Metagenome-enabled models improve genomic predictive ability and identification of herbivory-limiting genes in sweetpotato.

Plant-insect interactions are often influenced by host- or insect-associated metagenomic community members. The relative abundance of insects and the microbes that modulate their interactions were obtained from sweetpotato (Ipomoea batatas) leaf-associated metagenomes using quantitative reduced representation sequencing and strain/species-level profiling with the Qmatey software. Positive correlations were found between whitefly (Bemisia tabaci) and its endosymbionts (Candidatus Hamiltonella defensa, Candidatus Portiera aleyrodidarum, and Rickettsia spp.) and negative correlations with nitrogen-fixing bacteria that implicate nitric oxide in sweetpotato-whitefly interaction. Genome-wide associations using 252 975 dosage-based markers, and metagenomes as a covariate to reduce false positive rates, implicated ethylene and cell wall modification in sweetpotato-whitefly interaction. The predictive abilities (PA) for whitefly and Ocypus olens abundance were high in both populations (68%-69% and 33.3%-35.8%, respectively) and 69.9% for Frankliniella occidentalis. The metagBLUP (gBLUP) prediction model, which fits the background metagenome-based Cao dissimilarity matrix instead of the marker-based relationship matrix (G-matrix), revealed moderate PA (35.3%-49.1%) except for O. olens (3%-10.1%). A significant gain in PA after modeling the metagenome as a covariate (gGBLUP, ≤11%) confirms quantification accuracy and that the metagenome modulates phenotypic expression and might account for the missing heritability problem. Significant gains in PA were also revealed after fitting allele dosage (≤17.4%) and dominance effects (≤4.6%). Pseudo-diploidized genotype data underperformed for dominance models. Including segregation-distorted loci (SDL) increased PA by 6%-17.1%, suggesting that traits associated with fitness cost might benefit from the inclusion of SDL. Our findings confirm the holobiont theory of host-metagenome co-evolution and underscore its potential for breeding within the context of G × G × E interactions.

What is the effect of reducing the air change rate on the ventilation effectiveness in ultra-clean operating rooms?

BACKGROUND: The operating room (OR) department is one of the most energy-intensive departments of a hospital. The majority of ORs in the Netherlands have an air-handling installation with an ultra-clean ventilation system. However, not all surgeries require an ultra-clean OR. AIM: To determine the effect of reducing the air change rate on the ventilation effectiveness in ultra-clean ORs. METHODS: Lower air volume ventilation effectiveness (VELv) of conventional ventilation (CV), controlled dilution ventilation (cDV), temperature-controlled airflow (TcAF) and unidirectional airflow (UDAF) systems were evaluated within a 4 × 4 m measuring grid of 1 × 1 m. The VELv was defined as the recovery degree (RD), cleanliness recovery rate (CRR) and air change effectiveness (ACE). FINDINGS: The CV, cDVLv and TcAFLv ventilation systems showed a comparable mixing character in all areas (A, B and AB) when reducing the air change rate to 20/h. Ventilation effectiveness decreased when the air change rate was reduced, with the exception of the ACE. At all points for the UDAF-2Lv and at the centre point (C3) of the TcAFLv, higher RD10Lv and CRRLv were measured when compared with the other examined ventilation systems. CONCLUSIONS: The ventilation effectiveness decreased when an ultra-clean OR with an ultra-clean ventilation air-supply system was switched to an air change rate of 20/h. Reducing the air change rate in the OR from an ultra-clean OR to a generic OR will reduce the recovery degree (RD10) by a factor of 10-100 and the local air change rate (CRR) by between 42% and 81%.

Genotyping-by-Sequencing Reveals Population Differentiation and Linkage Disequilibrium in Alternaria linariae from Tomato.

Alternaria linariae is an economically important foliar pathogen that causes early blight disease in tomatoes. Understanding genetic diversity, population genetic structure, and evolutionary potential is crucial to contemplating effective disease management strategies. We leveraged genotyping-by-sequencing (GBS) technology to compare genome-wide variation in 124 isolates of Alternaria spp. (A. alternata, A. linariae, and A. solani) for comparative genome analysis and to test the hypotheses of genetic differentiation and linkage disequilibrium (LD) in A. linariae collected from tomatoes in western North Carolina. We performed a pangenome-aware variant calling and filtering with GBSapp and identified 53,238 variants conserved across the reference genomes of three Alternaria spp. The highest marker density was observed on chromosome 1 (7 Mb). Both discriminant analysis of principal components and Bayesian model-based STRUCTURE analysis of A. linariae isolates revealed three subpopulations with minimal admixture. The genetic differentiation coefficients (FST) within A. linariae subpopulations were similar and high (0.86), indicating that alleles in the subpopulations are fixed and the genetic structure is likely due to restricted recombination. Analysis of molecular variance indicated higher variation among populations (89%) than within the population (11%). We found long-range LD between pairs of loci in A. linariae, supporting the hypothesis of low recombination expected for a fungal pathogen with limited sexual reproduction. Our findings provide evidence of a high level of population genetic differentiation in A. linariae, which reinforces the importance of developing tomato varieties with broad-spectrum resistance to various isolates of A. linariae.

Qmatey: an automated pipeline for fast exact matching-based alignment and strain-level taxonomic binning and profiling of metagenomes.

Metagenomics is a powerful tool for understanding organismal interactions; however, classification, profiling and detection of interactions at the strain level remain challenging. We present an automated pipeline, quantitative metagenomic alignment and taxonomic exact matching (Qmatey), that performs a fast exact matching-based alignment and integration of taxonomic binning and profiling. It interrogates large databases without using metagenome-assembled genomes, curated pan-genes or k-mer spectra that limit resolution. Qmatey minimizes misclassification and maintains strain level resolution by using only diagnostic reads as shown in the analysis of amplicon, quantitative reduced representation and shotgun sequencing datasets. Using Qmatey to analyze shotgun data from a synthetic community with 35% of the 26 strains at low abundance (0.01-0.06%), we revealed a remarkable 85-96% strain recall and 92-100% species recall while maintaining 100% precision. Benchmarking revealed that the highly ranked Kraken2 and KrakenUniq tools identified 2-4 more taxa (92-100% recall) than Qmatey but produced 315-1752 false positive taxa and high penalty on precision (1-8%). The speed, accuracy and precision of the Qmatey pipeline positions it as a valuable tool for broad-spectrum profiling and for uncovering biologically relevant interactions.

Interrelations of α- and ß-amylase activity with starch, sugars, and culinary and nutritional quality attributes in sweetpotato storage roots.

BACKGROUND: Little information is available on α- and ß-amylase activity and their associations with starch, sugars and other culinary qualities in sweetpotato. The present study aimed to assess sweetpotato storage root α- and ß-amylase activity in relation to starch, sugars, ß-carotene content and storage root flesh color. RESULTS: α- and ß-amylase activity (α-AA and ß-AA) were assayed from a Tanzania (T) × Beauregard (B) genetic mapping population in their uncured (raw), cured and stored (approximately 11 weeks) forms during 2016 and 2017. Ceralpha and Betamyl methods, with modifications to suit a high-throughput microplate assay format, were used to quantify α-AA and ß-AA, respectively. Storage root dry matter, starch, glucose, fructose, sucrose and ß-carotene content were predicted using near infrared reflectance spectroscopy. There was little relationship (r2 = 0.02-0.08, P ≤ 0.05 in 2016 and r2 = 0.05-0.11, P ≤ 0.05 in 2017) between α-AA and ß-AA. We observed negative linear associations between α-AA and dry matter content and generally no correlations between ß-AA and dry matter content. ß-AA and sugars were weakly positively correlated. ß-AA and ß-carotene content were positively correlated (r = 0.3-0.4 in 2016 and 0.3-0.5 in 2017). CONCLUSION: Generally, the correlation coefficient for amylase enzyme activity and sugar components of storage roots at harvest increased after curing and during post-harvest storage. The present study is a major step forward in sweetpotato breeding in terms of providing a better understanding of how α- and ß-amylase activity are inter-associated with several culinary quality attributes. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Development of NIRS calibration curves for sugars in baked sweetpotato.

BACKGROUND: Variability in sugar content between raw and cooked sweetpotato storage roots impact nutritional and dietary importance with implications for consumer preference. High-throughput phenotyping is required to breed varieties that satisfy consumer preferences. RESULTS: Near-infrared reflectance spectroscopy (NIRS) calibration curves were developed for analysing sugars in baked storage roots using 147 genotypes from a population segregating for sugar content and other traits. The NIRS prediction curves had high coefficients of determination in calibration (R2 c ) of 0.96 (glucose), 0.93 (fructose), 0.96 (sucrose), and 0.96 (maltose). The corresponding coefficients of determination for cross-validation (R2 cv ) were 0.92 (glucose), 0.89 (fructose), 0.96 (sucrose) and 0.93 (maltose) and were similar to the R2 c for all sugars measured. The ratios of the standard deviation of the reference set to the standard error of cross-validation were greater than three for all sugars. These results confirm the applicability of the NIRS curves in efficiently determining sugar content in baked sweetpotato storage roots. External validation was performed on an additional 70 genotypes. Coefficients of determination (r2 ) were 0.88 (glucose), 0.88 (fructose), 0.86 (sucrose) and 0.49 (maltose). The results were comparable to those found for the calibration and cross-validation in fructose, glucose, and sucrose, but were moderate for maltose due to the low variability of maltose content in the population. CONCLUSIONS: NIRS can be used for screening sugar content in baked sweetpotato storage roots in breeding programs and can be used to assist with the development of improved sweetpotato varieties that better meet consumer preferences. © 2023 The Authors. Journal of The Science of Food and Agriculture published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

Using MixSIAR to quantify mixed contributions of primary producers from amino acid δ15N of marine consumers.

Estimations of the trophic position and the food web nitrogen baseline from compound-specific isotope analysis of individual amino acids (CSIA-AA) are challenged when the diet of consumer organisms relies on different proportions of vascular and non-vascular primary producers. Here we propose a method to infer such proportions using mixing models and the δ15N CSIA-AA values from marine herbivores. Combining published and new data, we first characterized CSIA-AA values in phytoplankton, macroalgae and vascular plants, and determined their characteristic ß values (i.e. the isotopic difference between trophic and source AA). Then, we applied MixSIAR Bayesian isotope mixing models to investigate the transfer of these isotopic signals to marine herbivores (molluscs, green turtles, zooplankton and fish), and their utility to quantify autotrophic sources. We demonstrated that primary producer groups have distinct δ15NAA fingerprints that can be tracked into their primary consumers, thus offering a rapid solution to quantify resource utilization and estimate ßmix values in mixed-sourced environments.

Development of Genomic Resources in Mexican Bursera (Section: Bullockia: Burseraceae): Genome Assembly, Annotation, and Marker Discovery for Three Copal Species.

Bursera comprises ~100 tropical shrub and tree species, with the center of the species diversification in Mexico. The genomic resources developed for the genus are scarce, and this has limited the study of the gene flow, local adaptation, and hybridization dynamics. In this study, based on ~155 million Illumina paired-end reads per species, we performed a de novo genome assembly and annotation of three Bursera species of the Bullockia section: Bursera bipinnata, Bursera cuneata, and Bursera palmeri. The total lengths of the genome assemblies were 253, 237, and 229 Mb for B. cuneata, B. palmeri, and B. bipinnata, respectively. The assembly of B. palmeri retrieved the most complete and single-copy BUSCOs (87.3%) relative to B. cuneata (86.5%) and B. bipinnata (76.6%). The ab initio gene prediction recognized between 21,000 and 32,000 protein-coding genes. Other genomic features, such as simple sequence repeats (SSRs), were also detected. Using the de novo genome assemblies as a reference, we identified single-nucleotide polymorphisms (SNPs) for a set of 43 Bursera individuals. Moreover, we mapped the filtered reads of each Bursera species against the chloroplast genomes of five Burseraceae species, obtaining consensus sequences ranging from 156 to 160 kb in length. Our work contributes to the generation of genomic resources for an important but understudied genus of tropical-dry-forest species.

Combining ability and heritability analysis of sweetpotato weevil resistance, root yield, and dry matter content in sweetpotato.

Efficient breeding and selection of superior genotypes requires a comprehensive understanding of the genetics of traits. This study was aimed at establishing the general combining ability (GCA), specific combining ability (SCA), and heritability of sweetpotato weevil (Cylas spp.) resistance, storage root yield, and dry matter content in a sweetpotato multi-parental breeding population. A population of 1,896 F1 clones obtained from an 8 × 8 North Carolina II design cross was evaluated with its parents in the field at two sweetpotato weevil hotspots in Uganda, using an augmented row-column design. Clone roots were further evaluated in three rounds of a no-choice feeding laboratory bioassay. Significant GCA effects for parents and SCA effects for families were observed for most traits and all variance components were highly significant (p ≤ 0.001). Narrow-sense heritability estimates for weevil severity, storage root yield, and dry matter content were 0.35, 0.36, and 0.45, respectively. Parental genotypes with superior GCA for weevil resistance included "Mugande," NASPOT 5, "Dimbuka-bukulula," and "Wagabolige." On the other hand, families that displayed the highest levels of resistance to weevils included "Wagabolige" × NASPOT 10 O, NASPOT 5 × "Dimbuka-bukulula," "Mugande" × "Dimbuka-bukulula," and NASPOT 11 × NASPOT 7. The moderate levels of narrow-sense heritability observed for the traits, coupled with the significant GCA and SCA effects, suggest that there is potential for their improvement through conventional breeding via hybridization and progeny selection and advancement. Although selection for weevil resistance may, to some extent, be challenging for breeders, efforts could be boosted through applying genomics-assisted breeding. Superior parents and families identified through this study could be deployed in further research involving the genetic improvement of these traits.

Mapping and identification of QTL in 5601T × U99-310255 RIL population using SNP genotyping: soybean seed quality traits.

BACKGROUND: Molecular markers have played and will continue to play a major role in the genetic characterization and improvement of soybeans. They have helped identify major loci for tolerance to abiotic stressors, disease resistance, herbicide resistance, soybean seed quality traits, and yield. However, most yield quantitative trait loci (QTL) are specific to a certain population, and the genetic variation found in the specific bi-parental population is not always shared in other populations. A major objective in soybean breeding is to develop high yielding cultivars. Unfortunately, soybean seed yield, as well as protein and oil content, are complex quantitative traits to characterize from the phenotypic and genotypic perspectives. The objectives of this study are to detect soybean genomic regions that increase protein content, while maintaining oil content and seed yield and to successfully identify soybean QTL associated with these seed quality traits. METHODS AND RESULTS: To achieve these objectives, data from the 138 recombinant inbred lines grown in six environments were used to perform QTL detection analyses in search of significant genomic regions affecting soybean seed protein, oil, and yield. CONCLUSIONS: A total of 21 QTL were successfully identified for yield, protein, oil, methionine, threonine, lodging, maturity, and meal. Knowledge of their locations and flanking markers will aid in marker assisted selection for plant breeders. This will lead to a more valuable soybean for farmers, processors, and animal nutritionists.

Operating room ventilation systems: recovery degree, cleanliness recovery rate and air change effectiveness in an ultra-clean area.

BACKGROUND: Entrainment test methods are described in most European standards and guidelines to determine the protected area for ultra-clean ventilation (UCV) systems. New UCV systems, such as temperature-controlled airflow (TcAF) and controlled dilution ventilation (cDV) systems, claim the whole operating room (OR) to be ultra-clean. However, current test standards were not developed to assess ventilation effectiveness outside the standard protected area. AIM: To assess and compare the ventilation effectiveness of four types of OR ventilation systems in the ultra-clean area using a uniform test grid. METHODS: Ventilation effectiveness of four ventilation systems was evaluated for three different ultra-clean (protected) areas: the standard protected area (A); the area outside the standard protected area (B); and a large protected area (AB). Ventilation effectiveness was assessed using recovery degree (RD), cleanliness recovery rate (CRR) and air change effectiveness (ACE). FINDINGS: RD, CRR and ACE were significantly higher for the unidirectional air flow (UDAF) system compared with the other systems in area A. In area B, the UDAF and cDV systems were comparable for RD and CRR, and the UDAF and conventional ventilation (CV) systems were comparable for ACE. In area AB, the UDAF and cDV systems were comparable for CRR and ACE, but significant differences were found in RD. CONCLUSION: In area A, the ventilation effectiveness of the UDAF system outperformed other ventilation systems. In area B, the cDV system was best, followed by the UDAF, TcAF and CV systems. In area AB, the UDAF system was best, followed by the cDV, TcAF and CV systems.

Genetic diversity, population structure, and selection of breeder germplasm subsets from the USDA sweetpotato (Ipomoea batatas) collection.

Sweetpotato (Ipomoea batatas) is the sixth most important food crop and plays a critical role in maintaining food security worldwide. Support for sweetpotato improvement research in breeding and genetics programs, and maintenance of sweetpotato germplasm collections is essential for preserving food security for future generations. Germplasm collections seek to preserve phenotypic and genotypic diversity through accession characterization. However, due to its genetic complexity, high heterogeneity, polyploid genome, phenotypic plasticity, and high flower production variability, sweetpotato genetic characterization is challenging. Here, we characterize the genetic diversity and population structure of 604 accessions from the sweetpotato germplasm collection maintained by the United States Department of Agriculture (USDA), Agricultural Research Service (ARS), Plant Genetic Resources Conservation Unit (PGRCU) in Griffin, Georgia, United States. Using the genotyping-by-sequencing platform (GBSpoly) and bioinformatic pipelines (ngsComposer and GBSapp), a total of 102,870 polymorphic SNPs with hexaploid dosage calls were identified from the 604 accessions. Discriminant analysis of principal components (DAPC) and Bayesian clustering identified six unique genetic groupings across seven broad geographic regions. Genetic diversity analyses using the hexaploid data set revealed ample genetic diversity among the analyzed collection in concordance with previous analyses. Following population structure and diversity analyses, breeder germplasm subsets of 24, 48, 96, and 384 accessions were established using K-means clustering with manual selection to maintain phenotypic and genotypic diversity. The genetic characterization of the PGRCU sweetpotato germplasm collection and breeder germplasm subsets developed in this study provide the foundation for future association studies and serve as precursors toward phenotyping studies aimed at linking genotype with phenotype.

Domestication reshaped the genetic basis of inbreeding depression in a maize landrace compared to its wild relative, teosinte.

Inbreeding depression is the reduction in fitness and vigor resulting from mating of close relatives observed in many plant and animal species. The extent to which the genetic load of mutations contributing to inbreeding depression is due to large-effect mutations versus variants with very small individual effects is unknown and may be affected by population history. We compared the effects of outcrossing and self-fertilization on 18 traits in a landrace population of maize, which underwent a population bottleneck during domestication, and a neighboring population of its wild relative teosinte. Inbreeding depression was greater in maize than teosinte for 15 of 18 traits, congruent with the greater segregating genetic load in the maize population that we predicted from sequence data. Parental breeding values were highly consistent between outcross and selfed offspring, indicating that additive effects determine most of the genetic value even in the presence of strong inbreeding depression. We developed a novel linkage scan to identify quantitative trait loci (QTL) representing large-effect rare variants carried by only a single parent, which were more important in teosinte than maize. Teosinte also carried more putative juvenile-acting lethal variants identified by segregation distortion. These results suggest a mixture of mostly polygenic, small-effect partially recessive effects in linkage disequilibrium underlying inbreeding depression, with an additional contribution from rare larger-effect variants that was more important in teosinte but depleted in maize following the domestication bottleneck. Purging associated with the maize domestication bottleneck may have selected against some large effect variants, but polygenic load is harder to purge and overall segregating mutational burden increased in maize compared to teosinte.

A conserved genetic architecture among populations of the maize progenitor, teosinte, was radically altered by domestication.

Very little is known about how domestication was constrained by the quantitative genetic architecture of crop progenitors and how quantitative genetic architecture was altered by domestication. Yang et al. [C. J. Yang et al., Proc. Natl. Acad. Sci. U.S.A. 116, 5643-5652 (2019)] drew multiple conclusions about how genetic architecture influenced and was altered by maize domestication based on one sympatric pair of teosinte and maize populations. To test the generality of their conclusions, we assayed the structure of genetic variances, genetic correlations among traits, strength of selection during domestication, and diversity in genetic architecture within teosinte and maize. Our results confirm that additive genetic variance is decreased, while dominance genetic variance is increased, during maize domestication. The genetic correlations are moderately conserved among traits between teosinte and maize, while the genetic variance-covariance matrices (G-matrices) of teosinte and maize are quite different, primarily due to changes in the submatrix for reproductive traits. The inferred long-term selection intensities during domestication were weak, and the neutral hypothesis was rejected for reproductive and environmental response traits, suggesting that they were targets of selection during domestication. The G-matrix of teosinte imposed considerable constraint on selection during the early domestication process, and constraint increased further along the domestication trajectory. Finally, we assayed variation among populations and observed that genetic architecture is generally conserved among populations within teosinte and maize but is radically different between teosinte and maize. While selection drove changes in essentially all traits between teosinte and maize, selection explains little of the difference in domestication traits among populations within teosinte or maize.

Microsatellite Loci Reveal Genetic Diversity of Asian Callery Pear (Pyrus calleryana) in the Species Native Range and in the North American Cultivars.

Pyrus calleryana Decne. (Callery pear) includes cultivars that in the United States are popular ornamentals in commercial and residential landscapes. Last few decades, this species has increasingly naturalized across portions of the eastern and southern US. However, the mechanisms behind this plant's spread are not well understood. The genetic relationship of present-day P.calleryana trees with their Asian P. calleryana forebears (native trees from China, Japan, and Korea) and the original specimens of US cultivars are unknown. We developed and used 18 microsatellite markers to analyze 147 Pyrus source samples and to articulate the status of genetic diversity within Asian P. calleryana and US cultivars. We hypothesized that Asian P. calleryana specimens and US cultivars would be genetically diverse and would show genetic relatedness. Our data revealed high genetic diversity, high gene flow, and presence of population structure in P. calleryana, potentially relating to the highly invasive capability of this species. Strong evidence for genetic relatedness between Asian P. calleryana specimens and US cultivars was also demonstrated. Our data suggest the source for P. calleryana that have become naturalized in US was China. These results will help understand the genetic complexity of invasive P. calleryana when developing management for escaped populations: In follow-up studies, we use the gSSRs developed here to analyze P. calleryana escape populations from across US.

ngsComposer: an automated pipeline for empirically based NGS data quality filtering.

Next-generation sequencing (NGS) enables massively parallel acquisition of large-scale omics data; however, objective data quality filtering parameters are lacking. Although a useful metric, evidence reveals that platform-generated Phred values overestimate per-base quality scores. We have developed novel and empirically based algorithms that streamline NGS data quality filtering. The pipeline leverages known sequence motifs to enable empirical estimation of error rates, detection of erroneous base calls and removal of contaminating adapter sequence. The performance of motif-based error detection and quality filtering were further validated with read compression rates as an unbiased metric. Elevated error rates at read ends, where known motifs lie, tracked with propagation of erroneous base calls. Barcode swapping, an inherent problem with pooled libraries, was also effectively mitigated. The ngsComposer pipeline is suitable for various NGS protocols and platforms due to the universal concepts on which the algorithms are based.

Discovery of a major QTL for root-knot nematode (Meloidogyne incognita) resistance in cultivated sweetpotato (Ipomoea batatas).

KEY MESSAGE: Utilizing a high-density integrated genetic linkage map of hexaploid sweetpotato, we discovered a major dominant QTL for root-knot nematode (RKN) resistance and modeled its effects. This discovery is useful for development of a modern sweetpotato breeding program that utilizes marker-assisted selection and genomic selection approaches for faster genetic gain of RKN resistance. The root-knot nematode [Meloidogyne incognita (Kofoid & White) Chitwood] (RKN) causes significant storage root quality reduction and yields losses in cultivated sweetpotato [Ipomoea batatas (L.) Lam.]. In this study, resistance to RKN was examined in a mapping population consisting of 244 progenies derived from a cross (TB) between 'Tanzania,' a predominant African landrace cultivar with resistance to RKN, and 'Beauregard,' an RKN susceptible major cultivar in the USA. We performed quantitative trait loci (QTL) analysis using a random-effect QTL mapping model on the TB genetic map. An RKN bioassay incorporating potted cuttings of each genotype was conducted in the greenhouse and replicated five times over a period of 10 weeks. For each replication, each genotype was inoculated with ca. 20,000 RKN eggs, and root-knot galls were counted ~62 days after inoculation. Resistance to RKN in the progeny was highly skewed toward the resistant parent, exhibiting medium to high levels of resistance. We identified one major QTL on linkage group 7, dominant in nature, which explained 58.3% of the phenotypic variation in RKN counts. This work represents a significant step forward in our understanding of the genetic architecture of RKN resistance and sets the stage for future utilization of genomics-assisted breeding in sweetpotato breeding programs.

Large deep-sea zooplankton biomass mirrors primary production in the global ocean.

The biological pump transports organic carbon produced by photosynthesis to the meso- and bathypelagic zones, the latter removing carbon from exchanging with the atmosphere over centennial time scales. Organisms living in both zones are supported by a passive flux of particles, and carbon transported to the deep-sea through vertical zooplankton migrations. Here we report globally-coherent positive relationships between zooplankton biomass in the epi-, meso-, and bathypelagic layers and average net primary production (NPP). We do so based on a global assessment of available deep-sea zooplankton biomass data and large-scale estimates of average NPP. The relationships obtained imply that increased NPP leads to enhanced transference of organic carbon to the deep ocean. Estimated remineralization from respiration rates by deep-sea zooplankton requires a minimum supply of 0.44 Pg C y-1 transported into the bathypelagic ocean, comparable to the passive carbon sequestration. We suggest that the global coupling between NPP and bathypelagic zooplankton biomass must be also supported by an active transport mechanism associated to vertical zooplankton migration.

The genetic architecture of the maize progenitor, teosinte, and how it was altered during maize domestication.

The genetics of domestication has been extensively studied ever since the rediscovery of Mendel's law of inheritance and much has been learned about the genetic control of trait differences between crops and their ancestors. Here, we ask how domestication has altered genetic architecture by comparing the genetic architecture of 18 domestication traits in maize and its ancestor teosinte using matched populations. We observed a strongly reduced number of QTL for domestication traits in maize relative to teosinte, which is consistent with the previously reported depletion of additive variance by selection during domestication. We also observed more dominance in maize than teosinte, likely a consequence of selective removal of additive variants. We observed that large effect QTL have low minor allele frequency (MAF) in both maize and teosinte. Regions of the genome that are strongly differentiated between teosinte and maize (high FST) explain less quantitative variation in maize than teosinte, suggesting that, in these regions, allelic variants were brought to (or near) fixation during domestication. We also observed that genomic regions of high recombination explain a disproportionately large proportion of heritable variance both before and after domestication. Finally, we observed that about 75% of the additive variance in both teosinte and maize is "missing" in the sense that it cannot be ascribed to detectable QTL and only 25% of variance maps to specific QTL. This latter result suggests that morphological evolution during domestication is largely attributable to very large numbers of QTL of very small effect.