Biology subjects

Hines, H. M.

Publications and source records attributed to Hines, H. M..

5 recordsLinked to original sources

bioRxiv2020

A combined RAD-Seq and WGS approach reveals the genomic basis of yellow colour variation in bumble bee Bombus terrestris

BackgroundIn the model bumble bee species B. terrestris, both males and females exhibit black coloration on the third thoracic and first metasomal segments. We discovered a fortuitous lab-generated mutant in which this typical black coloration is replaced by yellow. As this same color variant is found in several sister lineages to B. terrestris within the Bombus s.s. subgenus, this could be a result of ancestral allele sorting. ResultsUtilizing a combination of RAD-Seq and whole-genome re-sequencing approaches, we localized the color-generating variant to a single SNP in the protein-coding sequence of a homeobox transcription factor, cut. Sanger sequencing confirmed fixation of this SNP between wildtype and yellow mutants. Protein domain analysis revealed this SNP to generate an amino acid change (Ala38Pro) that modifies the conformation of coiled-coil structural elements which lie outside the characteristic DNA binding domains. We found all Hymenopterans including B. terrestris sister lineages possess the non-mutant allele, indicating different mechanism(s) are involved in the same black to yellow transition in nature. ConclusionsCut is a highly pleiotropic gene important for multiple facets of development, yet this mutation generated no noticeable external phenotypic effects outside of setal characteristics. Reproductive capacity was observed to be reduced, however, with queens being less likely to mate and produce female offspring, in a manner similar to workers. Our research implicates a novel developmental player in pigmentation, and potentially caste as well, thus contributing to a better understanding of the evolution of diversity in both of these processes.

genomics↗

bioRxiv2020

Phylogenomics of Ichneumonoidea (Hymenoptera) and implications for evolution of mode of parasitism and viral endogenization

Ichneumonoidea is one of the most diverse lineages of animals on the planet with more than 48,000 described species and many more undescribed. Parasitoid wasps of this superfamily are beneficial insects that attack and kill other arthropods and are important for understanding diversification and the evolution of life history strategies related to parasitoidism. Further, some lineages of parasitoids within Ichneumonoidea have acquired endogenous virus elements (EVEs) that are permanently a part of the wasps genome and benefit the wasp through host immune disruption and behavioral control. Unfortunately, understanding the evolution of viral acquisition, parasitism strategies, diversification, and host immune disruption mechanisms, is deeply limited by the lack of a robust phylogenetic framework for Ichneumonoidea. Here we design probes targeting 541 genes across 91 taxa to test phylogenetic relationships, the evolution of parasitoid strategies, and the utility of probes to capture polydnavirus genes across a diverse array of taxa. Phylogenetic relationships among Ichneumonoidea were largely well resolved with most higher-level relationships maximally supported. We noted codon use biases between the outgroups, Braconidae, and Ichneumonidae and within Pimplinae, which were largely solved through analyses of amino acids rather than nucleotide data. These biases may impact phylogenetic reconstruction and caution for outgroup selection is recommended. Ancestral state reconstructions were variable for Braconidae across analyses, but consistent for reconstruction of idiobiosis/koinobiosis in Ichneumonidae. The data suggest many transitions between parasitoid life history traits across the whole superfamily. The two subfamilies within Ichneumonidae that have polydnaviruses are supported as distantly related, providing strong evidence for two independent acquisitions of ichnoviruses. Polydnavirus capture using our designed probes was only partially successful and suggests that more targeted approaches would be needed for this strategy to be effective for surveying taxa for these viral genes. In total, these data provide a robust framework for the evolution of Ichneumonoidea.

evolutionary biology↗

bioRxiv2019

Measuring Perceptual Distance of Organismal Color Pattern using the Features of Deep Neural Networks

A wide range of research relies upon the accurate and repeatable measurement of the degree to which organisms resemble one another. Here, we present an unsupervised workflow for analyzing the relationships between organismal color patterns. This workflow utilizes several recent advancements in deep learning based computer vision techniques to calculate perceptual distance. We validate this approach using previously published datasets surrounding diverse applications of color pattern analysis including mimicry, population differentiation, heritability, and development. We demonstrate that our approach is able to reproduce the biologically relevant color pattern relationships originally reported in these studies. Importantly, these results are achieved without any task-specific training. In many cases, we were able to reproduce findings directly from original photographs or plates with minimum standardization, avoiding the need for intermediate representations such as a cartoonized images or trait matrices. We then present two artificial datasets designed to highlight how this approach handles aspects of color patterns, such as changes in pattern location and the perception of color contrast. These results suggest that this approach will generalize well to support the study of a wide range of biological processes in a diverse set of taxa while also accommodating a variety of data formats, preprocessing techniques, and study designs.

evolutionary biology↗

bioRxiv2019

Mülleriann mimicry in bumble bees is a transient continuum

Mullerian mimicry theory states that frequency dependent selection should favour geographic convergence of harmful species onto a shared colour pattern. As such, mimetic patterns are commonly circumscribed into discrete mimicry complexes each containing a predominant phenotype. Outside a few examples in butterflies, the location of transition zones between mimicry complexes and the factors driving them has rarely been examined. To infer the patterns and processes of Mullerian mimicry, we integrate large-scale data on the geographic distribution of colour patterns of all social bumble bees across the contiguous United States and use these to quantify colour pattern mimicry using an innovative machine learning approach based on computer vision and image recognition. Our data suggests that bumble bees exhibit a manifold of similar, but imperfect colour patterns, that continuously transition across the United States, supporting the idea that mimicry is not discrete. We propose that bumble bees are mimicking a perceptual colour pattern average that is evolutionarily transient. We examine three comimicking polymorphic species, Bombus flavifrons, B. melanopygus, and B. bifarius, where active selection is driving colour pattern frequencies and determine that their colour pattern transition zones differ in location and breadth within a broad region of poor mimicry. Furthermore, we explore factors driving these differences such as mimicry selection dynamics and climate.

evolutionary biology↗

bioRxiv2018

Incremental BLAST: incremental addition of new sequence databases through e-value correction

MotivationSearch results from local alignment search tools use statistical parameters sensitive to the size of the database. NCBI BLAST, for example, reports important matches using similarity scores and expect or e-values calculated against database size. Over the course of an investigation, the database grows and the best matches may change. To update the results of a sequence similarity search to find the most optimal hits, bioinformaticians must rerun the BLAST search against the entire database; this translates into irredeemable spent time, money, and computational resources.\n\nResultsWe develop an efficient way to redeem spent BLAST search effort by introducing the Incremental BLAST. This tool makes use of the previous BLAST search results as it conducts new searches on only the incremental part of the database, recomputes statistical metrics such as e-values and combines these two sets of results to produce updated results. We develop statistics for correcting e-values of any BLAST result against any arbitrary sequence database. The experimental results and accuracy analysis demonstrate that Incremental BLAST can provide search results identical to NCBI BLAST at a significantly reduced computational cost. We apply three case studies to showcase different use cases where Incremental BLAST can make biological discovery more efficiently at a reduced cost. This tool can be used to update sequence blasts during the course of genomic and transcriptomic projects, such as in re-annotation projects, and to conduct incremental addition of taxon-specific sequences to a BLAST database. Incremental BLAST performs (1 +{delta} )/{delta} times faster than NCBI BLAST for{delta} fraction of database growth.\n\nAvailabilityIncremental BLAST is available at https://bitbucket.org/sajal000/incremental-blast.\n\nContactsajal@vt.edu\n\nSupplementary informationSupplementary data are available at https://bitbucket.org/sajal000/incremental-blast

bioinformatics↗