Sparse Statistical Modelling in Gene Expression Genomics

Author(s):  
Joseph Lucas ◽  
Carlos Carvalho ◽  
Quanli Wang ◽  
Andrea Bild ◽  
Joseph R. Nevins ◽  
...  
eLife ◽  
2016 ◽  
Vol 5 ◽  
Author(s):  
Karen Featherstone ◽  
Kirsty Hey ◽  
Hiroshi Momiji ◽  
Anne V McNamara ◽  
Amanda L Patist ◽  
...  

Transcription at individual genes in single cells is often pulsatile and stochastic. A key question emerges regarding how this behaviour contributes to tissue phenotype, but it has been a challenge to quantitatively analyse this in living cells over time, as opposed to studying snap-shots of gene expression state. We have used imaging of reporter gene expression to track transcription in living pituitary tissue. We integrated live-cell imaging data with statistical modelling for quantitative real-time estimation of the timing of switching between transcriptional states across a whole tissue. Multiple levels of transcription rate were identified, indicating that gene expression is not a simple binary ‘on-off’ process. Immature tissue displayed shorter durations of high-expressing states than the adult. In adult pituitary tissue, direct cell contacts involving gap junctions allowed local spatial coordination of prolactin gene expression. Our findings identify how heterogeneous transcriptional dynamics of single cells may contribute to overall tissue behaviour.


2015 ◽  
Vol 12 (103) ◽  
pp. 20141153 ◽  
Author(s):  
Yinyin Yuan

Lymphocytic infiltration is associated with a favourable prognosis and predicts response to chemotherapy in many cancer types, including the aggressive triple-negative breast cancer (TNBC). However, it is not well understood owing to the high levels of spatial heterogeneity within tumours, which is difficult to analyse by traditional pathological assessment. This paper describes an unbiased methodology to statistically model the spatial distribution of lymphocytes among tumour cells based on automated analysis of haematoxylin-and-eosin-stained whole-tumour section images, which is applied to two independent TNBC cohorts of 181 patients with matched microarray gene expression data. The novelty of the proposed methodology is the fusion of image analysis and statistical modelling for an integrative understanding of intratumour heterogeneity of lymphocytic infiltration. Using this methodology, a quantitative measure of intratumour lymphocyte ratio is developed and found to be significantly associated with disease-specific survival in both TNBC cohorts independent to standard clinical parameters. The proposed image-based measure compares favourably to a number of gene expression signatures of immune infiltration. In addition, heterogeneous immune infiltration at the morphological level is reflected at the molecular scale and correlated with increased expression of CTLA4 , the target of ipilimumab. Taken together, these results support the fusion of high-throughput image analysis and statistical modelling to offer reproducible and robust biomarkers for the objective identification of patients with poor prognosis and treatment options.


2020 ◽  
Author(s):  
Daniel Brugger ◽  
Martin Hanauer ◽  
Johanna Ortner ◽  
Wilhelm M. Windisch

AbstractThis study compared the relative mRNA expression of all mammal zinc (Zn) transporter genes in selected tissues of weaned piglets challenged with short-term subclinical Zn deficiency (SZD). The dietary model involved restrictive feeding (450 g/animal*day−1) of a high-phytate diet (9 g/kg) supplemented with varying amounts of zinc from ZnSO4*7H2O ranging from deficient to sufficient supply levels (total diet Zn: 28.1, 33.6, 38.8, 42.7, 47.5, 58.2, 67.8, 88.0 mg Zn/kg). Total RNA preparations comprised jejunal and colonic mucosa as well as hepatic and nephric tissue. Statistical modelling involved broken-line regression (P ≤ 0.05). ZIP10 and ZIP12 mRNAs were not detected in any tissue and ZnT3 mRNA was only identified in the kidney. All other genes were expressed in all tissues but only a few gene expression patterns allowed a significant (P < 0.0001) fitting of broken-line regression models, indicating homeostatic regulation under the present experimental conditions. Interestingly, these genes could be subcategorized by showing significant turnarounds in their response patterns, either at ~40 or ~60 mg Zn/kg diet (P < 0.0001). In conclusion, the present study showed clear differences in Zn transporter gene expression in response to SZD compared to the present literature on clinical models. We recognized that certain Zn transporter genes were regulated under the present experimental conditions by two distinct homeostatic networks. For the best of our knowledge, this represents the first comprehensive screening of Zn transporter gene expression in a highly translational model to human physiology.


Author(s):  
W. K. Jones ◽  
J. Robbins

Two myosin heavy chains (MyHC) are expressed in the mammalian heart and are differentially regulated during development. In the mouse, the α-MyHC is expressed constitutively in the atrium. At birth, the β-MyHC is downregulated and replaced by the α-MyHC, which is the sole cardiac MyHC isoform in the adult heart. We have employed transgenic and gene-targeting methodologies to study the regulation of cardiac MyHC gene expression and the functional and developmental consequences of altered α-MyHC expression in the mouse.We previously characterized an α-MyHC promoter capable of driving tissue-specific and developmentally correct expression of a CAT (chloramphenicol acetyltransferase) marker in the mouse. Tissue surveys detected a small amount of CAT activity in the lung (Fig. 1a). The results of in situ hybridization analyses indicated that the pattern of CAT transcript in the adult heart (Fig. 1b, top panel) is the same as that of α-MyHC (Fig. 1b, lower panel). The α-MyHC gene is expressed in a layer of cardiac muscle (pulmonary myocardium) associated with the pulmonary veins (Fig. 1c). These studies extend our understanding of α-MyHC expression and delimit a third cardiac compartment.


2020 ◽  
Vol 477 (16) ◽  
pp. 3091-3104 ◽  
Author(s):  
Luciana E. Giono ◽  
Alberto R. Kornblihtt

Gene expression is an intricately regulated process that is at the basis of cell differentiation, the maintenance of cell identity and the cellular responses to environmental changes. Alternative splicing, the process by which multiple functionally distinct transcripts are generated from a single gene, is one of the main mechanisms that contribute to expand the coding capacity of genomes and help explain the level of complexity achieved by higher organisms. Eukaryotic transcription is subject to multiple layers of regulation both intrinsic — such as promoter structure — and dynamic, allowing the cell to respond to internal and external signals. Similarly, alternative splicing choices are affected by all of these aspects, mainly through the regulation of transcription elongation, making it a regulatory knob on a par with the regulation of gene expression levels. This review aims to recapitulate some of the history and stepping-stones that led to the paradigms held today about transcription and splicing regulation, with major focus on transcription elongation and its effect on alternative splicing.


2013 ◽  
Vol 54 ◽  
pp. 79-90 ◽  
Author(s):  
Saba Valadkhan ◽  
Lalith S. Gunawardane

Eukaryotic cells contain small, highly abundant, nuclear-localized non-coding RNAs [snRNAs (small nuclear RNAs)] which play important roles in splicing of introns from primary genomic transcripts. Through a combination of RNA–RNA and RNA–protein interactions, two of the snRNPs, U1 and U2, recognize the splice sites and the branch site of introns. A complex remodelling of RNA–RNA and protein-based interactions follows, resulting in the assembly of catalytically competent spliceosomes, in which the snRNAs and their bound proteins play central roles. This process involves formation of extensive base-pairing interactions between U2 and U6, U6 and the 5′ splice site, and U5 and the exonic sequences immediately adjacent to the 5′ and 3′ splice sites. Thus RNA–RNA interactions involving U2, U5 and U6 help position the reacting groups of the first and second steps of splicing. In addition, U6 is also thought to participate in formation of the spliceosomal active site. Furthermore, emerging evidence suggests additional roles for snRNAs in regulation of various aspects of RNA biogenesis, from transcription to polyadenylation and RNA stability. These snRNP-mediated regulatory roles probably serve to ensure the co-ordination of the different processes involved in biogenesis of RNAs and point to the central importance of snRNAs in eukaryotic gene expression.


2006 ◽  
Vol 73 ◽  
pp. 85-96 ◽  
Author(s):  
Richard J. Reece ◽  
Laila Beynon ◽  
Stacey Holden ◽  
Amanda D. Hughes ◽  
Karine Rébora ◽  
...  

The recognition of changes in environmental conditions, and the ability to adapt to these changes, is essential for the viability of cells. There are numerous well characterized systems by which the presence or absence of an individual metabolite may be recognized by a cell. However, the recognition of a metabolite is just one step in a process that often results in changes in the expression of whole sets of genes required to respond to that metabolite. In higher eukaryotes, the signalling pathway between metabolite recognition and transcriptional control can be complex. Recent evidence from the relatively simple eukaryote yeast suggests that complex signalling pathways may be circumvented through the direct interaction between individual metabolites and regulators of RNA polymerase II-mediated transcription. Biochemical and structural analyses are beginning to unravel these elegant genetic control elements.


2002 ◽  
Vol 69 ◽  
pp. 135-142 ◽  
Author(s):  
Elena M. Comelli ◽  
Margarida Amado ◽  
Steven R. Head ◽  
James C. Paulson

The development of microarray technology offers the unprecedented possibility of studying the expression of thousands of genes in one experiment. Its exploitation in the glycobiology field will eventually allow the parallel investigation of the expression of many glycosyltransferases, which will ultimately lead to an understanding of the regulation of glycoconjugate synthesis. While numerous gene arrays are available on the market, e.g. the Affymetrix GeneChip® arrays, glycosyltransferases are not adequately represented, which makes comprehensive surveys of their gene expression difficult. This chapter describes the main issues related to the establishment of a custom glycogenes array.


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