Using functional genomics to study PINK1 and metabolic physiology

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Using functional genomics to study PINK1 and metabolic physiology. / Scheele, Camilla; Larsson, Ola; Timmons, James A.

In: Methods in Enzymology, Vol. 457, 2009, p. 211-29.

Research output: Contribution to journalJournal articleResearchpeer-review

Harvard

Scheele, C, Larsson, O & Timmons, JA 2009, 'Using functional genomics to study PINK1 and metabolic physiology', Methods in Enzymology, vol. 457, pp. 211-29. https://doi.org/10.1016/S0076-6879(09)05012-5

APA

Scheele, C., Larsson, O., & Timmons, J. A. (2009). Using functional genomics to study PINK1 and metabolic physiology. Methods in Enzymology, 457, 211-29. https://doi.org/10.1016/S0076-6879(09)05012-5

Vancouver

Scheele C, Larsson O, Timmons JA. Using functional genomics to study PINK1 and metabolic physiology. Methods in Enzymology. 2009;457:211-29. https://doi.org/10.1016/S0076-6879(09)05012-5

Author

Scheele, Camilla ; Larsson, Ola ; Timmons, James A. / Using functional genomics to study PINK1 and metabolic physiology. In: Methods in Enzymology. 2009 ; Vol. 457. pp. 211-29.

Bibtex

@article{e1626f90368111df8ed1000ea68e967b,
title = "Using functional genomics to study PINK1 and metabolic physiology",
abstract = "Genome sequencing projects have provided the substrate for an unimaginable number of biological experiments. Further, genomic technologies such as microarrays and quantitative and exquisitely sensitive techniques such as real-time quantitative polymerase chain reaction have made it possible to reliably generate millions of data points per experiment. The data can be high quality and yield entirely new insights into how gene expression is coordinated under complex physiological situations. It can also be that the data and interpretation are meaningless because of a lack of physiological context or experimental control. Thus, functional genomics is now being applied to study metabolic physiology with varying degrees of success. From the genome sequencing projects we also have the information needed to design chemical tools that can knock down a gene transcript, even distinguishing between splice variants in mammalian cells. Use of such technologies, inspired by nature's endogenous RNAi mechanism-microRNA targeting, comes with significant caveats. While the discipline of Pharmacology taught us last century that inhibitor action specificity is dependent on the concentration used, these experiences have been ignored by users of siRNA technologies. What we provide in this chapter is some considerations and observations from functional genomic studies. We are largely concerned with the phase that follows a microarray study, where a candidate gene is selected for manipulation in a system that is considered to be simpler than the in vivo mammalian tissue and thus the methods discussed largely apply to this cell biology phase. We apologize for not referring to all relevant publications and for any technical considerations we have also failed to factor into our discussion.",
author = "Camilla Scheele and Ola Larsson and Timmons, {James A}",
note = "Keywords: Animals; Apoptosis; Cells, Cultured; Genomics; Humans; Mitochondria, Muscle; Models, Biological; Oligonucleotide Array Sequence Analysis; Protein Kinases; RNA, Small Interfering",
year = "2009",
doi = "10.1016/S0076-6879(09)05012-5",
language = "English",
volume = "457",
pages = "211--29",
journal = "Methods in Enzymology",
issn = "0076-6879",
publisher = "Academic Press",

}

RIS

TY - JOUR

T1 - Using functional genomics to study PINK1 and metabolic physiology

AU - Scheele, Camilla

AU - Larsson, Ola

AU - Timmons, James A

N1 - Keywords: Animals; Apoptosis; Cells, Cultured; Genomics; Humans; Mitochondria, Muscle; Models, Biological; Oligonucleotide Array Sequence Analysis; Protein Kinases; RNA, Small Interfering

PY - 2009

Y1 - 2009

N2 - Genome sequencing projects have provided the substrate for an unimaginable number of biological experiments. Further, genomic technologies such as microarrays and quantitative and exquisitely sensitive techniques such as real-time quantitative polymerase chain reaction have made it possible to reliably generate millions of data points per experiment. The data can be high quality and yield entirely new insights into how gene expression is coordinated under complex physiological situations. It can also be that the data and interpretation are meaningless because of a lack of physiological context or experimental control. Thus, functional genomics is now being applied to study metabolic physiology with varying degrees of success. From the genome sequencing projects we also have the information needed to design chemical tools that can knock down a gene transcript, even distinguishing between splice variants in mammalian cells. Use of such technologies, inspired by nature's endogenous RNAi mechanism-microRNA targeting, comes with significant caveats. While the discipline of Pharmacology taught us last century that inhibitor action specificity is dependent on the concentration used, these experiences have been ignored by users of siRNA technologies. What we provide in this chapter is some considerations and observations from functional genomic studies. We are largely concerned with the phase that follows a microarray study, where a candidate gene is selected for manipulation in a system that is considered to be simpler than the in vivo mammalian tissue and thus the methods discussed largely apply to this cell biology phase. We apologize for not referring to all relevant publications and for any technical considerations we have also failed to factor into our discussion.

AB - Genome sequencing projects have provided the substrate for an unimaginable number of biological experiments. Further, genomic technologies such as microarrays and quantitative and exquisitely sensitive techniques such as real-time quantitative polymerase chain reaction have made it possible to reliably generate millions of data points per experiment. The data can be high quality and yield entirely new insights into how gene expression is coordinated under complex physiological situations. It can also be that the data and interpretation are meaningless because of a lack of physiological context or experimental control. Thus, functional genomics is now being applied to study metabolic physiology with varying degrees of success. From the genome sequencing projects we also have the information needed to design chemical tools that can knock down a gene transcript, even distinguishing between splice variants in mammalian cells. Use of such technologies, inspired by nature's endogenous RNAi mechanism-microRNA targeting, comes with significant caveats. While the discipline of Pharmacology taught us last century that inhibitor action specificity is dependent on the concentration used, these experiences have been ignored by users of siRNA technologies. What we provide in this chapter is some considerations and observations from functional genomic studies. We are largely concerned with the phase that follows a microarray study, where a candidate gene is selected for manipulation in a system that is considered to be simpler than the in vivo mammalian tissue and thus the methods discussed largely apply to this cell biology phase. We apologize for not referring to all relevant publications and for any technical considerations we have also failed to factor into our discussion.

U2 - 10.1016/S0076-6879(09)05012-5

DO - 10.1016/S0076-6879(09)05012-5

M3 - Journal article

C2 - 19426870

VL - 457

SP - 211

EP - 229

JO - Methods in Enzymology

JF - Methods in Enzymology

SN - 0076-6879

ER -

ID: 18789570