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bioRxiv2019

Changes in gene expression shift and switch genetic interactions

An important goal in disease genetics and evolutionary biology is to understand how mutations combine to alter phenotypes and fitness. Non-additive interactions between mutations occur extensively and change across conditions, cell types, and species, making genetic prediction a difficult challenge. To understand the reasons for this, we reduced the problem to a minimal system where we combined mutations in a single protein performing a single function (a transcriptional repressor inhibiting a target gene). Even in this minimal system, a change in gene expression altered both the strength and type of genetic interactions. These seemingly complicated changes could, however, be predicted by a mathematical model that propagates the effects of mutations on protein folding to the cellular phenotype. We show that similar changes will be observed for many genes. These results provide fundamental insights into genotype-phenotype maps and illustrate how changes in genetic interactions can be predicted using hierarchical mechanistic models.\n\nOne sentence SummaryDeep mutagenesis of the lambda repressor reveals that changes in gene expression will alter the strength and direction of genetic interactions between mutations in many genes.\n\nHighlightsO_LIDeep mutagenesis of the lambda repressor at two expression levels reveals extensive changes in mutational effects and genetic interactions\nC_LIO_LIGenetic interactions can switch from positive (suppressive) to negative (enhancing) as the expression of a gene changes\nC_LIO_LIA mathematical model that propagates the effects of mutations on protein folding to the cellular phenotype accurately predicts changes in mutational effects and interactions\nC_LIO_LIChanges in expression will alter mutational effects and interactions for many genes\nC_LIO_LIFor some genes, perfect mechanistic models will never be able to predict how mutations of known effect combine without measurements of intermediate phenotypes\nC_LI

genetics↗

bioRxiv2019

REMI-seq: Development of methods and resources for functional genomics in Dictyostelium

Genomes can be sequenced with relative ease, but ascribing gene function remains a major challenge. Genetically tractable model systems are crucial to meet this challenge. One powerful model is the social amoeba Dictyostelium discoideum, a eukaryotic microbe widely used to study diverse questions in cell, developmental and evolutionary biology. However, its utility is hampered by the inefficiency with which sequence, transcriptome or proteome variation can be linked to phenotype. To address this, we have developed methods (REMI-seq) to (1) generate a near genome-wide resource of individual mutants (2) allow large-scale parallel phenotyping. We demonstrate that integrating these resources allows novel regulators of cell migration, phagocytosis and macropinocytosis to be rapidly identified. Therefore, these methods and resources provide a step change for high throughput gene discovery in a key model system, and the study of genes affecting traits associated with higher eukaryotes.

genomics↗

bioRxiv2019

An evaluation of pool-sequencing transcriptome-based exon capture for population genomics of non-model species

AO_SCPLOWBSTRACTC_SCPLOWExon capture coupled to high-throughput sequencing constitutes a cost-effective technical solution for addressing specific questions in evolutionary biology by focusing on expressed regions of the genome preferentially targeted by selection. Transcriptome-based capture, a process that can be used to capture the exons of non-model species, is use in phylogenomics. However, its use in population genomics remains rare due to the high costs of sequencing large numbers of indexed individuals across multiple populations. We evaluated the feasibility of combining transcriptome-based capture and the pooling of tissues from numerous individuals for DNA extraction as a cost-effective, generic and robust approach to estimating the variant allele frequencies of any species at the population level. We designed capture probes for [~]5 Mb of chosen de novo transcripts from the Asian ladybird Harmonia axyridis (5,717 transcripts). We called [~]300,000 bi-allelic SNPs for a pool of 36 non-indexed individuals. Capture efficiency was high, and pool-seq was as effective and accurate as individual-seq for detecting variants and estimating allele frequencies. Finally, we also evaluated an approach for simplifying bioinformatic analyses by mapping genomic reads directly to targeted transcript sequences to obtain coding variants. This approach is effective and does not affect the estimation of SNP allele frequencies, except for a small bias close to some exon ends. We demonstrate that this approach can also be used to predict the intron-exon boundaries of targeted de novo transcripts, making it possible to abolish genotyping biases near exon ends.

genomics↗

bioRxiv2019

Distribution of iridescent colours in hummingbird communities results from the interplay between selection for camouflage and communication

Identification errors between closely related, co-occurring, species may lead to misdirected social interactions such as costly interbreeding or misdirected aggression. This selects for divergence in traits involved in species identification among co-occurring species, resulting from character displacement. On the other hand, predation may select for crypsis, potentially leading co-occurring species that share the same environment and predators to have a similar appearance. However, few studies have explored how these antagonistic processes influence colour at the community level. Here, we assess colour clustering and overdispersion in 189 hummingbird communities, tallying 112 species, across Ecuador and suggest possible evolutionary mechanisms at stake by controlling for species phylogenetic relatedness. In hummingbirds, most colours are iridescent structural colours, defined as colours that change with the illumination or observation angle. Because small variations in the underlying structures can have dramatic effects on the resulting colours and because iridescent structures can produce virtually any hue and brightness, we expect iridescent colours to respond finely to selective pressures. Moreover, we predict that hue angular dependence - a specific aspect of iridescent colours - may be used as an additional channel for species recognition. In our hummingbird assemblages in Ecuador, we find support for colour overdispersion in ventral and facial patches at the community level even after controlling for the phylogeny, especially on iridescence-related traits, suggesting character displacement among co-occurring species. We also find colour clustering at the community level on dorsal patches, suspected to be involved in camouflage, suggesting that the same cryptic colours are selected among co-occurring species. This article has been peer-reviewed and recommended by Peer Community In Evolutionary Biology

ecology↗

bioRxiv2019

Breaking barriers: The effect of protected characteristics and their intersectionality on career transition in academics

Lay summaryIn the past decade the scientific community has been trying to tackle the historical underrepresentation of women in science and the fact that gender can constitute a barrier to career success. However, other characteristics, such as being of an ethnic minority or coming from an under-privileged background, have received less attention. In this study we find that ethnicity and socioeconomic status impact detrimentally on career progression in early career scientists, despite the fact that gender is more likely to be reported as a barrier. Our data suggest we need to widen the discussion regarding diversity and equality in science to incorporate potential barriers to career success in addition to gender.\n\nAbstractThe academic disciplines of Science Technology Engineering and Mathematics (STEM) have long suffered from a lack of diversity. While in recent years there has been some progress in addressing the underrepresentation of women in STEM subjects, other protected characteristics have received less attention. In this study, we survey early career scientists in the fields of ecology, evolutionary biology, behaviour, and related disciplines. We (i) quantitatively examine the effect of protected characteristics and their intersectionality on career transition, and (ii) provide practical suggestions, based on the qualitative responses of those surveyed, for overcoming some of the barriers we identified. We found that socioeconomic background and ethnicity impacted negatively on the quantitative measures of career progression we examined. Respondents that were female, LGBT, and from a lower socioeconomic background were more likely to report having faced a barrier, and the most frequent barrier named was related to gender. Our results suggest that respondents may have felt more confident discussing the experiences they have had related to their gender, potentially because there is now widespread discourse on this subject. However, respondents were less likely to discuss barriers they have faced in relation to ethnicity and socioeconomic status, despite the fact that the data indicates these are more detrimental to career progression. This may reflect the fact that these characteristics have received less attention, and are therefore deemed more sensitive. We hope that this study will stimulate wider discussion, and help to inform strategies to address the underrepresentation of minority groups in STEM subjects.

scientific communication and education↗

bioRxiv2019

Temporal distribution of deleterious variations influences the estimation of FST

Estimating the extent of genetic differentiation between populations is an important measure in population genetics, ecology and evolutionary biology. Fixation index or FST is an important measure, which is routinely used to quantify this. Previous studies have shown that FST estimated for selectively constrained regions was significantly lower than that estimated for neutral regions. By deriving the theoretical relationship between FST at neutral and constrained sites we show that an excess in the fraction of deleterious variations segregating within populations compared to that segregates between populations is the cause for the reduction in FST estimated at constrained sites. Using whole genome data, our results revealed that the magnitude of reduction in FST estimates obtained for selectively constrained regions was much higher for distantly related populations compared to those estimated for closely related pairs. For example, the reduction was 49% for comparison between European-African populations, 31% for European-Asian comparison, 16% for the Northern-Southern European pair and only 4% for the comparison involving two Southern European (Italian and Spanish) populations. Since deleterious variants are purged over time due to purifying selection, their contribution to the among population diversity at constrained sites decreases with the increase in the divergence between populations. However, within population diversity remain the same for all pairs compared above and therefore FST estimated at constrained sites for distantly related populations are much smaller than those estimated for closely related populations. Our results suggest that the level of population divergence should be considered when comparing constrained site FST estimates obtained for different pairs of populations.

genetics↗

bioRxiv2019

An integrative model finds comparable contributions to drug resistance from poor drug adherence and adapting bacteria

Antibiotic resistance is a compound effect of several factors in the infection to healing cycle, from molecular factors such as mutation rate of bacteria to habitual behaviors such as adherence to a prescribed drug. Usually each of these factors is modeled separately from biochemistry, evolutionary biology or population health perspectives. To develop an understanding for the drug resistance at a population level, which is of high global significance, it is important to weigh all these factors in an integrated model. We develop RASAID, a model for resistance considering bacterial adaptation, infection spread, population adherence, immunity, and drug dosage. We apply the model to antibiotic resistance in the spread of resistant strains of Streptococcus Pneumoniae (Sp) in a finite community. We analyze the contributions from several factors to resistance, with a goal towards asking how important is the pursuit of newer drug developments relative to improving the awareness about the good practices in drug usage.

pharmacology and toxicology↗

bioRxiv2019

Loss of critical developmental and human disease-causing genes in 58 mammals

Gene losses provide an insightful route for studying the morphological and physiological adaptations of species, but their discovery is challenging. Existing genome annotation tools and protein databases focus on annotating intact genes and do not attempt to distinguish nonfunctional genes from genes missing annotation due to sequencing and assembly artifacts. Previous attempts to annotate gene losses have required significant manual curation, which hampers their scalability for the ever-increasing deluge of newly sequenced genomes. Using extreme sequence erosion (deletion and non-synonymous substitution) as an unambiguous signature of loss, we developed an automated approach for detecting high-confidence protein-coding gene loss events across a species tree. Our approach relies solely on gene annotation in a single reference genome, raw assemblies for the remaining species to analyze, and the associated phylogenetic tree for all organisms involved. Using the hg38 human assembly as a reference, we discovered over 500 unique human genes affected by such high-confidence erosion events in different clades across 58 mammals. While most of these events likely have benign consequences, we also found dozens of clade-specific gene losses that result in early lethality in outgroup mammals or are associated with severe congenital diseases in humans. Our discoveries yield intriguing potential for translational medical genetics and for evolutionary biology, and our approach is readily applicable to large-scale genome sequencing efforts across the tree of life.

genomics↗

bioRxiv2019

Pollen-feeding Heliconius butterflies host distinctive adult-stage microbiomes

Lepidoptera (butterflies and moths) are diverse and ecologically important, yet we know little about how they interact with microbes as adults. Due to metamorphosis, the form and function of their adult-stage microbiomes might be very different from microbiomes in the larval stage (caterpillars). We studied adult-stage microbiomes of Heliconius and closely related passion-vine butterflies (Heliconiini), which are an important model system in evolutionary biology. To characterize the structure and dynamics of heliconiine microbiomes, we used field collections of wild butterflies, 16S rRNA gene sequencing, quantitative PCR, and shotgun metagenomics. We found that Heliconius harbor simple and abundant bacterial communities that are moderately consistent among conspecific individuals and over time. Heliconiine microbiomes also exhibited a strong signal of host phylogeny, with a major distinction between Heliconius and other butterflies. These patterns were largely driven by differing relative abundances of bacterial phylotypes shared among host species and genera, as opposed to the presence or absence of host-specific phylotypes. We suggest that phylogenetic structure in heliconiine microbiomes arises from conserved host traits that differentially filter microbes from the environment. While the relative importance of different traits remains unclear, our data indicate that pollen-feeding (unique to Heliconius) is not a primary driver. Using shotgun metagenomics, we also discovered trypanosomatids and microsporidia to be prevalent in butterfly guts, raising the possibility of antagonistic interactions between eukaryotic parasites and co-localized gut bacteria. Our discovery of characteristic and phylogenetically structured microbiomes provides a foundation for tests of adult-stage microbiome function, a poorly understood aspect of lepidopteran biology. ImportanceMany insects host microbiomes with important ecological functions. However, the prevalence of this phenomenon is unclear, because in many insect taxa microbiomes have only been studied in part of the life cycle, if at all. A prominent example is the butterflies and moths, in which the composition and functional role of adult-stage microbiomes are largely unknown. We comprehensively characterized microbiomes in adult passion-vine butterflies. Butterfly-associated bacterial communities are generally abundant in guts, consistent within populations, and composed of taxa widely shared among hosts. More closely related butterflies harbor more similar microbiomes, with the most dramatic shift in microbiome composition occurring in tandem with a suite of ecological and life history traits unique to the genus Heliconius. Butterflies are also frequently infected with previously undescribed eukaryotic parasites, which may interact with bacteria in important ways. These findings advance our understanding of butterfly biology and of insect-microbe interactions generally.

ecology↗

bioRxiv2019

Longest protein, longest transcript or most expression, for accurate gene reconstruction of transcriptomes?

Methods of transcript assembly and reduction filters are compared for recovery of reference gene sets of human, pig and plant, including longest coding sequence with EvidentialGene, longest transcript with CD-HIT, and most RNA-seq with TransRate. EvidentialGene methods are the most accurate in recovering reference genes, and maintain accuracy for alternate transcripts and paralogs. In comparison, filtering large over-assemblies by longest RNA measures, and most RNA-seq expression measures, discards a large portion of accurate models, especially alternates and paralogs. Accuracy of protein calculations is compared, with errors found in popular methods, as is accuracy of transcript assemblers. Gene reconstruction accuracy depends upon the underlying measurements, where protein criteria, including homology among species, have the strength of evolutionary biology that other criteria lack. EvidentialGene provides a gene reconstruction algorithm that is consistent with genome biology.

bioinformatics↗

bioRxiv2019

Multiple evidences suggest sox2 as the main driver of a young and complex sex determining ZW/ZZ system in turbot (Scophthalmus maximus)

A major challenge in evolutionary biology is to find an explanation for the variation in sex-determining (SD) systems across taxa and to understand the mechanisms driving sex chromosome differentiation. We studied the turbot, holding a ZW/ZZ SD system and no sex chromosome heteromorphism, by combining classical genetics and genomics approaches to disentangle the genetic architecture of this trait. RAD-Seq was used to genotype 18,214 SNPs on 1,135 fish from 36 families and a genome wide association study (GWAS) identified a [~] 6 Mb region on LG5 associated with sex (P < 0.05). The most significant associated markers were located close to sox2, dnajc19 and fxr1 genes. A segregation analysis enabled narrowing down the associated region and evidenced recombination suppression in a region overlapping the candidate genes. A Nanopore/Illumina assembly of the SD region using ZZ and WW individuals identified a single SNP fully associated with Z and W chromosomes. RNA-seq from 5-90 day-old fish detected the expression along the gonad differentiation period of a short non-coding splicing variant (ncRNA) included in a vertebrate-conserved long non-coding RNA overlapping sox2. qPCR showed that sox2 was the only differentially expressed gene between males and females at 50-55 days post fertilization, just prior the beginning of gonad differentiation. More refined information on the involvement of secondary genetic and environmental factors and their interactions on SD was gathered after the analysis of a broad sample of families. Our results confirm the complex nature of SD in turbot and support sox2 as its main driver.

genomics↗

bioRxiv2019

Versatile simulations of admixture and accurate local ancestry inference with mixnmatch and ancestryinfer

It is now clear that hybridization between species is much more common than previously recognized. As a result, we now know that the genomes of many modern species, including our own, are a patchwork of regions derived from past hybridization events. Increasingly researchers are interested in disentangling which regions of the genome originated from each parental species using local ancestry inference methods. Due to the diverse effects of admixture, this interest is shared across disparate fields, from human genetics to research in ecology and evolutionary biology. However, local ancestry inference methods are sensitive to a range of biological and technical parameters which can impact accuracy. Here we present paired simulation and ancestry inference pipelines, mixnmatch and ancestryinfer, to help researchers plan and execute local ancestry inference studies. mixnmatch can simulate arbitrarily complex demographic histories in the parental and hybrid populations, selection on hybrids, and technical variables such as coverage and contamination. ancestryinfer takes as input sequencing reads from simulated or real individuals, and implements an efficient local ancestry inference pipeline. We perform a series of simulations with mixnmatch to pinpoint factors that influence accuracy in local ancestry inference and highlight useful features of the two pipelines. Together, mixnmatch and ancestryinfer are powerful tools for predicting the performance of local ancestry inference methods on real data.

genomics↗

bioRxiv2019

Deep learning-based methods for individual recognition in small birds

O_LIIndividual identification is a crucial step to answer many questions in evolutionary biology and is mostly performed by marking animals with tags. Such methods are well established but often make data collection and analyses time consuming and consequently are not suited for collecting very large datasets. C_LIO_LIRecent technological and analytical advances, such as deep learning, can help overcome these limitations by automatizing data collection and analysis. Currently one of the bottlenecks preventing the application of deep learning for individual identification is the need of hundreds to thousands of labelled pictures required for training convolutional neural networks (CNNs). C_LIO_LIHere, we describe procedures that improve data collection and allow individual identification in captive and wild birds and we apply it to three small bird species, the sociable weaver Philetairus socius, the great tit Parus major and the zebra finch Taeniopygia guttata. C_LIO_LIFirst, we present an automated method that allows the collection of large samples of individually labelled images. Second, we describe how to train a CNN to identify individuals. Third, we illustrate the general applicability of CNN for individual identification in animal studies by showing that the trained CNN can predict the identity of birds from images collected in contexts that differ from the ones originally used to train the CNNs. Fourth, we present a potential solution to solve the issues of new incoming individuals. C_LIO_LIOverall our work demonstrates the feasibility of applying state-of-the-art deep learning tools for individual identification of birds, both in the lab and in the wild. These techniques are made possible by our approaches that allow efficient collection of training data. The ability to conduct individual identification of birds without requiring external markers that can be visually identified by human observers represents a major advance over current methods. C_LI

ecology↗

bioRxiv2025

The Goldilocks effect drives plant diversification on middle-aged Hawaiian islands

Islands are natural laboratories for studying dispersal, speciation, and extinction, yet the historical dynamics of many insular radiations remain poorly understood because of the difficulty aligning the tempo and mode of diversification with paleogeography during phylogenetic inference. We introduce a phylogenetic modeling framework, named TimeFIG, that combines data about species ranges and genetic variation with paleogeographic information to simultaneously infer divergence times, ancestral ranges, and historical diversification rates, without relying on fossils to time-calibrate the phylogeny. Applying TimeFIG to the spectacular radiation of Hawaiian Kadua (Rubiaceae) points to colonization of either modern Kaua'i or ancient now-eroded islands, with island isolation as the strongest correlate of dispersal, and with a tendency for net diversification to be highest on "middle-aged" islands. Modeling diversification within an explicit spatiotemporal context, while accounting for historical uncertainty regarding the timing and placement of phylogenetic and biogeographic events, enables the rigorous testing of foundational hypotheses in island biology and evolutionary theory for clades beyond Kadua.

evolutionary biology↗

bioRxiv2025

Orangutan: an R package for analyzing and visualizing phenotypic data in the context of ecology and systematics

AimPhenotypic characters have long been central to species diagnosis and delimitation and remain indispensable even in the age of genomics. However, phenotypic datasets are often complex-- spanning dozens of traits of varying types and units, with correlated variables and unbalanced sampling--posing challenges for robust, reproducible analysis. Existing software solutions are fragmented, usually requiring labor-intensive workflows across multiple tools and manual steps, which undermines reproducibility and hinders comparisons across studies. To address these methodological and practical challenges, I introduce Orangutan, an R package designed to provide a flexible, easy-to-implement framework for comparing groups using mensural and meristic data. InnovationOrangutan provides a flexible and efficient framework for analyzing mensural and meristic data, supporting a full suite of statistical and visualization tools optimized for species delimitation and population comparisons. The package streamlines the identification of diagnostic, non-overlapping traits between species, while enabling rigorous assessment of both individual and multivariate trait differences. Core features include optional allometric correction to remove size effects, automated selection of appropriate univariate tests with post hoc comparisons, and integrated multivariate analyses. All outputs, including summary statistics and annotated publication-ready figures, are generated with minimal coding, ensuring accessibility and standardization. Main ConclusionsEmpirical validation with real-world datasets--including animal and plant species-- demonstrates that Orangutan robustly identifies diagnostic traits, reveals both subtle and clear group differences, and achieves high classification accuracy with phenotypic data alone. By automating and unifying key analytical steps, Orangutan promotes reproducibility, transparency, and efficiency in phenotypic research. This package empowers researchers in taxonomy, ecology, and evolutionary biology to adopt quantitative best practices for species delimitation, facilitating comparative studies and advancing methodological standards in morphological data analysis. Orangutan is freely available with comprehensive documentation to support widespread adoption.

ecology↗

bioRxiv2026

The MexMAGIC population reveals the genetic architecture of clinal trait variation in Mexican native maize

Defining the genetic basis of local adaptation is fundamental to evolutionary biology and crop improvement. Theory predicts that when selective pressures track differences in the environment, a cline will be established. Such clines might be exploited to uncover adaptive variation by association of alleles with environmental stressors. However, monotonic phenotypic change over a cline is not necessarily mirrored by adaptive genetic variants. Furthermore, population structure can complicate the interpretation of genotype-environment association. To test the assumptions of genotype-environment association in a crop species, we developed a multi-parent advanced generation inter-cross (MAGIC) population using eight Mexican native maize varieties sourced from distinct agroecological zones. We mapped two clinal traits (tassel branching and flowering time) differing in genetic architecture. Variation in tassel branch number was dominated by a single QTL with allele effects that aligned well with a negative elevational cline. In contrast, we mapped 11 flowering time QTL with allele effects that were not consistently correlated with any one source environmental factor and distinct loci donated by highland and lowland early maturing varieties. Our observations support the theoretical result that genotype-environment association will be strongest under simple genetic architecture, although identification of adaptive alleles may still be confounded by population structure. Plain Language: Nine thousand years of careful selection and cultivation by indigenous farmers has generated a rich diversity of native Mexican maize (corn) varieties, grown from sea level to high mountains, and from jungle to semidesert. By crossing native varieties adapted to different locations, we can uncover important genetic variants conferring tolerance to environmental stressors.

genetics↗

bioRxiv2026

Genomic insights into rapid diversification and adaptive introgression in the earthworm Amynthas aspergillum

How species diversify in highly fragmented landscapes while maintaining genetic connectivity remains a central question in evolutionary biology. The megascolecid earthworm Amynthas aspergillum exemplifies this paradox, showing deeply divergent mitochondrial lineages despite extensive nuclear gene flow across southern China. We conducted whole-genome resequencing across its core distribution in the Guangxi karst region to elucidate the population structure and processes underlying this cytonuclear discordance. Genome-wide analyses identified three genetically distinct groups shaped by fine-scale karst isolation, alongside pervasive historical and contemporary introgression. Demographic modeling revealed rapid diversification during the Late Pleistocene ([~]0.14LJMa) with pronounced fluctuations in effective population size. Although isolation increased inbreeding and mutational load in some lineages, introgression persisted even among deeply divergent mitochondrial clades. Notably, several introgressed regions showed strong signatures of positive selection, including genes involved in mitochondrial function and metabolism.Together, these results demonstrate that gene flow can simultaneously mitigate the genomic costs of isolation and promote functional innovation via adaptive introgression, providing a genomic framework for diversification with gene flow in subterranean invertebrates inhabiting fragmented karst landscapes.

genomics↗

bioRxiv2026

Structural basis of the lobster carapace blue colour mediated by an HPR protein

The chemical basis underlying the striking blue hue of live H. americanus, known as American lobster, are studied in evolutionary biology and in polyene physical chemistry. Carapace colouration is generated by the antioxidant astaxanthin bound within the carotenoprotein crustacyanin complexes. Here, we present the ex vivo structure of the most abundant -crustacyanin and {beta}-crustacyanin forms, determined respectively by cryo-electron microscopy and X-ray crystallography to a resolution of 2.75 [A]. Our structural analysis reveals -crustacyanin as an elongated arrangement of {beta}-crustacyanin heterodimers tethered by an heptatricopeptide repeat (HPR) protein. In vitro complex formation between the {beta}-crustacyanin unit with a synthetic heptatricopeptide reproduces the observed blue colour of -crustacyanin, identifying the HPR protein, in concert with crustacyanins, as contributor in tuning carapace colour. Overall, these results explain how nature adjusts the colour across the entire visible spectrum by exploiting the bathochromic shift of astaxanthin from its unbound red form ({lambda}max = 472 nm) firstly to the {beta}-crustacyanin violet bound form ({lambda}max = 591 nm), and then to the -crustacyanin bound blue form ({lambda}max = 631 nm).

biochemistry↗