Positive effects of public breeding on US rice yields under future climate scenarios.

In this study, we model and predict rice yields by integrating molecular marker variation, varietal productivity, and climate, focusing on the Southern U.S. rice-growing region. This region spans the states of Arkansas, Louisiana, Texas, Mississippi, and Missouri and accounts for 85% of total U.S. rice production. By digitizing and combining four decades of county-level variety acreage data (1970 to 2015) with varietal information from genotyping-by-sequencing data, we estimate annual historical county-level allele frequencies. These allele frequencies are used together with county-level weather and yield data to develop ten machine learning models for yield prediction. A two-layer meta-learner ensemble model that combines all ten methods is externally evaluated against observations from historical Uniform Regional Rice Nursery trials (1980 to 2018) conducted in the same states. Finally, the ensemble model is used with forecasted weather from the Coupled Model Intercomparison Project across the 110 rice-growing counties to predict production in the coming decades for Composite Variety Groups assembled based on year of release, breeding program, and several breeding trends. Results indicate positive effects over time of public breeding on rice resilience to future climates, and potential reasons are discussed.

Genome assembly and association tests identify interacting loci associated with vigor, precocity, and sex in interspecific pistachio rootstocks.

Understanding the basis of hybrid vigor remains a key question in crop breeding and improvement, especially for rootstock development where F1 hybrids are extensively utilized. Full-sibling UCB-1 F1 seedling rootstocks are widely planted in commercial pistachio orchards that are generated by crossing 2 highly heterozygous outbreeding parental trees of Pistacia atlantica (female) and P. integerrima (male). This results in extensive phenotypic variability, prompting costly removal of low-yielding small trees. To identify the genetic basis of this variability, we assembled chromosome-scale genome assemblies of the parental trees of UCB-1. We genotyped 960 UCB-1 trees in an experimental orchard for which we also collected multiyear phenotypes. We genotyped an additional 1,358 rootstocks in 6 commercial pistachio orchards and collected single-year tree-size data. Genome-wide single marker association tests identified loci associated with tree size and shape, sex, and precocity. In the experimental orchard, we identified multiple trait-associated loci and a strong candidate for ZZ/ZW sex chromosomes. We found significant marker associations unique to different traits and to early vs late phenotypic measures of the same trait. We detected 2 loci strongly associated with rootstock size in commercial orchards. Pseudo-testcross classification of markers demonstrated that the trait-associated alleles for each locus were segregating in the gametes of opposite parents. These 2 loci interact epistatically to generate the bimodal distribution of tree size with undesirable small trees observed by growers. We identified candidate genes within these regions. These findings provide a foundational resource for marker development and genetic selection of vigorous pistachio UCB-1 rootstock.

Variance of allele balance calculated from low coverage sequencing data infers departure from a diploid state.

BACKGROUND: Polyploidy and heterokaryosis are common and consequential genetic phenomena that increase the number of haplotypes in an organism and complicate whole-genome sequence analysis. Allele balance has been used to infer polyploidy and heterokaryosis in diverse organisms using read sets sequenced to greater than 50× whole-genome coverage. However, sequencing to adequate depth is costly if applied to multiple individuals or large genomes. RESULTS: We developed VCFvariance.pl to utilize the variance of allele balance to infer polyploidy and/or heterokaryosis at low sequence coverage. This analysis requires as little as 10× whole-genome coverage and reduces the allele balance profile down to a single value, which can be used to determine if an individual has two or more haplotypes. This approach was validated using simulated, synthetic, and authentic read sets from the oomycete species Bremia lactucae and Phytophthora infestans, the fungal species Saccharomyces cerevisiae, and the plant species Arabidopsis arenosa. This approach was deployed to determine that nine of 21 genotyped European race-type isolates of Bremia lactucae were inconsistent with diploidy and therefore likely heterokaryotic. CONCLUSIONS: Variance of allele balance is a reliable metric to detect departures from a diploid state, including polyploidy, heterokaryosis, a mixed sample, or chromosomal copy number variation. Deploying this strategy is computationally inexpensive, can reduce the cost of sequencing by up to 80%, and used to test any organism.

Quantitative Trait Loci and Candidate Genes Associated with Photoperiod Sensitivity in Lettuce (Lactuca spp.).

KEY MESSAGE: A population of lettuce that segregated for photoperiod sensitivity was planted under long-day and short-day conditions. Genetic mapping revealed two distinct sets of QTLs controlling daylength-independent and photoperiod-sensitive flowering time. The molecular mechanism of flowering time regulation in lettuce is of interest to both geneticists and breeders because of the extensive impact of this trait on agricultural production. Lettuce is a facultative long-day plant which changes in flowering time in response to photoperiod. Variations exist in both flowering time and the degree of photoperiod sensitivity among accessions of wild (Lactuca serriola) and cultivated (L. sativa) lettuce. An F6 population of 236 recombinant inbred lines (RILs) was previously developed from a cross between a late-flowering, photoperiod-sensitive L. serriola accession and an early-flowering, photoperiod-insensitive L. sativa accession. This population was planted under long-day (LD) and short-day (SD) conditions in a total of four field and screenhouse trials; the developmental phenotype was scored weekly in each trial. Using genotyping-by-sequencing (GBS) data of the RILs, quantitative trait loci (QTL) mapping revealed five flowering time QTLs that together explained more than 20% of the variation in flowering time under LD conditions. Using two independent statistical models to extract the photoperiod sensitivity phenotype from the LD and SD flowering time data, we identified an additional five QTLs that together explained more than 30% of the variation in photoperiod sensitivity in the population. Orthology and sequence analysis of genes within the nine QTLs revealed potential functional equivalents in the lettuce genome to the key regulators of flowering time and photoperiodism, FD and CONSTANS, respectively, in Arabidopsis.

AFLAP: assembly-free linkage analysis pipeline using k-mers from genome sequencing data.

Our assembly-free linkage analysis pipeline (AFLAP) identifies segregating markers as k-mers in the raw reads without using a reference genome assembly for calling variants and provides genotype tables for the construction of unbiased, high-density genetic maps without a genome assembly. AFLAP is validated and contrasted to a conventional workflow using simulated data. AFLAP is applied to whole genome sequencing and genotype-by-sequencing data of F1, F2, and recombinant inbred populations of two different plant species, producing genetic maps that are concordant with genome assemblies. The AFLAP-based genetic map for Bremia lactucae enables the production of a chromosome-scale genome assembly.

High-resolution genetic dissection of the major QTL for tipburn resistance in lettuce, Lactuca sativa.

Tipburn is an important physiological disorder of lettuce, Lactuca sativa L., related to calcium deficiency that can result in leaf necrosis and unmarketable crops. The major quantitative trait locus (QTL), qTPB5.2, can account for up to 70% of the phenotypic variance for tipburn incidence in the field. This QTL was genetically dissected to identify candidate genes for tipburn by creating lines with recombination events within the QTL and assessing their resistance to tipburn. By comparing lines with contrasting haplotypes, the genetic region was narrowed down to ∼877 Kb that was associated with a reduction of tipburn by ∼60%. Analysis of the lettuce reference genome sequence revealed 12 genes in this region, one of which is a calcium transporter with a single nucleotide polymorphism in an exon between haplotypes with contrasting phenotypes. RNA-seq analysis of recombinants revealed two genes that were differentially expressed between contrasting haplotypes consistent with the tipburn phenotype. One encodes a Teosinte branched1/Cycloidea/Proliferating Cell factor transcription factor; however, differential expression of the calcium transporter was detected. The phenotypic data indicated that there is a second region outside of the ∼877 Kb region but within the QTL, at which a haplotype from the susceptible parent decreased tipburn by 10-20%. A recombinant line was identified with beneficial haplotypes in each region from both parents that showed greater tipburn resistance than the resistant parent; this line could be used as the foundation for breeding cultivars with more resistance than is currently available.

Drone phenotyping and machine learning enable discovery of loci regulating daily floral opening in lettuce.

Flower opening and closure are traits of reproductive importance in all angiosperms because they determine the success of self- and cross-pollination. The temporal nature of this phenotype rendered it a difficult target for genetic studies. Cultivated and wild lettuce, Lactuca spp., have composite inflorescences that open only once. An L. serriola×L. sativa F6 recombinant inbred line (RIL) population differed markedly for daily floral opening time. This population was used to map the genetic determinants of this trait; the floral opening time of 236 RILs was scored using time-course image series obtained by drone-based phenotyping on two occasions. Floral pixels were identified from the images using a support vector machine with an accuracy >99%. A Bayesian inference method was developed to extract the peak floral opening time for individual genotypes from the time-stamped image data. Two independent quantitative trait loci (QTLs; Daily Floral Opening 2.1 and qDFO8.1) explaining >30% of the phenotypic variation in floral opening time were discovered. Candidate genes with non-synonymous polymorphisms in coding sequences were identified within the QTLs. This study demonstrates the power of combining remote sensing, machine learning, Bayesian statistics, and genome-wide marker data for studying the genetics of recalcitrant phenotypes.

A Composite Analysis of Flowering Time Regulation in Lettuce.

Plants undergo profound physiological changes when transitioning from vegetative to reproductive growth. These changes affect crop production, as in the case of leafy vegetables. Lettuce is one of the most valuable leafy vegetable crops in the world. Past genetic studies have identified multiple quantitative trait loci (QTLs) that affect the timing of the floral transition in lettuce. Extensive functional molecular studies in the model organism Arabidopsis provide the opportunity to transfer knowledge to lettuce to explore the mechanisms through which genetic variations translate into changes in flowering time. In this review, we integrated results from past genetic and molecular studies for flowering time in lettuce with orthology and functional inference from Arabidopsis. This summarizes the basis for all known genetic variation underlying the phenotypic diversity of flowering time in lettuce and how the genetics of flowering time in lettuce projects onto the established pathways controlling flowering time in plants. This comprehensive overview reveals patterns across experiments as well as areas in need of further study. Our review also represents a resource for developing cultivars with delayed flowering time.

Upregulation of a KN1 homolog by transposon insertion promotes leafy head development in lettuce.

Leafy head is a unique type of plant architecture found in some vegetable crops, with leaves bending inward to form a compact head. The genetic and molecular mechanisms underlying leafy head in vegetables remain poorly understood. We genetically fine-mapped and cloned a major quantitative trait locus controlling heading in lettuce. The candidate gene (LsKN1) is a homolog of knotted 1 (KN1) from Zea mays Complementation and CRISPR/Cas9 knockout experiments confirmed the role of LsKN1 in heading. In heading lettuce, there is a CACTA-like transposon inserted into the first exon of LsKN1 (LsKN1▽). The transposon sequences act as a promoter rather than an enhancer and drive high expression of LsKN1▽. The enhanced expression of LsKN1▽ is necessary but not sufficient for heading in lettuce. Data from ChIP-sequencing, electrophoretic mobility shift assays, and dual luciferase assays indicate that the LsKN1▽ protein binds the promoter of LsAS1 and down-regulates its expression to alter leaf dorsoventrality. This study provides insight into plant leaf development and will be useful for studies on heading in other vegetable crops.

Genome-Wide Analysis of Cyclophilin Proteins in 21 Oomycetes.

Cyclophilins (CYPs), a highly-conserved family of proteins, belong to a subgroup of immunophilins. Ubiquitous in eukaryotes and prokaryotes, CYPs have peptidyl-prolyl cis-trans isomerase (PPIase) activity and have been implicated as virulence factors in plant pathogenesis by oomycetes. We identified 16 CYP orthogroups from 21 diverse oomycetes. Each species was found to encode 15 to 35 CYP genes. Three of these orthogroups contained proteins with signal peptides at the N-terminal end, suggesting a role in secretion. Multidomain analysis revealed five conserved motifs of the CYP domain of oomycetes shared with other eukaryotic PPIases. Expression analysis of CYP proteins in different asexual life stages of the hemibiotrophic Phytophthora infestans and the biotrophic Plasmopara halstedii demonstrated distinct expression profiles between life stages. In addition to providing detailed comparative information on the CYPs in multiple oomycetes, this study identified candidate CYP effectors that could be the foundation for future studies of virulence.

The buffering capacity of stems: genetic architecture of nonstructural carbohydrates in cultivated Asian rice, Oryza sativa.

Harnessing stem carbohydrate dynamics in grasses offers an opportunity to help meet future demands for plant-based food, fiber and fuel production, but requires a greater understanding of the genetic controls that govern the synthesis, interconversion and transport of such energy reserves. We map out a blueprint of the genetic architecture of rice (Oryza sativa) stem nonstructural carbohydrates (NSC) at two critical developmental time-points using a subpopulation-specific genome-wide association approach on two diverse germplasm panels followed by quantitative trait loci (QTL) mapping in a biparental population. Overall, 26 QTL are identified; three are detected in multiple panels and are associated with starch-at-maturity, sucrose-at-maturity and NSC-at-heading. They tag OsHXK6 (rice hexokinase), ISA2 (rice isoamylase) and a tandem array of sugar transporters. This study provides the foundation for more in-depth molecular investigation to validate candidate genes underlying rice stem NSC and informs future comparative studies in other agronomically vital grass species.