Genetic Modification of Herbaceous Plants for Feed and Fuel

Much of the research on the genetic modification of herbaceous plant cell walls has been conducted to improve the utilization of forages by ruminant livestock. The rumen of these animals is basically an anaerobic fermentation vat in which the microflora break down the complex polysaccharides of plant cell walls into simpler compounds that can be further digested and absorbed by the mammalian digestive system. Research on improving the forage digestibility of switchgrass, Panicum virgatum L., and other herbaceous species has demonstrated that genetic improvements can be made in forage quality that can have significant economic value. To meet future energy needs, herbaceous biomass will need to be converted into a liquid fuel, probably ethanol, via conversion technologies still under development. If feedstock quality can be genetically improved, the economics and efficiency of the conversion processes could be significantly enhanced. Improving an agricultural product for improved end product use via genetic modification requires knowledge of desired quality attributes, the relative economic value of the quality parameters in relation to yield, genetic variation for the desired traits, or for molecular breeding, knowledge of genes to suppress or add, and knowledge of any associated negative consequences of genetic manipulation. Because conversion technology is still under development, desirable plant feedstock characteristics have not been completely delineated. Some traits such as cellulose and lignin concentration will undoubtably be important. Once traits that affect biomass feedstock conversion are identified, it will be highly feasible to genetically modify the feedstock quality of herbaceous plants using both conventional and molecular breeding techniques. The use of molecular markers and transformation technology will greatly enhance the capability of breeders to modify the morphologic structure and cell walls of herbaceous species. It will be necessary to monitor gene flow to remnant wild populations of biomass plants and have strategies available to curtail gene flow if it becomes a potential problem. It will also be necessary to monitor plant survival and longterm productivity as affected by these genetic changes to herbaceous species

Modifying crops to increase cell wall digestibility

Improving digestibility of roughage cell walls will improve ruminant animal performance and reduce loss of nutrients to the environment. The main digestibility impediment for dicotyledonous plants is highly lignified secondary cell walls, notably in stem secondary xylem, which become almost non-digestible. Digestibility of grasses is slowed severely by lignification of most tissues, but these cell walls remain largely digestible. Cell wall lignification creates an access barrier to potentially digestible wall material by rumen bacteria if cells have not been physically ruptured. Traditional breeding has focused on increasing total dry matter digestibility rather than cell wall digestibility, which has resulted in minimal reductions in cell wall lignification. Brown midrib mutants in some annual grasses exhibit small reductions in lignin concentration and improved cell wall digestibility. Similarly, transgenic approaches down-regulating genes in monolignol synthesis have produced plants with reduced lignin content and improved cell wall digestibility. While major reductions in lignin concentration have been associated with poor plant fitness, smaller reductions in lignin provided measurable improvements in digestibility without significantly impacting agronomic fitness. Additional targets for genetic modification to enhance digestibility and improve roughages for use as biofuel feedstocks are discussed; including manipulating cell wall polysaccharide composition, novel lignin structures, reduced lignin/polysaccharide cross-linking, smaller lignin polymers, enhanced development of non-lignified tissues, and targeting specific cell types. Greater tissue specificity of transgene expression will be needed to maximize benefits while avoiding negative impacts on plant fitness.cauliflower mosiac virus (CaMV) 35S promote

Transcript profiling of two alfalfa genotypes with contrasting cell wall composition in stems using a cross-species platform: optimizing analysis by masking biased probes

<p>Abstract</p> <p>Background</p> <p>The GeneChip^®<it>Medicago </it>Genome Array, developed for <it>Medicago truncatula</it>, is a suitable platform for transcript profiling in tetraploid alfalfa [<it>Medicago sativa </it>(L.) subsp. <it>sativa</it>]. However, previous research involving cross-species hybridization (CSH) has shown that sequence variation between two species can bias transcript profiling by decreasing sensitivity (number of expressed genes detected) and the accuracy of measuring fold-differences in gene expression.</p> <p>Results</p> <p>Transcript profiling using the <it>Medicago </it>GeneChip^®was conducted with elongating stem (ES) and post-elongation stem (PES) internodes from alfalfa genotypes 252 and 1283 that differ in stem cell wall concentrations of cellulose and lignin. A protocol was developed that masked probes targeting inter-species variable (ISV) regions of alfalfa transcripts. A probe signal intensity threshold was selected that optimized both sensitivity and accuracy. After masking for both ISV regions and previously identified single-feature polymorphisms (SFPs), the number of differentially expressed genes between the two genotypes in both ES and PES internodes was approximately 2-fold greater than the number detected prior to masking. Regulatory genes, including transcription factor and receptor kinase genes that may play a role in development of secondary xylem, were significantly over-represented among genes up-regulated in 252 PES internodes compared to 1283 PES internodes. Several cell wall-related genes were also up-regulated in genotype 252 PES internodes. Real-time quantitative RT-PCR of differentially expressed regulatory and cell wall-related genes demonstrated increased sensitivity and accuracy after masking for both ISV regions and SFPs. Over 1,000 genes that were differentially expressed in ES and PES internodes of genotypes 252 and 1283 were mapped onto putative orthologous loci on <it>M. truncatula </it>chromosomes. Clustering simulation analysis of the differentially expressed genes suggested co-expression of some neighbouring genes on <it>Medicago </it>chromosomes.</p> <p>Conclusions</p> <p>The problems associated with transcript profiling in alfalfa stems using the <it>Medicago </it>GeneChip as a CSH platform were mitigated by masking probes targeting ISV regions and SFPs. Using this masking protocol resulted in the identification of numerous candidate genes that may contribute to differences in cell wall concentration and composition of stems of two alfalfa genotypes.</p

MiR-133b Targets Antiapoptotic Genes and Enhances Death Receptor-Induced Apoptosis

Despite the importance of microRNAs (miRs) for regulation of the delicate balance between cell proliferation and death, evidence for their specific involvement during death receptor (DR)-mediated apoptosis is scarce. Transfection with miR-133b rendered resistant HeLa cells sensitive to tumor necrosis factor-alpha (TNFα)-induced cell death. Similarly, miR-133b caused exacerbated proapoptotic responses to TNF-related apoptosis-inducing ligand (TRAIL) or an activating antibody to Fas/CD95. Comprehensive analysis, encompassing global RNA or protein expression profiling performed by microarray experiments and pulsed stable isotope labeling with amino acids in cell culture (pSILAC), led to the discovery of the antiapoptotic protein Fas apoptosis inhibitory molecule (FAIM) as immediate miR-133b target. Moreover, miR-133b impaired the expression of the detoxifying protein glutathione-S-transferase pi (GSTP1). Expression of miR-133b in tumor specimens of prostate cancer patients was significantly downregulated in 75% of the cases, when compared with matched healthy tissue. Furthermore, introduction of synthetic miR-133b into an ex-vivo model of prostate cancer resulted in impaired proliferation and cellular metabolic activity. PC3 cells were also sensitized to apoptotic stimuli after transfection with miR-133b similar to HeLa cells. These data reveal the ability of a single miR to influence major apoptosis pathways, suggesting an essential role for this molecule during cellular transformation, tumorigenesis and tissue homeostasis

Reference miRNAs for miRNAome Analysis of Urothelial Carcinomas

Background/Objective: Reverse transcription quantitative real-time PCR (RT-qPCR) is widely used in microRNA (miRNA) expression studies on cancer. To compensate for the analytical variability produced by the multiple steps of the method, relative quantification of the measured miRNAs is required, which is based on normalization to endogenous reference genes. No study has been performed so far on reference miRNAs for normalization of miRNA expression in urothelial carcinoma. The aim of this study was to identify suitable reference miRNAs for miRNA expression studies by RT-qPCR in urothelial carcinoma. Methods: Candidate reference miRNAs were selected from 24 urothelial carcinoma and normal bladder tissue samples by miRNA microarrays. The usefulness of these candidate reference miRNAs together with the commonly for normalization purposes used small nuclear RNAs RNU6B, RNU48, and Z30 were thereafter validated by RT-qPCR in 58 tissue samples and analyzed by the algorithms geNorm, NormFinder, and BestKeeper. Principal Findings: Based on the miRNA microarray data, a total of 16 miRNAs were identified as putative reference genes. After validation by RT-qPCR, miR-101, miR-125a-5p, miR-148b, miR-151-5p, miR-181a, miR-181b, miR-29c, miR-324-3p, miR-424, miR-874, RNU6B, RNU48, and Z30 were used for geNorm, NormFinder, and BestKeeper analyses that gave different combinations of recommended reference genes for normalization. Conclusions: The present study provided the first systematic analysis for identifying suitable reference miRNAs for miRNA expression studies of urothelial carcinoma by RT-qPCR. Different combinations of reference genes resulted in reliable expression data for both strongly and less strongly altered miRNAs. Notably, RNU6B, which is the most frequently used reference gene for miRNA studies, gave inaccurate normalization. The combination of four (miR-101, miR-125a-5p, miR-148b, and miR-151-5p) or three (miR-148b, miR-181b, and miR-874,) reference miRNAs is recommended for normalization

Using RNA-Seq for gene identification, polymorphism detection and transcript profiling in two alfalfa genotypes with divergent cell wall composition in stems

<p>Abstract</p> <p>Background</p> <p>Alfalfa, [<it>Medicago sativa </it>(L.) sativa], a widely-grown perennial forage has potential for development as a cellulosic ethanol feedstock. However, the genomics of alfalfa, a non-model species, is still in its infancy. The recent advent of RNA-Seq, a massively parallel sequencing method for transcriptome analysis, provides an opportunity to expand the identification of alfalfa genes and polymorphisms, and conduct in-depth transcript profiling.</p> <p>Results</p> <p>Cell walls in stems of alfalfa genotype 708 have higher cellulose and lower lignin concentrations compared to cell walls in stems of genotype 773. Using the Illumina GA-II platform, a total of 198,861,304 expression sequence tags (ESTs, 76 bp in length) were generated from cDNA libraries derived from elongating stem (ES) and post-elongation stem (PES) internodes of 708 and 773. In addition, 341,984 ESTs were generated from ES and PES internodes of genotype 773 using the GS FLX Titanium platform. The first alfalfa (<it>Medicago sativa</it>) gene index (MSGI 1.0) was assembled using the Sanger ESTs available from GenBank, the GS FLX Titanium EST sequences, and the <it>de novo </it>assembled Illumina sequences. MSGI 1.0 contains 124,025 unique sequences including 22,729 tentative consensus sequences (TCs), 22,315 singletons and 78,981 pseudo-singletons. We identified a total of 1,294 simple sequence repeats (SSR) among the sequences in MSGI 1.0. In addition, a total of 10,826 single nucleotide polymorphisms (SNPs) were predicted between the two genotypes. Out of 55 SNPs randomly selected for experimental validation, 47 (85%) were polymorphic between the two genotypes. We also identified numerous allelic variations within each genotype. Digital gene expression analysis identified numerous candidate genes that may play a role in stem development as well as candidate genes that may contribute to the differences in cell wall composition in stems of the two genotypes.</p> <p>Conclusions</p> <p>Our results demonstrate that RNA-Seq can be successfully used for gene identification, polymorphism detection and transcript profiling in alfalfa, a non-model, allogamous, autotetraploid species. The alfalfa gene index assembled in this study, and the SNPs, SSRs and candidate genes identified can be used to improve alfalfa as a forage crop and cellulosic feedstock.</p

Identification of heavy-flavour jets with the CMS detector in pp collisions at 13 TeV

Many measurements and searches for physics beyond the standard model at the LHC rely on the efficient identification of heavy-flavour jets, i.e. jets originating from bottom or charm quarks. In this paper, the discriminating variables and the algorithms used for heavy-flavour jet identification during the first years of operation of the CMS experiment in proton-proton collisions at a centre-of-mass energy of 13 TeV, are presented. Heavy-flavour jet identification algorithms have been improved compared to those used previously at centre-of-mass energies of 7 and 8 TeV. For jets with transverse momenta in the range expected in simulated $\mathrm{t}\overline{\mathrm{t}}$ events, these new developments result in an efficiency of 68% for the correct identification of a b jet for a probability of 1% of misidentifying a light-flavour jet. The improvement in relative efficiency at this misidentification probability is about 15%, compared to previous CMS algorithms. In addition, for the first time algorithms have been developed to identify jets containing two b hadrons in Lorentz-boosted event topologies, as well as to tag c jets. The large data sample recorded in 2016 at a centre-of-mass energy of 13 TeV has also allowed the development of new methods to measure the efficiency and misidentification probability of heavy-flavour jet identification algorithms. The heavy-flavour jet identification efficiency is measured with a precision of a few per cent at moderate jet transverse momenta (between 30 and 300 GeV) and about 5% at the highest jet transverse momenta (between 500 and 1000 GeV)