Genomic selection for resistance to mammalian bark stripping and associated chemical compounds in radiata pine

The Construction of lncRNA/circRNA-miRNA-mRNA Networks Reveals Functional Genes Related to Growth Traits in Schima superba

Schima superba is a precious timber and fire-resistant tree species widely distributed in southern China. Currently, there is little knowledge related to its growth traits, especially with respect to molecular breeding. The lack of relevant information has delayed the development of modern breeding. The purpose is to identify probable functional genes involved in S. superba growth through whole transcriptome sequencing. In this study, a total of 32,711 mRNAs, 525 miRNAs, 54,312 lncRNAs, and 1522 circRNAs were identified from 10 S. superba individuals containing different volumes of wood. Four possible regulators, comprising three lncRNAs, one circRNA, and eleven key miRNAs, were identified from the regulatory networks of lncRNA-miRNA-mRNA and circRNA-miRNA-mRNA to supply information on ncRNAs. Several candidate genes involved in phenylpropane and cellulose biosynthesis pathways, including Ss4CL2, SsCSL1, and SsCSL2, and transcription factors, including SsDELLA2 (SsSLR), SsDELLA3 (SsSLN), SsDELLA5 (SsGAI-like2), and SsNAM1, were identified to reveal the molecular regulatory mechanisms regulating the growth traits of S. superba. The results not merely provide candidate functional genes related to S. superba growth trait and will be useful to carry out molecular breeding, but the strategy and method also provide scientists with an effective approach to revealing mechanisms behind important economic traits in other species.

A simulation study comparing advanced marker-assisted selection with genomic selection in tree breeding programs

Advances in DNA sequencing technologies allow the sequencing of whole genomes of thousands of individuals and provide several million single nucleotide polymorphisms (SNPs) per individual. These data combined with precise and high-throughput phenotyping enable genome-wide association studies (GWAS) and the identification of SNPs underlying traits with complex genetic architectures. The identified causal SNPs and estimated allelic effects could then be used for advanced marker-assisted selection (MAS) in breeding programs. But could such MAS compete with the broadly used genomic selection (GS)? This question is of particular interest for the lengthy tree breeding strategies. Here, with our new software "SNPscan breeder," we simulated a simple tree breeding program and compared the impact of different selection criteria on genetic gain and inbreeding. Further, we assessed different genetic architectures and different levels of kinship among individuals of the breeding population. Interestingly, apart from progeny testing, GS using gBLUP performed best under almost all simulated scenarios. MAS based on GWAS results outperformed GS only if the allelic effects were estimated in large populations (ca. 10,000 individuals) of unrelated individuals. Notably, GWAS using 3,000 extreme phenotypes performed as good as the use of 10,000 phenotypes. GS increased inbreeding and thus reduced genetic diversity more strongly compared to progeny testing and GWAS-based selection. We discuss the practical implications for tree breeding programs. In conclusion, our analyses further support the potential of GS for forest tree breeding and improvement, although MAS may gain relevance with decreasing sequencing costs in the future.

Genetic diversity and population structure of Vernonia amygdalina Del. in Uganda based on genome wide markers

Determining the extent and distribution of genetic diversity is an essential component of plant breeding. In the present study, we explored the genetic diversity and population structure of Vernonia amygdalina, a fodder, vegetable and medicinal species of Africa and some parts of Yemen. Most empirical studies demonstrate that populations that are separated by geographic or ecological factors may experience genetic differentiation resulting from restricted gene flow between populations. A total of 238 individuals were sampled from two populations: i) Lake Victoria crescent (LVC) and ii) Southern and Eastern Lake Kyoga basin (SEK) agroecological zones of Uganda and genotyped using DArT platform. Of the two populations, the overall mean observed heterozygosity (Ho) was low to medium (Ho = 0.07[silicoDArTs] and 0.2[SNPs]). Inbreeding levels were also very low (-0.04 to -0.08) suggesting the presence of random mating. Partitioning of genetic structure in the two populations indicated that SEK exhibited a higher genetic diversity than LVC. The principal coordinates analysis (PCA) showed no geographical structuring, consistent with the low genetic differentiation (Fst = 0.00) and the low Euclidean genetic distance (1.38-1.39) between the LVC and SEK populations. However, STRUCTURE analysis with admixture models revealed weak possible genetic clusters with very small genetic distance among them. Overall, the results suggest low genetic diversity and weak genetic differentiation between the two populations. One possible explanation of the results could be the presence of human assisted gene flow over long distances.