text:
- Research
- Open Access
Sense-antisense pairs in mammals: functional and evolutionary considerations
© Galante et al.; licensee BioMed Central Ltd. 2007
- Received: 3 May 2006
- Accepted: 19 March 2007
- Published: 19 March 2007
A significant number of genes in mammalian genomes are being found to have natural antisense transcripts (NATs). These sense-antisense (S-AS) pairs are believed to be involved in several cellular phenomena.
Here, we generated a catalog of S-AS pairs occurring in the human and mouse genomes by analyzing different sources of expressed sequences available in the public domain plus 122 massively parallel signature sequencing (MPSS) libraries from a variety of human and mouse tissues. Using this dataset of almost 20,000 S-AS pairs in both genomes we investigated, in a computational and experimental way, several putative roles that have been assigned to NATs, including gene expression regulation. Furthermore, these global analyses allowed us to better dissect and propose new roles for NATs. Surprisingly, we found that a significant fraction of NATs are artifacts produced by genomic priming during cDNA library construction.
We propose an evolutionary and functional model in which alternative polyadenylation and retroposition account for the origin of a significant number of functional S-AS pairs in mammalian genomes.
- Additional Data File
- Antisense Transcript
- Massively Parallel Signature Sequencing
- Chimeric Transcript
- Antisense Gene
Natural antisense RNAs (or natural antisense transcripts (NATs)) are endogenous transcripts with sequence complementarity to other transcripts. There are two types of NATs in eukaryotic genomes: cis-encoded antisense NATs, which are transcribed from the opposite strand of the same genomic locus as the sense RNA and have a long (or perfect) overlap with the sense transcripts; and trans-encoded antisense NATs, which are transcribed from a different genomic locus of the sense RNA and have a short (or imperfect) overlap with the sense transcripts. Cis-NATs are usually related in a one-to-one fashion to the sense transcript, whereas a single trans-NAT may target several sense transcripts [1–3]. In this manuscript, we describe analyses in which only cis-NATs were considered. From now on, we refer to these loci as sense-antisense (S-AS) pairs.
When evaluated globally, several features related to the distribution of NATs strongly suggest they have a prominent role in antisense regulation in gene expression [4–7]. For instance, expression of S-AS transcripts tends to be positively or negatively correlated and is more evolutionarily conserved than expected by chance [4, 5, 7]. Although experimental validation of a putative regulatory role has been achieved for a few models [8–10], it is still unknown whether antisense regulation is a rule or an exception in the human genome. NATs have been implicated in RNA and translational interference [11], genomic imprinting [12], transcriptional interference [13], X-inactivation [14], alternative splicing [10, 15] and RNA editing [16]. Moreover, an accumulating body of evidence suggests that NATs might have a pivotal role in a range of human diseases [2].
NATs were initially identified in studies looking at individual genes. However, with the accumulation of whole genome and expressed sequences (mRNA and ESTs) in public databases, a significant number of NATs has been identified using computational analysis [17–22]. These studies showed a widespread occurrence of these transcripts in mammalian genomes. The first evidence that antisense transcription is a common feature of mammalian genomes came from analysis of reverse complementarity between all available mRNA sequences [17]. Subsequent studies, using larger collections of mRNA sequences, ESTs and genomic sequences, confirmed and extended these initial observations [18–22]. More recently, other sources of expression data, such as serial analysis of gene expression (SAGE) tags, were used to expand the catalog of NATs present in mammalian genomes [23, 24]. At present, it is estimated that at least 15% and 20% of mouse and human transcripts, respectively, might form S-AS pairs [18, 22], although a recent analysis [25] reported that 47% of human transcriptional units are involved in S-AS pairing (24.7% and 22.7% corresponding to S-AS pairs with exon and non-exon overlapping, respectively).
The major obstacle in using expressed sequence data for NAT identification is how to determine the correct orientation of the sequences, especially ESTs. Many ESTs were not directionally cloned and even well-known mRNA sequences were registered from both strands of cloned cDNAs or are incorrectly annotated. As done by others [18, 22, 23], we here established a set of stringent criteria, including the orientation of splicing sites, the presence of poly-A signal and tail as well as sequence annotation, to determine the correct orientation of each transcript relative to the genomic sequence and made a deep survey of NAT distribution in the human and mouse genomes. Using a set of computational and experimental procedures, we extensively explored expressed sequences and massively parallel signature sequencing (MPSS) data mapped onto the human and mouse genomes. Besides generating a catalog of known and new S-AS pairs, our analyses shed some light on functional and evolutionary aspects of S-AS pairs in mammalian genomes.
Results and discussion
Overall distribution of S-AS pairs in human and mouse genomes
To identify transcripts that derive from opposite strands of the same locus, we used a modified version of an in-house knowledgebase previously described for humans [26–28]. This knowledgebase contains more than 6 million expressed sequences mapped onto the human genome sequence and clustered in approximately 111,000 groups. Furthermore, SAGE [29] and MPSS [30] tags were also annotated with all associated information, such as tag frequency, library source and tag-to-gene-assignment (using a strategy developed by us for SAGE Genie [31]). An equivalent knowledgebase was built for the mouse genome (for more details see Materials and methods).
Overall distribution of S-AS pairs in the human and mouse genomes
cDNA type
Single bidirectional transcription
Multiple bidirectional transcription
The above numbers confirm that S-AS pairs are much more frequent in mammalian genomes than originally estimated [4, 17, 18]. Our analyses suggest that at least 21,000 human and 16,000 mouse genes are involved in S-AS pairing. These numbers are more in agreement with those from [32] in their analysis using tiling microarrays to evaluate gene expression of a fraction of the human genome. For the mouse genome, our numbers are in agreement with those reported by Katayama et al. [8]. A more recent analysis [25] also gives a similar estimate of S-AS pairs in both human and mouse genomes.
Could this high number of S-AS pairs be due to the stringency of our clustering strategy? If the same transcriptional unit is fragmented in close contigs due to 3' untranslated region (UTR) heterogeneity, the total number of clusters would be inflated, leading to an erroneous count of S-AS pairs. To evaluate this possibility, we relaxed our clustering parameters, requiring a minimum of 1 base-pair (bp) same strand overlap for clustering. Furthermore, we collapsed into a single cluster all pairs of clusters located in the same strand and less than 30 bp away from each other. Additional data file 3 shows the total number of clusters and S-AS pairs after this new clustering strategy was employed. As expected, both the total number of clusters and S-AS pairs decreased with the new clustering methodology. The total number of clusters decreased by 2% and 1% for human and mouse, respectively, while the total number of S-AS pairs decreased by 0.3% for both human and mouse. Thus, the small difference observed does not affect the conclusions on the genomic organization of S-AS pairs. For all further analyses, we decided to use the original dataset obtained with a more stringent clustering methodology.
Distribution of NATs in relation to the genomic structure of the sense transcript
Fully exonic
112 (20%)
32 (3%)
213 (40%)
156 (27%)
14 (2%)
227 (45%)
362 (64%)
372 (37%)
259 (48%)
360 (62%)
338 (42%)
242 (48%)
Fully intronic
92 (16%)
606 (60%)
61 (12%)
61 (11%)
448 (56%)
33 (7%)
Classification of S-AS pairs in reference to their orientation and the presence of introns at the genome level for both genes in a pair
NAT pair
Both with intron
342 (61%)
351 (35%)
417 (78%)
259 (45%)
394 (49%)
390 (78%)
206 (36%)
645 (64%)
103 (19%)
285 (49%)
398 (50%)
96 (19%)
Both intronless
18 (3%)
14 (1%)
13 (3%)
33 (6%)
8 (1%)
16 (3%)
All these results clearly show that subsets of S-AS pairs have distinct genomic organization, suggesting that they may play different biological roles in mammalian genomes. Below we will discuss these data in a functional/evolutionary context.
Conservation of S-AS pairs between human and mouse
Using our set of human and mouse S-AS pairs, we measured the degree of conservation between S-AS pairs from human and mouse. Since the numbers reported so far are discrepant, ranging from a few hundred [5, 6] to almost a thousand [25], we decided to use different strategies. We first used a strategy based on HomoloGene [35]. The number of S-AS pairs with both genes mapped to HomoloGene is 854 for human and 579 for mouse. Among these, 190 S-AS pairs are conserved between human and mouse. One problem with this type of analysis lies in its dependence on HomoloGene, which, for example, does not take into consideration genes that do not code for proteins. Therefore, we decided to implement a different strategy, in which we identified those pairs that had at least one conserved gene mapped by HomoloGene and tested each known gene's NAT for sequence level conservation. Using this strategy, we found an additional 546 cases, giving a total of 736 (190 + 546) conserved S-AS pairs between human and mouse. Finally, we also applied to our dataset the same strategy used by Engstrom et al. [25], in which they counted the number of human and mouse S-AS pairs that had exon overlap in corresponding positions in a BLASTZ alignment of the two genomes. We applied the same strategy to our dataset and found 1,136 and 1,144 corresponding S-AS pairs in human and mouse, respectively. As observed by Engstrom et al. [25] the numbers from human and mouse slightly differ because a small proportion of mouse pairs corresponded to several human pairs and vice versa. Additional data file 5 lists all S-AS pairs found by the three methodologies discussed above.
There is a predominance of 3'3' pairs in all sets of conserved S-AS pairs. For the first strategy solely based on HomoloGene, 67% of all pairs are 3'3' compared to 19% embedded and 14% 5'5'. For the dataset obtained using the strategy from Engstrom et al. [25], there is also a prevalence of 3'3'pairs (48%) compared to embedded (14%) and 5'5 (38%) pairs. We have also modified the method of Engstrom et al. [25] to take into account all S-AS pairs and not only those presenting exon-exon overlap. These data are shown in Additional Data File 6. We observed that S-AS pairs whose overlap is classified as 'Fully intronic' are less represented in the set of conserved S-AS pairs (18% in this set compared to 29% in the whole dataset of S-AS pairs). The same is true for S-AS pairs containing at least one intronless gene (26% in the set of conserved S-AS pairs compared to 47% in the whole dataset). These last results are in accordance with our previous observation that conserved S-AS pairs are enriched with 3'3' pairs. As seen in Tables 2 and 3, 3'3' pairs are poorly represented in the categories 'Fully intronic' (Table 2) and 'Intron/intronless' (Table 3).
Discovery of new S-AS pairs in human and mouse genomes using MPSS data
Large-scale expression profiling tools have been used to discover and analyze the co-expression of S-AS pairs [5, 23, 34]. Quéré et al. [23], for instance, recently explored the SAGE repositories to detect NATs. These authors searched for tags mapped on the reverse complement of known transcripts and analyzed their expression pattern on different SAGE libraries. However, no attempt was made to experimentally validate the existence of such NATs. Here, we made use of MPSS data available in public repositories [36, 37] to search for new NATs in both human and mouse genomes. Since MPSS tags are longer than conventional SAGE tags, we can use the genome sequence for tag mapping. Furthermore, MPSS offers a much deeper coverage of the transcriptome since at least a million tags are generated from each sample.
We made use of 122 MPSS libraries derived from a variety of human and mouse tissues (81 libraries for mouse, 41 for human; see the list in Additional data file 7). Our strategy was based on the generation of virtual tags from each genome by simply searching the respective genome sequence for DpnII sites. Since these sites are palindromes, we extract, for each one, two virtual tags (13 and 16 nucleotide long tags for human and mouse, respectively), both immediately downstream of the restriction site but in opposite orientations (see Materials and methods for more details). In this way, we could evaluate the expression of transcriptional units present in both strands of DNA. We obtained 5,580,158 and 8,645,994 virtual tags for the human and mouse genomes, respectively. This set of virtual tags was then compared to a list of tags observed in the MPSS libraries. As true for any study using mapped tags, our analysis misses those cases in which a tag maps exactly at an exon/exon border at the cDNA level.
We first evaluated the number of cDNA-based S-AS pairs (shown in Table 1) that were further confirmed by the presence of an MPSS tag. Data for this analysis are presented as Additional data file 8. Roughly, 84% and 51% of all cDNA-based S-AS pairs were confirmed by MPSS data for human and mouse, respectively.
Distribution of MPSS tags in an antisense orientation in human and mouse genomes
Number of clusters
One exonic tag
2,212 (51.3%)
124 (57.3%)
One intronic tag
875 (20.3%)
90 (41.7%)
Exonic and intronic tag
707 (16.4%)
2 (1%)
Multiple exonic tags
318 (7.4%)
Multiple intronic tags
196 (4.6%)
Among the 49.5% (91 - 46 = 45) of candidates that were not considered to be validated, we found 25 that were amplified in the GLGI-MPSS experiment but whose exon-intron organization was identical to the sense gene. Although antisense sequences like these have already been observed [39], we did not consider them as validated antisense transcripts. Orientation-specific RT-PCR confirmed the existence of one transcript, out of two that were tested.
Alternative polyadenylation as a major factor in defining S-AS pairs
Dahary et al. [6] observed that S-AS overlap usually involves transcripts generated by alternative polyadenylation. This observation had already been reported by us and others [40]. We decided to test if these preliminary observations would survive a more quantitative analysis. We found that the S-AS overlap is predominantly due to alternative polyadenylation variants. Roughly, 51% of all S-AS pairs (274 out of 533 3'3' pairs) overlap due to the existence of at least one variant. This number is certainly underestimated since many variants are still not represented in the sequence databases. The above observation raises the exciting possibility that antisense regulation is associated with the regulation of alternative polyadenylation. It is expected that the presence of overlapping genes imposes constraints on their evolution since any mutation will be evaluated by natural selection according to its effect in both genes. Thus, in principle, overlapping genes should impose a negative effect on the fitness of a subject. Alternative polyadenylation has the potential to relax such negative selection since the overlapping is dependent on a post-transcriptional modification.
If alternative polyadenylation is a significant factor in defining S-AS pairs, we would expect a lower rate of alternative polyadenylation in chromosome X, which has the smallest density of S-AS pairs. Indeed, only 20% of all messages from the X chromosome show at least two polyadenylation variants, compared to 27.5%, on average, for the autosomes (chi-square = 34.91, df = 1, p < 0.0001).
A fraction of S-AS pairs is generated through internal priming and retroposition events
During the validation of new NATs identified using the MPSS data, we noticed that a significant fraction of GLGI amplicons (19 out of 46 validated fragments) had their 3' ends aligning to stretches of As in the human genome. This motivated us to search for similar cases in the set of cDNA-based S-AS pairs identified in this study. We found that 18% and 26% of all S-AS pairs have at least one gene with its 3' end aligning with a stretch of A's in the human and mouse genomes, respectively. This number is certainly inflated by ESTs since it decreases to 11.7% for human and 12.6% for mouse when only mRNA/mRNA S-AS pairs are considered. Two possibilities could account for this observation. First, a fraction of all antisense transcripts would be artifacts due to genomic priming with contaminant genomic DNA during cDNA library construction. An alternative is the possibility that antisense genes were constructed during evolution by retroposition events. Both possibilities are in agreement with the observation that antisense genes are depleted of introns.
Some other features support the artifactual origin of these antisense transcripts. First, cDNAs containing a stretch of As at their 3' genomic end have much less polyadenylation signals than genes in general (17% compared to 85%). Furthermore, these genes have a much narrower and rarer expression pattern when analyzed by SAGE and MPSS than genes in general (data not shown). These observations suggest that a significant fraction of all antisense genes are actually artifacts, due to genomic priming during library construction.
Retroposition generates intronless copies of existing genes through reverse transcription of mature mRNAs followed by integration of the resulting cDNA into the genome (for a review, see Long et al. [41]). Eventually, the cDNA copy can be involved in homologous recombination with the original source gene as has been suggested for yeast [42]. Retroposition was thought to generate non-functional copies of functional genes. However, several groups have shown that retroposition has generated a significant amount of new functional genes in several species [43–45]. Recently, Marques et al. [43] found almost 4,000 retrocopies of functional genes in the human genome. More recently, the same group reported that more than 1,000 of these retrocopies are transcribed, of which at least 120 have evolved as bona fide genes [46].
Retrocopies usually have a poly-A tail at their 3' end because of the insertion of this post-transcriptional modification together with the remaining cDNA. Thus, retroposition can explain the high incidence of antisense transcripts with a poly-A tail at their 3' end. To evaluate the contribution of retrocopies to the formation of S-AS pairs we compared the loci identified by Marques et al. [43] as retrocopies with the list of S-AS pairs identified in this study. Out of 413 retrocopies represented in the cDNA databases, 138 were involved in S-AS pairs (70 mRNA/mRNA and 68 mRNA/EST pairs). For the 70 mRNA/mRNA pairs, 78% were classified as embedded. This is in agreement with our previous observation that embedded pairs are enriched with intronless genes. Thus, retroposition seems to significantly contribute to the origin of embedded S-AS pairs.
Expression patterns within S-AS pairs
A critical issue to effectively evaluate the role of antisense transcripts in regulating distinct cellular phenomena is related to the expression pattern of both sense and antisense transcripts belonging to the same S-AS pair. Several reports have been published based on large-scale gene-expression analyses [5, 19, 23, 47, 48]. Similar to Wang et al. [48], we here used MPSS libraries available for human to explore this issue. Tag to gene assignment was performed as previously described [31, 49]. To ensure the MPSS sequences were unambiguously matched to the assigned transcript, we removed tags mapped to more than one locus. Frequencies for all tags assigned to genes in an S-AS pair were collected from all MPSS libraries.
Influence of antisense transcripts in the splicing of sense transcripts
It is quite clear nowadays that a significant fraction of all human genes undergo regulated alternative splicing, producing more than one mature mRNA from a gene (Galante et al. [27] and references therein). Although several regulatory elements in cis and trans have been identified (for a review see Pagani and Baralle [50]), it is reasonable to say that we are far from a complete understanding of how constitutive and alternative splicing are regulated. One possible regulatory mechanism involves antisense sequences. Since the late 1980s, it is known that antisense RNA can inhibit splicing of a pre-mRNA in vitro [15]. A few years later, Munroe and Lazar [51] observed that NATs could inhibit the splicing of a message derived from the other DNA strand, more specifically the ErbAα gene. More recently, Yan et al. [52] characterized a new human gene, called SAF, which is transcribed from the opposite strand of the FAS gene. Over-expression of SAF altered the splicing pattern of FAS in a regulated way, suggesting that SAF controls the splicing of FAS. With the growing amount of genomic loci presenting both sense and antisense transcripts, a general role for S-AS pairing in splicing regulation has been proposed [47]. However, no systematic large-scale analysis has been reported so far investigating this issue for mammals. We made use of the human dataset described in this report to tackle this problem.
Frequency of different types of alternative splicing in exon-intron borders with or without an antisense transcript
Alternative borders
Intron retention
Exon skipping
Alternative 3'/5' site
Borders with antisense
Terminal donor
Internal donor
Terminal acceptor
Internal acceptor
Borders without antisense
Terminal donor
Internal donor
Terminal acceptor
Internal acceptor
Recently, Wiemann et al. [53] reported a new variant of IL4L1 that contains the first two exons of an upstream gene, NUP62. This chimeric transcript was expressed in a tissue and cell-specific manner. The authors speculated that cell type specific alternative splicing was involved in the generation of this chimeric transcript. We speculate that NATs could be involved in the generation of this type of chimeric cDNA. The same antisense message pairing with both sense messages would form a double-stranded RNA that could induce the spliceosome to skip the paired region and join the two sense messages, a process very similar to the one proposed for trans-splicing in mammals [54]. Interestingly, we found five examples in our dataset of S-AS pairs in which the genomic organization of both sense and antisense genes suggest a process like this. Additional data file 9 illustrates one of these cases. It can be seen that two transcripts represented by cDNAs AK095876 and AK000438 join messages from genes SERF2 and HYPK. The antisense transcript is represented by cDNA AK097682. Additional data file 10 lists all other putative cases of chimeric transcripts. The fact that both sense genes share a common antisense transcript raises the possibility that antisense transcripts can mediate trans-splicing of the sense genes, thereby generating the chimeric transcript.
On the evolution of S-AS pairs: functional implications
It is reasonable to assume that a fraction of all S-AS pairs reached this genome organization solely by chance. However, evidence presented here and elsewhere suggest that this fraction is probably small [6, 55, 56]. For example, Dahary et al. [6] concluded that antisense transcription had a significant effect on vertebrate genome evolution since the genomic organization of S-AS pairs is much more conserved than the organization of genes in general. However, how did this organization come to be? In principle, S-AS genomic organization should carry a negative effect on the overall fitness of a subject. For each gene in an S-AS pair, its evolution is constrained not only by features of its own sequence but also by functional features encoded by the other gene in the pair. The fact that we observed a significant amount of S-AS pairs in mammalian genomes suggests that there are advantages inherent to this organization to counter-balance the negative effects. The proposed role of NATs in gene regulation is certainly advantageous. We propose here two evolutionary scenarios, not mutually exclusive, that would speed up the generation of S-AS pairs. In one scenario, alternative polyadenylation has a fundamental role. Sun et al. [5] observed a preferential targeting of 3' UTRs for NATs. Our observation that 51% of 3'3' S-AS pairs overlap because of polyadenylation variants suggests that selection has favored cases where overlapping occurs only in a time and spatially regulated manner.
In a second scenario, retroposition generates NATs, which lack introns and may even show a polyadenylation tail integrated into the genome. We observe here that retroposition contributed significantly to the origin of S-AS pairs, especially those classified as embedded. What would be the selective advantages of retrocopies as NATs? Chen et al. [56] observed that antisense genes have shorter introns when compared to genes in general. They speculated that this feature was advantageous during evolution since NATs need to be "rapid responsers" to execute their regulatory activities. Although transcription is a slow process in eukaryotes, another bottleneck in the expression of a gene is splicing. Furthermore, Nott et al. [57] observed that the presence of introns in a gene affects gene expression by enhancing mRNA accumulation. Thus, the argument from Chen et al. [56] gets stronger with the data reported here and by Nott et al. [57] since intronless antisense genes would be transcribed even faster; their transcripts would simply skip splicing and the half-life of the respective messages would be shorter. All key features for genes involved in regulatory activities.
An important issue is the conservation of S-AS pairs between human and mouse. Although we found more than a thousand conserved pairs, this number is still small compared to the whole set of S-AS pairs in both species. Several factors, however, suggest that the number reported here is an underestimate. First, as discussed by Engstrom et al. [25], sequence conservation might not be of primary importance for antisense regulation. Furthermore, it is likely that many truly conserved pairs were not detected because transcript sequences have not been discovered yet. This is more critical in the face of our findings that a significant proportion of 3'3' S-AS pairs depend on alternative polyadenylation for an overlap. It is also quite likely that some S-AS pairs are lineage-specific. For instance, our finding that retroposition contributes to the origin of many S-AS pairs could explain the appearance of lineage-specific S-AS pairs, assuming that the retroposition event occurred after the divergence between human and mouse.
These two evolutionary scenarios (alternative polyadenylation and retroposition) might produce S-AS pairs with different functional implications. The expression and evolutionary conservation analyses presented here, together with evidence from others [5, 19, 23, 47, 48] suggest that 3'3' overlap achieved by polyadenylation variants was used throughout evolution to regulate gene expression. Those pairs generated through retroposition may be involved in some other types of regulation, such as alternative splicing.
This is the deepest survey so far of S-AS pairs in the human and mouse genomes. We made use of all cDNAs available in the public domain together with 122 MPSS libraries for human and mouse. The major findings of the present report include: as many as 10,077 and 8,091 S-AS pairs were identified for human and mouse respectively; using MPSS data, we found 4,308 and 216 new putative S-AS loci in human and mouse, respectively; a small fraction of all S-AS pairs are artifacts caused by genomic priming during cDNA library construction; a significant amount of S-AS pairs is due to retroposition events of one of the genes in the pair; quantitative analyses suggest that the presence of an antisense gene, complementary to an exon-intron border of the sense gene, increases the rate of retention of the respective intron. Furthermore, we propose an evolutionary model in which alternative polyadenylation and retroposition are important forces in the generation of S-AS pairs.
Taken together, these results offer, up to now, the vastest catalog of S-AS pairs in human and mouse genomes.
Materials and methods
Mapping cDNAs and MPSS tags onto the human and mouse genomes
We used a modified protocol similar to the one described previously to identify transcription clusters in the human and mouse genomes [27, 28]. Briefly, genome sequence (NCBI build no. 35 for human and NCBI build no. 33 for mouse), EST collections (5,992,459 sequences for human and 4,246,824 sequences for mouse) and mRNA sequences (186,358 for human and 120,058 for mouse) were downloaded from UCSC [58]. All cDNAs were mapped to the respective genome sequence using BLAT (default parameters) [59]. The best hit for each cDNA in the genome was identified, followed by a pairwise alignment using Sim4 [60]. Only transcripts presenting identity ≥94%, coverage ≥50% and all splice sites in the same orientations were used.
Correct orientation of ESTs was determined by the presence of a poly-A tail (a stretch of 8 As at the 3' end) and/or a splicing donor (GT) and acceptor (AG) sites. All mRNAs were considered in the 'sense' orientation (oriented from 5' end to 3' end). All cDNAs mapped and reliably orientated were assembled into clusters. One cluster contains cDNAs presenting the same orientation and sharing at least one exon-intron boundary or a minimum of 30 nucleotides of overlap (only for those sequences without a common exon/intron organization).
For the mapping of MPSS data, we first extracted 'virtual' tags for both human and mouse genomes by simply finding all DpnII sites and extracting a 13 (human) or 16 (mouse) nucleotide long sequence immediately downstream of the restriction site in both orientations. These 'virtual' tags present only once in the respective genomes were further used and matched against the 'real' tags found in 41 and 81 MPSS libraries for human and mouse, respectively. Only MPSS tags classified as 'reliable' (present in more than one sequencing run) and 'significant' (tags per million >3) were considered as trusted signatures.
Identification of S-AS pairs
S-AS pairs were identified as those cases in which two clusters, in opposite orientations, overlap at the genome level. For the correct orientation of all mapped cDNAs, we took into consideration several parameters, including: sequence annotation as available in the respective GenBank entry; splice junctions; and poly-A tails and poly-T heads. We excluded from our analyses all cDNAs that presented conflicting orientations as defined by the three criteria above. If only two clusters overlap in the opposite orientation, they were classified as a single bidirectional S-AS pair. If a given cluster overlaps with more than one antisense cluster, they were classified as multiple bidirectional S-AS pairs. S-AS pairs were also classified according to their genomic pattern. Parameters evaluated included: pattern of S-AS overlap (exonic, intronic and exonic/intronic); spanning of introns by the components of a pair as defined by their alignment onto the genome; and chromosome localization and relative orientation within the S-AS pairs (tail-tail, head-head and embedded).
Conservation between human and mouse S-AS pairs
We used three strategies to evaluate the degree of conservation between human and mouse S-AS pairs. First, all pairs were searched against the dataset from HomoloGene [35] and those pairs conserved in both species were counted. In our second strategy, we selected those S-AS pairs in which at least one gene was conserved according to HomoloGene. We then used Needle, an alignment algorithm [61], to test sequence conservation between the respective antisense genes. We classified as conserved those global alignments with identity >30%. Finally, we also used the strategy from Engstrom et al. [25]. We used the net alignment between human and mouse genomes (retrieved from the UCSC Genome Browser database) to define the corresponding (synthenic) regions. We considered a human S-AS pair to be conserved in mouse if it had an exon region aligning (>20 bp) to an exon region from a mouse pair.
Investigation of the expression pattern of S-AS transcripts
We evaluated the expression pattern of S-AS pairs at the whole genome level based on their expression profiles obtained from MPSS libraries (available at [36]). The procedure was previously described by us for SAGE and MPSS [27, 31, 49]. The tag to gene assignment was done by scanning and extracting virtual tags (13 nucleotide-long sequences present downstream to the 3'-most DpnII restriction sites of each mRNA sequence). To accurately represent the 3' end of a transcript, only mRNA sequences containing a poly-A tail were used. All tags mapped to two or more different genes were excluded and the frequencies of different tags for the same gene (mainly alternative polyadenylation variants) were summed. MPSS tags were normalized to counts-per-million and the expression data were cross-linked to genomic positions by the extraction of virtual tags for both the human and mouse genomes. Only tags showing 100% identity with a genomic locus were used in the analyses.
The classification of the expression pattern of S-AS pairs was done using those tags with ≥3 tags per million across all MPSS libraries. To evaluate the co-expression of all S-AS pairs, both genes in a pair had to be co-expressed in at least 04 libraries. If both genes in a pair were co-expressed in less than four libraries or they were independently expressed in different libraries, the pair was classified as 'single-gene expression'. The remaining S-AS pairs were classified as 'no-expression'.
Identification of antisense MPSS tags
All DpnII sites in the human and mouse genomes were identified and for each site two 'virtual' MPSS tags were extracted from both DNA strands in the correct orientation. All 'virtual' MPSS tags mapped in the opposite strand of known mRNAs in both genomes were identified. Those mRNAs belonging to an S-AS pair previously identified were excluded. Those antisense MPSS tags mapped just once in the respective genome and present in at least one MPSS library were identified and submitted to experimental validation.
Simulations on the genomic organization of S-AS pairs
A random distribution of S-AS pairs was obtained by re-indexing the coordinates of one gene in all the pairs 1,000 times. This was done by randomly selecting a genomic coordinate for the start of mapping of a given gene. All the remaining exon-intron borders were then re-indexed based on this initial coordinate. The relative organization of both genes in all random S-AS pairs was stored and frequencies for each category were calculated. Those frequencies were used as the expectation for chi-square tests of the null hypothesis.
Identification of splicing variants
Using the database mentioned earlier and described elsewhere [26–28] we identified all exon-intron borders complementary to a NAT. We then compared the rate of alternative splicing in these borders against the borders from the same genes without a NAT. We established a set of stringent criteria to identify alternative borders. These criteria are detailed elsewhere [26–28].
Experimental validation of MPSS antisense tags
MPSS tags corresponding to antisense transcripts were converted into their corresponding 3' cDNA fragments using GLGI-MPSS [37]. Antisense tags were selected from a MPSS library derived from the normal breast luminal epithelial cell line HB4a and the same RNA source was used for GLGI amplification. For the GLGI-MPSS amplification, we used a sense primer including 17 bases of the MPSS tag sequence and 6 additional bases (CAGGGA), giving a total of 23 bases for each primer (5'-CAGGGAGATCXXXXXXXXXXXXX-3'). We also used an antisense primer (ACTATCTAGAGCGGCCGCTT) present in the 3' end of all cDNA molecules that was incorporated from reverse transcription primers in cDNA synthesis. The reaction mixture was prepared in a final volume of 30 μl, including 1× PCR buffer, 2.0 mM MgCl2, 83 μM dNTPs, 2.3 ng/μl antisense primer, 2.3 ng/μl sense primer, 1.5 U of Taq Platinum DNA polymerase (Invitrogen, San Diego, CA, USA) and 0.5-0.8 μl of the same cDNA source used for MPSS library construction. PCR conditions used for amplification were 94°C for 2 minutes, followed by 30 cycles at 94°C for 30 s, 64°C for 30 s, and 72°C for 35 s. Reactions were kept at 72°C for 5 minutes after the last cycle. The amplified products were ethanol precipitated and cloned into the pGEM®-T Easy vector (Promega, Madison, WI, USA). Twelve colonies for each GLGI-MPSS fragment were screened by PCR using pGEM universal primers and positive colonies were sequenced using Big-Dye Terminator (Applied Biosystems, Foster City, CA, USA) and an ABI3100 sequencer (Applied Biosystems).
Experimental validation of genomic primed sequences
Total RNA derived from fetal liver, colon and lung was purchased from Clontech laboratories (Palo Alto, CA, USA). For cDNA synthesis, 2 μg of total RNA were treated (or not) with 100 units of DNAse I (FPLC-pure, Amersham, Piscataway, NJ, USA) and were reverse transcribed using oligo(dT)12-18, random primers and SuperScript II (Invitrogen), following the manufacturers' instructions. After synthesis, the resulting cDNA was subjected to RNase H treatment. The absence of genomic DNA contamination was evaluated for each preparation. DNA-free total RNA was subjected to PCR amplification using primers within intronic sequences flanking exon 12 of the hMLH-1 gene (forward, 5' TGGTGTCTCTAGTTCTGG3'; reverse 5' CATTGTTGTAGTAGCTCTGC 3'). All PCR amplifications were carried out using 2 μl of cDNA as a template to the final volume of 25 μl and 1× buffer, 1.5 mM MgCl2, 0.2 mM dNTP, 0.2 μM of each specific primer and 0.025 U/μl of Taq DNA polymerase (Life Technologies, San Diego, CA, USA). The following cycling protocol was used: initial denaturation of 94°C for 4 minutes; 94°C for 30 s; 55°C for 45 s; 72°C for 1 minute for 35 cycles; along with a final extension at 72°C for 7 minutes. All PCR products were resolved on 8% polyacrylamide gels and sequenced as described above to verify amplification specificity.
Strand-specific RT-PCR
In the strand-specific RT-PCR, orientation of the transcript is accessed by restricting which gene-specific primer is present during first-strand cDNA synthesis. For each candidate, 1 μg of total RNA was treated with Promega RQ1 RNAse-free DNAse and tested for remaining DNA contamination as described above. First-strand cDNA synthesis was carried out at 50°C for 2 h using 200 U of SuperScript II (Invitrogen) and 0.9 μM of a primer complementary to the antisense transcript. PCR amplifications were performed using 1 μl of the first-strand cDNA as a template in a final volume of 25 μl and 1× buffer, 1.5 mM MgCl2, 0.1 mM dNTP, 0.4 μM of gene specific primers and 1 U of Platinum Taq DNA polymerase (Invitrogen). The following cycling conditions were used for amplification: initial denaturation of 95°C for 2 minutes; 94°C for 40 s; reaction-specific annealing temperature for 40 s and 72°C for 1 minute for 35 cycles; followed by a final extension step at 72°C for 7 minutes. All PCR products were resolved on 8% polyacrylamide gels. Controls for the absence of self-priming during cDNA synthesis were done with reverse transcriptase in the absence of primers, and controls for the absence of DNA were done by incubation with primers but with no reverse transcriptase.
To make our dataset fully accessible to the community we have set up a worldwide web portal [62] containing all raw data generated in this study and a series of tools to explore the data.
Additional data files
The following additional data are available with the online version of this paper. Additional data file 1 is a list of representative GenBank entries for all S-AS pairs in both human and mouse. Additional data file 2 is a table showing the total number of S-AS pairs by chromosome for both human and mouse. Additional data file 3 shows the number of clusters and S-AS pairs when a less stringent clustering methodology is applied. Additional data file 4 shows a schematic view of all possible genomic organizations of S-AS pairs. Additional data file 5 lists all S-AS pairs conserved between human and mouse using the three strategies described in the text. Additional data file 6 shows the fraction of S-AS pairs conserved between human and mouse that are classified as 'Fully intronic' and the fraction of conserved S-AS pairs that contain at least one intronless gene. Additional data file 7 is a list of all MPSS libraries used in this study. Additional data file 8 presents the number of cDNA-based pairs that were further confirmed by the MPSS data. Additional data file 9 is a figure illustrating chimeric transcripts joining two adjacent genes (SERF2 and HYPK) with a NAT located between them. Additional file 10 lists all cases of chimeric transcripts identified in our dataset.
We would like to thank Artur Ramos de Souza for the design and maintenance of the web portal. We also thank Henrik Kaessmann for making available the data on human retrocopies. We are also indebt to Andrew Simpson for a critical review of the manuscript and to three anonymous reviewers for critical and constructive comments/suggestions.
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This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


text:
See the world through a new lens.
Now in its fifty-fourth year, Wildlife Photographer of the Year showcases extraordinary animal behaviour and the breathtaking diversity of life on Earth.
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subset: commoncrawl


text:
I know that the bash site has had numerous hot of spam. We are working on fixing the issue. I also know there hasn't been much traffic on the site either. I want to find out how many are left. Lets do a roll call and see how many people are out there to see how we will proceed. We are going to start posting daily.
I am still here and check in almost daily. Since my sedan is finished, (almost, still need interior) I don't have much to post about. Maybe I need to get a 34 coupe body, and start over.
Yeah Lee you need to get a '34 and start over!!! :)
We will make you a deal on the body and frame!!!
I check out the form all the time. I would hate to see it go
So far two people have responded and only 15 views so far.
I still follow the threads, but there hasn't been much activity. And a lot of spam! I'm having a load of fun with my recently finished T! I've been to the Lonestar and Nashville Goodguys events, and several local shows and cruise ins. I'm ready to build another one!
I come here daily to see what's new. The best suggestion would be to resubmit some of the old videos of how to and the way Bob does his work in the shop and keeping fresh ideas in his business plans
The best video I saw was when he had a fresh mold being prepped for a new run of bodies, which showed people how expensive and labor intensive it is to build fiberglass bodies. And another of installing the back door on a C-Cab. Fiberglass work isn't easy or cheap, no matter how you do it.
Articles like these give people a start on believing they can build a bucket at a cost that is reasonable with the amount of talent/money they have.
Facebook may be the trend right now, but a lot of the people who are capable to build a T-Bucket just don't use it to find out what they need. Computers are hard enough for them. So if they don't find what they are looking for on line, they use the phone or give up and do something else. Just my .02 worth and I hope more people will keep looking for these little cars to get into the hot rod world.
Yes we are planning on doing videos again. So far less than 40 people have viewed this post and only 4 people have commented on it.
As soon as I can get a hot rod or 2 sold and out of the way, I do want to start on a 34 coupe. Room is my problem now. With 7 cars that need kept inside, I ran out of room.
The videos were helpful, especially when needing some information on a subject that you may have not had a answer for.
I know when I was build the Honky line of trailers, the molds were the big expense, and the most time consuming. If for instance you had 10k in a mold, the first body out cost that much plus material and time. Lots of money for a 800 dollar body. Good thing is, you cut that in half every time you sell one.
I check the forum at least twice a week. I haven't started my thread on my build
yet, but I will soon. Iven
Iven can't wait to see your build.
Always good to watch the progress of a new build.
Each day I look to see if there is anything new. I always want to learn more about Spirit Cars.
im here too-- still building mine - if I didn't have the forum - wouldn't even have gotten this far! I check it daily. --------goufos
I had to stop coming after all the spam it took a little while to clean out my laptop. I still want to do a 23 T
Even though I've finished and driving my bucket , I still check in, usually check in on weekends. I agree with the others, I always enjoyed the videos especially when they include tips about the little things in building a tbucket. Although mine is not a Spirit kit I still learned alot from this site to help in my build. Thanks, Hershey.
I'm still around
If you go back and read post #8 and #9, I bet you will see a lot more traffic, for people need to know how to do things themselves because everyone can't afford it other wise.
We will do videos again. We have to get caught up first. We are extremely busy right now.
Money in the pocket is better than waiting for it to come in !!
Yes no complaining here. Just wish we could find some good help. We have a ton of orders and also turnkey cars to build too. We are truly blessed and very thankful every day.
I'm still here. I bought a '50 Ford coupe. but lost interest and will get back on the T when I fix it enough to sell. Got a real slick (I think) idea of something real off the wall that could get 30 MPG and have about 4.5:1 power to weight ratio. Should be real interesting! John
Still here...doing a lot of lurking
Still here also. Check in almost daily.
Well, it's been a while for me. Life and work keeps getting in the way. I hope to finish my T-bucket soon, I just have to build that garage first, but gonna start on the garage the first of Sept.
I am going to have to rethink the forum. The numbers are just not there. I have tried to keep up with the spam and also have posted a few things with minimum feedback and the number of views on the topics posted just are not great. I think too many use Facebook, twitter and other social media instead of message boards anymore.
Twitter and Facebook are good for chats or pics, but if your in search for information... Forums are where your headed...
Maybe a blog instead?
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text:
Small child occupation institute
The first illustrated book for children was published in Germany in 1658. The first creche was organized by Frenchman Johann Friedrich Oberlin in 1767. It was originally called the hall of refuge.
The first Kindergarten was opened in Blankenberg, Germany in 1837 by science teacher Frederick Greobel. It was originally called the "small child occupation institute."
The word creche means cradle in French. Generally, creche is for kids up to 3 years old. Kindergarten is for kids up to 5.


text:
Almost no one expected Nokia (NYSE: NOK) to post strong third quarter earnings, but it did. Revenue rose 5% to 10.27 billion euros. Operating profit rose to 423 million euros from a 426 million euro loss in the same period last year. The company said it would fire 1,800 people to improve gross margins and streamline operation.
New CEO Steve Elop has only been with the company for a month, so the move shows that he plans to increase the pace of restructuring the firm. Nokia's third-quarter earnings per share dropped to 0.14 euros from 0.18 euros a year ago, but beat all forecasts, which ranged between 0.08 to 0.12 euro in a Reuters poll of 36 analysts.
Shares rose almost 8% on the news.
While units sales rose, it was the smartphone sales that were impressive. Nokia total mobile device volumes of 110.4 million units, up 2% year-on-year and down 1% sequentially. Nokia converged mobile device (smartphone and mobile computer) volumes of 26.5 million units, up 61% year-on-year and 10% sequentially.
The numbers showed that the world's largest handset company is not out of the race in the smartphone market. Apple (NASDAQ: AAPL), Research In Motion (NASDAQ: RIMM), and Google (NASDAQ: GOOG) Android-based devices may have momentum, but Nokia's 26.5 million smartphone unit sales is larger than what its smaller competitors did in their last reported period. Apple sold 14.1 million iPads in its recently reported quarter.
Nokia expects Devices & Services net sales to be between EUR 8.2 billion and EUR 8.7 billion in the fourth quarter 2010. Nokia now expects its mobile device volume market share to be slightly down in 2010, compared to 2009. Nokia earlier targeted its mobile device volume market share to be flat in 2010, compared to 2009.
"In the five weeks since joining Nokia, I have found a company with many great strengths and a history of achievement that are second to none in the industry. And yet our company faces a remarkably disruptive time in the industry, with recent results demonstrating that we must reassess our role in and our approach to this industry," new CEO Steve Elop said. "Some of our most recent product launches illustrate that we have the talent, the capacity to innovate, and the resources necessary to lead through this period of disruption. We will make both the strategic and operational improvements necessary to ensure that we continue to delight our customers and deliver superior financial results to our shareholders."
For Elop, the news is nearly meaningless. The people fired are a tiny part of the total employee base. The quarterly numbers were produced by his predecessor, and he only has a quarter or two to show Wall St. progress
Douglas A. McIntyre


text:
2 Movie Tickets and Dinner = $15
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text: It started as a joke. I thought it would be funny to put Jake in our holiday cards as a goof – to laugh at myself. I've always been a huge fan of William Wegman, and since I have a Vizsla (a cousin of the Weirmaraner) I figured I could get away with dressing my poor dog up. As the years have gone on, the pictures have gotten better (I think this year takes the cake). BUT – I can't reveal this year until after the cards are sent! With a new family member on the way – this could be Jake's swan song – so I figured I'd post a review of some of the years past! I'm missing a couple, and honestly, I can't even remember what they were – but enjoy! And I know…. he's a good dog.


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Of all the great dialogue exchanges on Seinfeld, there is one often overlooked in "The Subway" episode -- which centers around all four of our heroes' outlandish encounters on the rail. Jerry falls asleep in one of the cars, only to wake up to an overweight nudist across the aisle. Jerry's incredulous, and the scene cuts away soon after. By the time we return, the two are locked in a debate about the Mets:
Nudist: They still have no pitching. Gooden's a question mark. You don't recover from those rotator cuffs so fast.
Jerry: I'm not worried about the Mets' pitching. They got pitching. They got no hitting.
Nudist: No, they got hitting. Bonilla, Murray. They got no defense.
Jerry: Defense? Please. They need speed.
Nudist: Speed? They've got Coleman. They need a bullpen.
Jerry: Franco's no good? They got no team leaders.
Nudist: They got Franco! What they need is a front office.
Jerry: But you gotta like their chances.
Nudist: I love their chances.
Jerry: If they win it this year, I'll sit naked with you at the World Series.
Nudist: It's a deal.
Obviously, the "joke" is that the Nudist is just like any other guy. The reason the joke "works" is because of its accuracy in depicting the polarity that can exist within, and between, sports fans. Together, Jerry and his new friend point out strengths and weaknesses within almost every branch of the Mets, never agreeing just where those strengths and weaknesses truly lie. As their compliments and misgivings accumulate, you may be thinking the Mets are a middle-of-the-road team. Lots of good, lots of bad. But then they agree the Mets could very well win the pennant.
I'd like to think Jerry's encounter was just some sort of dream (he had been sleeping, after all), where the obese nudist was actually one side of his personality poking at the other. I entertain that idea because the obese nudist in me has come out frequently this offseason, hauling my conscious into similar roster tête-à-têtes. This is in part because I don't know how long the Super Bowl window will remain open for my own team, the Green Bay Packers.
In my head, Green Bay is in a weird place right now, which puts me in a weirder place as a fan. They won a Super Bowl two years ago, took the division crown in the two years since and won 26 of 32 regular season games along the way. But they have about a half-dozen problem areas on their roster, which seems like a lot, while the rest of the team has really only marginally improved since that wonderyear.
And over the past two years, New York and San Francisco – two teams who seemed (at the time, at least) like more complete packages – convincingly dismissed Green Bay from the postseason. I think of Green Bay's squeamishness to free agency and I think of the limited chances rookies have to make immediate impacts and I think of the shopping list of needs and it all makes me feel kind of icky.
What I mean by "icky" is that these thoughts – which sound suspiciously like I'm (unjustifiably) panicking about a team who's been running wild with success – make me feel uncomfortable as someone who generally has a healthy relationship with his team. I swear I'm not one of those ungrateful bastard-fans. Please believe me.
But I've started to wrestle with the obese nude man inside me (that sounds weird, but hey it's a metaphor), and like his new friend Jerry, I can't decide what direction the team should go in. They need a tackle! Come on, Bulaga has his game figured out and we just need Sherrod to be healthy. We have no running back. Please. We always need a running back and do fine without one. We need a new middle linebacker. Hawk isn't a playmaker. How typical of you to under-appreciate him. He's fantastic against the run. The defensive line's going to keep suffering without a nose tackle who can help Raji. The D-line is deeper than safety, though. They need a thumper back there.
And so on.
I'd like to think the reason I'm having these thoughts is because it's simply the time of year when fans think about what their teams needs and doesn't need the most. During the season, you tend to think more about standings, team health, winning third-down situations and stuff like that. I'm hoping I settle down on Sept. 8 because, after all, there's so much to go bonkers for in Green Bay. Aaron Rodgers! Clay Matthews! B.J. Raji! Randall Cobb! (Sorta, also, kind of) Jermichael Finley! And general manager Ted Thompson has done well to keep a championship team afloat for so long. Baltimore, it seems, hardly lasted one month.
Meanwhile, Green Bay is said to be on the goal line with Rodgers about a new contract. Once the deal is completed, the Packers will have effectively locked up its two giant, marble pillars, with Matthews becoming the league's highest paid 'backer after signing a new contract in mid-April. Rodgers will literally strike gold like no other NFLer before him. The deal – expected to be worth between $110 and $160 million – will account for around one-sixth of the team's total payroll, according to the Milwaukee Journal-Sentinel.
But then comes the worry again, as I lay emotionally bare to the harsh reality of a sports league with a hard cap. I juxtapose the success Green Bay's system has had with young bench warmers blossoming into reliable, if not Pro Bowl-worthy, starters or role players with the length of time it might take to happen. This creates -- at least in the obese nude man inside me -- a sense of impending doom because of the required time risked to develop players to attach to the Rodgers juggernaut. Sometimes it happens quickly (Cobb, Sam Shields, Casey Hayward). Other times, it takes a few years (Desmond Bishop, Tramon Williams, T.J. Lang). I worry about whether my expectations for one, two or maybe three players to make such a leap next season will ruin the entire thing if it doesn't happen. Then I think about players split from the team, and how, as of late, Green Bay has struggled to keep up with the departed (Cullen Jenkins, Nick Collins, Scott Wells and Chad Clifton).
But then there's Aaron. Even the obese nudist in all of us can't deny his capabilities. For fans, conversations about the Packers in the playoffs or the Super Bowl wouldn't be possible without him. With a player like him, we know teams like the Packers can afford to have a no-name backfield and a shaky left tackle moreso than most teams, and that's why they're willing to dump colossal amounts of cash on him.
Which brings everything full circle. Yes, that may sound both irrational and rational at the same time. Great players give teams extra breathing room, sure, even if you don't necessarily want to leave them hanging out to dry and doing all the work (Rodgers does have a crack team of wide receivers, but the point remains). But appreciating that these type of stars can do what we pay them to do is what makes being a fan fun.
When you have a player who can give one hell of a piggyback ride if he needs to, you become okay with the fact that Green Bay probably will not be able to fix all of its problems over the weekend or in training camp, and Rodgers' new deal may strain cap space in the future. As long as he's around with a fairly good supporting cast, that Super Bowl window is going to stay open.
A player like him is enough to make any fan and the obese nudist in his head to shrug their shoulders, maybe give a little smirk and conclude with, "But you gotta like their chances."
We'll leave it at that. Though, seriously, put some pants on.
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Taking part in a partnership program implies paying certain fees to intermediaries counted off the deal between seller & customer done. You simply post the seller's ads on your website & get profit based on the products or ser
1. Intro
2. What are affiliate programs?
The definition
3. Parties in affiliate programs
Sponsors, intermediaries, and buyers as the main partnership participants
4. Reasons to work through affiliate programs
5. Advantages for you
- fast income without any investments. Even if you don't have your own website, you can offer the sponsor's products or services to your friends and relatives and get the initially discussed with a sponsor fee for the successful deals.
- After purchase payments. With most affiliate programs, you don't have to wait until the earned money is transferred to your account. As a rule, commissions are transferred to your card or e-wallet during 1-2 hours after the deal had been held.
- Additional advertisement for your own web-resource. Your own Internet-resource will attract new users that are looking for the products or services presented by your sponsor. In such a way, partnership expands your TA reach.
- No income limits. If you have a very well promoted web-resource or you are simply a heaven sent seller, you will be able to get money without any restrictions or limitations with affiliate. Your fees are multiplied by the number of customers you bring to the sponsor
How profitable is it to be an intermediary in an affiliate program?
6. Some platforms to start work with an affiliate program
A list of the biggest partner networks
7. How to find the right affiliate program for you
Tips on searching for a partnership
8. What are the requirements for starting affiliate marketing
Why even the personal website isn't required for an affiliate program
9. How to start an affiliate program for your business: where to begin?
Turning to the partner networks services
10. Starting work with an affiliate program: tips
Tips on increasing income by participating in the affiliate programs
11. Conclusion
During the last few years, affiliate programs have become not only a good source of income for Internet-resources owners but also a way of an additional promotion for the said resources. This feature elaborates on the 'affiliate program' concept, studies its main advantages, and tells how to start work with an affiliate program without even having your own web-resource.
What are affiliate programs?
Affiliate program is a sort of online cooperation where the standard format of marketing interaction between seller and buyer is complemented with a third participant – intermediary. An intermediary gets either a deal interest or a certain sum for selling, posting ads or other manipulations with a product or service of a seller (this is defined in the terms and conditions of participation). In any way, they receive money for deliberate activity of potential/existing buyers, not just for an ads link clicks.
Parties in affiliate programs
According the above-mentioned, an affiliate program has three sides: seller (sponsor, service provider, i.e. a person or a company that needs to promote its business among the new customers), intermediary (an entity that will advertise the seller's products or services for certain fees), and buyer – a potential source of income for the first two sides
Reasons to work through affiliate programs
The reasons for taking part in the discussed affair are quite obvious. For sellers – it is an utterly great way to expand their target audience with minimum expenses; for intermediaries – an excellent option of an additional, quite profitable, and, in some cases, totally passive income. Moreover, the intermediaries that possess their own website or a social network community can use affiliates to increase conversion.
Advantages for you
In case you have never been a participant of the discussed kind of cooperation, you are probably thinking what benefits might bring starting work with an affiliate program for my business. We define the four general advantages for any affiliate participant that acts as an intermediary.
Some platforms to start work with an affiliate program
Most people that want to take part in affiliates are looking for sponsors with the help of specialized platforms also known as partner networks. They are the places for posting offers of several (sometimes several thousands) advertisers selling products or services of absolutely various themes at once. Among the most popular platforms of such a kind are services Travelpayouts, eBay Partner Network, Amazon Associates, ShareASale, Flexoffers, Tradedoubler.
How to find the right affiliate program for you
If you are an owner of a popular web community, blog, online-store, or some other web-resource with good traffic, you will easily find the people that would like to 'repost' your ad banner, link, or something else. Another thing is that in order to get a deal (from which you will get a fee) out of a click on the link, you will have to look for the partners that distribute products or services similar to your resource's. If you are selling cosmetics, then an affiliate program with a clothing brand or even a travel agency may be a great idea. And vice versa, if you are keeping a blog dedicated to the healthy lifestyle, a building materials ad banner won't be really convenient.
What are the requirements for starting affiliate marketing
You don't have to pay a single penny in order to become a partner in the discussed program. As to the nonmaterial requirements for a potential partner, they are minimal. You don't even need to own a site to start earning. In particular, you can simply be a good SEO specialist or possess a wide circle of contacts to which the production/services of \the sponsor can be presented.
How to start an affiliate program for your business: where to begin?
So, let's try to answer a particular question of, for example, how to start affiliate marketing on your blog? The simplest way is to employ the partner network services. In such a case, you won't have to handle the organizational questions (the ones related to your salary, for instance) or approve the integrity of your sponsors (this goes both for partners relationships and the quality of services or products sold by the partners). All you need to do here is accept the conditions of the chosen network.
Starting work with an affiliate program: tips
As a matter of fact, there are two case scenarios where you can earn good money due to participating in an affiliate.
|Who are you?
|What needs to be done?
|A web-resource owner
|Asking yourself: "how to start an affiliate program for your website", it's important to realize that in order to start getting real money from such cooperation, an effort must be put into the promotion of your own site. To do that:
You goal is to beat the 100 people a day mark.
|You don't have your own web-resource, but you can sell
|In such case you can:
As we can see, the 'how to start an affiliate marketing program' affair can be resolved by a proper choice of partner and efficient promotion of one's own website. That way you will get a constant source of good income. On another hand, employing the affiliate services, you can get such a source without your own site, by simply recommending a certain establishment to friends and whatnot! If you become a member of the Travelpayouts partner network, which promotes the advertisers' travel business apps, you will be able to start earning in a few minutes after the registration!


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Interakt Community Theatre
We offer exciting and tailor made opportunities for all ages, abilities and disabilities because we care about your welfare and improving your lifestyle.
Our passion is to provide you with professional exposure in all aspects of theatre, art, fashion and education in relevant life skills, in this way we bring together the creative and practical aspect from all our sessions so that you can gain the optimum benefit.
We believe that everyone has the right to enrich their lives, be empowered, grow in confidence, gain and apply their skills safely in our diverse community of cultures.
If you would like to work with Interakt Community Theatre, please join The Mandy Network to get alerted to future job vacancies.
Members of Mandy Theatre Professionals UK who have worked for Interakt Community Theatre
Raven Kaliana , Puppetry Workshop Leader
- Shadow Puppetry & Mask Workshop
- Phoenix Centre
Interakt Community Theatre Jobs
For details of known Interakt Community Theatre vacancies, please check our jobs board for more information


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Serenity's Piece
As I mentioned a few months ago my friend Serenity who has cancer put on an art show to raise funds for her medical expenses. Here is the piece I did for her. She likes dolphins, butterflies and hearts. So I tried to incorporate all of them into a single maze and make it work. Not my best work but I have to say that the attempt really sparked a change in my work.
The past two mazes I shared were completed after this one. And I can see in my work more of a story vibe to each maze. This maze that took a lot longer than usual was the first attempt to the new direction that my art is taking.