Comparative genomic studies of closely related taxa are important for our understanding of the causes of divergence on a changing Earth. This being said, the genomic resources available for marine intertidal molluscs are limited and currently, there are few publicly available high-quality annotated genomes for intertidal habitats and for molluscs in general. Here we report transcriptome assemblies for six species of Patellogastropoda and genome assemblies and annotations for three of these species (Scurria scurra, Scurria viridula, and Scurria zebrina). Comparative analysis using these genomic resources suggest that there was a large gene family contraction during the early evolutionary history of Patellogastropoda (140-170 Mya) and recently diverging lineages (10-20 Mya) have experienced similar amounts of contractions and expansions but across different gene families. Furthermore, differences among recently diverged species are reflected in variation in the amount of coding and noncoding material in genomes, such as amount of repetitive elements and lengths of transcripts and introns and exons. Additionally, functional ontologies of species-specific and duplicated genes together with demographic inference support the finding that recent divergence among members of the genus Scurria aligns with their unique ecological characteristics. Overall, the resources presented here will be extremely valuable for future studies of adaptation in molluscs and in intertidal habitats as a whole.

Plants adapt to their local environment through complex interactions between genes, gene networks, and hormones. Although the impact of gene expression on trait regulation and evolution has been recognized for many decades, its role in the evolution of adaptation is still a subject of intense exploration. We used a Multi-parent Advanced Generation Inter-Cross (MAGIC) population, which we derived from crossing multiple parents from two distinct coastal ecotypes of an Australia wildflower, Senecio lautus. We focused on studying the contrasting gravitropic behaviors of these ecotypes, which have evolved independently multiple times and show strong responses to natural selection in field experiments, emphasizing the role of natural selection in their evolution. Here, we investigated how gene expression differences have contributed to the adaptive evolution of gravitropism. We studied gene expression in 600 pools at five time points (30, 60, 120, 240, and 480 minutes) after rotating half of the pools 90°. We found 428 genes with differential expression in response to the 90° rotation treatment. Of these, 81 genes (~19%) have predicted functions related to the plant hormones auxin and ethylene, which are crucial for the gravitropic response. By combining insights from Arabidopsis mutant studies and analyzing our gene networks, we propose a preliminary model to explain the differences in gravitropism between ecotypes. This model suggests that the differences arise from changes in the transport and availability of the hormones auxin and ethylene. Our findings indicate that the genetic basis of adaptation involves interconnected signaling pathways that work together to give rise to new ecotypes.

Unravelling the interplay among genes, networks, and signalling molecules is key to understanding how many natural populations adapt. Although the impact of gene expression on trait regulation and evolution has been recognised for many decades, its role in the evolution of adaptations is still a subject of intense exploration. Using a hybrid population derived from two contrasting ecotypes of an Australian wildflower, Senecio lautus, we investigated the role of gene expression divergence in their origins. Coastal ecotypes of S. lautus have contrasting vegetative heights and gravitropic behaviours that evolved independently many times, highlighting the role of natural selection in their evolution. We examined gene expression in 10 gravitropic and 10 agravitropic hybrid families from the hybrid population of Senecio at Lennox Head, NSW. We found 428 genes that showed differential expression between the gravitropic control and treatment groups when we rotated the hybrids 90 degrees. Of these, 81 genes (~19%) had predicted functions linked to several plant hormones. Using knowledge from Arabidopsis mutant screens and assessing our gene networks, we construct a model for differences in gravitropism between ecotypes that relies on modulating the movement and accessibility of the hormone auxin, known to control the gravitropic response across plants. Our findings suggest a role for the hormonal control of gravitropism in plant adaptation to coastal environments, where ecotypes are known to differ from their counterparts in other habitats. More generally, we posit that the genetics of adaptation encompasses the evolution of intertwined signalling pathways that ultimately contribute to the origin of new ecotypes.

Storing and manipulating Next Generation Sequencing (NGS) file formats for understanding biological phenomena is an essential but difficult task in the life sciences. Yet, most methods for analysing NGS data require complex command-line tools in high-performance computing (HPC) or web-based servers and have not yet been implemented in comprehensive, easy-to-use software. Here we present easyfm (easy file manipulation), a free standalone Graphical User Interface (GUI) software with Python support that can be used to facilitate the rapid discovery of target sequences (or user’s interest) in NGS datasets for novice users (more accessible to biologists). It enables them to perform end-to-end reproducible data analyses using a desktop application (Windows, Mac and Linux). Unlike existing tools, the GUI-based easyfm is not dependent on any HPC system and can be operated without an internet connection. For user-friendliness and convenience, easyfm was developed with four work modules and a secondary GUI window, covering different aspects of NGS data analysis, including post-processing, filtering, format conversion, generating results, real-time log, and help. In combination with the executable tools (BLAST+ and BLAT) and Python, easyfm allows the user to set analysis parameters, select/extract regions of interest, examine the input and output results, and convert to a wide range of file formats. To help augment the functionality of existing web-based and command-line tools, easyfm, a self-contained program, comes with extensive documentation (https://github.com/TaekAndBrendan/easyfm). This specific benefit allows easyfm to seamlessly integrate visual and interactive representations of NGS files, supporting a wider scope of bioinformatics applications in the life sciences.

Anopheles hinesorum is a mosquito species with variable host preference. Throughout New Guinea and northern Australia, An. hinesorum feeds on humans (it is opportunistically anthropophagic) while in the southwest Pacific’s Solomon Archipelago, the species is abundant but has rarely been found biting humans (it is exclusively zoophagic in most populations). There are at least two divergent zoophagic (non-human biting) mitochondrial lineages of An. hinesorum in the Solomon Archipelago. Since zoophagy is a derived (non-ancestral) trait in this species, this leads to the question: has zoophagy evolved independently in these divergent lineages? Or conversely: has nuclear gene flow or connectivity resulted in the transfer of zoophagy? Although we cannot conclusively answer this, we find close nuclear relationships between Solomon Archipelago populations indicating that recent nuclear gene flow has occurred between zoophagic populations from the divergent mitochondrial lineages. Recent work on isolated islands of the Western Province (Solomon Archipelago) has also revealed an anomalous, anthropophagic island population of An. hinesorum. We find a common shared mitochondrial haplotype between this Solomon Island population and another anthropophagic population from New Guinea. This finding suggests that there has been recent migration from New Guinea into the only known anthropophagic population from the Solomon Islands. Although currently localized to a few islands in the Western Province of the Solomon Archipelago, if anthropophagy presents a selective advantage, we may see An. hinesorum emerge as a new malaria vector in a region that is now working on malaria elimination.