Estimating Transcriptome Diversity and Specialization in Capsicum annuum L.

Chili pepper fruits of the genus Capsicum represent excellent experimental models to study the growth, development, and ripening processes in a non-climacteric species at the physiological, biochemical, and molecular levels. Fruit growth, development, and ripening involve a complex, harmonious, and finely controlled regulation of gene expression. The purpose of this study was to estimate the changes in transcriptome diversity and specialization, as well as gene specificities during fruit development in this crop, and to illustrate the advantages of estimating these parameters. To achieve these aims, we programmed and made publicly available an R package. In this study, we applied these methods to a set of 179 RNA-Seq libraries from a factorial experiment that includes 12 different genotypes at various stages of fruit development. We found that the diversity of the transcriptome decreases linearly from the flower to the mature fruit, while its specialization follows a complex and non-linear behavior during this process. Additionally, by defining sets of genes with different degrees of specialization and applying Gene Ontology enrichment analysis, we identified processes, functions, and components that play a central role in particular fruit development stages. In conclusion, the estimation of diversity, specialization, and specificity summarizes the global properties of the transcriptomes, providing insights that are difficult to achieve by other means.

Large scale sampling of Mexican maize landraces for the presence of transgenes.

The presence and levels of transgenic maize in Mexico and the effect this could have on local landraces or closely related species such as teosinte has been the subject of several previous reports, some showing contrasting results. Cultural, social and political factors all affect maize cultivation in Mexico and although since 1998 there has been a moratorium on the commercial cultivation of transgenic maize, Mexico imports maize, mainly from the USA where transgenic cultivars are widely grown. Additionally extensive migration between rural areas in Mexico and the USA and customs of seed exchange between farmers may also play an unintentional role in the establishment of transgenic seed. A comprehensive study of all Mexican maize landraces throughout the country is not feasible, however this report presents data based on analysis of 3204 maize accessions obtained from the central region of Mexico (where permits have never been authorized for cultivation of transgenic maize) and the northern region (where for a short period authorization for experimental plots was granted). The results of the study confirm that transgenes are present in all the geographical areas sampled and were more common in germplasm obtained in the northern region. However, there was no evidence that regions where field trials had been authorized showed higher levels of transgene presence or that the morphology of seed lots harboring transgenic material was significantly modified in favor of expected transgenic phenotypes.

Worldwide Selection Footprints for Drought and Heat in Bread Wheat (Triticum aestivum L.).

Genome-environment Associations (GEA) or Environmental Genome-Wide Association scans (EnvGWAS) have been poorly applied for studying the genomics of adaptive traits in bread wheat landraces (Triticum aestivum L.). We analyzed 990 landraces and seven climatic variables (mean temperature, maximum temperature, precipitation, precipitation seasonality, heat index of mean temperature, heat index of maximum temperature, and drought index) in GEA using the FarmCPU approach with GAPIT. Historical temperature and precipitation values were obtained as monthly averages from 1970 to 2000. Based on 26,064 high-quality SNP loci, landraces were classified into ten subpopulations exhibiting high genetic differentiation. The GEA identified 59 SNPs and nearly 89 protein-encoding genes involved in the response processes to abiotic stress. Genes related to biosynthesis and signaling are mainly mediated by auxins, abscisic acid (ABA), ethylene (ET), salicylic acid (SA), and jasmonates (JA), which are known to operate together in modulation responses to heat stress and drought in plants. In addition, we identified some proteins associated with the response and tolerance to stress by high temperatures, water deficit, and cell wall functions. The results provide candidate regions for selection aimed to improve drought and heat tolerance in bread wheat and provide insights into the genetic mechanisms involved in adaptation to extreme environments.

Phenolic Composition and Biological Properties of Rhus microphylla and Myrtillocactus geometrizans Fruit Extracts.

Plants from arid zones of Mexico are an interesting source of phytochemicals that exhibit a large number of biological properties. In this context, Rhus microphylla (Rm) and Myrtillocactus geometrizans (Mg) fruits have been used as folk remedies and to make traditional foods, respectively; however, studies on their composition and bioactivity are limited. Thus, the objective of this work was to evaluate the yields, phenolic composition, and bioactive properties (scavenging and reducing capacities, antiproliferative, and antifungal) of aqueous and hydroalcohol extracts of Rm and Mg fruits obtained by conventional agitation and ohmic heating (OH). The results showed that the Rm fruit extracts had the highest total phenolic content (TPC) values and the strongest scavenging and reducing capacities compared to those of Mg fruits, being characterized by the presence of gallic acid, while the composition of the Mg extracts varied with respect to the extraction conditions used. Regarding antifungal activity in vitro against two phytopathogenic fungi, Rhizopus stolonifer and Fusarium oxysporum, the hydroalcohol extracts obtained by conventional agitation of both plants (RmH-C and MgH-C) showed the best inhibitory effect, respectively. Interestingly, none of the extracts under study presented cytotoxicity against the noncancerous ARPE-19 cell line, while three extracts of Rm fruit exhibited a moderate antiproliferative activity against HeLa (cancerous) cell line. These findings reveal for the first time the potential of Rm and Mg fruits as a new source of bioactive compounds for future industrial applications.

A method to analyze time expression profiles demonstrated in a database of chili pepper fruit development.

RNA-Seq experiments allow genome-wide estimation of relative gene expression. Estimation of gene expression at different time points generates time expression profiles of phenomena of interest, as for example fruit development. However, such profiles can be complex to analyze and interpret. We developed a methodology that transforms original RNA-Seq data from time course experiments into standardized expression profiles, which can be easily interpreted and analyzed. To exemplify this methodology we used RNA-Seq data obtained from 12 accessions of chili pepper (Capsicum annuum L.) during fruit development. All relevant data, as well as functions to perform analyses and interpretations from this experiment, were gathered into a publicly available R package: "Salsa". Here we explain the rational of the methodology and exemplify the use of the package to obtain valuable insights into the multidimensional time expression changes that occur during chili pepper fruit development. We hope that this tool will be of interest for researchers studying fruit development in chili pepper as well as in other angiosperms.

Transcriptome Analyses Throughout Chili Pepper Fruit Development Reveal Novel Insights into the Domestication Process.

Chili pepper (Capsicum spp.) is an important crop, as well as a model for fruit development studies and domestication. Here, we performed a time-course experiment to estimate standardized gene expression profiles with respect to fruit development for six domesticated and four wild chili pepper ancestors. We sampled the transcriptomes every 10 days from flowering to fruit maturity, and found that the mean standardized expression profiles for domesticated and wild accessions significantly differed. The mean standardized expression was higher and peaked earlier for domesticated vs. wild genotypes, particularly for genes involved in the cell cycle that ultimately control fruit size. We postulate that these gene expression changes are driven by selection pressures during domestication and show a robust network of cell cycle genes with a time shift in expression, which explains some of the differences between domesticated and wild phenotypes.

An information theory approach to biocultural complexity.

The study of biocultural diversity requires the use of appropriate concepts and analytical tools. Particularly, there is a need of indices capable to show the degree of stratification in the set of interactions among cultures and groups of plants and animals in a given region. Here, we present a mathematical approach based on the mutual Shannon information theory to study the relationships among cultural and biological groups. Biocultural complexity was described in terms of effective biocultural units, a new concept defined in this work. From the mathematical formulation of biocultural complexity, formulas were derived to measure the specificity of biological groups and the specialization of cultures, based on the association of human societies with plant or animal groups. To exemplify the concepts and tools, two data sets were analyzed; 1) a set that included artificial data in order to demonstrate the use of the formulas and calculate the indices, and 2) a set that included published data on the use of 18 mushroom species by people in five villages of eastern India. Analysis of the first data set revealed a clear case of biocultural complexity, whereas that of the second set showed that the villages and the use of biological resources composed a single biocultural unit. Overall, hypothesis testing of the association among cultures and biological species was consistent with the information that was provided by the new indices.

GWAS to Identify Genetic Loci for Resistance to Yellow Rust in Wheat Pre-Breeding Lines Derived From Diverse Exotic Crosses.

Yellow rust (YR) or stripe rust, caused by Puccinia striformis f. sp tritici Eriks (Pst), is a major challenge to resistance breeding in wheat. A genome wide association study (GWAS) was performed using 22,415 single nucleotide polymorphism (SNP) markers and 591 haplotypes to identify genomic regions associated with resistance to YR in a subset panel of 419 pre-breeding lines (PBLs) developed at International Center for Maize and Wheat Improvement (CIMMYT). The 419 PBLs were derived from an initial set of 984 PBLs generated by a three-way crossing scheme (exotic/elite1//elite2) among 25 best elites and 244 exotics (synthetics, landraces) from CIMMYT's germplasm bank. For the study, 419 PBLs were characterized with 22,415 high-quality DArTseq-SNPs and phenotyped for severity of YR disease at five locations in Mexico. A population structure was evident in the panel with three distinct subpopulations, and a genome-wide linkage disequilibrium (LD) decay of 2.5 cM was obtained. Across all five locations, 14 SNPs and 7 haplotype blocks were significantly (P < 0.001) associated with the disease severity explaining 6.0 to 14.1% and 7.9 to 19.9% of variation, respectively. Based on average LD decay of 2.5 cM, identified 14 SNP-trait associations were delimited to seven quantitative trait loci in total. Seven SNPs were part of the two haplotype blocks on chromosome 2A identified in haplotypes-based GWAS. In silico analysis of the identified SNPs showed hits with interesting candidate genes, which are related to pathogenic process or known to regulate induction of genes related to pathogenesis such as those coding for glunolactone oxidase, quinate O-hydroxycinnamoyl transferase, or two-component histidine kinase. The two-component histidine kinase, for example, acts as a sensor in the perception of phytohormones ethylene and cytokinin. Ethylene plays a very important role in regulation of multiple metabolic processes of plants, including induction of defense mechanisms mediated by jasmonate. The SNPs linked to the promising genes identified in the study can be used for marker-assisted selection.

On an algorithmic definition for the components of the minimal cell.

Living cells are highly complex systems comprising a multitude of elements that are engaged in the many convoluted processes observed during the cell cycle. However, not all elements and processes are essential for cell survival and reproduction under steady-state environmental conditions. To distinguish between essential from expendable cell components and thus define the 'minimal cell' and the corresponding 'minimal genome', we postulate that the synthesis of all cell elements can be represented as a finite set of binary operators, and within this framework we show that cell elements that depend on their previous existence to be synthesized are those that are essential for cell survival. An algorithm to distinguish essential cell elements is presented and demonstrated within an interactome. Data and functions implementing the algorithm are given as supporting information. We expect that this algorithmic approach will lead to the determination of the complete interactome of the minimal cell, which could then be experimentally validated. The assumptions behind this hypothesis as well as its consequences for experimental and theoretical biology are discussed.

An informational view of accession rarity and allele specificity in germplasm banks for management and conservation.

Germplasm banks are growing in their importance, number of accessions and amount of characterization data, with a large emphasis on molecular genetic markers. In this work, we offer an integrated view of accessions and marker data in an information theory framework. The basis of this development is the mutual information between accessions and allele frequencies for molecular marker loci, which can be decomposed in allele specificities, as well as in rarity and divergence of accessions. In this way, formulas are provided to calculate the specificity of the different marker alleles with reference to their distribution across accessions, accession rarity, defined as the weighted average of the specificity of its alleles, and divergence, defined by the Kullback-Leibler formula. Albeit being different measures, it is demonstrated that average rarity and divergence are equal for any collection. These parameters can contribute to the knowledge of the structure of a germplasm collection and to make decisions about the preservation of rare variants. The concepts herein developed served as the basis for a strategy for core subset selection called HCore, implemented in a publicly available R script. As a proof of concept, the mathematical view and tools developed in this research were applied to a large collection of Mexican wheat accessions, widely characterized by SNP markers. The most specific alleles were found to be private of a single accession, and the distribution of this parameter had its highest frequencies at low levels of specificity. Accession rarity and divergence had largely symmetrical distributions, and had a positive, albeit non-strictly linear relationship. Comparison of the HCore approach for core subset selection, with three state-of-the-art methods, showed it to be superior for average divergence and rarity, mean genetic distance and diversity. The proposed approach can be used for knowledge extraction and decision making in germplasm collections of diploid, inbred or outbred species.

An SSR-based approach incorporating a novel algorithm for identification of rare maize genotypes facilitates criteria for landrace conservation in Mexico.

As maize was domesticated in Mexico around 9,000 years ago, local farmers have selected and maintained seed stocks with particular traits and adapted to local conditions. In the present day, many of these landraces are still cultivated; however, increased urbanization and migration from rural areas implies a risk that this invaluable maize germplasm may be lost. In order to implement an efficient mechanism of conservation in situ, the diversity of these landrace populations must be estimated. Development of a method to select the minimum number of samples that would include the maximum number of alleles and identify germplasm harboring rare combinations of particular alleles will also safeguard the efficient ex-situ conservation of this germplasm. To reach this goal, a strategy based on SSR analysis and a novel algorithm to define a minimum collection and rare genotypes using landrace populations from Puebla State, Mexico, was developed as a "proof of concept" for methodology that could be extended to all maize landrace populations in Mexico and eventually to other native crops. The SSR-based strategy using bulked DNA samples allows rapid processing of large numbers of samples and can be set up in most laboratories equipped for basic molecular biology. Therefore, continuous monitoring of landrace populations locally could easily be carried out. This methodology can now be applied to support incentives for small farmers for the in situ conservation of these traditional cultivars.

Long non-coding RNAs are major contributors to transcriptome changes in sunflower meiocytes with different recombination rates.

BACKGROUND: Meiosis is a form of specialized cell division that marks the transition from diploid meiocyte to haploid gamete, and provides an opportunity for genetic reassortment through recombination. Experimental data indicates that, relative to their wild ancestors, cultivated sunflower varieties show a higher recombination rate during meiosis. To better understand the molecular basis for this difference, we compared gene expression in male sunflower meiocytes in prophase I isolated from a domesticated line, a wild relative, and a F1 hybrid of the two. RESULTS: Of the genes that showed differential expression between the wild and domesticated genotypes, 63.62 % could not be identified as protein-coding genes, and of these genes, 70.98 % passed stringent filters to be classified as long non-coding RNAs (lncRNAs). Compared to the sunflower somatic transcriptome, meiocytes express a higher proportion of lncRNAs, and the majority of genes with exclusive expression in meiocytes were lncRNAs. Around 40 % of the lncRNAs showed sequence similarity with small RNAs (sRNA), while 1.53 % were predicted to be sunflower natural antisense transcripts (NATs), and 9.18 % contained transposable elements (TE). We identified 6895 lncRNAs that are exclusively expressed in meiocytes, these lncRNAs appear to have higher conservation, a greater degree of differential expression, a higher proportion of sRNA similarity, and higher TE content relative to lncRNAs that are also expressed in the somatic transcriptome. CONCLUSIONS: lncRNAs play important roles in plant meiosis and may participate in chromatin modification processes, although other regulatory functions cannot be excluded. lncRNAs could also be related to the different recombination rates seen for domesticated and wild sunflowers.

Analysis and optimization of bulk DNA sampling with binary scoring for germplasm characterization.

The strategy of bulk DNA sampling has been a valuable method for studying large numbers of individuals through genetic markers. The application of this strategy for discrimination among germplasm sources was analyzed through information theory, considering the case of polymorphic alleles scored binarily for their presence or absence in DNA pools. We defined the informativeness of a set of marker loci in bulks as the mutual information between genotype and population identity, composed by two terms: diversity and noise. The first term is the entropy of bulk genotypes, whereas the noise term is measured through the conditional entropy of bulk genotypes given germplasm sources. Thus, optimizing marker information implies increasing diversity and reducing noise. Simple formulas were devised to estimate marker information per allele from a set of estimated allele frequencies across populations. As an example, they allowed optimization of bulk size for SSR genotyping in maize, from allele frequencies estimated in a sample of 56 maize populations. It was found that a sample of 30 plants from a random mating population is adequate for maize germplasm SSR characterization. We analyzed the use of divided bulks to overcome the allele dilution problem in DNA pools, and concluded that samples of 30 plants divided into three bulks of 10 plants are efficient to characterize maize germplasm sources through SSR with a good control of the dilution problem. We estimated the informativeness of 30 SSR loci from the estimated allele frequencies in maize populations, and found a wide variation of marker informativeness, which positively correlated with the number of alleles per locus.

Informativeness of microsatellite markers.

Simple sequence repeats (SSR) are extensively used as genetic markers for studies of diversity, genetic mapping, and cultivar discrimination. The informativeness of a given SSR locus or a loci group depends on the number of alleles, their frequency distribution, as well as the kind of application. Here I describe several methods for calculating marker informativeness, all of them suitable for SSR polymorphisms, proposed by several authors and synthesized in an Information Theory framework. Additionally, free access software resources are described as well as their application through worked examples.

Cancer reduces transcriptome specialization.

A central goal of cancer biology is to understand how cells from this family of genetic diseases undergo specific morphological and physiological changes and regress to a de-regulated state of the cell cycle. The fact that tumors are unable to perform most of the specific functions of the original tissue led us to hypothesize that the degree of specialization of the transcriptome of cancerous tissues must be less than their normal counterparts. With the aid of information theory tools, we analyzed four datasets derived from transcriptomes of normal and tumor tissues to quantitatively test the hypothesis that cancer reduces transcriptome specialization. Here, we show that the transcriptional specialization of a tumor is significantly less than the corresponding normal tissue and comparable with the specialization of dedifferentiated embryonic stem cells. Furthermore, we demonstrate that the drop in specialization in cancerous tissues is largely due to a decrease in expression of genes that are highly specific to the normal organ. This approach gives us a better understanding of carcinogenesis and offers new tools for the identification of genes that are highly influential in cancer progression.

Defining diversity, specialization, and gene specificity in transcriptomes through information theory.

The transcriptome is a set of genes transcribed in a given tissue under specific conditions and can be characterized by a list of genes with their corresponding frequencies of transcription. Transcriptome changes can be measured by counting gene tags from mRNA libraries or by measuring light signals in DNA microarrays. In any case, it is difficult to completely comprehend the global changes that occur in the transcriptome, given that thousands of gene expression measurements are involved. We propose an approach to define and estimate the diversity and specialization of transcriptomes and gene specificity. We define transcriptome diversity as the Shannon entropy of its frequency distribution. Gene specificity is defined as the mutual information between the tissues and the corresponding transcript, allowing detection of either housekeeping or highly specific genes and clarifying the meaning of these concepts in the literature. Tissue specialization is measured by average gene specificity. We introduce the formulae using a simple example and show their application in two datasets of gene expression in human tissues. Visualization of the positions of transcriptomes in a system of diversity and specialization coordinates makes it possible to understand at a glance their interrelations, summarizing in a powerful way which transcriptomes are richer in diversity of expressed genes, or which are relatively more specialized. The framework presented enlightens the relation among transcriptomes, allowing a better understanding of their changes through the development of the organism or in response to environmental stimuli.

Validating a QTL region characterized by multiple haplotypes.

Validation of a quantitative trait locus (QTL) for outcrossing perennial plants is rarely reported due to complexity of plausible genetic models and reliance on field designs already available. Here, a particular marker-QTL haplotype exerted a large, positive effect on height for Pinus taeda and its origin could be traced to a founder, GP(3), in a three-generation QTL pedigree. To validate this QTL effect, we used an extended GP(3)-based pedigree. In the validation cross, each of the 46 offspring was clonally propagated from developing seeds using somatic embryogenesis technology. Subsequent analyses were conducted separately for seedlings and for other somatic emblings. For seedlings, the original QTL effect could not be fully validated. For somatic emblings, a strong negative QTL effect was detected in the validation cross; some evidence from another cross-supported the original positive QTL effect. From this part of the analysis, three distinct marker-QTL haplotypes at a single locus could be inferred. Validating QTL haplotypes in readily available field tests was feasible despite the genetic model complexity inherent to outcrossing long-lived perennials.

Estimating a founder's genomic proportion for each descendant in an outbred pedigree.

The question of how to estimate a founder's proportion of a single descendant's genome has renewed relevance for outbred pedigrees, given the abundant DNA sequence data for model and nonmodel eukaryotes alike. Here we show that a donor-recurrent shortcut method can provide a robust estimation of founder proportions. In addition, we define the theoretical variance and estimate confidence intervals using a nonparameteric bootstrap method. Using actual marker data from a highly heterozygous outbred Pinus taeda pedigree, it was found that each founder's genomic proportion varied widely for each descendant, ranging from 8.8% to 38.7%. In 1 case, skewed transmission of a founder's genome could be statistically detected. Its founder proportions ranged from 1.54% to 48.46%, and its mean value was 17.59%, well below the expected value of 25%. Two-thirds of its 91 descendants had 1 or the other founder haplotype, despite 2 successive meioses. The donor-recurrent method was robust; variation for estimated founder's proportions was also wide for simulated high-density datasets whether markers were dispersed or clustered. Estimating founder contributions using this computational shortcut has broad application for highly heterozygous outbred pedigrees characterized by large sibships, low population differentiation, and shallow physical mapping resources. The relevance of this computational shortcut for outbred populations used for conservation, domestication, and evolutionary biology research is discussed.

An entropy-based measure of founder informativeness.

Optimizing quantitative trait locus (QTL) mapping experiments requires a generalized measure of marker informativeness because variable information is obtained from different marker systems, marker distribution and pedigree types. Such a measure can be derived from the concept of Shannon entropy, a central concept in information theory. Here we introduce entropy-based founder informativeness (EFI), a new measure of information content generalized across pedigrees, maps, marker systems and mating configurations. We derived equations for inbred- and outbred-derived mapping populations. Mathematical properties of EFI include enhanced sensitivity to mapping population type and extension to any number of founders. To illustrate the use of EFI, we compared experimental designs for QTL mapping for three examples: (i) different marker systems for an F2 pedigree, (ii) different marker densities and sampling sizes for a BC1 pedigree and (iii) a comparison of haplotypic versus zygotic analyses of an outbred pedigree. As an a priori generalized measure of information content, EFI does not require phenotypic data for optimizing experimental designs for QTL mapping.

No clustering for linkage map based on low-copy and undermethylated microsatellites.

Clustering has been reported for conifer genetic maps based on hypomethylated or low-copy molecular markers, resulting in uneven marker distribution. To test this, a framework genetic map was constructed from three types of microsatellites: low-copy, undermethylated, and genomic. These Pinus taeda L. microsatellites were mapped using a three-generation pedigree with 118 progeny. The microsatellites were highly informative; of the 32 markers in intercross configuration, 29 were segregating for three or four alleles in the progeny. The sex-averaged map placed 51 of the 95 markers in 15 linkage groups at LOD > 4.0. No clustering or uneven distribution across the genome was observed. The three types of P. taeda microsatellites were randomly dispersed within each linkage group. The 51 microsatellites covered a map distance of 795 cM, an average distance of 21.8 cM between markers, roughly half of the estimated total map length. The minimum and maximum distances between any two bins was 4.4 and 45.3 cM, respectively. These microsatellites provided anchor points for framework mapping for polymorphism in P. taeda and other closely related hard pines.