Microbial genome-wide association studies: lessons from human GWAS
Key Points Genome-wide association studies (GWAS) have been highly successful in the analyses of human genomic data. The increased availability of microorganism whole genomes provides the opportunity for microbial GWAS. Initial microbial GWAS have had success identifying variants for traits under st...
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description | Key Points
Genome-wide association studies (GWAS) have been highly successful in the analyses of human genomic data. The increased availability of microorganism whole genomes provides the opportunity for microbial GWAS.
Initial microbial GWAS have had success identifying variants for traits under strong selection, such as drug resistance, in a range of bacteria, viruses and protozoa.
Several challenges to microbial GWAS exist that could hinder identifying variants under moderate selection. The primary challenge is the increased population stratification in microorganisms owing to selection and complex recombination patterns.
Novel software that is tailored to the needs of microbial GWAS would greatly expedite progress in the field. In particular, the application of polygenic methods has yet to be evaluated in microorganisms.
An exciting future area of research is the generation of host and microbial genomics data within the same samples. This will allow for genome-to-genome analyses to test for host–microorganism interactions.
With the increasing availability of microbial whole genomes, researchers are beginning to carry out genome-wide association studies (GWAS) in bacteria, viruses and protozoa. In this Review, the authors discuss the specific challenges and considerations associated with the application of GWAS methods to microorganisms and consider the future of microbial GWAS in the light of lessons learned from human studies.
The reduced costs of sequencing have led to whole-genome sequences for a large number of microorganisms, enabling the application of microbial genome-wide association studies (GWAS). Given the successes of human GWAS in understanding disease aetiology and identifying potential drug targets, microbial GWAS are likely to further advance our understanding of infectious diseases. These advances include insights into pressing global health problems, such as antibiotic resistance and disease transmission. In this Review, we outline the methodologies of GWAS, the current state of the field of microbial GWAS, and how lessons from human GWAS can direct the future of the field. |
doi_str_mv | 10.1038/nrg.2016.132 |
format | Article |
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Genome-wide association studies (GWAS) have been highly successful in the analyses of human genomic data. The increased availability of microorganism whole genomes provides the opportunity for microbial GWAS.
Initial microbial GWAS have had success identifying variants for traits under strong selection, such as drug resistance, in a range of bacteria, viruses and protozoa.
Several challenges to microbial GWAS exist that could hinder identifying variants under moderate selection. The primary challenge is the increased population stratification in microorganisms owing to selection and complex recombination patterns.
Novel software that is tailored to the needs of microbial GWAS would greatly expedite progress in the field. In particular, the application of polygenic methods has yet to be evaluated in microorganisms.
An exciting future area of research is the generation of host and microbial genomics data within the same samples. This will allow for genome-to-genome analyses to test for host–microorganism interactions.
With the increasing availability of microbial whole genomes, researchers are beginning to carry out genome-wide association studies (GWAS) in bacteria, viruses and protozoa. In this Review, the authors discuss the specific challenges and considerations associated with the application of GWAS methods to microorganisms and consider the future of microbial GWAS in the light of lessons learned from human studies.
The reduced costs of sequencing have led to whole-genome sequences for a large number of microorganisms, enabling the application of microbial genome-wide association studies (GWAS). Given the successes of human GWAS in understanding disease aetiology and identifying potential drug targets, microbial GWAS are likely to further advance our understanding of infectious diseases. These advances include insights into pressing global health problems, such as antibiotic resistance and disease transmission. In this Review, we outline the methodologies of GWAS, the current state of the field of microbial GWAS, and how lessons from human GWAS can direct the future of the field.</description><identifier>ISSN: 1471-0056</identifier><identifier>EISSN: 1471-0064</identifier><identifier>DOI: 10.1038/nrg.2016.132</identifier><identifier>PMID: 27840430</identifier><language>eng</language><publisher>London: Nature Publishing Group UK</publisher><subject>631/205/2138 ; 631/326/325 ; Agriculture ; Animal Genetics and Genomics ; Bacteria ; Biomedicine ; Cancer Research ; Communicable Diseases - genetics ; Communicable Diseases - microbiology ; Development and progression ; Disease ; Drug resistance ; Gene Function ; Genetic aspects ; Genetic Predisposition to Disease ; Genetic susceptibility ; Genome, Human ; Genome, Microbial ; Genome-wide association studies ; Genome-Wide Association Study ; Genomes ; Genomics ; Genotype ; Genotype & phenotype ; Health risk assessment ; Human Genetics ; Humans ; Hypotheses ; Microbial drug resistance ; Microorganisms ; Physiological aspects ; Polygenic inheritance ; Polymorphism ; Quality control ; Regression analysis ; review-article ; Single nucleotide polymorphisms</subject><ispartof>Nature reviews. Genetics, 2017-01, Vol.18 (1), p.41-50</ispartof><rights>Springer Nature Limited 2016</rights><rights>COPYRIGHT 2017 Nature Publishing Group</rights><rights>Copyright Nature Publishing Group Jan 2017</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c588t-66ad958fbe4ea13c9549bf443af091737187cf3cce89f43c428ea22b71c07a243</citedby><cites>FETCH-LOGICAL-c588t-66ad958fbe4ea13c9549bf443af091737187cf3cce89f43c428ea22b71c07a243</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27840430$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Power, Robert A.</creatorcontrib><creatorcontrib>Parkhill, Julian</creatorcontrib><creatorcontrib>de Oliveira, Tulio</creatorcontrib><title>Microbial genome-wide association studies: lessons from human GWAS</title><title>Nature reviews. Genetics</title><addtitle>Nat Rev Genet</addtitle><addtitle>Nat Rev Genet</addtitle><description>Key Points
Genome-wide association studies (GWAS) have been highly successful in the analyses of human genomic data. The increased availability of microorganism whole genomes provides the opportunity for microbial GWAS.
Initial microbial GWAS have had success identifying variants for traits under strong selection, such as drug resistance, in a range of bacteria, viruses and protozoa.
Several challenges to microbial GWAS exist that could hinder identifying variants under moderate selection. The primary challenge is the increased population stratification in microorganisms owing to selection and complex recombination patterns.
Novel software that is tailored to the needs of microbial GWAS would greatly expedite progress in the field. In particular, the application of polygenic methods has yet to be evaluated in microorganisms.
An exciting future area of research is the generation of host and microbial genomics data within the same samples. This will allow for genome-to-genome analyses to test for host–microorganism interactions.
With the increasing availability of microbial whole genomes, researchers are beginning to carry out genome-wide association studies (GWAS) in bacteria, viruses and protozoa. In this Review, the authors discuss the specific challenges and considerations associated with the application of GWAS methods to microorganisms and consider the future of microbial GWAS in the light of lessons learned from human studies.
The reduced costs of sequencing have led to whole-genome sequences for a large number of microorganisms, enabling the application of microbial genome-wide association studies (GWAS). Given the successes of human GWAS in understanding disease aetiology and identifying potential drug targets, microbial GWAS are likely to further advance our understanding of infectious diseases. These advances include insights into pressing global health problems, such as antibiotic resistance and disease transmission. In this Review, we outline the methodologies of GWAS, the current state of the field of microbial GWAS, and how lessons from human GWAS can direct the future of the field.</description><subject>631/205/2138</subject><subject>631/326/325</subject><subject>Agriculture</subject><subject>Animal Genetics and Genomics</subject><subject>Bacteria</subject><subject>Biomedicine</subject><subject>Cancer Research</subject><subject>Communicable Diseases - genetics</subject><subject>Communicable Diseases - microbiology</subject><subject>Development and progression</subject><subject>Disease</subject><subject>Drug resistance</subject><subject>Gene Function</subject><subject>Genetic aspects</subject><subject>Genetic Predisposition to Disease</subject><subject>Genetic susceptibility</subject><subject>Genome, Human</subject><subject>Genome, Microbial</subject><subject>Genome-wide association studies</subject><subject>Genome-Wide Association Study</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Genotype</subject><subject>Genotype & phenotype</subject><subject>Health risk assessment</subject><subject>Human Genetics</subject><subject>Humans</subject><subject>Hypotheses</subject><subject>Microbial drug resistance</subject><subject>Microorganisms</subject><subject>Physiological aspects</subject><subject>Polygenic inheritance</subject><subject>Polymorphism</subject><subject>Quality control</subject><subject>Regression analysis</subject><subject>review-article</subject><subject>Single nucleotide polymorphisms</subject><issn>1471-0056</issn><issn>1471-0064</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2017</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNqN0t1r1TAYB-AiipvTO6-lIIiCPeazSbw7Dp2DieAUL0OavunJaJOZtKj_vTmcOXdkiPQiJXny9eZXVY8xWmFE5auQhhVBuF1hSu5Uh5gJ3CDUsrvX_7w9qB7kfIGKwoLerw6IkAwxig6rNx-8TbHzZqwHCHGC5rvvoTY5R-vN7GOo87z0HvLreoTSG3LtUpzqzTKZUJ98XZ8_rO45M2Z4dNUeVV_evf18_L45-3hyerw-ayyXcm7a1vSKS9cBA4OpVZypzjFGjUOqHEtgKayj1oJUjlHLiARDSCewRcIQRo-q57t1L1P8tkCe9eSzhXE0AeKSNZZcMclxq_6DUoUJoRQX-vQvehGXFMpFNMWMlhJTxP-lyratFJxg9UcNZgTtg4tzMna7tV4zQVvBJRJFrW5R5eth8jYGcL707014sTehmBl-zINZctan55_27bMbdgNmnDc5jsv2JfM-fLmD5flzTuD0ZfKTST81RnobLF2CpbfB0iVYhT-5KsDSTdBf499JKqDZgVyGwgDpRoVuW_AXeoDRSA</recordid><startdate>20170101</startdate><enddate>20170101</enddate><creator>Power, Robert A.</creator><creator>Parkhill, Julian</creator><creator>de Oliveira, Tulio</creator><general>Nature Publishing Group UK</general><general>Nature Publishing Group</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>ISR</scope><scope>3V.</scope><scope>7QP</scope><scope>7QR</scope><scope>7RV</scope><scope>7TK</scope><scope>7TM</scope><scope>7X7</scope><scope>7XB</scope><scope>88A</scope><scope>88E</scope><scope>8AO</scope><scope>8C1</scope><scope>8FD</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FR3</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>KB0</scope><scope>LK8</scope><scope>M0S</scope><scope>M1P</scope><scope>M7P</scope><scope>NAPCQ</scope><scope>P64</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>RC3</scope><scope>7X8</scope></search><sort><creationdate>20170101</creationdate><title>Microbial genome-wide association studies: lessons from human GWAS</title><author>Power, Robert A. ; 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Genetics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Power, Robert A.</au><au>Parkhill, Julian</au><au>de Oliveira, Tulio</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Microbial genome-wide association studies: lessons from human GWAS</atitle><jtitle>Nature reviews. Genetics</jtitle><stitle>Nat Rev Genet</stitle><addtitle>Nat Rev Genet</addtitle><date>2017-01-01</date><risdate>2017</risdate><volume>18</volume><issue>1</issue><spage>41</spage><epage>50</epage><pages>41-50</pages><issn>1471-0056</issn><eissn>1471-0064</eissn><abstract>Key Points
Genome-wide association studies (GWAS) have been highly successful in the analyses of human genomic data. The increased availability of microorganism whole genomes provides the opportunity for microbial GWAS.
Initial microbial GWAS have had success identifying variants for traits under strong selection, such as drug resistance, in a range of bacteria, viruses and protozoa.
Several challenges to microbial GWAS exist that could hinder identifying variants under moderate selection. The primary challenge is the increased population stratification in microorganisms owing to selection and complex recombination patterns.
Novel software that is tailored to the needs of microbial GWAS would greatly expedite progress in the field. In particular, the application of polygenic methods has yet to be evaluated in microorganisms.
An exciting future area of research is the generation of host and microbial genomics data within the same samples. This will allow for genome-to-genome analyses to test for host–microorganism interactions.
With the increasing availability of microbial whole genomes, researchers are beginning to carry out genome-wide association studies (GWAS) in bacteria, viruses and protozoa. In this Review, the authors discuss the specific challenges and considerations associated with the application of GWAS methods to microorganisms and consider the future of microbial GWAS in the light of lessons learned from human studies.
The reduced costs of sequencing have led to whole-genome sequences for a large number of microorganisms, enabling the application of microbial genome-wide association studies (GWAS). Given the successes of human GWAS in understanding disease aetiology and identifying potential drug targets, microbial GWAS are likely to further advance our understanding of infectious diseases. These advances include insights into pressing global health problems, such as antibiotic resistance and disease transmission. In this Review, we outline the methodologies of GWAS, the current state of the field of microbial GWAS, and how lessons from human GWAS can direct the future of the field.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><pmid>27840430</pmid><doi>10.1038/nrg.2016.132</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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subjects | 631/205/2138 631/326/325 Agriculture Animal Genetics and Genomics Bacteria Biomedicine Cancer Research Communicable Diseases - genetics Communicable Diseases - microbiology Development and progression Disease Drug resistance Gene Function Genetic aspects Genetic Predisposition to Disease Genetic susceptibility Genome, Human Genome, Microbial Genome-wide association studies Genome-Wide Association Study Genomes Genomics Genotype Genotype & phenotype Health risk assessment Human Genetics Humans Hypotheses Microbial drug resistance Microorganisms Physiological aspects Polygenic inheritance Polymorphism Quality control Regression analysis review-article Single nucleotide polymorphisms |
title | Microbial genome-wide association studies: lessons from human GWAS |
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