Identification and characterisation of novel SNP markers in Atlantic cod: Evidence for directional selection

<p>Abstract</p> <p>Background</p> <p>The Atlantic cod (<it>Gadus morhua</it>) is a groundfish of great economic value in fisheries and an emerging species in aquaculture. Genetic markers are needed to identify wild stocks in order to ensure sustainable management, and for marker-assisted selection and pedigree determination in aquaculture. Here, we report on the development and evaluation of a large number of Single Nucleotide Polymorphism (SNP) markers from the alignment of Expressed Sequence Tag (EST) sequences in Atlantic cod. We also present basic population parameters of the SNPs in samples of North-East Arctic cod and Norwegian coastal cod obtained from three different localities, and test for SNPs that may have been targeted by natural selection.</p> <p>Results</p> <p>A total of 17,056 EST sequences were used to find 724 putative SNPs, from which 318 segregating SNPs were isolated. The SNPs were tested on Atlantic cod from four different sites, comprising both North-East Arctic cod (NEAC) and Norwegian coastal cod (NCC). The average heterozygosity of the SNPs was 0.25 and the average minor allele frequency was 0.18. <it>F</it>_{<it>ST </it>}values were highly variable, with the majority of SNPs displaying very little differentiation while others had <it>F</it>_{<it>ST </it>}values as high as 0.83. The <it>F</it>_{<it>ST </it>}values of 29 SNPs were found to be larger than expected under a strictly neutral model, suggesting that these loci are, or have been, influenced by natural selection. For the majority of these outlier SNPs, allele frequencies in a northern sample of NCC were intermediate between allele frequencies in a southern sample of NCC and a sample of NEAC, indicating a cline in allele frequencies similar to that found at the Pantophysin I locus.</p> <p>Conclusion</p> <p>The SNP markers presented here are powerful tools for future genetics work related to management and aquaculture. In particular, some SNPs exhibiting high levels of population divergence have potential to significantly enhance studies on the population structure of Atlantic cod.</p

Bud-burst modelling in Siberia and its impact on quantifying the carbon budget

Vegetation phenology is affected by climate change and in turn feeds back on climate by affecting the annual carbon uptake by vegetation. To quantify the impact of phenology on terrestrial carbon fluxes, we calibrate a bud-burst model and embed it in the Sheffield Dynamic Global Vegetation Model (SDGVM) in order to perform carbon budget calculations. Bud-burst dates derived from the VEGETATION sensor onboard the SPOT-4 satellite are used to calibrate a range of bud-burst models. This dataset has been recently developed using a new methodology based on the Normalised Difference Water Index (NDWI), which is able to distinguish snowmelt from the onset of vegetation activity after winter. After calibration, a simple spring warming model was found to perform as well as more complex models accounting for a chilling requirement, hence was used for the carbon flux calculations. The root mean square difference between the calibrated model and the VEGETATION dataset was 6.5 days, and was 6.9 days between the calibrated model and independent ground observations of bud-burst available at 9 locations over Siberia. The effects of bud-burst model uncertainties on the carbon budget were evaluated using the SDGVM. The 6.5 days RMS difference in the bud-burst date (a 6% variation in the growing season length), treated as a random noise, translates into about 41 gCm-2 year-1 in Net Primary Production (NPP), which corresponds to 8% of the mean NPP. This is a moderate impact and suggests the calibrated model is accurate enough for carbon budget calculations. In addition to random differences between the calibrated model and VEGETATION data, systematic errors between the calibrated bud-burst model and true ground behaviour may occur, because of bias in the temperature dataset or because the bud-burst detected by VEGETATION is due to some other phenological indicator. A systematic error of one day in bud-burst translates into a 10 gCm-2 year-1 error in NPP (about 2%). Based on the limited available ground data, any systematic error due to using the VEGETATION data should not lead to significant errors in the calculated carbon flux. In contrast, widely-used methods based on the Normalised Difference Vegetation Index (NDVI) from the AVHRR satellite are likely to confuse snowmelt and vegetation greening, leading to errors of up to 15 days in bud-burst date, with consequent large errors in carbon flux calculations