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Integrative analysis of multi-omics layers at single cell level is critical for accurate dissection of cell-to-cell variation within certain cell populations. Here we report scCAT-seq, a technique for simultaneously assaying chromatin accessibility and the transcriptome within the same single cell. We show that the combined single cell signatures enable accurate construction of regulatory relationships between cis-regulatory elements and the target genes at single-cell resolution, providing a new dimension of features that helps direct discovery of regulatory patterns specific to distinct cell identities. Moreover, we generate the first single cell integrated map of chromatin accessibility and transcriptome in early embryos and demonstrate the robustness of scCAT-seq in the precise dissection of master transcription factors in cells of distinct states. The ability to obtain these two layers of omics data will help provide more accurate definitions of “single cell state” and enable the deconvolution of regulatory heterogeneity from complex cell populations.

BackgroundmicroRNAs (miRNAs) are short RNA molecules that control gene expression by silencing complementary mRNA. They play a crucial role in stress response in plants, including biotic stress. Some miRNAs are known to respond to bacterial infection in Arabidopsis thaliana but it is currently unknown whether these responses are conserved in other plants and whether novel species-specific miRNAs could have a role in defense.ResultsThis work addresses the role of miRNAs in the Manihot esculenta (cassava)-Xanthomonas axonopodis pv. manihotis (Xam) interaction. Next-generation sequencing was used for analyzing small RNA libraries from cassava tissue infected and non-infected with Xam. A full repertoire of cassava miRNAs was characterized, which included 56 conserved families and 12 novel cassava-specific families. Endogenous targets were predicted in the cassava genome for many miRNA families. Some miRNA families' expression was increased in response to bacterial infection, including miRNAs known to mediate defense by targeting auxin-responding factors as well as some cassava-specific miRNAs. Some bacteria-repressed miRNAs included families involved in copper regulation as well as families targeting disease resistance genes. Putative transcription factor binding sites (TFBS) were identified in the MIRNA genes promoter region and compared to promoter regions in miRNA target genes and protein coding genes, revealing differences between MIRNA gene transcriptional regulation and other genes.ConclusionsTaken together these results suggest that miRNAs in cassava play a role in defense against Xam, and that the mechanism is similar to what's known in Arabidopsis and involves some of the same families.

28Integrative analysis of multi-omics layers at single cell level is critical for accurate dissection 29 of cell-to-cell variation within certain cell populations. Here we report scCAT-seq, a 30 technique for simultaneously assaying chromatin accessibility and the transcriptome within 31 the same single cell. We show that the combined single cell signatures enable accurate 32 construction of regulatory relationships between cis-regulatory elements and the target 33 genes at single-cell resolution, providing a new dimension of features that helps direct 34 discovery of regulatory patterns specific to distinct cell identities. Moreover, we generated 35 the first single cell integrated maps of chromatin accessibility and transcriptome in human 36 2 pre-implantation embryos and demonstrated the robustness of scCAT-seq in the precise 1 dissection of master transcription factors in cells of distinct states during embryo 2

Trans-acting small interfering RNAs (ta-siRNAs) and natural cis-antisense siRNAs (cis-nat-siRNAs) are recently discovered small RNAs (sRNAs) involved in post-transcriptional gene silencing. ta-siRNAs are transcribed from genomic loci and require processing by microRNAs (miRNAs). cis-nat-siRNAs are derived from antisense RNAs produced by the simultaneous transcription of overlapping antisense genes. Their roles in many plant processes, including pathogen response, are mostly unknown. In this work, we employed a bioinformatic approach to identify ta-siRNAs and cis-nat-siRNAs in cassava from two sRNA libraries, one constructed from healthy cassava plants and one from plants inoculated with the bacterium Xanthomonas axonopodis pv. manihotis (Xam). A total of 54 possible ta-siRNA loci were identified in cassava, including a homolog of TAS3, the best studied plant ta-siRNA. Fifteen of these loci were induced, while 39 were repressed in response to Xam infection. In addition, 15 possible cis-natural antisense transcript (cis-NAT) loci producing siRNAs were identified from overlapping antisense regions in the genome, and were found to be differentially expressed upon Xam infection. Roles of sRNAs were predicted by sequence complementarity and our results showed that many sRNAs identified in this work might be directed against various transcription factors. This work represents a significant step toward understanding the roles of sRNAs in the immune response of cassava.

Non-negative Matrix Factorization (NMF) has been widely used for the analysis of genomic data to perform feature extraction and signature identification due to the interpretability of the decomposed signatures. However, running a basic NMF analysis requires the installation of multiple tools and dependencies, along with a steep learning curve and computing time. To mitigate such obstacles, we developed ShinyButchR, a novel R/Shiny application that provides a complete NMF-based analysis workflow, allowing the user to perform matrix decomposition using NMF, feature extraction, interactive visualization, relevant signature identification and association to biological and clinical variables. ShinyButchR builds upon the also novel R package ButchR, which provides new TensorFlow solvers for algorithms of the NMF family, functions for downstream analysis, a rational method to determine the optimal factorization rank and a novel feature selection strategy. ShinyButchR is publicly hosted at https://hdsu-bioquant.shinyapps.io/shinyButchR/, the source code is available at https://github.com/hdsu-bioquant/shinyButchR, and a Docker image at https://hub.docker.com/r/hdsu/shinybutchr. ButchR is freely available at https://github.com/wurst-theke/ButchR under the GPLv3 license, and a Docker image including test datasets is available at https://hub.docker.com/r/hdsu/butchr.

The article discusses the operational and financial relationships among the channel members of a supply chain comprising of a manufacturing company and a distributor. This research simulates the financial system that enables a more accurate diagnosis of disaggregated metrics “Cash to Cash”, considering different interactions between material flow and the financial flow of the two links, manufacturer and distributor. This model considers the feedback loops between material flow models and financial models without which some interactions are lost during simulation. The proposed diagnostic method which incorporates an eclectic process re-engineering practices and state of the art of dynamic simulation with the implementation of advanced techniques of sensitivity and dynamic optimization models those are applied on the concept of stocks and flows. This methodology is used in order to analyze and improve business strategies by generating policies which help to improve cash flow of the company. To validate our model, a case study illustrating the improvement of different metrics of the supply chain is considered here. The results show that the companies have to invest in technology in order to generated strategic decision to enhance their financial metrics.