To reduce the recalcitrance and enhance enzymatic activity, dilute H₂SO₄ pretreatment was carried out on Alamo switchgrass (Panicum virgatum). Ball-milled lignin was isolated from switchgrass before ...and after pretreatment. Its structure was characterized by ¹³C, HSQC, and ³¹P NMR spectroscopy. It was confirmed that ball-milled switchgrass lignin is of HGS type with a considerable amount of p-coumarate and felurate esters of lignin. The major ball-milled lignin interunit was the β-O-4 linkage, and a minor amount of phenylcoumarin, resinol, and spirodienone units were also present. As a result of the acid pretreatment, there was 36% decrease of β-O-4 linkage observed. In addition to these changes, the S/G ratio decreases from 0.80 to 0.53.
Key message
Genome-wide association analysis in CIMMYT’s association panel revealed new favorable native genomic variations in/nearby important genes such as hydroxylases and CCD1 that have potential ...for carotenoid biofortification in maize.
Genome-wide association studies (GWAS) have been used extensively to identify allelic variation for genes controlling important agronomic and nutritional traits in plants. Provitamin A (proVA) enhancing alleles of lycopene epsilon cyclase (
LCYE
) and β-carotene hydroxylase 1 (
CRTRB1
), previously identified through candidate-gene based GWAS, are currently used in CIMMYT’s maize breeding program. The objective of this study was to identify genes or genomic regions controlling variation for carotenoid concentrations in grain for CIMMYT’s carotenoid association mapping panel of 380 inbred maize lines, using high-density genome-wide platforms with ~476,000 SNP markers. Population structure effects were minimized by adjustments using principal components and kinship matrix with mixed models. Genome-wide linkage disequilibrium (LD) analysis indicated faster LD decay (3.9 kb;
r
2
= 0.1) than commonly reported for temperate germplasm, and therefore the possibility of achieving higher mapping resolution with our mostly tropical diversity panel. GWAS for various carotenoids identified
CRTRB1,
LCYE
and other key genes or genomic regions that govern rate-critical steps in the upstream pathway, such as
DXS1, GGPS1,
and
GGPS2
that are known to play important roles in the accumulation of precursor isoprenoids as well as downstream genes
HYD5
,
CCD1
, and
ZEP1
, which are involved in hydroxylation and carotenoid degradation. SNPs at or near all of these regions were identified and may be useful target regions for carotenoid biofortification breeding efforts in maize; for example a genomic region on chromosome 2 explained ~16 % of the phenotypic variance for β-carotene independently of
CRTRB1,
and a variant of
CCD1
that resulted in reduced β-cryptoxanthin degradation was found in lines that have previously been observed to have low proVA degradation rates.
Summary
Cloud computing is an innovative computing paradigm designed to provide a flexible and low‐cost way to deliver information technology services on demand over the Internet. Proper scheduling ...and load balancing of the resources are required for the efficient operations in the distributed cloud environment. Since cloud computing is growing rapidly and customers are demanding better performance and more services, scheduling and load balancing of the cloud resources have become very interesting and important area of research. As more and more consumers assign their tasks to cloud, service‐level agreements (SLAs) between consumers and providers are emerging as an important aspect. The proposed prediction model is based on the past usage pattern and aims to provide optimal resource management without the violations of the agreed service‐level conditions in cloud data centers. It considers SLA in both the initial scheduling stage and in the load balancing stage, and it looks into different objectives to achieve the minimum makespan, the minimum degree of imbalance, and the minimum number of SLA violations. The experimental results show the effectiveness of the proposed system compared with other state‐of‐the‐art algorithms.
Abstract
With progressive climate change and the associated increase in mean temperature, heat stress tolerance has emerged as one of the key traits in the product profile of the maize breeding ...pipeline for lowland tropics. The present study aims to identify the genomic regions associated with heat stress tolerance in tropical maize. An association mapping panel, called the heat tolerant association mapping (HTAM) panel, was constituted by involving a total of 543 tropical maize inbred lines from diverse genetic backgrounds, test-crossed and phenotyped across nine locations in South Asia under natural heat stress. The panel was genotyped using a genotyping-by-sequencing (GBS) platform. Considering the large variations in vapor pressure deficit (VPD) at high temperature (Tmax) across different phenotyping locations, genome-wide association study (GWAS) was conducted separately for each location. The individual location GWAS identified a total of 269 novel significant single nucleotide polymorphisms (SNPs) for grain yield under heat stress at a p value of < 10
–5
. A total of 175 SNPs were found in 140 unique gene models implicated in various biological pathway responses to different abiotic stresses. Haplotype trend regression (HTR) analysis of the significant SNPs identified 26 haplotype blocks and 96 single SNP variants significant across one to five locations. The genomic regions identified based on GWAS and HTR analysis considering genomic region x environment interactions are useful for breeding efforts aimed at developing heat stress resilient maize cultivars for current and future climatic conditions through marker-assisted introgression into elite genetic backgrounds and/or genome-wide selection.
Key message
Genome-wide association study (GWAS) on 923 maize lines and validation in bi-parental populations identified significant genomic regions for kernel-Zinc and-Iron in maize.
...Bio-fortification of maize with elevated Zinc (Zn) and Iron (Fe) holds considerable promise for alleviating under-nutrition among the world’s poor. Bio-fortification through molecular breeding could be an economical strategy for developing nutritious maize, and hence in this study, we adopted GWAS to identify markers associated with high kernel-Zn and Fe in maize and subsequently validated marker-trait associations in independent bi-parental populations. For GWAS, we evaluated a diverse maize association mapping panel of 923 inbred lines across three environments and detected trait associations using high-density Single nucleotide polymorphism (SNPs) obtained through genotyping-by-sequencing. Phenotyping trials of the GWAS panel showed high heritability and moderate correlation between kernel-Zn and Fe concentrations. GWAS revealed a total of 46 SNPs (Zn-20 and Fe-26) significantly associated (
P
≤ 5.03 × 10
−05
) with kernel-Zn and Fe concentrations with some of these associated SNPs located within previously reported QTL intervals for these traits. Three double-haploid (DH) populations were developed using lines identified from the panel that were contrasting for these micronutrients. The DH populations were phenotyped at two environments and were used for validating significant SNPs (
P
≤ 1 × 10
−03
) based on single marker QTL analysis. Based on this analysis, 11 (Zn) and 11 (Fe) SNPs were found to have significant effect on the trait variance (
P
≤ 0.01,
R
2
≥ 0.05) in at least one bi-parental population. These findings are being pursued in the kernel-Zn and Fe breeding program, and could hold great value in functional analysis and possible cloning of high-value genes for these traits in maize.
ABSTRACT
Genomic selection incorporates all the available marker information into a model to predict genetic values of breeding progenies for selection. The objective of this study was to estimate ...genetic gains in grain yield from genomic selection (GS) in eight bi‐parental maize populations under managed drought stress environments. In each population, 148 to 300 F2:3 (C0) progenies were derived and crossed to a single‐cross tester from a complementary heterotic group. The resulting testcrosses of each population were evaluated under two to four managed drought stress and three to four well‐watered conditions in different locations and genotyped with 191 to 286 single nucleotide polymorphism (SNP) markers. The top 10% families were selected from C0 using a phenotypic selection index and were intermated to form C1. Selections both at C1 and C2 were based on genomic estimated breeding values (GEBVs). The best lines from C0 were also advanced using a pedigree selection scheme. For genetic gain studies, a total of 55 entries representing the eight populations were crossed to a single‐cross tester, and evaluated in four managed drought stress environments. Each population was represented by bulk seed containing equal amounts of seed of C0, C1, C2, C3, parents, F1s, and lines developed via pedigree selection. Five commercial checks were included for comparison. The average gain from genomic selection per cycle across eight populations was 0.086 Mg ha–1. The average grain yield of C3–derived hybrids was significantly higher than that of hybrids derived from C0. Hybrids derived from C3 produced 7.3% (0.176 Mg ha–1) higher grain yield than those developed through the conventional pedigree breeding method. The study demonstrated that genomic selection is more effective than pedigree‐based conventional phenotypic selection for increasing genetic gains in grain yield under drought stress in tropical maize.
Background: Economic feasibility and sustainability of lignocellulosic ethanol production requires the development of robust microorganisms that can efficiently degrade and convert plant biomass to ...ethanol. The anaerobic thermophilic bacterium Clostridium thermocellum is a candidate microorganism as it is capable of hydrolyzing cellulose and fermenting the hydrolysis products to ethanol and other metabolites. C. thermocellum achieves efficient cellulose hydrolysis using multiprotein extracellular enzymatic complexes, termed cellulosomes. Methodology/Principal Findings: In this study, we used quantitative proteomics (multidimensional LC-MS/MS and 15N-metabolic labeling) to measure relative changes in levels of cellulosomal subunit proteins (per CipA scaffoldin basis) when C. thermocellum ATCC 27405 was grown on a variety of carbon sources dilute-acid pretreated switchgrass, cellobiose, amorphous cellulose, crystalline cellulose (Avicel) and combinations of crystalline cellulose with pectin or xylan or both. Cellulosome samples isolated from cultures grown on these carbon sources were compared to 15N labeled cellulosome samples isolated from crystalline cellulose-grown cultures. In total from all samples, proteomic analysis identified 59 dockerin- and 8 cohesin-module containing components, including 16 previously undetected cellulosomal subunits. Many cellulosomal components showed differential protein abundance in the presence of non-cellulose substrates in the growth medium. Cellulosome samples from amorphous cellulose, cellobiose and pretreated switchgrass-grown cultures displayed the most distinct differences in composition as compared to cellulosome samples from crystalline cellulose-grown cultures. While Glycoside Hydrolase Family 9 enzymes showed increased levels in the presence of crystalline cellulose, and pretreated switchgrass, in particular, GH5 enzymes showed increased levels in response to the presence of cellulose in general, amorphous or crystalline. Conclusions/Significance: Overall, the quantitative results suggest a coordinated substrate-specific regulation of cellulosomal subunit composition in C. thermocellum to better suit the organism's needs for growth under different conditions. To date, this study provides the most comprehensive comparison of cellulosomal compositional changes in C. thermocellum in response to different carbon sources. Such studies are vital to engineering a strain that is best suited to grow on specific substrates of interest and provide the building blocks for constructing designer cellulosomes with tailored enzyme composition for industrial ethanol production.
Maize is rapidly replacing traditionally cultivated dual purpose crops of South Asia, primarily due to the better economic remuneration. This has created an impetus for improving maize for both grain ...productivity and stover traits. Molecular techniques can largely assist breeders in determining approaches for effectively integrating stover trait improvement in their existing breeding pipeline. In the current study we identified a suite of potential genomic regions associated to the two major stover quality traits-in-vitro organic matter digestibility (IVOMD) and metabolizable energy (ME) through genome wide association study. However, considering the fact that the loci identified for these complex traits all had smaller effects and accounted only a small portion of phenotypic variation, the effectiveness of following a genomic selection approach for these traits was evaluated. The testing set consists of breeding lines recently developed within the program and the training set consists of a panel of lines from the working germplasm comprising the founder lines of the newly developed breeding lines and also an unrelated diversity set. The prediction accuracy as determined by the Pearson's correlation coefficient between observed and predicted values of these breeding lines were high even at lower marker density (200 random SNPs), when the training and testing set were related. However, the accuracies were dismal, when there was no relationship between the training and the testing set.
To increase genetic gain for tolerance to drought, we aimed to identify environmentally stable QTL in
and testcross combination under well-watered (WW) and drought stressed (DS) conditions and ...evaluate the possible deployment of QTL using marker assisted and/or genomic selection (QTL/GS-MAS). A total of 169 doubled haploid lines derived from the cross between CML495 and LPSC7F64 and 190 testcrosses (tester CML494) were evaluated in a total of 11 treatment-by-population combinations under WW and DS conditions. In response to DS, grain yield (GY) and plant height (PHT) were reduced while time to anthesis and the anthesis silking interval (ASI) increased for both lines and hybrids. Forty-eight QTL were detected for a total of nine traits. The allele derived from CML495 generally increased trait values for anthesis, ASI, PHT, the normalized difference vegetative index (NDVI) and the green leaf area duration (GLAD; a composite trait of NDVI, PHT and senescence) while it reduced trait values for leaf rolling and senescence. The LOD scores for all detected QTL ranged from 2.0 to 7.2 explaining 4.4 to 19.4% of the observed phenotypic variance with R
ranging from 0 (GY, DS, lines) to 37.3% (PHT, WW, lines). Prediction accuracy of the model used for genomic selection was generally higher than phenotypic variance explained by the sum of QTL for individual traits indicative of the polygenic control of traits evaluated here. We therefore propose to use QTL-MAS in forward breeding to enrich the allelic frequency for a few desired traits with strong additive QTL in early selection cycles while GS-MAS could be used in more mature breeding programs to additionally capture alleles with smaller additive effects.
ABSTRACT
Genomic selection offers great potential for increasing the rate of genetic improvement in plant breeding programs. This research used simulation to evaluate the effectiveness of different ...strategies for genotyping and phenotyping to enable genomic selection in early generation individuals (e.g., F2) in breeding programs involving biparental or similar (e.g., backcross or top cross) populations. By using phenotypes that were previously collected in other biparental populations, selection decisions could be made without waiting for phenotypes that pertain directly to the selection candidate to be collected, a process that would take at least three growing seasons. If these phenotypes were collected in biparental populations that were closely related to the selection candidates, only a small number of markers (e.g., 200–500) and a small number of phenotypes (e.g., 1000) were needed to achieve effective accuracy of estimated breeding values. If these phenotypes were collected in biparental populations that were not closely related to the selection candidates, as many as 10,000 markers and 5000 to 20,000 phenotypes were needed. Increasing marker density beyond 10,000 markers did not show benefit and in some scenarios reduced the accuracy of prediction. This study provides a guide, enabling resource allocation to be optimized between genotyping and phenotyping investment dependent on the population under development.