Detection of Adaptive Genetic Diversity in Wild Potato Populations and Its Implications in Conservation of Potato Germplasm

A better understanding on how genetic diversity is structured at natural habitats can be helpful for exploration and acquisition of plant germplasm. Historically, studies have relied on DNA markers to elucidate potato genetic diversity. Current advances in genomics are broadening applications allowing the identification of markers linked to genomic regions under selection. Those markers, known as adaptive markers, unlock additional ways to value and organize germplasm diversity. For example, conservation priorities could be given to germplasm units containing markers associated to unique geographic identity, and/or linked to traits of tolerance to abiotic stresses. This study investigated if adaptive marker loci were possible to be identified in a large AFLP marker dataset of ninety-four populations of the wild potato species S. fendleri. These populations originated from six different mountain ranges in southern Arizona, USA. A total of 2094 polymorphic AFLP markers were used to conduct genetic diversity analyses of populations and mountain ranges. Adaptive markers were detected using Bayesian methods which distinguished marker loci departing significantly from frequencies expected under neutral models of genetic differentiation. This identified 16 AFLP loci that were considered to be adaptive. To contrast diversity parameters generated with each set of markers, analyses that included all the 2094 AFLP markers, and only the 16 adaptive markers were conducted. The results showed that both were efficient for establishing genetic associations among populations and mountain ranges. However, adaptive markers were better on revealing geographic patterns and identity which would suggest these markers were linked to selection at the natural sites. An additional test to determine if adaptive markers associated to climate variables found two loci associated to specific climate variables in populations from different regions but sharing similar environmental structure. The distribution of adaptive markers among populations revealed that only two were needed to build a core subset able to keep all the markers. This preliminary assessment shows that adaptive genetic diversity could offer an additional way to measure diversity in potato germplasm and to set up options for conservation and research.

The clock gene,period,influences migratory flight and reproduction of the oriental armyworm,Mythimna separata(Walker)

The oriental armyworm,Mythimna separata,is a major long-distance migratory insect pest of grain crops in China and other Asian countries.Migratory flights and reproductive behavior usually occur at night,regulated by a circadian rhythm.However,knowledge about the linkages between adult flight,reproduction,and clock genes is still incomplete.To fill this important gap in our knowledge,a clock gene(designated Msper)was identified and phylogenetic analysis indicated that the encoded protein(MsPER)was highly similar to PER proteins from other insect species.Quantitative RT-PCR assays demonstrated that significantly different spatiotemporal and circadian rhythmic accumulations of mRNA encoding MsPER occurred during development under steady 14 h:10 h light:dark conditions.The highest mRNA accumulation occurred in adult antennae and the lowest in larvae.Msper was expressed rhythmically in adult antennae,relatively less in photophase and more entering scotophase.Injecting small interference RNA(siRNA)into adult heads effectively knocked down Msper mRNA levels within 72 h.Most siRNA-injected adults reduced their evening flight activity significantly and did not exhibit a normal evening peak of flight activity.They also failed to mate and lay eggs within 72 h.Adult mating behavior was restored to control levels by 72 h post injection.We infer that Msper is a prominent clock gene that acts in regulating adult migratory flight and mating behaviors of M.separata.Because of its influence on migration and mating,Msper may be a valuable gene to target for effective management of this migratory insect.

iVenomDB: A manually curated database for insect venom proteins

DearEditor,Venomous animals,such as snakes,insects(wasps,bees,ants,and some bugs),spiders,scorpions,and cone snails,use venom for predation and/or defense.Venom is mostly composed of proteinsand peptides.Because of their high potency and selectivity,venom components have been developed into valuable resources,such as research tools,bioinsecticides(Heep et al.,2019),and drug leads(Badawi,2021).The advent of high-throughput sequencing and mass spectrometry enabled exploration of venom components to new depths and at an unprecedented pace.To be useful to the scientific community,knowledge on these proteins must be stored in a retrievable manner,annotated,and curated.Currently,several databases are dedicated to venoms from a wide range of animals,such as Arachnoserver(Pineda et al.,2018),Conoserver(Kaas et al.,2012),and the Tox-Prot program within UniprotKB(Jungo et al.,2012).

Use,calibration and verification of agroecologicalmodels for boreal environments:A review

Past assessments report negative impacts of the climate crisis in boreal areas;but milder and shorter winters and elevated atmospheric CO_(2) may provide opportunities for agricultural productivity potentially playing a significant role in future food security.Arable cropping systems are expanding in boreal areas,but the regional mainstay will likely continue to be livestock production.Agroecological models can when appropriately calibrated and evaluated,facilitate improved productivity while minimising environmental impacts by identifying system interactions,and quantifying greenhouse gas emissions,soil carbon stocks and fertiliser use.While models designed for temperate and tropical zones abound,few are developed specifically for boreal zones,and there is uncertainty around the performance of existing models in boreal areas.We reviewed model performance across boreal environments and management systems.We identified a dearth of modelling studies in boreal regions,with the publication of three or less papers per year since the year 2000,constituting a significant research gap.Models IFSM and BASGRA_N performed best in grassland production,DNDC best in predicting soil N_(2)O and NH_(3) emissions.No model outperformed all others,strengthening the case for ensemble modelling.Existing agroecological models would be worthy of further evaluation,providing model improvements designed for boreal systems.