The genome of Trypanosoma brucei, the causative agent of African trypanosomiasis, was published five years ago, yet identification of all genes and their transcripts remains to be accomplished. Annotation is challenged by the organization of genes transcribed by RNA polymerase II (Pol II) into long unidirectional gene clusters with no knowledge of how transcription is initiated. Here we report a single-nucleotide resolution genomic map of the T. brucei transcriptome, adding 1,114 new transcripts, including 103 non-coding RNAs, confirming and correcting many of the annotated features and revealing an extensive heterogeneity of 5′ and 3′ ends. Some of the new transcripts encode polypeptides that are either conserved in T. cruzi and Leishmania major or were previously detected in mass spectrometry analyses. High-throughput RNA sequencing (RNA-Seq) was sensitive enough to detect transcripts at putative Pol II transcription initiation sites. Our results, as well as recent data from the literature, indicate that transcription initiation is not solely restricted to regions at the beginning of gene clusters, but may occur at internal sites. We also provide evidence that transcription at all putative initiation sites in T. brucei is bidirectional, a recently recognized fundamental property of eukaryotic promoters. Our results have implications for gene expression patterns in other important human pathogens with similar genome organization (Trypanosoma cruzi, Leishmania sp.) and revealed heterogeneity in pre-mRNA processing that could potentially contribute to the survival and success of the parasite population in the insect vector and the mammalian host.
Identifying genes essential for survival in the host is fundamental to unraveling the biology of human pathogens and understanding mechanisms of pathogenesis. The protozoan parasite Trypanosoma brucei causes devastating diseases in humans and animals in sub-Saharan Africa, and the publication in 2005 of the genome sequence provided the first glance at the coding potential of this organism. Although at present there is a catalogue of predicted protein coding genes, the challenge remains to identify all authentic genes, including their boundaries. We used next generation RNA sequencing (RNA-Seq) to map transcribed regions and RNA polymerase II transcription initiation sites on a genome-wide scale. This approach allowed us to improve and correct the current annotation, to reveal a widespread heterogeneity of RNA processing sites (trans-splicing and polyadenylation) and to estimate that most genes are expressed at levels corresponding to 1 to 10 mRNAs per cell. Our data indicate that different transcript forms representing the same gene are present stochastically within the mRNA population. This unanticipated scenario may contribute to determining gene expression landscapes to adapt to different environments in the parasite life cycle.
Citation: Kolev NG, Franklin JB, Carmi S, Shi H, Michaeli S, Tschudi C (2010) The Transcriptome of the Human Pathogen Trypanosoma brucei at Single-Nucleotide Resolution. PLoS Pathog 6(9): e1001090. https://doi.org/10.1371/journal.ppat.1001090
Editor: Stephen M. Beverley, Washington University School of Medicine, United States of America
Received: April 27, 2010; Accepted: August 6, 2010; Published: September 9, 2010
Copyright: © 2010 Kolev et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was funded in part by National Institute of Allergy and Infectious Diseases Grants AI28798 to E. Ullu and AI43594 and AI078333 to CT. SC is supported by the Adams Fellowship Program of the Israel Academy of Sciences and Humanities. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
One of the milestones towards an understanding and possible treatment of human African trypanosomiasis was the publication of the genome sequence of its causative agent, the protozoan parasite Trypanosoma brucei . The availability of the potential coding capacity provided a first opportunity to comprehensively annotate the T. brucei genome. This initial analysis of the 11 megabase-sized chromosomes predicted 9,068 protein-coding genes, including about 900 pseudogenes. As of April 2010, the catalogue of annotated protein-coding genes has increased to 10,533 (TriTrypDB) , yet a major challenge remains to identify all authentic genes, including their boundaries. Such information is central to determining the timing and regulation of gene expression in different developmental stages and the identification of functional elements.
The genomes of T. brucei and related trypanosomatids are organized into long unidirectional gene clusters that are transcribed by RNA polymerase II (Pol II) into polycistronic primary transcripts –. However, the sites and mechanism of transcription initiation and termination for protein-coding genes are largely unknown. Individual mRNAs are matured by coupled trans-splicing and polyadenylation , . In trans-splicing, the spliced leader RNA (SL RNA) donates the 39-nt SL sequence that is attached to the 5′ end of all mRNAs and provides the 5′ cap structure for the mRNA . This intermolecular splicing mechanism is an ancient trait in eukaryotes and is found in many protozoa, nematodes, chordates and other organisms  and involves molecular mechanisms similar to cis-splicing . The sequence signals that determine the trans-splice acceptor site appear to consist only of AG dinucleotide at the site for exon junction preceded by a polypyrimidine tract of varying length , –. Additional nucleotides downstream of the splice site appear to modulate the efficiency of trans-splicing , , however, only a few cases have been studied. Trans-splicing is spatially and temporally coupled to polyadenylation of the upstream mRNA in the polycistron , , . Poly(A) tail addition has been shown to occur at one of several closely spaced positions with a possible preference for A residues, based on a limited set of cDNAs . Computational approaches have been used to predict trans-splice and polyadenylation sites in T. brucei ,  and when we started this study, there were no comprehensive studies of bona fide pre-mRNA processing sites in trypanosomatids. Thus, the emergence of next-generation sequencing technologies offered a unique opportunity to provide a complete catalogue of 5′ and 3′ end processing sites and to validate the annotated features of the T. brucei genome at the transcript level. In the current study, as well as in a recent publication by Siegel et al. , high-throughput RNA sequencing (RNA-Seq) was used to generate a T. brucei transcriptome map at single-nucleotide resolution.
Data sets obtained by RNA-Seq
To map transcribed regions in T. brucei on a genome-wide scale, we used the RNA-Seq approach . Starting with poly(A)+ RNA isolated from insect-form (culture-form adapted) T. brucei rhodesiense YTat 1.1 , double-stranded cDNA was generated conventionally with either random hexadeoxynucleotide or oligo(dT) primers (Figure 1A). We sequenced four libraries, namely two biological samples, each random-primed and oligo(dT)-primed (RNA-Seq data from this study have been submitted to the NCBI Sequence Read Archive - SRA at http://www.ncbi.nlm.nih.gov/Traces/sra/sra.cgi - under accession no. SRA012290). Pair-wise comparison of all sets resulted in Pearson correlation coefficients exceeding 0.99 (Figure S1), thus giving us a total of 30,860,548 sequence reads (Table 1). 25,245,618 reads (82%) aligned to the reference T. brucei brucei TREU 927 genome  by allowing up to two mismatches in the first 28 nucleotides (Table 1) with 16,651,856 reads (54%) mapping to a unique region in the genome. As expected based on similar approaches in yeast , this strategy resulted in an enrichment of RNA-Seq tags towards the 3′ end of transcripts (Figure 1B). To complement this bias, we took advantage of the unique structure of trypanosome mRNAs and devised a modified procedure for RNA-Seq. Briefly, total RNA was depleted of rRNAs by treatment with Terminator exonuclease, first-strand cDNA synthesis was performed with random hexamers and we then used the SL sequence present at the 5′ end of all trypanosome mRNAs to generate double-stranded cDNA with an SL-specific primer (Figure 1A). Three technical replicates were sequenced (Pearson correlation coefficients of 0.9) resulting in 33,338,202 total reads with 31,794,274 reads (95%) aligning to the genome (Table 1) with a clear preference for the 5′ end of transcripts (Figure 1B). Even though our RNA-Seq tags were obtained from a closely related Trypanosoma subspecies, overall 89% of the sequences aligned to the reference T. brucei brucei TREU 927 genome (Table 1). Furthermore, none of the tags aligned to the gene coding for the Tn10 transposase (Figure S2), which is present in the genome sequence assembly, but is the result of an artifact of BAC construction and thus is not a part of the genome .
(A) Outline of the protocol for generating libraries for sequencing. (B) Overlay of the number of reads (log2) from 5′-end- (blue) and 3′-end- (red) enriched libraries aligning to ∼10 kb genomic region. Numbers of end-reads, SL-containing (blue) and poly(A)-containing (red), are shown below the x-axis (−log2). (C–F) Examples of misannotated start codons (C), genes not producing their own transcript (D), alternatively processed transcripts (E) and new transcripts (F). Red arrows point to the highlighted transcriptome features.
Mining RNA-Seq data for gene boundaries and RNA levels
To map 5′- and 3′-end boundaries of trypanosome transcripts, we inspected the aligned data for regions of rapid changes in the abundance of RNA-Seq tags. In addition, our annotation was aided by the availability of end tags, i.e. 2,434,466 SL- and 328,881 poly(A)-containing reads (Table 1). This strategy allowed the precise mapping of both ends of 8,960 mRNA molecules with representative examples shown in Figure 1B. 898 previously annotated genes had very few reads and thus we were unable to precisely define their transcript boundaries. Most genes in this group are subtelomeric variant surface glycoprotein genes and pseudogenes (620), expression site-associated genes and pseudogenes (104), as well as unlikely ORFs, sequence orphans and conserved proteins (174). Our 5′-end mapping identified 532 genes (5.9% of all genes) with misannotated translation start codons (Figure 1C, Figure S3 and listed in Table S1) and RT-PCR experimentally confirmed that the ORFs of two genes on chromosome VIII were indeed shorter than currently annotated (Figure S3C). Furthermore, 805 annotated genes (not included in the total number of genes) did not produce a transcript of their own (Table S2), but were often part of the 5′UTR or 3′UTR of a transcript from a neighboring gene (Figure 1D and Figure S4), which we corroborated by Northern blot analysis for two such scenarios (Figure S4C).
We identified 441 genes that have unambiguous alternative processing in the 5′UTR (47 genes) or 3′UTR (394 genes), thus generating a full-length transcript, as well as a shorter ORF-containing and a putative non-coding transcript (Figures 1E and S5 and listed in Table S3). For instance, Tb927.4.4370 and Tb927.4.4490 fall into this category and by Northern blot analysis three distinct transcripts, as predicted by RNA-Seq, are easily detectable (Figure S5C). The functional significance of the UTR-internal transcripts remains to be investigated, since they have limited coding potential (Figure S6E) and it was inconclusive whether one such transcript derived from the 3′UTR of Tb927.4.4370 was associated with polyribosomes (Figure S6B).
The genome assembly of T. brucei lists four putative introns with two being experimentally validated , . Using the program TopHat , which aims to identify splice junctions, and confirmed by manual inspection, we only detected the experimentally validated introns in the genes for poly(A) polymerase (Tb927.3.3160) and an ATP-dependent DEAD/H RNA helicase (Tb927.8.1510) and found no evidence for additional introns in the T. brucei genome (data not shown) in line with a similar conclusion by Siegel et al. .
Our data also shed light on the synthesis of annotated small nucleolar RNAs (snoRNAs), whose genes are always oriented in the same direction as neighboring protein coding genes and are known to be transcribed by Pol II , . It appeared that snoRNAs are initially produced as long precursors with mRNA features, i.e. SL at the 5′ end and a poly(A) tail at the 3′ end, and these precursors may contain one or more snoRNA sequences. We noticed 27, 9 and 5 instances where snoRNAs mapped in 3′UTRs, predicted ORFs and 5′UTRs, respectively (Figure S7). Particularly intriguing is the scenario where 7 snoRNAs are embedded in the ORF of Tb927.3.1900 (Figure S7C), since these snoRNAs are expressed  and the predicted protein was detected in two separate proteomic analyses , . This unusual organization will need to be investigated further.
The above mapping of gene boundaries provided a platform to delineate and measure 5′ and 3′UTRs (Tables S4 and S5). The median length of 5′UTRs in T. brucei is 130 nt with a range from 39, with the SL abutting the initiation codon, to ∼2,500 nt (Figure 2A), whereas a similar analysis of 3′UTRs revealed a median length of 388 nt with a range of 10 to ∼6,000 nt (Figure 2B). The median lengths are in agreement with those described in Siegel et al.  of 128 nt and 400 nt for the 5′ and 3′UTRs, respectively. It is important to point out that in this study the 39-nt SL was included in the 5′UTR length calculation, whereas Siegel et al. opted to exclude the SL from their analysis .
(A) Distribution of 5′UTR length (including the 39 nt SL), n = 6,577. (B) Distribution of 3′UTR length, n = 1,902. (C–D) Coding potential of novel T. brucei transcripts. (C) Length distribution of possible ORF-encoded polypeptides (nonoverlapping ORFs, equal or longer than 75 nt), n = 4,540. (D) Positional distribution of translation start sites for possible ORFs in novel transcripts, n = 4,540.
Furthermore, by taking advantage of the quantitative nature of RNA-Seq , we were able to estimate RNA levels in the insect-form T. brucei rhodesiense YTat 1.1 strain (Table S6). We determined the signal in a 500-bp window immediately downstream of the first trans-splice site and, using the measured PGKB mRNA level as a reference point , we estimated that 75% of the genes generate between 1 and 10 mRNA molecules per cell (Figure S8). Our copy number estimates (median is 3 mRNAs per cell) for cultured procyclic T. brucei are comparable to data obtained for yeast ,  and mammals .
Novel coding and non-coding RNAs
We detected 1,114 new transcripts (12% of total) not originating from a previously annotated ORF (Table S7). They are trans-spliced and polyadenylated and the range of size and expression level closely resembles that of transcripts mapped to annotated ORFs (Figures 1F, 2 and S9 and Table S7). Setting a lower limit of 25 amino acids, 1,011 transcripts have the potential to encode one or more ORF with a considerable number having a predicted signal peptide (4.2%). In particular, 27 newly identified transcripts contain ORFs that are conserved and annotated in T. cruzi and/or Leishmania major (Table S8) and an additional 23 new transcripts encode potential polypeptides that are conserved, but not annotated in T. cruzi and/or L. major (Table S9). For instance, three novel transcripts on chromosome VIII, clearly detectable by Northern blot analysis, encode ribosomal protein L41 and two newly mapped transcripts on chromosome XI encode polypeptides that are conserved, but not annotated in T. cruzi and L. major (Figure S9). Tb10.NT.122 is a novel transcript on chromosome X with the longest predicted ORF encoding 32 amino acids. This transcript co-sedimented with polyribosomes on a sucrose density gradient and shifted to lighter fractions under conditions where translation was inhibited (Figure S6C), indicating a likely association with the translational apparatus. Finally, by searching the proteome data set of Panigrahi et al. that did not map to annotated genes , we identified 19 novel transcripts where the predicted ORF had one or more matches with peptides identified by mass spectrometry (Table S10), thus providing evidence that at least some of these new proteins are made.
Of the 1,114 novel transcripts, 9.2% (103) did not contain ORFs 25 amino acids or longer and ranged in size from 154 nt to 2,229 nt (Table S11). Although some of these transcripts might potentially code for a peptide, since the shortest verified coding sequence in eukaryotes is 33 nt, i.e. 11 amino acids , , it is worth noting that the six largest transcripts, each longer than 1,000 nt, have no coding potential at all (Table S11).
Heterogeneity of RNA processing sites
The depth of our coverage of 5′ end tags (Table 1) allowed us to expose a genome-wide picture of trans-splice sites, which turned out to be quite promiscuous (Figure 3A). Out of the 8,592 transcripts with at least 10 SL tags at the primary site, only 926 (11%) had a single site for SL addition, whereas 5,327 transcripts (62%) had between two and four 3′ trans-splice sites and 2,339 transcripts (27%) had five or more sites (Figures 3A and B). Additional sites were mainly located downstream of the primary site (Figure 3A) and occasionally mapped within the 5′ region of ORFs (Table S12). To validate this unexpected result, we first inspected trans-splice site usage at the α-tubulin gene (Figure S10). The most prominent site mapped by RNA-Seq coincided with the site identified by previous analysis of cDNAs, but minor sites were also evident. Next, we selected four genes representing the spectrum of heterogeneity and cDNAs generated by RT-PCR reproduced the multiple or highly homogenous SL addition sites seen by RNA-Seq (Figure S11).
(A) Heterogeneity of 3′-trans-splice sites. The trans-splice sites of each gene are shown in each line of the plot, n = 7,966. Each site is represented by a bar colored according to its usage (relative number of SL-containing reads). The site with the largest number of reads is centered, and sites within 150 nt upstream or downstream of this site are included. For display purposes, not all transcripts are shown. Genes are ranked from most homogeneous splice sites (top) to least homogeneous splice sites (bottom). (B) Number of trans-splice sites per gene, n = 8,815. (C) Compositional profile of the 3′-trans-splice site sequence, n = 7,966. Nucleotide positions are relative to the site of splicing. (D) Distribution of PPT–3′-trans-splice site distances, n = 7,996. (E) Distribution of PPT lengths, n = 7,966. (F) Distribution of poly(A) site–(downstream-)3′-trans-splice site distances, n = 1,759.
We were unable to identify any significant difference in the sequence signatures surrounding homogeneous and heterogeneous splice sites (data not shown) and there was only a very limited correlation between splice site heterogeneity and abundance of the corresponding transcript (data not shown). The only highly conserved sequence signals that appeared to define a 3′-trans-splice site in T. brucei are the well-known AG dinucleotide immediately upstream and the polypyrimidine tract (PPT) further upstream of the splice site, as well as the exclusion of G residues at position -3 (Figure 3C), which has been suspected previously . An AG dinucleotide was found at 98% of the major splice sites, whereas minor sites had an AG in 75% of the cases (Figure 3C and Table S4). At present we do not know whether this observation is of functional significance. Since two major sites with an apparent AA or GG dinucleotide in the 927 genome reference strain turned out to have bona fide AG splice acceptor sites in our strain used for RNA-Seq (data not shown), we cannot exclude the possibility that many of these variant non-AG sites are due to strain differences. The PPT starts 0 to ∼200 nt (median is 43) upstream of the splice site (Figures 3C and 3D), its median length is 18 nt with a range from 7 to 79 nt (Figure 3E) and its composition showed a clear preference for Ts over Cs (Figure 3C), in agreement with a comprehensive mutagenesis study . The median distance between the trans-splice site and the upstream polyadenylation site is 142 nt and in 50% of the cases is between 123 and 178 nt (Figure 3F), highlighting the tight spatial coupling of the two RNA processing events , .
Polyadenylation sites (PAS) in T. brucei transcripts appeared even more heterogeneous than trans-splice sites (Figure 4A and Table S13). A representative example is shown in Figure S10, where the processing sites in between the β and α-tubulin genes are summarized. The most prominent RNA-Seq sites correlated with experimental data , but this methodology also revealed an unanticipated extent of heterogeneity. The heterogeneity in 3′-end formation was not too surprising, since it is known that a poly(A) tail can be added at any one of several closely spaced positions , . Polyadenylation occurs preferentially at an A residue (before or after; our data cannot distinguish) in the transcript that is often followed by a second A, and our results showed a preference for T-rich sequence in the vicinity of the site for poly(A) tail addition (Figure 4B).
(A) The polyadenylation sites of each gene are shown in each line of the plot, n = 2,081. Each site is represented by a bar colored according to its usage [relative number of poly(A)-containing reads]. The site with the largest number of reads is centered, and only sites within 150 nt upstream or downstream of this site are included. For display purposes, not all transcripts are shown. Genes are ranked from most homogeneous polyadenylation sites (top) to least homogeneous polyadenylation sites (bottom). (B) Compositional profile of T. brucei polyadenylation sites, n = 2,081.
RNA-Seq tags map putative Pol II transcription initiation sites
An intriguing observation was the presence of a limited number of polyadenylated transcripts that appeared to be significantly underrepresented or even absent in our SL library data sets. In particular, these transcripts mapped closely to regions in the genome previously identified as putative Pol II transcription initiation sites , , , namely strand-switch regions of divergent transcription units, the beginning of Pol II transcription units that neighbor tRNA genes, shown previously to be strong stops for Pol II , as well as a few other regions within transcription units (Figures 5A, B and C). Such transcripts can be detected as heterogeneous species by Northern blotting (Figure 5D) and a large fraction of them appeared to be uncapped and have a single phosphate at their 5′ end, as judged by their susceptibility to degradation by Terminator exonuclease (a 5′ monophosphate-dependent enzyme) and alleviation of this susceptibility by a preceding phosphatase treatment (compare lanes 2, 8 and 12 in Figure 5E). In contrast, at most suspected ends of Pol II transcription units, we detected transcripts of extremely low abundance, i.e. less than one molecule per cell, that possess a SL sequence, but lack poly(A) tails, as judged by their absence in our poly(A)-enriched libraries (data not shown). [The transcripts without SL sequence or a poly(A) tail were not included in the total number of genes or in the number of novel transcripts.] Transcripts present near putative Pol II start sites lacking the SL but containing a poly(A) tail, as well as those with an SL but missing the poly(A) tail at possible Pol II termination sites, are best explained by the known coupling of trans-splicing and polyadenylation , . For example, trans-splicing of the first mRNA in a polycistronic transcript will by default result in the polyadenylation of the upstream RNA and thus generate the transcripts we detected.
(A) Plots of the number of reads (log2) from poly(A)-enriched (red) libraries and SL-enriched (blue) libraries aligning to a region of divergent transcription. a, b – transcripts underrepresented in the SL-enriched libraries. (B) Plots of the number of reads aligning to a region adjacent to a putative centromeric region on chromosome IV. c – a novel transcript, d – transcript underrepresented in the SL-enriched libraries. (C) Plots of the number of reads aligning to a region adjacent to a tRNA gene (green triangle). e – transcript underrepresented in the SL-enriched libraries. (D) Northern blots of RNA after one round of oligo(dT) selection with probes against the indicated transcripts. RNA size marker is visualized with methylene blue staining of the membrane. Multiple sizes transcripts are present for b and c, as suggested by the reads alignment plots in (A) and (B). Asterisks indicate bands cross-hybridizing to rRNA for the d and e blots. (E) RT-PCR assay to determine the nature of the 5′ ends of transcripts. After incubation of total RNA with the indicated enzymes, the samples were treated with or without Terminator exonuclease prior to reverse transcription and PCR. –RT – control sample without reverse transcriptase; Ctrl – control sample treated without any 5′-end-modifying enzyme; RPP – RNA 5′ polyphosphatase; TAP – tobacco acid pyrophosphatase; PNK – T4 polynucleotide kinase; CIP – calf intestinal alkaline phosphatase. Tb570 is a control detecting mRNA for Tb10.6k15.1610.
The SL-lacking RNAs described above could represent remnants of primary Pol II transcripts, i.e. RNA fragments from the very 5′ end of long polycistronic precursors that have either been processed by an unknown mechanism to expose a 5′-monophosphate or have been subjected to trimming of their triphosphate ends to a 5′-monophosphate. To explore this possibility, we generated and sequenced a cDNA library enriched for 5′-triphosphate RNA ends, the hallmark of a 5′ end generated by an RNA polymerase (Figure S12). The validity of our protocol was underscored by correctly mapping the transcription initiation site of the EP1 procyclin gene (Figure 6). Corroborating our hypothesis, RNA-Seq tags were again enriched in regions of the genome implicated to be sites for transcription initiation by Pol II (Figure 7A). In particular, this enrichment was observed at all sites suspected to act as Pol II promoters based on the accumulation of specifically modified and variant histones , i.e. primarily at every divergent transcription unit (Figure 7B and Table S14), at regions located at the beginning of transcription units in proximity to tRNA genes (Figure 7C and Table S14), as well as at internal sites within transcription units (Figure 7D and Table S14). One common theme of all regions was that they showed enrichment of not only sense, but also antisense 5′-triphosphate RNA-derived reads (in contrast to a Pol I transcription unit, Figure 6), suggesting that these putative Pol II transcription initiation sites are intrinsically bi-directional.
(A) Shown is a segment of chromosome X surrounding the EP1 procyclin gene. The EP1 ORF is indicated by a dark blue arrow. The fold enrichment of reads from the 5′-triphosphate end library [(number of reads in the 5′-triphosphate end-enriched library)×24/(number of reads in the 5′-end enriched library)] are plotted for the plus strand (sense, red) and the minus strand (antisense, blue). (B) Shown is the region surrounding the transcription start site for RNA polymerase I with the individual aligned reads (blue horizontal arrows). Since this library was prepared after oligo(dT) selection of transcripts, the obtained reads are most likely derived from the extremely low-abundance, full-length polyadenylated EP1 procyclin transcripts that have not been trans-spliced. Indicated by arrows in different shades of orange-red are previously determined transcription start sites by S1 protection  and primer extension , as well as the primary start site identified by RNA-Seq (this study).
Plots for the fold enrichment of reads from the 5′-triphosphate end library [(number of reads in the 5′-triphosphate end-enriched library)×24/(number of reads in the 5′-end enriched library)] are shown aligning to ∼40 kb genomic region for the plus strand (red) and the minus strand (blue). Annotated ORFs are shown in colored bars corresponding to their orientation. Annotated tRNAs are shown as green bars and are highlighted with green circles. (A) Plots for the examples shown in Figure 5A–C. (B) Examples of regions of divergent transcription. (C) Examples of genomic loci in proximity to tRNA genes. (D) Examples of genomic regions within transcription units.
The current annotation of the T. brucei genome relied heavily on bioinformatic approaches, since to date a mere 5,133 ESTs are available. Thus, our initial goal in the work presented here was to map gene boundaries at the transcript level and to provide experimental support for annotated features. We used RNA-Seq to generate a T. brucei transcriptome map at single-nucleotide resolution and confirmed many of the gene models, but also uncovered numerous cases of misannotated translation initiation codons, annotated ORFs not producing a distinct transcript and an abundance of novel transcripts, including ones which appear to be non-coding. Remarkably, we were also able to map, on a genome-wide scale, putative Pol II transcription start sites in T. brucei (summarized in Table S14). Our results corroborate a recent study where it was shown that such chromosome locations are marked by specifically modified and variant histones , . In addition, we detected both sense and antisense transcription originating from these genome loci, with sense transcripts at higher levels than antisense (Figure 7). This finding matches a scenario described for mammalian CpG promoters –, where transcription is divergent and initiates over a broad genomic region. Moreover, our RNA-Seq data for 5′-triphosphate-enriched RNAs showed reads mapping throughout Pol II transcription units in the sense and antisense orientation (Figure S13) and thus, we cannot exclude the possibility that these are actual transcription initiation sites similar to the ones described in exons/3′ UTRs in mammals .
One of the major benefits of RNA-Seq is its capability to accurately determine transcript boundaries. Our mapping of conventional 5′ and 3′ ends of T. brucei mRNAs revealed an abundant heterogeneity in trans-splice and polyadenylation sites. Whereas the heterogeneity of poly(A)-addition sites was somewhat anticipated ,  and to a lesser extent this scenario has been observed as local heterogeneity of polyadenylation positions in yeast  and mammals , , the degree of variability we encountered for trans-splice sites was quite unexpected. Although trans- and cis-splicing are mechanistically related, our finding highlights a fundamental difference between these two processes. Cis-splicing occurs predominantly within ORFs  and, thus, is subjected to evolutionary pressure to maintain an intact coding sequence. This apparent accuracy of intron excision is likely accompanied by rapid destruction of aberrantly spliced mRNAs by the nonsense-mediated decay pathway . In contrast, trans-splicing mainly takes place upstream of ORFs and appears to follow more relaxed rules for the selection of a nucleotide for the second trans-esterification reaction of splicing. As a consequence, the observed heterogeneity in T. brucei of both trans-splicing and polyadenylation generates a collection of mRNAs with the same coding potential, but with UTRs (3′ or 5′) of varying length, sometimes in the order of hundreds of nucleotides. This fluidity in generating mRNA ends is quite unusual, particularly in an organism where the regulation of gene expression has been attributed to occur mainly at the post-transcriptional level , . Importantly, the degree of heterogeneity of both trans-splicing and polyadenylation varies and different genes exhibit RNA processing patterns spanning from one extreme - a single detectable processing site - to the other, where no single site is used preferentially (Figure 8).
(A) Examples of homogeneous (left) and heterogeneous (right) trans-splice sites. Shown is the pileup of number of internal reads (log2) from 5′-end-enriched libraries (dark red). Individual SL-containing reads are depicted by red arrows under the graph. The identity of each gene is indicated above the black bar representing the beginning of the ORF. The light blue vertical lines are 100 nt apart. (B) Examples of homogeneous (left) and heterogeneous (right) polyadenylation sites. The pileup of number of internal reads (log2) from 3′-end-enriched libraries (red) is depicted above the individual poly(A)-containing reads (red dots). Scale as in (A). (C) Examples of “truly” alternatively processed transcripts. The number of internal reads (log2) from 5′-end- (dark red) and 3′-end-enriched (red) libraries aligning to the genomic regions surrounding the indicated ORFs (black arrows) are depicted. Easily identifiable peaks in the 3′-end-enriched libraries pileup (red arrows) and end-reads (not shown) indicate the alternative 3′ ends of the transcripts containing the ORFs. Note the scale difference from (A) and (B).
Overall, our data set is in good agreement with that of Siegel et al. . The overlap between the mapped trans-splice sites is excellent with most genes having a very high correlation (Figure S14A). There is a weak overlap between the polyadenylation sites (Figure S14B). This is most likely a reflection of the inherent difficulty to identify PAS due to the pervasive heterogeneity (Figure 4) and the prevalence of low-complexity sequences in the 3′UTR. Thus, our stringent filtering only yielded 2,081 PAS assignments with confidence (Figure 4). Finally, the mRNA abundance comparison (for the 6,728 transcripts present in both studies) is good with a Pearson correlation coefficient of 0.697 (Figure S15), considering the different T. brucei subspecies, as well as differences in culture conditions, mRNA isolation procedures, RNA-Seq cDNA library preparation protocols and methods of estimating the abundance.
Evidence and theorization over the past decade has resulted in a widespread appreciation of the benefits of stochastic models of gene expression over purely deterministic ones –. We estimate that 75% of T. brucei genes are expressed at levels between 1 and 10 mRNAs per procyclic cell (Figure S8). In addition, it is evident from our data and corroborated by Siegel et al.  that the majority of genes produce different transcript forms created by heterogeneity in trans-splicing and polyadenylation and bearing or lacking 5′ and/or 3′ UTR sequences that could influence the efficiency of RNA stability and/or translation. The possibility for regulation of pre-mRNA processing site choice clearly exists, however it remains to be seen whether alternative splicing or polyadenylation are part of a regulated process. Since transcription is one of the main intrinsic noise sources  and Pol II transcription in trypanosomatids appears to be uniform across individual polycistronic transcription units (and likely the entire Pol II transcriptome), heterogeneity in the sites for pre-mRNA processing provides an additional source of intrinsic stochasticity to compensate for the uniformity in transcription. Interestingly, it appears that heterogeneity of trans-splicing is a specific characteristic of trypanosomatids, since it was not described in the transcriptome analysis of the nematode Caenorhabditis elegans , an organism with prevalent trans-splicing in which most trans-spliced genes are individually transcribed . Our results have implications for gene expression patterns in other important human pathogens and point to heterogeneity in pre-mRNA processing (rather than transcription) as the main intrinsic source of stochasticity in gene expression for these protozoan parasites.
3′ end-enriched libraries
Total RNA was treated with RQ1 RNase-free DNase I and subjected to two rounds of poly(A)+ selection. First strand cDNA synthesis was initiated with random hexadeoxynucleotide primers or 5′-T15VN-3′ oligonucleotide. After incubation with RNase H and E. coli DNA polymerase I, double-stranded cDNA was fragmented with DNase I and cDNA fragments corresponding in size to about 200 bp were size-selected on an agarose gel. The cDNA ends were repaired, a single dA was added at the 3′ ends and genomic adapters (Illumina, Inc. All rights reserved.) were added. Libraries were enriched by limited PCR and purified on an agarose gel.
5′ end-enriched libraries
Total RNA was treated with Terminator 5′-monophosphate-dependent exonuclease, followed by DNase I and first strand cDNA synthesis was initiated with random primers. Second strand cDNA synthesis was primed with the SL Primer (5′-GCTATTATTAGAACAGTTTCTGTACTATATTG-3′) and platinum Pfx DNA polymerase. cDNA was further processed as described above.
Total RNA was subjected to two rounds of poly(A)+ selection and treated with Terminator 5′-phosphate-dependent exonuclease. Next, the RNA was treated with RNA 5′-polyphosphatase and a 5′ adapter with a BpuE I restriction site (5′-GCACCATATAACCGCTTCCrUrUrGrArG-3′) was ligated to the available 5′-monophosphate ends. Following first strand cDNA synthesis as described above, double-starnded cDNA was generated with a BpuE I Primer (5′-GCACCATATAACCGCTTCCTTGAG-3′) and Pfx DNA polymerase. DNA fragments larger than 100 bp were gel purified, digested with BpuE I in the presence of S-adenosylmethionine. The DNA was separated on an agarose gel and several gel segments spanning the ∼130 bp size range were excised and processed for Illumina sequencing.
Enzyme assays for RNA 5′-end analysis
Reactions with 5′-end-modifying enzymes were performed in a volume of 40 µL with 14 µg total RNA with 40 U RNA 5′-polyphosphatase, 40 U tobacco acid pyrophosphatase, 10 U T4 polynucleotide kinase plus 1 mM ATP, or 1 U alkaline phosphatase. After the appropriate incubation, reactions were divided into two tubes and one aliquot was treated with 1 U Terminator 5′-phosphate-dependent exonuclease and the second aliquot served as a control. Reverse transcription with random hexamers was performed and the resulting cDNA was used as a template for PCR with forward and reverse primers specific for the transcripts of interest.
Processing of 5′ end reads
Over 2.5 million reads from the SL-primed library contained the entire splice-leader sequence at their 5′ ends. This sequence was removed, leaving 43 nucleotides, and the first 28 nucleotides were aligned to the genome reference, with a maximum of 2 allowed mismatches and one alignment reported per read. Unless indicated, all read manipulations, as well as the genome-wide site analyses, were performed with custom scripts written either in Perl or for a combination of the R statistical software with the bioinformatics-centric Bioconductor tools installed.
Processing of 3′ end reads
Reads consisting primarily of A or T nucleotides (more than 31 out of 35 total nucleotides) were removed from the 3′ end-enriched libraries. Next, contiguous A or T stretches, 5–15 letters long, were trimmed off the 5′ or 3′ ends of the sequences, respectively. Trimmed reads, ranging in length from 15–30 nucleotides, represented putative 3′ end-reads and were aligned to the genome reference. In order to distinguish poly(A) tails from RNA transcribed from contiguous As in the genome, alignments were only considered to represent polyadenylation sites, if the end-read contained a longer stretch of A's than was present in the genome.
Analysis of 5′-triphosphate-end-enriched libraries
Preparation of the 5′-triphosphate-end-enriched library produced two sets of reads, categorized by the position of the 14-nt sequence representing the 5′ transcript end (the “end-sequence”). The first set, corresponding to the top strand contained the 24 nt adapter (GCACCATATAACCGCTTCCTTGAG) at the beginning of the read, followed by the end-sequence, spanning nucleotides 25 through 38. The second set contained reverse complement of the end-sequence in the left-most 14 nt, followed by the same reverse complement of the 24 nt adapter. These 14 nt end sequences were extracted from the two sets of reads, and the second set was reverse complemented, to produce the end-reads. Alignment to the genome was with no mismatches allowed, and one alignment reported per read.
Alignment and interactive analysis of RNA-Seq data
Sequence reads obtained from the Illumina GA2 platform, ranging from 35–75 nucleotides in length, were aligned to the eleven major chromosomes in the T. brucei genome sequence, version 4 (genedb.org). All alignments were conducted with Bowtie . Alignments were only considered if they contained fewer than two mismatches in the first 28 nucleotides of the alignment. For transcript-end analyses, end-reads were first identified then trimmed before alignment. Reads reporting multiple alignments were retained and aligned pseudo-randomly (according to Bowtie's default method). Processed RNA-Seq reads, including end-tags, were loaded into a customized, local installation of the Generic Genome Browser  for interactive annotation and analysis of transcript ends and novel transcriptome features.
Measurement of transcript abundance
A relative measure of transcript abundance was derived from the number of reads (not including end-reads) that aligned within a 500-nucleotide window, extending into the gene from the 5′ end of the transcript for the SL-library and from the 3′ end for the poly(A) library.
Polypyrimidine tract calculations
The polypyrimidine tract was identified as the longest stretch of pyrimidines separated by no more than one purine in a 200 nt window upstream of the splice site with the maximal number of reads.
We eliminated from the analysis transcripts in which the maximal number of reads per splice site was less than 10. We developed a metric, dispersion, to capture and summarize the positional information about the splice sites of each gene. Essentially, dispersion is the weighted average of the distance between each site to the most popular site:
Assume a gene has N splice sites. Define ci as the number of reads of site i and ri as the position of the site. Denote and let i* represent the splice site with the maximal number of reads. The splicing dispersion is then defined as:
Similarly, the average 5′ UTR length is the weighted average of the distance of all splice sites from the start codon. Symbolically:
For UTR analyses, except where noted, splice sites downstream of the annotated start codon are not included in the sum (and C is the sum only over splice sites upstream of the start codon). Misannotated or unannotated transcripts were not considered for this analysis. We used a similar approach for analysis of polyadenylation sites, 3′UTRs.
Additional methods can be found in Supporting Information S1.
Comparison of technical and biological replica data sets. (A–I) Transcript abundance measures were derived from the number of reads (not including end-reads) that align within a 500-nucleotide window at the 5′ end of the transcript (for the SL-libraries) or at the 3′ end (for the poly-A enriched libraries; random primed or oligo(dT) primed). Shown above each graph are the Pearson's correlation coefficient (ρP) and the Spearman's rank correlation coefficient (ρS). Pcr, pct and pcs indicate libraries from procyclic cells prepared with random primers, oligo(dT) primer and SL primer (for the second cDNA strand), respectively.
(0.64 MB PDF)
Accuracy of alignment of sequence reads to the T. brucei reference genome. Shown is the overlay of the number of reads (log2) from 5′-end- (blue) and 3′-end-enriched (red) libraries aligning to ∼4kb window on chromosome III that contains the ORF for Tn10 transposase (Tb927.3.1050). Numbers of end-reads [SL-containing, blue; poly(A)-containing, red] are also shown (−log2). ORFs are represented by black arrows. No reads align to the Tn10 transposase ORF, which clearly is inserted within the sequence of a single transcript that covers both Tb927.3.1040 and Tb927.3.1060 (both currently annotated as interrupted, conserved hypothetical protein pseudogenes). According to GeneDB (www.genedb.org), the Tn10 insertion is an artifact from BAC construction and is not present in the Trypanosoma brucei brucei strain 927 genomic DNA or other BACs covering this region .
(0.07 MB PDF)
Experimental validation of misannotated translation start codons in T. brucei genes. Overlay of the number of reads (log2) from 5′-end- (blue) and 3′-end- (red) enriched libraries aligning to the shown regions of chromosome VIII covering the ORFs for Tb927.8.1270 (A) and Tb927.8.2000 (B). Numbers of end-reads (−log2) are also shown [SL, blue; poly(A), red]. Dashed lines indicate the positions of a gene-specific primer, the newly annotated trans-splice site and the currently annotated ATG for each of the two genes. Green bars indicate the potential products from an RT-PCR assay with SL and gene-specific primers. (C) RT-PCR assay. Poly(A)+ RNA was reverse transcribed with random primers and the resulting cDNA was used as a template for nested PCR with an identical SL forward primer for both amplification steps. Nested PCR was used to ensure specificity of amplification since the forward SL primer anneals to cDNA products from all T. brucei mRNAs. The sizes of the amplified products indicate that the ORFs for the corresponding genes are shorter than currently annotated.
(0.13 MB PDF)
Experimental validation of misannotated T. brucei genes that are part of transcripts from neighboring genes. Overlay of the number of reads (log2) from 5′-end- (blue) and 3′-end-enriched (red) libraries aligning to the shown regions of chromosomes VIII (A) and I (B). Black arrows represent ORFs encoding conserved proteins and grey arrows represent ORFs for a sequence orphan Tb927.8.5790 (A) and the unlikely hypothetical proteins Tb927.1.3060, Tb927.1.3080, Tb927.1.3090 and Tb927.1.3100 (B). (C) Northern blots of total RNA fractionated on denaturing agarose gels with probes against the indicated ORFs (adjacent lanes of the gel were used for the blots with different probes). The probes against Tb927.8.5780 and Tb927.8.5790 are detecting the same size transcript of ∼2.9 kb [∼2.8 kb plus a poly(A) tail]. The probes against Tb927.1.3070 and Tb927.1.3100 are also detecting the same size transcript of ∼2.6 kb [∼2.5 kb plus a poly(A) tail]. Positions of markers are indicated on the left.
(0.13 MB PDF)
Experimental validation of T. brucei genes that produce alternatively processed transcripts. Overlay of the number of reads (log2) from 5′-end- (blue) and 3′-end-enriched (red) libraries aligning to the shown regions of chromosome IV covering the transcripts produced for Tb927.4.4370 (A) and Tb927.4.4490 (B). Black arrows represent the annotated ORFs and purple arrows represent transcripts suggested by the internal tags (peaks in the pileups are indicated with red and blue downward arrows) and end-reads (not shown) alignment to the T. brucei genome. Note that Tb927.4.4370 is another example of a gene with a misanotated translation start codon. The positions of the regions hybridizing to specific probes are indicated by short black lines. (C) Northern blots of total RNA fractionated on denaturing agarose gels with the indicated (a–d) probes. Both probes a and b detect the full-length Tb927.4.4370 transcript. Probe a additionally detects a shorter transcript containing the Tb927.4.4370 ORF, while probe b additionally detects a shorter transcript that is a part of the 3′ UTR of the full-length Tb927.4.4370 transcript. Probes c and d both detect the full-length Tb927.4.4490 transcript. Probe c additionally detects a shorter transcript containing the Tb927.4.4490 ORF, while probe d additionally detects a shorter transcript that is a part of the 3′ UTR of the full-length Tb927.4.4490 transcript. Positions of marker RNA bands are indicated on the left.
(0.17 MB PDF)
A novel transcript with limited coding potential is possibly associated with polyribosomes. (A) Cell extracts prepared in the presence of pactamycin (an antibiotic that promotes apparent polyribosome dissociation through inhibition of the formation of complete translation initiation complexes) or cycloheximide (an antibiotic that arrests polyribosomes by interfering with ribosome translocation) were subjected to sucrose gradient ultracentrifugation. RNA was purified from individual gradient fractions, separated on a denaturing agarose gel, transferred and cross-linked to a nylon membrane, and large rRNAs were visualized by staining with methylene blue. Shown is every other fraction from the gradient. (B) Northern blot of the fractionated RNA with a probe detecting the full-length Tb927.4.4370 transcript (FL) and a shorter transcript that is a part of the 3′UTR of the full-length Tb927.4.4370 transcript (3′UTR) as a result of alternative processing (probe b in Supplemental Fig. S5). (C) Northern blot with a probe detecting a transcript from a novel gene on chromosome X (Tb10.NT.122). (D) Northern blot with a probe against α-tubulin transcripts. Note the shift of α-tubulin mRNA from polysome fractions of the gradient in the cycloheximide-treated extract to lighter gradient fractions in the pactamycin-treated extract. A similar shift is seen for Tb10.NT.122 (C). Three frame translation for Tb927.4.4370 3′UTR transcript (E) and Tb10.NT.122 (F) highlighting the limited coding potential of these transcripts. All ORFs are colored orange.
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Examples of snoRNA-precursor transcripts. (A) A transcript containing a single snoRNA. (B) Multiple snoRNAs embedded in the 3′ UTR of a protein coding transcript. (C) Multiple snoRNAs embedded in the ORF of a protein coding transcript. (D) A snoRNA cluster producing multiple precursor transcripts containing more than one snoRNA. All panels show the overlay of the number of reads (log2) from 5′-end- (blue) and 3′-end-enriched (red) libraries. Numbers of end-reads (−log2) are also shown (SL, blue; poly(A), red). Black arrows represent currently annotated ORFs and red arrowheads represent mature snoRNA sequences.
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Abundance profile of T. brucei transcripts. Relative transcript abundance represents the number of reads (not including end-reads) that align within a 500-nucleotide window at the 5′ end of the transcript (combined for the SL-library replicas) for each gene. Plotted is the number of genes with identical number of reads aligning to the 500 nt window. Genes without reads aligning to their sequence are not shown. Calculation of the estimated number of mRNA molecules per cell was based on using the precisely measured PGKB mRNA level in cultured procyclic T. brucei cells  as a reference point. Our estimates for mRNAs copy numbers in T. brucei closely resemble data obtained for yeast ,  and mammals . Darker shades of red background indicate higher copy numbers per cell.
(0.04 MB PDF)
Experimental validation of transcripts for novel T. brucei genes. (A) Overlay of the number of reads (log2) from 5′-end- (blue) and 3′-end-enriched (red) libraries aligning to the shown regions of chromosomes VIII and XI. Transcripts for novel genes (purple bars) are labeled a through e and their approximate sizes indicated [excluding the poly(A) tail]. (B) Sequence of the polypeptides encoded by putative ORFs in the indicated (a–e) transcripts. a, b, and c encode the T. brucei ribosomal protein L41. Also shown are the sequences for the three Leishmania braziliensis L41 polypeptides (encoded by three unannotated, tandemly arranged genes) and the human L41 sequence. Identical amino acids between the sequences from the three species are colored red. d and e encode 56 AA and 62 AA proteins respectively that are conserved but not annotated in L. braziliensis. (C) Northern blots of total RNA fractionated on denaturing agarose gels with probes against the indicated (a–e) transcripts. The (a, b, c) blot was performed with a probe against the short ORF present in all three transcripts. Transcripts a and b have almost identical size and they co-migrate during electrophoretic separation of the RNA sample. Positions of marker RNA bands are indicated on the left.
(0.17 MB PDF)
Comparison between RNA-Seq mapped processing sites with sites mapped by previous sequencing of cDNA clones . Polyadenylation sites and 3′-trans-splice sites mapped by cDNA clones sequencing in the β-tubulin/α-tubulin inter-ORF region are indicated by dark red and dark blue upward arrows, respectively. Polyadenylation sites and 3′-trans-splice sites mapped by end-reads in our RNA-Seq for all β-tubulin/α-tubulin regions are indicated by red and blue downward arrows, respectively. The numbers on top of the arrows designate the number of reads. Asterisk at the beginning of the sequence indicates the β-tubulin stop codon and asterisk at the end of the sequence indicates the α-tubulin start codon.
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Experimental validation of multiple primary trans-splice sites for T. brucei genes. Overlay of the number of reads (log2) from 5′-end- (blue) and 3′-end-enriched (red) libraries aligning to the shown regions of chromosomes IV (A–C) and V (D) covering the ORFs for Tb927.4.1020 (A), Tb927.4.1180 (B), Tb927.4.1600 (C) and Tb927.5.990 (D). SL-containing end-reads are shown as blue or red horizontal lines depending on their orientation (minus or plus strand, respectively). Dashed lines indicate the positions of a nested gene-specific primer and the expected positions of the 3′ trans-splice sites. Green bars indicate the potential products from an RT-PCR assay with SL and gene-specific primers with the predicted size of the fragments indicated on the left. (E) RT-PCR assay. Poly(A)+ RNA was reverse transcribed with random primers and the resulting cDNA was used as a template for nested PCR with an identical SL forward primer for both amplification steps. Tb927.5.990 is an example of a gene with highly homogeneous site for SL addition.
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Outline of the protocol for generation of 5′-triphosphate-end-enriched library for RNA-Seq. Generation and sequencing of a cDNA library enriched for 5′-triphosphate RNA ends, the hallmark of a 5′ end generated by an RNA polymerase.
(0.05 MB PDF)
Comparison between normalized (A) and non-normalized 5′-triphosphate-end-enriched library (B). Shown is a segment of chromosome VII surrounding a strand-switch region (SSR) of divergent transcription. Individual ORFs are indicated by bars colored based on their orientation. Grey arrows indicate the direction of transcription. The fold enrichment of reads (A) [(number of reads in the 5′-triphosphate-end-enriched library)×24/(number of reads in the 5′-end enriched library)] is plotted for the plus strand (red) and the minus strand (blue). The non-normalized number of reads (B) is shown for the plus strand (red) and the minus strand (blue).
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Comparison between the mapped splice sites and polyadenylation sites in this study and the data set in . For the splice sites (A) and poly(A) sites (B), we defined a per-gene measure of overlap between the data in this study and the data in Siegel et al. 2010, as follows: define the entire set of sites found by both studies as si, for i = 1,…n. Define (in each study) the probability to observe the i'th site, pi, as the number of reads for that site divided by the total number of reads for the gene. The overlap is the sum over all sites of min(pi(this study), pi(Siegel et al 2010)). This gives 1, if there is perfect overlap and 0, if there is no overlap at all.
(0.06 MB PDF)
Abundance comparison between the data set in this study and that in . Pairwise (gene-by-gene) comparison of RNA-Seq-based gene abundance reported previously with those derived from the current study (tabulated in Table S6). Correlation coefficients between the sets are 0.697 (Pearson) and 0.483 (Spearman).
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Additional description of materials and methods.
(0.17 MB PDF)
List of predicted ORFs in GeneDB v_4 with a misannotated translation start codon, i.e. the SAS (the transcript 5′ end) mapped within the ORF.
(0.09 MB XLS)
List of annotated ORFs in GeneDB v_4 not producing a detectable transcript in this analysis.
(0.11 MB XLS)
List of genes that have an alternative processing site in the 5′ UTR or 3′ UTR.
(0.09 MB XLS)
Listing of all mapped trans-splice acceptor sites (SAS) and measurement of the 5′UTR length. SAS mapping inside an ORF are indicated by NA in the 5′UTR length column. 5′UTRs were not defined for novel transcripts (NA).
(3.67 MB XLS)
Listing of all mapped poly (A) addition sites (PAS) and measurement of the 3′UTR length. 3′UTRs were not defined for novel transcripts (NA).
(5.05 MB XLS)
Abundance (RNAs/cell) of all transcripts detected in this analysis.
(1.32 MB XLS)
List of all novel transcripts in T. brucei procyclic cells identified in this study.
(0.18 MB XLS)
List of novel transcripts coding for ORFs with homology to annotated gene products in T. cruzi and/or L. major.
(0.05 MB XLS)
List of novel transcripts coding for ORFs with homology to non-annotated ORFs in T. cruzi and/or L. major.
(0.03 MB XLS)
List of novel transcripts in T. brucei procyclic cells identified in this study with matching MS/MS peptides by Panigrahi et al. .
(0.05 MB XLS)
List of putative non-coding transcripts.
(0.02 MB XLS)
Splice site (SAS) dispersion.
(0.86 MB XLS)
Poly (A) site (PAS) dispersion.
(0.23 MB XLS)
We thank P. Zumbo for discussion on methods for cDNA library preparation for Illumina sequencing, R. L. Barnes for help in annotating transcript ends and E. Ullu for discussions and comments on the manuscript.
Conceived and designed the experiments: NGK JBF CT. Performed the experiments: NGK JBF HS. Analyzed the data: NGK JBF SC HS SM CT. Wrote the paper: NGK JBF CT.
- 1. Berriman M, Ghedin E, Hertz-Fowler C, Blandin G, Renauld H, et al. (2005) The genome of the African trypanosome Trypanosoma brucei. Science 309: 416–422.M. BerrimanE. GhedinC. Hertz-FowlerG. BlandinH. Renauld2005The genome of the African trypanosome Trypanosoma brucei.Science309416422
- 2. Aslett M, Aurrecoechea C, Berriman M, Brestelli J, Brunk BP, et al. (2010) TriTrypDB: a functional genomic resource for the Trypanosomatidae. Nucleic Acids Res 38: D457–462.M. AslettC. AurrecoecheaM. BerrimanJ. BrestelliBP Brunk2010TriTrypDB: a functional genomic resource for the Trypanosomatidae.Nucleic Acids Res38D457462
- 3. Clayton CE (2002) Life without transcriptional control? From fly to man and back again. EMBO J 21: 1881–1888.CE Clayton2002Life without transcriptional control? From fly to man and back again.EMBO J2118811888
- 4. Martinez-Calvillo S, Yan S, Nguyen D, Fox M, Stuart K, et al. (2003) Transcription of Leishmania major Friedlin chromosome 1 initiates in both directions within a single region. Mol Cell 11: 1291–1299.S. Martinez-CalvilloS. YanD. NguyenM. FoxK. Stuart2003Transcription of Leishmania major Friedlin chromosome 1 initiates in both directions within a single region.Mol Cell1112911299
- 5. Martinez-Calvillo S, Nguyen D, Stuart K, Myler PJ (2004) Transcription initiation and termination on Leishmania major chromosome 3. Eukaryot Cell 3: 506–517.S. Martinez-CalvilloD. NguyenK. StuartPJ Myler2004Transcription initiation and termination on Leishmania major chromosome 3.Eukaryot Cell3506517
- 6. Palenchar JB, Bellofatto V (2006) Gene transcription in trypanosomes. Mol Biochem Parasitol 146: 135–141.JB PalencharV. Bellofatto2006Gene transcription in trypanosomes.Mol Biochem Parasitol146135141
- 7. LeBowitz JH, Smith HQ, Rusche L, Beverley SM (1993) Coupling of poly(A) site selection and trans-splicing in Leishmania. Genes Dev 7: 996–1007.JH LeBowitzHQ SmithL. RuscheSM Beverley1993Coupling of poly(A) site selection and trans-splicing in Leishmania.Genes Dev79961007
- 8. Matthews KR, Tschudi C, Ullu E (1994) A common pyrimidine-rich motif governs trans-splicing and polyadenylation of tubulin polycistronic pre-mRNA in trypanosomes. Genes Dev 8: 491–501.KR MatthewsC. TschudiE. Ullu1994A common pyrimidine-rich motif governs trans-splicing and polyadenylation of tubulin polycistronic pre-mRNA in trypanosomes.Genes Dev8491501
- 9. Perry KL, Watkins KP, Agabian N (1987) Trypanosome mRNAs have unusual “cap 4” structures acquired by addition of a spliced leader. Proc Natl Acad Sci U S A 84: 8190–8194.KL PerryKP WatkinsN. Agabian1987Trypanosome mRNAs have unusual “cap 4” structures acquired by addition of a spliced leader.Proc Natl Acad Sci U S A8481908194
- 10. Hastings KE (2005) SL trans-splicing: easy come or easy go? Trends Genet 21: 240–247.KE Hastings2005SL trans-splicing: easy come or easy go?Trends Genet21240247
- 11. Liang XH, Haritan A, Uliel S, Michaeli S (2003) Trans and cis splicing in trypanosomatids: mechanism, factors, and regulation. Eukaryot Cell 2: 830–840.XH LiangA. HaritanS. UlielS. Michaeli2003Trans and cis splicing in trypanosomatids: mechanism, factors, and regulation.Eukaryot Cell2830840
- 12. Siegel TN, Tan KS, Cross GA (2005) Systematic study of sequence motifs for RNA trans splicing in Trypanosoma brucei. Mol Cell Biol 25: 9586–9594.TN SiegelKS TanGA Cross2005Systematic study of sequence motifs for RNA trans splicing in Trypanosoma brucei.Mol Cell Biol2595869594
- 13. Benz C, Nilsson D, Andersson B, Clayton C, Guilbride DL (2005) Messenger RNA processing sites in Trypanosoma brucei. Mol Biochem Parasitol 143: 125–134.C. BenzD. NilssonB. AnderssonC. ClaytonDL Guilbride2005Messenger RNA processing sites in Trypanosoma brucei.Mol Biochem Parasitol143125134
- 14. Lopez-Estrano C, Tschudi C, Ullu E (1998) Exonic sequences in the 5′ untranslated region of alpha-tubulin mRNA modulate trans splicing in Trypanosoma brucei. Mol Cell Biol 18: 4620–4628.C. Lopez-EstranoC. TschudiE. Ullu1998Exonic sequences in the 5′ untranslated region of alpha-tubulin mRNA modulate trans splicing in Trypanosoma brucei.Mol Cell Biol1846204628
- 15. Ullu E, Matthews KR, Tschudi C (1993) Temporal order of RNA-processing reactions in trypanosomes: rapid trans splicing precedes polyadenylation of newly synthesized tubulin transcripts. Mol Cell Biol 13: 720–725.E. UlluKR MatthewsC. Tschudi1993Temporal order of RNA-processing reactions in trypanosomes: rapid trans splicing precedes polyadenylation of newly synthesized tubulin transcripts.Mol Cell Biol13720725
- 16. Gopal S, Awadalla S, Gaasterland T, Cross GA (2005) A computational investigation of kinetoplastid trans-splicing. Genome Biol 6: R95.S. GopalS. AwadallaT. GaasterlandGA Cross2005A computational investigation of kinetoplastid trans-splicing.Genome Biol6R95
- 17. Siegel TN, Hekstra DR, Wang X, Dewell S, Cross GA (2010) Genome-wide analysis of mRNA abundance in two life-cycle stages of Trypanosoma brucei and identification of splicing and polyadenylation sites. Nucleic Acids Res. TN SiegelDR HekstraX. WangS. DewellGA Cross2010Genome-wide analysis of mRNA abundance in two life-cycle stages of Trypanosoma brucei and identification of splicing and polyadenylation sites.Nucleic Acids ResIn press. In press.
- 18. Wang Z, Gerstein M, Snyder M (2009) RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet 10: 57–63.Z. WangM. GersteinM. Snyder2009RNA-Seq: a revolutionary tool for transcriptomics.Nat Rev Genet105763
- 19. Ruben L, Egwuagu C, Patton CL (1983) African trypanosomes contain calmodulin which is distinct from host calmodulin. Biochim Biophys Acta 758: 104–113.L. RubenC. EgwuaguCL Patton1983African trypanosomes contain calmodulin which is distinct from host calmodulin.Biochim Biophys Acta758104113
- 20. Nagalakshmi U, Wang Z, Waern K, Shou C, Raha D, et al. (2008) The transcriptional landscape of the yeast genome defined by RNA sequencing. Science 320: 1344–1349.U. NagalakshmiZ. WangK. WaernC. ShouD. Raha2008The transcriptional landscape of the yeast genome defined by RNA sequencing.Science32013441349
- 21. Ivens AC, Peacock CS, Worthey EA, Murphy L, Aggarwal G, et al. (2005) The genome of the kinetoplastid parasite, Leishmania major. Science 309: 436–442.AC IvensCS PeacockEA WortheyL. MurphyG. Aggarwal2005The genome of the kinetoplastid parasite, Leishmania major.Science309436442
- 22. Mair G, Shi H, Li H, Djikeng A, Aviles HO, et al. (2000) A new twist in trypanosome RNA metabolism: cis-splicing of pre-mRNA. RNA 6: 163–169.G. MairH. ShiH. LiA. DjikengHO Aviles2000A new twist in trypanosome RNA metabolism: cis-splicing of pre-mRNA.RNA6163169
- 23. Trapnell C, Pachter L, Salzberg SL (2009) TopHat: discovering splice junctions with RNA-Seq. Bioinformatics 25: 1105–1111.C. TrapnellL. PachterSL Salzberg2009TopHat: discovering splice junctions with RNA-Seq.Bioinformatics2511051111
- 24. Dunbar DA, Chen AA, Wormsley S, Baserga SJ (2000) The genes for small nucleolar RNAs in Trypanosoma brucei are organized in clusters and are transcribed as a polycistronic RNA. Nucleic Acids Res 28: 2855–2861.DA DunbarAA ChenS. WormsleySJ Baserga2000The genes for small nucleolar RNAs in Trypanosoma brucei are organized in clusters and are transcribed as a polycistronic RNA.Nucleic Acids Res2828552861
- 25. Liang XH, Uliel S, Hury A, Barth S, Doniger T, et al. (2005) A genome-wide analysis of C/D and H/ACA-like small nucleolar RNAs in Trypanosoma brucei reveals a trypanosome-specific pattern of rRNA modification. RNA 11: 619–645.XH LiangS. UlielA. HuryS. BarthT. Doniger2005A genome-wide analysis of C/D and H/ACA-like small nucleolar RNAs in Trypanosoma brucei reveals a trypanosome-specific pattern of rRNA modification.RNA11619645
- 26. Bridges DJ, Pitt AR, Hanrahan O, Brennan K, Voorheis HP, et al. (2008) Characterisation of the plasma membrane subproteome of bloodstream form Trypanosoma brucei. Proteomics 8: 83–99.DJ BridgesAR PittO. HanrahanK. BrennanHP Voorheis2008Characterisation of the plasma membrane subproteome of bloodstream form Trypanosoma brucei.Proteomics88399
- 27. Broadhead R, Dawe HR, Farr H, Griffiths S, Hart SR, et al. (2006) Flagellar motility is required for the viability of the bloodstream trypanosome. Nature 440: 224–227.R. BroadheadHR DaweH. FarrS. GriffithsSR Hart2006Flagellar motility is required for the viability of the bloodstream trypanosome.Nature440224227
- 28. Haanstra JR, Stewart M, Luu VD, van Tuijl A, Westerhoff HV, et al. (2008) Control and regulation of gene expression: quantitative analysis of the expression of phosphoglycerate kinase in bloodstream form Trypanosoma brucei. J Biol Chem 283: 2495–2507.JR HaanstraM. StewartVD LuuA. van TuijlHV Westerhoff2008Control and regulation of gene expression: quantitative analysis of the expression of phosphoglycerate kinase in bloodstream form Trypanosoma brucei.J Biol Chem28324952507
- 29. Velculescu VE, Zhang L, Zhou W, Vogelstein J, Basrai MA, et al. (1997) Characterization of the yeast transcriptome. Cell 88: 243–251.VE VelculescuL. ZhangW. ZhouJ. VogelsteinMA Basrai1997Characterization of the yeast transcriptome.Cell88243251
- 30. Holstege FC, Jennings EG, Wyrick JJ, Lee TI, Hengartner CJ, et al. (1998) Dissecting the regulatory circuitry of a eukaryotic genome. Cell 95: 717–728.FC HolstegeEG JenningsJJ WyrickTI LeeCJ Hengartner1998Dissecting the regulatory circuitry of a eukaryotic genome.Cell95717728
- 31. Carter MG, Sharov AA, VanBuren V, Dudekula DB, Carmack CE, et al. (2005) Transcript copy number estimation using a mouse whole-genome oligonucleotide microarray. Genome Biol 6: R61.MG CarterAA SharovV. VanBurenDB DudekulaCE Carmack2005Transcript copy number estimation using a mouse whole-genome oligonucleotide microarray.Genome Biol6R61
- 32. Panigrahi AK, Ogata Y, Zikova A, Anupama A, Dalley RA, et al. (2009) A comprehensive analysis of Trypanosoma brucei mitochondrial proteome. Proteomics 9: 434–450.AK PanigrahiY. OgataA. ZikovaA. AnupamaRA Dalley2009A comprehensive analysis of Trypanosoma brucei mitochondrial proteome.Proteomics9434450
- 33. Kondo T, Hashimoto Y, Kato K, Inagaki S, Hayashi S, et al. (2007) Small peptide regulators of actin-based cell morphogenesis encoded by a polycistronic mRNA. Nat Cell Biol 9: 660–665.T. KondoY. HashimotoK. KatoS. InagakiS. Hayashi2007Small peptide regulators of actin-based cell morphogenesis encoded by a polycistronic mRNA.Nat Cell Biol9660665
- 34. Galindo MI, Pueyo JI, Fouix S, Bishop SA, Couso JP (2007) Peptides encoded by short ORFs control development and define a new eukaryotic gene family. PLoS Biol 5: e106.MI GalindoJI PueyoS. FouixSA BishopJP Couso2007Peptides encoded by short ORFs control development and define a new eukaryotic gene family.PLoS Biol5e106
- 35. Thomas S, Green A, Sturm NR, Campbell DA, Myler PJ (2009) Histone acetylations mark origins of polycistronic transcription in Leishmania major. BMC Genomics 10: 152.S. ThomasA. GreenNR SturmDA CampbellPJ Myler2009Histone acetylations mark origins of polycistronic transcription in Leishmania major.BMC Genomics10152
- 36. Siegel TN, Hekstra DR, Kemp LE, Figueiredo LM, Lowell JE, et al. (2009) Four histone variants mark the boundaries of polycistronic transcription units in Trypanosoma brucei. Genes Dev 23: 1063–1076.TN SiegelDR HekstraLE KempLM FigueiredoJE Lowell2009Four histone variants mark the boundaries of polycistronic transcription units in Trypanosoma brucei.Genes Dev2310631076
- 37. Marchetti MA, Tschudi C, Silva E, Ullu E (1998) Physical and transcriptional analysis of the Trypanosoma brucei genome reveals a typical eukaryotic arrangement with close interspersionof RNA polymerase II- and III-transcribed genes. Nucleic Acids Res 26: 3591–3598.MA MarchettiC. TschudiE. SilvaE. Ullu1998Physical and transcriptional analysis of the Trypanosoma brucei genome reveals a typical eukaryotic arrangement with close interspersionof RNA polymerase II- and III-transcribed genes.Nucleic Acids Res2635913598
- 38. Carninci P, Sandelin A, Lenhard B, Katayama S, Shimokawa K, et al. (2006) Genome-wide analysis of mammalian promoter architecture and evolution. Nat Genet 38: 626–635.P. CarninciA. SandelinB. LenhardS. KatayamaK. Shimokawa2006Genome-wide analysis of mammalian promoter architecture and evolution.Nat Genet38626635
- 39. Seila AC, Calabrese JM, Levine SS, Yeo GW, Rahl PB, et al. (2008) Divergent transcription from active promoters. Science 322: 1849–1851.AC SeilaJM CalabreseSS LevineGW YeoPB Rahl2008Divergent transcription from active promoters.Science32218491851
- 40. Core LJ, Waterfall JJ, Lis JT (2008) Nascent RNA sequencing reveals widespread pausing and divergent initiation at human promoters. Science 322: 1845–1848.LJ CoreJJ WaterfallJT Lis2008Nascent RNA sequencing reveals widespread pausing and divergent initiation at human promoters.Science32218451848
- 41. Pauws E, van Kampen AH, van de Graaf SA, de Vijlder JJ, Ris-Stalpers C (2001) Heterogeneity in polyadenylation cleavage sites in mammalian mRNA sequences: implications for SAGE analysis. Nucleic Acids Res 29: 1690–1694.E. PauwsAH van KampenSA van de GraafJJ de VijlderC. Ris-Stalpers2001Heterogeneity in polyadenylation cleavage sites in mammalian mRNA sequences: implications for SAGE analysis.Nucleic Acids Res2916901694
- 42. Pickrell JK, Marioni JC, Pai AA, Degner JF, Engelhardt BE, et al. (2010) Understanding mechanisms underlying human gene expression variation with RNA sequencing. Nature 464: 768–772.JK PickrellJC MarioniAA PaiJF DegnerBE Engelhardt2010Understanding mechanisms underlying human gene expression variation with RNA sequencing.Nature464768772
- 43. Roy SW, Gilbert W (2006) The evolution of spliceosomal introns: patterns, puzzles and progress. Nat Rev Genet 7: 211–221.SW RoyW. Gilbert2006The evolution of spliceosomal introns: patterns, puzzles and progress.Nat Rev Genet7211221
- 44. Conti E, Izaurralde E (2005) Nonsense-mediated mRNA decay: molecular insights and mechanistic variations across species. Curr Opin Cell Biol 17: 316–325.E. ContiE. Izaurralde2005Nonsense-mediated mRNA decay: molecular insights and mechanistic variations across species.Curr Opin Cell Biol17316325
- 45. Kaern M, Elston TC, Blake WJ, Collins JJ (2005) Stochasticity in gene expression: from theories to phenotypes. Nat Rev Genet 6: 451–464.M. KaernTC ElstonWJ BlakeJJ Collins2005Stochasticity in gene expression: from theories to phenotypes.Nat Rev Genet6451464
- 46. Karlebach G, Shamir R (2008) Modelling and analysis of gene regulatory networks. Nat Rev Mol Cell Biol 9: 770–780.G. KarlebachR. Shamir2008Modelling and analysis of gene regulatory networks.Nat Rev Mol Cell Biol9770780
- 47. Larson DR, Singer RH, Zenklusen D (2009) A single molecule view of gene expression. Trends Cell Biol 19: 630–637.DR LarsonRH SingerD. Zenklusen2009A single molecule view of gene expression.Trends Cell Biol19630637
- 48. Hillier LW, Reinke V, Green P, Hirst M, Marra MA, et al. (2009) Massively parallel sequencing of the polyadenylated transcriptome of C. elegans. Genome Res 19: 657–666.LW HillierV. ReinkeP. GreenM. HirstMA Marra2009Massively parallel sequencing of the polyadenylated transcriptome of C. elegans.Genome Res19657666
- 49. Consortium CeS (1998) Genome sequence of the nematode C. elegans: a platform for investigating biology. Science 282: 2012–2018.Consortium CeS1998Genome sequence of the nematode C. elegans: a platform for investigating biology.Science28220122018
- 50. Langmead B, Trapnell C, Pop M, Salzberg SL (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10: R25.B. LangmeadC. TrapnellM. PopSL Salzberg2009Ultrafast and memory-efficient alignment of short DNA sequences to the human genome.Genome Biol10R25
- 51. Stein LD, Mungall C, Shu S, Caudy M, Mangone M, et al. (2002) The generic genome browser: a building block for a model organism system database. Genome Res 12: 1599–1610.LD SteinC. MungallS. ShuM. CaudyM. Mangone2002The generic genome browser: a building block for a model organism system database.Genome Res1215991610
- 52. Brown SD, Huang J, Van der Ploeg LH (1992) The promoter for the procyclic acidic repetitive protein (PARP) genes of Trypanosoma brucei shares features with RNA polymerase I promoters. Mol Cell Biol 12: 2644–2652.SD BrownJ. HuangLH Van der Ploeg1992The promoter for the procyclic acidic repetitive protein (PARP) genes of Trypanosoma brucei shares features with RNA polymerase I promoters.Mol Cell Biol1226442652
- 53. Pays E, Coquelet H, Tebabi P, Pays A, Jefferies D, et al. (1990) Trypanosoma brucei: constitutive activity of the VSG and procyclin gene promoters. EMBO J 9: 3145–3151.E. PaysH. CoqueletP. TebabiA. PaysD. Jefferies1990Trypanosoma brucei: constitutive activity of the VSG and procyclin gene promoters.EMBO J931453151
- 54. Bendtsen JD, Nielsen H, von Heijne G, Brunak S (2004) Improved prediction of signal peptides: SignalP 3.0. J Mol Biol 340: 783–795.JD BendtsenH. NielsenG. von HeijneS. Brunak2004Improved prediction of signal peptides: SignalP 3.0.J Mol Biol340783795