Rapid speciation with gene flow following the formation of Mount Etna
http://gbe.oxfordjournals.org/content/early/2013/08/23/gbe.evt127.full.pdf+html
Environmental or geological changes can create new niches which drive ecological species divergence without the immediate cessation of gene flow. However, few such cases have been characterised. On the recently formed volcano, Mt. Etna, Senecio aethnensis and S. chrysanthemifolius inhabit contrasting environments of high and low altitude respectively. They have very distinct phenotypes, despite hybridising promiscuously, and thus may represent an important example of ecological speciation ‘in action’, possibly as a response to the rapid geological changes which Mt. Etna has recently undergone. To elucidate the species' evolutionary history, and help establish the species as study system for speciation genomics, we sequenced the transcriptomes of the two Etnean species, and the outgroup, S. vernalis, using Illumina sequencing. Despite the species' substantial phenotypic divergence, synonymous divergence between the high- and low-altitude species was low (dS = 0.016 ± 0.017 [SD]). A comparison of species divergence models with and without gene flow provided unequivocal support in favor of the former and demonstrated a recent time of species divergence (153,080 ya ± 11,470[SE]) that coincides with the growth of Mount Etna to the altitudes which separate the species today. Analysis of dN/dSrevealed wide variation in selective constraint between genes, and evidence that highly expressed genes, more ‘multifunctional’ genes and those with more paralogues were under elevated purifying selection. Taken together, these results are consistent with a model of ecological speciation, potentially as a response to the emergence of a new, high altitude niche as the volcano grew.
2013年8月23日星期五
2013年8月18日星期日
Alternative forms for genomic clines
http://onlinelibrary.wiley.com/doi/10.1002/ece3.609/full
Understanding factors regulating hybrid fitness and gene exchange is a major research challenge for evolutionary biology. Genomic cline analysis has been used to evaluate alternative patterns of introgression, but only two models have been used widely and the approach has generally lacked a hypothesis testing framework for distinguishing effects of selection and drift. I propose two alternative cline models, implement multivariate outlier detection to identify markers associated with hybrid fitness, and simulate hybrid zone dynamics to evaluate the signatures of different modes of selection. Analysis of simulated data shows that previous approaches are prone to false positives (multinomial regression) or relatively insensitive to outlier loci affected by selection (Barton's concordance). The new, theory-based logit-logistic cline model is generally best at detecting loci affecting hybrid fitness. Although some generalizations can be made about different modes of selection, there is no one-to-one correspondence between pattern and process. These new methods will enhance our ability to extract important information about the genetics of reproductive isolation and hybrid fitness. However, much remains to be done to relate statistical patterns to particular evolutionary processes. The methods described here are implemented in a freely available package “HIest” for the R statistical software (CRAN; http://cran.r-project.org/).
Understanding factors regulating hybrid fitness and gene exchange is a major research challenge for evolutionary biology. Genomic cline analysis has been used to evaluate alternative patterns of introgression, but only two models have been used widely and the approach has generally lacked a hypothesis testing framework for distinguishing effects of selection and drift. I propose two alternative cline models, implement multivariate outlier detection to identify markers associated with hybrid fitness, and simulate hybrid zone dynamics to evaluate the signatures of different modes of selection. Analysis of simulated data shows that previous approaches are prone to false positives (multinomial regression) or relatively insensitive to outlier loci affected by selection (Barton's concordance). The new, theory-based logit-logistic cline model is generally best at detecting loci affecting hybrid fitness. Although some generalizations can be made about different modes of selection, there is no one-to-one correspondence between pattern and process. These new methods will enhance our ability to extract important information about the genetics of reproductive isolation and hybrid fitness. However, much remains to be done to relate statistical patterns to particular evolutionary processes. The methods described here are implemented in a freely available package “HIest” for the R statistical software (CRAN; http://cran.r-project.org/).
2013年8月12日星期一
hybrid zone
hybrid zones allow us:
(1) to quantify the genetic differences responsible for speciation,
(2) to measure the diffusion of genes between diverging taxa,
(3) to understand the spread of alternative adaptations.
(1) to quantify the genetic differences responsible for speciation,
(2) to measure the diffusion of genes between diverging taxa,
(3) to understand the spread of alternative adaptations.
The genomic impacts of drift and selection for hybrid performance
1. http://arxiv.org/abs/1307.7313
Modern maize breeding relies upon selection in inbreeding populations to improve the performance of cross-population hybrids. The United States Department of Agriculture - Agricultural Research Service reciprocal recurrent selection experiment between the Iowa Stiff Stalk Synthetic (BSSS) and the Iowa Corn Borer Synthetic No. 1 (BSCB1) populations represents one of the longest standing models of selection for hybrid performance. To investigate the genomic impact of this selection program, we used the Illumina MaizeSNP50 high-density SNP array to determine genotypes of progenitor lines and over 600 individuals across multiple cycles of selection. Consistent with previous research (Messmer et al., 1991; Labate et al., 1997; Hagdorn et al., 2003; Hinze et al., 2005), we found that genetic diversity within each population steadily decreases, with a corresponding increase in population structure. High marker density also enabled the first view of haplotype ancestry, fixation and recombination within this historic maize experiment. Extensive regions of haplotype fixation within each population are visible in the pericentromeric regions, where large blocks trace back to single founder inbreds. Simulation attributes most of the observed reduction in genetic diversity to genetic drift. Signatures of selection were difficult to observe in the background of this strong genetic drift, but heterozygosity in each population has fallen more than expected. Regions of haplotype fixation represent the most likely targets of selection, but as observed in other germplasm selected for hybrid performance (Feng et al., 2006), there is no overlap between the most likely targets of selection in the two populations. We discuss how this pattern is likely to occur during selection for hybrid performance, and how it poses challenges for dissecting the impacts of modern breeding and selection on the maize genome.
How Increasing CO2 and Temperatures Affect Plant Development
1. http://www.sciencedaily.com/releases/2013/07/130731225931.htm
2. http://www.nature.com/ncomms/2013/130731/ncomms3145/full/ncomms3145.html
Elevated levels of CO2 and temperature can both affect plant growth and development, but the signalling pathways regulating these processes are still obscure. MicroRNAs function to silence gene expression, and environmental stresses can alter their expressions. Here we identify, using the small RNA-sequencing method, microRNAs that change significantly in expression by either doubling the atmospheric CO2 concentration or by increasing temperature 3–6 °C. Notably, nearly all CO2-influenced microRNAs are affected inversely by elevated temperature. Using the RNA-sequencing method, we determine strongly correlated expression changes between miR156/157 and miR172, and their target transcription factors under elevated CO2 concentration. Similar correlations are also found for microRNAs acting in auxin-signalling, stress responses and potential cell wall carbohydrate synthesis. Our results demonstrate that both CO2 and temperature alter microRNA expression to affect Arabidopsis growth and development, and miR156/157- and miR172-regulated transcriptional network might underlie the onset of early flowering induced by increasing CO2.
2. http://www.nature.com/ncomms/2013/130731/ncomms3145/full/ncomms3145.html
Elevated levels of CO2 and temperature can both affect plant growth and development, but the signalling pathways regulating these processes are still obscure. MicroRNAs function to silence gene expression, and environmental stresses can alter their expressions. Here we identify, using the small RNA-sequencing method, microRNAs that change significantly in expression by either doubling the atmospheric CO2 concentration or by increasing temperature 3–6 °C. Notably, nearly all CO2-influenced microRNAs are affected inversely by elevated temperature. Using the RNA-sequencing method, we determine strongly correlated expression changes between miR156/157 and miR172, and their target transcription factors under elevated CO2 concentration. Similar correlations are also found for microRNAs acting in auxin-signalling, stress responses and potential cell wall carbohydrate synthesis. Our results demonstrate that both CO2 and temperature alter microRNA expression to affect Arabidopsis growth and development, and miR156/157- and miR172-regulated transcriptional network might underlie the onset of early flowering induced by increasing CO2.
2013年8月11日星期日
Workflow of gene family evolution study
Workflow of gene family evolution study:
1. Analysis Method
Sequence Collection
PlantTribe, PlantGDB, GenBank, Conifer DBMagic assemblies
25 taxa comprising of 71 sequences
2. Phylogenetic analysis
Maximum Likelihood: RAxML (Stamatakis et. al)
Bayesian Method: MrBayes (Huelsenbeck, et al.)
Tree reconciliation: NOTUNG 2.6 (Chen et al.)
3. A case study
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3394424/
1. Analysis Method
Sequence Collection
PlantTribe, PlantGDB, GenBank, Conifer DBMagic assemblies
25 taxa comprising of 71 sequences
2. Phylogenetic analysis
Maximum Likelihood: RAxML (Stamatakis et. al)
Bayesian Method: MrBayes (Huelsenbeck, et al.)
Tree reconciliation: NOTUNG 2.6 (Chen et al.)
3. A case study
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3394424/
What use is a reference genome sequence . . . in applied tree breeding
• As a reference for re-sequencing elite individuals to identify
functional alleles or haplotypes, and consequently, to provide
superior estimates of kinship.
• As a physical map of marker locations, to guide imputation of
missing genotype data
• Essential for matrix-based methods of analysis
• Allows accurate imputation of progeny from structured
mating design based on known parental haplotypes
• As the fundamental framework for knowledge of conifer
genes and regulatory elements, to enable future advances in
MAS strategies as technology develops.
http://pinegenome.org/pinerefseq/files/Westerngulf_2013_Wheeler_Whetten.pdf
functional alleles or haplotypes, and consequently, to provide
superior estimates of kinship.
• As a physical map of marker locations, to guide imputation of
missing genotype data
• Essential for matrix-based methods of analysis
• Allows accurate imputation of progeny from structured
mating design based on known parental haplotypes
• As the fundamental framework for knowledge of conifer
genes and regulatory elements, to enable future advances in
MAS strategies as technology develops.
http://pinegenome.org/pinerefseq/files/Westerngulf_2013_Wheeler_Whetten.pdf
2013年8月10日星期六
What use is a reference genome sequence to applied tree breeding
http://pinegenome.org/pinerefseq/files/Westerngulf_2013_Wheeler_Whetten.pdf
Primary goal: Produce improved genetic material for
deployment as planting stock, while maintaining sufficient
genetic diversity to manage risk.
Understanding biological mechanisms is not a goal, but it can
be a tool.
• Primary tool: Modeling the genetic basis of phenotypic variation
in breeding populations.
Phenotypes measured in field tests of progeny from
structured mating designs.
Genetic information primarily based on pedigree records
BLUP (best linear unbiased predictor) relies heavily on kinship
information!
Primary goal: Produce improved genetic material for
deployment as planting stock, while maintaining sufficient
genetic diversity to manage risk.
Understanding biological mechanisms is not a goal, but it can
be a tool.
• Primary tool: Modeling the genetic basis of phenotypic variation
in breeding populations.
Phenotypes measured in field tests of progeny from
structured mating designs.
Genetic information primarily based on pedigree records
BLUP (best linear unbiased predictor) relies heavily on kinship
information!
2013年8月5日星期一
Cronn Lab:Protocols
http://openwetware.org/wiki/Random_Lab_Methods
Illumina GA Data Management
Short read toolbox. Many of our projects use short-read data from Illumina Genome Analyzer and HiSeq. Brian Knaus from our lab developed a number of scripts for managing and analyzing short-read files and data for the GA1 and GA2 platforms.
Illumina GA DNA-Seq
DNA_Seq Prep. Our research group has developed several methods for sequencing small genomes (mitochondria, chloroplasts, BACS) in multiplex using Illumina GA2. This page provides details on DNA-Seq library construction.
Illumina GA RNA-Seq
RNA_Seq Prep. We do mRNA-sequencing using methods developed by Todd Mockler's group at Oregon State University. This page provides details on RNA-Seq library construction.
Illumina GA Hyb-Seq
Hyb_Seq Prep. Like many groups, we've developed customized approaches to enrich rare genomic targets for high-throughput sequencing. Our method for isolating chloroplast genomes by Hyb-Seq is detailed here.
Whole Genome Amplification
WGA Prep. We use phi29-based whole-genome amplification in a variety of different applications. Our standard phi29 WGA method is detailed here.
Purifying DNA with Agilent AMPure Beads
AMPure_Mods. By altering the ratio of DNA:AMPure beads, it's possible to alter the size of the retained bands. We use AMPure beads to clean DNA bands, as well as reduce or eliminate the abundance of small DNAs (oligos, double-stranded adapters, primer dimers).
Random Lab Methods
Random Lab Methods. RNA extraction, DNA extraction, gels, short cuts... find it here
Rapid Isolation of RNA from Conifer Needles
Conifer_RNA_prep. Conifers join a long list of 'recalcitrant' plants that are difficult for RNA extraction, and fail using "traditional" RNA extraction kits. We use a modification of the method by Tai et al, 2004.
Isolation of poly(A) mRNA with Sera-Mag Oligo(dT) beads
mRNA_Prep. There are many methods for isolating mRNA from total RNA. We have had excellent results with Sera-Mag Oligo(dT) beads. We use this approach for constructing Illumina mRNA-Seq libraries, but it should be useful for any application that demands rRNA-depleted mRNA.
Preparation of strand-specific mRNA-Seq libraries with the Illumina TruSeq RNA Sample kit
directional-RNAseq_Prep. There are many methods available for making strand-specific mRNA libraries. We chose to adapt one of the most reliable methods identified by Levin et al. (2010) - dUTP labelling followed by dUTP degredation - for use in the Illumina TruSeq mRNA kit. This method produces mRNA-Seq libraries that are highly enriched for the complementary sequence of the native mRNA.
Rapid Isolation of DNA from Conifer Needles
DNA_Seq Prep. Conifers join a long list of 'recalcitrant' plants that are difficult for DNA extraction. We use a modification of the Fast-Prep method.
2013年3月25日星期一
2013年3月15日星期五
contact zone and population structure
http://mbe.oxfordjournals.org/content/26/9/1963.full
Genetic admixture of distinct gene pools is the consequence of complex spatiotemporal processes that could have involved massive migration and local mating during the history of a species. However, current methods for estimating individual admixture proportions lack the incorporation of such a piece of information. Here, we extend Bayesian clustering algorithms by including global trend surfaces and spatial autocorrelation in the prior distribution on individual admixture coefficients. We test our algorithm by using spatially explicit and realistic coalescent simulations of colonization followed by secondary contact. By coupling our multiscale spatial analyses with a Bayesian evaluation of model complexity and fit, we show that the algorithm provides a correct description of smooth clinal variation, while still detecting zones of sharp variation when they are present in the data. We also apply our approach to understand the population structure of the killifish, Fundulus heteroclitus, for which the algorithm uncovers a presumed contact zone in the Atlantic coast of North America.
Genetic admixture of distinct gene pools is the consequence of complex spatiotemporal processes that could have involved massive migration and local mating during the history of a species. However, current methods for estimating individual admixture proportions lack the incorporation of such a piece of information. Here, we extend Bayesian clustering algorithms by including global trend surfaces and spatial autocorrelation in the prior distribution on individual admixture coefficients. We test our algorithm by using spatially explicit and realistic coalescent simulations of colonization followed by secondary contact. By coupling our multiscale spatial analyses with a Bayesian evaluation of model complexity and fit, we show that the algorithm provides a correct description of smooth clinal variation, while still detecting zones of sharp variation when they are present in the data. We also apply our approach to understand the population structure of the killifish, Fundulus heteroclitus, for which the algorithm uncovers a presumed contact zone in the Atlantic coast of North America.
2013年2月24日星期日
test for local adaptation and to analyze the performance of hybrids relative to native parental plants
tool and a reference on transplantation data analysis.
1. Geyer, C. J., S. Wagenius, and R. G. Shaw. 2007. Aster models for life history analysis. Biometrika 94:415–42
2.
http://onlinelibrary.wiley.genomics of ecological speciation - some cases
1. http://onlinelibrary.wiley.com/doi/10.1111/j.1461-0248.2010.01546.x/full
A guide to the genomics of ecological speciation in natural animal populations
Interest in ecological speciation is growing, as evidence accumulates showing that natural selection can lead to rapid divergence between subpopulations. However, whether and how ecological divergence can lead to the buildup of reproductive isolation remains under debate. What is the relative importance of natural selection vs. neutral processes? How does adaptation generate reproductive isolation? Can ecological speciation occur despite homogenizing gene flow? These questions can be addressed using genomic approaches, and with the rapid development of genomic technology, will become more answerable in studies of wild populations than ever before. In this article, we identify open questions in ecological speciation theory and suggest useful genomic methods for addressing these questions in natural animal populations. We aim to provide a practical guide for ecologists interested in incorporating genomic methods into their research programs. An increased integration between ecological research and genomics has the potential to shed novel light on the origin of species.
2. http://www.sciencedirect.com/science/article/pii/S0169534712001863
A guide to the genomics of ecological speciation in natural animal populations
Interest in ecological speciation is growing, as evidence accumulates showing that natural selection can lead to rapid divergence between subpopulations. However, whether and how ecological divergence can lead to the buildup of reproductive isolation remains under debate. What is the relative importance of natural selection vs. neutral processes? How does adaptation generate reproductive isolation? Can ecological speciation occur despite homogenizing gene flow? These questions can be addressed using genomic approaches, and with the rapid development of genomic technology, will become more answerable in studies of wild populations than ever before. In this article, we identify open questions in ecological speciation theory and suggest useful genomic methods for addressing these questions in natural animal populations. We aim to provide a practical guide for ecologists interested in incorporating genomic methods into their research programs. An increased integration between ecological research and genomics has the potential to shed novel light on the origin of species.
2. http://www.sciencedirect.com/science/article/pii/S0169534712001863
What is needed for next-generation ecological and evolutionary genomics?
Ecological and evolutionary genomics (EEG) aims to link gene functions and genomic features to phenotypes and ecological factors. Although the rapid development of technologies allows central questions to be addressed at an unprecedented level of molecular detail, they do not alleviate one of the major challenges of EEG, which is that a large fraction of genes remains without any annotation. Here, we propose two solutions to this challenge. The first solution is in the form of a database that regroups associations between genes, organismal attributes and abiotic and biotic conditions. This database would result in an ecological annotation of genes by allowing cross-referencing across studies and taxa. Our second solution is to use new functional techniques to characterize genes implicated in the response to ecological challenges.
Divergent selection and heterogeneous genomic divergence
Levels of genetic differentiation between populations can be highly variable across the genome, with divergent selection contributing to such heterogeneous genomic divergence. For example, loci under divergent selection and those tightly physically linked to them may exhibit stronger differentiation than neutral regions with weak or no linkage to such loci. Divergent selection can also increase genome-wide neutral differentiation by reducing gene flow (e.g. by causing ecological speciation), thus promoting divergence via the stochastic effects of genetic drift. These consequences of divergent selection are being reported in recently accumulating studies that identify: (i) ‘outlier loci’ with higher levels of divergence than expected under neutrality, and (ii) a positive association between the degree of adaptive phenotypic divergence and levels of molecular genetic differentiation across population pairs [‘isolation by adaptation’ (IBA)]. The latter pattern arises because as adaptive divergence increases, gene flow is reduced (thereby promoting drift) and genetic hitchhiking increased. Here, we review and integrate these previously disconnected concepts and literatures. We find that studies generally report 5–10% of loci to be outliers. These selected regions were often dispersed across the genome, commonly exhibited replicated divergence across different population pairs, and could sometimes be associated with specific ecological variables. IBA was not infrequently observed, even at neutral loci putatively unlinked to those under divergent selection. Overall, we conclude that divergent selection makes diverse contributions to heterogeneous genomic divergence. Nonetheless, the number, size, and distribution of genomic regions affected by selection varied substantially among studies, leading us to discuss the potential role of divergent selection in the growth of regions of differentiation (i.e. genomic islands of divergence), a topic in need of future investigation.
2012年7月22日星期日
2012年6月15日星期五
2012年6月14日星期四
Homoploid hybrid expectations
What is your expectation for a homoploid hybrid species?
1.Genetic and phenotypic divergence of homoploid hybrid species from parental species
http://www.nature.com/hdy/journal/v108/n3/full/hdy201180a.html
2.Molecular genetic and quantitative trait divergence associated with recent homoploid hybrid speciation : a study of (Asteraceae)
http://www.nature.com/hdy/journal/v108/n2/full/hdy201146a.html
1.
http://www.nature.com/hdy/journal/v108/n3/full/hdy201180a.html
2.
http://www.nature.com/hdy/journal/v108/n2/full/hdy201146a.html
2012年6月5日星期二
ASReml-R cookbook
http://apiolaza.net/asreml-r/
Recipes
Recipes
- Very basic usage.
- Specifying model equations.
- Univariate analysis
, including basic equivalent models, diallels, clonal trials and multiple-site as single trait. - Extracting results
like variance components, fixed and random effects, etc, from the fitted model. - Covariance structures.
- Multiple environments.
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