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This work was supported by the Rural & Environment Science & Analytical Services (RESAS) Division of the Scottish Government through project JHI-B1-1, the Biotechnology and Biological Sciences Research Council (BBSRC) through award BB/S015663/1 and the Royal Society through award NAF\R1\201061. MS and LHB were supported through the East of Scotland Bioscience Doctoral Training Partnership (EASTBIO DTP), funded by the BBSRC award BB/T00875X/1. YW was supported through the CSC scholarship program, China. Background : In the ten years since the initial publication of the RenSeq protocol, the method has proved to be a powerful tool for studying disease resistance in plants and providing target genes for breeding programmes. Since the initial publication of the methodology, it has continued to be developed as new technologies have become available and the increased availability of computing power has made new bioinformatic approaches possible. Most recently, this has included the development of a k-mer based association genetics approach, the use of PacBio HiFi data, and graphical genotyping with diagnostic RenSeq. However, there is not yet a unified workflow available and researchers must instead configure approaches from various sources themselves. This makes reproducibility and version control a challenge and limits the ability to perform these analyses to those with bioinformatics expertise. Results : Here we present HISS, consisting of three workflows which take a user from raw RenSeq reads to the identification of candidates for disease resistance genes. These workflows conduct the assembly of enriched HiFi reads from an accession with the resistance phenotype of interest. A panel of accessions both possessing and lacking the resistance are then used in an association genetics approach (AgRenSeq) to identify contigs positively associated with the resistance phenotype. Candidate genes are then identified on these contigs and assessed for their presence or absence in the panel with a graphical genotyping approach that uses dRenSeq. These workflows are implemented via Snakemake, a python-based workflow manager. Software dependencies are either shipped with the release or handled with conda. All code is freely available and is distributed under the GNU GPL-3.0 license. Conclusions : HISS provides a user-friendly, portable, and easily customised approach for identifying novel disease resistance genes in plants. It is easily installed with all dependencies handled internally or shipped with the release and represents a significant improvement in the ease of use of these bioinformatics analyses. Publisher PDF

Transcriptomics is being increasingly applied to generate new insight into the interactions between plants and their pathogens. For the wheat yellow (stripe) rust pathogen (Puccinia striiformis f. sp. tritici, Pst) RNA-based sequencing (RNA-Seq) has proved particularly valuable, overcoming the barriers associated with its obligate biotrophic nature. This includes the application of RNA-Seq approaches to study Pst and wheat gene expression dynamics over time and the Pst population composition through the use of a novel RNA-Seq based surveillance approach called “field pathogenomics”. As a dual RNA-Seq approach, the field pathogenomics technique also provides gene expression data from the host, giving new insight into host responses. However, this has created a wealth of data for interrogation. Results: Here, we used the field pathogenomics approach to generate 538 new RNA-Seq datasets from Pst-infected field wheat samples, doubling the amount of transcriptomics data available for this important pathosystem. We then analysed these datasets alongside 66 RNA-Seq datasets from four Pst infection time-courses and 420 Pst-infected plant field and laboratory samples that were publicly available. A database of gene expression values for Pst and wheat was generated for each of these 1024 RNA-Seq datasets and incorporated into the development of the rust expression browser (http://www.rust-expression.com). This enables for the first time simultaneous ‘point-and-click’ access to gene expression profiles for Pst and its wheat host and represents the largest database of processed RNA-Seq datasets available for any of the three Puccinia wheat rust pathogens. We also demonstrated the utility of the browser through investigation of expression of putative Pst virulence genes over time and examined the host plants response to Pst infection. Conclusions: The rust expression browser offers immense value to the wider community, facilitating data sharing and transparency and the underlying database can be continually expanded as more datasets become publicly available. EEA Bordenave Fil: Adams, Thomas M.. John Innes Centre. Norwich Research Park; Reino Unido Fil: Olsson, Tjelvar S.G. John Innes Centre. Norwich Research Park; Reino Unido Fil: Ramírez-González, Ricardo H. John Innes Centre. Norwich Research Park; Reino Unido Fil: Bryant, Ruth. RAGT Seeds Ltd.; Reino Unido Fil: Bryson, Rosie. BASF SE. Agricultural Centre; Alemania Fil: Campos, Pablo Eduardo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Bordenave; Argentina Fil: Fenwick, Paul. Limagrain UK Ltd.; Reino Unido Fil: Feuerhelm, David. Syngenta Seeds Ltd.; Reino Unido Fil: Hayes, Charlotte. Elsoms Wheat Ltd.; Reino Unido Fil: Henriksson, Tina. Lantmännen Lantbruk; Suecia Fil: Hubbard, Amelia. NIAB; Reino Unido Fil: Jevtić, Radivoje. Institute of Field and Vegetable Crops; Serbia Fil: Judge, Christopher. NIAB; Reino Unido Fil: Kerton, Matthew. DSV United Kingdom Ltd.; Reino Unido Fil: Lage, Jacob. KWS UK Limited; Reino Unido Fil: Lewis, Clare M. John Innes Centre. Norwich Research Park; Reino Unido Fil: Lilly, Christine. Frontier Agriculture; Reino Unido Fil: Meidan, Udi. Hazera Seeds Ltd.; Israel Fil: Novoselović, Dario. Agricultural Institute Osijek; Croacia Fil: Patrick, Colin. Masstock Arable (UK) Ltd.; Reino Unido Fil: Wanyera, Ruth. Kenya Agricultural and Livestock Research Organization; Kenia Fil: Saunders, Diane G.O. John Innes Centre. Norwich Research Park; Reino Unido

Puccinia striiformisf. sp.tritici(Pst) is the causative agent of wheat yellow rust disease, affecting wheat production worldwide. In order to effectively manage this disease, it is important to monitor the genotypes present through surveillance programs. Additionally, the use of public, open source tools such as the Nextstrain toolkit allow for rapid and efficient sharing of data from surveillance programmes. Here we present a Nextstrain instance forPst, which will be a valuable resource for understanding and tracking the distribution of specific genotypes of this important pathogen.

In this Perspective, the author presents his vision of scholarship as consisting of hierarchically nested levels of specialization, each level offering its own perspective and value. He argues that in an era of increasingly sophisticated analysis tools, modern scholarship tends to proceed largely unaware of the benefits of conducting research at the higher, more general levels of the hierarchy. Drawing upon his own research and that of others, he gives examples of the manner in which generalist scholarship may proceed, the type of unique insights it uncovers, and the wisdom afforded us via an awareness of where our scholarship resides within the hierarchy.

An experimental investigation addressing the effect of the release of dissolved noncondensables on the heat transfer in a long, heated microchannel subject to subcooled liquid forced convection was conducted. The convection heat transfer coefficients near the exit of a copper microchannel with 0.76 mm inner diameter and 16 cm heated length, subject to forced-flow cooling by subcooled water, were measured. The range of experimental parameters were: wall heat flux=0.5–2.5 MW/m2; liquid velocity=2.07 to 8.53 m/s; channel exit pressure=5.9 bar. Experiments were performed with degassed water and water saturated with air. The convection heat transfer coefficients obtained with degassed water were systematically under predicted by the widely-used Dittus–Boelter correlation for turbulent pipe flow. The presence of dissolved air in water could increase the heat transfer coefficients by as much as 17%, despite the fact that the maximum increase in the coolant velocity due to the noncondensable gas release was only a few percent. The heat transfer enhancement increased with increasing the heat flux and decreasing the liquid velocity.

Turbulent, single-phase forced convection of water in circular microchannels with diameters of 0.76 and 1.09 mm has been investigated. The data show that the Nusselt numbers for the microchannels are higher than those predicted by traditional large channel correlations. Based on the data obtained in this investigation, along with earlier data for smaller diameter channels, a generalized correlation for the Nusselt number for turbulent, single-phase, forced convection in circular microchannels has been developed. The diameter, Reynolds number, and Prandtl number ranges are 0.102–1.09 mm, 2.6 × 103−2.3 × 104, and 1.53–6.43, respectively. With a confidence level of greater than 95%, differences between experimental and predicted Nusselt number values are less than ± 18.6%.

One of the most important resources available in the field of fluid mechanics, the Moody Chart gives Darcy friction factor as a function of Reynolds number and relative roughness. The experimentalists who generated the data correlated in the Moody Chart, however, roughened pipe surfaces by coating their internal surfaces with a monolayer of sand, the pipe wall roughness being defined as the average diameter of the sand grains. Thus, the sand-grain roughness values required for use with the Moody Chart are not derived from any direct measure of roughness using modern surface characterization equipment, such as an optical profilometer. Using direct measurements of surface roughness in fluid flow calculations may therefore result in significant error. In this paper we present a simple algorithm with which various measured surface roughness parameters can be converted to equivalent sand-grain roughness. For nearly every surface roughness value converted to equivalent sand-grain roughness using the algorithm, better agreement with fluid flow experiments is seen over using the raw roughness value.

Due to the small scales encountered in MEMS and microfluidic devices, surface tension can play a significant role in the device physics. As such, many microscale devices have exploited surface tension forces to serve as passive valves and to move fluids. Surprisingly, few models for surface tension driven flow seem to have been developed. In this study a theoretical mathematical model for surface tension driven flow through a capillary of an arbitrary cross section is derived. The model is based on macroscopic mass and momentum balances, allowing for different physical insights to be drawn compared to approaches starting with the Navier-Stokes equations. Expressions for flow length and velocity are derived for both frictionless flow and for flow with wall friction. For frictionless flow the result of surface tension force is to increase the momentum of the fluid by constantly drawing mass into the capillary at a constant characteristic velocity. In the case of flow with wall friction, a characteristic time scale can be calculated. For times on the order of the characteristic time scale, the flow velocity exponentially decays from the characteristic velocity, whereas for larger times the velocity shows an inverse power law dependence. The model well predicts flow behaviour for previously published experiments in which the characteristic time is small. For systems in which the characteristic time is larger, the model may show improved performance over previous models.