Simultaneous Dissection of Grain Carotenoid Levels and Kernel Color in Biparental Maize Populations with Yellow-to-Orange Grain

ABSTRACT Maize enriched in provitamin A carotenoids could be key in combatting vitamin A deficiency in human populations relying on maize as a food staple. Consumer studies indicate that orange maize may be regarded as novel and preferred. This study identifies genes of relevance for grain carotenoid concentrations and kernel color, through simultaneous dissection of these traits in 10 families of the U.S. maize nested association mapping panel that have yellow to orange grain. Quantitative trait loci (QTL) were identified via joint-linkage analysis, with phenotypic variation explained for individual kernel color QTL ranging from 2.4 to 17.5%. These QTL were cross-analyzed with significant marker-trait associations in a genome-wide association study that utilized ∼27 million variants. Nine genes were identified: four encoding activities upstream of the core carotenoid pathway, one at the pathway branchpoint, three within the α- or β-pathway branches, and one encoding a carotenoid cleavage dioxygenase. Of these, three exhibited significant pleiotropy between kernel color and one or more carotenoid traits. Kernel color exhibited moderate positive correlations with β-branch and total carotenoids and negligible correlations with α-branch carotenoids. These findings can be leveraged to simultaneously achieve desirable kernel color phenotypes and increase concentrations of provitamin A and other priority carotenoids.

Genomic Selection and Genome-Wide Association Studies for Grain Protein Content Stability in a Nested Association Mapping Population of Wheat

Grain protein content (GPC) is controlled by complex genetic systems and their interactions and is an important quality determinant for hard spring wheat as it has a positive effect on bread and pasta quality. GPC is variable among genotypes and strongly influenced by the environment. Thus, understanding the genetic control of wheat GPC and identifying genotypes with improved stability is an important breeding goal. The objectives of this research were to identify genetic backgrounds with less variation for GPC across environments and identify quantitative trait loci (QTLs) controlling the stability of GPC. A spring wheat nested association mapping (NAM) population of 650 recombinant inbred lines (RIL) derived from 26 diverse founder parents crossed to one common parent, ‘Berkut’, was phenotyped over three years of field trials (2014–2016). Genomic selection models were developed and compared based on predictions of GPC and GPC stability. After observing variable genetic control of GPC within the NAM population, seven RIL families displaying reduced marker-by-environment interaction were selected based on a stability index derived from a Finlay–Wilkinson regression. A genome-wide association study identified eighteen significant QTLs for GPC stability with a Bonferroni-adjusted p-value < 0.05 using four different models and out of these eighteen QTLs eight were identified by two or more GWAS models simultaneously. This study also demonstrated that genome-wide prediction of GPC with ridge regression best linear unbiased estimates reached up to r = 0.69. Genomic selection can be used to apply selection pressure for GPC and improve genetic gain for GPC.

Identification and Molecular Mapping of a Major Quantitative Trait Locus Underlying Branch Angle in Soybean

Soybean branch angle is a critical architectural trait that affects many other traits of agronomic importance associated with the plant’s productivity and grain yield, and is thus a vital consideration in soybean breeding. However, the genetic basis for modulating this important trait in soybean and many other crops remain unknown. Previously, we developed a recombinant inbred line (RIL) population derived from a cross between a domesticated soybean (Glycine max) variety, Williams 82, and a wild soybean (Glycine soja) accession, PI 479752, and observed drastic variation in plant architecture including branch angle among individual RILs. In this study, one of the RILs possessing extremely wide branch angle (WBA) was crossed with an elite soybean cultivar (LD00-3309) possessing narrow branch angle (NBA) to produce an F2 population composed of 147 plants and F2-derived F3 families for inheritance analysis and QTL mapping. We found that branch angle is controlled by a major QTL located on chromosome 19, designated qGmBa1, and that WBA – derived from the wild soybean accession – is dominant over NBA. This locus was also detected as a major one underlying branch angle by QTL mapping using a subset of the soybean nested association mapping (SoyNAM) population composed of 140 RILs, which were derived from a cross between a landrace, PI 437169B, possessing WBA and an elite variety, IA3023, possessing NBA. Molecular markers located in the QTL region defined by both mapping populations can be used for marker-assisted selection of branch angle in soybean breeding.

Natural variation further increases resilience of sorghum bred for chronically drought–prone environments

Climate–change–associated shifts in rainfall distribution together with a looming worldwide water crisis make drought resilience of central importance to food security. Even for relatively drought resilient crops such as sorghum, moisture stress is nonetheless one of the major constraints for production. Here, we explore the potential to use natural genetic variation to build on the inherent drought tolerance of an elite cultivar (Teshale) bred for Ethiopian conditions including chronic drought, evaluating a backcross nested-association mapping (BC–NAM) population using 12 diverse founder lines crossed with Teshale under three drought-prone environments in Ethiopia. All twelve populations averaged higher head exsertion and lower leaf senescence than the recurrent parent in the two highest-stress environments, reflecting new drought resilience mechanisms from the donors. A total of 154 QTLs were detected for eight drought responsive traits – the validity of these were supported in that 100 (64.9%) overlapped with QTLs previously detected for the same traits, concentrated in regions previously associated with ′stay-green′ traits as well as the flowering regulator Ma6 and drought resistant gene P5CS2. Allele effects show that some favorable alleles are already present in the Ethiopian cultivar, however the exotic donors offer rich scope for increasing drought resilience. Using model-selected SNPs associated with eight traits in this study and three in a companion study, phenotypic prediction accuracies for grain yield were equivalent to genome-wide SNPs and were significantly better than random SNPs, indicating that these studied traits are predictive of sorghum grain yield. Rich scope for improving drought resilience even in cultivars bred for drought–prone regions, together with phenotypic prediction accuracy for grain yield, provides a foundation to enhance food security in drought-prone areas like the African Sahel.

New adaptive peaks for crops – an example from improvement of drought-resilience of sorghum in Ethiopia

As the center of diversity for sorghum [Sorghum bicolor (L.) Moench], elite cultivars selected in Ethiopia are of central importance to sub-Saharan food security. Despite being presumably well adapted to their center of diversity, elite Ethiopian sorghums nonetheless experience constraints to productivity, for example associated with shifting rainfall patterns associated with climate change. A sorghum backcross nested association mapping (BC-NAM) population developed by crossing thirteen diverse lines pre-identified to have various drought resilience mechanisms, with an Ethiopian elite cultivar, Teshale, was tested under three rain-fed environments in Ethiopia. 27, 15, and 15 QTLs with predominantly small additive effects were identified for days to flowering, days to maturity, and plant height, respectively. Many associations detected in this study corresponded closely to known or candidate genes or previously mapped QTLs, supporting their validity. Field tests show drought resilience to be improved by incorporation of adaptations from the diverse donor lines. The expectation that genotypes such as Teshale from near the center of diversity tend to have a history of strong balancing selection, with novel variations more likely to persist in small marginal populations, was strongly supported in that for these three traits, nearly equal numbers of alleles from the donor lines conferred increases and decreases in phenotype relative to the Teshale allele. Such rich variation provides a foundation for selection to traverse a 'valley' of reduced yield and arrive at a new 'adaptive peak', exemplifying the nature of efforts that may be necessary to adapt many crops to new climate extremes.

Footprints of Selection Derived From Temporal Heterozygosity Patterns in a Barley Nested Association Mapping Population

Nowadays, genetic diversity more than ever represents a key driver of adaptation to climate challenges like drought, heat, and salinity. Therefore, there is a need to replenish the limited elite gene pools with favorable exotic alleles from the wild progenitors of our crops. Nested association mapping (NAM) populations represent one step toward exotic allele evaluation and enrichment of the elite gene pool. We investigated an adaptive selection strategy in the wild barley NAM population HEB-25 based on temporal genomic data by studying the fate of 214,979 SNP loci initially heterozygous in individual BC1S3 lines after five cycles of selfing and field propagation. We identified several loci exposed to adaptive selection in HEB-25. In total, 48.7% (104,725 SNPs) of initially heterozygous SNP calls in HEB-25 were fixed in BC1S3:8 generation, either toward the wild allele (19.9%) or the cultivated allele (28.8%). Most fixed SNP loci turned out to represent gene loci involved in domestication and flowering time as well as plant height, for example, btr1/btr2, thresh-1, Ppd-H1, and sdw1. Interestingly, also unknown loci were found where the exotic allele was fixed, hinting at potentially useful exotic alleles for plant breeding.

Haplotype associated RNA expression (HARE) improves prediction of complex traits in maize

Genomic prediction typically relies on associations between single-site polymorphisms and traits of interest. This representation of genomic variability has been successful for predicting many complex traits. However, it usually cannot capture the combination of alleles in haplotypes and it has generated little insight about the biological function of polymorphisms. Here we present a novel and cost-effective method for imputing cis haplotype associated RNA expression (HARE), studied their transferability across tissues, and evaluated genomic prediction models within and across populations. HARE focuses on tightly linked cis acting causal variants in the immediate vicinity of the gene, while excluding trans effects from diffusion and metabolism. Therefore, HARE estimates were more transferrable across different tissues and populations compared to measured transcript expression. We also showed that HARE estimates captured one-third of the variation in gene expression. HARE estimates were used in genomic prediction models evaluated within and across two diverse maize panels–a diverse association panel (Goodman Association panel) and a large half-sib panel (Nested Association Mapping panel)–for predicting 26 complex traits. HARE resulted in up to 15% higher prediction accuracy than control approaches that preserved haplotype structure, suggesting that HARE carried functional information in addition to information about haplotype structure. The largest increase was observed when the model was trained in the Nested Association Mapping panel and tested in the Goodman Association panel. Additionally, HARE yielded higher within-population prediction accuracy as compared to measured expression values. The accuracy achieved by measured expression was variable across tissues, whereas accuracy by HARE was more stable across tissues. Therefore, imputing RNA expression of genes by haplotype is stable, cost-effective, and transferable across populations.

Simultaneous Dissection of Grain Carotenoid Levels and Kernel Color in Biparental Maize Populations with Yellow-to-Orange Grain

ABSTRACTMaize enriched in provitamin A carotenoids could be key in combatting vitamin A deficiency in human populations relying on maize as a food staple. Consumer studies indicate that orange maize may be regarded as novel and preferred. This study identifies genes of relevance for grain carotenoid concentrations and kernel color, through simultaneous dissection of these traits in 10 families of the U.S. maize nested association mapping population that have yellow to orange grain. Quantitative trait loci (QTL) were identified via joint-linkage analysis, with phenotypic variation explained for individual kernel color QTL ranging from 2.4 to 17.5%. These QTL were cross-analyzed with significant marker-trait associations in a genome-wide association study that utilized ∼27 million variants. Nine genes were identified: four encoding activities upstream of the core carotenoid pathway, one at the pathway branchpoint, three within the α- or β-pathway branches, and one encoding a carotenoid cleavage dioxygenase. Of these, three exhibited significant pleiotropy between kernel color and one or more carotenoid traits. Kernel color exhibited moderate positive correlations with β-branch and total carotenoids and negligible correlations with α-branch carotenoids. These findings can be leveraged to simultaneously achieve desirable kernel color phenotypes and increase concentrations of provitamin A and other priority carotenoids.

De novo assembly, annotation, and comparative analysis of 26 diverse maize genomes

We report de novo genome assemblies, transcriptomes, annotations, and methylomes for the 26 inbreds that serve as the founders for the maize nested association mapping population. The number of pan-genes in these diverse genomes exceeds 103,000, with approximately a third found across all genotypes. The results demonstrate that the ancient tetraploid character of maize continues to degrade by fractionation to the present day. Excellent contiguity over repeat arrays and complete annotation of centromeres revealed additional variation in major cytological landmarks. We show that combining structural variation with single-nucleotide polymorphisms can improve the power of quantitative mapping studies. We also document variation at the level of DNA methylation and demonstrate that unmethylated regions are enriched for cis-regulatory elements that contribute to phenotypic variation.