Low-frequency somatic mutations are heritable in tropical trees Dicorynia guianensis and Sextonia rubra.

Somatic mutations potentially play a role in plant evolution, but common expectations pertaining to plant somatic mutations remain insufficiently tested. Unlike in most animals, the plant germline is assumed to be set aside late in development, leading to the expectation that plants accumulate somatic mutations along growth. Therefore, several predictions were made on the fate of somatic mutations: mutations have generally low frequency in plant tissues; mutations at high frequency have a higher chance of intergenerational transmission; branching topology of the tree dictates mutation distribution; and exposure to UV (ultraviolet) radiation increases mutagenesis. To provide insights into mutation accumulation and transmission in plants, we produced two high-quality reference genomes and a unique dataset of 60 high-coverage whole-genome sequences of two tropical tree species, Dicorynia guianensis (Fabaceae) and Sextonia rubra (Lauraceae). We identified 15,066 de novo somatic mutations in D. guianensis and 3,208 in S. rubra, surprisingly almost all found at low frequency. We demonstrate that 1) low-frequency mutations can be transmitted to the next generation; 2) mutation phylogenies deviate from the branching topology of the tree; and 3) mutation rates and mutation spectra are not demonstrably affected by differences in UV exposure. Altogether, our results suggest far more complex links between plant growth, aging, UV exposure, and mutation rates than commonly thought.

Estimation of contemporary effective population size in plant populations: Limitations of genomic datasets.

Effective population size (N e) is a pivotal evolutionary parameter with crucial implications in conservation practice and policy. Genetic methods to estimate N e have been preferred over demographic methods because they rely on genetic data rather than time-consuming ecological monitoring. Methods based on linkage disequilibrium (LD), in particular, have become popular in conservation as they require a single sampling and provide estimates that refer to recent generations. A software program based on the LD method, GONE, looks particularly promising to estimate contemporary and recent-historical N e (up to 200 generations in the past). Genomic datasets from non-model species, especially plants, may present some constraints to the use of GONE, as linkage maps and reference genomes are seldom available, and SNP genotyping is usually based on reduced-representation methods. In this study, we use empirical datasets from four plant species to explore the limitations of plant genomic datasets when estimating N e using the algorithm implemented in GONE, in addition to exploring some typical biological limitations that may affect N e estimation using the LD method, such as the occurrence of population structure. We show how accuracy and precision of N e estimates potentially change with the following factors: occurrence of missing data, limited number of SNPs/individuals sampled, and lack of information about the location of SNPs on chromosomes, with the latter producing a significant bias, previously unexplored with empirical data. We finally compare the N e estimates obtained with GONE for the last generations with the contemporary N e estimates obtained with the programs currentNe and NeEstimator.

A micromethod for high throughput RNA extraction in forest trees

A large quantity of high quality RNA is often required in the analysis of gene expression. However, RNA extraction from samples taken from woody plants is generally complex, and represents the main limitation to study gene expression, particularly in refractory species like conifers. Standard RNA extraction protocols are available but they are highly time consuming, and not adapted to large scale extraction. Here we present a high-throughput RNA extraction protocol. This protocol was adapted to a micro-scale by modifying the classical cetyltrimethylammonium (CTAB) protocol developed for pine: (i) quantity of material used (100-200 mg of sample), (ii) disruption of samples in microtube using a mechanical tissue disrupter, and (iii) the use of SSTE buffer. One hundred samples of woody plant tissues/organs can be easily treated in two working days. An average of 15 /ig of high quality RNA per sample was obtained. The RNA extracted is suitable for applications such as real time reverse transcription polymerase chain reaction, cDNA library construction or synthesis of complex targets for microarray analysis.