Diversity in capsule and seed morphological and phytochemical features and essential oil composition of korarima (Aframomum corrorima (braun) P. C. M. jansen) collections from Ethiopia

Korarima (Aframomum corrorima (Braun) P. C. M. Jansen) is one of the Ethiopian native perennial aromatic herbs belonging to the family Zingiberaceae. Conservation of genotypes and genetic improvement of korarima has been hampered due to lack of evidences on genetic diversity of korarima. Genetic diversity of 44 korarima collections was assessed based on joint capsules and seeds morphological and phytochemical characters. Chemical composition of essential oil in seed samples has also been investigated. Physical measurements were done manually while total organic nutrients, crude fiber and total ash in the seeds were done in terms of proximate analysis. Essential oil in the seed samples was extracted by hydro-distillation and its chemical composition was analyzed with gas chromatography and mass spectrometry (GC-MS). ANOVA revealed significant variations in all the variables considered except capsule and seed shape. Ayda collections showed the largest record for fresh capsule weight (25.3 g), dry capsule weight (6.6 g), hundred seed weight (2.8 g), seed to husk ratio (2.1), total organic matter (66.6%) and seed essential oil (7.3%). Collection from Bazet was also excellent in dry weight of seed per capsule (4.45 g) while those from Metser were best in fruit husk essential oil (1.45%). Cluster analysis of the 44 collections revealed four groups each showing large (23.82–280.13) and significant (p < 0.01) pairwise genetic distance. The pattern of grouping is weak and does not match with the region of collections indicating the presence of different genetic background within the collections as well as genetic similarity among the collections. Principal component analysis (PCA) revealed about 81.2% of the total variations in the first four PCs and the pattern of grouping is similar to cluster analysis. In Essential oil composition, Bona Kike collection was remarkable in 1, 8-Cineole (60.81%). Ayda collection showed the highest m-Mentha-1,8-diene, (+)- (10.05%) and β-farnesene (24.03%). Adele Bise collection was highest in D-Limonene (20.21%). The genetic variability in essential oil composition among the samples was revealed because of spatial separation. The result suggests the potential of Ethiopian korarima in general and the collections in particular for further improvement and commercialization. Overall, the higher extent of morphological and biochemical genetic diversity observed signpost the high opportunity for genetic improvement of the crop via hybridization and selection.     

Intraspecific trait variation influences physiological performance and fitness in the South Africa shrub genus Protea (Proteaceae)

Background and AimsGlobal plant trait datasets commonly identify trait relationships that are interpreted to reflect fundamental trade-offs associated with plant strategies, but often these trait relationships are not identified when evaluating them at smaller taxonomic and spatial scales. In this study we evaluate trait relationships measured on individual plants for five widespread Protea species in South Africa to determine whether broad-scale patterns of structural trait (e.g. leaf area) and physiological trait (e.g. photosynthetic rates) relationships can be detected within natural populations, and if these traits are themselves related to plant fitness.MethodsWe evaluated the variance structure (i.e. the proportional intraspecific trait variation relative to among-species variation) for nine structural traits and six physiological traits measured in wild populations. We used a multivariate path model to evaluate the relationships between structural traits and physiological traits, and the relationship between these traits and plant size and reproductive effort.Key ResultsWhile intraspecific trait variation is relatively low for structural traits, it accounts for between 50 and 100 % of the variation in physiological traits. Furthermore, we identified few trait associations between any one structural trait and physiological trait, but multivariate regressions revealed clear associations between combinations of structural traits and physiological performance (R² = 0.37–0.64), and almost all traits had detectable associations with plant fitness.ConclusionsIntraspecific variation in structural traits leads to predictable differences in individual-level physiological performance in a multivariate framework, even though the relationship of any particular structural trait to physiological performance may be weak or undetectable. Furthermore, intraspecific variation in both structural and physiological traits leads to differences in plant size and fitness. These results demonstrate the importance of considering measurements of multivariate phenotypes on individual plants when evaluating trait relationships and how trait variation influences predictions of ecological and evolutionary outcomes.     

A SNP-based genetic dissection of versatile traits in bread wheat (Triticum aestivum L.)

The continuous increase in global population prompts increased wheat production. Future wheat (Triticum aestivum L.) breeding will heavily rely on dissecting molecular and genetic bases of wheat yield and related traits which is possible through the discovery of quantitative trait loci (QTLs) in constructed populations, such as recombinant inbred lines (RILs). Here, we present an evaluation of 92 RILs in a bi-parental RIL mapping population (the International Triticeae Mapping Initiative Mapping Population [ITMI/MP]) using newly generated phenotypic data in 3-year experiments (2015), older phenotypic data (1997–2009), and newly created single nucleotide polymorphism (SNP) marker data based on 92 of the original RILs to search for novel and stable QTLs. Our analyses of more than 15 unique traits observed in multiple experiments included analyses of 46 traits in three environments in the USA, 69 traits in eight environments in Germany, 149 traits in 10 environments in Russia, and 28 traits in four environments in India (292 traits in 25 environments) with 7584 SNPs (292 × 7584 = 2 214 528 data points). A total of 874 QTLs were detected with limit of detection (LOD) scores of 2.01–3.0 and 432 QTLs were detected with LOD > 3.0. Moreover, 769 QTLs could be assigned to 183 clusters based on the common markers and relative proximity of related QTLs, indicating gene-rich regions throughout the A, B, and D genomes of common wheat. This upgraded genotype–phenotype information of ITMI/MP can assist breeders and geneticists who can make crosses with suitable RILs to improve or investigate traits of interest.     

Uncloaking a Lost Cause: Decolonizing ancestry estimation in the United States

Since the professionalization of US-based forensic anthropology in the 1970s, ancestry estimation has been included as a standard part of the biological profile, because practitioners have assumed it necessary to achieve identifications in medicolegal contexts. Simultaneously, forensic anthropologists have not fully considered the racist context of the criminal justice system in the United States related to the treatment of Black, Indigenous, and People of Color; nor have we considered that ancestry estimation might actually hinder identification efforts because of entrenched racial biases. Despite ongoing criticisms from mainstream biological anthropology that ancestry estimation perpetuates race science, forensic anthropologists have continued the practice. Recent years have seen the prolific development of retooled typological approaches with 21st century statistical prowess to include methods for estimating ancestry from cranial morphoscopic traits, despite no evidence that these traits reflect microevolutionary processes or are suitable genetic proxies for population structure; and such approaches have failed to critically evaluate the societal consequences for perpetuating the biological race concept. Around the country, these methods are enculturated in every aspect of the discipline ranging from university classrooms, to the board-certification examination marking the culmination of training, to standard operating procedures adopted by forensic anthropology laboratories. Here, we use critical race theory to interrogate the approaches utilized to estimate ancestry to include a critique of the continued use of morphoscopic traits, and we assert that the practice of ancestry estimation contributes to white supremacy. Based on the lack of scientific support that these traits reflect evolutionary history, and the inability to disentangle skeletal-based ancestry estimates from supporting the biological validity of race, we urge all forensic anthropologists to abolish the practice of ancestry estimation.     

The interaction between host and host plant influences the oviposition and performance of a generalist ectoparasitoid

The successful development of parasitoids of herbivores depends on the quality of their host, which is often affected by the host plant. Therefore, a parasitoid’s oviposition decisions will directly depend on the host, but also on plant quality. Here, we investigated the direct effects of host species and the indirect effects of the host’s food plant on the oviposition decisions and performance of the gregarious ectoparasitoid Euplectrus platyhypenae Howard (Hymenoptera: Eulophidae). With a series of no‐choice experiments, we determined the oviposition and performance of the parasitoid on: (1) two caterpillar species, fall armyworm, Spodoptera frugiperda JE Smith (Lepidoptera: Noctuidae), and velvet armyworm, Spodoptera latifascia Walker, reared on maize (Zea mays L., Poaceae), (2) the same caterpillars reared on maize, bean (Phaseolus vulgaris L., Fabaceae), or squash (Cucurbita pepo L., Cucurbitaceae) leaves, and (3) S. latifascia caterpillars reared on leaves of wild and cultivated lima bean, Phaseolus lunatus L. All these insects and plants originate from Mesoamerica where they have coexisted for thousands of years in the traditional agricultural system known as Milpa in which maize, beans, and squash are planted together. We found that the preferred and best combination of host and host plant for parasitoid performance was S. frugiperda on maize. Parasitoids laid larger clutches, had higher survival, and more females and larger adults emerged from S. frugiperda reared on maize. However, when both caterpillar species were reared on squash, S. latifascia was the better host. Contrary to the literature, S. frugiperda was not able to develop on bean plants. Results from the lima bean experiment showed that parasitoid performance was best when S. latifascia was reared on leaves of cultivated compared to wild lima bean. These findings are discussed in the context of mixed cropping in which the ability of generalist parasitoids to switch among hosts and host plant species could be advantageous for pest management.     

Translating insights from the seed metabolome into improved prediction for lipid-composition traits in oat (Avena sativa L.)

Oat (Avena sativa L.) seed is a rich resource of beneficial lipids, soluble fiber, protein, and antioxidants, and is considered a healthful food for humans. Little is known regarding the genetic controllers of variation for these compounds in oat seed. We characterized natural variation in the mature seed metabolome using untargeted metabolomics on 367 diverse lines and leveraged this information to improve prediction for seed quality traits. We used a latent factor approach to define unobserved variables that may drive covariance among metabolites. One hundred latent factors were identified, of which 21% were enriched for compounds associated with lipid metabolism. Through a combination of whole-genome regression and association mapping, we show that latent factors that generate covariance for many metabolites tend to have a complex genetic architecture. Nonetheless, we recovered significant associations for 23% of the latent factors. These associations were used to inform a multi-kernel genomic prediction model, which was used to predict seed lipid and protein traits in two independent studies. Predictions for 8 of the 12 traits were significantly improved compared to genomic best linear unbiased prediction when this prediction model was informed using associations from lipid-enriched factors. This study provides new insights into variation in the oat seed metabolome and provides genomic resources for breeders to improve selection for health-promoting seed quality traits. More broadly, we outline an approach to distill high-dimensional “omics” data to a set of biologically meaningful variables and translate inferences on these data into improved breeding decisions.