The future of laboratory medicine - A 2014 perspective.

Predicting the future is a difficult task. Not surprisingly, there are many examples and assumptions that have proved to be wrong. This review surveys the many predictions, beginning in 1887, about the future of laboratory medicine and its sub-specialties such as clinical chemistry and molecular pathology. It provides a commentary on the accuracy of the predictions and offers opinions on emerging technologies, economic factors and social developments that may play a role in shaping the future of laboratory medicine

Experimental and computational applications of microarray technology for malaria eradication in Africa

Various mutation assisted drug resistance evolved in Plasmodium falciparum strains and insecticide resistance to female Anopheles mosquito account for major biomedical catastrophes standing against all efforts to eradicate malaria in Sub-Saharan Africa. Malaria is endemic in more than 100 countries and by far the most costly disease in terms of human health causing major losses among many African nations including Nigeria. The fight against malaria is failing and DNA microarray analysis need to keep up the pace in order to unravel the evolving parasite’s gene expression profile which is a pointer to monitoring the genes involved in malaria’s infective metabolic pathway. Huge data is generated and biologists have the challenge of extracting useful information from volumes of microarray data. Expression levels for tens of thousands of genes can be simultaneously measured in a single hybridization experiment and are collectively called a “gene expression profile”. Gene expression profiles can also be used in studying various state of malaria development in which expression profiles of different disease states at different time points are collected and compared to each other to establish a classifying scheme for purposes such as diagnosis and treatments with adequate drugs. This paper examines microarray technology and its application as supported by appropriate software tools from experimental set-up to the level of data analysis. An assessment of the level of microarray technology in Africa, its availability and techniques required for malaria eradication and effective healthcare in Nigeria and Africa in general were also underscored

Ten years of the horse reference genome: insights into equine biology, domestication and population dynamics in the post-genome era.

The horse reference genome from the Thoroughbred mare Twilight has been available for a decade and, together with advances in genomics technologies, has led to unparalleled developments in equine genomics. At the core of this progress is the continuing improvement of the quality, contiguity and completeness of the reference genome, and its functional annotation. Recent achievements include the release of the next version of the reference genome (EquCab3.0) and generation of a reference sequence for the Y chromosome. Horse satellite-free centromeres provide unique models for mammalian centromere research. Despite extremely low genetic diversity of the Y chromosome, it has been possible to trace patrilines of breeds and pedigrees and show that Y variation was lost in the past approximately 2300 years owing to selective breeding. The high-quality reference genome has led to the development of three different SNP arrays and WGSs of almost 2000 modern individual horses. The collection of WGS of hundreds of ancient horses is unique and not available for any other domestic species. These tools and resources have led to global population studies dissecting the natural history of the species and genetic makeup and ancestry of modern breeds. Most importantly, the available tools and resources, together with the discovery of functional elements, are dissecting molecular causes of a growing number of Mendelian and complex traits. The improved understanding of molecular underpinnings of various traits continues to benefit the health and performance of the horse whereas also serving as a model for complex disease across species

Automated SNP genotype clustering algorithm to improve data completeness in high-throughput SNP genotyping datasets from custom arrays

High-throughput SNP genotyping platforms use automated genotype calling algorithms to assign genotypes. While these algorithms work efficiently for individual platforms, they are not compatible with other platforms, and have individual biases that result in missed genotype calls. Here we present data on the use of a second complementary SNP genotype clustering algorithm. The algorithm was originally designed for individual fluorescent SNP genotyping assays, and has been optimized to permit the clustering of large datasets generated from custom-designed Affymetrix SNP panels. In an analysis of data from a 3K array genotyped on 1,560 samples, the additional analysis increased the overall number of genotypes by over 45,000, significantly improving the completeness of the experimental data. This analysis suggests that the use of multiple genotype calling algorithms may be advisable in high-throughput SNP genotyping experiments. The software is written in Perl and is available from the corresponding author

Expression profiles of genes regulating dairy cow fertility: recent findings, ongoing activities and future possibilities

Subfertility has negative effects for dairy farm profitability, animal welfare and sustainability of animal production. Increasing herd sizes and economic pressures restrict the amount of time that farmers can spend on counteractive management Genetic improvement will become increasingly important to restore reproductive performance. Complementary to traditional breeding value estimation procedures, genomic selection based on genome-wide information will become more widely applied. Functional genomics, including transcriptomics (gene expression profiling), produces the information to understand the consequences of selection as it helps to unravel physiological mechanisms underlying female fertility traits. Insight into the latter is needed to develop new effective management strategies to combat subfertility. Here, the importance of functional genomics for dairy cow reproduction so far and in the near future is evaluated. Recent gene profiling studies in the field of dairy cow fertility are reviewed and new data are presented on genes that are expressed in the brains of dairy cows and that are involved in dairy cow oestrus (behaviour). Fast-developing new research areas in the field of functional genomics, such as epigenetics, RNA interference, variable copy numbers and nutrigenomics are discussed including their promising future value for dairy cow fertility

Sequencing the Major Mycosphaerella Pathogens of Wheat and Banana

Mycosphaerella is one of the largest genera of plant-pathogenic fungi with more than 1,000 named species, many of which are important pathogens causing leaf spotting diseases in a wide variety of crops including cereals, citrus, banana, eucalypts, soft fruits and horticultural crops. A few species of Mycosphaerella cause disease in humans and other vertebrates. An international project was initiated to sequence the genomes of M. graminicola and M. fijiensis, two of the most economically important pathogens of wheat and banana, respectively, along with 40,000 ESTs from M. fijiensis and the related maize pathogen Cercospora zeae-maydis. The 9x M. graminicola genome size is 39.8 Mb with chromosome sizes from 548 kb to 6 Mb and a complete circular mitochondrial genome of 43,947 bp. Our data indicate that M. graminicola has both the largest chromosome number and the smallest chromosome sizes recorded among filamentous ascomycetes. The Mycosphaerella Genomics Consortium, which was established in 2003, decided to use M. graminicola as the model to develop more genetic and genomic research on M. fijiensis. Since 2003, M. fijiensis EST sequencing has resulted in more than 30,000 ESTs, and the genome sequencing was recently finished at 7.8x. The genome size of M. fijiensis is 80% larger than that of M. graminicola. The completed mitochondrial sequence is more then twice as large, and the estimated nuclear genome size is approximately 72 Mb. The extension of the genome size of M. fijiensis seems to be mostly due to additional repeated sequences. The status of Mycosphaerella sequencing will have a significant effect on future studies aimed at the control of black leaf streak disease. The current status of both sequencing projects and other initiatives to exploit this information and to put it into a multidisciplinary approach focusing on sustainable management of the disease will be discusse

Whole-transcriptome, high-throughput RNA sequence analysis of the bovine macrophage response to Mycobacterium bovis infection in vitro

BACKGROUND: Mycobacterium bovis, the causative agent of bovine tuberculosis, is an intracellular pathogen that can persist inside host macrophages during infection via a diverse range of mechanisms that subvert the host immune response. In the current study, we have analysed and compared the transcriptomes of M. bovis-infected monocyte-derived macrophages (MDM) purified from six Holstein-Friesian females with the transcriptomes of non-infected control MDM from the same animals over a 24 h period using strand-specific RNA sequencing (RNA-seq). In addition, we compare gene expression profiles generated using RNA-seq with those previously generated by us using the high-density Affymetrix® GeneChip® Bovine Genome Array platform from the same MDM-extracted RNA. RESULTS: A mean of 7.2 million reads from each MDM sample mapped uniquely and unambiguously to single Bos taurus reference genome locations. Analysis of these mapped reads showed 2,584 genes (1,392 upregulated; 1,192 downregulated) and 757 putative natural antisense transcripts (558 upregulated; 119 downregulated) that were differentially expressed based on sense and antisense strand data, respectively (adjusted P-value ≤ 0.05). Of the differentially expressed genes, 694 were common to both the sense and antisense data sets, with the direction of expression (i.e. up- or downregulation) positively correlated for 693 genes and negatively correlated for the remaining gene. Gene ontology analysis of the differentially expressed genes revealed an enrichment of immune, apoptotic and cell signalling genes. Notably, the number of differentially expressed genes identified from RNA-seq sense strand analysis was greater than the number of differentially expressed genes detected from microarray analysis (2,584 genes versus 2,015 genes). Furthermore, our data reveal a greater dynamic range in the detection and quantification of gene transcripts for RNA-seq compared to microarray technology. CONCLUSIONS: This study highlights the value of RNA-seq in identifying novel immunomodulatory mechanisms that underlie host-mycobacterial pathogen interactions during infection, including possible complex post-transcriptional regulation of host gene expression involving antisense RNA

From access and integration to mining of secure genomic data sets across the grid

The UK Department of Trade and Industry (DTI) funded BRIDGES project (Biomedical Research Informatics Delivered by Grid Enabled Services) has developed a Grid infrastructure to support cardiovascular research. This includes the provision of a compute Grid and a data Grid infrastructure with security at its heart. In this paper we focus on the BRIDGES data Grid. A primary aim of the BRIDGES data Grid is to help control the complexity in access to and integration of a myriad of genomic data sets through simple Grid based tools. We outline these tools, how they are delivered to the end user scientists. We also describe how these tools are to be extended in the BBSRC funded Grid Enabled Microarray Expression Profile Search (GEMEPS) to support a richer vocabulary of search capabilities to support mining of microarray data sets. As with BRIDGES, fine grain Grid security underpins GEMEPS