BackgroundGiven an organism to study with RNA-seq, it may have a reference genome or not. In either case, why can't we annotate everything else to the quality of the human or mouse annotations?Considerations in this review will include software, pipelines, problems and best practices.WorkflowThe overall workflow of data->results will serve as the organization for the paper. The focus is not about each step of this workflow (see Conesa et al. 2016). Instead, how will each step affect the annotation?1. Data acquisition: Library prep:Effect of different library preps – both (comment 6 in discussion)    - poly(A)-selection    - ribo-zero (ribosomal subtraction)Type of RNA    - Coding    - Non_coding: Non-coding RNA (comment 9 in discussion)RNA-seq Data type:    - ONP    - PacBio    - IlluminaCost benefits of PacBio / Oxford Nanopore sequencing (24e,      2. Pre-processing :Filtration of RNAseq transcriptomes – both (7,- quality trimming- adapter trimmingBest practices (Matt McManus' paper): Less trimming, the better- diginorm: helps with low-coverage discovery vs. reference-based will cause to be more fragmented, and sometimes lose junctions between exons (unpublished horse transcriptome)3. Assembly, split the paper into 2 categories:    - reference-based: quality of genome is limiting factor, concept needs to be developed that says if your genome quality is good, then you should do reference-based mapping, or if your quality is poor, then do de novo assembly Effect of genome quality on transcriptome assembly – both (4,5,24a,27Review of Genome-based annotation pipelines (3,15, - pipelines: e.g. Maker & PASA    - de novo assembly4. Annotation: this is the meat of what we're talking about in the paper: How to give your gene a name (12, 13,16,18,21,22,23It's a mess.    - spotlight the mess    - plan for how to solving the messSoftware:  dammit, Trinotate5. Databases and Archiving- No universal formatting for description column in gtf, affects downstream analysesMajor genome annotation databases (2,19,26, 24c,29Functional annotations (8,11,14,20,24b,28, 24f, 24gAssignments for everyone:Write down examples faced with trouble with annotation:- getting (archiving)- applying- using downstreamIf you were able to solve, what is the best way to go around?Coordinate in groups:reference-based:- Daniel- Erica- Husseinde novo assembly:- Lisa- Harriet- Tessa- Camille

Target? http://www.nature.com/nature/careers/

We consider two types of graphs: weighted and unweighted:UnweightedAdjacency matrix will require Weighted:

Some text and \cite{Boettiger_2012a}

I started a Twitter account in 2010, during my first year of graduate school, because I was told I needed to. Not by my graduate program, but by the Society for Neuroscience (SfN). I had just been accepted to be an official “neuro-blogger” for the SfN conference – an annual gathering that draws over 30,000 attendees. The requirements for outreach were minimal: at least one blog post per day during the conference, preferably within our assigned “theme”. Additional postings were encouraged and Twitter accounts were mandatory. 

Author contributions (alphabetical by last name) - Dylan Alexander Carlin [2]: molecular cloning, designed experiments, wrote software used in analysis, analyzed data, Rosetta modeling, FoldX modeling, machine learning, wrote paper - Ryan Caster [1]: characterized expression for mutants - Bill Chan [1]: characterized Tm for mutants, analyzed data, contributed to paper - Natalie Damrau [1]: characterized mutants - Siena Hapig-Ward [1]: characterized Tm and kinetic constants, analyzed data, drew figures, contributed to paper - Mary Riley [1]: characterized mutants - Justin B. Siegel [1,3,4]: PI Author affiliations: 1. Genome Center, University of California, Davis CA, USA 2. Biophysics Graduate Group, University of California, Davis CA, USA 3. Department of Chemistry, University of California, Davis CA, USA 4. Department of Biochemistry & Molecular Medicine, University of California, Davis CA, USA

EDUCATION University of California, Davis - Ph.D. Microbiology (2012) Dissertation Title: Exploring Microbial Community Composition and Genome Evolution Using Environmental and Comparative Genomics ##University of Texas, Arlington - M.S. Quantitative Biology (2001) Thesis Title: Worldwide Phylogeny of the Damselfly Genus Ischnura Based on Mitochondrial Cytochrome Oxidase II and Cytochrome B Sequence Data ##University of New Orleans - B.S. Biology (1995)

MOTIVATION A single microbial community can be composed of many thousands of species, and the tools most commonly used (pie charts and stacked bar graphs) to visualize the relative abundances of species in communities are inadequate. The human brain is not adept at estimating the areas of wedges in a pie or rectangles in a bar, and if it were, the color palette and graph size required to faithfully represent the relative abundances of thousands of species of even a single community would be prohibitively large. There is a great need to develop more intuitive visualization tools, especially for comparing microbial community composition across a large number of samples. Fortunately, human evolution, via natural selection has engineered a solution to this problem. The human brain has a region, the fusiform face area, that is entirely devoted to facial recognition. This region of the brain allows us to process a very complex image in an instant, requiring minimal decomposition into component parts. Instead, faces are perceived holistically, as a gestalt. Faces are infinitely variable, and we can quickly pick up on even very subtle differences and similarities between them.

ABSTRACT Background: While significant attention has been paid to the potential risk of pathogenic microbes aboard crewed spacecraft, the non-pathogenic microbes in these habitats have received less consideration. Preliminary work has demonstrated that the interior of the International Space Station (ISS) has a microbial community resembling those of built environments on earth. Here we report results of sending 48 bacterial strains, collected from built environments on earth, for a growth experiment on the ISS. This project was a component of Project MERCCURI (Microbial Ecology Research Combining Citizen and University Researchers on ISS). Results: Of the 48 strains sent to the ISS, 45 of them showed similar growth in space and on earth using a relative growth measurement adapted for microgravity. The vast majority of species tested in this experiment have also been found in culture-independent surveys of the ISS. Only one bacterial strain showed significantly different growth in space. _Bacillus safensis_ JPL-MERTA-8-2 grew 60% better in space than on earth. Conclusions: The majority of bacteria tested were not affected by conditions aboard the ISS in this experiment (e.g., microgravity, cosmic radiation). Further work on _Bacillus safensis_ could lead to interesting insights on why this strain grew so much better in space.

INTRODUCTION [Probably start with modeling] A fundamental goal of biochemistry is understanding the intricate relationship between a protein sequence, its structure, and its function. Atomic-level knowledge of enzymes in particular has proven immensely challenging. Because we don't understand how enzymes work, the field of synthetic biology is unable to harness the catalytic power of enzymes for arbitrary chemical reactions. Previous efforts to computationally model the relationship between the thermal stability of enzymes and point mutations in enzyme systems have relied on the addition of evolutionary information (Thompson) and, see CASP, have had success in creating models of proteins to an accuracy of X previously-believed to be impossible to model accurately. People have tried to model the biophysical constraints on protein evolution but there is rarely any actual mutational data to draw from (only the "fossil record" of known holomologues sequences and the evolutionary history of the organisms that we see a snapshot of) Here, we measure the thermal denaturation temperature of 117 mutants of a family 1 glycoside hydrolase, BlgB. After generating models of each mutant, we combine the experimental data with 45 features (e.g., total system energy, ligand energy). A machine learning algorithm trained on the data is used to make a prediction for the thermal stability of 15 point mutants evenly sampled from the single nucleotide polymorphism--accessible space and 15 point mutants evenly sampled from the elastic net model. The predictive model achieved a Pearson correlation coefficient of [...] in our tests, showing that [...] Bagel uses residues E164, E353, and Y295 as catalytic residues [Bagel enzyme in general, represents a common fold and evolutionary conserved function and diverse sequences that all fold the same way and have the same function, just residing in different organisms] Evolutionary constraints limit protein evolvability in the sense that only certain mutations are physically possible (SNP-accessible, not divert folding trajectory)

Molecular cloning and sequencing of designed hydratase enzymes Synthetic genes coding for 12 designed hydratase proteins based on 5 naturally-occuring enzymes were synthesized as linear dsDNA by Life Technologies. Constructs were cloned into expression vector pET29b(+) using Gibson assembly. TABLE 1 shows the progress of 12 constructs. Sequence verification for 10 constructs is in progress, and 2 constructs are currently sequence verified. Protein expression and purification of verified constructs Small-scale protein expresion For small-scale expression experiments, 2 sequence-verified constructs were transformed into _Escherichia coli_ BLR, and single colonies were used to inoculate 25 mL of Terrific Broth in 50 mL Falcon tubes. In parallel, cells were grown in 25 mL cultures in 250 mL flasks. No difference in pellet weights or soluble protein expression as assessed by SDS-PAGE was observed (data not shown) between these two growth methods. Large-scale protein expresion Currently, we are testing the expression of these proteins in large-scale 500 mL cultures to see if higher yields can be obtained. We expect to have small- and large-scale expression data for each of these 12 proteins in the next quarterly report.

PROJECT SUMMARY (1 PAGE) Due: January 25, 2016 at 5 PM (local time) DEB - Biodiversity: Discovery & Analysis Cluster Solicitation: http://www.nsf.gov/pubs/2015/nsf15609/nsf15609.htm Cluster description: http://www.nsf.gov/funding/pgm_summ.jsp?pims_id=503666&org=DEB&from=home Overview The broad goal with this proposal is to increase the overall knowledge of the true diversity of microbial eukaryotes by identifying and culturing microeukaryotes from seagrass beds. Microorganisms, and specifically marine microbial eukaryotes, represent an underexplored area of diversity. Microbial eukaryotes are known to be important on a number of trophic levels in the marine system CITE, and microbial eukaryotes found in seagrass beds likely contribute to their tremendous biodiversity and roles as important players in nutrient cycling and carbon sequestration in the oceans. We will use a combination of sequencing and culturing techniques to (1) characterize microeukaryotes in a global census of the seagrass _Zostera marina_, (2) Explore microbial eukaryotic diversity across the Order Alismatales, including the 3 separate lineages of seagrasses and their freshwater and brackish relatives, and (3) Create a publicly available culture collection of microbial eukaryotes from _Zostera marina_ samples from Bodega Bay, CA. Intellectual Merit Microorganisms comprise the majority of diversity on Earth. Traditionally classified using morphological approaches, the advent of sequence data has dramatically altered our views of microbial evolution and diversity. Specifically, high throughput sequencing technologies have enabled us to explore multiple genes and genomes from microorganisms, giving us insight into genome complexity and function in these unseen organisms. As a result microbial ecologists are finding themselves in uncharted territory as they analyze large data sets full of "unclassified" organisms, and it now clear that microorganisms are much more diverse than previously thought. Although certain pathogenic microeukaryotes have been studied in great detail (ex. _giardia_, see ) for review, environmental microeukaryotes, specifically marine microeukatyores, are grossly uncharacterized despite their important functional roles in their ecosystems . Novel marine microeukaryotic lineages have previously been found at all phylogenetic scales ; however, many of these novel organisms are still a mystery to us as they have yet to be cultured. It is estimated that the total diversity of microbial eukaryotes is much higher than what we currently have in culture . Seagrasses are a unique system in which to explore marine microbial eukaryotic diversity. These important marine angiosperms provide habitat and food to many rare and endemic species, and contain tremendous levels of biodiversity that has currently only been characterized at the macrobe level . Seagrasses are known to be important contributors to biogeochemical processes within the ocean and are one of the largest carbon sinks on earth, sequestering carbon 35X faster than Tropical Rainforests . Given their importance in the complex marine food web and their contributions to nutrient cycling within the oceans, we hypothesize that seagrass-associated marine microbial eukaryotes are important to both the high levels of macrobe biodiversity within seagrass beds and to their role in nutrient cycling and carbon sequestration in the ocean ecosystem. We propose to perform a global census of microbial eukaryotes found in association with the leaves, roots, and sediment of the seagrass _Zostera marina_. We will then expand our investigation to census the microbial eukaryotes found in association with plants across the Order Alismatales, which includes three independent lineages of seagrasses. Concurrently with the afformentioned censuses, we will establish a culture collection of microbial eukaryotes found associated with _Zostera marina_ from Bodega Bay, California. We are uniquely positioned to be successful at the proposed research; using funds provided by the Gordon and Betty Moore Foundation, we have already established a program to explore bacterial diversity within seagrass beds, and have completed the majority of field work and formed ongoing collaborations with other seagrass researchers from both the Zostera Experimental Network (ZEN) and other research institutions. Broader Impacts The project we propose here is a global interdisciplinary collaboration that will result in increased knowledge of the biodiversity of an understudied group of organisms from an important marine ecosystem. The preposed project is the first to explore seagrass-associated microbial eukaryotes using both sequence and culture based methods, and will generate large amounts of publicly available sequence data and numerous new entries of novel marine organisms to culture collections. The project we are proposing will include a large outreach component both at the local level (undergraduate researchers, high school students) and the global level (website, collaborators). Undergraduates and local high school students will be intimately involved in creating the culture collection and our progress will be transparently available on our lab website.

Robert Langer George Whitesides Charles Lieber Joseph Wang Xi Yin Howard Stone Kaustav Banerjee Li-Yi Wei Zhenan Bao David Weitz David Quere

Nature Science Proceedings of the National Academy of Sciences Nature Communications Nature Physics Physical Review Letters Applied Physics Letters Nature Chemistry Journal of American Chemistry Society Analytical Chemistry Nature Materials Advanced Materials Advanced Functional Materials Nature Nanotechnology Nano Letters ACS Nano Lab on a Chip Physics of Fluids Journal of Fluid Mechanics

DE NOVO DESIGN OF EPOXIDE REDUCTASE "NO GO" DECISION Our proposal for quarter 8 included a set of experiments that would allow us to determine if we should continue with the de novo design of the epoxide reductase (pathway 2). We established "go" and "no go" criteria for each option. After performing the planned experiments (results described in detail below), our verdict is "no go" for continued efforts to engineer an expoxide reductase.

ABSTRACT Background Modern advances in sequencing technology have enabled the census of microbial members of many natural ecosystems. Recently, attention is increasingly being paid to the microbial residents of human-made, built ecosystems, both private (homes) and very public (subways, office buildings, and hospitals). Here, we report results of the characterization of the microbial ecology of a singular built environment, the International Space Station (ISS). This ISS sampling involved the collection and microbial analysis (via 16S rDNA PCR) of 15 samples swabbed from surfaces onboard the ISS. This sampling is a component of Project MERCCURI - a collaborative effort of the "microbiology of the Built Environment network" (microBEnet) project, Science Cheerleaders, NanoRacks, Space Florida, and Scistarter.com. Learning more about the microbial inhabitants of the "buildings" in which we travel through space will take on increasing importance, as plans for human exploration and colonization of the solar system come to fruition. Methodology/Principal Findings Sterile swabs were used to sample 15 surfaces onboard the ISS. The sites sampled were designed to be analogous to samples collected for 1) the Wildlife of Our Homes project and 2) a study of cell phones and shoes that were concurrently being collected for another component of Project MERCCURI. Sequencing of the 16S rRNA genes amplified from DNA extracted from each swab was used to produce a "census" of the microbes present on each surface sampled. We compared the microbes found on the ISS swabs to those from both the Earth homes and the Human Microbiome Project. Conclusions/Significance While significantly different from homes on Earth and the Human Microbiome Project samples analyzed here, the microbial community composition on the ISS was more similar to home surfaces than to the human microbiome samples. The ISS surfaces are species-rich with 1036-4294 operational taxonomic units (OTUs per sample). There was no discernible biogeography of microbes on the 15 ISS surfaces, although this may be a reflection of the small sample size we were able to obtain.

ABSTRACT Background Modern advances in sequencing technology have enabled the census of microbial members of many natural ecosystems. Recently, attention is increasingly being paid to the microbial residents of human-made, built ecosystems, both private (homes) and very public (subways, office buildings, and hospitals). Here, we report results of the characterization of the microbial ecology of a singular built environment, the International Space Station. This sampling involved the collection and microbial analysis (via 16S rDNA PCR) of 15 samples swabbed from surfaces onboard the International Space Station. This sampling is a component of Project MERCCURI (Microbial Ecology Research Combining Citizen and University Researchers on ISS) - a collaborative effort of the "microbiology of the Built Environment network" (microBE.net) project, Science Cheerleaders, NanoRacks, Space Florida, and Scistarter.com. Learning more about the microbial inhabitants of the "buildings" in which we travel through space will take on increasing importance, as plans for human exploration and colonization of the solar system come to fruition. Results Sterile swabs were used to sample 15 surfaces onboard the International Space Station. The sites sampled were designed to be analogous to samples collected for 1) the Wildlife of Our Homes project and 2) a study of cell phones and shoes that were concurrently being collected for another component of Project MERCCURI. Sequencing of the 16S rRNA genes amplified from DNA extracted from each swab was used to produce a "census" of the microbes present on each surface sampled. We compared the microbes found on the ISS swabs to those from both the Earth homes and the Human Microbiome Project. Conclusions While significantly different from homes on Earth and the Human Microbiome Project samples analyzed here, the microbial community composition on the International Space Station was more similar to home surfaces than to the human microbiome samples. The International Space Station surfaces are species-rich with 1036-4294 operational taxonomic units per sample. There was no discernible biogeography of microbes on the 15 surfaces, although this may be a reflection of the small sample size we were able to obtain.

ABSTRACT Background Submerged aquatic vegetation (SAV) are plants that are rooted in sediment and fully submerged most of the time, and have many adaptations for coping with varied salinity and osmotic conditions. We focus here on one aspect of SAV - their microbiome - which was studied in the Potomac River along a salinity gradient as the river empties into the Chesapeake Bay. The goal was to find a link between the microbial communities on different SAV species and the changing salinity across the river. Results One of the four successfully sampled sites was very different from the rest in terms of microbial community and water/sediment chemistry, clustering separately from the other sites on PCoA plots. _Methylotenera_, _Planctomyces_, _Rhodobacter_, and _Providencia_ are commonly found amongst most SAV species across all sites, and sulfur oxidizing bacteria were present in high relative abundance in the roots of _Potamogeton perfoliatus_ at one site. Conclusions Site location, which had distinct water and sediment chemistries, was a main driver of the microbial community structure. Host species of SAV and sample types (leaves or roots) also have different microbial communities. Due to the small sample size in this study, it is difficult to draw robust conclusions about the impact of salinity on microbial community structure. Therefore, future efforts will sample more thoroughly along the Potomac river, as well as along the length of the James River, which provides a nearby, parallel salinity gradient.