Genome-Wide Association Mapping of Starch Pasting Properties in Maize Using Single-Locus and Multi-Locus Models
Maize starch plays a critical role in food processing and industrial application. The pasting properties, the most important starch characteristics, have enormous influence on fabrication property, flavor characteristics, storage, cooking, and baking. Understanding the genetic basis of starch pasting properties will be beneficial for manipulation of starch properties for a given purpose. Genome-wide association studies (GWAS) are becoming a powerful tool for dissecting the complex traits. Here, we carried out GWAS for seven pasting properties of maize starch with a panel of 230 inbred lines and 145,232 SNPs using one single-locus method, genome-wide efficient mixed model association (GEMMA), and three multi-locus methods, FASTmrEMMA, FarmCPU, and LASSO. We totally identified 60 quantitative trait nucleotides (QTNs) for starch pasting properties with these four GWAS methods. FASTmrEMMA detected the most QTNs (29), followed by FarmCPU (19) and LASSO (12), GEMMA detected the least QTNs (7). Of these QTNs, seven QTNs were identified by more than one method simultaneously. We further investigated locations of these significantly associated QTNs for possible candidate genes. These candidate genes and significant QTNs provide the guidance for further understanding of molecular mechanisms of starch pasting properties. We also compared the statistical powers and Type I errors of the four GWAS methods using Monte Carlo simulations. The results suggest that the multi-locus method is more powerful than the single-locus method and a combination of these multi-locus methods could help improve the detection power of GWAS.
| Medienart: |
E-Artikel |
|---|
| Erscheinungsjahr: |
2018 |
|---|---|
| Erschienen: |
2018 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:9 |
|---|---|
| Enthalten in: |
Frontiers in plant science - 9(2018) vom: 20., Seite 1311 |
| Sprache: |
Englisch |
|---|
| Beteiligte Personen: |
Xu, Yang [VerfasserIn] |
|---|
| Links: |
|---|
| Themen: |
|---|
| Anmerkungen: |
Date Revised 01.10.2020 published: Electronic-eCollection Citation Status PubMed-not-MEDLINE |
|---|
| doi: |
10.3389/fpls.2018.01311 |
|---|
| funding: |
|
|---|---|
| Förderinstitution / Projekttitel: |
|
| PPN (Katalog-ID): |
NLM288702646 |
|---|
| LEADER | 01000naa a22002652 4500 | ||
|---|---|---|---|
| 001 | NLM288702646 | ||
| 003 | DE-627 | ||
| 005 | 20231225060920.0 | ||
| 007 | cr uuu---uuuuu | ||
| 008 | 231225s2018 xx |||||o 00| ||eng c | ||
| 024 | 7 | |a 10.3389/fpls.2018.01311 |2 doi | |
| 028 | 5 | 2 | |a pubmed24n0962.xml |
| 035 | |a (DE-627)NLM288702646 | ||
| 035 | |a (NLM)30233634 | ||
| 040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
| 041 | |a eng | ||
| 100 | 1 | |a Xu, Yang |e verfasserin |4 aut | |
| 245 | 1 | 0 | |a Genome-Wide Association Mapping of Starch Pasting Properties in Maize Using Single-Locus and Multi-Locus Models |
| 264 | 1 | |c 2018 | |
| 336 | |a Text |b txt |2 rdacontent | ||
| 337 | |a ƒaComputermedien |b c |2 rdamedia | ||
| 338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
| 500 | |a Date Revised 01.10.2020 | ||
| 500 | |a published: Electronic-eCollection | ||
| 500 | |a Citation Status PubMed-not-MEDLINE | ||
| 520 | |a Maize starch plays a critical role in food processing and industrial application. The pasting properties, the most important starch characteristics, have enormous influence on fabrication property, flavor characteristics, storage, cooking, and baking. Understanding the genetic basis of starch pasting properties will be beneficial for manipulation of starch properties for a given purpose. Genome-wide association studies (GWAS) are becoming a powerful tool for dissecting the complex traits. Here, we carried out GWAS for seven pasting properties of maize starch with a panel of 230 inbred lines and 145,232 SNPs using one single-locus method, genome-wide efficient mixed model association (GEMMA), and three multi-locus methods, FASTmrEMMA, FarmCPU, and LASSO. We totally identified 60 quantitative trait nucleotides (QTNs) for starch pasting properties with these four GWAS methods. FASTmrEMMA detected the most QTNs (29), followed by FarmCPU (19) and LASSO (12), GEMMA detected the least QTNs (7). Of these QTNs, seven QTNs were identified by more than one method simultaneously. We further investigated locations of these significantly associated QTNs for possible candidate genes. These candidate genes and significant QTNs provide the guidance for further understanding of molecular mechanisms of starch pasting properties. We also compared the statistical powers and Type I errors of the four GWAS methods using Monte Carlo simulations. The results suggest that the multi-locus method is more powerful than the single-locus method and a combination of these multi-locus methods could help improve the detection power of GWAS | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a GWAS | |
| 650 | 4 | |a maize | |
| 650 | 4 | |a multi-locus | |
| 650 | 4 | |a pasting properties | |
| 650 | 4 | |a starch | |
| 700 | 1 | |a Yang, Tiantian |e verfasserin |4 aut | |
| 700 | 1 | |a Zhou, Yao |e verfasserin |4 aut | |
| 700 | 1 | |a Yin, Shuangyi |e verfasserin |4 aut | |
| 700 | 1 | |a Li, Pengcheng |e verfasserin |4 aut | |
| 700 | 1 | |a Liu, Jun |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, Shuhui |e verfasserin |4 aut | |
| 700 | 1 | |a Yang, Zefeng |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, Chenwu |e verfasserin |4 aut | |
| 773 | 0 | 8 | |i Enthalten in |t Frontiers in plant science |d 2010 |g 9(2018) vom: 20., Seite 1311 |w (DE-627)NLM218083777 |x 1664-462X |7 nnns |
| 773 | 1 | 8 | |g volume:9 |g year:2018 |g day:20 |g pages:1311 |
| 856 | 4 | 0 | |u http://dx.doi.org/10.3389/fpls.2018.01311 |3 Volltext |
| 912 | |a GBV_USEFLAG_A | ||
| 912 | |a GBV_NLM | ||
| 951 | |a AR | ||
| 952 | |d 9 |j 2018 |b 20 |h 1311 | ||