Huntington F. Willard

Bio: Huntington F. Willard is an academic researcher from Duke University. The author has contributed to research in topics: X chromosome & X-inactivation. The author has an hindex of 31, co-authored 53 publications receiving 15116 citations. Previous affiliations of Huntington F. Willard include University of Massachusetts Amherst & University Hospitals of Cleveland.

X-inactivation profile reveals extensive variability in X-linked gene expression in females

Abstract: In female mammals, most genes on one X chromosome are silenced as a result of X-chromosome inactivation. However, some genes escape X-inactivation and are expressed from both the active and inactive X chromosome. Such genes are potential contributors to sexually dimorphic traits, to phenotypic variability among females heterozygous for X-linked conditions, and to clinical abnormalities in patients with abnormal X chromosomes. Here, we present a comprehensive X-inactivation profile of the human X chromosome, representing an estimated 95% of assayable genes in fibroblast-based test systems. In total, about 15% of X-linked genes escape inactivation to some degree, and the proportion of genes escaping inactivation differs dramatically between different regions of the X chromosome, reflecting the evolutionary history of the sex chromosomes. An additional 10% of X-linked genes show variable patterns of inactivation and are expressed to different extents from some inactive X chromosomes. This suggests a remarkable and previously unsuspected degree of expression heterogeneity among females.

A gene from the region of the human X inactivation centre is expressed exclusively from the inactive X chromosome

Abstract: X-chromosome inactivation results in the cis-limited dosage compensation of genes on one of the pair of X chromosomes in mammalian females. Although most X-linked genes are believed to be subject to inactivation, several are known to be expressed from both active and inactive X chromosomes. Here we describe an X-linked gene with a novel expression pattern--transcripts are detected only from the inactive X chromosome (Xi) and not from the active X chromosome (Xa). This gene, called XIST (for Xi-specific transcripts), is a candidate for a gene either involved in or uniquely influenced by the process of X inactivation.

The DNA sequence of the human X chromosome

Abstract: The human X chromosome has a unique biology that was shaped by its evolution as the sex chromosome shared by males and females. We have determined 99.3% of the euchromatic sequence of the X chromosome. Our analysis illustrates the autosomal origin of the mammalian sex chromosomes, the stepwise process that led to the progressive loss of recombination between X and Y, and the extent of subsequent degradation of the Y chromosome. LINE1 repeat elements cover one-third of the X chromosome, with a distribution that is consistent with their proposed role as way stations in the process of X-chromosome inactivation. We found 1,098 genes in the sequence, of which 99 encode proteins expressed in testis and in various tumour types. A disproportionately high number of mendelian diseases are documented for the X chromosome. Of this number, 168 have been explained by mutations in 113 X-linked genes, which in many cases were characterized with the aid of the DNA sequence.

Cloning of human androgen receptor complementary DNA and localization to the X chromosome.

Abstract: The androgen receptor (AR) mediates the actions of male sex steroids. Human AR genomic DNA was cloned from a flow-sorted human X chromosome library by using a consensus nucleotide sequence from the DNA-binding domain of the family of nuclear receptors. The AR gene was localized on the human X chromosome between the centromere and q13. Cloned complementary DNA, selected with an AR-specific oligonucleotide probe, was expressed in monkey kidney (COS) cells and yielded a high-affinity androgen-binding protein with steroid-binding specificity corresponding to that of native AR. A predominant messenger RNA species of 9.6 kilobases was identified in human, rat, and mouse tissues known to contain AR and was undetectable in tissues lacking AR androgen-binding activity, including kidney and liver from androgen-insensitive mice. The deduced amino acid sequence of AR within the DNA-binding domain has highest sequence identity with the progesterone receptor.

Initial sequencing and analysis of the human genome.

Abstract: The human genome holds an extraordinary trove of information about human development, physiology, medicine and evolution. Here we report the results of an international collaboration to produce and make freely available a draft sequence of the human genome. We also present an initial analysis of the data, describing some of the insights that can be gleaned from the sequence.

Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls

Abstract: There is increasing evidence that genome-wide association ( GWA) studies represent a powerful approach to the identification of genes involved in common human diseases. We describe a joint GWA study ( using the Affymetrix GeneChip 500K Mapping Array Set) undertaken in the British population, which has examined similar to 2,000 individuals for each of 7 major diseases and a shared set of similar to 3,000 controls. Case-control comparisons identified 24 independent association signals at P < 5 X 10(-7): 1 in bipolar disorder, 1 in coronary artery disease, 9 in Crohn's disease, 3 in rheumatoid arthritis, 7 in type 1 diabetes and 3 in type 2 diabetes. On the basis of prior findings and replication studies thus-far completed, almost all of these signals reflect genuine susceptibility effects. We observed association at many previously identified loci, and found compelling evidence that some loci confer risk for more than one of the diseases studied. Across all diseases, we identified a large number of further signals ( including 58 loci with single-point P values between 10(-5) and 5 X 10(-7)) likely to yield additional susceptibility loci. The importance of appropriately large samples was confirmed by the modest effect sizes observed at most loci identified. This study thus represents a thorough validation of the GWA approach. It has also demonstrated that careful use of a shared control group represents a safe and effective approach to GWA analyses of multiple disease phenotypes; has generated a genome-wide genotype database for future studies of common diseases in the British population; and shown that, provided individuals with non-European ancestry are excluded, the extent of population stratification in the British population is generally modest. Our findings offer new avenues for exploring the pathophysiology of these important disorders. We anticipate that our data, results and software, which will be widely available to other investigators, will provide a powerful resource for human genetics research.

Inositol trisphosphate and calcium signalling

Abstract: Inositol trisphosphate is a second messenger that controls many cellular processes by generating internal calcium signals. It operates through receptors whose molecular and physiological properties closely resemble the calcium-mobilizing ryanodine receptors of muscle. This family of intracellular calcium channels displays the regenerative process of calcium-induced calcium release responsible for the complex spatiotemporal patterns of calcium waves and oscillations. Such a dynamic signalling pathway controls many cellular processes, including fertilization, cell growth, transformation, secretion, smooth muscle contraction, sensory perception and neuronal signalling.

Genetic alterations during colorectal-tumor development.

Abstract: Because most colorectal carcinomas appear to arise from adenomas, studies of different stages of colorectal neoplasia may shed light on the genetic alterations involved in tumor progression. We looked for four genetic alterations (ras-gene mutations and allelic deletions of chromosomes 5, 17, and 18) in 172 colorectal-tumor specimens representing various stages of neoplastic development. The specimens consisted of 40 predominantly early-stage adenomas from 7 patients with familial adenomatous polyposis, 40 adenomas (19 without associated foci of carcinoma and 21 with such foci) from 33 patients without familial polyposis, and 92 carcinomas resected from 89 patients. We found that ras-gene mutations occurred in 58 percent of adenomas larger than 1 cm and in 47 percent of carcinomas. However, ras mutations were found in only 9 percent of adenomas under 1 cm in size. Sequences on chromosome 5 that are linked to the gene for familial adenomatous polyposis were not lost in adenomas from the patients with polyposis but were lost in 29 to 35 percent of adenomas and carcinomas, respectively, from other patients. A specific region of chromosome 18 was deleted frequently in carcinomas (73 percent) and in advanced adenomas (47 percent) but only occasionally in earlier-stage adenomas (11 to 13 percent). Chromosome 17p sequences were usually lost only in carcinomas (75 percent). The four molecular alterations accumulated in a fashion that paralleled the clinical progression of tumors. These results are consistent with a model of colorectal tumorigenesis in which the steps required for the development of cancer often involve the mutational activation of an oncogene coupled with the loss of several genes that normally suppress tumorigenesis.

GSVA: gene set variation analysis for microarray and RNA-seq data.

Abstract: Gene set enrichment (GSE) analysis is a popular framework for condensing information from gene expression profiles into a pathway or signature summary. The strengths of this approach over single gene analysis include noise and dimension reduction, as well as greater biological interpretability. As molecular profiling experiments move beyond simple case-control studies, robust and flexible GSE methodologies are needed that can model pathway activity within highly heterogeneous data sets. To address this challenge, we introduce Gene Set Variation Analysis (GSVA), a GSE method that estimates variation of pathway activity over a sample population in an unsupervised manner. We demonstrate the robustness of GSVA in a comparison with current state of the art sample-wise enrichment methods. Further, we provide examples of its utility in differential pathway activity and survival analysis. Lastly, we show how GSVA works analogously with data from both microarray and RNA-seq experiments. GSVA provides increased power to detect subtle pathway activity changes over a sample population in comparison to corresponding methods. While GSE methods are generally regarded as end points of a bioinformatic analysis, GSVA constitutes a starting point to build pathway-centric models of biology. Moreover, GSVA contributes to the current need of GSE methods for RNA-seq data. GSVA is an open source software package for R which forms part of the Bioconductor project and can be downloaded at http://www.bioconductor.org .