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Commitment in embryonic stem cells is often depicted as a binary choice between alternate cell states, pluripotency and specification to a particular germ layer or extraembryonic lineage. However, close examination of human ES cell cultures has revealed significant heterogeneity in the stem cell compartment. We isolated subpopulations of embryonic stem cells using surface markers, then examined their expression of pluripotency genes and lineage specific transcription factors at the single cell level, and tested their ability to regenerate colonies of stem cells. Transcript analysis of single embryonic stem cells showed that there is a gradient and a hierarchy of expression of pluripotency genes in the population. Even cells at the top of the hierarchy generally express only a subset of the stem cell genes studied. Many cells co-express pluripotency and lineage specific genes. Cells along the continuum show a progressively decreasing likelihood of self renewal as their expression of stem cell surface markers and pluripotency genes wanes. Most cells that are positive for stem cell surface markers express Oct-4, but only those towards the top of the hierarchy express the nodal receptor TDGF-1 and the growth factor GDF3. These findings on gene expression in single embryonic stem cells are in concert with recent studies of early mammalian development, which reveal molecular heterogeneity and a stochasticity of gene expression in blastomeres. Our work indicates that only a small fraction of the population resides at the top of the hierarchy, that lineage priming (co-expression of stem cell and lineage specific genes) characterizes pluripotent stem cell populations, and that extrinsic signaling pathways are upstream of transcription factor networks that control pluripotency.

Background The developing mouse kidney is currently the best-characterized model of organogenesis at a transcriptional level. Detailed spatial maps have been generated for gene expression profiling combined with systematic in situ screening. These studies, however, fall short of capturing the transcriptional complexity arising from each locus due to the limited scope of microarray-based technology, which is largely based on \"gene-centric\" models. Results To address this, the polyadenylated RNA and microRNA transcriptomes of the 15.5 dpc mouse kidney were profiled using strand-specific RNA-sequencing (RNA-Seq) to a depth sufficient to complement spatial maps from pre-existing microarray datasets. The transcriptional complexity of RNAs arising from mouse RefSeq loci was catalogued; including 3568 alternatively spliced transcripts and 532 uncharacterized alternate 3' UTRs. Antisense expressions for 60% of RefSeq genes was also detected including uncharacterized non-coding transcripts overlapping kidney progenitor markers, Six2 and Sall1, and were validated by section in situ hybridization. Analysis of genes known to be involved in kidney development, particularly during mesenchymal-to-epithelial transition, showed an enrichment of non-coding antisense transcripts extended along protein-coding RNAs. Conclusion The resulting resource further refines the transcriptomic cartography of kidney organogenesis by integrating deep RNA sequencing data with locus-based information from previously published expression atlases. The added resolution of RNA-Seq has provided the basis for a transition from classical gene-centric models of kidney development towards more accurate and detailed \"transcript-centric\" representations, which highlights the extent of transcriptional complexity of genes that direct complex development events.

Application of next-generation sequencing using the ABI SOLiD technology to mammalian transcriptome analysis enabled a survey of the content, the complexity and the developmental dynamics of the embryonic stem cell transcriptome in the mouse. Also in this issue, Mortazavi et al . report Illumina technology–based RNA-Seq analysis of the mouse transcriptome in three different tissues. We developed a massive-scale RNA sequencing protocol, short quantitative random RNA libraries or SQRL, to survey the complexity, dynamics and sequence content of transcriptomes in a near-complete fashion. This method generates directional, random-primed, linear cDNA libraries that are optimized for next-generation short-tag sequencing. We surveyed the poly(A) + transcriptomes of undifferentiated mouse embryonic stem cells (ESCs) and embryoid bodies (EBs) at an unprecedented depth (10 Gb), using the Applied Biosystems SOLiD technology. These libraries capture the genomic landscape of expression, state-specific expression, single-nucleotide polymorphisms (SNPs), the transcriptional activity of repeat elements, and both known and new alternative splicing events. We investigated the impact of transcriptional complexity on current models of key signaling pathways controlling ESC pluripotency and differentiation, highlighting how SQRL can be used to characterize transcriptome content and dynamics in a quantitative and reproducible manner, and suggesting that our understanding of transcriptional complexity is far from complete.

Background Kiwi represent the most basal extant avian lineage (paleognaths) and exhibit biological attributes that are unusual or extreme among living birds, such as large egg size, strong olfaction, nocturnality, flightlessness and long lifespan. Despite intense interest in their evolution and their threatened status, genomic resources for kiwi were virtually non-existent until the recent publication of a single genome. Here we present the most comprehensive kiwi transcriptomes to date, obtained via Illumina sequencing of whole blood and de novo assembly of mRNA sequences of eight individuals from each of the two rarest kiwi species, little spotted kiwi (LSK; Apteryx owenii ) and rowi ( A. rowi ). Results Sequences obtained were orthologous with a wide diversity of functional genes despite the sequencing of a single tissue type. Individual and composite assemblies contain more than 7900 unique protein coding transcripts in each of LSK and rowi that show strong homology with chicken ( Gallus gallus ), including those associated with growth, development, disease resistance, reproduction and behavior. The assemblies also contain 66,909 SNPs that distinguish between LSK and rowi, 12,384 SNPs among LSK (associated with 3088 genes), and 29,313 SNPs among rowi (associated with 4953 genes). We found 3084 transcripts differentially expressed between LSK and rowi and 150 transcripts differentially expressed between the sexes. Of the latter, 83 could be mapped to chicken chromosomes with 95% syntenic with chromosome Z. Conclusions Our study has simultaneously sequenced multiple species, sexes, and individual kiwi at thousands of genes, and thus represents a significant leap forward in genomic resources available for kiwi. The expression pattern we observed among chromosome Z related genes in kiwi is similar to that observed in ostriches and emu, suggesting a common and ancestral pattern of sex chromosome homomorphy, recombination, and gene dosage among living paleognaths. The transcriptome assemblies described here will provide a rich resource for polymorphic marker development and studies of adaptation of these highly unusual and endangered birds.

Pancreatic cancer is a highly lethal malignancy with few effective therapies. We performed exome sequencing and copy number analysis to define genomic aberrations in a prospectively accrued clinical cohort ( n = 142) of early (stage I and II) sporadic pancreatic ductal adenocarcinoma. Detailed analysis of 99 informative tumours identified substantial heterogeneity with 2,016 non-silent mutations and 1,628 copy-number variations. We define 16 significantly mutated genes, reaffirming known mutations ( KRAS , TP53 , CDKN2A, SMAD4 , MLL3 , TGFBR2, ARID1A and SF3B1 ), and uncover novel mutated genes including additional genes involved in chromatin modification ( EPC1 and ARID2 ), DNA damage repair ( ATM ) and other mechanisms ( ZIM2 , MAP2K4 , NALCN , SLC16A4 and MAGEA6 ). Integrative analysis with in vitro functional data and animal models provided supportive evidence for potential roles for these genetic aberrations in carcinogenesis. Pathway-based analysis of recurrently mutated genes recapitulated clustering in core signalling pathways in pancreatic ductal adenocarcinoma, and identified new mutated genes in each pathway. We also identified frequent and diverse somatic aberrations in genes described traditionally as embryonic regulators of axon guidance, particularly SLIT/ROBO signalling, which was also evident in murine Sleeping Beauty transposon-mediated somatic mutagenesis models of pancreatic cancer, providing further supportive evidence for the potential involvement of axon guidance genes in pancreatic carcinogenesis. Exome sequencing and copy number analysis are used to define genomic aberrations in early sporadic pancreatic ductal adenocarcinoma; among the findings are mutations in genes involved in chromatin modification and DNA damage repair, and frequent and diverse somatic aberrations in genes known as embryonic regulators of axon guidance. New mutations identified in pancreatic cancer This large-scale study presents exome sequencing and copy number variant analysis from 142 patients with pancreatic ductal adenocarcinoma, the most common form of pancreatic cancer. Among the findings are mutations in genes involved in chromatin modification and DNA damage repair, not previously implicated in this disease. Importantly, the data show that abnormal expression of genes involved in slit and semaphorin signalling is associated with poor patient survival, and in animal models was associated with disease development and progression.

Pancreatic cancer is a highly lethal malignancy with few effective therapies. We performed exome sequencing and copy number analysis to define genomic aberrations in a prospectively accrued clinical cohort (n = 142) of early (stage I and II) sporadic pancreatic ductal adenocarcinoma. Detailed analysis of 99 informative tumours identified substantial heterogeneity with 2,016 non-silent mutations and 1,628 copy-number variations. We define 16 significantly mutated genes, reaffirming known mutations (KRAS, TP53, CDKN2A, SMAD4, MLL3, TGFBR2, ARID1A and SF3B1), and uncover novel mutated genes including additional genes involved in chromatin modification (EPC1 and ARID2), DNA damage repair (ATM) and other mechanisms (ZIM2, MAP2K4, NALCN, SLC16A4 and MAGEA6). Integrative analysis with in vitro functional data and animal models provided supportive evidence for potential roles for these genetic aberrations in carcinogenesis. Pathway-based analysis of recurrently mutated genes recapitulated clustering in core signalling pathways in pancreatic ductal adenocarcinoma, and identified new mutated genes in each pathway. We also identified frequent and diverse somatic aberrations in genes described traditionally as embryonic regulators of axon guidance, particularly SLIT/ROBO signalling, which was also evident in murine Sleeping Beauty transposon-mediated somatic mutagenesis models of pancreatic cancer, providing further supportive evidence for the potential involvement of axon guidance genes in pancreatic carcinogenesis. [PUBLICATION ABSTRACT]

Precision medicine (PM) research in recent years has witnessed a remarkable surge in large-scale population genomics programs. In 2017, Singapore initiated the National Precision Medicine (NPM) program, a three-phase national strategy driving PM research, innovation, and enterprise capitalizing on Singapore’s unique multi-ancestral Asian population. Coordinated by Precision Health Research, Singapore (PRECISE), NPM Phase I assembled an Asian reference genome of 10,000 individuals completed using highly manual and laborious laboratory sample workflows. NPM Phase II, targeting a 100,000 population cohort (PRECISE-SG100K), required the transformation of the genome sequencing workflow to a production-scale operation leveraging high-throughput automation and robotics. Here we share detailed technical blueprints for implementing and maintaining Singapore’s PRECISE-SG100K Genomic Engine, learning from and overcoming Phase I’s pain-points and bottlenecks. The Genomic Engine allowed the successful scale up of genomic sequencing and throughput, enabling the anticipated completion of sequencing of 100,000 whole genomes in three years.