The genus Calceolaria (Calceolariaceae) is emblematic of the Andes, is hypothesized to have originated as a recent, rapid radiation, and has important taxonomic needs. Additionally, the genus is a model for the study of specialized pollination systems, as its flowers are nectarless and many offer floral oils as a pollination reward collected by specialist bees. Despite their evolutionary and ecological significance, obtaining a resolved phylogeny for the group has proved difficult. To address this challenge, we present a new bait set for targeted sequencing of nuclear loci in Calceolariaceae and close relatives.
Methods
We developed a bioinformatic workflow to use incomplete, low-coverage genomes of 10 Calceolaria species to identify single-copy loci suitable for phylogenetic studies and design baits for targeted sequencing.
Results
Our approach resulted in the identification of 809 single-copy loci (733 noncoding and 76 coding regions) and the development of 39,937 baits, which we validated in silico (10 specimens) and in vitro (29 Calceolariaceae and six outgroups). In both cases, the data allowed us to recover robust phylogenetic estimates.
Discussion
Our results demonstrate the appropriateness of the bait set for sequencing recent and historic specimens of Calceolariaceae and close relatives, and open new doors for further investigation of the evolutionary history of this hyperdiverse genus.
{"title":"Calceolariaceae809: A bait set for targeted sequencing of nuclear loci","authors":"Nicolas Medina, David C. Tank, Anahí Espíndola","doi":"10.1002/aps3.11557","DOIUrl":"10.1002/aps3.11557","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>The genus <i>Calceolaria</i> (Calceolariaceae) is emblematic of the Andes, is hypothesized to have originated as a recent, rapid radiation, and has important taxonomic needs. Additionally, the genus is a model for the study of specialized pollination systems, as its flowers are nectarless and many offer floral oils as a pollination reward collected by specialist bees. Despite their evolutionary and ecological significance, obtaining a resolved phylogeny for the group has proved difficult. To address this challenge, we present a new bait set for targeted sequencing of nuclear loci in Calceolariaceae and close relatives.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We developed a bioinformatic workflow to use incomplete, low-coverage genomes of 10 <i>Calceolaria</i> species to identify single-copy loci suitable for phylogenetic studies and design baits for targeted sequencing.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Our approach resulted in the identification of 809 single-copy loci (733 noncoding and 76 coding regions) and the development of 39,937 baits, which we validated in silico (10 specimens) and in vitro (29 Calceolariaceae and six outgroups). In both cases, the data allowed us to recover robust phylogenetic estimates.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>Our results demonstrate the appropriateness of the bait set for sequencing recent and historic specimens of Calceolariaceae and close relatives, and open new doors for further investigation of the evolutionary history of this hyperdiverse genus.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"11 6","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://bsapubs.onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.11557","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138526691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The explosion of available genomic data poses significant opportunities and challenges for genome-wide association studies. Current approaches via linear mixed models (LMM) are straightforward but prevent flexible assumptions of an a priori genomic architecture, while Bayesian sparse LMMs (BSLMMs) allow this flexibility. Complex traits, such as specialized metabolites, are subject to various hierarchical effects, including gene regulation, enzyme efficiency, and the availability of reactants.
Methods
To identify alternative genetic architectures, we examined the genetic architecture underlying the carotenoid content of an association mapping panel of Helianthus annuus individuals using multiple BSLMM and LMM frameworks.
Results
The LMMs of genome-wide single-nucleotide polymorphisms (SNPs) identified a single transcription factor responsible for the observed variations in the carotenoid content; however, a BSLMM of the SNPs with the bottom 1% of effect sizes from the results of the LMM identified multiple biologically relevant quantitative trait loci (QTLs) for carotenoid content external to the known (annotated) carotenoid pathway. A candidate pathway analysis (CPA) suggested a β-carotene isomerase to be the enzyme with the highest impact on the observed carotenoid content within the carotenoid pathway.
Discussion
While traditional LMM approaches suggested a single unknown transcription factor associated with carotenoid content variation in sunflower petals, BSLMM proposed several QTLs with interpretable biological relevance to this trait. In addition, the CPA allowed for the dissection of the regulatory vs. biosynthetic genetic architectures underlying this metabolic trait.
{"title":"Candidate pathway association and genome-wide association approaches reveal alternative genetic architectures of carotenoid content in cultivated sunflower (Helianthus annuus)","authors":"Jordan A. Dowell, Chase Mason","doi":"10.1002/aps3.11558","DOIUrl":"10.1002/aps3.11558","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>The explosion of available genomic data poses significant opportunities and challenges for genome-wide association studies. Current approaches via linear mixed models (LMM) are straightforward but prevent flexible assumptions of an a priori genomic architecture, while Bayesian sparse LMMs (BSLMMs) allow this flexibility. Complex traits, such as specialized metabolites, are subject to various hierarchical effects, including gene regulation, enzyme efficiency, and the availability of reactants.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>To identify alternative genetic architectures, we examined the genetic architecture underlying the carotenoid content of an association mapping panel of <i>Helianthus annuus</i> individuals using multiple BSLMM and LMM frameworks.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>The LMMs of genome-wide single-nucleotide polymorphisms (SNPs) identified a single transcription factor responsible for the observed variations in the carotenoid content; however, a BSLMM of the SNPs with the bottom 1% of effect sizes from the results of the LMM identified multiple biologically relevant quantitative trait loci (QTLs) for carotenoid content external to the known (annotated) carotenoid pathway. A candidate pathway analysis (CPA) suggested a β-carotene isomerase to be the enzyme with the highest impact on the observed carotenoid content within the carotenoid pathway.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>While traditional LMM approaches suggested a single unknown transcription factor associated with carotenoid content variation in sunflower petals, BSLMM proposed several QTLs with interpretable biological relevance to this trait. In addition, the CPA allowed for the dissection of the regulatory vs. biosynthetic genetic architectures underlying this metabolic trait.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"11 6","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://bsapubs.onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.11558","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138526693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Scott R. Lakeram, Scott Elrick, Surangi W. Punyasena
Coal balls, in which fossil plants are preserved in permineralized peat deposits, have widely been described from coal deposits representing the tropical forest of the Carboniferous. Coal ball preparation techniques have evolved over the past century, with the cellulose acetate peel method becoming the standard in the 1950s. While coal ball research is not as active as it has been in the past, large collections of coal balls and their respective peels still form a large part of many museum and university collections. This contribution aims to review coal ball preparation methods, curation, and the digital archiving of peels to create a cohesive guide for researchers working with coal balls and other petrified plant material. The physical and digital curation of cellulose acetate peels and other types of coal ball specimens is critical for long-term preservation and accessibility. Physical curation involves embedding coal balls in media to slow pyrite deterioration. Digital curation creates high-resolution scans of peels, which can be shared and accessed online. Cellulose acetate peels and their digital curation are a valuable and accessible technique for the analysis of coal balls, and physical and digital curation ensures long-term preservation.
{"title":"Review of the cellulose acetate peel method and the physical and digital curation of coal balls","authors":"Scott R. Lakeram, Scott Elrick, Surangi W. Punyasena","doi":"10.1002/aps3.11556","DOIUrl":"10.1002/aps3.11556","url":null,"abstract":"<p>Coal balls, in which fossil plants are preserved in permineralized peat deposits, have widely been described from coal deposits representing the tropical forest of the Carboniferous. Coal ball preparation techniques have evolved over the past century, with the cellulose acetate peel method becoming the standard in the 1950s. While coal ball research is not as active as it has been in the past, large collections of coal balls and their respective peels still form a large part of many museum and university collections. This contribution aims to review coal ball preparation methods, curation, and the digital archiving of peels to create a cohesive guide for researchers working with coal balls and other petrified plant material. The physical and digital curation of cellulose acetate peels and other types of coal ball specimens is critical for long-term preservation and accessibility. Physical curation involves embedding coal balls in media to slow pyrite deterioration. Digital curation creates high-resolution scans of peels, which can be shared and accessed online. Cellulose acetate peels and their digital curation are a valuable and accessible technique for the analysis of coal balls, and physical and digital curation ensures long-term preservation.</p>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"11 6","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-11-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://bsapubs.onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.11556","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138526695","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Laymon D. Ball, Ana M. Bedoya, Charlotte M. Taylor, Laura P. Lagomarsino
Premise
Rubiaceae is among the most species-rich plant families, as well as one of the most morphologically and geographically diverse. Currently available phylogenies have mostly relied on few genomic and plastid loci, as opposed to large-scale genomic data. Target enrichment provides the ability to generate sequence data for hundreds to thousands of phylogenetically informative, single-copy loci, which often leads to improved phylogenetic resolution at both shallow and deep taxonomic scales; however, a publicly accessible Rubiaceae-specific probe set that allows for comparable phylogenetic inference across clades is lacking.
Methods
Here, we use publicly accessible genomic resources to identify putatively single-copy nuclear loci for target enrichment in two Rubiaceae groups: tribe Hillieae (Cinchonoideae) and tribal complex Palicoureeae+Psychotrieae (Rubioideae). We sequenced 2270 exonic regions corresponding to 1059 loci in our target clades and generated in silico target enrichment sequences for other Rubiaceae taxa using our designed probe set. To test the utility of our probe set for phylogenetic inference across Rubiaceae, we performed a coalescent-aware phylogenetic analysis using a subset of 27 Rubiaceae taxa from 10 different tribes and three subfamilies, and one outgroup in Apocynaceae.
Results
We recovered an average of 75% and 84% of targeted exons and loci, respectively, per Rubiaceae sample. Probes designed using genomic resources from a particular subfamily were most efficient at targeting sequences from taxa in that subfamily. The number of paralogs recovered during assembly varied for each clade. Phylogenetic inference of Rubiaceae with our target regions resolves relationships at various scales. Relationships are largely consistent with previous studies of relationships in the family with high support (≥0.98 local posterior probability) at nearly all nodes and evidence of gene tree discordance.
Discussion
Our probe set, which we call Rubiaceae2270x, was effective for targeting loci in species across and even outside of Rubiaceae. This probe set will facilitate phylogenomic studies in Rubiaceae and advance systematics and macroevolutionary studies in the family.
{"title":"A target enrichment probe set for resolving phylogenetic relationships in the coffee family, Rubiaceae","authors":"Laymon D. Ball, Ana M. Bedoya, Charlotte M. Taylor, Laura P. Lagomarsino","doi":"10.1002/aps3.11554","DOIUrl":"10.1002/aps3.11554","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Rubiaceae is among the most species-rich plant families, as well as one of the most morphologically and geographically diverse. Currently available phylogenies have mostly relied on few genomic and plastid loci, as opposed to large-scale genomic data. Target enrichment provides the ability to generate sequence data for hundreds to thousands of phylogenetically informative, single-copy loci, which often leads to improved phylogenetic resolution at both shallow and deep taxonomic scales; however, a publicly accessible Rubiaceae-specific probe set that allows for comparable phylogenetic inference across clades is lacking.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>Here, we use publicly accessible genomic resources to identify putatively single-copy nuclear loci for target enrichment in two Rubiaceae groups: tribe Hillieae (Cinchonoideae) and tribal complex Palicoureeae+Psychotrieae (Rubioideae). We sequenced 2270 exonic regions corresponding to 1059 loci in our target clades and generated in silico target enrichment sequences for other Rubiaceae taxa using our designed probe set. To test the utility of our probe set for phylogenetic inference across Rubiaceae, we performed a coalescent-aware phylogenetic analysis using a subset of 27 Rubiaceae taxa from 10 different tribes and three subfamilies, and one outgroup in Apocynaceae.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We recovered an average of 75% and 84% of targeted exons and loci, respectively, per Rubiaceae sample. Probes designed using genomic resources from a particular subfamily were most efficient at targeting sequences from taxa in that subfamily. The number of paralogs recovered during assembly varied for each clade. Phylogenetic inference of Rubiaceae with our target regions resolves relationships at various scales. Relationships are largely consistent with previous studies of relationships in the family with high support (≥0.98 local posterior probability) at nearly all nodes and evidence of gene tree discordance.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>Our probe set, which we call Rubiaceae2270x, was effective for targeting loci in species across and even outside of Rubiaceae. This probe set will facilitate phylogenomic studies in Rubiaceae and advance systematics and macroevolutionary studies in the family.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"11 6","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://bsapubs.onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.11554","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138526711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Vuruputoor, V. S., D. Monyak, K. C. Fetter, C. Webster, A. Bhattarai, B. Shrestha, S. Zaman, et al. 2023. Welcome to the big leaves: Best practices for improving genome annotation in non-model plant genomes. Applications in Plant Sciences 11(4): e11533.
Figure 4 in the published manuscript contained the following errors. Figure 4A and 4B were missing violin plots for MAKER, which should have been colored green. Figure 4C incorrectly displayed the ideal range of scores—the yellow bar should have spanned 85 to 100 instead of the range shown. Additionally, the color scheme was incorrect. The BRAKER runs should have been colored blue and the StringTie2 runs should have been red. The corrected Figure 4 is presented here with its original caption, which was correct.
We apologize for this error.
Vuruputoor, V. S, D. Monyak, K. C. Fetter, C. Webster, A. Bhattarai, B. Shrestha, S. Zaman等。2023。欢迎来到大叶子:改进非模式植物基因组注释的最佳实践。植物科学应用11(4):e11533。已发表稿件中的图4包含以下错误。图4A和4B缺少MAKER的小提琴情节，应该用绿色标注。图4C错误地显示了分数的理想范围——黄色条应该跨越85到100，而不是显示的范围。此外，配色方案也不正确。BRAKER的运行应该是蓝色的，StringTie2的运行应该是红色的。更正后的图4显示在这里，其原始标题是正确的。我们为这个错误道歉。
{"title":"Correction to Welcome to the big leaves: Best practices for improving genome annotation in non-model plant genomes","authors":"","doi":"10.1002/aps3.11553","DOIUrl":"10.1002/aps3.11553","url":null,"abstract":"<p>Vuruputoor, V. S., D. Monyak, K. C. Fetter, C. Webster, A. Bhattarai, B. Shrestha, S. Zaman, et al. 2023. Welcome to the big leaves: Best practices for improving genome annotation in non-model plant genomes. <i>Applications in Plant Sciences</i> 11(4): e11533.</p><p>Figure 4 in the published manuscript contained the following errors. Figure 4A and 4B were missing violin plots for MAKER, which should have been colored green. Figure 4C incorrectly displayed the ideal range of scores—the yellow bar should have spanned 85 to 100 instead of the range shown. Additionally, the color scheme was incorrect. The BRAKER runs should have been colored blue and the StringTie2 runs should have been red. The corrected Figure 4 is presented here with its original caption, which was correct.</p><p>We apologize for this error.</p>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"11 6","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://bsapubs.onlinelibrary.wiley.com/doi/epdf/10.1002/aps3.11553","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135539842","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Christina Steinecke, Jeremiah Lee, Jannice Friedman
Premise
Variation in seed traits is common within and among populations of plant species and often has ecological and evolutionary implications. However, due to the time-consuming nature of manual seed measurements and the level of variability in imaging techniques, quantifying and interpreting the extent of seed variation can be challenging.
Methods
We developed a standardized high-throughput technique to measure seed number, as well as individual seed area and color, using a derived empirical scale to constrain area in Arabidopsis thaliana, Brassica rapa, and Mimulus guttatus. We develop a specific rational model using seed area measured at various spatial scales relative to the pixel count, observing the asymptotic value of the seed area as the modeled number of pixels approaches infinity.
Results
We found that our model has high reliability in estimating seed traits and efficiently processes large numbers of images, facilitating the quantification of seed traits in studies with large sample sizes.
Discussion
This technique facilitates consistency between imaging sessions and standardizes the measurement of seed traits. These novel advances allow researchers to directly and reliably measure seed traits, which will enable tests of the ecological and evolutionary causes of their variation.
{"title":"A standardized and efficient technique to estimate seed traits in plants with numerous small propagules","authors":"Christina Steinecke, Jeremiah Lee, Jannice Friedman","doi":"10.1002/aps3.11552","DOIUrl":"10.1002/aps3.11552","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Variation in seed traits is common within and among populations of plant species and often has ecological and evolutionary implications. However, due to the time-consuming nature of manual seed measurements and the level of variability in imaging techniques, quantifying and interpreting the extent of seed variation can be challenging.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We developed a standardized high-throughput technique to measure seed number, as well as individual seed area and color, using a derived empirical scale to constrain area in <i>Arabidopsis thaliana, Brassica rapa</i>, and <i>Mimulus guttatus</i>. We develop a specific rational model using seed area measured at various spatial scales relative to the pixel count, observing the asymptotic value of the seed area as the modeled number of pixels approaches infinity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We found that our model has high reliability in estimating seed traits and efficiently processes large numbers of images, facilitating the quantification of seed traits in studies with large sample sizes.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>This technique facilitates consistency between imaging sessions and standardizes the measurement of seed traits. These novel advances allow researchers to directly and reliably measure seed traits, which will enable tests of the ecological and evolutionary causes of their variation.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"11 5","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71419880","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Because of the trade-off between water loss and carbon dioxide assimilation, the conductivity of the transpiration path in a leaf is an important limit on photosynthesis. Closely packed veins correspond to short paths and high assimilation rates while widely spaced veins are associated with higher resistance to flow and lower maximum photosynthetic rates. Vein length per area (VLA) has become the standard metric for comparing leaves with different vein densities; its measurement typically utilizes digital image processing with varying amounts of human input.
Methods and Results
Here, we propose three new ways of measuring vein density using image analysis that improve on currently available procedures: (1) areole area distributions, (2) a sizing transform, and (3) a distance map. Each alternative has distinct practical, statistical, and biological limitations and advantages. In particular, we advocate the log-transformed modal distance map of a vein mask as an estimator to replace VLA as a standard metric for vein density.
Conclusions
These methods, for which open-source code appropriate for high-throughput automation is provided, improve on VLA by producing determinate measures of vein density as distributions rather than point estimates. Combined with advances in image quality and computational efficiency, these methods should help clarify the physiological and evolutionary significance of vein density.
{"title":"How dense can you be? New automatic measures of vein density in angiosperm leaves","authors":"Walton A. Green, Juan M. Losada","doi":"10.1002/aps3.11551","DOIUrl":"10.1002/aps3.11551","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Because of the trade-off between water loss and carbon dioxide assimilation, the conductivity of the transpiration path in a leaf is an important limit on photosynthesis. Closely packed veins correspond to short paths and high assimilation rates while widely spaced veins are associated with higher resistance to flow and lower maximum photosynthetic rates. Vein length per area (VLA) has become the standard metric for comparing leaves with different vein densities; its measurement typically utilizes digital image processing with varying amounts of human input.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods and Results</h3>\u0000 \u0000 <p>Here, we propose three new ways of measuring vein density using image analysis that improve on currently available procedures: (1) areole area distributions, (2) a sizing transform, and (3) a distance map. Each alternative has distinct practical, statistical, and biological limitations and advantages. In particular, we advocate the log-transformed modal distance map of a vein mask as an estimator to replace VLA as a standard metric for vein density.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>These methods, for which open-source code appropriate for high-throughput automation is provided, improve on VLA by producing determinate measures of vein density as distributions rather than point estimates. Combined with advances in image quality and computational efficiency, these methods should help clarify the physiological and evolutionary significance of vein density.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"11 5","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-10-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71419882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pamela S. Soltis, Luiza Teixeira-Costa, Pierre Bonnet, R. Gil Nelson
<p>New imaging technologies are dramatically transforming all of biology. From remote sensing of continents to computed tomography (CT) scanning of individual organisms or parts of organisms, novel views are emerging that span planetary to suborganismal scales. In plant biology, observations from satellites (e.g., Deneu et al., <span>2021</span>; Cavender-Bares et al., <span>2022</span>) and airborne instruments (e.g., Sun et al., <span>2021</span>) are providing new insight into the distribution of botanical diversity, species abundance, and ecosystem productivity and how these features are changing in response to human activity. At the same time, advances in X-ray technologies are revealing exquisite anatomical detail of both living and fossil plant structures (Brodersen and Roddy, <span>2016</span>). Innovations in imaging, largely enabled by the development of new sensors and analysis capabilities, are also capturing specific attributes of individual plants as well as their community context in the field.</p><p>In this special issue of <i>Applications in Plant Sciences</i> (<i>APPS</i>), we explore innovations in imaging and their contributions to plant biology. The 10 papers included in this collection span imaging of live plants in the field to chemical mapping of specific compounds. The authors emphasize sample preparation techniques, practical aspects of image capture, standardization of imaging techniques and resulting images, multiple forms of image analysis, and alternatives for image archival in public repositories. Moreover, the diversity of the imaging approaches and protocols presented in this collection can be applied to a broad range of research, teaching, and public outreach.</p><p>Two papers in this special issue note the lack of consistency in photographs of plants taken in the field. These photographs might serve as a virtual voucher of a rare species (when destructive sampling would be detrimental to the population) or as a source of plant traits for ecological or evolutionary research, but field photographs of plants are rarely standardized. Unlike other groups of organisms for which “standard views” have been developed, the vast diversity of plants in terms of both size and structure precludes many traditional approaches to standardization. These issues, as well as others, render currently available collections, such as those downloadable from iNaturalist (https://www.inaturalist.org/), less useful than they could be if images were captured, processed, and archived following specified standards. To standardize and improve the usefulness of field-captured images of plants, Weaver and Smith (<span>2023a</span>) report the development and implementation of FieldPrism, a system of photogrammetric markers, QR codes, and software to automate the curation of snapshot vouchers. They also developed FieldStation, a mobile imaging system that records images, GPS location, and other metadata on multiple storage devices. The combined u
{"title":"Advances in plant imaging across scales","authors":"Pamela S. Soltis, Luiza Teixeira-Costa, Pierre Bonnet, R. Gil Nelson","doi":"10.1002/aps3.11550","DOIUrl":"https://doi.org/10.1002/aps3.11550","url":null,"abstract":"<p>New imaging technologies are dramatically transforming all of biology. From remote sensing of continents to computed tomography (CT) scanning of individual organisms or parts of organisms, novel views are emerging that span planetary to suborganismal scales. In plant biology, observations from satellites (e.g., Deneu et al., <span>2021</span>; Cavender-Bares et al., <span>2022</span>) and airborne instruments (e.g., Sun et al., <span>2021</span>) are providing new insight into the distribution of botanical diversity, species abundance, and ecosystem productivity and how these features are changing in response to human activity. At the same time, advances in X-ray technologies are revealing exquisite anatomical detail of both living and fossil plant structures (Brodersen and Roddy, <span>2016</span>). Innovations in imaging, largely enabled by the development of new sensors and analysis capabilities, are also capturing specific attributes of individual plants as well as their community context in the field.</p><p>In this special issue of <i>Applications in Plant Sciences</i> (<i>APPS</i>), we explore innovations in imaging and their contributions to plant biology. The 10 papers included in this collection span imaging of live plants in the field to chemical mapping of specific compounds. The authors emphasize sample preparation techniques, practical aspects of image capture, standardization of imaging techniques and resulting images, multiple forms of image analysis, and alternatives for image archival in public repositories. Moreover, the diversity of the imaging approaches and protocols presented in this collection can be applied to a broad range of research, teaching, and public outreach.</p><p>Two papers in this special issue note the lack of consistency in photographs of plants taken in the field. These photographs might serve as a virtual voucher of a rare species (when destructive sampling would be detrimental to the population) or as a source of plant traits for ecological or evolutionary research, but field photographs of plants are rarely standardized. Unlike other groups of organisms for which “standard views” have been developed, the vast diversity of plants in terms of both size and structure precludes many traditional approaches to standardization. These issues, as well as others, render currently available collections, such as those downloadable from iNaturalist (https://www.inaturalist.org/), less useful than they could be if images were captured, processed, and archived following specified standards. To standardize and improve the usefulness of field-captured images of plants, Weaver and Smith (<span>2023a</span>) report the development and implementation of FieldPrism, a system of photogrammetric markers, QR codes, and software to automate the curation of snapshot vouchers. They also developed FieldStation, a mobile imaging system that records images, GPS location, and other metadata on multiple storage devices. The combined u","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"11 5","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71934122","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Katherine A. Wolcott, Edward L. Stanley, Osman A. Gutierrez, Stefan Wuchty, Barbara Ann Whitlock
Premise
Imaging technologies that capture three-dimensional (3D) variation in floral morphology at micro- and nano-resolutions are increasingly accessible. In herkogamous flowers, such as those of Theobroma cacao, structural barriers between anthers and stigmas represent bottlenecks that restrict pollinator size and access to reproductive organs. To study the unresolved pollination biology of cacao, we present a novel application of micro-computed tomography (micro-CT) using floral dimensions to quantify pollinator functional size limits.
Methods
We generated micro-CT data sets from field-collected flowers and museum specimens of potential pollinators. To compare floral variation, we used 3D Slicer to place landmarks on the surface models and performed a geometric morphometric (GMM) analysis using geomorph R. We identified the petal side door (an opening between the petal hoods and filament) as the main bottleneck for pollinator access. We compared its mean dimensions with proposed pollinators to identify viable candidates.
Results
We identified three levels of likelihood for putative pollinators based on the number of morphological (body) dimensions that fit through the petal side door. We also found floral reward microstructures whose presence and location were previously unclear.
Discussion
Using micro-CT and GMM to study the 3D pollination biology of cacao provides new evidence for predicting unknown pollinators. Incorporating geometry and floral rewards will strengthen plant–pollinator trait matching models for cacao and other species.
{"title":"3D pollination biology using micro-computed tomography and geometric morphometrics in Theobroma cacao","authors":"Katherine A. Wolcott, Edward L. Stanley, Osman A. Gutierrez, Stefan Wuchty, Barbara Ann Whitlock","doi":"10.1002/aps3.11549","DOIUrl":"https://doi.org/10.1002/aps3.11549","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Imaging technologies that capture three-dimensional (3D) variation in floral morphology at micro- and nano-resolutions are increasingly accessible. In herkogamous flowers, such as those of <i>Theobroma cacao</i>, structural barriers between anthers and stigmas represent bottlenecks that restrict pollinator size and access to reproductive organs. To study the unresolved pollination biology of cacao, we present a novel application of micro-computed tomography (micro-CT) using floral dimensions to quantify pollinator functional size limits.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>We generated micro-CT data sets from field-collected flowers and museum specimens of potential pollinators. To compare floral variation, we used 3D Slicer to place landmarks on the surface models and performed a geometric morphometric (GMM) analysis using geomorph R. We identified the petal side door (an opening between the petal hoods and filament) as the main bottleneck for pollinator access. We compared its mean dimensions with proposed pollinators to identify viable candidates.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We identified three levels of likelihood for putative pollinators based on the number of morphological (body) dimensions that fit through the petal side door. We also found floral reward microstructures whose presence and location were previously unclear.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>Using micro-CT and GMM to study the 3D pollination biology of cacao provides new evidence for predicting unknown pollinators. Incorporating geometry and floral rewards will strengthen plant–pollinator trait matching models for cacao and other species.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"11 5","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71982944","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Quantitative plant traits play a crucial role in biological research. However, traditional methods for measuring plant morphology are time consuming and have limited scalability. We present LeafMachine2, a suite of modular machine learning and computer vision tools that can automatically extract a base set of leaf traits from digital plant data sets.
Methods
LeafMachine2 was trained on 494,766 manually prepared annotations from 5648 herbarium images obtained from 288 institutions and representing 2663 species; it employs a set of plant component detection and segmentation algorithms to isolate individual leaves, petioles, fruits, flowers, wood samples, buds, and roots. Our landmarking network automatically identifies and measures nine pseudo-landmarks that occur on most broadleaf taxa. Text labels and barcodes are automatically identified by an archival component detector and are prepared for optical character recognition methods or natural language processing algorithms.
Results
LeafMachine2 can extract trait data from at least 245 angiosperm families and calculate pixel-to-metric conversion factors for 26 commonly used ruler types.
Discussion
LeafMachine2 is a highly efficient tool for generating large quantities of plant trait data, even from occluded or overlapping leaves, field images, and non-archival data sets. Our project, along with similar initiatives, has made significant progress in removing the bottleneck in plant trait data acquisition from herbarium specimens and shifted the focus toward the crucial task of data revision and quality control.
{"title":"From leaves to labels: Building modular machine learning networks for rapid herbarium specimen analysis with LeafMachine2","authors":"William N. Weaver, Stephen A. Smith","doi":"10.1002/aps3.11548","DOIUrl":"10.1002/aps3.11548","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Premise</h3>\u0000 \u0000 <p>Quantitative plant traits play a crucial role in biological research. However, traditional methods for measuring plant morphology are time consuming and have limited scalability. We present LeafMachine2, a suite of modular machine learning and computer vision tools that can automatically extract a base set of leaf traits from digital plant data sets.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Methods</h3>\u0000 \u0000 <p>LeafMachine2 was trained on 494,766 manually prepared annotations from 5648 herbarium images obtained from 288 institutions and representing 2663 species; it employs a set of plant component detection and segmentation algorithms to isolate individual leaves, petioles, fruits, flowers, wood samples, buds, and roots. Our landmarking network automatically identifies and measures nine pseudo-landmarks that occur on most broadleaf taxa. Text labels and barcodes are automatically identified by an archival component detector and are prepared for optical character recognition methods or natural language processing algorithms.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>LeafMachine2 can extract trait data from at least 245 angiosperm families and calculate pixel-to-metric conversion factors for 26 commonly used ruler types.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Discussion</h3>\u0000 \u0000 <p>LeafMachine2 is a highly efficient tool for generating large quantities of plant trait data, even from occluded or overlapping leaves, field images, and non-archival data sets. Our project, along with similar initiatives, has made significant progress in removing the bottleneck in plant trait data acquisition from herbarium specimens and shifted the focus toward the crucial task of data revision and quality control.</p>\u0000 </section>\u0000 </div>","PeriodicalId":8022,"journal":{"name":"Applications in Plant Sciences","volume":"11 5","pages":""},"PeriodicalIF":3.6,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"71432179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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