The Human Genome Project: its relevance to ocular disease

This article describes the history of the Human Genome Project, how the human genome was sequenced, and analyses the likely impact which the results will have on the diagnosis, scientific understanding and, ultimately, treatment of ocular disease in the future.

1997 Delegates to the Second International Strategy Meeting on Human Genome Sequencing in Bermuda from Gert-Jan van Ommen

Photographs from the February 1997 Bermuda meeting. Courtesy of Gert-Jan van Ommen.

Beyond the human genome: microbes, metaphors and what it means to be human in an interconnected post-genomic world

Four years after the completion of the Human Genome Project, the US National Institutes for Health launched the Human Microbiome Project on 19 December 2007. Using metaphor analysis, this article investigates reporting in English-language newspapers on advances in microbiomics from 2003 onwards, when the word “microbiome” was first used. This research was said to open up a “new frontier” and was conceived as a “second human genome project”, this time focusing on the genomes of microbes that inhabit and populate humans rather than focusing on the human genome itself. The language used by scientists and by the journalists who reported on their research employed a type of metaphorical framing that was very different from the hyperbole surrounding the decipherment of the “book of life”. Whereas during the HGP genomic successes had been mainly framed as being based on a unidirectional process of reading off information from a passive genetic or genomic entity, the language employed to discuss advances in microbiomics frames genes, genomes and life in much more active and dynamic ways.

Conservation of synteny between the genome of the pufferfish (Fugu rubripes) and the region on human chromosome 14 (14q24.3) associated with familial Alzheimer disease (AD3 locus)

The genome of the pufferfish (Fugu rubripes) (400 Mb) is approximately 7.5 times smaller than the human genome, but it has a similar gene repertoire to that of man. If regions of the two genomes exhibited conservation of gene order (i.e., were syntenic), it should be possible to reduce dramatically the effort required for identification of candidate genes in human disease loci by sequencing syntenic regions of the compact Fugu genome. We have demonstrated that three genes (dihydrolipoamide succinyltransferase, S31iii125, and S20i15), which are linked to FOS in the familial Alzheimer disease focus (AD3) on human chromosome 14, have homologues in the Fugu genome adjacent to Fugu cFOS. The relative gene order of cFOS, S31iii125, and S20i15 was the same in both genomes, but in Fugu these three genes lay within a 12.4-kb region, compared to >600 kb in the human AD3 locus. These results demonstrate the conservation of synteny between the genomes of Fugu and man and highlight the utility of this approach for sequence-based identification of genes in human disease loci.

Multiple evolutionary rate classes in animal genome evolution

The proportion of functional sequence in the human genome is currently a subject of debate. The most widely accepted figure is that approximately 5% is under purifying selection. In Drosophila, estimates are an order of magnitude higher, though this corresponds to a similar quantity of sequence. These estimates depend on the difference between the distribution of genomewide evolutionary rates and that observed in a subset of sequences presumed to be neutrally evolving. Motivated by the widening gap between these estimates and experimental evidence of genome function, especially in mammals, we developed a sensitive technique for evaluating such distributions and found that they are much more complex than previously apparent. We found strong evidence for at least nine well-resolved evolutionary rate classes in an alignment of four Drosophila species and at least seven classes in an alignment of four mammals, including human. We also identified at least three rate classes in human ancestral repeats. By positing that the largest of these ancestral repeat classes is neutrally evolving, we estimate that the proportion of nonneutrally evolving sequence is 30% of human ancestral repeats and 45% of the aligned portion of the genome. However, we also question whether any of the classes represent neutrally evolving sequences and argue that a plausible alternative is that they reflect variable structure-function constraints operating throughout the genomes of complex organisms.

The human tissue kallikrein and kallikrein-related peptidase family

The human kallikrein-related peptidases are a subgroup of trypsin and chymotrypsin-like serine peptidases that are characterized by their homology to tissue kallikrein or kallikrein 1 (KLK1) encoded by the KLK1 gene (reviewed in[1-4]). The human KLK locus spans an approximately 320 kb region on chromosome 19q13.3-13.4 and contains fifteen genes encoding KLK1 and fourteen other kallikrein-related peptidases, KLK2-KLK15, which have been named contiguously in the locus in the order of their discovery [5-8] (Figure 606.1). It is the largest contiguous cluster of serine protease encoding genes in the human genome which has evolved from gene duplication of KLK1 and then subsequent reduplication of the newly evolved KLK genes [2]. The high conservation noted for KLK1-KLK3 (62-77%) reflects the proposed duplication of the KLK1 gene that produced the KLK2 gene which further generated the KLK3 gene. In contrast, the newer KLK4-KLK15 proteases share much less similarity, from 24-66%, although strong homology between KLK4 and KLK5, KLK9 and KLK11, and KLK10 and KLK12 suggests these genes are duplications of each other [2]...

Development of an eight gene expression profile implicating human breast tumours of all grade

The goal of improving systemic treatment of breast cancers is to evolve from treating every patient with non-specific cytotoxic chemotherapy/hormonal therapy, to a more individually-tailored direct treatment. Although anatomic staging and histological grade are important prognostic factors, they often fail to predict the clinical course of this disease. This study aimed to develop a gene expression profile associated with breast cancers of differing grades. We extracted mRNA from FFPE archival breast IDC tissue samples (Grades I–III), including benign tumours. Affymetrix GeneChip� Human Genome U133 Plus 2.0 Arrays were used to determine gene expression profiles and validated by Q-PCR. IHC was used to detect the AXIN2 protein in all tissues. From the array data, an independent group t-test revealed that 178 genes were significantly (P B 0.01) differentially expressed between three grades of malignant breast tumours when compared to benign tissues. From these results, eight genes were significantly differentially expressed in more than one comparison group and are involved in processes implicated in breast cancer development and/or progression. The two most implicated candidates genes were CLD10 and ESPTI1 as their gene expression profile from the microarray analysis was replicated in Q-PCR analyses of the original tumour samples as well as in an extended population. The IHC revealed a significant association between AXIN2 protein expression and ER status. It is readily acknowledged and established that significant differences exist in gene expression between different cancer grades. Expansion of this approach may lead to an improved ability to discriminate between cancer grade and other pathological factors.

Semaphorin–plexin signalling genes associated with human breast tumourigenesis

Introduction Gene expression profiling has enabled us to demonstrate the heterogeneity of breast cancers. The potential of a tumour to grow and metastasise is partly dependant on its ability to initiate angiogenesis or growth and remodelling of new blood vessels, usually from a pre-existing vascular network, to ensure delivery of oxygen, nutrients, and growth factors to rapidly dividing transformed cells along with access to the systemic circulation. Cell–cell signalling of semaphorin ligands through interaction with their plexin receptors is important for the homeostasis and morphogenesis of many tissues and has been widely studied for a role in neural connectivity, cancer, cell migration and immune responses. This study investigated the role of four semaphorin/plexin signalling genes in human breast cancers in vivo and in vitro. Materials and methods mRNA was extracted from formalin fixed paraffin embedded archival breast invasive ductal carcinoma tissue samples of progressive grades (grades I–III) and compared to tissue from benign tumours. Gene expression profiles were determined by microarray using the Affymetrix GeneChip® Human Genome U133 Plus 2.0 Arrays and validated by Q-PCR using a Corbett RotorGene 6000. Following validation, the gene expression profile of the identified targets was correlated with those of the human breast cancer cell lines MCF-7 and MDA-MD-231. Results The array data revealed that 888 genes were found to be significantly (p ≤ 0.05) differentially expressed between grades I and II tumours and 563 genes between grade III and benign tumours. From these genes, we identified four genes involved in semaphorin–plexin signalling including SEMA4D which has previously been identified as being involved in increased angiogenesis in breast cancers, and three other genes, SEMA4F, PLXNA2 and PLXNA3, which in the literature were associated with tumourigenesis, but not directly in breast tumourigenesis. The microarray analysis revealed that SEMA4D was significantly (P = 0.0347) down-regulated in the grade III tumours compared to benign tumours; SEMA4F, was significantly (P = 0.0159) down-regulated between grades I and II tumours; PLXNA2 was significantly (P = 0.036) down-regulated between grade III and benign tumours and PLXNA3 significantly (P = 0.042) up-regulated between grades I and II tumours. Gene expression of SEMA4D was validated using Q-PCR, demonstrating the same expression profile in both data sets. When the sample set was increased to incorporate more cases, SEMA4D continued to follow the same expression profile, including statistical significance for the differences observed and small standard deviations. In vitro the same pattern was present where expression for SEMA4D was significantly higher in MDA-MB-231 cells when compared to MCF-7 cells. The expression of SEMA4F, PLXNA2 and PLXNA3 could not be validated using Q-PCR, however in vitro analysis of these three genes revealed that both SEMA4F and PLXNA3 followed the microarray trend in expression, although they did not reach significance. In contrast, PLXNA2 demonstrated statistical significance and was in concordance with the literature. Discussion We, and others, have proposed SEMA4D to be a gene with a potentially protective effect in benign tumours that contributes to tumour growth and metastatic suppression. Previous data supports a role for SEMA4F as a tumour suppressor in the peripheral nervous system but our data seems to indicate that the gene is involved in tumour progression in breast cancer. Our in vitro analysis of PLXNA2 revealed that the gene has higher expression in more aggressive breast cancer cell types. Finally, our in vitro analysis on PLXNA3 also suggest that this gene may have some form of growth suppressive role in breast cancer, in addition to a similar role for the gene previously reported in ovarian cancer. From the data obtained in this study, SEMA4D may have a role in more aggressive and potentially metastatic breast tumours. Conclusions Semaphorins and their receptors, the plexins, have been implicated in numerous aspects of neural development, however their expression in many other epithelial tissues suggests that the semaphorin–plexin signalling system also contributes to blood vessel growth and development. These findings warrant further investigation of the role of semaphorins and plexins and their role in normal and tumour-induced angiogenesis in vivo and in vitro. This may represent a new front of attack in anti-angiogenic therapies of breast and other cancers.

Prospects for whole genome linkage disequilibrium mapping in domestic dog breeds

Linkage disequilibrium (LD) mapping is commonly used as a fine mapping tool in human genome mapping and has been used with some success for initial disease gene isolation in certain isolated in-bred human populations. An understanding of the population history of domestic dog breeds suggests that LD mapping could be routinely utilized in this species for initial genome-wide scans. Such an approach offers significant advantages over traditional linkage analysis. Here, we demonstrate, using canine copper toxicosis in the Bedlington terrier as the model, that LD mapping could be reasonably expected to be a useful strategy in low-resolution, genome-wide scans in pure-bred dogs. Significant LD was demonstrated over distances up to 33.3 cM. It is very unlikely, for a number of reasons discussed, that this result could be extrapolated to the rest of the genome. It is, however, consistent with the expectation given the population structure of canine breeds and, in this breed at least, with the hypothesis that it may be possible to utilize LD in a genome-wide scan. In this study, LD mapping confirmed the location of the copper toxicosis in Bedlington terrier gene (CT-BT) and was able to do so in a population that was refractory to traditional linkage analysis.

Scanning the genome for essential hypertension loci

1. Essential hypertension occurs in people with an underlying genetic predisposition who subject themselves to adverse environmental influences. The number of genes involved is unknown, as is the extent to which each contributes to final blood pressure and the severity of the disease. 2. In the past, studies of potential candidate genes have been performed by association (case-control) analysis of unrelated individuals or linkage (pedigree or sibpair) analysis of families. These studies have resulted in several positive findings but, as one may expect, also an enormous number of negative results. 3. In order to uncover the major genetic loci for essential hypertension, it is proposed that scanning the genome systematically in 100- 200 affected sibships should prove successful. 4. This involves genotyping sets of hypertensive sibships to determine their complement of several hundred microsatellite polymorphisms. Those that are highly informative, by having a high heterozygosity, are most suitable. Also, the markers need to be spaced sufficiently evenly across the genome so as to ensure adequate coverage. 5. Tests are performed to determine increased segregation of alleles of each marker with hypertension. The analytical tools involve specialized statistical programs that can detect such differences. Non- parametric multipoint analysis is an appropriate approach. 6. In this way, loci for essential hypertension are beginning to emerge.

Genetic susceptibility to complex traits : moving towards informed analysis of whole-genome screens

Susceptibility to complex traits, by definition, involves aetiological polymorphisms at multiple genetic loci combined with variable contributions by environmental factors. However, the approaches taken to identifying genetic loci implicated in susceptibility to complex traits frequently overlooks the compounding contribution of multiple loci in favour of highlighting a single gene solely responsible for predisposition. It is only in a small minority of cases that this has resulted in clear disease heritability associated with polymorphisms in a single gene. More often, this approach has led to an accumulation of single-gene associations with minor contributions to disease susceptibility. As the genomic era advances and genome-wide screens become higher in resolution and throughput, the need for simultaneous consideration of multiple loci is becoming more important. With special reference to non-Hodgkin’s lymphoma (NHL), this chapter will overview the current progress made in elucidating genetic polymorphisms associated with disease susceptibility. We also present novel data from a high-resolution single nucleotide polymorphism (SNP) microarray screen for susceptibility loci that are involved in NHL. Using an ‘informed approach’, the findings are highlighted within the context of cellular pathways, and provide insight and new ideas for methods of analysis for genome-wide screens for susceptibility.

Computational analysis of epigenetic information in human DNA sequences

Over the last few years, investigations of human epigenetic profiles have identified key elements of change to be Histone Modifications, stable and heritable DNA methylation and Chromatin remodeling. These factors determine gene expression levels and characterise conditions leading to disease. In order to extract information embedded in long DNA sequences, data mining and pattern recognition tools are widely used, but efforts have been limited to date with respect to analyzing epigenetic changes, and their role as catalysts in disease onset. Useful insight, however, can be gained by investigation of associated dinucleotide distributions. The focus of this paper is to explore specific dinucleotides frequencies across defined regions within the human genome, and to identify new patterns between epigenetic mechanisms and DNA content. Signal processing methods, including Fourier and Wavelet Transformations, are employed and principal results are reported.

Genetic clustering on the hippocampal surface for genome-wide association studies

Imaging genetics aims to discover how variants in the human genome influence brain measures derived from images. Genome-wide association scans (GWAS) can screen the genome for common differences in our DNA that relate to brain measures. In small samples, GWAS has low power as individual gene effects are weak and one must also correct for multiple comparisons across the genome and the image. Here we extend recent work on genetic clustering of images, to analyze surface-based models of anatomy using GWAS. We performed spherical harmonic analysis of hippocampal surfaces, automatically extracted from brain MRI scans of 1254 subjects. We clustered hippocampal surface regions with common genetic influences by examining genetic correlations (r(g)) between the normalized deformation values at all pairs of surface points. Using genetic correlations to cluster surface measures, we were able to boost effect sizes for genetic associations, compared to clustering with traditional phenotypic correlations using Pearson's r.

Bivariate genome-wide association study of genetically correlated neuroimaging phenotypes from DTI and MRI through a seemingly unrelated regression model

Large multisite efforts (e.g., the ENIGMA Consortium), have shown that neuroimaging traits including tract integrity (from DTI fractional anisotropy, FA) and subcortical volumes (from T1-weighted scans) are highly heritable and promising phenotypes for discovering genetic variants associated with brain structure. However, genetic correlations (rg) among measures from these different modalities for mapping the human genome to the brain remain unknown. Discovering these correlations can help map genetic and neuroanatomical pathways implicated in development and inherited risk for disease. We use structural equation models and a twin design to find rg between pairs of phenotypes extracted from DTI and MRI scans. When controlling for intracranial volume, the caudate as well as related measures from the limbic system - hippocampal volume - showed high rg with the cingulum FA. Using an unrelated sample and a Seemingly Unrelated Regression model for bivariate analysis of this connection, we show that a multivariate GWAS approach may be more promising for genetic discovery than a univariate approach applied to each trait separately.