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1. Changing Hydrographic, Biogeochemical, and Acidification Properties in the Gulf of Maine as Measured by the Gulf of Maine North Atlantic Time Series, GNATS, Between 1998 and 2018

   https://doi.org/10.1029/2022JG006790  

   Balch, William M. ; Drapeau, David T. ; Bowler, Bruce C. ; Record, Nicholas R. ; Bates, Nicholas R. ; Pinkham, Sunny ; Garley, Rebecca ; Mitchell, Catherine ( June 2022 , Journal of Geophysical Research: Biogeosciences)

   The Gulf of Maine North Atlantic Time Series (GNATS) has been run since 1998, across the Gulf of Maine (GoM), between Maine and Nova Scotia. GNATS goals are to provide ocean color satellite validation and to examine change in this coastal ecosystem. We have sampled hydrographical, biological, chemical, biogeochemical, and bio‐optical variables. After 2008, warm water intrusions (likely North Atlantic Slope Water [NASW]) were observed in the eastern GoM at 50–180 m depths. Shallow waters (<50 m) significantly warmed in winter, summer, and fall butcooledduring spring. Surface salinity and density of the GoM also significantly increased over the 20 years. Phytoplankton standing stock and primary production showed highly‐significant decreases during the period. Concentrations of phosphate increased, silicate decreased, residual nitrate [N*; nitrate‐silicate] increased, and the ratio of dissolved inorganic nitrogen:phosphate decreased, suggesting increasing nitrogen limitation. Dissolved organic carbon (DOC) and its optical indices generally increased over two decades, suggesting changes to the DOC cycle. Surface seawater carbonate chemistry showed winter periods where the aragonite saturation (Ω_ar) dropped below 1.6 gulf‐wide due to upward winter mixing of cool, corrosive water. However, associated with increased average GoM temperatures, Ω_arhas significantly increased. These results reinforce the hypothesis that the observed decrease in surface GoM primary production resulted from a switch from Labrador Sea Water to NASW entering the GoM. A multifactor analysis shows that decreasing GoM primary production is most significantly correlated to decreases in chlorophyll and particulate organic carbon plus increases in N* and temperature.

    

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2. SCOUR: a stepwise machine learning framework for predicting metabolite-dependent regulatory interactions

   https://doi.org/10.1186/s12859-021-04281-7  

   Lee, Justin Y. ; Nguyen, Britney ; Orosco, Carlos ; Styczynski, Mark P. ( July 2021 , BMC Bioinformatics)

   The topology of metabolic networks is both well-studied and remarkably well-conserved across many species. The regulation of these networks, however, is much more poorly characterized, though it is known to be divergent across organisms—two characteristics that make it difficult to model metabolic networks accurately. While many computational methods have been built to unravel transcriptional regulation, there have been few approaches developed for systems-scale analysis and study of metabolic regulation. Here, we present a stepwise machine learning framework that applies established algorithms to identify regulatory interactions in metabolic systems based on metabolic data: stepwise classification of unknown regulation, or SCOUR.

   We evaluated our framework on both noiseless and noisy data, using several models of varying sizes and topologies to show that our approach is generalizable. We found that, when testing on data under the most realistic conditions (low sampling frequency and high noise), SCOUR could identify reaction fluxes controlled only by the concentration of a single metabolite (its primary substrate) with high accuracy. The positive predictive value (PPV) for identifying reactions controlled by the concentration of two metabolites ranged from 32 to 88% for noiseless data, 9.2 to 49% for either low sampling frequency/low noise or high sampling frequency/high noise data, and 6.6–27% for low sampling frequency/high noise data, with results typically sufficiently high for lab validation to be a practical endeavor. While the PPVs for reactions controlled by three metabolites were lower, they were still in most cases significantly better than random classification.

   SCOUR uses a novel approach to synthetically generate the training data needed to identify regulators of reaction fluxes in a given metabolic system, enabling metabolomics and fluxomics data to be leveraged for regulatory structure inference. By identifying and triaging the most likely candidate regulatory interactions, SCOUR can drastically reduce the amount of time needed to identify and experimentally validate metabolic regulatory interactions. As high-throughput experimental methods for testing these interactions are further developed, SCOUR will provide critical impact in the development of predictive metabolic models in new organisms and pathways.

    

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3. Egg hatching success is influenced by the time of thermal stress in four hard tick species

   https://doi.org/10.1093/jme/tjad142  

   Ajayi, Oluwaseun M. ; Oyen, Kennan J. ; Davies, Benjamin ; Finch, Geoffrey ; Piller, Benjamin D. ; Harmeyer, Alison A. ; Wendeln, Katherine ; Perretta, Carlie ; Rosendale, Andrew J. ; Benoit, Joshua B. ; et al ( October 2023 , Journal of Medical Entomology)

   Ticks are blood-feeding arthropods responsible for the transmission of disease-causing pathogens to a wide range of vertebrate hosts, including livestock and humans. Tick-borne diseases have been implicated in significant economic losses to livestock production, and this threat will increase as these obligate parasites widen their geographical ranges. Similar to other ectotherms, thermal stress due to changing global temperatures has been shown to influence tick survival and distribution. However, studies on the influence of extreme temperatures in ticks have focused on advanced, mobile stages, ignoring immobile stages that cannot move to more favorable microhabitats. In this study, low- and high-temperature regimens were assessed in relation to egg viability for hard tick species—Amblyomma maculatum (Gulf Coast tick), Ixodes scapularis (black-legged tick), Dermacentor variabilis (American dog tick), and Rhipicephalus sanguineus (Brown dog tick). Tick eggs exposed early in development (freshly laid during early embryo development) were significantly more susceptible to thermal stress when compared with those exposed later in development (late embryo development denoted by a fecal spot). Based on our studies, differences in egg hatching success among treatments were greater than in hatching success when comparing species. Lastly, there was evidence of extreme thermal exposure significantly altering the hatching times of tick eggs for specific treatments. These results provide insights into the critical period for tick egg viability in relation to thermal exposure and tick survival associated with stress and climate change.

    

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4. Zebrafish gonad mutant models reveal neuroendocrine mechanisms of brain sexual dimorphism and male mating behaviors of different brain regions

   https://doi.org/10.1186/s13293-023-00534-7  

   Dai, Xiangyan ; Pradhan, Ajay ; Liu, Jiao ; Liu, Ruolan ; Zhai, Gang ; Zhou, Linyan ; Dai, Jiyan ; Shao, Feng ; Yuan, Zhiyong ; Wang, Zhijian ; et al ( August 2023 , Biology of Sex Differences)

   Sexually dimorphic mating behaviors differ between sexes and involve gonadal hormones and possibly sexually dimorphic gene expression in the brain. However, the associations among the brain, gonad, and sexual behavior in teleosts are still unclear. Here, we utilized germ cells-freetdrd12knockout (KO) zebrafish, and steroid synthesis enzymecyp17a1-deficient zebrafish to investigate the differences and interplays in the brain–gonad–behavior axis, and the molecular control of brain dimorphism and male mating behaviors.

   Tdrd12^+/−;cyp17a1^+/−double heterozygous parents were crossed to obtaintdrd12^−/−;cyp17a1^+/+(tdrd12 KO),tdrd12^+/+;cyp17a1^−/−(cyp17a1 KO), andtdrd12^−/−;cyp17a1^−/−(double KO) homozygous progenies. Comparative analysis of mating behaviors were evaluated using Viewpoint zebrafish tracking software and sexual traits were thoroughly characterized based on anatomical and histological experiments in these KOs and wild types. The steroid hormone levels (testosterone, 11-ketotestosterone and 17β-estradiol) in the brains, gonads, and serum were measured using ELISA kits. To achieve a higher resolution view of the differences in region-specific expression patterns of the brain, the brains of these KOs, and control male and female fish were dissected into three regions: the forebrain, midbrain, and hindbrain for transcriptomic analysis.

   Qualitative analysis of mating behaviors demonstrated thattdrd12^−/−fish behaved in the same manner as wild-type males to trigger oviposition behavior, whilecyp17a1^−/−and double knockout (KO) fish did not exhibit these behaviors. Based on the observation of sex characteristics, mating behaviors and hormone levels in these mutants, we found that the maintenance of secondary sex characteristics and male mating behavior did not depend on the presence of germ cells; rather, they depended mainly on the 11-ketotestosterone and testosterone levels secreted into the brain–gonad regulatory axis. RNA-seq analysis of different brain regions revealed that the brain transcript profile oftdrd12^−/−fish was similar to that of wild-type males, especially in the forebrain and midbrain. However, the brain transcript profiles ofcyp17a1^−/−and double KO fish were distinct from those of wild-type males and were partially biased towards the expression pattern of the female brain. Our results revealed important candidate genes and signaling pathways, such as synaptic signaling/neurotransmission, MAPK signaling, and steroid hormone pathways, that shape brain dimorphism and modulate male mating behavior in zebrafish.

   Our results provide comprehensive analyses and new insights regarding the endogenous interactions in the brain–gonad–behavior axis. Moreover, this study revealed the crucial candidate genes and neural signaling pathways of different brain regions that are involved in modulating brain dimorphism and male mating behavior in zebrafish, which would significantly light up the understanding the neuroendocrine and molecular mechanisms modulating brain dimorphism and male mating behavior in zebrafish and other teleost fish.

    

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5. Convergent selection of a WD40 protein that enhances grain yield in maize and rice

   https://doi.org/10.1126/science.abg7985  

   Chen, Wenkang ; Chen, Lu ; Zhang, Xuan ; Yang, Ning ; Guo, Jianghua ; Wang, Min ; Ji, Shenghui ; Zhao, Xiangyu ; Yin, Pengfei ; Cai, Lichun ; et al ( March 2022 , Science)

   INTRODUCTION During the independent process of cereal evolution, many trait shifts appear to have been under convergent selection to meet the specific needs of humans. Identification of convergently selected genes across cereals could help to clarify the evolution of crop species and to accelerate breeding programs. In the past several decades, researchers have debated whether convergent phenotypic selection in distinct lineages is driven by conserved molecular changes or by diverse molecular pathways. Two of the most economically important crops, maize and rice, display some conserved phenotypic shifts—including loss of seed dispersal, decreased seed dormancy, and increased grain number during evolution—even though they experienced independent selection. Hence, maize and rice can serve as an excellent system for understanding the extent of convergent selection among cereals. RATIONALE Despite the identification of a few convergently selected genes, our understanding of the extent of molecular convergence on a genome-wide scale between maize and rice is very limited. To learn how often selection acts on orthologous genes, we investigated the functions and molecular evolution of the grain yield quantitative trait locus KRN2 in maize and its rice ortholog OsKRN2 . We also identified convergently selected genes on a genome-wide scale in maize and rice, using two large datasets. RESULTS We identified a selected gene, KRN2 ( kernel row number2 ), that differs between domesticated maize and its wild ancestor, teosinte. This gene underlies a major quantitative trait locus for kernel row number in maize. Selection in the noncoding upstream regions resulted in a reduction of KRN2 expression and an increased grain number through an increase in kernel rows. The rice ortholog, OsKRN2 , also underwent selection and negatively regulates grain number via control of secondary panicle branches. These orthologs encode WD40 proteins and function synergistically with a gene of unknown function, DUF1644, which suggests that a conserved protein interaction controls grain number in maize and rice. Field tests show that knockout of KRN2 in maize or OsKRN2 in rice increased grain yield by ~10% and ~8%, respectively, with no apparent trade-off in other agronomic traits. This suggests potential applications of KRN2 and its orthologs for crop improvement. On a genome-wide scale, we identified a set of 490 orthologous genes that underwent convergent selection during maize and rice evolution, including KRN2/OsKRN2 . We found that the convergently selected orthologous genes appear to be significantly enriched in two specific pathways in both maize and rice: starch and sucrose metabolism, and biosynthesis of cofactors. A deep analysis of convergently selected genes in the starch metabolic pathway indicates that the degree of genetic convergence via convergent selection is related to the conservation and complexity of the gene network for a given selection. CONCLUSION Our findings show that common phenotypic shifts during maize and rice evolution acting on conserved genes are driven at least in part by convergent selection, which in maize and rice likely occurred both during and after domestication. We provide evolutionary and functional evidence on the convergent selection of KRN2/OsKRN2 for grain number between maize and rice. We further found that a complete loss-of-function allele of KRN2/OsKRN2 increased grain yield without an apparent negative impact on other agronomic traits. Exploring the role of KRN2/OsKRN2 and other convergently selected genes across the cereals could provide new opportunities to enhance the production of other global crops. Shared selected orthologous genes in maize and rice for convergent phenotypic shifts during domestication and improvement. By comparing 3163 selected genes in maize and 18,755 selected genes in rice, we identified 490 orthologous gene pairs, including KRN2 and its rice ortholog OsKRN2 , as having been convergently selected. Knockout of KRN2 in maize or OsKRN2 in rice increased grain yield by increasing kernel rows and secondary panicle branches, respectively. 

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