Genetics and quantitative trait loci mapping of biomass yield and quality traits in maize (Zea mays L.) for forage utilization

Genetic studies and quantitative traits loci (QTL) mapping on maize (Zea mays L.) for forage yield and quality traits for animal feed are lacking, especially those conducted in the tropical region. Efficient breeding and selection strategies of maize for forage utilization require sound knowledge an...

Full description

Saved in:
Bibliographic Details
Main Author: Naharudin, Nazatul Shima
Format: Thesis
Language:English
Published: 2017
Subjects:
Online Access:http://psasir.upm.edu.my/id/eprint/70430/1/FP%202017%2041%20IR.pdf
Tags: Add Tag
No Tags, Be the first to tag this record!
id my-upm-ir.70430
record_format uketd_dc
institution Universiti Putra Malaysia
collection PSAS Institutional Repository
language English
topic Genetics - Statistical methods
Gene mapping
Corn
spellingShingle Genetics - Statistical methods
Gene mapping
Corn
Naharudin, Nazatul Shima
Genetics and quantitative trait loci mapping of biomass yield and quality traits in maize (Zea mays L.) for forage utilization
description Genetic studies and quantitative traits loci (QTL) mapping on maize (Zea mays L.) for forage yield and quality traits for animal feed are lacking, especially those conducted in the tropical region. Efficient breeding and selection strategies of maize for forage utilization require sound knowledge and understanding of the genetics associated with biomass yield and forage quality. A series of experiments and analyses were conducted to elucidate important genetic parameters and to map QTLs for biomass yield and forage quality traits in maize. Two crosses between inbred lines (CML 152 × CML 383 and CML 491 × CML 331) with contrasting values for biomass yield and quality traits were made to produce two F2 populations. Heterosis, inbreeding depression and broad-sense heritability of 16 biomass yield and forage quality traits were estimated from evaluation of the hybrids, the F2 populations and the parents involved. In general, Cross 1 showed higher heterosis and inbreeding depression for biomass yield traits compared to Cross 2. The broad sense heritability estimates in both populations were moderate to high for plant height, dry leaf yield, protein content and acid detergent lignin, indicating that these traits can be used as the selection criteria. Predicted genetic gain from selection were found high for fresh and dry biomass yield and moderate for plant height and protein content in both populations. Correlation analysis on biomass yield and quality traits revealed that all biomass yield components were significantly correlated. For forage quality traits, moderate positive correlations were found among the traits related to cell wall composition (neutral and acid detergent fiber and acid detergent lignin contents). Moreover, these traits were also found to be moderately correlated with dry plant yield. Mapping of QTLs linked to biomass yield and forage quality traits was done on two F2 mapping populations derived from CML 152 × CML 383 and CML 491 × CML 331 crosses. Out of 180 SSR markers used in screening, 61 markers were polymorphic in Cross 1 and 62 markers were polymorphic in Cross 2, which were then used to construct linkage maps. Ten linkage groups were detected in both populations with the size of 822.2 cM in Population 1 and 740.5 cM in Population 2. Data were analyzed using single marker regression analysis and composite interval mapping analysis to detect markers and regions with significant QTLs. For biomass yield traits, eight QTLs were identified in Population 1 and 10 QTLs were detected in Population 2 based on single marker regression analysis. When combined in multiple loci model, these QTLs accounted for up to 30.41% (Population 1) and 85.89% (Population 2) of the phenotypic variation explained (PVE). QTLs on Chromosomes 1 and 8 in Population 1, and QTLs on Chromosomes 1 and 9 in Population 2 were associated with multiple traits, suggesting the presence of pleiotropic effects. Composite interval mapping analysis detected three intervals on Chromosomes 1 and 8 in Population 1 and four on Chromosomes 1, 3, 4 and 9 in Population 2 associated with biomass yield traits, some of which coincide with the markers with high PVE in single marker regression analysis. Epistatic interactions among the loci for plant height were identified, contributing 13.02% to PVE. Most of the QTLs detected for biomass yield in Population 1 were found to have dominance effects, while QTLs in Population 2 had additive effects, thus explaining the higher expressions of heterosis for biomass yield traits in Population 1 compared to Population 2. For forage quality traits, in Population 1, single marker regression detected three putative QTLs to be associated with protein content on Chromosomes 1 and 2, and eight putative QTLs for cell wall components on Chromosomes 3, 5, 8, and 9. In Population 2, four putative QTLs were detected for protein content, whereas for cell wall components, one QTL was detected for neutral detergent fiber, acid detergent fiber and acid detergent lignin contents, respectively. Composite interval mapping analysis revealed three QTLs with main effects and epistatic interactions on Chromosomes 1, 6 and 8 for acid detergent lignin in Population 1. Although no main effect QTLs were detected for neutral detergent fiber and acid detergent fiber, regions with epistatic interactions were detected for these traits. QTLs for protein content were only detected in Population 2 and none in Population 1. Some of the QTLs detected for biomass yield were also present in other inbred lines in the germplasm collection, and could be confirmed by association mapping analysis. The identified QTLs could be utilized in marker assisted breeding programs or high resolution mapping after QTL validation in various environmental condition using different populations for future forage maize improvement in the tropical region.
format Thesis
qualification_level Doctorate
author Naharudin, Nazatul Shima
author_facet Naharudin, Nazatul Shima
author_sort Naharudin, Nazatul Shima
title Genetics and quantitative trait loci mapping of biomass yield and quality traits in maize (Zea mays L.) for forage utilization
title_short Genetics and quantitative trait loci mapping of biomass yield and quality traits in maize (Zea mays L.) for forage utilization
title_full Genetics and quantitative trait loci mapping of biomass yield and quality traits in maize (Zea mays L.) for forage utilization
title_fullStr Genetics and quantitative trait loci mapping of biomass yield and quality traits in maize (Zea mays L.) for forage utilization
title_full_unstemmed Genetics and quantitative trait loci mapping of biomass yield and quality traits in maize (Zea mays L.) for forage utilization
title_sort genetics and quantitative trait loci mapping of biomass yield and quality traits in maize (zea mays l.) for forage utilization
granting_institution Universiti Putra Malaysia
publishDate 2017
url http://psasir.upm.edu.my/id/eprint/70430/1/FP%202017%2041%20IR.pdf
_version_ 1747812836642390016
spelling my-upm-ir.704302019-08-16T07:36:30Z Genetics and quantitative trait loci mapping of biomass yield and quality traits in maize (Zea mays L.) for forage utilization 2017-06 Naharudin, Nazatul Shima Genetic studies and quantitative traits loci (QTL) mapping on maize (Zea mays L.) for forage yield and quality traits for animal feed are lacking, especially those conducted in the tropical region. Efficient breeding and selection strategies of maize for forage utilization require sound knowledge and understanding of the genetics associated with biomass yield and forage quality. A series of experiments and analyses were conducted to elucidate important genetic parameters and to map QTLs for biomass yield and forage quality traits in maize. Two crosses between inbred lines (CML 152 × CML 383 and CML 491 × CML 331) with contrasting values for biomass yield and quality traits were made to produce two F2 populations. Heterosis, inbreeding depression and broad-sense heritability of 16 biomass yield and forage quality traits were estimated from evaluation of the hybrids, the F2 populations and the parents involved. In general, Cross 1 showed higher heterosis and inbreeding depression for biomass yield traits compared to Cross 2. The broad sense heritability estimates in both populations were moderate to high for plant height, dry leaf yield, protein content and acid detergent lignin, indicating that these traits can be used as the selection criteria. Predicted genetic gain from selection were found high for fresh and dry biomass yield and moderate for plant height and protein content in both populations. Correlation analysis on biomass yield and quality traits revealed that all biomass yield components were significantly correlated. For forage quality traits, moderate positive correlations were found among the traits related to cell wall composition (neutral and acid detergent fiber and acid detergent lignin contents). Moreover, these traits were also found to be moderately correlated with dry plant yield. Mapping of QTLs linked to biomass yield and forage quality traits was done on two F2 mapping populations derived from CML 152 × CML 383 and CML 491 × CML 331 crosses. Out of 180 SSR markers used in screening, 61 markers were polymorphic in Cross 1 and 62 markers were polymorphic in Cross 2, which were then used to construct linkage maps. Ten linkage groups were detected in both populations with the size of 822.2 cM in Population 1 and 740.5 cM in Population 2. Data were analyzed using single marker regression analysis and composite interval mapping analysis to detect markers and regions with significant QTLs. For biomass yield traits, eight QTLs were identified in Population 1 and 10 QTLs were detected in Population 2 based on single marker regression analysis. When combined in multiple loci model, these QTLs accounted for up to 30.41% (Population 1) and 85.89% (Population 2) of the phenotypic variation explained (PVE). QTLs on Chromosomes 1 and 8 in Population 1, and QTLs on Chromosomes 1 and 9 in Population 2 were associated with multiple traits, suggesting the presence of pleiotropic effects. Composite interval mapping analysis detected three intervals on Chromosomes 1 and 8 in Population 1 and four on Chromosomes 1, 3, 4 and 9 in Population 2 associated with biomass yield traits, some of which coincide with the markers with high PVE in single marker regression analysis. Epistatic interactions among the loci for plant height were identified, contributing 13.02% to PVE. Most of the QTLs detected for biomass yield in Population 1 were found to have dominance effects, while QTLs in Population 2 had additive effects, thus explaining the higher expressions of heterosis for biomass yield traits in Population 1 compared to Population 2. For forage quality traits, in Population 1, single marker regression detected three putative QTLs to be associated with protein content on Chromosomes 1 and 2, and eight putative QTLs for cell wall components on Chromosomes 3, 5, 8, and 9. In Population 2, four putative QTLs were detected for protein content, whereas for cell wall components, one QTL was detected for neutral detergent fiber, acid detergent fiber and acid detergent lignin contents, respectively. Composite interval mapping analysis revealed three QTLs with main effects and epistatic interactions on Chromosomes 1, 6 and 8 for acid detergent lignin in Population 1. Although no main effect QTLs were detected for neutral detergent fiber and acid detergent fiber, regions with epistatic interactions were detected for these traits. QTLs for protein content were only detected in Population 2 and none in Population 1. Some of the QTLs detected for biomass yield were also present in other inbred lines in the germplasm collection, and could be confirmed by association mapping analysis. The identified QTLs could be utilized in marker assisted breeding programs or high resolution mapping after QTL validation in various environmental condition using different populations for future forage maize improvement in the tropical region. Genetics - Statistical methods Gene mapping Corn 2017-06 Thesis http://psasir.upm.edu.my/id/eprint/70430/ http://psasir.upm.edu.my/id/eprint/70430/1/FP%202017%2041%20IR.pdf text en public doctoral Universiti Putra Malaysia Genetics - Statistical methods Gene mapping Corn