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Proximity loggers are a novel biotelemetry device used for quantifying animal-animal interactions in a non-invasive way. Such data has been used for studying a range of interactions from disease spread among badgers and cattle to quantifying cow-calf interactions. Such quantitative behavioral traits could be used for the purpose of selective breeding in domesticated animals. With the use of real data, from the study of oestrus behavior in cattle populations raised in an extensive grazing system, we have identified poor reciprocal agreement (RA) as a source of variation. To date, RA has not been adequately considered or addressed and can have serious implications for further analyses aimed at correctly quantifying and interpreting social behavior. We provide a database schema for storing the millions of contact records produced by proximity loggers and programming functions, for use in the statistical programming language R, for performing raw data quality control, data import, database queries and classification of RA between proximity logger pairs. Poor RA leads to a lack of confidence in the data recorded by a pair of loggers. At best, substantial noise is added to the data set and at worst can lead to over or under estimation of contacts between pairs of animals. Over successive deployments, the identification and removal of loggers consistently involved in poor RA pairs can improve the level of agreement and confidence in the recorded data. This is a necessity for the accurate estimation of genetic parameters based on proximity logger data. [ABSTRACT FROM PUBLISHER]

Using microscopy to investigate stomatal behaviour is common in plant physiology research. Manual inspection and measurement of stomatal pore features is low throughput, relies upon expert knowledge to record stomatal features accurately, requires significant researcher time and investment, and can represent a significant bottleneck to research pipelines. To alleviate this, we introduce StomaAI (SAI): a reliable, user-friendly and adaptable tool for stomatal pore and density measurements via the application of deep computer vision, which has been initially calibrated and deployed for the model plant Arabidopsis (dicot) and the crop plant barley (monocot grass). SAI is capable of producing measurements consistent with human experts and successfully reproduced conclusions of published datasets. SAI boosts the number of images that can be evaluated in a fraction of the time, so can obtain a more accurate representation of stomatal traits than is routine through manual measurement. An online demonstration of SAI is hosted at https://sai.aiml.team, and the full local application is publicly available for free on GitHub through https://github.com/xdynames/sai-app., (© 2023 The Authors. New Phytologist © 2023 New Phytologist Foundation.)

High-yielding crop varieties will become critical in meeting the future food demand in the face of worsening weather extremes and threatening biotic stressors. The bread wheat cultivar Sonmez-2001 is a registered variety that is notable for its performance under low-irrigation conditions, which further improves upon irrigation. Additionally, Sonmez-2001 is resilient against certain biotic stressors, particularly soil-borne pathogens. Here, we provide a reference-guided whole genome sequence of Sonmez-2001, assembled into 21 chromosomes of the A, B and D genomes and totaling 13.3 gigabase-pairs in length. Additionally, a de novo assembly of an additional 1.05 gigabase-pairs was generated that represents either Sonmez-specific sequences or sequences that considerably diverged between Sonmez and Chinese Spring. Within this de novo assembly, we identified 35 gene models, of which 11 were high-confidence, that may contribute to the favorable traits of this high-performing variety. We identified up to 24 million sequence variants, of which up to 2.4% reside in coding sequences, that can be used to develop molecular markers that should be of immediate use to the cereal community., Competing Interests: Competing interests: H. Budak and A. Akpinar are employed by Montana BioAgriculture Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright: © 2022 Akpinar BA et al.)

Factors facilitating the chronicity of otitis media (OM) in children are, to date, not fully understood. An understanding of molecular factors aiding bacterial persistence within the middle ear during OM could reveal pathways required for disease. This study performed a detailed analysis of Streptococcus pneumoniae populations isolated from the nasopharynx and middle ear of one OM case. Isolates were assessed for growth in vitro and infection in a mouse intranasal challenge model. Whole genome sequencing was performed to compare the nasopharyngeal and middle ear isolates. The middle ear isolate displayed a reduced rate of growth and enhanced potential to transit to the middle ear in a murine model. The middle ear population possessed a single nucleotide polymorphism (SNP) in the IgA1 protease gene igA, predicted to render its product non-functional. Allelic exchange mutagenesis of the igA alleles from the genetic variant middle ear and nasopharyngeal isolates was able to reverse the niche-adaptation phenotype in the murine model. These results indicate the potential role of a SNP in the gene encoding the IgA1 protease, in determining S. pneumoniae adaptation to the middle ear during chronic OM. In contrast, a functional IgA1 protease was associated with increased colonisation of the nasopharynx., (© The Author(s) 2020. Published by Oxford University Press on behalf of FEMS.)

Nuclear male-sterile mutants with non-conditional, recessive and strictly monogenic inheritance are useful for both hybrid and conventional breeding systems, and have long been a research focus for many crops. In allohexaploid wheat, however, genic redundancy results in rarity of such mutants, with the ethyl methanesulfonate-induced mutant ms5 among the few reported to date. Here, we identify TaMs5 as a glycosylphosphatidylinositol-anchored lipid transfer protein required for normal pollen exine development, and by transgenic complementation demonstrate that TaMs5-A restores fertility to ms5. We show ms5 locates to a centromere-proximal interval and has a sterility inheritance pattern modulated by TaMs5-D but not TaMs5-B. We describe two allelic forms of TaMs5-D, one of which is non-functional and confers mono-factorial inheritance of sterility. The second form is functional but shows incomplete dominance. Consistent with reduced functionality, transcript abundance in developing anthers was found to be lower for TaMs5-D than TaMs5-A. At the 3B homoeolocus, we found only non-functional alleles among 178 diverse hexaploid and tetraploid wheats that include landraces and Triticum dicoccoides. Apparent ubiquity of non-functional TaMs5-B alleles suggests loss-of-function arose early in wheat evolution and, therefore, at most knockout of two homoeoloci is required for sterility. This work provides genetic information, resources and tools required for successful implementation of ms5 sterility in breeding systems for bread and durum wheats., (© 2019 The Authors The Plant Journal © 2019 John Wiley & Sons Ltd.)

EMBL Australia Bioinformatics Resource (EMBL-ABR) is a developing national research infrastructure, providing bioinformatics resources and support to life science and biomedical researchers in Australia. EMBL-ABR comprises 10 geographically distributed national nodes with one coordinating hub, with current funding provided through Bioplatforms Australia and the University of Melbourne for its initial 2-year development phase. The EMBL-ABR mission is to: (1) increase Australia's capacity in bioinformatics and data sciences; (2) contribute to the development of training in bioinformatics skills; (3) showcase Australian data sets at an international level and (4) enable engagement in international programs. The activities of EMBL-ABR are focussed in six key areas, aligning with comparable international initiatives such as ELIXIR, CyVerse and NIH Commons. These key areas-Tools, Data, Standards, Platforms, Compute and Training-are described in this article., (© The Author 2017. Published by Oxford University Press.)

Background: Numerous scaffold-level sequences for wheat are now being released and, in this context, we report on a strategy for improving the overall assembly to a level comparable to that of the human genome., Results: Using chromosome 7A of wheat as a model, sequence-finished megabase-scale sections of this chromosome were established by combining a new independent assembly using a bacterial artificial chromosome (BAC)-based physical map, BAC pool paired-end sequencing, chromosome-arm-specific mate-pair sequencing and Bionano optical mapping with the International Wheat Genome Sequencing Consortium RefSeq v1.0 sequence and its underlying raw data. The combined assembly results in 18 super-scaffolds across the chromosome. The value of finished genome regions is demonstrated for two approximately 2.5 Mb regions associated with yield and the grain quality phenotype of fructan carbohydrate grain levels. In addition, the 50 Mb centromere region analysis incorporates cytological data highlighting the importance of non-sequence data in the assembly of this complex genome region., Conclusions: Sufficient genome sequence information is shown to now be available for the wheat community to produce sequence-finished releases of each chromosome of the reference genome. The high-level completion identified that an array of seven fructosyl transferase genes underpins grain quality and that yield attributes are affected by five F-box-only-protein-ubiquitin ligase domain and four root-specific lipid transfer domain genes. The completed sequence also includes the centromere.