Laboratory of Genomic Research and Biotechnology, Federal Research Center "Krasnoyarsk Science Center of the Siberian Branch of the Russian Academy of Sciences", 660036 Krasnoyarsk, Russia.
Laboratory of Forest Genomics, Genome Research and Education Center, Institute of Fundamental Biology and Biotechnology, Siberian Federal University, 660041 Krasnoyarsk, Russia.
Int J Mol Sci. 2023 Feb 25;24(5):4530. doi: 10.3390/ijms24054530.
Forest trees growing in high altitude conditions offer a convenient model for studying adaptation processes. They are subject to a whole range of adverse factors that are likely to cause local adaptation and related genetic changes. Siberian larch ( Ledeb.), whose distribution covers different altitudes, makes it possible to directly compare lowland with highland populations. This paper presents for the first time the results of studying the genetic differentiation of Siberian larch populations, presumably associated with adaptation to the altitudinal gradient of climatic conditions, based on a joint analysis of altitude and six other bioclimatic variables, together with a large number of genetic markers, single nucleotide polymorphisms (SNPs), obtained from double digest restriction-site-associated DNA sequencing (ddRADseq). In total, 25,143 SNPs were genotyped in 231 trees. In addition, a dataset of 761 supposedly selectively neutral SNPs was assembled by selecting SNPs located outside coding regions in the Siberian larch genome and mapped to different contigs. The analysis using four different methods (PCAdapt, LFMM, BayeScEnv and RDA) revealed 550 outlier SNPs, including 207 SNPs whose variation was significantly correlated with the variation of some of environmental factors and presumably associated with local adaptation, including 67 SNPs that correlated with altitude based on either LFMM or BayeScEnv and 23 SNPs based on both of them. Twenty SNPs were found in the coding regions of genes, and 16 of them represented non-synonymous nucleotide substitutions. They are located in genes involved in the processes of macromolecular cell metabolism and organic biosynthesis associated with reproduction and development, as well as organismal response to stress. Among these 20 SNPs, nine were possibly associated with altitude, but only one of them was identified as associated with altitude by all four methods used in the study, a nonsynonymous SNP in scaffold_31130 in position 28092, a gene encoding a cell membrane protein with uncertain function. Among the studied populations, at least two main groups (clusters), the Altai populations and all others, were significantly genetically different according to the admixture analysis based on any of the three SNP datasets as follows: 761 supposedly selectively neutral SNPs, all 25,143 SNPs and 550 adaptive SNPs. In general, according to the AMOVA results, genetic differentiation between transects or regions or between population samples was relatively low, although statistically significant, based on 761 neutral SNPs ( = 0.036) and all 25,143 SNPs ( = 0.017). Meanwhile, the differentiation based on 550 adaptive SNPs was much higher ( = 0.218). The data showed a relatively weak but highly significant linear correlation between genetic and geographic distances ( = 0.206, = 0.001).
生长在高海拔地区的森林树木为研究适应过程提供了一个方便的模型。它们受到一系列可能导致局部适应和相关遗传变化的不利因素的影响。西伯利亚落叶松( Ledeb.)的分布涵盖了不同的海拔高度,这使得我们可以直接比较低地和高地种群。本文首次介绍了基于联合分析海拔和其他六个生物气候变量以及大量遗传标记(单核苷酸多态性(SNPs))的结果,这些标记是通过双酶切限制位点相关 DNA 测序(ddRADseq)获得的,研究了西伯利亚落叶松种群的遗传分化,这些种群可能与适应气候条件的海拔梯度有关。总共在 231 棵树上对 25,143 个 SNPs 进行了基因型分析。此外,通过选择位于西伯利亚落叶松基因组编码区之外的 SNPs 并将其映射到不同的连续体上,组装了一个包含 761 个假定选择性中性 SNPs 的数据集。使用四种不同的方法(PCAdapt、LFMM、BayeScEnv 和 RDA)进行的分析揭示了 550 个异常 SNP,其中 207 个 SNP 的变异与一些环境因素的变异显著相关,并且可能与局部适应有关,包括基于 LFMM 或 BayeScEnv 与海拔相关的 67 个 SNP 和基于两者的 23 个 SNP。在基因的编码区域发现了 20 个 SNP,其中 16 个代表非同义核苷酸替换。它们位于与繁殖和发育有关的大分子细胞代谢和有机生物合成过程以及生物体对压力的反应相关的基因中。在这 20 个 SNP 中,有 9 个可能与海拔有关,但只有一个 SNP 被研究中使用的四种方法中的每一种都确定与海拔有关,即位于位置 28092 的支架 31130 中的非同义 SNP,该基因编码一种具有不确定功能的细胞膜蛋白。在所研究的种群中,根据基于三个 SNP 数据集(761 个假定选择性中性 SNP、所有 25,143 个 SNP 和 550 个适应性 SNP)中的任何一个进行的混合分析,至少有两个主要群体(集群),即阿尔泰种群和其他所有种群,在遗传上存在显著差异。一般来说,根据 AMOVA 结果,基于 761 个中性 SNP( = 0.036)和所有 25,143 SNP( = 0.017),种间或区域间或种群样本间的遗传分化相对较低,尽管具有统计学意义。同时,基于 550 个适应性 SNP 的分化要高得多( = 0.218)。数据显示遗传和地理距离之间存在较弱但高度显著的线性相关性( = 0.206, = 0.001)。