Amborella trichopoda is strongly supported as the single living species of the sister lineage to all other extant flowering plants, providing a unique reference for inferring the genome content and structure of the most recent common ancestor (MRCA) of living angiosperms. Sequencing the Amborella genome, we identified an ancient genome duplication predating angiosperm diversification, without evidence of subsequent, lineage-specific genome duplications. Comparisons between Amborella and other angiosperms facilitated reconstruction of the ancestral angiosperm gene content and gene order in the MRCA of core eudicots. We identify new gene families, gene duplications, and floral protein-protein interactions that first appeared in the ancestral angiosperm. Transposable elements in Amborella are ancient and highly divergent, with no recent transposon radiations. Population genomic analysis across Amborella's native range in New Caledonia reveals a recent genetic bottleneck and geographic structure with conservation implications.

Summary• Genomic selection is increasingly considered vital to accelerate genetic improvement. However, it is unknown how accurate genomic selection prediction models remain when used across environments and ages. This knowledge is critical for breeders to apply this strategy in genetic improvement.• Here, we evaluated the utility of genomic selection in a Pinus taeda population of c. 800 individuals clonally replicated and grown on four sites, and genotyped for 4825 singlenucleotide polymorphism (SNP) markers. Prediction models were estimated for diameter and height at multiple ages using genomic random regression best linear unbiased predictor (BLUP).• Accuracies of prediction models ranged from 0.65 to 0.75 for diameter, and 0.63 to 0.74 for height. The selection efficiency per unit time was estimated as 53-112% higher using genomic selection compared with phenotypic selection, assuming a reduction of 50% in the breeding cycle. Accuracies remained high across environments as long as they were used within the same breeding zone. However, models generated at early ages did not perform well to predict phenotypes at age 6 yr.• These results demonstrate the feasibility and remarkable gain that can be achieved by incorporating genomic selection in breeding programs, as long as models are used at the relevant selection age and within the breeding zone in which they were estimated.

Prolactin (PRL) stimulates breast cancer cell proliferation; however, the involvement of PRL-activated signaling molecules in cell proliferation is not fully established. Here we studied the role of c-Src on PRL-stimulated proliferation of T47D and MCF7 breast cancer cells. We initially observed that PRL-dependent activation of focal adhesion kinase (Fak), Erk1/2, and cell proliferation was mediated by c-Src in T47D cells, because expression of a dominant-negative form of c-Src (SrcDM, K295A/Y527F) blocked the PRL-dependent effects. The Src inhibitor PP1 abrogated PRL-dependent in vivo activation of Fak, Erk1/2, p70S6K, and Akt and the proliferation of T47D and MCF7 cells; Janus kinase 2 (Jak2) activation was not affected. However, in vitro, Fak and Jak2 kinases were not directly inhibited by PP1, demonstrating the effect of PP1 on c-Src kinase as an upstream activator of Fak. Expression of Fak mutant Y397F abrogated PRL-dependent activation of Fak, Erk1/2, and thymidine incorporation, but had no effect on p70S6K and Akt kinases. MAPK kinase 1/2 (Mek1/2) inhibitor PD184352 blocked PRL-induced stimulation of Erk1/2 and cell proliferation; however, p70S6K and Akt activation were unaffected. The phosphatidylinositol 3-kinase (PI3K) inhibitor LY294002 abolished cell proliferation and activation of p70S6K and Akt; however, PRL-dependent activation of Erk1/2 was not modified. Moreover, we show that both c-Src/PI3K and c-Src/Fak/Erk1/2 pathways are involved in the up-regulation of c-myc and cyclin d1 expression mediated by PRL. The previous findings suggest the existence of two PRL-dependent signaling cascades, initiated by the c-Src-mediated activation of Fak/Erk1/2 and PI3K pathways that, subsequently, control the expression of c-Myc and cyclin D1 and the proliferation of T47D and MCF7 breast cancer cells.

Understanding the consequences of local adaptation at the genomic diversity is a central goal in evolutionary genetics of natural populations. In species with large continuous geographical distributions the phenotypic signal of local adaptation is frequently clear, but the genetic basis often remains elusive. We examined the patterns of genetic diversity in Pinus sylvestris, a keystone species in many Eurasian ecosystems with a huge distribution range and decades of forestry research showing that it is locally adapted to the vast range of environmental conditions. Making P. sylvestris an even more attractive subject of local adaptation study, population structure has been shown to be weak previously and in this study. However, little is known about the molecular genetic basis of adaptation, as the massive size of gymnosperm genomes has prevented large scale genomic surveys. We generated a both geographically and genomically extensive dataset using a targeted sequencing approach. By applying divergence-based and landscape genomics methods we identified several loci contributing to local adaptation, but only few with large allele frequency changes across latitude. We also discovered a very large (ca. 300 Mbp) putative inversion potentially under selection, which to our knowledge is the first such discovery in conifers. Our results call for more detailed analysis of structural variation in relation to genomic basis of local adaptation, emphasize the lack of large effect loci contributing to local adaptation in the coding regions and thus point out the need for more attention towards multi-locus analysis of polygenic adaptation.

Understanding the consequences of local adaptation at the genomic diversity is a central goal in evolutionary genetics of natural populations. In species with large continuous geographical distributions the phenotypic signal of local adaptation is frequently clear, but the genetic background often remains elusive. We examined the patterns of genetic diversity in Pinus sylvestris, a keystone species in many Eurasian ecosystems with a huge distribution range and decades of forestry research showing that it is locally adapted to the vast range of environmental conditions. Making P. sylvestris an even more attractive subject of local adaptation study, population structure has been shown to be weak previously and in this study. However, little is known about the molecular genetic basis of adaptation, as the massive size of gymnosperm genomes has prevented large scale genomic surveys. We generated a both geographically and genomically extensive dataset using a targeted sequencing approach. By applying divergence-based and landscape genomics methods we found that several coding loci contribute to local adaptation. We also discovered a very large (ca. 300 Mbp) putative inversion with a signal of local adaptation, which to our knowledge is the first such discovery in conifers. Our results call for more detailed analysis of structural variation in relation to genomic basis of local adaptation, emphasize the lack of large effect loci contributing to local adaptation in the coding regions and thus point out to the need for more attention towards multi-locus analysis of polygenic adaptation.

Leptocybe invasa is an insect pest causing gall formation on oviposited shoot tips and leaves of Eucalyptus trees leading to leaf deformation, stunting, and death in severe cases. We previously observed different constitutive and induced terpenes, plant specialized metabolites that may act as attractants or repellents to insects, in a resistant and susceptible clone of Eucalyptus challenged with L. invasa. We tested the hypothesis that specific terpenes are associated with pest resistance in a Eucalyptus grandis half-sib population. Insect damage was scored over 2 infestation cycles, and leaves were harvested for near-infrared reflectance (NIR) and terpene measurements. We used Bayesian model averaging for terpene selection and obtained partial least squares NIR models to predict terpene content and L. invasa infestation damage. In our optimal model, 29% of the phenotypic variation could be explained by 7 terpenes, and the monoterpene combination, limonene, α-terpineol, and 1,8-cineole, could be predicted with an NIR prediction ability of  .67. Bayesian model averaging supported α-pinene, γ-terpinene, and iso-pinocarveol as important for predicting L. invasa infestation. Susceptibility was associated with increased γ-terpinene and α-pinene, which may act as a pest attractant, whereas reduced susceptibility was associated with iso-pinocarveol, which may act to recruit parasitoids or have direct toxic effects.

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Global near infrared spectroscopy models (multiple-species, multiple-sites) were developed to predict chemical properties of Eucalyptus wood. The sample data set included 186 samples from four data sets (five species) originating from six countries: Eucalyptus urophylla from Argentina, Colombia, Venezuela, and South Africa; Eucalyptus dunnii from Uruguay; Eucalyptus globulus and Eucalyptus nitens from Chile; and Eucalyptus grandis from Colombia. The 186 samples were all preselected from larger collections of 400 to nearly 1800 samples to represent the range of chemical and spectral variation in each data set. The chemical traits modeled were total lignin, insoluble lignin, soluble lignin, syringyl-guaiacyl ratio (S/G), glucose, xylose, galactose, arabinose, and mannose. Single-species models and global multiple-species models were developed for each chemical constituent. For the global model, the R 2 cv for total lignin, insoluble lignin and syringylguaiacyl ratio were 0.95, 0.96, and 0.86, respectively. An alternate expression of the syringyl-guaiacyl relationship (S/(SþG)) resulted in better near infrared calibrations (e.g., for the global model, R 2 cv ¼ 0.95). The global models for sugar content were also very good, but were slightly inferior to those for the lignin related traits, with R 2 cv ¼ 0.74 for glucose, 0.89 for xylose, and from 0.72 to 0.91 for the minor sugars. To investigate the utility of the global models to predict chemical traits for species not included in the calibration, three-species calibrations were used to predict each trait in a fourth species data set. The prediction fit statistics ranged from excellent to poor depending on the species and trait, but in general the predictions would be at least moderately useful for most species-trait combinations. For some species-trait combinations with poor initial predictions from the global model, the inclusion of 10 samples from the ''new'' species into the calibration global model improved the fit statistics substantially. The global calibrations will be useful in tree breeding programs to rank species, families, and clones for important wood chemical traits.