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Biology subjects

Feldman, M. J.

Publications and source records attributed to Feldman, M. J..

9 recordsLinked to original sources

Fish presence alters amphibian and zooplankton communities in kettle lakes, but not hydrological connectivity

Fishless lakes, critical drivers of biodiversity across freshwater landscapes, are becoming increasingly rare due to fish introductions. Although the impacts of fish introduction are well understood in high-elevation fishless lakes, their effects on fishless kettle lakes remain poorly understood. Many kettle lakes are disconnected from the surface water network and are therefore fishless. In this study, we examined how amphibian and zooplankton communities differ between fishless and fish-bearing kettle lakes by comparing 36 lakes in Quebec, Canada. Some kettle lakes are hydrologically connected to surrounding aquatic ecosystems, allowing natural colonization by fish. We therefore also evaluated how amphibian and zooplankton communities differ between connected and disconnected kettle lakes. Fish presence was associated with differences at each stage of the amphibian life cycle. Reproductive calls of adult amphibians were detected regardless of fish presence, indicating that reproduction occurred in all lake types. However, the presence of fish was associated with fewer amphibian egg masses and lower larval abundance, and the absence of salamanders at the larval stage. Small-bodied zooplankton were more abundant in fish-bearing lakes, while overall species richness was lower. In particular, Chaoborus americanus, a large top-predatory zooplankton species, was found exclusively in fishless lakes. In contrast to fish presence, hydrological connectivity had no significant effect on most communities, except for adult American toads, adult wood frogs, and mink frogs larvae, which responded positively to the interaction between fish presence and connectivity. Based on our results, we recommend avoiding fish stocking of kettle lakes to preserve essential reproductive habitats for amphibians, maintain refuges for sensitive zooplankton species, and safeguard the spatial heterogeneity that underpins landscape-scale biodiversity.

ecology↗

Distinct genomic and immunologic tumor evolution in germline TP53-driven breast cancers

Pathogenic germline TP53 alterations cause Li-Fraumeni Syndrome (LFS), and breast cancer is the most common cancer in LFS females. We performed first of its kind multimodal analysis of LFS breast cancer (LFS-BC) compared to sporadic premenopausal BC. Nearly all LFS-BC underwent biallelic loss of TP53 with no recurrent oncogenic variants except ERBB2 (HER2) amplification. Compared to sporadic BC, in situ and invasive LFS-BC exhibited a high burden of short amplified aneuploid segments (SAAS). Pro-apoptotic p53 target genes BAX and TP53I3 failed to be up-regulated in LFS-BC as was seen in sporadic BC compared to normal breast tissue. LFS-BC had lower CD8+ T-cell infiltration compared to sporadic BC yet higher levels of proliferating cytotoxic T-cells. Within LFS-BC, progression from in situ to invasive BC was marked by an increase in chromosomal instability with a decrease in proliferating cytotoxic T-cells. Our study uncovers critical events in mutant p53-driven tumorigenesis in breast tissue.

genetics↗

A scalable, low-cost phenotyping strategy to assess tuber size, shape, and the colorimetric features of tuber skin and flesh in potato breeding populations

Tuber size, shape, colorimetric characteristics, and defect susceptibility are all factors that influence the acceptance of new potato cultivars. Despite the importance of these characteristics, our understanding of their inheritance is substantially limited by our inability to precisely measure these features quantitatively on the scale needed to evaluate breeding populations. To alleviate this bottleneck, we developed a low-cost, semi-automated workflow to capture data and measure each of these characteristics using machine vision. This workflow was applied to assess the phenotypic variation present within 189 F1 progeny of the A08241 breeding population. Our results provide an example of quantitative measurements acquired using machine vision methods that are reliable, heritable, and can be used to understand and select upon multiple traits simultaneously in structured potato breeding populations.

plant biology↗

A deep learning algorithm for potato tuber hollowheart classification

A novel deep learning algorithm is proposed for hollow heart detection which is an internal tuber defect. Hollow heart is one of many internal defects that decrease the market value of potatoes in the fresh market and food processing sectors. Susceptibility to internal defects like the hollow heart is influenced by genetic and environmental factors so elimination of defect-prone material in potato breeding programs is important. Current methods of evaluation utilize human scoring which is limiting (only collects binary data) relative to the data collection capacity afforded by computer vision or are based upon X-ray transmission techniques that are both expensive and can be hazardous. Automation of defect classification (e.g. hollow heart) from data sets collected using inexpensive, consumer-grade hardware has the potential to increase throughput and reduce bias in public breeding programs. The proposed algorithm consists of ResNet50 as the backbone of the model followed by a shallow fully connected network (FCN). A simple augmentation technique is performed to increase the number of images in the data set. The performance of the proposed algorithm is validated by investigating metrics such as precision and the area under the curve (AUC).

plant biology↗

Correlation and co-localization of QTL for stomatal density and canopy temperature under drought stress in Setaria

Mechanistic modeling indicates that stomatal conductance could be reduced to improve water use efficiency (WUE) in C4 crops. Genetic variation in stomatal density and canopy temperature was evaluated in the model C4 genus, Setaria. Recombinant inbred lines (RIL) derived from a Setaria italica x Setaria viridis cross were grown with ample or limiting water supply under field conditions in Illinois. An optical profilometer was used to rapidly assess stomatal patterning and canopy temperature was measured using infrared imaging. Stomatal density and canopy temperature were positively correlated but both were negatively correlated with total above-ground biomass. These trait relationships suggest a likely interaction between stomatal density and the other drivers of water use such as stomatal size and aperture. Multiple QTLs were identified for stomatal density and canopy temperature, including co-located QTLs on chromosomes 5 and 9. The direction of the additive effect of these QTLs on chromosome 5 and 9 were in accordance with the positive phenotypic relationship between these two traits. This suggests a common genetic architecture between stomatal patterning in the greenhouse and canopy transpiration in the field, while highlighting the potential of setaria as a model to understand the physiology and genetics of WUE in C4 species. HighlightThis article reports a phenotypic and genetic relationship between two water use related traits operating at leaf level and canopy level in a C4 model crop species.

plant biology↗

Trends and gaps in the use of citizen science derived data as input for species distribution models: a quantitative review

Citizen science (CS) currently refers to some level of volunteer participation in any discipline of scientific research. Over the last two decades, nature-based CS has flourished due to innovative technology, novel devices, and widespread digital platforms used to collect and classify species occurrence data. For scientists, CS offers a low-cost approach of collecting species occurrence information at large spatial scales that otherwise would be prohibitively expensive. We examined the trends and gaps linked to the use of CS as a source of data for species distribution models (SDMs), in order to propose guidelines and highlight solutions. We conducted a quantitative literature review of 224 peer-reviewed articles to measure how the representation of different taxa, regions, and data types have changed in SDM publications since the 2010s. Our review shows that the number of papers using CS for SDMs has increased at approximately double the rate of the overall number of SDM papers. However, disparities in taxonomic and geographic coverage remain in studies using CS. Western Europe and North America were the regions with the most coverage (71.2%). Papers on birds (51.2%) and mammals (26.2%) outnumbered other taxa. Among invertebrates, flying insects including Lepidoptera and Odonata received the most attention. Compared to studies on animal taxa, papers on plants using CS data remain rare. Although the aims and scope of SDM papers are diverse, conservation remained the central theme of SDM using CS data. We present examples of the use of CS and highlight recommendations to motivate further research, such as combining multiple data sources and promoting local and traditional knowledge. We hope our findings will strengthen citizen-researchers partnerships to better inform SDMs, especially for less-studied taxa and regions. Researchers stand to benefit from the large quantity of data available from CS sources to improve global predictions of species distributions.

ecology↗

Trait components of whole plant water use efficiency are defined by unique, environmentally responsive genetic signatures in the model C4 grass Setaria

Plant growth and water use are interrelated processes influenced by the genetic control of both plant morphological and biochemical characteristics. Improving plant water use efficiency (WUE) to sustain growth in different environments is an important breeding objective that can improve crop yields and enhance agricultural sustainability. However, genetic improvements of WUE using traditional methods have proven difficult due to low throughput and environmental heterogeneity encountered in field settings. To overcome these limitations the study presented here utilizes a high-throughput phenotyping platform to quantify plant size and water use of an interspecific Setaria italica x Setaria viridis recombinant inbred line population at daily intervals in both well-watered and water-limited conditions. Our findings indicate that measurements of plant size and water use in this system are strongly correlated; therefore, a linear modeling approach was used to partition this relationship into predicted values of plant size given water use and deviations from this relationship at the genotype level. The resulting traits describing plant size, water use and WUE were all heritable and responsive to soil water availability, allowing for a genetic dissection of the components of plant WUE under different watering treatments. Linkage mapping identified major loci underlying two different pleiotropic components of WUE. This study indicates that alleles controlling WUE derived from both wild and domesticated accessions of the model C4 species Setaria can be utilized to predictably modulate trait values given a specified precipitation regime.

plant biology↗

High fidelity detection of crop biomass QTL from low-cost imaging in the field

Above-ground biomass production is a key target for studies of crop abiotic stress tolerance, disease resistance and yield improvement. However, biomass is slow and laborious to evaluate in the field using traditional destructive methods. High-throughput phenotyping (HTP) is widely promoted as a potential solution that can rapidly and non-destructively assess plant traits by exploiting advances in sensor and computing technology. A key potential application of HTP is for quantitative genetics studies that identify loci where allelic variation is associated with variation in crop production. And, the value of performing such studies in the field, where environmental conditions match that of production farming, is recognized. To date, HTP of biomass productivity in field trials has largely focused on expensive and complex methods, which - even if successful - will limit their use to a subset of wealthy research institutions and companies with extensive research infrastructure and highly-trained personnel. Even with investment in ground vehicles, aerial vehicles and gantry systems ranging from thousands to millions of dollars, there are very few examples where Quantitative trait loci (QTLs) detected by HTP of biomass production in a field-grown crop are shown to match QTLs detected by direct measures of biomass traits by destructive harvest techniques. Until such proof of concept for HTP proxies is generated it is unlikely to replace existing technology and be widely adopted. Therefore, there is a need for methods that can be used to assess crop performance by small teams with limited training and at field sites that are remote or have limited infrastructure. Here we use an inexpensive and simple, miniaturized system of hemispherical imaging and light attenuation modeling to identify the same set of key QTLs for biomass production as traditional destructive harvest methods applied to a field-grown Setaria mapping population. This provides a case study of a HTP technology that can deliver results for QTL mapping without high costs or complexity.

plant biology↗

Time dependent genetic analysis links field and controlled environment phenotypes in the model C4 grass Setaria

Vertical growth of plants is a dynamic process that is influenced by genetic and environmental factors and has a pronounced effect on overall plant architecture and biomass composition. We have performed twelve controlled growth trials of an interspecific Setaria italica x Setaria viridis recombinant inbred line population to assess how the genetic architecture of plant height is influenced by developmental queues, water availability and planting density. The nondestructive nature of plant height measurements has enabled us to monitor vertical growth throughout the plant life cycle in both field and controlled environments. We find that plant height is reduced under water limitation and high density planting and affected by growth environment (field vs. growth chamber). The results support a model where plant height is a heritable, polygenic trait and that the major genetic loci that influence plant height function independent of growth environment. The identity and contribution of loci that influence height changes dynamically throughout development and the reduction of growth observed in water limited environments is a consequence of delayed progression through the genetic program which establishes plant height in Setaria. In this population, alleles inherited from the weedy S. viridis parent act to increase plant height early, whereas a larger number of small effect alleles inherited from the domesticated S. italica parent collectively act to increase plant height later in development.

plant biology↗