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Pluripotent stem cells (PSCs) may provide a potential source of haematopoietic stem/progenitor cells (HSPCs) for transplantation; however, unknown molecular barriers prevent the self-renewal of PSC-HSPCs. Using two-step differentiation, human embryonic stem cells (hESCs) differentiated in vitro into multipotent haematopoietic cells that had the CD34(+)CD38(-/lo)CD90(+)CD45(+)GPI-80(+) fetal liver (FL) HSPC immunophenotype, but exhibited poor expansion potential and engraftment ability. Transcriptome analysis of immunophenotypic hESC-HSPCs revealed that, despite their molecular resemblance to FL-HSPCs, medial HOXA genes remained suppressed. Knockdown of HOXA7 disrupted FL-HSPC function and caused transcriptome dysregulation that resembled hESC-derived progenitors. Overexpression of medial HOXA genes prolonged FL-HSPC maintenance but was insufficient to confer self-renewal to hESC-HSPCs. Stimulation of retinoic acid signalling during endothelial-to-haematopoietic transition induced the HOXA cluster and other HSC/definitive haemogenic endothelium genes, and prolonged HSPC maintenance in culture. Thus, medial HOXA gene expression induced by retinoic acid signalling marks the establishment of the definitive HSPC fate and controls HSPC identity and function.

Scl/Tal1 confers hemogenic competence and prevents ectopic cardiomyogenesis in embryonic endothelium by unknown mechanisms. We discovered that Scl binds to hematopoietic and cardiac enhancers that become epigenetically primed in multipotent cardiovascular mesoderm, to regulate the divergence of hematopoietic and cardiac lineages. Scl does not act as a pioneer factor but rather exploits a pre-established epigenetic landscape. As the blood lineage emerges, Scl binding and active epigenetic modifications are sustained in hematopoietic enhancers, whereas cardiac enhancers are decommissioned by removal of active epigenetic marks. Our data suggest that, rather than recruiting corepressors to enhancers, Scl prevents ectopic cardiogenesis by occupying enhancers that cardiac factors, such as Gata4 and Hand1, use for gene activation. Although hematopoietic Gata factors bind with Scl to both activated and repressed genes, they are dispensable for cardiac repression, but necessary for activating genes that enable hematopoietic stem/progenitor cell development. These results suggest that a unique subset of enhancers in lineage-specific genes that are accessible for regulators of opposing fates during the time of the fate decision provide a platform where the divergence of mutually exclusive fates is orchestrated.

Advances in pluripotent stem cell and reprogramming technologies have given us the hope of generating hematopoietic stem cells (HSCs) in culture. To succeed, greater understanding of the self-renewing HSC during human development is required. We discovered that the glycophosphatidylinositol-anchored surface protein GPI-80 defines a subpopulation of human fetal liver hematopoietic stem/progenitor cells (HSPCs) with self-renewal ability. CD34(+)CD38(lo/-)CD90(+)GPI-80(+) HSPCs were the sole population that maintained proliferative potential and an undifferentiated state in stroma coculture and engrafted in immunodeficient mice. GPI-80 expression also enabled tracking of HSPCs once they emerged from endothelium and migrated between human fetal hematopoietic niches. GPI-80 colocalized on the surface of HSPCs with Integrin alpha-M (ITGAM), which in leukocytes cooperates with GPI-80 to support migration. Knockdown of GPI-80 or ITGAM was sufficient to compromise HSPC expansion in culture and engraftment in vivo. These findings indicate that human fetal HSCs employ mechanisms used in leukocyte adhesion and migration to mediate HSC self-renewal.

Haematopoietic cells arise from spatiotemporally restricted domains in the developing embryo. Although studies of non-mammalian animal and in vitro embryonic stem cell models suggest a close relationship among cardiac, endocardial and haematopoietic lineages, it remains unknown whether the mammalian heart tube serves as a haemogenic organ akin to the dorsal aorta. Here we examine the haemogenic activity of the developing endocardium. Mouse heart explants generate myeloid and erythroid colonies in the absence of circulation. Haemogenic activity arises from a subset of endocardial cells in the outflow cushion and atria earlier than in the aorta-gonad-mesonephros region, and is transient and definitive in nature. Interestingly, key cardiac transcription factors, Nkx2-5 and Isl1, are expressed in and required for the haemogenic population of the endocardium. Together, these data suggest that a subset of endocardial/endothelial cells serve as a de novo source for transient definitive haematopoietic progenitors.

Expression of the cell-surface antigen CD10 has long been used to define the lymphoid commitment of human cells. Here we report a unique lymphoid-primed population in human bone marrow that was generated from hematopoietic stem cells (HSCs) before onset of the expression of CD10 and commitment to the B cell lineage. We identified this subset by high expression of the homing molecule L-selectin (CD62L). CD10(-)CD62L(hi) progenitors had full lymphoid and monocytic potential but lacked erythroid potential. Gene-expression profiling placed the CD10(-)CD62L(hi) population at an intermediate stage of differentiation between HSCs and lineage-negative (Lin(-)) CD34(+)CD10(+) progenitors. CD62L was expressed on immature thymocytes, and its ligands were expressed at the cortico-medullary junction of the thymus, which suggested a possible role for this molecule in homing to the thymus. Our studies identify the earliest stage of lymphoid priming in human bone marrow.

Genome tiling microarray studies have consistently documented rich transcriptional activity beyond the annotated genes. However, systematic characterization and transcriptional profiling of the putative novel transcripts on the genome scale are still lacking. We report here the identification of 25,352 and 27,744 transcriptionally active regions (TARs) not encoded by annotated exons in the rice (Oryza. sativa) subspecies japonica and indica, respectively. The non-exonic TARs account for approximately two thirds of the total TARs detected by tiling arrays and represent transcripts likely conserved between japonica and indica. Transcription of 21,018 (83%) japonica non-exonic TARs was verified through expression profiling in 10 tissue types using a re-array in which annotated genes and TARs were each represented by five independent probes. Subsequent analyses indicate that about 80% of the japonica TARs that were not assigned to annotated exons can be assigned to various putatively functional or structural elements of the rice genome, including splice variants, uncharacterized portions of incompletely annotated genes, antisense transcripts, duplicated gene fragments, and potential non-coding RNAs. These results provide a systematic characterization of non-exonic transcripts in rice and thus expand the current view of the complexity and dynamics of the rice transcriptome.

A central challenge in genome annotation is determining the function of sequences that do not encode proteins, but make up the overwhelming bulk of large genomes--some 99% in humans. A [...]

Abstract Background Tiling arrays have been the tool of choice for probing an organism's transcriptome without prior assumptions about the transcribed regions, but RNA-Seq is becoming a viable alternative as the costs of sequencing continue to decrease. Understanding the relative merits of these technologies will help researchers select the appropriate technology for their needs. Results Here, we compare these two platforms using a matched sample of poly(A)-enriched RNA isolated from the second larval stage of C. elegans. We find that the raw signals from these two technologies are reasonably well correlated but that RNA-Seq outperforms tiling arrays in several respects, notably in exon boundary detection and dynamic range of expression. By exploring the accuracy of sequencing as a function of depth of coverage, we found that about 4 million reads are required to match the sensitivity of two tiling array replicates. The effects of cross-hybridization were analyzed using a "nearest neighbor" classifier applied to array probes; we describe a method for determining potential "black list" regions whose signals are unreliable. Finally, we propose a strategy for using RNA-Seq data as a gold standard set to calibrate tiling array data. All tiling array and RNA-Seq data sets have been submitted to the modENCODE Data Coordinating Center. Conclusions Tiling arrays effectively detect transcript expression levels at a low cost for many species while RNA-Seq provides greater accuracy in several regards. Researchers will need to carefully select the technology appropriate to the biological investigations they are undertaking. It will also be important to reconsider a comparison such as ours as sequencing technologies continue to evolve.

Abstract Background An important problem in genomics is the automatic inference of groups of homologous proteins from pairwise sequence similarities. Several approaches have been proposed for this task which are "local" in the sense that they assign a protein to a cluster based only on the distances between that protein and the other proteins in the set. It was shown recently that global methods such as spectral clustering have better performance on a wide variety of datasets. However, currently available implementations of spectral clustering methods mostly consist of a few loosely coupled Matlab scripts that assume a fair amount of familiarity with Matlab programming and hence they are inaccessible for large parts of the research community. Results SCPS (Spectral Clustering of Protein Sequences) is an efficient and user-friendly implementation of a spectral method for inferring protein families. The method uses only pairwise sequence similarities, and is therefore practical when only sequence information is available. SCPS was tested on difficult sets of proteins whose relationships were extracted from the SCOP database, and its results were extensively compared with those obtained using other popular protein clustering algorithms such as TribeMCL, hierarchical clustering and connected component analysis. We show that SCPS is able to identify many of the family/superfamily relationships correctly and that the quality of the obtained clusters as indicated by their F-scores is consistently better than all the other methods we compared it with. We also demonstrate the scalability of SCPS by clustering the entire SCOP database (14,183 sequences) and the complete genome of the yeast Saccharomyces cerevisiae (6,690 sequences). Conclusions Besides the spectral method, SCPS also implements connected component analysis and hierarchical clustering, it integrates TribeMCL, it provides different cluster quality tools, it can extract human-readable protein descriptions using GI numbers from NCBI, it interfaces with external tools such as BLAST and Cytoscape, and it can produce publication-quality graphical representations of the clusters obtained, thus constituting a comprehensive and effective tool for practical research in computational biology. Source code and precompiled executables for Windows, Linux and Mac OS X are freely available at http://www.paccanarolab.org/software/scps.

Corrected abstract We are correcting the abstract of our published article (1). The sentence that starts "We observe that 4.5% of MPSS tags...." was not scientifically complete in the original abstract, having only two of the four numbers required to describe a comparison of two technologies in two different organisms. The abstract below more accurately describes our findings, as documented in Figure 1 of the manuscript.

Abstract Background There are two main technologies for transcriptome profiling, namely, tiling microarrays and high-throughput sequencing. Recently there has been a tremendous amount of excitement about the latter because of the advent of next-generation sequencing technologies and its promises. Consequently, the question of the moment is how these two technologies compare. Here we attempt to develop an approach to do a fair comparison of transcripts identified from tiling microarray and MPSS sequencing data. Findings This comparison is a challenging task because the sequencing data is discrete while the tiling array data is continuous. We use the published rice and Arabidopsis datasets which provide currently best matched sets of arrays and sequencing experiments using a slightly earlier generation of sequencing, the MPSS tag sequencing technology. After scoring the arrays consistently in both the organisms, a first pass comparison reveals a surprisingly small overlap in transcripts of 22% and 66% respectively, in rice and Arabidopsis. However, when we do the analysis in detail, we find that this is an underestimate. In particular, when we map the probe intensities onto the sequencing tags and then look at their intensity distribution, we see that they are very similar to exons. Furthermore, restricting our comparison to only protein-coding gene loci revealed a very good overlap between the two technologies. Conclusion Our approach to compare genome tiling microarray and MPSS sequencing data suggests that there is actually a reasonable overlap in transcripts identified by the two technologies. This overlap is distorted by the scoring and thresholding in the tiling array scoring procedure.