to improve the de novo assembly. We developed the Scaffolding using Translation Mapping (STM) method that uses mapping against the closest available reference proteome for scaffolding contigs that map onto the same protein. In a controlled experiment using simulated data, we show that the STM method considerably improves the assembly, with few errors. We applied these two methods to assemble the transcriptome of the non-model catfish Loricaria gr. cataphracta. Using the Multiple-k and STM methods, the assembly increases in contiguity and in gene identification, showing that our methods clearly improve quality and can be widely used. The new methods were used to assemble successfully the transcripts of the core set of genes regulating tooth development in vertebrates, while classic de novo assembly failed.

Tropical South America possesses the largest ichthyofauna of any continental region. To test whether palaeohydrological changes may have been the causes of such diversification, the 'hydrogeological' hypothesis, the phylogenetic relationships of 51 representatives of the catfish genus Hypostomus (Siluriformes: Loricariidae) were inferred using mitochondrial D-loop haplotype sequences. Specimens were collected in all main tropical South American rivers systems east to the Andes. The major interrelationships found with the D-loop data were confirmed with a subset of 21 species using complete internal transcribed spacer (ITS) region sequences. The phylogenetic analysis indicate that the genus Hypostomus can be divided into four monophyletic clades. The historical biogeographical analysis of each of these clades allows the identification of seven major cladogenetic events. Using calibrated D-loop and ITS molecular clocks, date estimations were attributed to each of these cladogenetic events allowing a linkage between four of them with documented hydrogeological changes. Comparisons with published distribution patterns of unrelated fish groups indicate that several of the reconstructed and dated hydrogeological-cladogenetic events may have acted at a large scale on the diversification of Neotropical freshwater fish fauna during late Tertiary.

A key component of the ongoing ENCODE project involves rigorous comparative sequence analyses for the initially targeted 1% of the human genome. Here, we present orthologous sequence generation, alignment, and evolutionary constraint analyses of 23 mammalian species for all ENCODE targets. Alignments were generated using four different methods; comparisons of these methods reveal large-scale consistency but substantial differences in terms of small genomic rearrangements, sensitivity (sequence coverage), and specificity (alignment accuracy). We describe the quantitative and qualitative trade-offs concomitant with alignment method choice and the levels of technical error that need to be accounted for in applications that require multisequence alignments. Using the generated alignments, we identified constrained regions using three different methods. While the different constraint-detecting methods are in general agreement, there are important discrepancies relating to both the underlying alignments and the specific algorithms. However, by integrating the results across the alignments and constraint-detecting methods, we produced constraint annotations that were found to be robust based on multiple independent measures. Analyses of these annotations illustrate that most classes of experimentally annotated functional elements are enriched for constrained sequences; however, large portions of each class (with the exception of protein-coding sequences) do not overlap constrained regions. The latter elements might not be under primary sequence constraint, might not be constrained across all mammals, or might have expendable molecular functions. Conversely, 40% of the constrained sequences do not overlap any of the functional elements that have been experimentally identified. Together, these findings demonstrate and quantify how many genomic functional elements await basic molecular characterization.