Cargando…
Genetics of single-cell protein abundance variation in large yeast populations
Variation among individuals arises in part from differences in DNA sequences, but the genetic basis for variation in most traits, including common diseases, remains only partly understood. Many DNA variants influence phenotypes by altering the expression level of one or multiple genes. The effects o...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4285441/ https://www.ncbi.nlm.nih.gov/pubmed/24402228 http://dx.doi.org/10.1038/nature12904 |
_version_ | 1782351576146378752 |
---|---|
author | Albert, Frank W. Treusch, Sebastian Shockley, Arthur H. Bloom, Joshua S. Kruglyak, Leonid |
author_facet | Albert, Frank W. Treusch, Sebastian Shockley, Arthur H. Bloom, Joshua S. Kruglyak, Leonid |
author_sort | Albert, Frank W. |
collection | PubMed |
description | Variation among individuals arises in part from differences in DNA sequences, but the genetic basis for variation in most traits, including common diseases, remains only partly understood. Many DNA variants influence phenotypes by altering the expression level of one or multiple genes. The effects of such variants can be detected as expression quantitative trait loci (eQTL) (1). Traditional eQTL mapping requires large-scale genotype and gene expression data for each individual in the study sample, which limits sample sizes to hundreds of individuals in both humans and model organisms and reduces statistical power (2–6). Consequently, many eQTL are likely missed, especially those with smaller effects (7). Further, most studies use mRNA rather than protein abundance as the measure of gene expression. Studies that have used mass-spectrometry proteomics (8–13) reported surprising differences between eQTL and protein QTL (pQTL) for the same genes (9,10), but these studies have been even more limited in scope. Here, we introduce a powerful method for identifying genetic loci that influence protein expression in the yeast Saccharomyes cerevisiae. We measure single-cell protein abundance through the use of green-fluorescent-protein tags in very large populations of genetically variable cells, and use pooled sequencing to compare allele frequencies across the genome in thousands of individuals with high vs. low protein abundance. We applied this method to 160 genes and detected many more loci per gene than previous studies. We also observed closer correspondence between loci that influence protein abundance and loci that influence mRNA abundance of a given gene. Most loci cluster at hotspot locations that influence multiple proteins—in some cases, more than half of those examined. The variants that underlie these hotspots have profound effects on the gene regulatory network and provide insights into genetic variation in cell physiology between yeast strains. |
format | Online Article Text |
id | pubmed-4285441 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
record_format | MEDLINE/PubMed |
spelling | pubmed-42854412015-01-06 Genetics of single-cell protein abundance variation in large yeast populations Albert, Frank W. Treusch, Sebastian Shockley, Arthur H. Bloom, Joshua S. Kruglyak, Leonid Nature Article Variation among individuals arises in part from differences in DNA sequences, but the genetic basis for variation in most traits, including common diseases, remains only partly understood. Many DNA variants influence phenotypes by altering the expression level of one or multiple genes. The effects of such variants can be detected as expression quantitative trait loci (eQTL) (1). Traditional eQTL mapping requires large-scale genotype and gene expression data for each individual in the study sample, which limits sample sizes to hundreds of individuals in both humans and model organisms and reduces statistical power (2–6). Consequently, many eQTL are likely missed, especially those with smaller effects (7). Further, most studies use mRNA rather than protein abundance as the measure of gene expression. Studies that have used mass-spectrometry proteomics (8–13) reported surprising differences between eQTL and protein QTL (pQTL) for the same genes (9,10), but these studies have been even more limited in scope. Here, we introduce a powerful method for identifying genetic loci that influence protein expression in the yeast Saccharomyes cerevisiae. We measure single-cell protein abundance through the use of green-fluorescent-protein tags in very large populations of genetically variable cells, and use pooled sequencing to compare allele frequencies across the genome in thousands of individuals with high vs. low protein abundance. We applied this method to 160 genes and detected many more loci per gene than previous studies. We also observed closer correspondence between loci that influence protein abundance and loci that influence mRNA abundance of a given gene. Most loci cluster at hotspot locations that influence multiple proteins—in some cases, more than half of those examined. The variants that underlie these hotspots have profound effects on the gene regulatory network and provide insights into genetic variation in cell physiology between yeast strains. 2014-01-08 2014-02-27 /pmc/articles/PMC4285441/ /pubmed/24402228 http://dx.doi.org/10.1038/nature12904 Text en Users may view, print, copy, download and text and data- mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use: http://www.nature.com/authors/editorial_policies/license.html#terms |
spellingShingle | Article Albert, Frank W. Treusch, Sebastian Shockley, Arthur H. Bloom, Joshua S. Kruglyak, Leonid Genetics of single-cell protein abundance variation in large yeast populations |
title | Genetics of single-cell protein abundance variation in large yeast populations |
title_full | Genetics of single-cell protein abundance variation in large yeast populations |
title_fullStr | Genetics of single-cell protein abundance variation in large yeast populations |
title_full_unstemmed | Genetics of single-cell protein abundance variation in large yeast populations |
title_short | Genetics of single-cell protein abundance variation in large yeast populations |
title_sort | genetics of single-cell protein abundance variation in large yeast populations |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4285441/ https://www.ncbi.nlm.nih.gov/pubmed/24402228 http://dx.doi.org/10.1038/nature12904 |
work_keys_str_mv | AT albertfrankw geneticsofsinglecellproteinabundancevariationinlargeyeastpopulations AT treuschsebastian geneticsofsinglecellproteinabundancevariationinlargeyeastpopulations AT shockleyarthurh geneticsofsinglecellproteinabundancevariationinlargeyeastpopulations AT bloomjoshuas geneticsofsinglecellproteinabundancevariationinlargeyeastpopulations AT kruglyakleonid geneticsofsinglecellproteinabundancevariationinlargeyeastpopulations |