Identification of nodulation-related genes in Medicago truncatula using genome-wide association studies and co-expression networks

Jean Michel Michno; Junqi Liu; Joseph R. Jeffers; Robert M. Stupar; Chad L. Myers

doi:10.1002/pld3.220

Identification of nodulation-related genes in Medicago truncatula using genome-wide association studies and co-expression networks

Jean Michel Michno, Junqi Liu, Joseph R. Jeffers, Robert M. Stupar, Chad L. Myers

Research output: Contribution to journal › Article › peer-review

3 Scopus citations

Abstract

Genome-wide association studies (GWAS) have proven to be a valuable approach for identifying genetic intervals associated with phenotypic variation in Medicago truncatula. These intervals can vary in size, depending on the historical local recombination. Typically, significant intervals span numerous gene models, limiting the ability to resolve high-confidence candidate genes underlying the trait of interest. Additional genomic data, including gene co-expression networks, can be combined with the genetic mapping information to successfully identify candidate genes. Co-expression network analysis provides information about the functional relationships of each gene through its similarity of expression patterns to other well-defined clusters of genes. In this study, we integrated data from GWAS and co-expression networks to pinpoint candidate genes that may be associated with nodule-related phenotypes in M. truncatula. We further investigated a subset of these genes and confirmed that several had existing evidence linking them nodulation, including MEDTR2G101090 (PEN3-like), a previously validated gene associated with nodule number.

Original language	English (US)
Article number	e00220
Journal	Plant Direct
Volume	4
Issue number	5
DOIs	https://doi.org/10.1002/pld3.220
State	Published - May 1 2020

Bibliographical note

Funding Information:
We would like to thank Peter Tiffin and Liana Burghardt for help with providing insights and direction, the University of Minnesota Office of Information Technology for accommodating our data storage needs, and the Department of Computer Science at the University of Minnesota for server maintenance and support. This work was supported by funding from the National Science Foundation (IOS-1237993) with partial funding from (IOS-1126950). Funding sources played no role in the design of this study or the collection, analysis, and the interpretation of data and in writing the manuscript.

Funding Information:
We would like to thank Peter Tiffin and Liana Burghardt for help with providing insights and direction, the University of Minnesota Office of Information Technology for accommodating our data storage needs, and the Department of Computer Science at the University of Minnesota for server maintenance and support. This work was supported by funding from the National Science Foundation (IOS‐1237993) with partial funding from (IOS‐1126950). Funding sources played no role in the design of this study or the collection, analysis, and the interpretation of data and in writing the manuscript.

Publisher Copyright:
© 2020 The Authors. Plant Direct published by American Society of Plant Biologists, Society for Experimental Biology and John Wiley & Sons Ltd

Keywords

Medicago
bioinformatics
co-expression
genome-wide association studies
nodulation

Access

10.1002/pld3.220

OpenUrl availability

Full text

Cite this

@article{49d363521d9b4298a07352aa5aa17692,

title = "Identification of nodulation-related genes in Medicago truncatula using genome-wide association studies and co-expression networks",

abstract = "Genome-wide association studies (GWAS) have proven to be a valuable approach for identifying genetic intervals associated with phenotypic variation in Medicago truncatula. These intervals can vary in size, depending on the historical local recombination. Typically, significant intervals span numerous gene models, limiting the ability to resolve high-confidence candidate genes underlying the trait of interest. Additional genomic data, including gene co-expression networks, can be combined with the genetic mapping information to successfully identify candidate genes. Co-expression network analysis provides information about the functional relationships of each gene through its similarity of expression patterns to other well-defined clusters of genes. In this study, we integrated data from GWAS and co-expression networks to pinpoint candidate genes that may be associated with nodule-related phenotypes in M. truncatula. We further investigated a subset of these genes and confirmed that several had existing evidence linking them nodulation, including MEDTR2G101090 (PEN3-like), a previously validated gene associated with nodule number.",

keywords = "Medicago, bioinformatics, co-expression, genome-wide association studies, nodulation",

author = "Michno, {Jean Michel} and Junqi Liu and Jeffers, {Joseph R.} and Stupar, {Robert M.} and Myers, {Chad L.}",

note = "Funding Information: We would like to thank Peter Tiffin and Liana Burghardt for help with providing insights and direction, the University of Minnesota Office of Information Technology for accommodating our data storage needs, and the Department of Computer Science at the University of Minnesota for server maintenance and support. This work was supported by funding from the National Science Foundation (IOS-1237993) with partial funding from (IOS-1126950). Funding sources played no role in the design of this study or the collection, analysis, and the interpretation of data and in writing the manuscript. Funding Information: We would like to thank Peter Tiffin and Liana Burghardt for help with providing insights and direction, the University of Minnesota Office of Information Technology for accommodating our data storage needs, and the Department of Computer Science at the University of Minnesota for server maintenance and support. This work was supported by funding from the National Science Foundation (IOS‐1237993) with partial funding from (IOS‐1126950). Funding sources played no role in the design of this study or the collection, analysis, and the interpretation of data and in writing the manuscript. Publisher Copyright: {\textcopyright} 2020 The Authors. Plant Direct published by American Society of Plant Biologists, Society for Experimental Biology and John Wiley & Sons Ltd",

year = "2020",

month = may,

day = "1",

doi = "10.1002/pld3.220",

language = "English (US)",

volume = "4",

journal = "Plant Direct",

issn = "2475-4455",

publisher = "John Wiley and Sons Inc.",

number = "5",

}

TY - JOUR

T1 - Identification of nodulation-related genes in Medicago truncatula using genome-wide association studies and co-expression networks

AU - Michno, Jean Michel

AU - Liu, Junqi

AU - Jeffers, Joseph R.

AU - Stupar, Robert M.

AU - Myers, Chad L.

N1 - Funding Information: We would like to thank Peter Tiffin and Liana Burghardt for help with providing insights and direction, the University of Minnesota Office of Information Technology for accommodating our data storage needs, and the Department of Computer Science at the University of Minnesota for server maintenance and support. This work was supported by funding from the National Science Foundation (IOS-1237993) with partial funding from (IOS-1126950). Funding sources played no role in the design of this study or the collection, analysis, and the interpretation of data and in writing the manuscript. Funding Information: We would like to thank Peter Tiffin and Liana Burghardt for help with providing insights and direction, the University of Minnesota Office of Information Technology for accommodating our data storage needs, and the Department of Computer Science at the University of Minnesota for server maintenance and support. This work was supported by funding from the National Science Foundation (IOS‐1237993) with partial funding from (IOS‐1126950). Funding sources played no role in the design of this study or the collection, analysis, and the interpretation of data and in writing the manuscript. Publisher Copyright: © 2020 The Authors. Plant Direct published by American Society of Plant Biologists, Society for Experimental Biology and John Wiley & Sons Ltd

PY - 2020/5/1

Y1 - 2020/5/1

N2 - Genome-wide association studies (GWAS) have proven to be a valuable approach for identifying genetic intervals associated with phenotypic variation in Medicago truncatula. These intervals can vary in size, depending on the historical local recombination. Typically, significant intervals span numerous gene models, limiting the ability to resolve high-confidence candidate genes underlying the trait of interest. Additional genomic data, including gene co-expression networks, can be combined with the genetic mapping information to successfully identify candidate genes. Co-expression network analysis provides information about the functional relationships of each gene through its similarity of expression patterns to other well-defined clusters of genes. In this study, we integrated data from GWAS and co-expression networks to pinpoint candidate genes that may be associated with nodule-related phenotypes in M. truncatula. We further investigated a subset of these genes and confirmed that several had existing evidence linking them nodulation, including MEDTR2G101090 (PEN3-like), a previously validated gene associated with nodule number.

AB - Genome-wide association studies (GWAS) have proven to be a valuable approach for identifying genetic intervals associated with phenotypic variation in Medicago truncatula. These intervals can vary in size, depending on the historical local recombination. Typically, significant intervals span numerous gene models, limiting the ability to resolve high-confidence candidate genes underlying the trait of interest. Additional genomic data, including gene co-expression networks, can be combined with the genetic mapping information to successfully identify candidate genes. Co-expression network analysis provides information about the functional relationships of each gene through its similarity of expression patterns to other well-defined clusters of genes. In this study, we integrated data from GWAS and co-expression networks to pinpoint candidate genes that may be associated with nodule-related phenotypes in M. truncatula. We further investigated a subset of these genes and confirmed that several had existing evidence linking them nodulation, including MEDTR2G101090 (PEN3-like), a previously validated gene associated with nodule number.

KW - Medicago

KW - bioinformatics

KW - co-expression

KW - genome-wide association studies

KW - nodulation

UR - http://www.scopus.com/inward/record.url?scp=85085702129&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85085702129&partnerID=8YFLogxK

U2 - 10.1002/pld3.220

DO - 10.1002/pld3.220

M3 - Article

C2 - 32426691

AN - SCOPUS:85085702129

SN - 2475-4455

VL - 4

JO - Plant Direct

JF - Plant Direct

IS - 5

M1 - e00220

ER -

Identification of nodulation-related genes in Medicago truncatula using genome-wide association studies and co-expression networks

Abstract

Bibliographical note

Keywords

Access

OpenUrl availability

Other files and links

Fingerprint

Cite this