scholarly journals CRISPRi-Seq for the Identification and Characterisation of Essential Mycobacterial Genes and Transcriptional Units

2018 ◽  
Author(s):  
Timothy J. de Wet ◽  
Irene Gobe ◽  
Musa M. Mhlanga ◽  
Digby F. Warner
Keyword(s):  
High Throughput ◽  
Large Scale ◽  
Essential Gene ◽  
Experimental Models ◽  
Bacterial Gene ◽  
Growth And Survival ◽  
Genome Wide ◽  
A Genome ◽  
Wide Scale ◽  
Transcriptional Units

AbstractHigh-throughput essentiality screens have enabled genome-wide assessments of the genetic requirements for growth and survival of a variety of bacteria in different experimental models. The reliance in many of these studies on transposon (Tn)-based gene inactivation has, however, limited the ability to probe essential gene function or design targeted screens. We interrogated the potential of targeted, large-scale, pooled CRISPR interference (CRISPRi)-based screens to extend conventional Tn approaches in mycobacteria through the capacity for positionally regulable gene repression. Here, we report the utility of the “CRISPRi-Seq” method for targeted, pooled essentiality screening, confirming strong overlap with Tn-Seq datasets. In addition, we exploit this high-throughput approach to provide insight into CRISPRi functionality. By interrogating polar effects and combining image-based phenotyping with CRISPRi-mediated depletion of selected essential genes, we demonstrate that CRISPRi-Seq can functionally validate Transcriptional Units within operons. Together, these observations suggest the utility of CRISPRi-Seq to provide insights into (myco)bacterial gene regulation and expression on a genome-wide scale.

Interrogating CD8+ T cell reactivity on a genome-wide scale

2019 ◽  
Vol 11 (506) ◽  
pp. eaaz0302
Author(s):  
Kamila Naxerova
Keyword(s):  
T Cell ◽  
Large Scale ◽  
Cd8 T Cell ◽  
Cell Reactivity ◽  
Human T Cell ◽  
Genome Wide ◽  
A Genome ◽  
T Cell Antigens ◽  
Wide Scale ◽  
T Cell Reactivity

A new method enables large-scale identification of human T cell antigens.

Cis-regulatory elements and human evolution

2014 ◽  
Author(s):  
Adam Siepel ◽  
Leonardo Arbiza
Keyword(s):  
Transcriptional Regulation ◽  
Human Evolution ◽  
Large Scale ◽  
Regulatory Elements ◽  
Data Sets ◽  
Regulatory Evolution ◽  
Genome Wide ◽  
A Genome ◽  
Wide Scale ◽  
Human Polymorphism

Modification of gene regulation has long been considered an important force in human evolution, particularly through changes to cis-regulatory elements (CREs) that function in transcriptional regulation. For decades, however, the study of cis-regulatory evolution was severely limited by the available data. New data sets describing the locations of CREs and genetic variation within and between species have now made it possible to study CRE evolution much more directly on a genome-wide scale. Here, we review recent research on the evolution of CREs in humans based on large-scale genomic data sets. We consider inferences based on primate divergence,human polymorphism, and combinations of divergence and polymorphism. We then consider "new frontiers" in this field stemming from recent research on transcriptional regulation.

scholarly journals Towards a Systems Approach in the Genetic Analysis of Archaea: Accelerating Mutant Construction and Phenotypic Analysis inHaloferax volcanii

Archaea ◽  
2010 ◽  
Vol 2010 ◽  
pp. 1-11 ◽  
Author(s):  
Ian K. Blaby ◽  
Gabriela Phillips ◽  
Crysten E. Blaby-Haas ◽  
Kevin S. Gulig ◽  
Basma El Yacoubi ◽  
...  
Keyword(s):  
High Throughput ◽  
Gene Deletion ◽  
Systems Approach ◽  
Essential Gene ◽  
Gene Knockout ◽  
Deletion Mutants ◽  
Mutant Library ◽  
Phenotypic Analysis ◽  
Genome Wide ◽  
A Genome

With the availability of a genome sequence and increasingly sophisticated genetic tools,Haloferax volcaniiis becoming a model for both Archaea and halophiles. In order forH. volcaniito reach a status equivalent toEscherichia coli, Bacillus subtilis, orSaccharomyces cerevisiae, a gene knockout collection needs to be constructed in order to identify the archaeal essential gene set and enable systematic phenotype screens. A streamlined gene-deletion protocol adapted for potential automation was implemented and used to generate 22H. volcaniideletion strains and identify several potentially essential genes. These gene deletion mutants, generated in this and previous studies, were then analyzed in a high-throughput fashion to measure growth rates in different media and temperature conditions. We conclude that these high-throughput methods are suitable for a rapid investigation of anH. volcaniimutant library and suggest that they should form the basis of a larger genome-wide experiment.

Whole human exome capture for high-throughput sequencing

Genome ◽  
2010 ◽  
Vol 53 (7) ◽  
pp. 568-574 ◽  
Author(s):  
Dae-Won Kim ◽  
Seong-Hyeuk Nam ◽  
Ryong Nam Kim ◽  
Sang-Haeng Choi ◽  
Hong-Seog Park
Keyword(s):  
High Throughput ◽  
High Throughput Sequencing ◽  
Exome Capture ◽  
Microarray Design ◽  
Genome Wide ◽  
Human Genes ◽  
Practical Usefulness ◽  
A Genome ◽  
Wide Scale ◽  
Total Base

We captured the whole human exome by hybridization using synthesized oligonucleotides, based on a high-density microarray design, and we sequenced those captured human exons using high-throughput sequencing on a Genome Sequencer FLX instrument. Of the uniquely mapped reads, 71% fell within target regions, and these corresponded to coverage of 94% of human genes, 87% of exons, and 70% of the total base-pair length of the CCDS set. Our study provides strong evidence for the practical usefulness of this method on a genome-wide scale, showing the resequenced whole human exome database with 501 microRNAs and 307 novel SNPs.

Computational methods for annotation of plant regulatory non-coding RNAs using RNA-seq

2020 ◽  
Author(s):  
A T Vivek ◽  
Shailesh Kumar
Keyword(s):  
Computational Methods ◽  
High Throughput ◽  
Rna Seq ◽  
Physiological Mechanisms ◽  
Software Packages ◽  
Genome Wide ◽  
A Genome ◽  
Wide Scale ◽  
Plant Transcriptome ◽  
Non Coding Rnas

Abstract Plant transcriptome encompasses numerous endogenous, regulatory non-coding RNAs (ncRNAs) that play a major biological role in regulating key physiological mechanisms. While studies have shown that ncRNAs are extremely diverse and ubiquitous, the functions of the vast majority of ncRNAs are still unknown. With ever-increasing ncRNAs under study, it is essential to identify, categorize and annotate these ncRNAs on a genome-wide scale. The use of high-throughput RNA sequencing (RNA-seq) technologies provides a broader picture of the non-coding component of transcriptome, enabling the comprehensive identification and annotation of all major ncRNAs across samples. However, the detection of known and emerging class of ncRNAs from RNA-seq data demands complex computational methods owing to their unique as well as similar characteristics. Here, we discuss major plant endogenous, regulatory ncRNAs in an RNA sample followed by computational strategies applied to discover each class of ncRNAs using RNA-seq. We also provide a collection of relevant software packages and databases to present a comprehensive bioinformatics toolbox for plant ncRNA researchers. We assume that the discussions in this review will provide a rationale for the discovery of all major categories of plant ncRNAs.

scholarly journals Functional Genomics–Linking Genotype with Phenotype on Genome-wide Scale

2019 ◽  
Vol 4 (01) ◽  
pp. 4-12
Author(s):  
Nida Tabassum Khan ◽  
Namra Jameel ◽  
Maham Jamil Khan
Keyword(s):  
Functional Genomics ◽  
High Throughput ◽  
Genomic Data ◽  
Genome Wide ◽  
A Genome ◽  
Genomic Studies ◽  
Wide Scale

Functional genomics manipulates genomic data to study genes and its expression on a genome wide scale involving high-throughput methods. The keyobjective of Functional genomics is to exploit the data acquired from transcriptomic and genomic studies to explain the functions and interfaces of a genome and its corresponding phenotype.

scholarly journals Technical Note: Efficient and accurate estimation of genotype odds ratios in biobank-based unbalanced case-control studies

2019 ◽  
Author(s):  
Rounak Dey ◽  
Seunggeun Lee
Keyword(s):  
Large Scale ◽  
Association Studies ◽  
Case Control ◽  
Accurate Estimation ◽  
Genome Wide Association Studies ◽  
Odds Ratios ◽  
Case Control Studies ◽  
Genome Wide ◽  
A Genome ◽  
Wide Scale

AbstractIn genome-wide association studies (GWASs), genotype log-odds ratios (LORs) quantify the effects of the variants on the binary phenotypes, and calculating the genotype LORs for all of the markers is required for several downstream analyses. Calculating genotype LORs at a genome-wide scale is computationally challenging, especially when analyzing large-scale biobank data, which involves performing thousands of GWASs phenome-wide. Since most of the binary phenotypes in biobank-based studies have unbalanced (case : control = 1 : 10) or often extremely unbalanced (case : control = 1 : 100) case-control ratios, the existing methods cannot provide a scalable and accurate way to estimate the genotype LORs. The traditional logistic regression provides biased LOR estimates in such situations. Although the Firth bias correction method can provide unbiased LOR estimates, it is not scalable for genome-wide or phenome-wide scale association analyses typically used in biobank-based studies, especially when the number of non-genetic covariates is large. On the other hand, the saddlepoint approximation-based test (fastSPA), which can provide accurate p values and is scalable to analyse large-scale biobank data, does not provide the genotype LOR estimates as it is a score-based test. Here, we propose a scalable method based on score statistics, to accurately estimate the genotype LORs, adjusting for non-genetic covariates. Comparing to the Firth method, our proposed method reduces the computational complexity from O(nK2 + K3) to O(n), where n is the sample-size, and K is the number of non-genetic covariates. Our method is ~ 10x faster than the Firth method when 15 covariates are being adjusted for. Through extensive numerical simulations, we show that the proposed method is both scalable and accurate in estimating the genotype ORs in genome-wide or phenome-wide scale.

scholarly journals Large-Scale Gene Expression Data Analysis: A New Challenge to Computational Biologists

1999 ◽  
Vol 9 (8) ◽  
pp. 681-688 ◽  
Author(s):  
Michael Q. Zhang
Keyword(s):  
Gene Expression ◽  
Gene Expression Data ◽  
Large Scale ◽  
Yeast Genome ◽  
Expression Data ◽  
Dna Arrays ◽  
Gene Expression Data Analysis ◽  
Genome Wide ◽  
A Genome ◽  
Wide Scale

The use of high-density DNA arrays to monitor gene expression at a genome-wide scale constitutes a fundamental advance in biology. In particular, the expression pattern of all genes in Saccharomyces cerevisiae can be interrogated using microarray analysis where cDNAs are hybridized to an array of each of the ∼6000 genes in the yeast genome. In this survey I review three recent experiments related to transcriptional regulation and discuss the great challenge for computational biologists trying to extract functional information from such large-scale gene expression data.

scholarly journals Genetic Analysis of Walnut (Juglans regia L.) Pellicle Pigment Variation Through a Novel, High-Throughput Phenotyping Platform

2020 ◽  
Vol 10 (12) ◽  
pp. 4411-4424
Author(s):  
Gina M. Sideli ◽  
Peter McAtee ◽  
Annarita Marrano ◽  
Brian J. Allen ◽  
Patrick J. Brown ◽  
...  
Keyword(s):  
High Throughput ◽  
Large Scale ◽  
Juglans Regia ◽  
Color Space ◽  
Consumer Preference ◽  
Improvement Program ◽  
Genome Wide ◽  
A Genome ◽  
High Throughput Phenotyping ◽  
Pigment Variation

Walnut pellicle color is a key quality attribute that drives consumer preference and walnut sales. For the first time a high-throughput, computer vision-based phenotyping platform using a custom algorithm to quantitatively score each walnut pellicle in L* a* b* color space was deployed at large-scale. This was compared to traditional qualitative scoring by eye and was used to dissect the genetics of pellicle pigmentation. Progeny from both a bi-parental population of 168 trees (‘Chandler’ × ‘Idaho’) and a genome-wide association (GWAS) with 528 trees of the UC Davis Walnut Improvement Program were analyzed. Color phenotypes were found to have overlapping regions in the ‘Chandler’ genetic map on Chr01 suggesting complex genetic control. In the GWAS population, multiple, small effect QTL across Chr01, Chr07, Chr08, Chr09, Chr10, Chr12 and Chr13 were discovered. Marker trait associations were co-localized with QTL mapping on Chr01, Chr10, Chr14, and Chr16. Putative candidate genes controlling walnut pellicle pigmentation were postulated.

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