Polymorphisms in monolignol biosynthetic genes are associated with biomass yield and agronomic traits in European maize (Zea mays L.)

<p>Abstract</p> <p>Background</p> <p>Reduced lignin content leads to higher cell wall digestibility and, therefore, better forage quality and increased conversion of lignocellulosic biomass into ethanol. However, reduced lignin content might lead to weaker stalks, lodging, and reduced biomass yield. Genes encoding enzymes involved in cell wall lignification have been shown to influence both cell wall digestibility and yield traits.</p> <p>Results</p> <p>In this study, associations between monolignol biosynthetic genes and plant height (PHT), days to silking (DTS), dry matter content (DMC), and dry matter yield (DMY) were identified by using a panel of 39 European elite maize lines. In total, 10 associations were detected between polymorphisms or tight linkage disequilibrium (LD) groups within the <it>COMT</it>, <it>CCoAOMT2</it>, <it>4CL1</it>, <it>4CL2</it>, <it>F5H</it>, and <it>PAL </it>genomic fragments, respectively, and the above mentioned traits. The phenotypic variation explained by these polymorphisms or tight LD groups ranged from 6% to 25.8% in our line collection. Only <it>4CL1 </it>and <it>F5H </it>were found to have polymorphisms associated with both yield and forage quality related characters. However, no pleiotropic polymorphisms affecting both digestibility of neutral detergent fiber (DNDF), and PHT or DMY were discovered, even under less stringent statistical conditions.</p> <p>Conclusion</p> <p>Due to absence of pleiotropic polymorphisms affecting both forage yield and quality traits, identification of optimal monolignol biosynthetic gene haplotype(s) combining beneficial quantitative trait polymorphism (QTP) alleles for both quality and yield traits appears possible within monolignol biosynthetic genes. This is beneficial to maximize forage and bioethanol yield per unit land area.</p

Characterization of phenylpropanoid pathway genes within European maize (Zea mays L.) inbreds

<p>Abstract</p> <p>Background</p> <p>Forage quality of maize is influenced by both the content and structure of lignins in the cell wall. Biosynthesis of monolignols, constituting the complex structure of lignins, is catalyzed by enzymes in the phenylpropanoid pathway.</p> <p>Results</p> <p>In the present study we have amplified partial genomic fragments of six putative phenylpropanoid pathway genes in a panel of elite European inbred lines of maize (<it>Zea mays </it>L.) contrasting in forage quality traits. Six loci, encoding C4H, 4CL1, 4CL2, C3H, F5H, and CAD, displayed different levels of nucleotide diversity and linkage disequilibrium (LD) possibly reflecting different levels of selection. Associations with forage quality traits were identified for several individual polymorphisms within the <it>4CL1</it>, <it>C3H</it>, and <it>F5H </it>genomic fragments when controlling for both overall population structure and relative kinship. A 1-bp indel in <it>4CL1 </it>was associated with <it>in vitro </it>digestibility of organic matter (IVDOM), a non-synonymous SNP in <it>C3H </it>was associated with IVDOM, and an intron SNP in <it>F5H </it>was associated with neutral detergent fiber. However, the <it>C3H </it>and <it>F5H </it>associations did not remain significant when controlling for multiple testing.</p> <p>Conclusion</p> <p>While the number of lines included in this study limit the power of the association analysis, our results imply that genetic variation for forage quality traits can be mined in phenylpropanoid pathway genes of elite breeding lines of maize.</p

Polymorphisms in O-methyltransferase genes are associated with stover cell wall digestibility in European maize (Zea mays L.)

<p>Abstract</p> <p>Background</p> <p>OMT (O-methyltransferase) genes are involved in lignin biosynthesis, which relates to stover cell wall digestibility. Reduced lignin content is an important determinant of both forage quality and ethanol conversion efficiency of maize stover.</p> <p>Results</p> <p>Variation in genomic sequences coding for <it>COMT, CCoAOMT1</it>, and <it>CCoAOMT2 </it>was analyzed in relation to stover cell wall digestibility for a panel of 40 European forage maize inbred lines, and re-analyzed for a panel of 34 lines from a published French study. Different methodologies for association analysis were performed and compared. Across association methodologies, a total number of 25, 12, 1, 6 <it>COMT </it>polymorphic sites were significantly associated with DNDF, OMD, NDF, and WSC, respectively. Association analysis for <it>CCoAOMT1 </it>and <it>CCoAOMT2 </it>identified substantially fewer polymorphic sites (3 and 2, respectively) associated with the investigated traits. Our re-analysis on the 34 lines from a published French dataset identified 14 polymorphic sites significantly associated with cell wall digestibility, two of them were consistent with our study. Promising polymorphisms putatively causally associated with variability of cell wall digestibility were inferred from the total number of significantly associated SNPs/Indels.</p> <p>Conclusions</p> <p>Several polymorphic sites for three O-methyltransferase loci were associated with stover cell wall digestibility. All three tested genes seem to be involved in controlling DNDF, in particular <it>COMT</it>. Thus, considerable variation among <it>Bm3 </it>wildtype alleles can be exploited for improving cell-wall digestibility. Target sites for functional markers were identified enabling development of efficient marker-based selection strategies.</p

Genomic prediction within and across maize landrace derived populations using haplotypes

Genomic prediction (GP) using haplotypes is considered advantageous compared to GP solely reliant on single nucleotide polymorphisms (SNPs), owing to haplotypes’ enhanced ability to capture ancestral information and their higher linkage disequilibrium with quantitative trait loci (QTL). Many empirical studies supported the advantages of haplotype-based GP over SNP-based approaches. Nevertheless, the performance of haplotype-based GP can vary significantly depending on multiple factors, including the traits being studied, the genetic structure of the population under investigation, and the particular method employed for haplotype construction. In this study, we compared haplotype and SNP based prediction accuracies in four populations derived from European maize landraces. Populations comprised either doubled haploid lines (DH) derived directly from landraces, or gamete capture lines (GC) derived from crosses of the landraces with an inbred line. For two different landraces, both types of populations were generated, genotyped with 600k SNPs and phenotyped as lines per se for five traits. Our study explores three prediction scenarios: (i) within each of the four populations, (ii) across DH and GC populations from the same landrace, and (iii) across landraces using either DH or GC populations. Three haplotype construction methods were evaluated: 1. fixed-window blocks (FixedHB), 2. LD-based blocks (HaploView), and 3. IBD-based blocks (HaploBlocker). In within population predictions, FixedHB and HaploView methods performed as well as or slightly better than SNPs for all traits. HaploBlocker improved accuracy for certain traits but exhibited inferior performance for others. In prediction across populations, the parameter setting from HaploBlocker which controls the construction of shared haplotypes between populations played a crucial role for obtaining optimal results. When predicting across landraces, accuracies were low for both, SNP and haplotype approaches, but for specific traits substantial improvement was observed with HaploBlocker. This study provides recommendations for optimal haplotype construction and identifies relevant parameters for constructing haplotypes in the context of genomic prediction

Identification of candidate genes associated with cell wall digestibility and eQTL (expression quantitative trait loci) analysis in a Flint × Flint maize recombinant inbred line population

Abstract Background Cell-wall digestibility is the major target for improving the feeding value of forage maize. An understanding of the molecular basis for cell-wall digestibility is crucial towards breeding of highly digestible maize. Results 865 candidate ESTs for cell-wall digestibility were selected according to the analysis of expression profiles in 1) three sets of brown-midrib isogenic lines in the genetic background of inbreds 1332 (1332 and 1332 bm3), 5361 (5361 and 5361 bm3), and F2 (F2, F2 bm1, F2 bm2, and F2 bm3), 2) the contrasting extreme lines of FD (Flint × Dent, AS08 × AS 06), DD1 (Dent × Dent, AS11 × AS09), and DD2 (Dent × Dent, AS29 × AS30) mapping populations, and 3) two contrasting isogenic inbreds, AS20 and AS21. Out of those, 439 ESTs were assembled on our "Forage Quality Array", a small microarray specific for cell wall digestibility related experiments. Transcript profiles of 40 lines of a Flint × Flint population were monitored using the Forage Quality Array, which were contrasting for cell wall digestibility. Using t-tests (p < 0.01), the expression patterns of 102 ESTs were significantly different between high and low quality groups. Using interval mapping, eQTL (LOD ≥ 2.4) were detected for 20% (89 of 439) of the spotted ESTs. On average, these eQTL explained 39% of the transcription variation of the corresponding ESTs. Only 26% (23 of 89) ESTs detected a single eQTL. eQTL hotspots, containing greater than 5% of the total number of eQTL, were located in chromosomal bins 1.07, 1.12, 3.05, 8.03, and 9.04, respectively. Bin 3.05 was co-localized with a cell-wall digestibility related QTL cluster. Conclusion 102 candidate genes for cell-wall digestibility were validated by genetical genomics approach. Although the cDNA array highlights gene types (the tested gene and any close family members), trans-acting factors or metabolic bottlenecks seem to play the major role in controlling heritable variation of gene expression related to cell-wall digestibility, since no in silico mapped ESTs were in the same location as their own eQTL. Transcriptional variation was generally found to be oligogenic rather than monogenic inherited due to only 26% ESTs detected a single eQTL in the present study. One eQTL hotspot was co-localized with cell wall digestibility related QTL cluster on bins 3.05, implying that in this case the gene(s) underlying QTL and eQTL are identical. As the field of genetical genomics develops, it is expected to significantly improve our knowledge about complex traits, such as cell wall degradability. Comprehensive knowledge of the lignin pathway and cell wall biogenesis will allow plant breeders to choose the best genomic targets controlling these characters, for improving forage digestibility through genetic engineering or marker-assisted selection

Two major quantitative trait loci controlling the number of seminal roots in maize co-map with the root developmental genes rtcs and rum1

The genetic dissection of root architecture and functions allows for a more effective and informed design of novel root ideotypes and paves the way to evaluate their effects on crop resilience to a number of abiotic stresses. In maize, limited attention has been devoted to the genetic analysis of root architecture diversity at the early stage. The difference in embryonic (including seminal and primary) root architecture between the maize reference line B73 (which mostly develops three seminal roots) and the landrace Gasp\ue9 Flint (with virtually no seminal roots) was genetically dissected using a collection of introgression lines grown in paper rolls and pots. Quantitative trait locus (QTL) analysis identified three QTLs controlling seminal root number (SRN) on chromosome bins 1.02, 3.07, and 8.04-8.05, which collectively explained 66% of the phenotypic variation. In all three cases, Gasp\ue9 Flint contributed the allele for lower SRN. Primary root dry weight was negatively correlated with SRN (r=-0.52), and QTLs for primary root size co-mapped with SRN QTLs, suggesting a pleiotropic effect of SRN QTLs on the primary root, most probably caused by competition for seed resources. Interestingly, two out of three SRN QTLs co-mapped with the only two known maize genes (rtcs and rum1) affecting the number of seminal roots. The strong additive effect of the three QTLs and the development of near isogenic lines for each QTL in the elite B73 background provide unique opportunities to characterize functionally the genes involved in root development and to evaluate how root architecture affects seedling establishment, early development, and eventually yield in maize