Pinus aristata, P. balfouriana und P. longaeva, drei bemerkenswerte Kiefernarten aus dem Südwesten der USA

Pinus aristata, Pinus balfouriana und Pinus longaeva sind drei ähnliche Kiefernarten. Sie sind im Westen der USA heimisch und können mit über 1000 Jahren sehr alt werden. Wichtige Unterscheidungsmerkmale beziehen sich auf die Nadeln. Eigene Untersuchungen zeigen, dass aber die Zahl der Harzkanäle pro Nadel kein bestimmungsrelevantes Merkmal ist, obwohl dies in der Literatur oft angegeben wird. Die drei Kiefernarten werden mit ihrer Biologie, Morphologie und Ökologie vorgestellt.

The genetic architecture of local adaptation II: The QTL landscape of water-use efficiency for foxtail pine (Pinus balfouriana Grev. & Balf.)

Water availability is an important driver of the geographic distribution of many plant species, although its importance relative to other climatic variables varies across climate regimes and species. A common indirect measure of water-use efficiency (WUE) is the ratio of carbon isotopes (δ13C) fixed during photosynthesis, especially when analyzed in conjunction with a measure of leaf-level resource utilization (δ15N). Here, we test two hypotheses about the genetic architecture of WUE for foxtail pine (Pinus balfouriana Grev. & Balf.) using a novel mixture of double digest restriction site associated DNA sequencing, species distribution modeling, and quantitative genetics. First, we test the hypothesis that water availability is an important determinant of the geographical range of foxtail pine. Second, we test the hypothesis that variation in δ13C and δ15N is genetically based, differentiated between regional populations, and has genetic architectures that include loci of large effect. We show that precipitation-related variables structured the geographical range of foxtail pine, climate-based niches differed between regional populations, and δ13C and δ15N were heritable with moderate signals of differentiation between regional populations. A set of large-effect QTLs (n = 11 for δ13C; n = 10 for δ15N) underlying δ13C and δ15N variation, with little to no evidence of pleiotropy, was discovered using multiple-marker, half-sibling regression models. Our results represent a first approximation to the genetic architecture of these phenotypic traits, including documentation of several patterns consistent with δ13C being a fitness-related trait affected by natural selection.

The genetic architecture of local adaptation I: The genomic landscape of foxtail pine (Pinus balfouriana Grev. & Balf.) as revealed from a high-density linkage map

Explaining the origin and evolutionary dynamics of the genetic architecture of adaptation is a major research goal of evolutionary genetics. Despite controversy surrounding success of the attempts to accomplish this goal, a full understanding of adaptive genetic variation necessitates knowledge about the genomic location and patterns of dispersion for the genetic components affecting fitness-related phenotypic traits. Even with advances in next generation sequencing technologies, the production of full genome sequences for non-model species is often cost prohibitive, especially for tree species such as pines where genome size often exceeds 20 to 30 Gbp. We address this need by constructing a dense linkage map for fox- tail pine (Pinus balfouriana Grev. & Balf.), with the ultimate goal of uncovering and explaining the origin and evolutionary dynamics of adaptive genetic variation in natural populations of this forest tree species. We utilized megagametophyte arrays (n = 76?95 megagametophytes/tree) from four maternal trees in combination with double-digestion restriction site associated DNA sequencing (ddRADseq) to produce a consensus linkage map covering 98.58% of the foxtail pine genome, which was estimated to be 1276 cM in length (95% CI: 1174cM to 1378cM). A novel bioinformatic approach using iterative rounds of marker ordering and imputation was employed to produce single-tree linkage maps (507?17066 contigs/map; lengths: 1037.40?1572.80 cM). These linkage maps were collinear across maternal trees, with highly correlated marker orderings (Spearman's ρ > 0.95). A consensus linkage map derived from these single-tree linkage maps contained 12 linkage groups along which 20 655 contigs were non-randomly distributed across 901 unique positions (n = 23 contigs/position), with an average spacing of 1.34 cM between adjacent positions. Of the 20 655 contigs positioned on the consensus linkage map, 5627 had enough sequence similarity to contigs contained within the most recent build of the loblolly pine (P. taeda L.) genome to identify them as putative homologs containing both genic and non-genic loci. Importantly, all 901 unique positions on the consensus linkage map had at least one contig with putative homology to loblolly pine. When combined with the other biological signals that predominate in our data (e.g., correlations of recombination fractions across single trees), we show that dense linkage maps for non-model forest tree species can be efficiently constructed using next generation sequencing technologies. We subsequently discuss the usefulness of these maps as community-wide resources and as tools with which to test hypotheses about the genetic architecture of adaptation.