ALBERT

Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Hirschberger, C., Sleight, V. A., Criswell, K. E., Clark, S. J., & Gillis, J. A. Conserved and unique transcriptional features of pharyngeal arches in the skate (Leucoraja erinacea) and evolution of the jaw. Molecular Biology and Evolution, (2021): msab123, https://doi.org/10.1093/molbev/msab123

Description: The origin of the jaw is a long-standing problem in vertebrate evolutionary biology. Classical hypotheses of serial homology propose that the upper and lower jaw evolved through modifications of dorsal and ventral gill arch skeletal elements, respectively. If the jaw and gill arches are derived members of a primitive branchial series, we predict that they would share common developmental patterning mechanisms. Using candidate and RNAseq/differential gene expression analyses, we find broad conservation of dorsoventral patterning mechanisms within the developing mandibular, hyoid and gill arches of a cartilaginous fish, the skate (Leucoraja erinacea). Shared features include expression of genes encoding members of the ventralising BMP and endothelin signalling pathways and their effectors, the joint markers nkx3.2 and gdf5 and pro-chondrogenic transcription factor barx1, and the dorsal territory marker pou3f3. Additionally, we find that mesenchymal expression of eya1/six1 is an ancestral feature of the mandibular arch of jawed vertebrates, while differences in notch signalling distinguish the mandibular and gill arches in skate. Comparative transcriptomic analyses of mandibular and gill arch tissues reveal additional genes differentially expressed along the dorsoventral axis of the pharyngeal arches, including scamp5 as a novel marker of the dorsal mandibular arch, as well as distinct transcriptional features of mandibular and gill arch muscle progenitors and developing gill buds. Taken together, our findings reveal conserved patterning mechanisms in the pharyngeal arches of jawed vertebrates, consistent with serial homology of their skeletal derivatives, as well as unique transcriptional features that may underpin distinct jaw and gill arch morphologies.

Description: This work was supported by a Biotechnology and Biological Sciences Research Council Doctoral Training Partnership studentship to CH, by a Wolfson College Junior Research Fellowship and MBL Whitman Early Career Fellowship to VAS, and by a Royal Society University Research Fellowship (UF130182 and URF\R\191007), Royal Society Research Grant (RG140377) and University of Cambridge Sir Isaac Newton Trust Grant (14.23z) to JAG.

Description: Motivation: Gene networks have become a central tool in the analysis of genomic data but are widely regarded as hard to interpret. This has motivated a great deal of comparative evaluation and research into best practices. We explore the possibility that this may lead to overfitting in the field as a whole. Results: We construct a model of ‘research communities’ sampling from real gene network data and machine learning methods to characterize performance trends. Our analysis reveals an important principle limiting the value of replication, namely that targeting it directly causes ‘easy’ or uninformative replication to dominate analyses. We find that when sampling across network data and algorithms with similar variability, the relationship between replicability and accuracy is positive (Spearman’s correlation, r s ~0.33) but where no such constraint is imposed, the relationship becomes negative for a given gene function ( r s ~ –0.13). We predict factors driving replicability in some prior analyses of gene networks and show that they are unconnected with the correctness of the original result, instead reflecting replicable biases. Without these biases, the original results also vanish replicably. We show these effects can occur quite far upstream in network data and that there is a strong tendency within protein–protein interaction data for highly replicable interactions to be associated with poor quality control. Availability and implementation: Algorithms, network data and a guide to the code available at: https://github.com/wimverleyen/AggregateGeneFunctionPrediction . Contact: jgillis@cshl.edu Supplementary information: Supplementary data are available at Bioinformatics online.

Description: Motivation: RNA-seq co-expression analysis is in its infancy and reasonable practices remain poorly defined. We assessed a variety of RNA-seq expression data to determine factors affecting functional connectivity and topology in co-expression networks. Results: We examine RNA-seq co-expression data generated from 1970 RNA-seq samples using a Guilt-By-Association framework, in which genes are assessed for the tendency of co-expression to reflect shared function. Minimal experimental criteria to obtain performance on par with microarrays were 〉20 samples with read depth 〉10 M per sample. While the aggregate network constructed shows good performance (area under the receiver operator characteristic curve ~0.71), the dependency on number of experiments used is nearly identical to that present in microarrays, suggesting thousands of samples are required to obtain ‘gold-standard’ co-expression. We find a major topological difference between RNA-seq and microarray co-expression in the form of low overlaps between hub-like genes from each network due to changes in the correlation of expression noise within each technology. Contact: jgillis@cshl.edu or sballouz@cshl.edu Supplementary information: Networks are available at: http://gillislab.labsites.cshl.edu/supplements/rna-seq-networks/ and supplementary data are available at Bioinformatics online.

Description: Motivation: Network-based gene function inference methods have proliferated in recent years, but measurable progress remains elusive. We wished to better explore performance trends by controlling data and algorithm implementation, with a particular focus on the performance of aggregate predictions. Results: Hypothesizing that popular methods would perform well without hand-tuning, we used well-characterized algorithms to produce verifiably ‘untweaked’ results. We find that most state-of-the-art machine learning methods obtain ‘gold standard’ performance as measured in critical assessments in defined tasks. Across a broad range of tests, we see close alignment in algorithm performances after controlling for the underlying data being used. We find that algorithm aggregation provides only modest benefits, with a 17% increase in area under the ROC (AUROC) above the mean AUROC. In contrast, data aggregation gains are enormous with an 88% improvement in mean AUROC. Altogether, we find substantial evidence to support the view that additional algorithm development has little to offer for gene function prediction. Availability and implementation: The supplementary information contains a description of the algorithms, the network data parsed from different biological data resources and a guide to the source code (available at: http://gillislab.cshl.edu/supplements/ ). Contact: jgillis@cshl.edu

Description: Aims Darwin’s naturalization hypothesis proposes that successfully established alien species are less closely related to native species due to differences in their ecological niches. Studies have provided support both for and against this hypothesis. One reason for this is the tendency for phylogenetic clustering between aliens and natives at broad spatial scales with overdispersion at fine scales. However, little is known about how the phylogenetic relatedness of alien species alters the phylogenetic structure of the communities they invade, and at which spatial scales effects may manifest. Here, we examine if invaded understorey plant communities, i.e. containing both native and alien taxa, are phylogenetically clustered or overdispersed, how relatedness changes with spatial scale and how aliens affect phylogenetic patterns in understorey communities. Methods Field surveys were conducted in dry forest understorey communities in south-east Australia at five spatial scales (1, 20, 500, 1500 and 4500 m2). Standardized effect sizes of two metrics were used to quantify phylogenetic relatedness between communities and their alien and native subcommunities, and to examine how phylogenetic patterns change with spatial scale: (i) mean pairwise distance and (ii) mean nearest taxon distance (MNTD). Important Findings Aliens were closely related to each other, and this relatedness tended to increase with scale. Native species and the full community exhibited either no clear pattern of relatedness with increasing spatial scale or were no different from random. At intermediate spatial scales (20–500 m2), the whole community tended towards random whereas the natives were strongly overdispersed and the alien subcommunity strongly clustered. This suggests that invasion by closely related aliens shifts community phylogenetic structure from overdispersed towards random. Aliens and natives were distantly related across spatial scales, supporting Darwin’s naturalization hypothesis, but only when phylogenetic distance was quantified as MNTD. Phylogenetic dissimilarity between aliens and natives increased with spatial scale, counter to expected patterns. Our findings suggest that the strong phylogenetic clustering of aliens is driven by human-mediated introductions involving closely related taxa that can establish and spread successfully. Unexpected scale-dependent patterns of phylogenetic relatedness may result from stochastic processes such as fire and dispersal events and suggest that competition and habitat filtering do not exclusively dominate phylogenetic relationships at fine and coarse spatial scales, respectively. Distinguishing between metrics that focus on different evolutionary depths is important, as different metrics can exhibit different scale-dependent patterns.

Description: The origin of the jaw is a long-standing problem in vertebrate evolutionary biology. Classical hypotheses of serial homology propose that the upper and lower jaw evolved through modifications of dorsal and ventral gill arch skeletal elements, respectively. If the jaw and gill arches are derived members of a primitive branchial series, we predict that they would share common developmental patterning mechanisms. Using candidate and RNAseq/differential gene expression analyses, we find broad conservation of dorsoventral (DV) patterning mechanisms within the developing mandibular, hyoid, and gill arches of a cartilaginous fish, the skate (Leucoraja erinacea). Shared features include expression of genes encoding members of the ventralizing BMP and endothelin signaling pathways and their effectors, the joint markers nkx3.2 and gdf5 and prochondrogenic transcription factor barx1, and the dorsal territory marker pou3f3. Additionally, we find that mesenchymal expression of eya1/six1 is an ancestral feature of the mandibular arch of jawed vertebrates, whereas differences in notch signaling distinguish the mandibular and gill arches in skate. Comparative transcriptomic analyses of mandibular and gill arch tissues reveal additional genes differentially expressed along the DV axis of the pharyngeal arches, including scamp5 as a novel marker of the dorsal mandibular arch, as well as distinct transcriptional features of mandibular and gill arch muscle progenitors and developing gill buds. Taken together, our findings reveal conserved patterning mechanisms in the pharyngeal arches of jawed vertebrates, consistent with serial homology of their skeletal derivatives, as well as unique transcriptional features that may underpin distinct jaw and gill arch morphologies.