Variations in photosynthetic rates of fourteen coleus cultivars

Fourteen cultivars of coleus (Coleus blumei Benth) were found to vary in chlorophyll content, photosynthetic rate, anthocyanin content and number of stomates.     

Genome Wide Association Study Identifies New Loci Associated with Undesired Coat Color Phenotypes in Saanen Goats

This paper reports a quantitative genetics and genomic analysis of undesirable coat color patterns in goats. Two undesirable coat colors have routinely been recorded for the past 15 years in French Saanen goats. One fifth of Saanen females have been phenotyped “pink” (8.0%) or “pink neck” (11.5%) and consequently have not been included in the breeding program as elite animals. Heritability of the binary “pink” and “pink neck” phenotype, estimated from 103,443 females was 0.26 for “pink” and 0.21 for “pink neck”. Genome wide association studies (using haplotypes or single SNPs) were implemented using a daughter design of 810 Saanen goats sired by 9 Artificial Insemination bucks genotyped with the goatSNP50 chip. A highly significant signal (-log10pvalue = 10.2) was associated with the “pink neck” phenotype on chromosome 11, suggesting the presence of a major gene. Highly significant signals for the “pink” phenotype were found on chromosomes 5 and 13 (-log10p values of 7.2 and, 7.7 respectively). The most significant SNP on chromosome 13 was in the ASIP gene region, well known for its association with coat color phenotypes. Nine significant signals were also found for both traits. The highest signal for each trait was detected by both single SNP and haplotype approaches, whereas the smaller signals were not consistently detected by the two methods. Altogether these results demonstrated a strong genetic control of the “pink” and “pink neck” phenotypes in French Saanen goats suggesting that SNP information could be used to identify and remove undesired colored animals from the breeding program.     

RMDAP: a versatile, ready-to-use toolbox for multigene genetic transformation

Background

The use of transgenes to improve complex traits in crops has challenged current genetic transformation technology for multigene transfer. Therefore, a multigene transformation strategy for use in plant molecular biology and plant genetic breeding is thus needed.

Methodology/Principal Findings

Here we describe a versatile, ready-to-use multigene genetic transformation method, named the Recombination-assisted Multifunctional DNA Assembly Platform (RMDAP), which combines many of the useful features of existing plant transformation systems. This platform incorporates three widely-used recombination systems, namely, Gateway technology, in vivo Cre/loxP and recombineering into a highly efficient and reliable approach for gene assembly. RMDAP proposes a strategy for gene stacking and contains a wide range of flexible, modular vectors offering a series of functionally validated genetic elements to manipulate transgene overexpression or gene silencing involved in a metabolic pathway. In particular, the ability to construct a multigene marker-free vector is another attractive feature. The built-in flexibility of original vectors has greatly increased the expansibility and applicability of the system. A proof-of-principle experiment was confirmed by successfully transferring several heterologous genes into the plant genome.

Conclusions/Significance

This platform is a ready-to-use toolbox for full exploitation of the potential for coordinate regulation of metabolic pathways and molecular breeding, and will eventually achieve the aim of what we call “one-stop breeding.”     

A novel approach for multi-domain and multi-gene family identification provides insights into evolutionary dynamics of disease resistance genes in core eudicot plants

Background

Recent advances in DNA sequencing techniques resulted in more than forty sequenced plant genomes representing a diverse set of taxa of agricultural, energy, medicinal and ecological importance. However, gene family curation is often only inferred from DNA sequence homology and lacks insights into evolutionary processes contributing to gene family dynamics. In a comparative genomics framework, we integrated multiple lines of evidence provided by gene synteny, sequence homology and protein-based Hidden Markov Modelling to extract homologous super-clusters composed of multi-domain resistance (R)-proteins of the NB-LRR type (for NUCLEOTIDE BINDING/LEUCINE-RICH REPEATS), that are involved in plant innate immunity.

Results

To assess the diversity of R-proteins within and between species, we screened twelve eudicot plant genomes including six major crops and found a total of 2,363 NB-LRR genes. Our curated R-proteins set shows a 50% average for tandem duplicates and a 22% fraction of gene copies retained from ancient polyploidy events (ohnologs). We provide evidence for strong positive selection and show significant differences in molecular evolution rates (Ka/Ks-ratio) among tandem- (mean = 1.59), ohnolog (mean = 1.36) and singleton (mean = 1.22) R-gene duplicates. To foster the process of gene-edited plant breeding, we report species-specific presence/absence of all 140 NB-LRR genes present in the model plant Arabidopsis and describe four distinct clusters of NB-LRR “gatekeeper” loci sharing syntenic orthologs across all analyzed genomes.

Conclusion

By curating a near-complete set of multi-domain R-protein clusters in an eudicot-wide scale, our analysis offers significant insight into evolutionary dynamics underlying diversification of the plant innate immune system. Furthermore, our methods provide a blueprint for future efforts to identify and more rapidly clone functional NB-LRR genes from any plant species.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-966) contains supplementary material, which is available to authorized users.     

Pectin esterase in relation to leaf abscission in coleus and phaseolus

Pectin esterase (PE) activities in abscission zones, other portions of leaves, and adjacent stem tissues were compared in attached leaves and abscissing petioles (previously debladed) of Coleus blumei Benth. and Phaseolus vulgaris L., cv. Canadian Wonder. Earlier findings of Osborne in bean were confirmed and changes in PE activity in coleus were shown to resemble those in bean in some respects. In both plants PE was lower in the distal portion of abscission zones of abscissing petioles than in that portion of attached leaves but this difference was not as large or as consistently clear-cut in coleus as in bean. The general level of PE activity was an order of magnitude lower and changes associated with abscission were smaller in coleus than in bean. Auxin treatment of debladed petioles of coleus prevented abscission and resulted in small increases in PE activity in abscission zones and most of the other regions sampled. The largest increase was observed in the stem tissue adjacent to the attached leaf opposite the debladed, auxin treated one.     

Harvesting the Promising Fruits of Genomics: Applying Genome Sequencing Technologies to Crop Breeding

Next generation sequencing (NGS) technologies are being used to generate whole genome sequences for a wide range of crop species. When combined with precise phenotyping methods, these technologies provide a powerful and rapid tool for identifying the genetic basis of agriculturally important traits and for predicting the breeding value of individuals in a plant breeding population. Here we summarize current trends and future prospects for utilizing NGS-based technologies to develop crops with improved trait performance and increase the efficiency of modern plant breeding. It is our hope that the application of NGS technologies to plant breeding will help us to meet the challenge of feeding a growing world population.

This article is part of the PLOS Biology Collection “The Promise of Plant Translational Research.”

     

Detection of copy number variations and their effects in Chinese bulls

Background

Copy number variations (CNVs) are a main source of genomic structural variations underlying animal evolution and production traits. Here, with one pure-blooded Angus bull as reference, we describe a genome-wide analysis of CNVs based on comparative genomic hybridization arrays in 29 Chinese domesticated bulls and examined their effects on gene expression and cattle growth traits.

Results

We identified 486 copy number variable regions (CNVRs), covering 2.45% of the bovine genome, in 24 taurine (Bos taurus), together with 161 ones in 2 yaks (Bos grunniens) and 163 ones in 3 buffaloes (Bubalus bubalis). Totally, we discovered 605 integrated CNVRs, with more “loss” events than both “gain” and “both” ones, and clearly clustered them into three cattle groups. Interestingly, we confirmed their uneven distributions across chromosomes, and the differences of mitochondrion DNA copy number (gain: taurine, loss: yak & buffalo). Furthermore, we confirmed approximately 41.8% (253/605) and 70.6% (427/605) CNVRs span cattle genes and quantitative trait loci (QTLs), respectively. Finally, we confirmed 6 CNVRs in 9 chosen ones by using quantitative PCR, and further demonstrated that CNVR22 had significantly negative effects on expression of PLA2G2D gene, and both CNVR22 and CNVR310 were associated with body measurements in Chinese cattle, suggesting their key effects on gene expression and cattle traits.

Conclusions

The results advanced our understanding of CNV as an important genomic structural variation in taurine, yak and buffalo. This study provides a highly valuable resource for Chinese cattle’s evolution and breeding researches.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2164-15-480) contains supplementary material, which is available to authorized users.     

Assessment of Genetic Heterogeneity in Structured Plant Populations Using Multivariate Whole-Genome Regression Models

Plant breeding populations exhibit varying levels of structure and admixture; these features are likely to induce heterogeneity of marker effects across subpopulations. Traditionally, structure has been dealt with as a potential confounder, and various methods exist to “correct” for population stratification. However, these methods induce a mean correction that does not account for heterogeneity of marker effects. The animal breeding literature offers a few recent studies that consider modeling genetic heterogeneity in multibreed data, using multivariate models. However, these methods have received little attention in plant breeding where population structure can have different forms. In this article we address the problem of analyzing data from heterogeneous plant breeding populations, using three approaches: (a) a model that ignores population structure [A-genome-based best linear unbiased prediction (A-GBLUP)], (b) a stratified (i.e., within-group) analysis (W-GBLUP), and (c) a multivariate approach that uses multigroup data and accounts for heterogeneity (MG-GBLUP). The performance of the three models was assessed on three different data sets: a diversity panel of rice (Oryza sativa), a maize (Zea mays L.) half-sib panel, and a wheat (Triticum aestivum L.) data set that originated from plant breeding programs. The estimated genomic correlations between subpopulations varied from null to moderate, depending on the genetic distance between subpopulations and traits. Our assessment of prediction accuracy features cases where ignoring population structure leads to a parsimonious more powerful model as well as others where the multivariate and stratified approaches have higher predictive power. In general, the multivariate approach appeared slightly more robust than either the A- or the W-GBLUP.     

Using continuous directed evolution to improve enzymes for plant applications

Continuous directed evolution of enzymes and other proteins in microbial hosts is capable of outperforming classical directed evolution by executing hypermutation and selection concurrently in vivo, at scale, with minimal manual input. Provided that a target enzyme’s activity can be coupled to growth of the host cells, the activity can be improved simply by selecting for growth. Like all directed evolution, the continuous version requires no prior mechanistic knowledge of the target. Continuous directed evolution is thus a powerful way to modify plant or non-plant enzymes for use in plant metabolic research and engineering. Here, we first describe the basic features of the yeast (Saccharomyces cerevisiae) OrthoRep system for continuous directed evolution and compare it briefly with other systems. We then give a step-by-step account of three ways in which OrthoRep can be deployed to evolve primary metabolic enzymes, using a THI4 thiazole synthase as an example and illustrating the mutational outcomes obtained. We close by outlining applications of OrthoRep that serve growing demands (i) to change the characteristics of plant enzymes destined for return to plants, and (ii) to adapt (“plantize”) enzymes from prokaryotes—especially exotic prokaryotes—to function well in mild, plant-like conditions.

Continuous directed evolution using the yeast OrthoRep system is a powerful way to improve enzymes for use in plant engineering as illustrated by “plantizing” a bacterial thiamin synthesis enzyme.     

Tracheid analysis and modeling of the minor veins of the coleus and smilax leaves

Tracheid analysis was carried out on the veinlets and minor veins of the coleus (Solenostemon scutellarioides [L.] Codd) leaf. Third- to fifth-order, or minor, veins average 3.4 tracheids in tandem and they bipartition islets when these enclosed islets reach a critical size; both these features of vein length and islet size contribute to a self-similar process of vein pattern generation. An areole was calculated to be initially comprised of about ten cells making the patterning event for vein formation requiring only a few cells. An algorithmic model developed here for minor vein formation includes five production rules, and this computer model explains the 3–4 tracheids per minor vein, presence of isolated tracheids, the structure of veinlets, and the elaborate branching patterns of veinlets in coleus and other plants.     

Dynamic Interpretation of Hedgehog Signaling in the Drosophila Wing Disc

Morphogens are classically defined as molecules that control patterning by acting at a distance to regulate gene expression in a concentration-dependent manner. In the Drosophila wing imaginal disc, secreted Hedgehog (Hh) forms an extracellular gradient that organizes patterning along the anterior–posterior axis and specifies at least three different domains of gene expression. Although the prevailing view is that Hh functions in the Drosophila wing disc as a classical morphogen, a direct correspondence between the borders of these patterns and Hh concentration thresholds has not been demonstrated. Here, we provide evidence that the interpretation of Hh signaling depends on the history of exposure to Hh and propose that a single concentration threshold is sufficient to support multiple outputs. Using mathematical modeling, we predict that at steady state, only two domains can be defined in response to Hh, suggesting that the boundaries of two or more gene expression patterns cannot be specified by a static Hh gradient. Computer simulations suggest that a spatial “overshoot” of the Hh gradient occurs, i.e., a transient state in which the Hh profile is expanded compared to the Hh steady-state gradient. Through a temporal examination of Hh target gene expression, we observe that the patterns initially expand anteriorly and then refine, providing in vivo evidence for the overshoot. The Hh gene network architecture suggests this overshoot results from the Hh-dependent up-regulation of the receptor, Patched (Ptc). In fact, when the network structure was altered such that the ptc gene is no longer up-regulated in response to Hh-signaling activation, we found that the patterns of gene expression, which have distinct borders in wild-type discs, now overlap. Our results support a model in which Hh gradient dynamics, resulting from Ptc up-regulation, play an instructional role in the establishment of patterns of gene expression.     

Priors in Whole-Genome Regression: The Bayesian Alphabet Returns

Whole-genome enabled prediction of complex traits has received enormous attention in animal and plant breeding and is making inroads into human and even Drosophila genetics. The term “Bayesian alphabet” denotes a growing number of letters of the alphabet used to denote various Bayesian linear regressions that differ in the priors adopted, while sharing the same sampling model. We explore the role of the prior distribution in whole-genome regression models for dissecting complex traits in what is now a standard situation with genomic data where the number of unknown parameters (p) typically exceeds sample size (n). Members of the alphabet aim to confront this overparameterization in various manners, but it is shown here that the prior is always influential, unless n ≫ p. This happens because parameters are not likelihood identified, so Bayesian learning is imperfect. Since inferences are not devoid of the influence of the prior, claims about genetic architecture from these methods should be taken with caution. However, all such procedures may deliver reasonable predictions of complex traits, provided that some parameters (“tuning knobs”) are assessed via a properly conducted cross-validation. It is concluded that members of the alphabet have a room in whole-genome prediction of phenotypes, but have somewhat doubtful inferential value, at least when sample size is such that n ≪ p.     

Spiked GBS: a unified,open platform for single marker genotyping and whole-genome profiling

Background

In plant breeding, there are two primary applications for DNA markers in selection: 1) selection of known genes using a single marker assay (marker-assisted selection; MAS); and 2) whole-genome profiling and prediction (genomic selection; GS). Typically, marker platforms have addressed only one of these objectives.

Results

We have developed spiked genotyping-by-sequencing (sGBS), which combines targeted amplicon sequencing with reduced representation genotyping-by-sequencing. To minimize the cost of targeted assays, we utilize a small percent of sequencing capacity available in runs of GBS libraries to “spike” amplified targets of a priori alleles tagged with a different set of unique barcodes. This open platform allows multiple, single-target loci to be assayed while simultaneously generating a whole-genome profile. This dual-genotyping approach allows different sets of samples to be evaluated for single markers or whole genome-profiling. Here, we report the application of sGBS on a winter wheat panel that was screened for converted KASP markers and newly-designed markers targeting known polymorphisms in the leaf rust resistance gene Lr34.

Conclusions

The flexibility and low-cost of sGBS will enable a range of applications across genetics research. Specifically in breeding applications, the sGBS approach will allow breeders to obtain a whole-genome profile of important individuals while simultaneously targeting specific genes for a range of selection strategies across the breeding program.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1404-9) contains supplementary material, which is available to authorized users.     

Evaluating the Effect of 3′-UTR Variants in DICER1 and DROSHA on Their Tissue-Specific Expression by miRNA Target Prediction

Untranslated gene regions (UTRs) play an important role in controlling gene expression. 3′-UTRs are primarily targeted by microRNA (miRNA) molecules that form complex gene regulatory networks. Cancer genomes are replete with non-coding mutations, many of which are connected to changes in tumor gene expression that accompany the development of cancer and are associated with resistance to therapy. Therefore, variants that occurred in 3′-UTR under cancer progression should be analysed to predict their phenotypic effect on gene expression, e.g., by evaluating their impact on miRNA target sites. Here, we analyze 3′-UTR variants in DICER1 and DROSHA genes in the context of myelodysplastic syndrome (MDS) development. The key features of this analysis include an assessment of both “canonical” and “non-canonical” types of mRNA-miRNA binding and tissue-specific profiling of miRNA interactions with wild-type and mutated genes. As a result, we obtained a list of DICER1 and DROSHA variants likely altering the miRNA sites and, therefore, potentially leading to the observed tissue-specific gene downregulation. All identified variants have low population frequency consistent with their potential association with pathology progression.