Библиографическое описание:Genetic Adaptation of Siberian Larch (Larix sibirica Ledeb.) to High Altitudes : научное издание / Serafima V. Novikova [et al.]. - Текст : непосредственный // International Journal of Molecular Sciences. - 2023. - Т.24, №5. - P. 4530. - ISSN 1661-6596. - ISSN 1422-0067, DOI 10.3390/ijms24054530.
Аннотация: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 (Larix sibirica 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 (FST = 0.036) and all 25,143 SNPs (FST = 0.017). Meanwhile, the differentiation based on 550 adaptive SNPs was much higher (FST = 0.218). The data showed a relatively weak but highly significant linear correlation between genetic and geographic distances (r = 0.206, p = 0.001).
Источник:International Journal of Molecular Sciences
Выпуск:Т.24, №5
Номера страниц:4530
Держатель оригинала документа:A. N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Center for Integrated Breeding Research, George-August University of Göttingen, Federal Research Center “Krasnoyarsk Science Center of the Siberian Branch of the Russian Academy of Sciences”, Federal State Budgetary Educational Institution of Higher Professional Education Voronezh State Forestry Engineering University named after G.F. Morozov, Genome Research and Education Center, Institute of Fundamental Biology and Biotechnology, Siberian Federal University, Georg-August University of Göttingen, Institute of Fundamental Biology and Biotechnology, Siberian Federal University, Institute of Space and Information Technologies, Siberian Federal University, N. I. Vavilov Institute of General Genetics, Russian Academy of Sciences, Tauber Bioinformatics Research Center, University of Haifa, V. N. Sukachev Institute of Forest, Siberian Branch of Russian Academy of Sciences
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