The U5 RNA of trypanosomes deviates from the canonical U5 RNA: The Leptomonas collosoma U5 RNA and its coding gene

Fractionation of the abundant small ribonucleoproteins (RNPs) of the trypanosomatid Leptomonas collosoma revealed the existence of a group of unidentified small RNPs that were shown to fractionate differently than the well-characterized trans-spliceosomal RNPs. One of these RNAs, an 80-nt RNA, did not possess a trimethylguanosine (TMG) cap structure but did possess a 5′ phosphate terminus and an invariant consensus U5 snRNA loop 1. The gene coding for the RNA was cloned, and the coding region showed 55% sequence identity to the recently described U5 homologue of Trypanosoma brucei [Dungan, J. D., Watkins, K. P. & Agabian, N. (1996) EMBO J. 15, 4016–4029]. The L. collosoma U5 homologue exists in multiple forms of RNP complexes, a 10S monoparticle, and two subgroups of 18S particles that either contain or lack the U4 and U6 small nuclear RNAs, suggesting the existence of a U4/U6⋅U5 tri-small nuclear RNP complex. In contrast to T. brucei U5 RNA (62 nt), the L. collosoma homologue is longer (80 nt) and possesses a second stem–loop. Like the trypanosome U3, U6, and 7SL RNA genes, a tRNA gene coding for tRNACys was found 98 nt upstream to the U5 gene. A potential for base pair interaction between U5 and SL RNA in the 5′ splice site region (positions −1 and +1) and downstream from it is proposed. The presence of a U5-like RNA in trypanosomes suggests that the most essential small nuclear RNPs are ubiquitous for both cis- and trans-splicing, yet even among the trypanosomatids the U5 RNA is highly divergent.

SpliceDB: database of canonical and non-canonical mammalian splice sites

A database (SpliceDB) of known mammalian splice site sequences has been developed. We extracted 43 337 splice pairs from mammalian divisions of the gene-centered Infogene database, including sites from incomplete or alternatively spliced genes. Known EST sequences supported 22 815 of them. After discarding sequences with putative errors and ambiguous location of splice junctions the verified dataset includes 22 489 entries. Of these, 98.71% contain canonical GT–AG junctions (22 199 entries) and 0.56% have non-canonical GC–AG splice site pairs. The remainder (0.73%) occurs in a lot of small groups (with a maximum size of 0.05%). We especially studied non-canonical splice sites, which comprise 3.73% of GenBank annotated splice pairs. EST alignments allowed us to verify only the exonic part of splice sites. To check the conservative dinucleotides we compared sequences of human non-canonical splice sites with sequences from the high throughput genome sequencing project (HTG). Out of 171 human non-canonical and EST-supported splice pairs, 156 (91.23%) had a clear match in the human HTG. They can be classified after sequence analysis as: 79 GC–AG pairs (of which one was an error that corrected to GC–AG), 61 errors corrected to GT–AG canonical pairs, six AT–AC pairs (of which two were errors corrected to AT–AC), one case was produced from a non-existent intron, seven cases were found in HTG that were deposited to GenBank and finally there were only two other cases left of supported non-canonical splice pairs. The information about verified splice site sequences for canonical and non-canonical sites is presented in SpliceDB with the supporting evidence. We also built weight matrices for the major splice groups, which can be incorporated into gene prediction programs. SpliceDB is available at the computational genomic Web server of the Sanger Centre: http://genomic.sanger.ac.uk/spldb/SpliceDB.html and at http://www.softberry.com/spldb/SpliceDB.html.

The asymptotic distribution of canonical correlations and vectors in higher-order cointegrated models

The study of the large-sample distribution of the canonical correlations and variates in cointegrated models is extended from the first-order autoregression model to autoregression of any (finite) order. The cointegrated process considered here is nonstationary in some dimensions and stationary in some other directions, but the first difference (the “error-correction form”) is stationary. The asymptotic distribution of the canonical correlations between the first differences and the predictor variables as well as the corresponding canonical variables is obtained under the assumption that the process is Gaussian. The method of analysis is similar to that used for the first-order process.