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Here, we present an annotated, chromosome-anchored, genome assembly for Lake Trout (Salvelinus namaycush) - a highly diverse salmonid species of notable conservation concern and an excellent model for research on adaptation and speciation. We leveraged Pacific Biosciences long-read sequencing, paired-end Illumina sequencing, proximity ligation (Hi-C) sequencing, and a previously published linkage map to produce a highly contiguous assembly composed of 7378 contigs (contig N50 = 1.8 Mb) assigned to 4120 scaffolds (scaffold N50 = 44.975 Mb). Long read sequencing data were generated using DNA from a female double haploid individual. 84.7% of the genome was assigned to 42 chromosome-sized scaffolds and 93.2% of Benchmarking Universal Single Copy Orthologues were recovered, putting this assembly on par with the best currently available salmonid genomes. Estimates of genome size based on k-mer frequency analysis were highly similar to the total size of the finished genome, suggesting that the entirety of the genome was recovered. A mitochondrial genome assembly was also produced. Self-versus-self synteny analysis allowed us to identify homeologs resulting from the salmonid specific autotetraploid event (Ss4R) as well as regions exhibiting delayed rediploidization. Alignment with three other salmonid genomes and the Northern Pike (Esox lucius) genome also allowed us to identify homologous chromosomes in related taxa. We also generated multiple resources useful for future genomic research on Lake Trout, including a repeat library and a sex-averaged recombination map. A novel RNA sequencing data set for liver tissue was also generated in order to produce a publicly available set of annotations for 49,668 genes and pseudogenes. Potential applications of these resources to population genetics and the conservation of native populations are discussed.

Background Sixty percent of surgically resected brain metastases (BrM) recur within 1 year. These recurrences have long been thought to result from the dispersion of cancer cells during surgery. We tested the alternative hypothesis that invasion of cancer cells into the adjacent brain plays a significant role in local recurrence and shortened overall survival. Methods We determined the invasion pattern of 164 surgically resected BrM and correlated with local recurrence and overall survival. We performed single-cell RNA sequencing (scRNAseq) of >15,000 cells from BrM and adjacent brain tissue. Validation of targets was performed with a novel cohort of BrM patient-derived xenografts (PDX) and patient tissues. Results We demonstrate that invasion of metastatic cancer cells into the adjacent brain is associated with local recurrence and shortened overall survival. scRNAseq of paired tumor and adjacent brain samples confirmed the existence of invasive cancer cells in the tumor-adjacent brain. Analysis of these cells identified cold-inducible RNA-binding protein (CIRBP) overexpression in invasive cancer cells compared to cancer cells located within the metastases. Applying PDX models that recapitulate the invasion pattern observed in patients, we show that CIRBP is overexpressed in highly invasive BrM and is required for efficient invasive growth in the brain. Conclusions These data demonstrate peritumoral invasion as a driver of treatment failure in BrM that is functionally mediated by CIRBP. These findings improve our understanding of the biology underlying postoperative treatment failure and lay the groundwork for rational clinical trial development based upon invasion pattern in surgically resected BrM.

Background The olive fruit fly, Bactrocera oleae, is the most important pest in the olive fruit agribusiness industry. This is because female flies lay their eggs in the unripe fruits and upon hatching the larvae feed on the fruits thus destroying them. The lack of a high-quality genome and other genomic and transcriptomic data has hindered progress in understanding the fly’s biology and proposing alternative control methods to pesticide use. Results Genomic DNA was sequenced from male and female Demokritos strain flies, maintained in the laboratory for over 45 years. We used short-, mate-pair-, and long-read sequencing technologies to generate a combined male-female genome assembly (GenBank accession GCA_001188975.2). Genomic DNA sequencing from male insects using 10x Genomics linked-reads technology followed by mate-pair and long-read scaffolding and gap-closing generated a highly contiguous 489 Mb genome with a scaffold N50 of 4.69 Mb and L50 of 30 scaffolds (GenBank accession GCA_001188975.4). RNA-seq data generated from 12 tissues and/or developmental stages allowed for genome annotation. Short reads from both males and females and the chromosome quotient method enabled identification of Y-chromosome scaffolds which were extensively validated by PCR. Conclusions The high-quality genome generated represents a critical tool in olive fruit fly research. We provide an extensive RNA-seq data set, and genome annotation, critical towards gaining an insight into the biology of the olive fruit fly. In addition, elucidation of Y-chromosome sequences will advance our understanding of the Y-chromosome’s organization, function and evolution and is poised to provide avenues for sterile insect technique approaches.

Wastewater-based epidemiology has emerged as a promising tool to monitor pathogens in a population, particularly when clinical diagnostic capacities become overwhelmed. During the ongoing COVID-19 pandemic caused by Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2), several jurisdictions have tracked viral concentrations in wastewater to inform public health authorities. While some studies have also sequenced SARS-CoV-2 genomes from wastewater, there have been relatively few direct comparisons between viral genetic diversity in wastewater and matched clinical samples from the same region and time period. Here we report sequencing and inference of SARS-CoV-2 mutations and variant lineages (including variants of concern) in 936 wastewater samples and thousands of matched clinical sequences collected between March 2020 and July 2021 in the cities of Montreal, Quebec City, and Laval, representing almost half the population of the Canadian province of Quebec. We benchmarked our sequencing and variant-calling methods on known viral genome sequences to establish thresholds for inferring variants in wastewater with confidence. We found that variant frequency estimates in wastewater and clinical samples are correlated over time in each city, with similar dates of first detection. Across all variant lineages, wastewater detection is more concordant with targeted outbreak sequencing than with semi-random clinical swab sampling. Most variants were first observed in clinical and outbreak data due to higher sequencing rate. However, wastewater sequencing is highly efficient, detecting more variants for a given sampling effort. This shows the potential for wastewater sequencing to provide useful public health data, especially at places or times when sufficient clinical sampling is infrequent or infeasible.

The complex relationship between metabolic disease risk and body fat distribution in humans involves cellular characteristics which are specific to body fat compartments. Here we show depot-specific differences in the stromal vascual fraction of visceral and subcutaneous adipose tissue by performing single-cell RNA sequencing of tissue specimen from obese individuals. We characterize multiple immune cells, endothelial cells, fibroblasts, adipose and hematopoietic stem cell progenitors. Subpopulations of adipose-resident immune cells are metabolically active and associated with metabolic disease status and those include a population of potential dysfunctional CD8+ T cells expressing metallothioneins. We identify multiple types of adipocyte progenitors that are common across depots, including a subtype enriched in individuals with type 2 diabetes. Depot-specific analysis reveals a class of adipocyte progenitors unique to visceral adipose tissue, which shares common features with beige preadipocytes. Our human single-cell transcriptome atlas across fat depots provides a resource to dissect functional genomics of metabolic disease.

Despite the commercial importance of Greenland Halibut (Reinhardtius hippoglossoides), important gaps still persist in our knowledge of this species, including its reproductive biology and sex determination mechanism. Here, we combined single-molecule sequencing of long reads (Pacific Sciences) with chromatin conformation capture sequencing (Hi-C) data to assemble the first chromosome-level reference genome for this species. The high-quality assembly encompassed more than 598 Megabases (Mb) assigned to 1594 scaffolds (scaffold N50 = 25 Mb) with 96% of its total length distributed among 24 chromosomes. Investigation of the syntenic relationship with other economically important flatfish species revealed a high conservation of synteny blocks among members of this phylogenetic clade. Sex determination analysis revealed that similar to other teleost fishes, flatfishes also exhibit a high level of plasticity and turnover in sex determination mechanisms. A low-coverage whole-genome sequence analysis of 198 individuals revealed that Greenland Halibut possesses a male heterogametic XY system and several putative candidate genes implied in the sex determination of this species. Our study also suggests for the first time in flatfishes that a putative Y-autosomal fusion could be associated with a reduction of recombination typical of the early steps of sex chromosome evolution.

Across a species range, multiple sources of environmental heterogeneity, at both small and large scales, create complex landscapes of selection, which may challenge adaptation, particularly when gene flow is high. One key to multidimensional adaptation may reside in the heterogeneity of recombination along the genome. Structural variants, like chromosomal inversions, reduce recombination, increasing linkage disequilibrium among loci at a potentially massive scale. In this study, we examined how chromosomal inversions shape genetic variation across a species range, and ask how their contribution to adaptation in the face of gene flow varies across geographic scales. We sampled the seaweed flyCoelopa frigidaalong a bioclimatic gradient stretching across 10° of latitude, a salinity gradient and a range of heterogeneous, patchy habitats. We generated a chromosome-level genome assembly to analyse 1,446 low-coverage whole genomes collected along those gradients. We found several large non-recombining genomic regions, including putative inversions. In contrast to the collinear regions, inversions and low recombining regions differentiated populations more strongly, either along an ecogeographic cline or at a fine-grained scale. These genomic regions were associated with environmental factors and adaptive phenotypes, albeit with contrasting patterns. Altogether, our results highlight the importance of recombination in shaping adaptation to environmental heterogeneity at local and large scales.

Despite the commercial importance of Greenland Halibut (Reinhardtius hippoglossoides), important gaps still persist in our knowledge of this species, including its reproductive biology and sex determination mechanism. In this study, we combined single molecule sequencing of long reads (Pacific Sciences) with Chromatin Conformation Capture sequencing (Hi-C) data to provide the first chromosome-level genome reference for this species. The high-quality assembly encompassed more than 598 Megabases (Mb) assigned to 1 594 scaffolds (scaffold N50 = 25 Mb) with 96 % of its total length distributed among 24 chromosomes. The investigation of its syntenic relationships with other economically important flatfish species revealed a high conservation of synteny blocks among members of this phylogenetic clade. Sex determination analysis revealed that flatfishes do not escape the rule applied to other teleost fish and exhibit a high level of plasticity and turnover in sex-determination mechanisms. A whole-genome sequence analysis of 198 individuals allowed us to draw a full picture of the molecular sex determination (SD) system for Greenland Halibut, revealing that this species possesses a very nascent male heterogametic XY system, with a putative major effect of the sox2 gene, also described as the main SD driver in two other flatfishes. Interestingly, our study also suggested for the first time in flatfishes that a putative Y-autosomal fusion could be associated with a reduction of recombination typical of early steps of sex chromosome evolution.

Here we present an annotated, chromosome-anchored, genome assembly for Lake Trout (Salvelinus namaycush) – a highly diverse salmonid species of notable conservation concern and an excellent model for research on adaptation and speciation. We leveraged Pacific Biosciences long-read sequencing, paired-end Illumina sequencing, proximity ligation (Hi-C), and a previously published linkage map to produce a highly contiguous assembly composed of 7,378 contigs (contig N50 = 1.8 mb) assigned to 4,120 scaffolds (scaffold N50 = 44.975 mb). 84.7% of the genome was assigned to 42 chromosome-sized scaffolds and 93.2% of Benchmarking Universal Single Copy Orthologs were recovered, putting this assembly on par with the best currently available salmonid genomes. Estimates of genome size based on k-mer frequency analysis were highly similar to the total size of the finished genome, suggesting that the entirety of the genome was recovered. A mitome assembly was also produced. Self-vs-self synteny analysis allowed us to identify homeologs resulting from the Salmonid specific autotetraploid event (Ss4R) and alignment with three other salmonid species allowed us to identify homologous chromosomes in other species. We also generated multiple resources useful for future genomic research on Lake Trout including a repeat library and a sex averaged recombination map. A novel RNA sequencing dataset was also used to produce a publicly available set of gene annotations using the National Center for Biotechnology Information Eukaryotic Genome Annotation Pipeline. Potential applications of these resources to population genetics and the conservation of native populations are discussed.

BACKGROUND Surgery as a single modality for the treatment of brain metastases (BrM) results in local recurrence (LR) in 60% of patients. These failure rates are reduced by half with post-operative radiotherapy. The non-invasive nature of BrM has led to the assumption that local recurrence is caused by spillage of cancer cells into the surgical cavity at the time of surgery. We present evidence suggesting that invasion of metastatic cancer cells into the adjacent brain is present in the majority of BrM and is associated with LR, leptomeningeal metastasis (LM), and overall survival (OS). METHODS We assessed the histopathological growth pattern (HGP) of 164 surgically resected BrM. HGP was correlated with LR, LM and OS. Single-cell transcriptomics (scRNAseq) was performed on 15,615 cells from metastasis center (MC) and surrounding brain (SB) adjacent to the tumor. N=30 orthotopic patient-derived xenograft models (OPDX) were established from BrM. RESULTS 56/164 (34%) BrM specimens showed a minimally invasive (MI) HGP between the tumor and adjacent brain while 108/164 (66%) showed significant invasion of tumor lobules or single-cells into the brain (HI-HGP). HI-HGP was associated with LR, LM and shortened OS in BrM patients. scRNAseq identified abundant cancer cells in SB that overexpressed pathways and genes involved in cell survival and stress adaptation compared to matched cancer cells in MC. Validation of these targets with immunohistochemistry in patient and OPDX tissues revealed cold-inducible RNA binding protein (CIRBP) overexpression in HI-HGP patient and OPDX BrM. Modulation of CIRBP expression in OPDX and cell line models of HI-HGP BrM delayed BrM progression and extended OS. CONCLUSION HI-HGP is a poor prognostic indicator in patients with surgically resected BrM, establishing HGP as an important prognostic factor that should be considered by clinicians treating BrM patients. We identify CIRBP as a functional mediator of this process.

The opioid receptor (OPR) family comprises the mu-, delta-, and kappa-opioid, and nociceptin receptors that belong to the superfamily of 7-transmembrane spanning G protein-coupled receptors (GPCRs). The mu-opioid receptor is the main target for clinically used opioid analgesics, and its biology has been extensively studied. The N-terminally truncated 6TM receptors isoform produced through alternative splicing of the OPRM1 gene displays unique signaling and analgesic properties, but it is unclear if other OPRs have the same ability. In this study, we have built a comprehensive map of alternative splicing events that produce 6TM receptor variants in all the OPRs and demonstrated their evolutionary conservation. We then obtained evidence for their translation through ribosomal footprint analysis. We discovered that N-terminally truncated 6TM GPCRs are rare in the human genome and OPRs are overrepresented in this group. Finally, we also observed a significant enrichment of 6TM GPCR genes among genes associated with pain, psychiatric disorders, and addiction. Understanding the biology of 6TM receptors and leveraging this knowledge for drug development should pave the way for novel therapies. Electronic supplementary material The online version of this article (10.1007/s10571-020-00971-7) contains supplementary material, which is available to authorized users.

The complex relationship between metabolic disease risk and body fat distribution in humans involves cellular characteristics which are specific to body fat compartments. Here we show depot-specific differences in the stromal vascual fraction of visceral and subcutaneous adipose tissue by performing single-cell RNA sequencing of tissue specimen from obese individuals. We characterize multiple immune cells, endothelial cells, fibroblasts, adipose and hematopoietic stem cell progenitors. Subpopulations of adipose-resident immune cells are metabolically active and associated with metabolic disease status and those include a population of potential dysfunctional CD8+ T cells expressing metallothioneins. We identify multiple types of adipocyte progenitors that are common across depots, including a subtype enriched in individuals with type 2 diabetes. Depot-specific analysis reveals a class of adipocyte progenitors unique to visceral adipose tissue, which shares common features with beige preadipocytes. Our human single-cell transcriptome atlas across fat depots provides a resource to dissect functional genomics of metabolic disease.

Index hopping is the main cause of incorrect sample assignment of sequencing reads in multiplexed pooled libraries. We introduce a statistical model for estimating the sample index-hopping rate in multiplexed droplet-based single-cell RNA-seq data and for probabilistic inference of the true sample of origin of hopped reads. We analyze several datasets and estimate the sample index hopping probability to range between 0.003–0.009, a small number that counter-intuitively gives rise to a large fraction of phantom molecules — the fraction of phantom molecules exceeds 8% in more than 25% of samples and reaches as high as 85% in low-complexity samples. Phantom molecules lead to widespread complications in downstream analyses, including transcriptome mixing across cells, emergence of phantom copies of cells from other samples, and misclassification of empty droplets as cells. We demonstrate that our approach can correct for these artifacts by accurately purging the majority of phantom molecules from the data., Sample index hopping results in various artefacts in multiplexed scRNA-seq experiments. Here, the authors introduce a statistical model to estimate sample index hopping rate in droplet-based scRNA-seq data and show that artifacts can be corrected by purging phantom molecules from the data.

Sample index hopping can substantially confound the analysis of multiplexed sequencing data due to the resulting erroneous assignment of some, or even all, of the sequencing reads generated by a cDNA fragment in a given sample to other samples. In those target samples, the data cross-contamination artifact takes the form of phantom molecules, molecules that exist only in the data by virtue of read misassignment. The presence of phantom molecules in droplet-based single-cell RNA-seq data should be a cause of great concern since they can introduce both phantom cells and artifactual differentially-expressed genes in downstream analyses. More importantly, even when the index hopping rate is very small, the fraction of phantom molecules in the entire dataset can be high due to the distributional properties of sequencing reads across samples. To our knowledge, current computational methods are unable to accurately estimate the underlying rate of index hopping nor adequately correct for the resultant misassignment in droplet-based single cell RNA-seq data. Here, we introduce a probabilistic model that formalizes the phenomenon of index hopping and allows the accurate estimation of its rate. Application of the proposed model to several multiplexed datasets suggests that the sample index hopping probability ranges between 0.003 to 0.009, but which, counter-intuitively, can give rise to a large fraction of phantom molecules - as high as 85%. We also present a model-based approach for inferring the true sample of origin of the reads, thus allowing the purging of the majority of phantom molecules in the data. Using empirical and simulated data, we show that we can reassign reads to their true sample of origin and remove predicted phantom molecules through a principled probabilistic procedure that optimally minimizes the false positive rate. Thus, even though sample index hopping often substantially compromises single-cell RNA-seq data, it is possible to accurately quantify, detect, and reassign the affected reads and remove the phantom molecules generated by index hopping.

Long-read sequencing has greatly contributed to the generation of high quality assemblies, albeit at a high cost. It is also not always clear how to combine sequencing platforms. We sequenced the genome of the olive fruit fly (Bactrocera oleae), the most important pest in the olive fruits agribusiness industry, using Illumina short-reads, mate-pairs, 10x Genomics linked-reads, Pacific Biosciences (PacBio), and Oxford Nanopore Technologies (ONT). The 10x linked-reads assembly gave the most contiguous assembly with an N50 of 2.16 Mb. Scaffolding the linked-reads assembly using long-reads from ONT gave a more contiguous assembly with scaffold N50 of 4.59 Mb. We also present the most extensive transcriptome datasets of the olive fly derived from different tissues and stages of development. Finally, we used the Chromosome Quotient method to identify Y-chromosome scaffolds and show that the long-reads based assembly generates very highly contiguous Y-chromosome assembly.JR is a member of the MinION Access Program (MAP) and has received free-of-charge flow cells and sequencing kits from Oxford Nanopore Technologies for other projects. JR has had no other financial support from ONT.AB has received re-imbursement for travel costs associated with attending Nanopore Community meeting 2018, a meeting organized my Oxford Nanopore Technologies.

The article “Alternative Splicing of Opioid Receptor Genes Shows a Conserved Pattern for 6TM Receptor Variants”, written by Marjo Piltonen, Andrey Krokhotin, Marc Parisien, Pierre Berube, Haig Djambazian, Rob Sladek, Nikolay V. Dokholyan, Svetlana A. Shabalina and Luda Diatchenko was originally published electronically on the publisher’s internet portal on October 3, 2020 without open access. With the author(s)’ decision to opt for Open Choice the copyright of the article changed on October 27, 2020 to © The Author(s) 2020 and the article is forthwith distributed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, https://creativecommons.org/licenses/by/4.0/ .

RNA sequencing using next-generation sequencing (NGS, RNA-Seq) technologies is currently the standard approach for gene expression profiling, particularly for large-scale high-throughput studies. NGS technologies comprise short-read RNA-Seq (dominated by Illumina) and long-read RNA-Seq technologies provided by Pacific Bioscience (PacBio) and Oxford Nanopore Technologies (ONT). Although short-read sequencing technologies are the most widely used, long-read technologies are increasingly becoming the standard approach for de novo transcriptome assembly and isoform expression quantification due to the complex nature of the transcriptome which consists of variable lengths of transcripts and multiple alternatively spliced isoforms for most genes. In this chapter, we describe experimental procedures for library preparation, sequencing, and associated data analysis approaches for PacBio and ONT with a major focus on full length cDNA synthesis, de novo transcriptome assembly, and isoform quantification.

The delta-opioid receptor (DOPr) participates in mediating the effects of opioid analgesics. However, no selective agonists have entered clinical care despite potential to ameliorate many neurological and psychiatric disorders. In an effort to address the drug development challenges, the functional contribution of receptor isoforms created by alternative splicing of the three-exonic coding gene, OPRD1, has been overlooked. We report that the gene is transcriptionally more diverse than previously demonstrated, producing novel protein isoforms in humans and mice. We provide support for the functional relevance of splice variants through context-dependent expression profiling (tissues, disease model) and conservation of the transcriptional landscape in closely related vertebrates. The conserved alternative transcriptional events have two distinct patterns. First, cassette exon inclusions between exons 1 and 2 interrupt the reading frame, producing truncated receptor fragments comprising only the first transmembrane (TM) domain, despite the lack of exact exon orthologues between distant species. Second, a novel promoter and transcriptional start site upstream of exon 2 produces a transcript of an N-terminally truncated 6TM isoform. However, a fundamental difference in the exonic landscaping as well as translation and translation products poses limits for modelling the human DOPr receptor system in mice.

RNA sequencing using next-generation sequencing (NGS, RNA-Seq) technologies is currently the standard approach for gene expression profiling, particularly for large-scale high-throughput studies. NGS technologies comprise short-read RNA-Seq (dominated by Illumina) and long-read RNA-Seq technologies provided by Pacific Bioscience (PacBio) and Oxford Nanopore Technologies (ONT). Although short-read sequencing technologies are the most widely used, long-read technologies are increasingly becoming the standard approach for de novo transcriptome assembly and isoform expression quantification due to the complex nature of the transcriptome which consists of variable lengths of transcripts and multiple alternatively spliced isoforms for most genes. In this chapter, we describe experimental procedures for library preparation, sequencing, and associated data analysis approaches for PacBio and ONT with a major focus on full length cDNA synthesis, de novo transcriptome assembly, and isoform quantification.

To assess the performance of the Oxford Nanopore Technologies MinION sequencing platform, cDNAs from the External RNA Controls Consortium (ERCC) RNA Spike-In mix were sequenced. This mix mimics mammalian mRNA species and consists of 92 polyadenylated transcripts with known concentration. cDNA libraries were generated using a template switching protocol to facilitate the direct comparison between different sequencing platforms. The MinION performance was assessed for its ability to sequence the cDNAs directly with good accuracy in terms of abundance and full length. The abundance of the ERCC cDNA molecules sequenced by MinION agreed with their expected concentration. No length or GC content bias was observed. The majority of cDNAs were sequenced as full length. Additionally, a complex cDNA population derived from a human HEK-293 cell line was sequenced on an Illumina HiSeq 2500, PacBio RS II and ONT MinION platforms. We observed that there was a good agreement in the measured cDNA abundance between PacBio RS II and ONT MinION (rpearson = 0.82, isoforms with length more than 700bp) and between Illumina HiSeq 2500 and ONT MinION (rpearson = 0.75). This indicates that the ONT MinION can sequence quantitatively both long and short full length cDNA molecules.

Myogenesis is a tightly controlled process involving the transcriptional activation and repression of thousands of genes. Although many components of the transcriptional network regulating the later phases of myogenesis have been identified, relatively few studies have described the transcriptional landscape during the first 24 h, when myoblasts commit to differentiate. Through dense temporal profiling of differentiating C2C12 myoblasts, we identify 193 transcriptional regulators (TRs) whose expression is significantly altered within the first 24 h of myogenesis. A high-content shRNA screen of 77 TRs involving 427 stable lines identified 42 genes whose knockdown significantly inhibits differentiation of C2C12 myoblasts. Of the TRs that were differentially expressed within the first 24 h, over half inhibited differentiation when knocked down, including known regulators of myogenesis ( Myod1, Myog, and Myf5), as well as 19 TRs not previously associated with this process. Surprisingly, a similar proportion (55%) of shRNAs targeting TRs whose expression did not change also inhibited C2C12 myogenesis. We further show that a subset of these TRs inhibits myogenesis by downregulating expression of known regulatory and structural proteins. Our findings clearly illustrate that several TRs critical for C2C12 myogenesis are not differentially regulated, suggesting that approaches that focus functional studies on differentially-expressed transcripts will fail to provide a comprehensive view of this complex process.

There are two major array formats used in life science research and biomedical analysis. The first is the microwell plate format with millimeter-sized wells each with microliter capacity addressed individually and repeatedly during experiments. The second is the microarray format with micrometer-sized spots that are patterned initially but not addressable individually thereafter. Here, we present an addressable nanoliter-well plate with micrometer sized wells that combines the advantages of the two array formats. The nanowells are formed by reversibly sealing a steel stencil featuring an array of micrometer-scale openings to an optically transparent substrate. The nanowells have a capacity of approximately 1 nL, are approximately 140 microm in diameter, and are arrayed at a density of 1600 wells cm(-2). A soft polymer is patterned photolithographically around each opening so as to form a microgasket for pressure sensitive, liquid tight, and reversible sealing to any type of smooth substrate, either hydrophilic or hydrophobic. The rigidity of the steel prevents the distortion that occurs in soft, all-polymeric stencils and permits accurate registration across the entire array, which in turn allows for repeated, individual addressing of wells using an inkjet spotter. The stencils are used to pattern cells, make protein microarrays, and create nanowells on surfaces to study reverse transfection by first spotting plasmids encoding fluorescent proteins into the wells, seeding cells, and monitoring the transfection of the cells in real time using time-lapse imaging. The hybrid elastomer-metal stencils (HEMSs) are versatile and useful for multiplexed analysis of drugs, biomolecules, and cells with microarray density.

Aim PacBio SMRT sequencing technology is considered new approach to HLA typing. HLA class I genotyping has been reported using PacBio SMRT technology but little has been published to investigate the feasibility and the performance of the SMRT sequencing technology for both HLA class I and class II genes. Methods We report here genotyping of 16 DNA samples, 5 loci (HLA-A, B, C, DRB1 and DQB1). The amplicons corresponding to the different genes were first pooled for each sample. The pooled genes from different samples were then pooled again after barcoded SMRTbell PacBio library construction. After sequencing an independent molecule consensus approach was applied. Whole gene amplicons were generated for both HLA class I and class II genes using Omixon Holotype protocol and were sequenced by PacBio SMRT sequencing as well as using Illumina. Bioinformatic algorithm and analysis were important to result in quality consensus sequences and allele assignment. Results PacBio consensus sequences using at least 75 independent molecules were obtained for each locus and each sample. Balance between class I and class II genes of different length is important as imbalanced multiplexing may affect the typing results. We have shown for the first time that concurrent HLA typing of both class I and class II genes using the same sequencing SMRTcell is possible. Conclusion Using in house allele assignment method, our PacBio analysis was in perfect agreement with the reference samples sequenced by Illumina (Omixon Twin protocol) to the 3rd field. The in house allele assignment method has the potential to resolve up to the 4th field of HLA genotyping.

With the increasing popularity of cloud computing, Hadoop has become a widely used open source cloud computing framework for large scale data processing. However, few efforts have been made to demonstrate the applicability of Hadoop to various real-world application scenarios in fields other than server side computations such as web indexing, etc. In this paper, we use the Hadoop cloud computing framework to develop a user application that allows processing of scientific data on clouds. A simple extension to Hadoop’s MapReduce is described which allows it to handle scientific data processing problems with arbitrary input formats and explicit control over how the input is split. This approach is used to develop a Hadoop-based cloud computing application that processes sequences of microscope images of live cells, and we test its performance. It is discussed how the approach can be generalized to more complicated scientific data processing problems.

A multilevel aggregation method is applied to the problem of segmenting live cell bright field microscope images. The method employed is a variant of the so-called “Segmentation by Weighted Aggregation” technique, which itself is based on Algebraic Multigrid methods. The variant of the method used is described in detail, and it is explained how it is tailored to the application at hand. In particular, a new scale-invariant “saliency measure” is proposed for deciding when aggregates of pixels constitute salient segments that should not be grouped further. It is shown how segmentation based on multilevel intensity similarity alone does not lead to satisfactory results for bright field cells. However, the addition of multilevel intensity variance (as a measure of texture) to the feature vector of each aggregate leads to correct cell segmentation. Preliminary results are presented for applying the multilevel aggregation algorithm in space time to temporal sequences of microscope images, with the goal of obtaining space-time segments (“object tunnels”) that track individual cells. The advantages and drawbacks of the space-time aggregation approach for segmentation and tracking of live cells in sequences of bright field microscope images are presented, along with a discussion on how this approach may be used in the future work as a building block in a complete and robust segmentation and tracking system.

Background Current methods of measuring transcription in high-throughput have led to significant improvements in our knowledge of transcriptional regulation and Systems Biology. However, endpoint measurements obtained from methods that pool populations of cells are not amenable to studying time-dependent processes that show cell heterogeneity. Results Here we describe a high-throughput platform for measuring transcriptional changes in real time in single mammalian cells. By using reverse transfection microarrays we are able to transfect fluorescent reporter plasmids into 600 independent clusters of cells plated on a single microscope slide and image these clusters every 20 minutes. We use a fast-maturing, destabilized and nuclear-localized reporter that is suitable for automated segmentation to accurately measure promoter activity in single cells. We tested this platform with synthetic drug-inducible promoters that showed robust induction over 24 hours. Automated segmentation and tracking of over 11 million cell images during this period revealed that cells display substantial heterogeneity in their responses to the applied treatment, including a large proportion of transfected cells that do not respond at all. Conclusions The results from our single-cell analysis suggest that methods that measure average cellular responses, such as DNA microarrays, RT-PCR and chromatin immunoprecipitation, characterize a response skewed by a subset of cells in the population. Our method is scalable and readily adaptable to studying complex systems, including cell proliferation, differentiation and apoptosis.