SNP development from RNA‐seq data in a nonmodel fish: how many individuals are needed for accurate allele frequency prediction?

Single nucleotide polymorphisms (SNPs) are rapidly becoming the marker of choice in population genetics due to a variety of advantages relative to other markers, including higher genomic density, data quality, reproducibility and genotyping efficiency, as well as ease of portability between laboratories. Advances in sequencing technology and methodologies to reduce genomic representation have made the isolation of SNPs feasible for nonmodel organisms. RNA‐seq is one such technique for the discovery of SNPs and development of markers for large‐scale genotyping. Here, we report the development of 192 validated SNP markers for parentage analysis in Tripterygion delaisi (the black‐faced blenny), a small rocky‐shore fish from the Mediterranean Sea. RNA‐seq data for 15 individual samples were used for SNP discovery by applying a series of selection criteria. Genotypes were then collected from 1599 individuals from the same population with the resulting loci. Differences in heterozygosity and allele frequencies were found between the two data sets. Heterozygosity was lower, on average, in the population sample, and the mean difference between the frequencies of particular alleles in the two data sets was 0.135 ± 0.100. We used bootstrap resampling of the sequence data to predict appropriate sample sizes for SNP discovery. As cDNA library production is time‐consuming and expensive, we suggest that using seven individuals for RNA sequencing reduces the probability of discarding highly informative SNP loci, due to lack of observed polymorphism, whereas use of more than 12 samples does not considerably improve prediction of true allele frequencies.     

Estimating and accounting for genotyping errors in RAD‐seq experiments

In non‐model organisms, evolutionary questions are frequently addressed using reduced representation sequencing techniques due to their low cost, ease of use, and because they do not require genomic resources such as a reference genome. However, evidence is accumulating that such techniques may be affected by specific biases, questioning the accuracy of obtained genotypes, and as a consequence, their usefulness in evolutionary studies. Here, we introduce three strategies to estimate genotyping error rates from such data: through the comparison to high quality genotypes obtained with a different technique, from individual replicates, or from a population sample when assuming Hardy‐Weinberg equilibrium. Applying these strategies to data obtained with Restriction site Associated DNA sequencing (RAD‐seq), arguably the most popular reduced representation sequencing technique, revealed per‐allele genotyping error rates that were much higher than sequencing error rates, particularly at heterozygous sites that were wrongly inferred as homozygous. As we exemplify through the inference of genome‐wide and local ancestry of well characterized hybrids of two Eurasian poplar (Populus) species, such high error rates may lead to wrong biological conclusions. By properly accounting for these error rates in downstream analyses, either by incorporating genotyping errors directly or by recalibrating genotype likelihoods, we were nevertheless able to use the RAD‐seq data to support biologically meaningful and robust inferences of ancestry among Populus hybrids. Based on these findings, we strongly recommend carefully assessing genotyping error rates in reduced representation sequencing experiments, and to properly account for these in downstream analyses, for instance using the tools presented here.     

Substantial differences in bias between single‐digest and double‐digest RAD‐seq libraries: A case study

The trade‐offs of using single‐digest vs. double‐digest restriction site‐associated DNA sequencing (RAD‐seq) protocols have been widely discussed. However, no direct empirical comparisons of the two methods have been conducted. Here, we sampled a single population of Gulf pipefish (Syngnathus scovelli) and genotyped 444 individuals using RAD‐seq. Sixty individuals were subjected to single‐digest RAD‐seq (sdRAD‐seq), and the remaining 384 individuals were genotyped using a double‐digest RAD‐seq (ddRAD‐seq) protocol. We analysed the resulting Illumina sequencing data and compared the two genotyping methods when reads were analysed either together or separately. Coverage statistics, observed heterozygosity, and allele frequencies differed significantly between the two protocols, as did the results of selection components analysis. We also performed an in silico digestion of the Gulf pipefish genome and modelled five major sources of bias: PCR duplicates, polymorphic restriction sites, shearing bias, asymmetric sampling (i.e., genotyping fewer individuals with sdRAD‐seq than with ddRAD‐seq) and higher major allele frequencies. This combination of approaches allowed us to determine that polymorphic restriction sites, an asymmetric sampling scheme, mean allele frequencies and to some extent PCR duplicates all contribute to different estimates of allele frequencies between samples genotyped using sdRAD‐seq versus ddRAD‐seq. Our finding that sdRAD‐seq and ddRAD‐seq can result in different allele frequencies has implications for comparisons across studies and techniques that endeavour to identify genomewide signatures of evolutionary processes in natural populations.     

RNA‑seq技术在水生生物生态毒理学中的应用进展

水域是地球环境的重要组成部分,也是最易受污染的生态系统之一。水生态系统中不同营养级别的水生生物可通过摄食、接触等多种途径摄入水体中的污染物。因此,监测水域污染物对水生生物和生态系统的影响,解析污染物对不同水生生物的毒性机制,筛选敏感、有效的生物标志物对生态毒理学研究和环境风险评价具有重要意义。RNA测序（RNA sequencing,RNA?seq）技术因所需样品量少,且不需参考序列,可在整体水平上鉴定基因差异表达,成为水生生物生态毒理学研究的最佳方法之一。基于此,介绍了RNA?seq技术的基本流程与数据分析过程,对该技术在不同生态位的水生生物（如鱼类、两栖类、贝类、甲壳类等）生态毒理学中的应用展开综述,并对RNA?seq技术面临的不足、挑战及发展趋势进行探讨,以期为该技术在水生生物生态毒理学研究中的应用,尤其是水生态环境中污染物胁迫水生生物机制的阐明及污染水域生态环境恢复提供参考。     

Testing the effect of early‐life reproductive effort on age‐related decline in a wild insect

The disposable soma theory of ageing predicts that when organisms invest in reproduction they do so by reducing their investment in body maintenance, inducing a trade‐off between reproduction and survival. Experiments on invertebrates in the lab provide support for the theory by demonstrating the predicted responses to manipulation of reproductive effort or lifespan. However, experimental studies in birds and evidence from observational (nonmanipulative) studies in nature do not consistently reveal trade‐offs. Most species studied previously in the wild are mammals and birds that reproduce over multiple discrete seasons. This contrasts with temperate invertebrates, which typically have annual generations and reproduce over a single season. We expand the taxonomic range of senescence study systems to include life histories typical of most temperate invertebrates. We monitored reproductive effort, ageing, and survival in a natural field cricket population over ten years to test the prediction that individuals investing more in early‐reproduction senesce faster and die younger. We found no evidence of a trade‐off between early‐life reproductive effort and survival, and only weak evidence for a trade‐off with phenotypic senescence. We discuss the possibility that organisms with multiple discrete breeding seasons may have greater opportunities to express trade‐offs between reproduction and senescence.     

Is RAD‐seq suitable for phylogenetic inference? An in silico assessment and optimization

Inferring phylogenetic relationships between closely related taxa can be hindered by three factors: (1) the lack of informative molecular variation at short evolutionary timescale; (2) the lack of established markers in poorly studied taxa; and (3) the potential phylogenetic conflicts among different genomic regions due to incomplete lineage sorting or introgression. In this context, Restriction site Associated DNA sequencing (RAD‐seq) seems promising as this technique can generate sequence data from numerous DNA fragments scattered throughout the genome, from a large number of samples, and without preliminary knowledge on the taxa under study. However, divergence beyond the within‐species level will necessarily reduce the number of conserved and non‐duplicated restriction sites, and therefore the number of loci usable for phylogenetic inference. Here, we assess the suitability of RAD‐seq for phylogeny using a simulated experiment on the 12 Drosophila genomes, with divergence times ranging from 5 to 63 million years. These simulations show that RAD‐seq allows the recovery of the known Drosophila phylogeny with strong statistical support, even for relatively ancient nodes. Notably, this conclusion is robust to the potentially confounding effects of sequencing errors, heterozygosity, and low coverage. We further show that clustering RAD‐seq data using the BLASTN and SiLiX programs significantly improves the recovery of orthologous RAD loci compared with previously proposed approaches, especially for distantly related species. This study therefore validates the view that RAD sequencing is a powerful tool for phylogenetic inference.     

RNA‐sequencing profiles hippocampal gene expression in a validated model of cancer‐induced depression

To investigate the pathophysiology of cancer‐induced depression (CID), we have recently developed a validated CID mouse model. Given that the efficacy of antidepressants in cancer patients is controversial, it remains unclear whether CID is a biologically distinct form of depression. We used RNA‐sequencing (RNA‐seq) to investigate differentially expressed genes (DEGs) in hippocampi of animals from our CID model relative a positive control model of depressive‐like behavior induced with chronic corticosterone (CORT). To validate RNA‐seq results, we performed quantitative real‐time RT‐PCR (qRT‐PCR) on a subset of DEGs. Enrichment analysis using DAVID was performed on DEGs to identify enriched Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways and biological process gene ontologies (GO:BP). qRT‐PCR results significantly predicted RNA‐seq results. RNA‐seq revealed that most DEGs identified in the CORT model overlapped with the CID model. Enrichment analyses identified KEGG pathways and GO:BP terms associated with ion homeostasis and neuronal communication for both the CORT and CID model. In addition, CID DEGs were enriched in pathways and terms relating to neuronal development, intracellular signaling, learning and memory. This study is the first to investigate CID at the mRNA level. We have shown that most hippocampal mRNA changes that are associated with a depressive‐like state are also associated with cancer. Several other changes occur at the mRNA level in cancer, suggesting that the CID model may represent a biologically distinct form of a depressive‐like state.     

Genotyping‐in‐Thousands by sequencing (GT‐seq) panel development and application to minimally invasive DNA samples to support studies in molecular ecology

Minimally invasive sampling (MIS) is widespread in wildlife studies; however, its utility for massively parallel DNA sequencing (MPS) is limited. Poor sample quality and contamination by exogenous DNA can make MIS challenging to use with modern genotyping‐by‐sequencing approaches, which have been traditionally developed for high‐quality DNA sources. Given that MIS is often more appropriate in many contexts, there is a need to make such samples practical for harnessing MPS. Here, we test the ability for Genotyping‐in‐Thousands by sequencing (GT‐seq), a multiplex amplicon sequencing approach, to effectively genotype minimally invasive cloacal DNA samples collected from the Western Rattlesnake (Crotalus oreganus), a threatened species in British Columbia, Canada. As there was no previous genetic information for this species, an optimized panel of 362 SNPs was selected for use with GT‐seq from a de novo restriction site‐associated DNA sequencing (RADseq) assembly. Comparisons of genotypes generated within and among RADseq and GT‐seq for the same individuals found low rates of genotyping error (GT‐seq: 0.50%; RADseq: 0.80%) and discordance (2.57%), the latter likely due to the different genotype calling models employed. GT‐seq mean genotype discordance between blood and cloacal swab samples collected from the same individuals was also minimal (1.37%). Estimates of population diversity parameters were similar across GT‐seq and RADseq data sets, as were inferred patterns of population structure. Overall, GT‐seq can be effectively applied to low‐quality DNA samples, minimizing the inefficiencies presented by exogenous DNA typically found in minimally invasive samples and continuing the expansion of molecular ecology and conservation genetics in the genomics era.     

CRISPR Editing in Biological and Biomedical Investigation

The CRISPR (clustered regularly interspaced short palindromic repeat)‐Cas (CRISPR‐associated protein) system, a prokaryotic RNA‐based adaptive immune system against viral infection, is emerging as a powerful genome editing tool in broad research areas. To further improve and expand its functionality, various CRISPR delivery strategies have been tested and optimized, and key CRISPR system components such as Cas protein have been engineered with different purposes. Benefiting from more in‐depth understanding and further development of CRISPR, versatile CRISPR‐based platforms for genome editing have been rapidly developed to advance investigations in biology and biomedicine. In biological research area, CRISPR has been widely adopted in both fundamental and applied research fields, such as genomic and epigenomic modification, genome‐wide screening, cell and animal research, agriculture transforming, livestock breeding, food manufacture, industrial biotechnology, and gene drives in disease agents control. In biomedical research area, CRISPR has also shown its extensive applicability in the establishment of animal models for genetic disorders, generation of tissue donors, implementation of antimicrobial and antiviral studies, identification and assessment of new drugs, and even treatment for clinical diseases. However, there are still several problems to consider, and the biggest concerns are the off‐target effects and ethical issues of this technology. In this prospect article, after highlighting recent development of CRISPR systems, we outline different applications and current limitations of CRISPR in biological and biomedical investigation. Finally, we provide a perspective on future development and potential risks of this multifunctional technology. J. Cell. Biochem. 119: 52–61, 2018. © 2017 Wiley Periodicals, Inc.     

Double‐digest RAD sequencing outperforms microsatellite loci at assigning paternity and estimating relatedness: A proof of concept in a highly promiscuous bird

Information on genetic relationships among individuals is essential to many studies of the behaviour and ecology of wild organisms. Parentage and relatedness assays based on large numbers of single nucleotide polymorphism (SNP) loci hold substantial advantages over the microsatellite markers traditionally used for these purposes. We present a double‐digest restriction site‐associated DNA sequencing (ddRAD‐seq) analysis pipeline that, as such, simultaneously achieves the SNP discovery and genotyping steps and which is optimized to return a statistically powerful set of SNP markers (typically 150–600 after stringent filtering) from large numbers of individuals (up to 240 per run). We explore the trade‐offs inherent in this approach through a set of experiments in a species with a complex social system, the variegated fairy‐wren (Malurus lamberti) and further validate it in a phylogenetically broad set of other bird species. Through direct comparisons with a parallel data set from a robust panel of highly variable microsatellite markers, we show that this ddRAD‐seq approach results in substantially improved power to discriminate among potential relatives and considerably more precise estimates of relatedness coefficients. The pipeline is designed to be universally applicable to all bird species (and with minor modifications to many other taxa), to be cost‐ and time‐efficient, and to be replicable across independent runs such that genotype data from different study periods can be combined and analysed as field samples are accumulated.