Background: New sequencing technologies have lowered financial barriers to whole genome sequencing, but resulting assemblies are often fragmented and far from ‘finished’. Updating multi-scaffold drafts to chromosome-level status can be achieved through experimental mapping or re-sequencing efforts. Avoiding the costs associated with such approaches, comparative genomic analysis of gene order conservation (synteny) to predict scaffold neighbours (adjacencies) offers a potentially useful complementary method for improving draft assemblies. Results: We evaluated and employed 3 gene synteny-based methods applied to 21 Anopheles mosquito assemblies to produce consensus sets of scaffold adjacencies. For subsets of the assemblies, we integrated these with additional supporting data to confirm and complement the synteny-based adjacencies: 6 with physical mapping data that anchor scaffolds to chromosome locations, 13 with paired-end RNA sequencing (RNAseq) data, and 3 with new assemblies based on re-scaffolding or long-read data. Our combined analyses produced 20 new superscaffolded assemblies with improved contiguities: 7 for which assignments of non-anchored scaffolds to chromosome arms span more than 75% of the assemblies, and a further 7 with chromosome anchoring including an 88% anchored Anopheles arabiensis assembly and, respectively, 73% and 84% anchored assemblies with comprehensively updated cytogenetic photomaps for Anopheles funestus and Anopheles stephensi. Conclusions: Experimental data from probe mapping, RNAseq, or long-read technologies, where available, all contribute to successful upgrading of draft assemblies. Our evaluations show that gene synteny-based computational methods represent a valuable alternative or complementary approach. Our improved Anopheles reference assemblies highlight the utility of applying comparative genomics approaches to improve community genomic resources.

The Gene Ontology (GO) is a cornerstone of functional genomics research that drives discoveries through knowledge-informed computational analysis of biological data from large-scale assays. Key to this success is how the GO can be used to support hypotheses or conclusions about the biology or evolution of a study system by identifying annotated functions that are overrepresented in subsets of genes of interest. Graphical visualizations of such GO term enrichment results are critical to aid interpretation and avoid biases by presenting researchers with intuitive visual data summaries. Amongst current visualization tools and resources there is a lack of standalone open-source software solutions that facilitate explorations of key features of multiple lists of GO terms. To address this we developed GO-Figure!, an open-source Python software for producing user-customisable semantic similarity scatterplots of redundancy-reduced GO term lists. The lists are simplified by grouping together terms with similar functions using their quantified information contents and semantic similarities, with user-control over grouping thresholds. Representatives are then selected for plotting in two-dimensional semantic space where similar terms are placed closer to each other on the scatterplot, with an array of user-customisable graphical attributes. GO-Figure! offers a simple solution for command-line plotting of informative summary visualizations of lists of GO terms, designed to support exploratory data analyses and dataset comparisons.

Mosquitoes are widely despised for their exasperating buzzing and irritating bites, and more poignantly because, during blood-feeding, females may transmit pathogens that cause devastating diseases. However, the ability to transmit such viruses, filarial worms, or malaria parasites varies greatly amongst the ∼3500 recognised mosquito species. Applying omics technologies to sample this diversity and explore the biology underlying these variations is bringing increasingly greater resolution that enhances our understanding of mosquito evolution. Here we review the current status of mosquito omics, or 'mozomics', resources and recent advances in their applications to characterise mosquito biology and evolution, with a focus on the intersection of evolutionary and functional genomics to understand the putative links between gene and genome dynamism and mosquito diversity.

Background: Lumbar interbody fusion (IF) is a common procedure to fuse the anterior spine. However, a lack of consensus on image-based fusion assessment limits the validity and comparison of IF studies. This systematic review aims to (1) report on IF assessment strategies and definitions and (2) summarize available literature on the diagnostic reliability and accuracy of these assessments. Methods: Two searches were performed according to the Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. Search 1 identified studies on adult lumbar IF that provided a detailed description of image-based fusion assessment. Search 2 analyzed studies on the reliability of specific fusion criteria/classifications and the accuracy assessed with surgical exploration. Results: A total of 442 studies were included for search 1 and 8 studies for search 2. Fusion assessment throughout the literature was highly variable. Eighteen definitions and more than 250 unique fusion assessment methods were identified. The criteria that showed most consistent use were continuity of bony bridging, radiolucency around the cage, and angular motion <5°. However, reliability and accuracy studies were scarce. Conclusion: This review highlights the challenges in reaching consensus on IF assessment. The variability in IF assessment is very high, which limits the translatability of studies. Accuracy studies are needed to guide innovations of assessment. Future IF assessment strategies should focus on the standardization of computed tomography–based continuity of bony bridging. Knowledge from preclinical and imaging studies can add valuable information to this ongoing discussion. Level of Evidence: Diagnostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Background: Noninvasive assessment of osseous fusion after spinal fusion surgery is essential for timely diagnosis of patients with symptomatic pseudarthrosis and for evaluation of the performance of spinal fusion procedures. There is, however, no consensus on the definition and assessment of successful posterolateral fusion (PLF) of the lumbar spine. This systematic review aimed to (1) summarize the criteria used for imaging-based fusion assessment after instrumented PLF and (2) evaluate their diagnostic accuracy and reliability. Methods: First, a search of the literature was conducted in November 2018 to identify reproducible criteria for imaging-based fusion assessment after primary instrumented PLF between T10 and S1 in adult patients, and to determine their frequency of use. A second search in July 2021 was directed at primary studies on the diagnostic accuracy (with surgical exploration as the reference) and/or reliability (interobserver and intraobserver agreement) of these criteria. Article selection and data extraction were performed by at least 2 reviewers independently. The methodological quality of validation studies was assessed with the QUADAS-2 (Quality Assessment of Diagnostic Accuracy Studies 2) and QAREL (Quality Appraisal of Reliability Studies). Results: Of the 187 articles included from the first search, 47% used a classification system and 63% used ≥1 descriptive criterion related to osseous bridging (104 articles), absence of motion (78 articles), and/or absence of static signs of nonunion (39 articles). A great variation in terminology, cutoff values, and assessed anatomical locations was observed. While the use of computed tomography (CT) increased over time, radiographs remained predominant. The second search yielded 11 articles with considerable variation in outcomes and quality concerns. Agreement between imaging-based assessment and surgical exploration with regard to demonstration of fusion ranged between 55% and 80%, while reliability ranged from poor to excellent. Conclusions: None of the available criteria for noninvasive assessment of fusion status after instrumented PLF were demonstrated to have both sufficient accuracy and reliability. Further elaboration and validation of a well-defined systematic CT-based assessment method that allows grading of the intertransverse and interfacet fusion mass at each side of each fusion level and includes signs of nonunion is recommended. Level of Evidence: Diagnostic Level III. See Instructions for Authors for a complete description of levels of evidence.

Background: Protein function prediction is an important part of bioinformatics and genomics studies. There are many different predictors available, however most of these are in the form of web-servers instead of open-source locally installable versions. Such local versions are necessary to perform large scale genomics studies due to the presence of limitations imposed by web servers such as queues, prediction speed, and updatability of databases. Methods: This paper describes Wei2GO: a weighted sequence similarity and python-based open-source protein function prediction software. It uses DIAMOND and HMMScan sequence alignment searches against the UniProtKB and Pfam databases respectively, transfers Gene Ontology terms from the reference protein to the query protein, and uses a weighing algorithm to calculate a score for the Gene Ontology annotations. Results: Wei2GO is compared against the Argot2 and Argot2.5 web servers, which use a similar concept, and DeepGOPlus which acts as a reference. Wei2GO shows an increase in performance according to precision and recall curves, F_max scores, and S_min scores for biological process and molecular function ontologies. Computational time compared to Argot2 and Argot2.5 is decreased from several hours to several minutes. Availability: Wei2GO is written in Python 3, and can be found at https://gitlab.com/mreijnders/Wei2GO.