Genomic signals found using RNA sequencing show signatures of selection and subtle population differentiation in walleye (Sander vitreus) in a large freshwater ecosystem

Extensive transcriptome data providing great efficacy in genetic research and adaptive gene discovery: a case study of Elymus sibiricus L. (Poaceae, Triticeae)

Genetic markers play a central role in understanding genetic diversity, speciation, evolutionary processes, and how species respond to environmental stresses. However, conventional molecular markers are less effective when studying polyploid species with large genomes. In this study, we compared gene expression levels in 101 accessions of Elymus sibiricus, a widely distributed allotetraploid forage species across the Eurasian continent. A total of 20,273 high quality transcriptomic SNPs were identified. In addition, 72,344 evolutionary information loci of these accessions of E. sibiricus were identified using genome skimming data in conjunction with the assembled composite genome. The population structure results suggest that transcriptome SNPs were more effective than SNPs derived from genome skimming data in revealing the population structure of E. sibiricus from different locations, and also outperformed gene expression levels. Compared with transcriptome SNPs, the investigation of population-specifically-expressed genes (PSEGs) using expression levels revealed a larger number of locally adapted genes mainly involved in the ion response process in the Sichuan, Inner Mongolia, and Xizang geographical groups. Furthermore, we performed the weighted gene co-expression network analysis (WGCNA) and successfully identified potential regulators of PSEGs. Therefore, for species lacking genomic information, the use of transcriptome SNPs is an efficient approach to perform population structure analysis. In addition, analyzing genes under selection through nucleotide diversity and genetic differentiation index analysis based on transcriptome SNPs, and exploring PSEG through expression levels is an effective method for analyzing locally adaptive genes.

Hepatic transcriptome, transcriptional effects and antioxidant responses in Poecilia vivipara exposed to sanitary sewage

Aquatic environments are subject to threats from multiple human activities, particularly through the release of untreated sanitary sewage into the coastal environments. These effluents contain a large group of natural or synthetic compounds referred to as emerging contaminants. Monitoring the types and quantities of toxic substances in the environment, especially complex mixtures, is an exhausting and challenging task. Integrative effect-based tools, such as biomarkers, are recommended for environmental quality monitoring programs. In this study, fish Poecilia vivipara were exposed for 24 and 96 h to raw untreated sewage diluted 33 % (v/v) in order to identify hepatic genes to be used as molecular biomarkers. Through a de novo hepatic transcriptome assembly, using Illumina MiSeq, 54,285 sequences were assembled creating a reference transcriptome for this guppy species. Transcripts involved in biotransformation systems, antioxidant defenses, ABC transporters, nuclear and xenobiotic receptors were identified and evaluated by qPCR. Sanitary sewage induced transcriptional changes in AhR, PXR, CYP2K1, CYP3A30, NQO1, UGT1A1, GSTa3, GSTmu, ST1C1, SOD, ABCC1 and SOX9 genes from liver of fish, particularly after 96 h of exposure. Changes in hepatic enzyme activities were also observed. The enzymes showed differences in fish exposed to both periods, while in the gills there was a prevalence of significant results after 96 h. The observed differences were associated to gender and/or to sewage exposure. The obtained results support the use of P. vivipara as sentinel and model organism for ecotoxicological studies and evidence the importance of understanding the differential responses associated to gender.

RNA-Seq-Pop: Exploiting the sequence in RNA sequencing-A Snakemake workflow reveals patterns of insecticide resistance in the malaria vector Anopheles gambiae

We provide a reproducible and scalable Snakemake workflow, called RNA-Seq-Pop, which provides end-to-end analysis of RNA sequencing data sets. The workflow allows the user to perform quality control, perform differential expression analyses and call genomic variants. Additional options include the calculation of allele frequencies of variants of interest, summaries of genetic variation and population structure, and genome-wide selection scans, together with clear visualizations. RNA-Seq-Pop is applicable to any organism, and we demonstrate the utility of the workflow by investigating pyrethroid resistance in selected strains of the major malaria mosquito, Anopheles gambiae. The workflow provides additional modules specifically for An. gambiae, including estimating recent ancestry and determining the karyotype of common chromosomal inversions. The Busia laboratory colony used for selections was collected in Busia, Uganda, in November 2018. We performed a comparative analysis of three groups: a parental G24 Busia strain; its deltamethrin-selected G28 offspring; and the susceptible reference strain Kisumu. Measures of genetic diversity reveal patterns consistent with that of laboratory colonization and selection, with the parental Busia strain exhibiting the highest nucleotide diversity, followed by the selected Busia offspring, and finally, Kisumu. Differential expression and variant analyses reveal that the selected Busia colony exhibits a number of distinct mechanisms of pyrethroid resistance, including the Vgsc-995S target-site mutation, upregulation of SAP genes, P450s and a cluster of carboxylesterases. During deltamethrin selections, the 2La chromosomal inversion rose in frequency (from 33% to 86%), supporting a previous link with pyrethroid resistance. RNA-Seq-Pop is hosted at: github.com/sanjaynagi/rna-seq-pop. We anticipate that the workflow will provide a useful tool to facilitate reproducible, transcriptomic studies in An. gambiae and other taxa.

Single Nucleotide Polymorphism Markers with Applications in Conservation and Exploitation of Aquatic Natural Populations

An increasing number of aquatic species have been studied for genetic polymorphism, which extends the knowledge on their natural populations. One type of high-resolution molecular marker suitable for studying the genetic diversity of large numbers of individuals is single nucleotide polymorphism (SNP). This review is an attempt to show the range of applications of SNPs in studies of natural populations of aquatic animals. In recent years, SNPs have been used in the genetic analysis of wild and enhanced fish and invertebrate populations in natural habitats, exploited migratory species in the oceans, migratory anadromous and freshwater fish and demersal species. SNPs have been used for the identification of species and their hybrids in natural environments, to study the genetic consequences of restocking for conservation purposes and the negative effects on natural populations of fish accidentally escaping from culture. SNPs are very useful for identifying genomic regions correlated with phenotypic variants relevant for wildlife protection, management and aquaculture. Experimental size-selective catches of populations created in tanks have caused evolutionary changes in life cycles of fishes. The research results have been discussed to clarify whether the fish populations in natural conditions can undergo changes due to selective harvesting targeting the fastest-growing fishes.

The use of non-lethal sampling for transcriptomics to assess the physiological status of wild fishes

Fishes respond to different abiotic and biotic stressors through changes in gene expression as a part of an integrated physiological response. Transcriptomics approaches have been used to quantify gene expression patterns as a reductionist approach to understand responses to environmental stressors in animal physiology and have become more commonly used to study wild fishes. We argue that non-lethal sampling for transcriptomics should become the norm for assessing the physiological status of wild fishes, especially when there are conservation implications. Processes at the level of the transcriptome provide a "snapshot" of the cellular conditions at a given time; however, by using a non-lethal sampling protocol, researchers can connect the transcriptome profile with fitness-relevant ecological endpoints such as reproduction, movement patterns and survival. Furthermore, telemetry is a widely used approach in fisheries to understand movement patterns in the wild, and when combined with transcriptional profiling, provides arguably the most powerful use of non-lethal sampling for transcriptomics in wild fishes. In this review, we discuss the different tissues that can be successfully incorporated into non-lethal sampling strategies, which is particularly useful in the context of the emerging field of conservation transcriptomics. We briefly describe different methods for transcriptional profiling in fishes from high-throughput qPCR to whole transcriptome approaches. Further, we discuss strategies and the limitations of using transcriptomics for non-lethally studying fishes. Lastly, as 'omics' technology continues to advance, transcriptomics paired with different omics approaches to study wild fishes will provide insight into the factors that regulate phenotypic variation and the physiological responses to changing environmental conditions in the future.

Mixed-stock analysis using Rapture genotyping to evaluate stock-specific exploitation of a walleye population despite weak genetic structure

Mixed-stock analyses using genetic markers have informed fisheries management in cases where strong genetic differentiation occurs among local spawning populations, yet many fisheries are supported by multiple, weakly differentiated stocks. Freshwater fisheries exemplify this problem, with many populations supported by multiple stocks of young evolutionary age and isolated across small spatial scales. Consequently, attempts to conduct genetic mixed-stock analyses of inland fisheries have often been unsuccessful. Advances in genomic sequencing offer the ability to discriminate among populations with weak population structure, providing the necessary resolution to conduct mixed-stock assignment among previously indistinguishable stocks. We used genomic data to conduct a mixed-stock analysis of eastern Lake Erie's commercial and recreational walleye (Sander vitreus) fisheries and estimate the relative harvest of weakly differentiated stocks (pairwise F ST < 0.01). Using RAD-capture (Rapture), we sequenced and genotyped individuals from western and eastern basin local spawning stocks at 12,081 loci with 95% reassignment accuracy, which was not possible in the past using microsatellite markers. A baseline assessment of 395 walleye from 11 spawning stocks identified three reporting groups and refined previous assessments of gene flow among walleye stocks. Genetic assignment of 1,075 walleye harvested in eastern Lake Erie's recreational and commercial fisheries indicated that western basin stocks constituted the majority of harvest during the peak walleye fishing season (July-September), whereas eastern basin individuals comprised much of the early season harvest (May-June). Clear spatial structure in harvest composition existed; catches in more easterly sites contained more individuals of eastern basin origin than did more westerly sites. Our study provides important stock contribution estimates for Lake Erie fishery management and demonstrates the utility of genomic data to facilitate mixed-stock analysis in exploited fish populations having weak population structure or limited existing genetic resources.

RNA sequencing describes both population structure and plasticity-selection dynamics in a non-model fish

Background

Messenger RNA sequencing is becoming more common in studies of non-model species and is most often used for gene expression-based investigations. However, the method holds potential for numerous other applications as well—including analyses of alternative splicing, population structure, and signatures of selection. To maximize the utility of mRNA data sets, distinct analyses may be combined such as by exploring dynamics between gene expression with signatures of selection in the context of population structure. Here, we compare two published data sets describing two populations of a minnow species endemic to the San Francisco Estuary (Sacramento splittail, Pogonichthys macrolepidotus): a microsatellite data set showing population structure, and an mRNA whole transcriptome data set obtained after the two populations were exposed to a salinity challenge. We compared measures of population structure and genetic variation using single nucleotide polymorphisms (SNPs) called from mRNA from the whole transcriptome sequencing study with those patterns determined from microsatellites. For investigating plasticity and evolution, intra- and inter-population transcriptome plasticity was investigated with differential gene expression, differential exon usage, and gene expression variation. Outlier SNP analysis was also performed on the mRNA data set and signatures of selection and phenotypic plasticity were investigated on an individual-gene basis.

Results

We found that mRNA sequencing revealed patterns of population structure consistent with those found with microsatellites, but with lower magnitudes of genetic variation and population differentiation consistent with widespread purifying selection expected when using mRNA. In addition, within individual genes, phenotypic plasticity or signatures of selection were found in almost mutual exclusion (except heatr6, nfu1, slc22a6, sya, and mmp13).

Conclusions

These results show that an mRNA sequencing data set may have multiple uses, including describing population structure and for investigating the mechanistic interplay of evolution and plasticity in adaptation. MRNA sequencing thus complements traditional sequencing methods used for population genetics, in addition to its utility for describing phenotypic plasticity.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07592-4.