Addressing noise in co-expression network construction.

Gene co-expression networks (GCNs) provide multiple benefits to molecular research including hypothesis generation and biomarker discovery. Transcriptome profiles serve as input for GCN construction and are derived from increasingly larger studies with samples across multiple experimental conditions, treatments, time points, genotypes, etc. Such experiments with larger numbers of variables confound discovery of true network edges, exclude edges and inhibit discovery of context (or condition) specific network edges. To demonstrate this problem, a 475-sample dataset is used to show that up to 97% of GCN edges can be misleading because correlations are false or incorrect. False and incorrect correlations can occur when tests are applied without ensuring assumptions are met, and pairwise gene expression may not meet test assumptions if the expression of at least one gene in the pairwise comparison is a function of multiple confounding variables. The 'one-size-fits-all' approach to GCN construction is therefore problematic for large, multivariable datasets. Recently, the Knowledge Independent Network Construction toolkit has been used in multiple studies to provide a dynamic approach to GCN construction that ensures statistical tests meet assumptions and confounding variables are addressed. Additionally, it can associate experimental context for each edge of the network resulting in context-specific GCNs (csGCNs). To help researchers recognize such challenges in GCN construction, and the creation of csGCNs, we provide a review of the workflow.

GEMmaker: process massive RNA-seq datasets on heterogeneous computational infrastructure.

BACKGROUND: Quantification of gene expression from RNA-seq data is a prerequisite for transcriptome analysis such as differential gene expression analysis and gene co-expression network construction. Individual RNA-seq experiments are larger and combining multiple experiments from sequence repositories can result in datasets with thousands of samples. Processing hundreds to thousands of RNA-seq data can result in challenges related to data management, access to sufficient computational resources, navigation of high-performance computing (HPC) systems, installation of required software dependencies, and reproducibility. Processing of larger and deeper RNA-seq experiments will become more common as sequencing technology matures. RESULTS: GEMmaker, is a nf-core compliant, Nextflow workflow, that quantifies gene expression from small to massive RNA-seq datasets. GEMmaker ensures results are highly reproducible through the use of versioned containerized software that can be executed on a single workstation, institutional compute cluster, Kubernetes platform or the cloud. GEMmaker supports popular alignment and quantification tools providing results in raw and normalized formats. GEMmaker is unique in that it can scale to process thousands of local or remote stored samples without exceeding available data storage. CONCLUSIONS: Workflows that quantify gene expression are not new, and many already address issues of portability, reusability, and scale in terms of access to CPUs. GEMmaker provides these benefits and adds the ability to scale despite low data storage infrastructure. This allows users to process hundreds to thousands of RNA-seq samples even when data storage resources are limited. GEMmaker is freely available and fully documented with step-by-step setup and execution instructions.

Phosphine Mediated Conjugation of S-Nitrosothiols and Aldehydes.

S-Nitrosothiols (SNO) and their biological implications as an important post-translational modification are under active investigation. In our work on bioorthogonal reactions of protein SNO we have uncovered chemistry of this functionality that shows synthetic promise. Herein we report a phosphine-mediated reaction between SNO and aldehydes to form thioimines. A simple synthesis of benzoisothiazole based on this reaction is presented.

Named Data Networking for Genomics Data Management and Integrated Workflows.

Advanced imaging and DNA sequencing technologies now enable the diverse biology community to routinely generate and analyze terabytes of high resolution biological data. The community is rapidly heading toward the petascale in single investigator laboratory settings. As evidence, the single NCBI SRA central DNA sequence repository contains over 45 petabytes of biological data. Given the geometric growth of this and other genomics repositories, an exabyte of mineable biological data is imminent. The challenges of effectively utilizing these datasets are enormous as they are not only large in the size but also stored in geographically distributed repositories in various repositories such as National Center for Biotechnology Information (NCBI), DNA Data Bank of Japan (DDBJ), European Bioinformatics Institute (EBI), and NASA's GeneLab. In this work, we first systematically point out the data-management challenges of the genomics community. We then introduce Named Data Networking (NDN), a novel but well-researched Internet architecture, is capable of solving these challenges at the network layer. NDN performs all operations such as forwarding requests to data sources, content discovery, access, and retrieval using content names (that are similar to traditional filenames or filepaths) and eliminates the need for a location layer (the IP address) for data management. Utilizing NDN for genomics workflows simplifies data discovery, speeds up data retrieval using in-network caching of popular datasets, and allows the community to create infrastructure that supports operations such as creating federation of content repositories, retrieval from multiple sources, remote data subsetting, and others. Named based operations also streamlines deployment and integration of workflows with various cloud platforms. Our contributions in this work are as follows 1) we enumerate the cyberinfrastructure challenges of the genomics community that NDN can alleviate, and 2) we describe our efforts in applying NDN for a contemporary genomics workflow (GEMmaker) and quantify the improvements. The preliminary evaluation shows a sixfold speed up in data insertion into the workflow. 3) As a pilot, we have used an NDN naming scheme (agreed upon by the community and discussed in Section 4) to publish data from broadly used data repositories including the NCBI SRA. We have loaded the NDN testbed with these pre-processed genomes that can be accessed over NDN and used by anyone interested in those datasets. Finally, we discuss our continued effort in integrating NDN with cloud computing platforms, such as the Pacific Research Platform (PRP). The reader should note that the goal of this paper is to introduce NDN to the genomics community and discuss NDN's properties that can benefit the genomics community. We do not present an extensive performance evaluation of NDN-we are working on extending and evaluating our pilot deployment and will present systematic results in a future work.

A Fixed Cohort Field Study of Gene Expression in Circulating Leukocytes From Dairy Cows With and Without Mastitis.

Specifically designed gene expression studies can be used to prioritize candidate genes and identify novel biomarkers affecting resilience against mastitis and other diseases in dairy cattle. The primary goal of this study was to assess whether specific peripheral leukocyte genes expressed differentially in a previous study of dairy cattle with postpartum disease, also would be expressed differentially in peripheral leukocytes from a diverse set of different dairy cattle with moderate to severe clinical mastitis. Four genes were selected for this study due to their differential expression in a previous transcriptomic analysis of circulating leukocytes from dairy cows with and without evidence of early postpartum disease. An additional 15 genes were included based on their cellular, immunologic, and inflammatory functions associated with resistance and tolerance to mastitis. This fixed cohort study was conducted on a conventional dairy in Washington state. Cows >50 days in milk (DIM) with mastitis (n = 12) were enrolled along with healthy cows (n = 8) selected to match the DIM and lactation numbers of mastitic cows. Blood was collected for a complete blood count (CBC), serum biochemistry, leukocyte isolation, and RNA extraction on the day of enrollment and twice more at 6 to 8-days intervals. Latent class analysis was performed to discriminate healthy vs. mastitic cows and to describe disease resolution. RNA samples were processed by the Primate Diagnostic Services Laboratory (University of Washington, Seattle, WA). Gene expression analysis was performed using the Nanostring System (Nanostring Technologies, Seattle, Washington, USA). Of the four genes (C5AR1, CATHL6, LCN2, and PGLYRP1) with evidence of upregulation in cows with mastitis, three of those genes (CATHL6, LCN2, and PGLYRP1) were investigated due to their previously identified association with postpartum disease. These genes are responsible for immunomodulatory molecules that selectively enhance or alter host innate immune defense mechanisms and modulate pathogen-induced inflammatory responses. Although further research is warranted to explain their functional mechanisms and bioactivity in cattle, our findings suggest that these conserved elements of innate immunity have the potential to bridge disease states and target tissues in diverse dairy populations.

S-Nitrosothiols: chemistry and reactions.

The formation of S-nitrosothiols (SNO) in protein cysteine residues is an important post-translational modification elicited by nitric oxide (NO). This process is involved in virtually every class of cell signaling and has attracted considerable attention in redox biology. On the other hand, their unique structural characters make SNO potentially useful synthons. In this review, we summarized the fundamental chemical/physical properties of SNO. We also highlighted the reported chemical reactions of SNO, including the reactions with phosphine reagents, sulfinic acids, various nucleophiles, SNO-mediated radical additions, and the reactions of acyl SNO species.

Proline-based phosphoramidite reagents for the reductive ligation of S-nitrosothiols.

S-Nitrosothiols (RSNOs) have many biological implications but are rarely used in organic synthesis. In this work we report the development of proline-based phosphoramidite substrates that can effectively convert RSNOs to proline-based sulfenamides through a reductive ligation process. A unique property of this method is that the phosphine oxide moiety on the ligation products can be readily removed under acidic conditions. In conjugation with the facile preparation of RSNOs from the corresponding thiols (RSHs), this method provides a new way to prepare proline-based sulfenamides from simple thiol starting materials.

Hydrogen sulfide (H2S) releasing agents: chemistry and biological applications.

Hydrogen sulfide (H2S) is a newly recognized signaling molecule with very potent cytoprotective actions. The fields of H2S physiology and pharmacology have been rapidly growing in recent years, but a number of fundamental issues must be addressed to advance our understanding of the biology and clinical potential of H2S in the future. Hydrogen sulfide releasing agents (also known as H2S donors) have been widely used in these fields. These compounds are not only useful research tools, but also potential therapeutic agents. It is therefore important to study the chemistry and pharmacology of exogenous H2S and to be aware of the limitations associated with the choice of donors used to generate H2S in vitro and in vivo. In this review we summarized the developments and limitations of currently available donors including H2S gas, sulfide salts, garlic-derived sulfur compounds, Lawesson's reagent/analogs, 1,2-dithiole-3-thiones, thiol-activated donors, photo-caged donors, and thioamino acids. Some biological applications of these donors were also discussed.

A proline-based phosphine template for Staudinger ligation.

A proline-based phosphine template enabling a rapid Staudinger ligation of azide-containing substrates under mild conditions is reported. This reaction has a second-order rate constant of 1.12 M(-1) s(-1). It is expected that the proline-based Staudinger ligation strategy will be a useful method for bioconjugation and proline based peptide coupling.