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采用六种基因组扫描方法来检测地中海条纹红鲻鱼(Mullus surmuletus)耐盐候选基因。

Combining six genome scan methods to detect candidate genes to salinity in the Mediterranean striped red mullet (Mullus surmuletus).

机构信息

CEFE UMR 5175, EPHE, PSL Research University, CNRS, UM, SupAgro, IRD, INRA, 34293, Montpellier, France.

MARBEC UMR 9190, CNRS - IRD - Université Montpellier - Ifremer, 34095, Montpellier, France.

出版信息

BMC Genomics. 2018 Mar 27;19(1):217. doi: 10.1186/s12864-018-4579-z.

Abstract

BACKGROUND

Adaptive genomics may help predicting how a species will respond to future environmental changes. Genomic signatures of local adaptation in marine organisms are often driven by environmental selective agents impacting the physiology of organisms. With one of the highest salinity level, the Mediterranean Sea provides an excellent model to investigate adaptive genomic divergence underlying salinity adaptation. In the present study, we combined six genome scan methods to detect potential genomic signal of selection in the striped red mullet (Mullus surmuletus) populations distributed across a wide salinity gradient. We then blasted these outlier sequences on published fish genomic resources in order to identify relevant potential candidate genes for salinity adaptation in this species.

RESULTS

Altogether, the six genome scan methods found 173 outliers out of 1153 SNPs. Using a blast approach, we discovered four candidate SNPs belonging to three genes potentially implicated in adaptation of M. surmuletus to salinity. The allele frequency at one of these SNPs significantly increases with salinity independently from the effect of longitude. The gene associated to this SNP, SOCS2, encodes for an inhibitor of cytokine and has previously been shown to be expressed under osmotic pressure in other marine organisms. Additionally, our results showed that genome scan methods not correcting for spatial structure can still be an efficient strategy to detect potential footprints of selection, when the spatial and environmental variation are confounded, and then, correcting for spatial structure in a second step represents a conservative method.

CONCLUSION

The present outcomes bring evidences of potential genomic footprint of selection, which suggest an adaptive response of M. surmuletus to salinity conditions in the Mediterranean Sea. Additional genomic data such as sequencing of a full-genome and transcriptome analyses of gene expression would provide new insights regarding the possibility that some striped red mullet populations are locally adapted to their saline environment.

摘要

背景

适应基因组学可以帮助预测一个物种将如何应对未来的环境变化。海洋生物的局部适应的基因组特征通常是由影响生物体生理的环境选择剂驱动的。地中海的盐度水平是最高的之一,为研究盐度适应的基础适应性基因组分歧提供了一个极好的模型。在本研究中,我们结合了六种基因组扫描方法,以检测分布在广泛盐度梯度中的条纹红鲻(Mullus surmuletus)种群中的潜在选择基因组信号。然后,我们将这些异常序列与已发表的鱼类基因组资源进行比对,以确定该物种盐度适应的相关潜在候选基因。

结果

总共,六种基因组扫描方法在 1153 个 SNP 中发现了 173 个异常值。使用 Blast 方法,我们发现了四个候选 SNP,它们属于三个基因,这些基因可能参与了 M. surmuletus 对盐度的适应。这些 SNP 之一的等位基因频率随着盐度的增加而显著增加,而与经度的影响无关。与该 SNP 相关的基因 SOCS2 编码一种细胞因子抑制剂,先前已在其他海洋生物中显示在渗透压下表达。此外,我们的结果表明,当空间和环境变化相互混淆时,不校正空间结构的基因组扫描方法仍然是检测潜在选择足迹的有效策略,然后在第二步中校正空间结构代表一种保守策略。

结论

本研究结果提供了潜在选择基因组足迹的证据,表明 M. surmuletus 对地中海盐度条件的适应反应。额外的基因组数据,如全基因组测序和基因表达的转录组分析,将为一些条纹红鲻种群是否适应其盐环境提供新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7070/5870821/daedefd672e9/12864_2018_4579_Fig1_HTML.jpg

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