Finding needles in a genomic haystack: targeted capture identifies clear signatures of selection in a nonmodel plant species

Teasing apart neutral and adaptive genomic processes and identifying loci that are targets of selection can be difficult, particularly for nonmodel species that lack a reference genome. However, identifying such loci and the factors driving selection have the potential to greatly assist conservation and restoration practices, especially for the management of species in the face of contemporary and future climate change. Here, we focus on assessing adaptive genomic variation within a nonmodel plant species, the narrow‐leaf hopbush (Dodonaea viscosa ssp. angustissima), commonly used for restoration in Australia. We used a hybrid‐capture target enrichment approach to selectively sequence 970 genes across 17 populations along a latitudinal gradient from 30°S to 36°S. We analysed 8462 single‐nucleotide polymorphisms (SNPs) for F_ST outliers as well as associations with environmental variables. Using three different methods, we found 55 SNPs with significant correlations to temperature and water availability, and 38 SNPs to elevation. Genes containing SNPs identified as under environmental selection were diverse, including aquaporin and abscisic acid genes, as well as genes with ontologies relating to responses to environmental stressors such as water deprivation and salt stress. Redundancy analysis demonstrated that only a small proportion of the total genetic variance was explained by environmental variables. We demonstrate that selection has led to clines in allele frequencies in a number of functional genes, including those linked to leaf shape and stomatal variation, which have been previously observed to vary along the sampled environmental cline. Using our approach, gene regions subject to environmental selection can be readily identified for nonmodel organisms.     

Application of SNPs for population genetics of nonmodel organisms: new opportunities and challenges

Recent improvements in the speed, cost and accuracy of next generation sequencing are revolutionizing the discovery of single nucleotide polymorphisms (SNPs). SNPs are increasingly being used as an addition to the molecular ecology toolkit in nonmodel organisms, but their efficient use remains challenging. Here, we discuss common issues when employing SNP markers, including the high numbers of markers typically employed, the effects of ascertainment bias and the inclusion of nonneutral loci in a marker panel. We provide a critique of considerations specifically associated with the application and population genetic analysis of SNPs in nonmodel taxa, focusing specifically on some of the most commonly applied methods.     

基于新一代测序技术的昆虫转录组学研究进展

新一代测序技术具有快速、 高通量和低成本的特点, 为“组学”研究带来了新方法、 新方案, 正在深刻地改变着当前生物学的研究模式。近年来, 新一代测序技术极大促进了昆虫特别是无参考基因组信息昆虫的转录组学研究。自2008年至今, 采用新一代测序技术已对7个目的68种昆虫进行了转录组测序, 其中由我国学者完成了6个目的22种昆虫的转录组测序。目前, 昆虫转录组学研究主要集中在基因挖掘、 分子标记开发、 基因表达分析等方面, 为全面揭示昆虫生命活动中相关基因功能、 系统发生与进化以及昆虫与其他生物相互作用等奠定了基础。本文总结了当前昆虫转录组学研究的已有成果, 分析了其今后的发展趋势, 讨论了采用新一代测序技术开展昆虫转录组学研究中存在的诸如研究对象相对局限、 测序准确性不够高等不足, 并指出开展昆虫转录组学研究时需充分思考所要回答的科学问题, 选择合适的研究策略, 评估性价比, 以及开发转录组信息高效利用的方法等。作者建议未来的研究方向侧重于： （1）大规模开展基于新一代测序技术的昆虫转录组学研究, 特别是对其他目以及独特生态环境中的代表性昆虫应予以重点关注; （2）开发昆虫转录组数据存储及分析的软硬件; （3）合理利用新一代测序技术研究昆虫转录组并充分挖掘已测昆虫转录组中的遗传信息。     

dRNA-seq原理及其在原核生物转录组学研究中的应用

第二代测序技术不仅推进了基因组学的研究, 而且也广泛应用到转录组学的研究中。原核生物转录组学的研究方法主要有Tiling芯片和RNA-seq, 后者因其较高的覆盖率和分辨率以及越来越低廉的成本而逐渐被更多的研究单位采用。根据对mRNA富集方法或rRNA去除方法的不同, 目前RNA-seq方法主要有6种, 其中dRNA-seq由于采用了5′单磷酸依赖的外切酶, 可以特异性地降解加工过的转录本, 从而使初始转录本得到富集, 已被广泛应用到原核生物转录起始位点、小的调控RNA、启动子及操纵子等研究中。文章对dRNA-seq的原理、技术流程及其在原核生物转录组学研究中的应用进行了综述, 并对这一研究方法在现阶段应用的优势和局限性进行了讨论, 也进一步对该方法在未来的发展和应用进行了展望, 期望为国内相关领域研究人员提供参考。     

Linkage disequilibrium network analysis (LDna) gives a global view of chromosomal inversions,local adaptation and geographic structure

Recent advances in sequencing allow population‐genomic data to be generated for virtually any species. However, approaches to analyse such data lag behind the ability to generate it, particularly in nonmodel species. Linkage disequilibrium (LD, the nonrandom association of alleles from different loci) is a highly sensitive indicator of many evolutionary phenomena including chromosomal inversions, local adaptation and geographical structure. Here, we present linkage disequilibrium network analysis (LDna), which accesses information on LD shared between multiple loci genomewide. In LD networks, vertices represent loci, and connections between vertices represent the LD between them. We analysed such networks in two test cases: a new restriction‐site‐associated DNA sequence (RAD‐seq) data set for Anopheles baimaii, a Southeast Asian malaria vector; and a well‐characterized single nucleotide polymorphism (SNP) data set from 21 three‐spined stickleback individuals. In each case, we readily identified five distinct LD network clusters (single‐outlier clusters, SOCs), each comprising many loci connected by high LD. In A. baimaii, further population‐genetic analyses supported the inference that each SOC corresponds to a large inversion, consistent with previous cytological studies. For sticklebacks, we inferred that each SOC was associated with a distinct evolutionary phenomenon: two chromosomal inversions, local adaptation, population‐demographic history and geographic structure. LDna is thus a useful exploratory tool, able to give a global overview of LD associated with diverse evolutionary phenomena and identify loci potentially involved. LDna does not require a linkage map or reference genome, so it is applicable to any population‐genomic data set, making it especially valuable for nonmodel species.