Biology subjects

Tan, B.

Publications and source records attributed to Tan, B..

4 recordsLinked to original sources

bioRxiv2017

Natural variation at FLOWERING LOCUS T2 mediates local adaptation in a key life history trait in European aspen

BackgroundThe initiation of growth cessation and dormancy represent critical life-history tradeoffs between survival and growth, and have important fitness effects in perennial plants. Such adaptive life history traits often show strong local adaptation along environmental gradients but despite their importance, the genetic architecture of these traits remains poorly understood.\n\nResultsWe integrate whole genome re-sequencing with environmental and phenotypic data from common garden experiments to investigate the genomic basis of local adaptation across a latitudinal gradient in European aspen (Populus tremula). We discover a single genomic region containing the PtFT2 gene that mediates local adaptation in the timing of bud set and that explains 65% of the observed genetic variation in bud set. This locus is the likely target of a recent selective sweep that originated right before or during colonization of northern Scandinavia following the last glaciation. Field and greenhouse experiments confirm that variation in PtFT2 gene expression affect the phenotypic variation in bud set that we observe in wild natural populations.\n\nConclusionsOur results reveal a major effect locus that determine the timing of bud set and that have facilitated rapid adaptation to shorter growing seasons and colder climates in European aspen. The discovery of a single locus explaining a substantial fraction of the variation in a key life history trait is remarkable given that such traits are generally considered to be highly polygenic. These findings provide a dramatic illustration of how loci of large-effect for adaptive traits can arise and be maintained over large geographical scales in natural populations.

evolutionary biology↗

bioRxiv2017

Genomic prediction reveals significant non-additive effects for growth in hybrid Eucalyptus

Non-additive genetic effects can be effectively exploited in control-pollinated families with the availability of genome-wide markers. We used 41,304 SNP markers and compared pedigree vs. marker-based genetic models by analysing height, diameter, basic density and pulp yield for 338 Eucalyptus urophylla x E.grandis control-pollinated families represented by 949 informative individuals. We evaluated models accounting for additive, dominance, and first-order epistatic interactions (additive by additive, dominance by dominance, and additive by dominance). We showed that the models can capture a large proportion of the genetic variance from dominance and epistasis for growth traits as those components are typically not independent. We also show that we could partition genetic variances more precisely when using relationship matrices derived from markers compared to using only pedigree information. In addition, phenotypic prediction accuracies were only slightly increased by including dominance effects for growth traits since estimates of non-additive variances yielded rather high standard errors. This novel result improves our current understanding of the architecture of quantitative traits and recommends accounting for dominance variance when developing genomic selection strategies in hybrid Eucalyptus.

genetics↗

bioRxiv2017

Vitamin and amino acid auxotrophy in anaerobic consortia operating under methanogenic condition

Syntrophy among Archaea and Bacteria facilitates the anaerobic degradation of organic compounds to CH4 and CO2. Particularly during aliphatic and aromatic hydrocarbon mineralization, as in crude oil reservoirs and petroleum-contaminated sediments, metabolic interactions between obligate mutualistic microbial partners are of central importance1. Using micro-manipulation combined with shotgun metagenomic approaches, we disentangled the genomes of complex consortia inside a short chain alkane-degrading cultures operating under methanogenic conditions. Metabolic reconstruction revealed that only a small fraction of genes in the metagenome-assembled genomes of this study, encode the capacity for fermentation of alkanes facilitated by energy conservation linked to H2 metabolism. Instead, inferred lifestyles based on scavenging anabolic products and intermediate fermentation products derived from detrital biomass was a common feature in the consortia. Additionally, inferred auxotrophy for vitamins and amino acids suggests that the hydrocarbon-degrading microbial assemblages are structured and maintained by multiple interactions beyond the canonical H2-producing and syntrophic alkane degrader-methanogen partnership2. Our study uncovers the complexity of interactomes within microbial consortia mediating hydrocarbon transformation under anaerobic conditions.

microbiology↗

bioRxiv2016

Evaluating the accuracy of genomic prediction of growth and wood traits in two Eucalyptus species and their F1 hybrids

BackgroundGenomic prediction is a genomics assisted breeding methodology that can increase genetic gains by accelerating the breeding cycle and potentially improving the accuracy of breeding values. In this study, we used 41,304 informative SNPs genotyped in a Eucalyptus breeding population involving 90 E.grandis and 78 E.urophylla parents and their 949 F1 hybrids to develop genomic prediction models for eight phenotypic traits - basic density and pulp yield, circumference at breast height and height and tree volume scored at age thee and six years. Based on different genomic prediction methods we assessed the impact of the composition and size of the training/validation sets and the number and genomic location of SNPs on the predictive ability (PA).\n\nResultsHeritabilities estimated using the realized genomic relationship matrix (GRM) were considerably higher than estimates based on the expected pedigree, mainly due to inconsistencies in the expected pedigree that were readily corrected by the GRM. Moreover, GRM more precisely capture Mendelian sampling among related individuals, such that the genetic covariance was based on the actual proportion of the genome shared between individuals. PA improved considerably when increasing the size of the training set and by enhancing relatedness to the validation set. Prediction models trained on pure species parents could not predict well in F1 hybrids, indicating that model training has to be carried out in hybrid populations if one is to predict in hybrid selection candidates. The different genomic prediction methods provided similar results for all traits, therefore GBLUP or rrBLUP represents better compromises between computational time and prediction efficiency. Only slight improvement was observed in PA when more than 5,000 SNPs were used for all traits. Using SNPs in intergenic regions provided slightly better PA than using SNPs sampled exclusively in genic regions.\n\nConclusionsEffects of training set size and composition and number of SNPs used are the most important factors for model prediction rather than prediction method and the genomic location of SNPs. Furthermore, training the prediction model on pure parental species provide limited ability to predict traits in interspecific hybrids. Our results provide additional promising perspectives for the implementation of genomic prediction in Eucalyptus breeding programs.

genetics↗