Historical Datasets Support Genomic Selection Models for the Prediction of Cotton Fiber Quality Phenotypes Across Multiple Environments.

Genomic selection (GS) has successfully been used in plant breeding to improve selection efficiency and reduce breeding time and cost. However, there has not been a study to evaluate GS prediction models that may be used for predicting cotton breeding lines across multiple environments. In this study, we evaluated the performance of Bayes Ridge Regression, BayesA, BayesB, BayesC and Reproducing Kernel Hilbert Spaces regression models.

Nonindigenous Plant Advantage in Native and Exotic Australian Grasses under Experimental Drought, Warming, and Atmospheric CO2 Enrichment.

A general prediction of ecological theory is that climate change will favor invasive nonindigenous plant species (NIPS) over native species. However, the relative fitness advantage enjoyed by NIPS is often affected by resource limitation and potentially by extreme climatic events such as drought. Genetic constraints may also limit the ability of NIPS to adapt to changing climatic conditions.

Phylogeography of Quercus variabilis based on chloroplast DNA sequence in East Asia: multiple glacial refugia and Mainland-migrated island populations.

The biogeographical relationships between far-separated populations, in particular, those in the mainland and islands, remain unclear for widespread species in eastern Asia where the current distribution of plants was greatly influenced by the Quaternary climate. Deciduous Oriental oak (Quercus variabilis) is one of the most widely distributed species in eastern Asia. In this study, leaf material of 528 Q.

Strong spatial genetic structure in peripheral but not core populations of Sitka spruce [Picea sitchensis (Bong.) Carr.].

We examined spatial genetic structure within eight populations of Sitka spruce classified as core or peripheral based on ecological niche, and continuous or disjunct based on species distribution. In each population, 200 trees were spatially mapped and genotyped for eight cDNA-based sequence tagged site (STS) codominant markers. Spatial autocorrelation was assessed by estimating p(ij), the average co-ancestry coefficient, between individuals within distance intervals.