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Open Access Publications from the University of California

Department of Plant Sciences

UC Davis

This series is automatically populated with publications deposited by UC Davis Department of Plant Sciences researchers in accordance with the University of California’s open access policies. For more information see Open Access Policy Deposits and the UC Publication Management System.

Cover page of No-till is more of sustaining the soil than a climate change mitigation option

No-till is more of sustaining the soil than a climate change mitigation option


No-till is often referred to as a climate change mitigation option, possibly with a stronger conviction, than as a practice to manage soil organic C (SOC) content. We conducted a global meta-analysis to evaluate the effect of no-till (NT) on SOC concentration (SOCc, g C kg−1 soil) and stock (SOCs, Mg C ha−1 land) across climate, soil texture, cropping systems, and no-till duration to appraise the priority-setting. Compared to conventional tillage, NT favoured a significant rise (ΔSOCc) of 38% in the 0–5 cm soil layer and a much lesser 6% increase in the 5–10 cm layer and no change beyond 10 cm. The temperate climate had nearly twice ΔSOCc in the 0–5 cm layer compared to other climates, while the tropical climate favoured sub-surface accumulation. Coarse- and medium-textured soils and the inclusion of legumes in crop rotation facilitated larger positive ΔSOCs under NT. The microbial biomass C was the most abundant C pool, with 61% and 23% increases under NT in 0–5 and 5–10 cm layers. A large ΔSOCc in aggregates also characterized the top 0–5 cm layer. The difference in SOCs was realized to a maximum 30 cm depth (5.4 Mg ha−1 or 14%) in favour of NT, although varying with the duration of its adoption. The contribution of NT in mitigating global anthropogenic greenhouse gas emissions is meagre, although it can substantially offset emissions from agriculture (17–58%). The benefit of NT in improving SOC is primarily restricted to the surface layer, which is potentially exposed, and therefore an increase could be short-lived. Nevertheless, a short-term gain in SOC is likely to enhance soil quality and crop productivity. Thus, NT may be promoted as a sustainable agricultural management practice rather than emphasizing its role as a potential climate change mitigation option.

Cover page of Reducing crop losses by gene-editing control of organ developmental physiology.

Reducing crop losses by gene-editing control of organ developmental physiology.


Some physiological processes in reproductive organs, if not controlled, can lead to crop loss even in the absence of environmental stress. These processes may occur pre- or post- harvest, and in diverse species and include abscission processes in cereal grain, e.g., shattering and in immature fruit, e.g., preharvest drop, preharvest sprouting of cereals, and postharvest senescence in fruit. Some of the molecular mechanisms and genetic determinants underlying these processes are now better detailed, making it possible to refine them by gene editing. Here, we discuss using advanced genomics to identify genetic determinants underlying crop physiological traits. Examples of improved phenotypes developed for preharvest problems are provided, and suggestions for reducing postharvest fruit losses by gene and promoter editing were made.

Cover page of Naturally engineered plant microbiomes in resource-limited ecosystems.

Naturally engineered plant microbiomes in resource-limited ecosystems.


Nature-designed plant microbiomes may offer solutions to improve crop production and ecosystem restoration in less than optimum environments. Through a full exploration of metagenomic data, Camargo et al. showed that a previously unknown microbial diversity enhances nutrient mobilization in stress-adapted plants.

Cover page of Harnessing underutilized gene bank diversity and genomic prediction of cross usefulness to enhance resistance to Phytophthora cactorum in strawberry.

Harnessing underutilized gene bank diversity and genomic prediction of cross usefulness to enhance resistance to Phytophthora cactorum in strawberry.


The development of strawberry (Fragaria × ananassa Duchesne ex Rozier) cultivars resistant to Phytophthora crown rot (PhCR), a devastating disease caused by the soil-borne pathogen Phytophthora cactorum (Lebert & Cohn) J. Schröt., has been challenging partly because the resistance phenotypes are quantitative and only moderately heritable. To develop deeper insights into the genetics of resistance and build the foundation for applying genomic selection, a genetically diverse training population was screened for resistance to California isolates of the pathogen. Here we show that genetic gains in breeding for resistance to PhCR have been negligible (3% of the cultivars tested were highly resistant and none surpassed early 20th century cultivars). Narrow-sense genomic heritability for PhCR resistance ranged from 0.41 to 0.75 among training population individuals. Using multivariate genome-wide association studies (GWAS), we identified a large-effect locus (predicted to be RPc2) that explained 43.6-51.6% of the genetic variance, was necessary but not sufficient for resistance, and was associated with calcium channel and other candidate genes with known plant defense functions. The addition of underutilized gene bank resources to our training population doubled additive genetic variance, increased the accuracy of genomic selection, and enabled the discovery of individuals carrying favorable alleles that are either rare or not present in modern cultivars. The incorporation of an RPc2-associated single-nucleotide polymorphism (SNP) as a fixed effect increased genomic prediction accuracy from 0.40 to 0.55. Finally, we show that parent selection using genomic-estimated breeding values, genetic variances, and cross usefulness holds promise for enhancing resistance to PhCR in strawberry.

Cover page of Updated guidelines for gene nomenclature in wheat.

Updated guidelines for gene nomenclature in wheat.


Key message

Here, we provide an updated set of guidelines for naming genes in wheat that has been endorsed by the wheat research community. The last decade has seen a proliferation in genomic resources for wheat, including reference- and pan-genome assemblies with gene annotations, which provide new opportunities to detect, characterise, and describe genes that influence traits of interest. The expansion of genetic information has supported growth of the wheat research community and catalysed strong interest in the genes that control agronomically important traits, such as yield, pathogen resistance, grain quality, and abiotic stress tolerance. To accommodate these developments, we present an updated set of guidelines for gene nomenclature in wheat. These guidelines can be used to describe loci identified based on morphological or phenotypic features or to name genes based on sequence information, such as similarity to genes characterised in other species or the biochemical properties of the encoded protein. The updated guidelines provide a flexible system that is not overly prescriptive but provides structure and a common framework for naming genes in wheat, which may be extended to related cereal species. We propose these guidelines be used henceforth by the wheat research community to facilitate integration of data from independent studies and allow broader and more efficient use of text and data mining approaches, which will ultimately help further accelerate wheat research and breeding.

Mega-scale Bayesian regression methods for genome-wide prediction and association studies with thousands of traits.


Large-scale phenotype data are expected to increase the accuracy of genome-wide prediction and the power of genome-wide association analyses. However, genomic analyses of high-dimensional, highly correlated traits are challenging. We developed a method for implementing high-dimensional Bayesian multivariate regression to simultaneously analyze genetic variants underlying thousands of traits. As a demonstration, we implemented the BayesC prior in the R package MegaLMM. Applied to Genomic Prediction, MegaBayesC effectively integrated hyperspectral reflectance data from 620 hyperspectral wavelengths to improve the accuracy of genetic value prediction on grain yield in a wheat dataset. Applied to Genome-Wide Association Studies, we used simulations to show that MegaBayesC can accurately estimate the effect sizes of QTL across a range of genetic architectures and causes of correlations among traits. To apply MegaBayesC to a realistic scenario involving whole-genome marker data, we developed a 2-stage procedure involving a preliminary step of candidate marker selection prior to multivariate regression. We then used MegaBayesC to identify genetic associations with flowering time in Arabidopsis thaliana, leveraging expression data from 20,843 genes. MegaBayesC selected 15 single nucleotide polymorphisms as important for flowering time, with 13 located within 100 kb of known flowering-time related genes, a higher validation rate than achieved by a single-stage analysis using only the flowering time data itself. These results demonstrate that MegaBayesC can efficiently and effectively leverage high-dimensional phenotypes in genetic analyses.

Cover page of Mutations in the miRNA165/166 binding site of the HB2 gene result in pleiotropic effects on morphological traits in wheat

Mutations in the miRNA165/166 binding site of the HB2 gene result in pleiotropic effects on morphological traits in wheat


Leaf, spike, stem, and root morphologies are key factors that determine crop growth, development, and productivity. Multiple genes that control these morphological traits have been identified in Arabidopsis, rice, maize, and other plant species. However, little is known about the genomic regions and genes associated with morphological traits in wheat. Here, we identified the ethyl methanesulfonate-derived mutant wheat line M133 that displays multiple morphological changes that include upward-curled leaves, paired spikelets, dwarfism, and delayed heading. Using bulked segregant RNA sequencing (BSR-seq) and a high-resolution genetic map, we identified TraesCS1D02G155200 (HB-D2) as a potential candidate gene. HB-D2 encodes a class III homeodomain-leucine zipper (HD-ZIP III) transcription factor, and the mutation was located in the miRNA165/166 complementary site, resulting in a resistant allele designated rHb-D2. The relative expression of rHb2 in the mutant plants was significantly higher (P < 0.01) than in plants homozygous for the WT allele. Independent resistant mutations that disrupt the miRNA165/166 complementary sites in the A- (rHb-A2) and B-genome (rHb-B2) homoeologs showed similar phenotypic alterations, but the relative intensity of the effects was different. Transgenic plants expressing rHb-D2 gene driven by the maize UBIQUITIN (UBI) promoter showed similar phenotypes to the rHb-D2 mutant. These results confirmed that HB-D2 is the causal gene responsible for the mutant phenotypes. Finally, a survey of 1397 wheat accessions showed that the complementary sites for miRNA165/166 in all three HB2 homoeologs are highly conserved. Our results suggest that HB2 plays an important role in regulating growth and development in wheat.

Economic and social feasibility pilot of ethanol fuel for clean cooking in upland Sierra Leone


Ninety-seven percent of Sierra Leonean households prepare food over wood or charcoal, a practice that leads to adverse health and environmental consequences. In this pilot study, we introduced ethanol cookstoves to households in Bo, Sierra Leone. We assessed their potential as an alternative to biomass fuels and the only existing improved cookstove, butane gas. Ethanol cookstoves were economically competitive with butane stoves, but could not outcompete biomass fuel (wood and charcoal). The cookstoves displayed significant benefits to women in time savings and comfort, but raised concerns around alcoholism, unequal access to technologies, and other gendered constraints in the cultural context.