Plant Breeding and Genomics News

We present a novel image analysis tool that allows the semi-automated quantification of complex root system architectures in a range of plant species, grown and imaged in a variety of ways. The automatic component of RootNav takes a top-down approach, utilising the powerful Expectation-Maximisation classification algorithm to examine regions of the input image, calculating the likelihood that given pixels correspond to roots. This information is used as the basis for an optimisation approach to root detection and quantification, which effectively fits a root model to the image data. The resulting user experience is akin to defining routes on a motorist&rsquo's satellite navigation system: RootNav makes an initial optimised estimate of paths from the seed point to root apices, and the user is able to easily and intuitively refine the results using a visual approach. The proposed method is evaluated on winter wheat images (and demonstrated on Arabidopsis thaliana, Brassica napus and Oryza sativa), and results compared to manual analysis. Four exemplar traits are calculated, and show clear illustrative differences between some of the wheat accessions. RootNav, however, provides the structural information needed to support extraction of a wider variety of biologically relevant measures. A separate Viewer tool is provided to recover a rich set of architectural traits from RootNav's core representation.

Background: Forward-time population genetic simulations play a central role in deriving and testing evolutionary hypotheses. Such simulations may be data-intensive, depending on the settings to the various parameters controlling them. In particular, for certain settings, the data footprint may quickly exceed the memory of a single compute node. Results: We develop a novel and general method for addressing the memory issue inherent in forward-time simulations by compressing and decompressing, in real-time, active and ancestral genotypes, while carefully accounting for the time overhead. We propose a general graph data structure for compressing the genotype space explored during a simulation run, along with efficient algorithms for constructing and updating compressed genotypes which support both mutation and recombination. We tested the performance of our method in very large-scale simulations. Results show that our method not only scales well, but that it also overcomes memory issues that would cripple existing tools. Conclusions: As evolutionary analyses are being increasingly performed on genomes, pathways, and networks, particularly in the era of systems biology, scaling population genetic simulators to handle large-scale simulations is crucial. We believe our method offers a significant step in that direction. Further, the techniques we provide are generic and can be integrated with existing population genetic simulators to boost their performance in terms of memory usage.

Background

Recent genome-wide studies have suggested that in addition to genetic variation, epigenetic variation may also be associated with differential gene expression and growth vigor in plant hybrids. Maize is an ideal model system for the study of epigenetic variation in hybrids, given the significant heterotic performance of the plant, the well-known complexity of the genome, and the rich history of epigenetic studies using this organism. However, integrated comparative transcriptomic and epigenomic analyses in different organs of maize hybrids remain largely unexplored.

Methods

We generated integrated maps of transcriptomes and epigenomes from shoots and roots of two maize inbred lines and their reciprocal hybrids, and globally surveyed the epigenetic variations and their relationships with transcriptional divergence between different organs and genotypes.

Results

Whereas histone modifications varied both between organs and between genotypes, DNA-methylation patterns were more distinguishable between genotypes than between organs. Histone modifications were associated with transcriptomic divergence between organs and between hybrids and parents. Further, genes that were upregulated in both shoots and roots of hybrids were significantly enriched in the nucleosome assembly pathway. Interestingly, small interfering RNAs (siRNAs) of 22 and 24 nucleotides long were shown to be derived from distinct transposable elements, and for different transposable elements in both shoots and roots, the differences in siRNA activity between hybrids and patents were primarily driven by different siRNA species.

Conclusions

These results suggest that despite variation in specific genes or genomic loci, similar mechanisms may account for the genome-wide epigenetic regulation of gene activity and transposon stability in different organs of maize hybrids.

Background

Visualization plays an essential role in genomics research by making it possible to observe correlations and trends in large datasets as well as communicate findings to others. Visual analysis, which combines visualization with analysis tools to enable seamless use of both approaches for scientific investigation, offers a powerful method for performing complex genomic analyses. However, there are numerous challenges that arise when creating rich, interactive Web-based visualizations/visual analysis applications for high-throughput genomics. These challenges include managing data flow from Web server to Web browser, integrating analysis tools and visualizations, and sharing visualizations with colleagues.

Results

We have created a platform simplifies the creation of Web-based visualization/visual analysis applications for high-throughput genomics. This platform provides components that make it simple to efficiently query very large datasets, draw common representations of genomic data, integrate with analysis tools, and share or publish fully interactive visualizations. Using this platform, we have created a Circos-style genome-wide viewer, a generic scatter plot for correlation analysis, an interactive phylogenetic tree, a scalable genome browser for next-generation sequencing data, and an application for systematically exploring tool parameter spaces to find good parameter values. All visualizations are interactive and fully customizable. The platform is integrated with the Galaxy (http://galaxyproject.org) genomics workbench, making it easy to integrate new visual applications into Galaxy.

Conclusions

Visualization and visual analysis play an important role in high-throughput genomics experiments, and approaches are needed to make it easier to create applications for these activities. Our framework provides a foundation for creating Web-based visualizations and integrating them into Galaxy. Finally, the visualizations we have created using the framework are useful tools for high-throughput genomics experiments.

When confronted with water limitation, plants actively reprogram their metabolism and growth. Recently, it has become clear that growing tissues show specific and highly dynamic responses to drought, which differ from the well-studied responses in mature tissues. Here, we provide an overview of recent advances in understanding shoot growth regulation in water-limiting conditions. Of special interest is the balance between maintained growth and competitiveness on the one hand and ensured survival on the other hand. A number of master regulators controlling this balance have been identified, such as DELLAs and AP2/ERF-type transcription factors. The perspectives to engineer or breed crops that maintain growth in periods of mild drought, but are still able to activate protective tolerance mechanisms, are discussed.

Background

Cotton fiber length is very important to the quality of textiles. Understanding the genetics and physiology of cotton fiber elongation can provide valuable tools to the cotton industry by targeting genes or other molecules responsible for fiber elongation. Ligon Lintless-1 (Li1) is a monogenic mutant in Upland cotton (Gossypium hirsutum) which exhibits an early cessation of fiber elongation resulting in very short fibers (< 6mm) at maturity. This presents an excellent model system for studying the underlying molecular and cellular processes involved with cotton fiber elongation. Previous reports have characterized Li1 at early cell wall elongation and during later secondary cell wall synthesis, however there has been very limited analysis of the transition period between these developmental time points.

Results

Physical and morphological measurements of the Li1 mutant fibers were conducted, including measurement of the cellulose content during development. Affymetrix microarrays were used to analyze transcript profiles at the critical developmental time points of 3 days post anthesis (DPA), the late elongation stage of 12 DPA and the early secondary cell wall synthesis stage of 16 DPA. The results indicated severe disruption to key hormonal and other pathways related to fiber development, especially pertaining to the transition stage from elongation to secondary cell wall synthesis. Gene Ontology enrichment analysis identified several key pathways at the transition stage that exhibited altered regulation. Genes involved in ethylene biosynthesis and primary cell wall rearrangement were affected, and a primary cell wall-related cellulose synthase was transcriptionally repressed. Linkage mapping using a population of 2,553 F2 individuals identified SSR markers associated with the Li1 genetic locus on chromosome 22. Linkage mapping in combination with utilizing the diploid G. raimondii genome sequences permitted additional analysis of the region containing the Li1 gene.

Conclusions

The early termination of fiber elongation in the Li1 mutant is likely controlled by an early upstream regulatory factor resulting in the altered regulation of hundreds of downstream genes. Several elongation-related genes that exhibited altered expression profiles in the Li1 mutant were identified. Molecular markers closely associated with the Li1 locus were developed. Results presented here will lay the foundation for further investigation of the genetic and molecular mechanisms of fiber elongation.

June 14, 2013 by Shawn C. Yarnes

 

Yesterday the Supreme Court banned patents on naturally occurring DNA.  The judges determined that Myriad Genetics does not have the right to patent the isolation of naturally occurring BRCA1 and BRCA2 genes.  Myriad Genetics’s original patent effectively prohibited others from isolating these genes, because they held the patent on all 15 base pair segments of these genes.

 

Interestingly, the court upheld Myriad Genetics’s patent on the complementary DNA (cDNA) of these genes.  cDNA is a synthetic DNA copy of an RNA molecule. They ruled that cDNA is “not a product of nature,” and therefore patent eligible.  Most eukaryotic genes, including BRCA1 and BRAC2, contain introns, or non-coding DNA, that are spliced out of messenger RNA (mRNA) before proteins are made from the mRNA template. Since DNA is a much more stable molecule than RNA, mRNA is regularly copied to cDNA for sequencing and manipulation using the enzyme, reverse transcriptase. Expressed gene sequences are arguably the most important portions of the eukaryotic genome, because they are templates for protein synthesis. 

 

The ability to patent cDNA appears to limit the ability of others to synthesize the BRCA1 and BRCA2 proteins.  However, a cDNA patent alone poses only minor limitations to the synthesis of a bioidentical protein.  For example the BRCA1 protein is made of 1863 amino acids, and each amino acid, with the exception of methionine, is redundantly coded by 2-4 nucleic acid codons.  Roughly calculated, assuming that each amino acid can be coded by 2.8 nucleic acid codons, over 1.4 billion different DNA sequences can code for exactly the same 1863 amino acid protein.  Copying naturally occurring mRNA into cDNA, remains the simplest and cheapest way to synthesize proteins, but de novo DNA synthesis using alternate codons is possible, and like reverse transcription of spliced mRNA, creates novel molecules that are not a "product of nature." If de novo synthesis is also patent eligible, than there maybe no reason anyone would patent cDNA. 

 

What seems clear from yesterday’s ruling is that the information within naturally occurring non-coding regions of eukaryotic genomes, including promoters and introns, is not patent eligible.  The same holds true for the information within prokaryotic and viral genomes where mRNAs are not generally spliced.  It will be interesting to see how the cDNA patent issue is interpreted.

 

  

Read the ruling here: http://www.supremecourt.gov/opinions/12pdf/12-398_8njq.pdf

The conclusion that emerges is that a radical rethink is needed in the orientation of agriculture. Research has to underpin innovations that will allow more food, fiber, and biofuel to be produced but in ways that alleviate rural poverty, improve diets and health, and allow increases in stocks of the environmental assets upon which all depends. Progress towards these four goals requires new ways of organizing research, new ways of setting priorities, and more subtle ways of assessing outcomes and impacts. The solutions will not be narrow sectoral or technical innovations but nested sets of innovations at the scale of the plant, the agronomic system, the landscape, and the institutional environment.

Background

There is growing evidence for the prevalence of copy number variation (CNV) and its role in phenotypic variation in many eukaryotic species. Here we use array comparative genomic hybridization to explore the extent of this type of structural variation in domesticated barley cultivars and wild barleys.

Results

A collection of 14 barley genotypes including eight cultivars and six wild barleys were used for comparative genomic hybridization. CNV affects 14.9% of all the sequences that were assessed. Higher levels of CNV diversity are present in the wild accessions relative to cultivated barley. CNVs are enriched near the ends of all chromosomes except 4H, which exhibits the lowest frequency of CNVs. CNV affects 9.5% of the coding sequences represented on the array and the genes affected by CNV are enriched for sequences annotated as disease-resistance proteins and protein kinases. Sequence-based comparisons of CNV between cultivars Barke and Morex provided evidence that DNA repair mechanisms of double-strand breaks via single-stranded annealing and synthesis-dependent strand annealing play an important role in the origin of CNV in barley.

Conclusions

We present the first catalog of CNVs in a diploid Triticeae species, which opens the door for future genome diversity research in a tribe that comprises the economically important cereal species wheat, barley, and rye. Our findings constitute a valuable resource for the identification of CNV affecting genes of agronomic importance. We also identify potential mechanisms that can generate variation in copy number in plant genomes.