Strategies for automated analysis of <Emphasis Type="Italic">C. elegans</Emphasis> locomotion

Automated analysis of C. elegans behaviour is a rapidly developing field, offering the possibility of behaviour-based, high-throughput drug screens and systematic phenotyping. Standard methods for parameterizing worm shapes and movements are emerging, and progress has been made towards overcoming the difficulties introduced by interactions between worms, as well as worm coiling and omega turning. Current methods have facilitated the identification of subtle phenotypes and the characterisation of roles of neurones in forward locomotion and chemotaxis, as well as the quantitative characterisation of behaviour choice and circadian patterns of activity. Given the speed with which C. elegans has been deployed in genetic screens and chemical screens, it is to be hoped that wormtrackers may eventually provide similar rapidity in assaying behavioural phenotypes. However, considerable progress must be made before this can be accomplished. In the case of genome-wide RNAi screens, for example, the presence in the worm genome of some 19,000 genes means that even the minimal user intervention in an automatic phenotyping system will be very costly. Nonetheless, recent advances have shown that drug actions on large numbers of worms can be tracked, raising hopes that high-throughput behavioural screens may soon be available.     

Genome-wide high-throughput screens in functional genomics

The availability of complete genome sequences from many organisms has yielded the ability to perform high-throughput, genome-wide screens of gene function. Within the past year, rapid advances have been made towards this goal in many major model systems, including yeast, worms, flies, and mammals. Yeast genome-wide screens have taken advantage of libraries of deletion strains, but RNA-interference has been used in other organisms to knockdown gene function. Examples of recent large-scale functional genetic screens include drug-target identification in yeast, regulators of fat accumulation in worms, growth and viability in flies, and proteasome-mediated degradation in mammalian cells. Within the next five years, such screens are likely to lead to annotation of function of most genes across multiple organisms. Integration of such data with other genomic approaches will extend our understanding of cellular networks.     

Parallel reverse genetic screening in mutant human cells using transcriptomics

Reverse genetic screens have driven gene annotation and target discovery in model organisms. However, many disease‐relevant genotypes and phenotypes cannot be studied in lower organisms. It is therefore essential to overcome technical hurdles associated with large‐scale reverse genetics in human cells. Here, we establish a reverse genetic approach based on highly robust and sensitive multiplexed RNA sequencing of mutant human cells. We conduct 10 parallel screens using a collection of engineered haploid isogenic cell lines with knockouts covering tyrosine kinases and identify known and unexpected effects on signaling pathways. Our study provides proof of concept for a scalable approach to link genotype to phenotype in human cells, which has broad applications. In particular, it clears the way for systematic phenotyping of still poorly characterized human genes and for systematic study of uncharacterized genomic features associated with human disease.     

High-throughput phenotyping of multicellular organisms: finding the link between genotype and phenotype

High-throughput phenotyping approaches (phenomics) are being combined with genome-wide genetic screens to identify alterations in phenotype that result from gene inactivation. Here we highlight promising technologies for 'phenome-scale' analyses in multicellular organisms.     

A Scalable Open-Source Pipeline for Large-Scale Root Phenotyping of Arabidopsis

Large-scale phenotyping of multicellular organisms is one of the current challenges in biology. We present a comprehensive and scalable pipeline that allows for the efficient phenotyping of root growth traits on a large scale. This includes a high-resolution, low-cost acquisition setup as well as the automated image processing software BRAT. We assess the performance of this pipeline in Arabidopsis thaliana under multiple growth conditions and show its utility by performing genome-wide association studies on 16 root growth traits quantified by BRAT each day during a 5-d time-course experiment. The most significantly associated genome region for root growth rate is a locus encoding a calcium sensing receptor. We find that loss of function and overexpression of this gene can significantly alter root growth in a growth condition dependent manner and that the minor natural allele of the Calcium Sensor Receptor locus is highly significantly enriched in populations in coastal areas, demonstrating the power of our approach to identify regulators of root growth that might have adaptive relevance.     

RNAi screens in Caenorhabditis elegans in a 96-well liquid format and their application to the systematic identification of genetic interactions

We describe a protocol for performing RNA interference (RNAi) screens in Caenorhabditis elegans in liquid culture in 96-well plates. The procedure allows a single researcher to set-up and score RNAi experiments at approximately 2,000 genes per day. By comparing RNAi phenotypes between wild-type worms and worms carrying a defined genetic mutation, we have used this protocol to identify synthetic lethal interactions between genes systematically. We also describe how the protocol can be adapted to target two genes simultaneously by combinatorial RNAi.     

High-throughput RNAi screening by time-lapse imaging of live human cells

RNA interference (RNAi) is a powerful tool to study gene function in cultured cells. Transfected cell microarrays in principle allow high-throughput phenotypic analysis after gene knockdown by microscopy. But bottlenecks in imaging and data analysis have limited such high-content screens to endpoint assays in fixed cells and determination of global parameters such as viability. Here we have overcome these limitations and developed an automated platform for high-content RNAi screening by time-lapse fluorescence microscopy of live HeLa cells expressing histone-GFP to report on chromosome segregation and structure. We automated all steps, including printing transfection-ready small interfering RNA (siRNA) microarrays, fluorescence imaging and computational phenotyping of digital images, in a high-throughput workflow. We validated this method in a pilot screen assaying cell division and delivered a sensitive, time-resolved phenoprint for each of the 49 endogenous genes we suppressed. This modular platform is scalable and makes the power of time-lapse microscopy available for genome-wide RNAi screens.     

Quantitative and Automated High-throughput Genome-wide RNAi Screens in C. elegans

RNA interference is a powerful method to understand gene function, especially when conducted at a whole-genome scale and in a quantitative context. In C. elegans, gene function can be knocked down simply and efficiently by feeding worms with bacteria expressing a dsRNA corresponding to a specific gene ¹. While the creation of libraries of RNAi clones covering most of the C. elegans genome ^2,3 opened the way for true functional genomic studies (see for example ^4-7), most established methods are laborious. Moy and colleagues have developed semi-automated protocols that facilitate genome-wide screens ⁸. The approach relies on microscopic imaging and image analysis. Here we describe an alternative protocol for a high-throughput genome-wide screen, based on robotic handling of bacterial RNAi clones, quantitative analysis using the COPAS Biosort (Union Biometrica (UBI)), and an integrated software: the MBioLIMS (Laboratory Information Management System from Modul-Bio) a technology that provides increased throughput for data management and sample tracking. The method allows screens to be conducted on solid medium plates. This is particularly important for some studies, such as those addressing host-pathogen interactions in C. elegans, since certain microbes do not efficiently infect worms in liquid culture.We show how the method can be used to quantify the importance of genes in anti-fungal innate immunity in C. elegans. In this case, the approach relies on the use of a transgenic strain carrying an epidermal infection-inducible fluorescent reporter gene, with GFP under the control of the promoter of the antimicrobial peptide gene nlp 29 and a red fluorescent reporter that is expressed constitutively in the epidermis. The latter provides an internal control for the functional integrity of the epidermis and nonspecific transgene silencing⁹. When control worms are infected by the fungus they fluoresce green. Knocking down by RNAi a gene required for nlp 29 expression results in diminished fluorescence after infection. Currently, this protocol allows more than 3,000 RNAi clones to be tested and analyzed per week, opening the possibility of screening the entire genome in less than 2 months.     

Breeding by design

Breeding by Design is a concept that aims to control all allelic variation for all genes of agronomic importance. This concept can be achieved through a combination of precise genetic mapping, high-resolution chromosome haplotyping and extensive phenotyping. Thanks to marker technology, software tools and the know-how available today, this goal can now be achieved. Depending on the crop-specific generation time, controlled marker-assisted selection strategies could lead to the production of superior varieties within five to ten years.     

A call to fins! Zebrafish as a gerontological model

Among the wide variety of model organisms commonly used for studies on aging, such as worms, flies and rodents, a wide research gap exists between the invertebrate and vertebrate model systems. In developmental biology, a similar gap has been filled by the zebrafish (Danio rerio). We propose that the zebrafish is uniquely suited to serve as a bridge model for gerontology. With high fecundity and economical husbandry requirements, large populations of zebrafish may be generated quickly and cheaply, facilitating large-scale approaches including demographic studies and mutagenesis screens. A variety of mutants identified in such screens have led to modelling of human disease, including cardiac disorders and cancer. While zebrafish longevity is at least 50% longer than in commonly used mouse strains, as an ectothermic fish species, its life span may be readily modulated by caloric intake, ambient temperature and reproductive activity. These features, coupled with a growing abundance of biological resources, including an ongoing genome sequencing project, make the zebrafish a compelling model organism for studies on aging.     

Ramanome technology platform for label-free screening and sorting of microbial cell factories at single-cell resolution

Phenotypic profiling of natural, engineered or synthetic cells has increasingly become a bottleneck in the mining and engineering of cell factories. Single-cell phenotyping technologies are highly promising for tackling this hurdle, yet ideally they should allow non-invasive live-cell probing, be label-free, provide landscape-like phenotyping capability, distinguish complex functions, operate with high speed, sufficient throughput and low cost, and finally, couple with cell sorting so as to enable downstream omics analysis. This review focuses on recent progress in Ramanome Technology Platform (RTP), which consists of Raman spectroscopy based phenotyping, sorting and sequencing of single cells, and discuss the key challenges and emerging trends. In addition, we propose ramanome, a collection of single-cell Raman spectra (SCRS) acquired from individual cells within a cellular population or consortium, as a new type of biological phenome datatype at the single-cell resolution. By establishing the phenome-genome links in a label-free, single-cell manner, RTP should find wide applications in functional screening and strain development of live microbial, plant and animal cell factories.     

Bimolecular fluorescence complementation (BiFC) analysis of protein interactions in Caenorhabditis elegans

Protein interactions are essential components of signal transduction in cells. With the progress in genome-wide yeast two hybrid screens and proteomics analyses, many protein interaction networks have been generated. These analyses have identified hundreds and thousands of interactions in cells and organisms, creating a challenge for further validation under physiological conditions. The bimolecular fluorescence complementation (BiFC) assay is such an assay that meets this need. The BiFC assay is based on the principle of protein fragment complementation, in which two non-fluorescent fragments derived from a fluorescent protein are fused to a pair of interacting partners. When the two partners interact, the two non-fluorescent fragments are brought into proximity and an intact fluorescent protein is reconstituted. Hence, the reconstituted fluorescent signals reflect the interaction of two proteins under study. Over the past six years, the BiFC assay has been used for visualization of protein interactions in living cells and organisms, including our application of the BiFC assay to the transparent nematode Caenorhabditis elegans. We have demonstrated that BiFC analysis in C. elegans provides a direct means to identify and validate protein interactions in living worms and allows visualization of temporal and spatial interactions. Here, we provide a guideline for the implementation of BiFC analysis in living worms and discuss the factors that are critical for BiFC analysis.     

Design and evaluation of genome-wide libraries for RNA interference screens

RNA interference (RNAi) screens have enabled the systematic analysis of many biological processes in cultured cells and whole organisms. The success of such screens and the interpretation of the data depend on the stringent design of RNAi libraries. We describe and validate NEXT-RNAi, a software for the automated design and evaluation of RNAi sequences on a genome-wide scale. NEXT-RNAi is implemented as open-source software and is accessible at http://www.nextrnai.org/     

Shifts in the Distribution of Mass Densities Is a Signature of Caloric Restriction in Caenorhabditis elegans

Although the starvation response of the model multicellular organism Caenorhabditis elegans is a subject of much research, there is no convenient phenotypic readout of caloric restriction that can be applicable to large numbers of worms. This paper describes the distribution of mass densities of populations of C. elegans, from larval stages up to day one of adulthood, using isopycnic centrifugation, and finds that density is a convenient, if complex, phenotypic readout in C. elegans. The density of worms in synchronized populations of wildtype N2 C. elegans grown under standard solid-phase culture conditions was normally distributed, with distributions peaked sharply at a mean of 1.091 g/cm³ for L1, L2 and L3 larvae, 1.087 g/cm³ for L4 larvae, 1.081 g/cm³ for newly molted adults, and 1.074 g/cm³ at 24 hours of adulthood. The density of adult worms under starvation stress fell well outside this range, falling to a mean value of 1.054 g/cm³ after eight hours of starvation. This decrease in density correlated with the consumption of stored glycogen in the food-deprived worms. The density of the worms increased when deprived of food for longer durations, corresponding to a shift in the response of the worms: worms sacrifice their bodies by retaining larvae, which consume the adults from within. Density-based screens with the drug Ivermectin on worms cultured on single plates resulted in a clear bimodal (double-peaked) distribution of densities corresponding to drug exposed and non-exposed worms. Thus, measurements of changes in density could be used to conduct screens on the effects of drugs on several populations of worms cultured on single plates.     

The art and design of genetic screens: RNA interference

The remarkable gene knockdown technique of RNAi has opened exciting new avenues for genetic screens in model organisms and human cells. Here we describe the current state of the art for RNAi screening, and stress the importance of well-designed assays and of analytical approaches for large-scale screening experiments, from high-throughput screens using simplified homogenous assays to microscopy and whole-animal experiments. Like classical genetic screens in the past, the success of large-scale RNAi surveys depends on a careful development of phenotypic assays and their interpretation in a relevant biological context.     

Nested effects models for high-dimensional phenotyping screens

MOTIVATION: In high-dimensional phenotyping screens, a large number of cellular features is observed after perturbing genes by knockouts or RNA interference. Comprehensive analysis of perturbation effects is one of the most powerful techniques for attributing functions to genes, but not much work has been done so far to adapt statistical and computational methodology to the specific needs of large-scale and high-dimensional phenotyping screens. RESULTS: We introduce and compare probabilistic methods to efficiently infer a genetic hierarchy from the nested structure of observed perturbation effects. These hierarchies elucidate the structures of signaling pathways and regulatory networks. Our methods achieve two goals: (1) they reveal clusters of genes with highly similar phenotypic profiles, and (2) they order (clusters of) genes according to subset relationships between phenotypes. We evaluate our algorithms in the controlled setting of simulation studies and show their practical use in two experimental scenarios: (1) a data set investigating the response to microbial challenge in Drosophila melanogaster, and (2) a compendium of expression profiles of Saccharomyces cerevisiae knockout strains. We show that our methods identify biologically justified genetic hierarchies of perturbation effects. AVAILABILITY: The software used in our analysis is freely available in the R package 'nem' from www.bioconductor.org.     

Crop 3D—a LiDAR based platform for 3D high-throughput crop phenotyping

With the growing population and the reducing arable land, breeding has been considered as an effective way to solve the food crisis.As an important part in breeding, high-throughput phenotyping can accelerate the breeding process effectively. Light detection and ranging(LiDAR) is an active remote sensing technology that is capable of acquiring three-dimensional(3 D) data accurately,and has a great potential in crop phenotyping. Given that crop phenotyping based on LiDAR technology is not common in China,we developed a high-throughput crop phenotyping platform, named Crop 3 D, which integrated LiDAR sensor, high-resolution camera, thermal camera and hyperspectral imager. Compared with traditional crop phenotyping techniques, Crop 3 D can acquire multi-source phenotypic data in the whole crop growing period and extract plant height, plant width, leaf length, leaf width, leaf area, leaf inclination angle and other parameters for plant biology and genomics analysis. In this paper, we described the designs,functions and testing results of the Crop 3 D platform, and briefly discussed the potential applications and future development of the platform in phenotyping. We concluded that platforms integrating LiDAR and traditional remote sensing techniques might be the future trend of crop high-throughput phenotyping.     

Cytogenetic genotype-phenotype studies: improving genotyping, phenotyping and data storage

High-resolution molecular cytogenetic techniques such as genomic array CGH and MLPA detect submicroscopic chromosome aberrations in patients with unexplained mental retardation. These techniques rapidly change the practice of cytogenetic testing. Additionally, these techniques may improve genotype-phenotype studies of patients with microscopically visible chromosome aberrations, such as Wolf-Hirschhorn syndrome, 18q deletion syndrome and 1p36 deletion syndrome. In order to make the most of high-resolution karyotyping, a similar accuracy of phenotyping is needed to allow researchers and clinicians to make optimal use of the recent advances. International agreements on phenotype nomenclature and the use of computerized 3D face surface models are examples of such improvements in the practice of phenotyping patients with chromosomal anomalies. The combination of high-resolution cytogenetic techniques, a comprehensive, systematic system for phenotyping and optimal data storage will facilitate advances in genotype-phenotype studies and a further deconstruction of chromosomal syndromes. As a result, critical regions or single genes can be determined to be responsible for specific features and malformations.     

Computational identification of cellular networks and pathways

In this article we highlight recent developments in computational functional genomics to identify networks of functionally related genes and proteins based on diverse sources of genomic data. Our specific focus is on statistical methods to identify genetic networks. We discuss integrated analysis of microarray datasets, methods to combine heterogeneous data sources, the analysis of high-dimensional phenotyping screens and describe efforts to establish a reliable and unbiased gold standard for method comparison and evaluation.     

Gene-environment interactions differentially affect mouse strain behavioral parameters

Systematic phenotyping of mouse strains and mutants generated through genome-wide mutagenesis programs promises to deliver a wealth of functional genetic information. To this end, the appropriation of a standard series of phenotyping protocols is desirable to produce data sets that are consistent within and across laboratories and across time. Standard phenotyping protocols such as EMPReSS (European Mouse Phenotyping Resource for Standardised Screens) provide a series of protocols aimed at phenotyping multiple body systems that could realistically be adopted and/or reproduced in any laboratory. This includes a series of neurologic and behavioral screens, bearing in mind that this class of phenotype is well represented in targeted mutants and mutagenesis screens. Having cross-validated screening batteries in a number of laboratories and in a number of commonly used inbred strains, our group was interested in establishing whether subtle changes in cage environment could affect behavioral test outcome. Aside from unavoidable quantitative differences in test outcome, we identified significant and distinct genotype-environment-test interactions. For example, specific strain order in open-field center entries and total distance traveled can be reversed depending on the form of enrichment used, while prepulse inhibition of the acoustic startle response is, even quantitatively, unaffected by the enrichment condition. Our findings argue that unless systematically recorded, behavioral studies conducted under subtle variations in cage environment may lead to data misinterpretation, although this could be limited to particular behaviors. Further investigations into the extent and limits of genetic and environmental variables are critical for the realization of both behavioral and functional genomics endpoints.