Tomato (Solanum lycopersicum) is a major crop plant and a model system for fruit development. Solanum is one of the largest angiosperm genera(1) and includes annual and perennial plants from diverse habitats. Here we present a high-quality genome sequence of domesticated tomato, a draft sequence of its closest wild relative, Solanum pimpinellifolium(2), and compare them to each other and to the potato genome (Solanum tuberosum). The two tomato genomes show only 0.6% nucleotide divergence and signs of recent admixture, but show more than 8% divergence from potato, with nine large and several smaller inversions. In contrast to Arabidopsis, but similar to soybean, tomato and potato small RNAs map predominantly to gene-rich chromosomal regions, including gene promoters. The Solanum lineage has experienced two consecutive genome triplications: one that is ancient and shared with rosids, and a more recent one. These triplications set the stage for the neofunctionalization of genes controlling fruit characteristics, such as colour and fleshiness
The Sol Genomics Network (SGN, http://solgenomics.net) is a web portal with genomic and phenotypic data, and analysis tools for the Solanaceae family and close relatives. SGN hosts whole genome data for an increasing number of Solanaceae family members including tomato, potato, pepper, eggplant, tobacco and Nicotiana benthamiana. The database also stores loci and phenotype data, which researchers can upload and edit with user-friendly web interfaces. Tools such as BLAST, GBrowse and JBrowse for browsing genomes, expression and map data viewers, a locus community annotation system and a QTL analysis tools are available. A new tool was recently implemented to improve Virus-Induced Gene Silencing (VIGS) constructs called the SGN VIGS tool. With the growing genomic and phenotypic data in the database, SGN is now advancing to develop new web-based breeding tools and implement the code and database structure for other species or clade-specific databases.
We develop a new method for estimating effective population sizes, N e , and selection coefficients, s, from time-series data of allele frequencies sampled from a single diallelic locus. The method is based on calculating transition probabilities, using a numerical solution of the diffusion process, and assuming independent binomial sampling from this diffusion process at each time point. We apply the method in two example applications. First, we estimate selection coefficients acting on the CCR5-D32 mutation on the basis of published samples of contemporary and ancient human DNA. We show that the data are compatible with the assumption of s ¼ 0, although moderate amounts of selection acting on this mutation cannot be excluded. In our second example, we estimate the selection coefficient acting on a mutation segregating in an experimental phage population. We show that the selection coefficient acting on this mutation is $0.43.
R-band intensity measurements along the light curve of Type Ia supernovae discovered by the Supernova Cosmology Project (SCP) are fitted in brightness to templates allowing a free parameter the time-axis width factor w ≡ s × (1 + 2 z). The data points are then individually aligned in the time-axis, normalized and K-corrected back to the rest frame, after which the nearly 1300 normalized intensity measurements are found to lie on a well-determined common rest-frame B-band curve which we call the "composite curve". The same procedure is applied to 18 low-redshift Calán/Tololo SNe with z < 0.11; these nearly 300 B-band photometry points are found to lie on the composite curve equally well. The SCP search technique produces several measurements before maximum light for each supernova. We demonstrate that the linear stretch factor, s, which parameterizes the light-curve timescale appears independent of z, and applies equally well to the declining and rising parts of the light curve. In fact, the B band template that best fits this composite curve fits the individual supernova photometry data when stretched by a factor s with χ 2 /DoF ≈ 1, thus as well as any parameterization can, given the current data sets. The measurement of the date of explosion, however, is model dependent and not tightly constrained by the current data. We also demonstrate the 1 + z light-curve time-axis broadening expected from cosmological expansion. This argues strongly against alternative explanations, such as tired light, for the redshift of distant objects.
Arbuscular mycorrhizal symbiosis (AMS), a widespread mutualistic association of land plants and fungi(1), is predicted to have arisen once, early in the evolution of land plants(2-4). Consistent with this notion, several genes required for AMS have been conserved throughout evolution(5) and their symbiotic functions preserved, at least between monocot and dicot plants(6,7). Despite its significance, knowledge of the plants' genetic programme for AMS is limited. To date, most genes required for AMS have been found through commonalities with the evolutionarily younger nitrogen-fixing Rhizobium legume symbiosis (RLS)(8) or by reverse genetic analyses of differentially expressed candidate genes(9). Large sequence-indexed insertion mutant collections and recent genome editing technologies have vastly increased the power of reverse genetics but selection of candidate genes, from the thousands of genes that change expression during AMS, remains an arbitrary process. Here, we describe a phylogenomics approach to identify genes whose evolutionary history predicts conservation for AMS and we demonstrate the accuracy of the predictions through reverse genetics analysis. Phylogenomics analysis of 50 plant genomes resulted in 138 genes from Medicago truncatula predicted to function in AMS. This includes 15 genes with known roles in AMS. Additionally, we demonstrate that mutants in six previously uncharacterized AMS-conserved genes are all impaired in AMS. Our results demonstrate that phylogenomics is an effective strategy to identify a set of evolutionarily conserved genes required for AMS.
Domesticated Asian rice (Oryza sativa) is one of the oldest domesticated crop species in the world, having fed more people than any other plant in human history. We report the patterns of DNA sequence variation in rice and its wild ancestor, O. rufipogon, across 111 randomly chosen gene fragments, and use these to infer the evolutionary dynamics that led to the origins of rice. There is a genome-wide excess of high-frequency derived single nucleotide polymorphisms (SNPs) in O. sativa varieties, a pattern that has not been reported for other crop species. We developed several alternative models to explain contemporary patterns of polymorphisms in rice, including a (i) selectively neutral population bottleneck model, (ii) bottleneck plus migration model, (iii) multiple selective sweeps model, and (iv) bottleneck plus selective sweeps model. We find that a simple bottleneck model, which has been the dominant demographic model for domesticated species, cannot explain the derived nucleotide polymorphism site frequency spectrum in rice. Instead, a bottleneck model that incorporates selective sweeps, or a more complex demographic model that includes subdivision and gene flow, are more plausible explanations for patterns of variation in domesticated rice varieties. If selective sweeps are indeed the explanation for the observed nucleotide data of domesticated rice, it suggests that strong selection can leave its imprint on genome-wide polymorphism patterns, contrary to expectations that selection results only in a local signature of variation.
The Sol Genomics Network (SGN; http://solgenomics.net/) is a clade-oriented database (COD) containing biological data for species in the Solanaceae and their close relatives, with data types ranging from chromosomes and genes to phenotypes and accessions. SGN hosts several genome maps and sequences, including a pre-release of the tomato (Solanum lycopersicum cv Heinz 1706) reference genome. A new transcriptome component has been added to store RNA-seq and microarray data. SGN is also an open source software project, continuously developing and improving a complex system for storing, integrating and analyzing data. All code and development work is publicly visible on GitHub (http://github.com). The database architecture combines SGN-specific schemas and the community-developed Chado schema (http://gmod.org/wiki/Chado) for compatibility with other genome databases. The SGN curation model is community-driven, allowing researchers to add and edit information using simple web tools. Currently, over a hundred community annotators help curate the database. SGN can be accessed at http://solgenomics.net/.
Comparative genome analysis is a powerful tool that can facilitate the reconstruction of the evolutionary history of the genomes of modern-day species. The model plant Arabidopsis thaliana with its n = 5 genome is thought to be derived from an ancestral n = 8 genome. Pairwise comparative genome analyses of A. thaliana with polyploid and diploid Brassicaceae species have suggested that rapid genome evolution, manifested by chromosomal rearrangements and duplications, characterizes the polyploid, but not the diploid, lineages of this family. In this study, we constructed a low-density genetic linkage map of Arabidopsis lyrata ssp. lyrata (A. l. lyrata; n = 8, diploid), the closest known relative of A. thaliana (MRCA ∼5 Mya), using A. thaliana-specific markers that resolve into the expected eight linkage groups. We then performed comparative Bayesian analyses using raw mapping data from this study and from a Capsella study to infer the number and nature of rearrangements that distinguish the n = 8 genomes of A. l. lyrata and Capsella from the n = 5 genome of A. thaliana. We conclude that there is strong statistical support in favor of the parsimony scenarios of 10 major chromosomal rearrangements separating these n = 8 genomes from A. thaliana. These chromosomal rearrangement events contribute to a rate of chromosomal evolution higher than previously reported in this lineage. We infer that at least seven of these events, common to both sets of data, are responsible for the change in karyotype and underlie genome reduction in A. thaliana.[Supplemental material is available online at www.genome.org. The following individuals kindly provided reagents, samples, or unpublished information as indicated in the paper: C. Langley.]Comparative genome analysis can be a powerful tool to address questions pertaining to the evolution of the structure of genomes (Paterson and Bennetzen 2001). In plant families that include model taxa, such as the Brassicaceae, the Solanaceae, and the Poaceae, comparative mapping studies allow evolutionary inferences related to the nature and number of rearrangements that distinguish the genomes of the model species from those of their less well-studied relatives (Bonierbale et al. 1988;Ahn and Tanksley 1993;Prince et al. 1993;Chittendan et al. 1994;Kurata et al. 1994;Periera et al. 1994;Lagercrantz and Lydiate 1996;Gale and Devos 1998;Lagercrantz 1998;Doganlar et al. 2002). Not only do such inferences facilitate the transfer of knowledge from model taxa to their relatives, but they also provide insight into the process of genome restructuring that can lead to reproductive isolation and ultimately speciation (Rieseberg 2001;Hall et al. 2002). The larger the number of taxa analyzed within a family, the more comprehensive the information is for inferring the nature of ancestral genomes and the evolutionary history that led to the speciation of the members of that family.The Brassicaceae (or Cruciferae) is a dicot family divided into 13 tribes with a total of 360 genera (Al-Shehbaz 1973) including th...
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.